Home/Federal/Federal Register/2022-07906

Proposed Rule2022-07906

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 2023; Request for Information on Revising the Requirements for Long-Term Care Facilities To Establish Mandatory Minimum Staffing Levels

Primary source

Metadata and text below are from the Federal Register, a public-domain U.S. government work. Always verify the official published version before relying on it for any legal matter.

Published

April 15, 2022

Issuing agencies

Health and Human Services DepartmentCenters for Medicare & Medicaid Services

Abstract

This proposed rule would update: Payment rates; forecast error adjustment; diagnosis code mappings; the Patient Driven Payment Model (PDPM) parity adjustment, the SNF Quality Reporting Program (QRP), SNF Value-Based Purchasing (VBP) Program. It also proposes to establish a permanent cap policy. This proposed rule also includes a request for information related to long-term care (LTC) facilities. CMS requests comments on these proposals as well as on related subjects and announces the application of a risk adjustment for the SNF Readmission Measure for COVID-19 beginning in FY 2023.

Full Text

<html>
<head>
<title>Federal Register, Volume 87 Issue 73 (Friday, April 15, 2022)</title>
</head>
<body><pre>
[Federal Register Volume 87, Number 73 (Friday, April 15, 2022)]
[Proposed Rules]
[Pages 22720-22809]
From the Federal Register Online via the Government Publishing Office [<a href="http://www.gpo.gov">www.gpo.gov</a>]
[FR Doc No: 2022-07906]

[[Page 22719]]

Vol. 87

Friday,

No. 73

April 15, 2022

Part III

Department of Health and Human Services

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

Centers for Medicare & Medicaid Services

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

42 CFR Part 413

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
2023; Request for Information on Revising the Requirements for Long-
Term Care Facilities To Establish Mandatory Minimum Staffing Levels;
Proposed Rule

Federal Register / Vol. 87 , No. 73 / Friday, April 15, 2022 /
Proposed Rules

[[Page 22720]]

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

DEPARTMENT OF HEALTH AND HUMAN SERVICES

Centers for Medicare & Medicaid Services

42 CFR Part 413

[CMS-1765-P]
RIN 0938-AU76

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 2023; Request for Information on Revising the Requirements for
Long-Term Care Facilities To Establish Mandatory Minimum Staffing
Levels

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

ACTION: Proposed rule; request for comments.

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

SUMMARY: This proposed rule would update: Payment rates; forecast error
adjustment; diagnosis code mappings; the Patient Driven Payment Model
(PDPM) parity adjustment, the SNF Quality Reporting Program (QRP), SNF
Value-Based Purchasing (VBP) Program. It also proposes to establish a
permanent cap policy. This proposed rule also includes a request for
information related to long-term care (LTC) facilities. CMS requests
comments on these proposals as well as on related subjects and
announces the application of a risk adjustment for the SNF Readmission
Measure for COVID-19 beginning in FY 2023.

DATES: To be assured consideration, comments must be received at one of
the addresses provided below, by June 10, 2022.

ADDRESSES: In commenting, please refer to file code CMS-1765-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 <a href="https://www.regulations.gov">https://www.regulations.gov</a>. 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-1765-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-1765-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: <a href="/cdn-cgi/l/email-protection#7f2f3b2f323f1c120c5117170c51181009">[email&#160;protected]</a> 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.

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: <a href="https://www.regulations.gov">https://www.regulations.gov</a>. Follow the search instructions on that website to
view public comments. CMS will not post on <a href="http://Regulations.gov">Regulations.gov</a> 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 <a href="https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/SNFPPS/WageIndex.html">https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/SNFPPS/WageIndex.html</a>.
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 2023 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. Proposed Permanent Cap on Wage Index Decreases
B. Technical Updates to PDPM ICD-10 Mappings
C. Recalibrating the PDPM Parity Adjustment
D. Request for Information: Infection Isolation
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 Beginning With the FY 2025
SNF QRP
D. SNF QRP Quality Measures Under Consideration for Future
Years: Request for Information (RFI)
E. Overarching Principles for Measuring Equity and Healthcare
Quality Disparities Across CMS Quality Programs--Request for
Information (RFI)
F. Inclusion of the CoreQ: Short Stay Discharge Measure in a
Future SNF QRP Program Year--Request for Information (RFI)
G. Form, Manner, and Timing of Data Submission Under the SNF QRP
H. 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. Performance Standards
E. SNF VBP Performance Scoring
F. Proposal To Adopt a Validation Process for the SNF VBP
Program Beginning With the FY 2023 Program Year
G. Proposed SNF Value-Based Incentive Payments for FY 2023

[[Page 22721]]

H. Public Reporting on the Provider Data Catalog Website
I. Requests for Comment on Additional SNF VBP Program Measure
Considerations for Future Years
VIII. Request for Information: Revising the Requirements for Long-
Term Care (LTC) Facilities To Establish Mandatory Minimum Staffing
Levels
IX. Collection of Information Requirements
X. Response to Comments
XI. Economic Analyses
A. Regulatory Impact Analysis
B. Regulatory Flexibility Act Analysis
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) 2023, 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 proposes requirements for the Skilled
Nursing Facility Quality Reporting Program (SNF QRP) and the Skilled
Nursing Facility Value-Based Purchasing Program (SNF VBP), including
proposals to adopt new quality measures for the SNF VBP Program. The
SNF QRP includes proposals to adopt one new measure to promote patient
safety, begin collection of information which is expected to improve
quality of care for all SNF patients, and revise associated regulation
text. The proposal also seeks comment on several subjects related to
the SNF QRP including principles for measuring healthcare quality
disparities and developing measures of healthcare equity in the SNF
QRP. This proposed rule also seeks comment on numerous issues related
to the SNF VBP Program, including additional measures on staffing
turnover and COVID-19 vaccination for healthcare personnel, the
Program's exchange function, validation, and the SNF VBP Program's
approach to health equity. This proposed rule also includes a request
for information on revising the requirements for long-term care (LTC)
facilities to establish mandatory minimum staffing levels.

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 2022 (86
FR 42424, August 4, 2021). In addition, the proposed rule includes a
proposed forecast error adjustment for FY 2023, proposes updates to the
diagnosis code mappings used under the Patient Driven Payment Model
(PDPM), and includes a proposed recalibration of the PDPM parity
adjustment. Additionally, this proposed rule solicits comments on
criteria related to patient isolation for active infection in a SNF.
This proposed rule also proposes to establish a permanent cap policy to
smooth the impact of year-to-year changes in SNF payments related to
changes in the SNF wage index.
This proposed rule proposes requirements for the SNF QRP, including
the adoption of one new measure beginning with the FY 2025 SNF QRP: The
Influenza Vaccination Coverage among Healthcare Personnel (HCP) (NQF
#0431) measure. We are also proposing to revise the compliance date for
the Transfer of Health Information measures and certain standardized
patient assessment data elements. In addition, we are proposing to
revise regulation text that pertains to data submission requirements
for the SNF QRP. Finally, we are seeking comment on three subjects:
Future measure concepts for the SNF QRP, overarching principles for
measuring equity and healthcare disparities across CMS programs,
including the SNF QRP, and the inclusion of the CoreQ: Short Stay
Discharge Measure in the SNF QRP.
Additionally, we are proposing several updates for the SNF VBP
Program, including a policy to suppress the Skilled Nursing Facility
30-Day All-Cause Readmission Measure (SNFRM) for the FY 2023 SNF VBP
Program Year for scoring and payment adjustment purposes. We are also
proposing to add two new measures to the SNF VBP Program beginning with
the FY 2026 SNF VBP program year and one new measure beginning with the
FY 2027 program year. We are also proposing several updates to the
scoring methodology beginning with the FY 2026 program year and
requesting public comments on several other measures we are considering
for future rulemaking including a measure of staff turnover, whether we
should update the exchange function, issues related to validation of
SNF VBP data, and issues related to health equity. We are also
proposing to revise our regulation text in accordance with our
proposals.

C. Summary of Cost and Benefits
[GRAPHIC] [TIFF OMITTED] TP15AP22.008

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

[[Page 22722]]

Information Technology (ONC) participate in the Post-Acute Care
Interoperability Workgroup (PACIO) to facilitate collaboration with
industry stakeholders to develop Health Level Seven
International[supreg] (HL7) Fast Healthcare Interoperability
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.
---------------------------------------------------------------------------

\1\ HL7 FHIR Release 4. Available at <a href="https://www.hl7.org/fhir/">https://www.hl7.org/fhir/</a>.
\2\ HL7 FHIR. PACIO Functional Status Implementation Guide.
Available at <a href="https://paciowg.github.io/functional-status-ig/">https://paciowg.github.io/functional-status-ig/</a>.
\3\ PACIO Project. Available at <a href="http://pacioproject.org/about/">http://pacioproject.org/about/</a>.
---------------------------------------------------------------------------

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 2022 ISA is available at <a href="https://www.healthit.gov/isa/sites/isa/files/inline-files/2022-ISA-Reference-Edition.pdf">https://www.healthit.gov/isa/sites/isa/files/inline-files/2022-ISA-Reference-Edition.pdf</a>.
---------------------------------------------------------------------------

\4\ Centers for Medicare & Medicaid Services. Newsroom. Fact
sheet: CMS Data Element Library Fact Sheet. June 21, 2018. Available
at <a href="https://www.cms.gov/newsroom/fact-sheets/cms-data-element-library-fact-sheet">https://www.cms.gov/newsroom/fact-sheets/cms-data-element-library-fact-sheet</a>.
---------------------------------------------------------------------------

The 21st Century Cures Act (Cures Act) (Pub. L. 114-255, enacted
December 13, 2016) required HHS and ONC to take steps to promote
adoption and use of electronic health record (EHR) technology.\5\
Specifically, section 4003(b) of the Cures Act required ONC to take
steps to advance interoperability through the development of a Trusted
Exchange Framework and Common Agreement aimed at establishing a
universal floor of interoperability across the country. On January 18,
2022, ONC announced a significant milestone by releasing the Trusted
Exchange Framework \6\ and Common Agreement Version 1.\7\ The Trusted
Exchange 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
Trusted Exchange Framework and the Common Agreement follows a network-
of-networks structure, which allows for connections at different levels
and is inclusive of many different types of entities at those different
levels, such as health information networks, healthcare practices,
hospitals, public health agencies, and Individual Access Services (IAS)
Providers.\8\ For more information, we refer readers to <a href="https://www.healthit.gov/topic/interoperability/trusted-exchange-framework-and-common-agreement">https://www.healthit.gov/topic/interoperability/trusted-exchange-framework-and-common-agreement</a>.
---------------------------------------------------------------------------

\5\ Sections 4001 through 4008 of Public Law 114-255. Available
at <a href="https://www.govinfo.gov/content/pkg/PLAW-114publ255/html/PLAW-114publ255.htm">https://www.govinfo.gov/content/pkg/PLAW-114publ255/html/PLAW-114publ255.htm</a>.
\6\ The Trusted Exchange Framework (TEF): Principles for Trusted
Exchange (Jan. 2022). Available at <a href="https://www.healthit.gov/sites/default/files/page/2022-01/Trusted_Exchange_Framework_0122.pdf">https://www.healthit.gov/sites/default/files/page/2022-01/Trusted_Exchange_Framework_0122.pdf</a>.
\7\ Common Agreement for Nationwide Health Information
Interoperability Version 1 (Jan. 2022). Available at <a href="https://www.healthit.gov/sites/default/files/page/2022-01/Common_Agreement_for_Nationwide_Health_Information_Interoperability_Version_1.pdf">https://www.healthit.gov/sites/default/files/page/2022-01/Common_Agreement_for_Nationwide_Health_Information_Interoperability_Version_1.pdf</a>.
\8\ The Common Agreement defines Individual Access Services
(IAS) as ``with respect to the Exchange Purposes definition, the
services provided utilizing the Connectivity Services, to the extent
consistent with Applicable Law, to an Individual with whom the QHIN,
Participant, or Subparticipant has a Direct Relationship to satisfy
that Individual's ability to access, inspect, or obtain a copy of
that Individual's Required Information that is then maintained by or
for any QHIN, Participant, or Subparticipant.'' The Common Agreement
defines ``IAS Provider'' as: ``Each QHIN, Participant, and
Subparticipant that offers Individual Access Services.'' See Common
Agreement for Nationwide Health Information Interoperability Version
1, at 7 (Jan. 2022), <a href="https://www.healthit.gov/sites/default/files/page/2022-01/Common_Agreement_for_Nationwide_Health_Information_Interoperability_Version_1.pdf">https://www.healthit.gov/sites/default/files/page/2022-01/Common_Agreement_for_Nationwide_Health_Information_Interoperability_Version_1.pdf</a>.
---------------------------------------------------------------------------

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 <a href="https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/SNFPPS/Downloads/Legislative_History_2018-10-01.pdf">https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/SNFPPS/Downloads/Legislative_History_2018-10-01.pdf</a>.
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 IMPACT Act 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)
updated section 1888(h) of the Act, authorizing the Secretary to apply
up to nine additional measures to the VBP program for SNFs.

[[Page 22723]]

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
2022 (86 FR 42424, August 4, 2021).
Section 1888(e)(4)(H) of the Act specifies that we provide for
publication annually in the Federal Register the following:
<bullet> The unadjusted Federal per diem rates to be applied to
days of covered SNF services furnished during the upcoming FY.
<bullet> The case-mix classification system to be applied for these
services during the upcoming FY.
<bullet> The factors to be applied in making the area wage
adjustment for these services.
Along with other revisions discussed later in this preamble, this
proposed rule provides the required annual updates to the per diem
payment rates for SNFs for FY 2023.

III. Proposed SNF PPS Rate Setting Methodology and FY 2023 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 index, 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 Index
Section 1888(e)(5)(A) of the Act requires us to establish a SNF
market basket index 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 index 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 market basket index, 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 market basket index,
which included updating the base year from 2014 to 2018.
The SNF market basket index is used to compute the market basket
percentage change 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 update is adjusted by a forecast error
correction, 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. of this proposed rule.
For this proposed rule, we propose a FY 2023 SNF market basket
percentage of 2.8 percent based on IHS Global Inc.'s (IGI's) fourth
quarter 2021 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 2023 SNF market basket percentage
change, labor-related share relative importance, forecast error
adjustment, or productivity adjustment in the SNF PPS final rule.
In section III.B.5. of this proposed rule, we discuss the 2 percent
reduction applied to the market basket update for those SNFs that fail
to submit measures data as required by section 1888(e)(6)(A) of the
Act.
2. Use of the SNF Market Basket Percentage
Section 1888(e)(5)(B) of the Act defines the SNF market basket
percentage as the percentage change in the SNF market basket index from
the midpoint of the previous FY to the midpoint of the current FY. For
the Federal rates set forth in this proposed rule, we use the
percentage change in the SNF market basket index to compute the update
factor for FY 2023. This factor is based on the FY 2023 percentage
increase in the 2018-based SNF market basket index reflecting routine,
ancillary, and capital-related expenses. As stated previously, in this
proposed rule, the SNF market basket percentage update is estimated to
be 2.8 percent for FY 2023 based on IGI's fourth quarter 2021 forecast.
3. Forecast Error Adjustment
As discussed in the June 10, 2003 supplemental proposed rule (68 FR
34768) and finalized in the August 4, 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

[[Page 22724]]

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 2021 (the most recently available FY for which there is
final data), the forecasted or estimated increase in the SNF market
basket index was 2.2 percent, and the actual increase for FY 2021 is
3.7 percent, resulting in the actual increase being 1.5 percentage
point higher than the estimated increase. Accordingly, as the
difference between the estimated and actual amount of change in the
market basket index exceeds the 0.5 percentage point threshold, under
the policy previously described (comparing the forecasted and actual
increase in the market basket), the FY 2023 market basket percentage
change of 2.8 percent, would be adjusted upward to account for the
forecast error correction of 1.5 percentage point, resulting in a SNF
market basket percentage change of 3.9 percent after reducing the
market basket update by the productivity adjustment of 0.4 percentage
point, discussed later in this section of the preamble.
Table 2 shows the forecasted and actual market basket increases for
FY 2021.
[GRAPHIC] [TIFF OMITTED] TP15AP22.009

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 in 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 multifactor productivity (MFP) with total factor
productivity (TFP). BLS noted that this is a change in terminology only
and will not affect the data or methodology. As a result of the BLS
name change, the productivity measure referenced in section
1886(b)(3)(B)(xi)(II) of the Act is now published by BLS as private
nonfarm business total factor productivity. However, as mentioned
above, the data and methods are unchanged. We refer readers to the BLS
website at <a href="http://www.bls.gov">www.bls.gov</a> for the BLS historical published TFP data.
A complete description of the TFP projection methodology is
available on our website at <a href="https://www.cms.gov/Research-Statistics-Data-and-Systems/Statistics-Trends-and-Reports/MedicareProgramRatesStats/MarketBasketResearch">https://www.cms.gov/Research-Statistics-Data-and-Systems/Statistics-Trends-and-Reports/MedicareProgramRatesStats/MarketBasketResearch</a>. In addition, in the FY
2022 SNF final rule (86 FR 42429) we noted that, effective with FY 2022
and forward, we are changing the name of this adjustment to refer to it
as the ``productivity adjustment,'' rather than the ``MFP adjustment.''
a. Incorporating the Productivity Adjustment Into the Market Basket
Update
Per section 1888(e)(5)(A) of the Act, the Secretary shall establish
a SNF market basket index 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 2023 SNF PPS proposed rule,
the current proposed productivity adjustment (the 10-year moving
average of TFP for the period ending September 30, 2023) is projected
to be 0.4 percentage point.
Consistent with section 1888(e)(5)(B)(i) of the Act and Sec.
413.337(d)(2), as discussed previously in this section of the preamble,
the market basket percentage for FY 2023 for the SNF PPS is based on
IGI's fourth quarter 2021 forecast of the SNF market basket percentage,
which is estimated to be 2.8 percent. This market basket percentage is
then increased by 1.5 percentage point, due to application of the
forecast error adjustment discussed earlier in this section of the
preamble. Finally, as discussed earlier in this section of the
preamble, we are applying a 0.4 percentage point productivity
adjustment to the FY 2023 SNF market basket percentage. The resulting

[[Page 22725]]

productivity-adjusted FY 2023 SNF market basket update is, therefore,
equal to 3.9 percent, or 2.8 percent plus 1.5 percentage point to
account for forecast error and less 0.4 percentage point to account for
the productivity adjustment.
5. Market Basket Update Factor for FY 2023
Sections 1888(e)(4)(E)(ii)(IV) and (e)(5)(i) of the Act require
that the update factor used to establish the FY 2023 unadjusted Federal
rates be at a level equal to the market basket index percentage change.
Accordingly, we determined the total growth from the average market
basket level for the period of October 1, 2021 through September 30,
2022 to the average market basket level for the period of October 1,
2022 through September 30, 2023. This process yields a percentage
change in the 2018-based SNF market basket of 2.8 percent.
As further explained in section III.B.3. of this proposed rule, as
applicable, we adjust the market basket percentage change by the
forecast error 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 change in the market basket
exceeds a 0.5 percentage point threshold in absolute terms. Since the
actual FY 2021 SNF market basket percentage change exceeded the
forecasted FY 2021 SNF market basket percentage change (FY 2021 is the
most recently available FY for which there is historical data) by more
than the 0.5 percentage point threshold, we propose to adjust the FY
2023 market basket percentage change upward by the forecast error
correction. Applying the 1.5 percentage point forecast error correction
results in an adjusted FY 2023 SNF market basket percentage change of
4.3 percent (2.8 percent market basket update plus 1.5 percentage point
forecast error adjustment).
Section 1888(e)(5)(B)(ii) of the Act requires us to reduce the
market basket percentage change by the productivity adjustment (10-year
moving average of changes in TFP for the period ending September 30,
2023) which is estimated to be 0.4 percentage point, as described in
section III.B.4. of this proposed rule. Thus, we apply a net SNF market
basket update factor of 3.9 percent in our determination of the FY 2022
SNF PPS unadjusted Federal per diem rates, which reflects a market
basket increase factor of 2.8 percent, plus the 1.5 percentage point
forecast error correction and less the 0.4 percentage point
productivity adjustment.
We note that if more recent data become available (for example, a
more recent estimate of the SNF market basket and/or productivity
adjustment), we would use such data, if appropriate, to determine the
FY 2023 SNF market basket percentage change, labor-related share
relative importance, forecast error adjustment, or productivity
adjustment in the FY 2023 SNF PPS final 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
1 percent market basket increase for FY 2018). 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
index 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.
6. Unadjusted Federal Per Diem Rates for FY 2023
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 proposed to use the SNF
market basket, adjusted as described previously, to adjust each per
diem component of the Federal rates forward to reflect the change in
the average prices for FY 2023 from the average prices for FY 2022. We
propose to further adjust the rates by a wage index budget neutrality
factor, described later in this section. 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 <a href="https://www.whitehouse.gov/wp-content/uploads/2018/09/Bulletin-18-04.pdf">https://www.whitehouse.gov/wp-content/uploads/2018/09/Bulletin-18-04.pdf</a>) 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
2023, prior to adjustment for case-mix.
[GRAPHIC] [TIFF OMITTED] TP15AP22.010

[[Page 22726]]

[GRAPHIC] [TIFF OMITTED] TP15AP22.011

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 <a href="https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/NursingHomeQualityInits/MDS30RAIManual.html">https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/NursingHomeQualityInits/MDS30RAIManual.html</a>.
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 2023 payment rates set forth in this
proposed rule reflect the use of the PDPM case-mix classification
system from October 1, 2022, through September 30, 2023. The case-mix
adjusted PDPM payment rates for FY 2023 are listed separately for urban
and rural SNFs, in Tables 5 and 6 with corresponding case-mix values.
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 <a href="https://www.whitehouse.gov/wp-content/uploads/2018/09/Bulletin-18-04.pdf">https://www.whitehouse.gov/wp-content/uploads/2018/09/Bulletin-18-04.pdf</a>) to identify a facility's urban or rural status
effective beginning with FY 2021.
As we noted in the FY 2022 SNF PPS final rule (86 FR 42434), we
continue to monitor the impact of PDPM implementation on patient
outcomes and program outlays. Because of this analysis, in section V.C.
of this

[[Page 22727]]

proposed rule, we propose to recalibrate the PDPM parity adjustment
discussed in the FY 2020 SNF PPS final rule (84 FR 38734). Following
the methodology of this proposed change, Tables 5 and 6 incorporate the
proposed recalibration of the PDPM parity adjustment.
BILLING CODE 4120-01-P
[GRAPHIC] [TIFF OMITTED] TP15AP22.012

[[Page 22728]]

[GRAPHIC] [TIFF OMITTED] TP15AP22.013

BILLING CODE 4120-01-C

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 2023, 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 2023, the updated wage data are for hospital cost reporting
periods beginning on or after October 1, 2018 and before October 1,
2019 (FY 2019 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) authorized us to establish a geographic
reclassification procedure that is 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. However, 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. In addition, 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. Therefore,
as discussed above in this section, in the absence of a SNF-specific
wage index, we believe the use of the pre-reclassified and pre-floor
hospital wage data (without the occupational mix adjustment) continue
to be an appropriate and reasonable proxy for the SNF PPS.

[[Page 22729]]

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 proposed to continue using the average wage
index from all contiguous Core-Based Statistical Areas (CBSAs) as a
reasonable proxy. For FY 2023, there are no rural geographic areas that
do not have hospitals, and thus, this methodology will not be applied.
For rural Puerto Rico, we proposed not to apply this methodology due to
the distinct economic circumstances that exist there (for example, due
to the close proximity to one another 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 proposed that we would use the
average wage indexes of all of the urban areas within the State to
serve as a reasonable proxy for the wage index of that urban CBSA. For
FY 2023, the only urban area without wage index data available is CBSA
25980, Hinesville-Fort Stewart, GA.
The wage index applicable to FY 2023 is set forth in Tables A and B
available on the CMS website at <a href="https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/SNFPPS/WageIndex.html">https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/SNFPPS/WageIndex.html</a>.
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 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 <a href="https://www.whitehouse.gov/wp-content/uploads/2018/09/Bulletin-18-04.pdf">https://www.whitehouse.gov/wp-content/uploads/2018/09/Bulletin-18-04.pdf</a>) 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. For FY 2023 and subsequent years, we are
proposing 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, which is further discussed in
section V.A. of this proposed 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. We note that on March 6, 2020, OMB issued Bulletin No. 20-
01, which provided updates to and superseded OMB Bulletin No. 18-04
that was issued on September 14, 2018. The attachments to OMB Bulletin
No. 20-01 provided detailed information on the updates (available on
the web at <a href="https://www.whitehouse.gov/wp-content/uploads/2020/03/Bulletin-20-01.pdf">https://www.whitehouse.gov/wp-content/uploads/2020/03/Bulletin-20-01.pdf</a>). In the FY 2021 SNF PPS final rule (85 FR 47611),
we stated that we intended to propose any updates from OMB Bulletin No.
20-01 in the FY 2022 SNF PPS proposed rule. After reviewing OMB
Bulletin No. 20-01, we have determined that the changes in OMB Bulletin
20-01 encompassed delineation changes that do not impact the CBSA-based
labor market area delineations adopted in FY 2021. Therefore, while we
proposed to adopt the updates set forth in OMB Bulletin No. 20-01
consistent with our longstanding policy of adopting OMB delineation
updates, we noted that specific wage index updates would not be
necessary for FY 2022 as a result of adopting these OMB updates and for
these reasons CMS is likewise not making such a proposal for FY 2023.
The proposed wage index applicable to FY 2023 is set forth in
Tables A and B and is available on the CMS website at <a href="http://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/SNFPPS/WageIndex.html">http://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/SNFPPS/WageIndex.html</a>.
Once calculated, we would apply the wage index adjustment to the
labor-related portion of the Federal rate. Each year, we calculate a
revised 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 2018 (82 FR 36548 through
36566), we finalized a proposal to revise the labor-related share to
reflect the relative importance of the 2014-based SNF market basket
cost weights for the following cost categories: Wages and Salaries;
Employee Benefits; Professional Fees: Labor-Related; Administrative and
Facilities Support

[[Page 22730]]

Services; Installation, Maintenance, and Repair Services; All Other:
Labor-Related Services; and a proportion of Capital-Related expenses.
Effective beginning FY 2022 (86 FR 42437), we rebased and revised 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 42424).
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 2023. 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 2023 than the base year weights
from the SNF market basket. We calculate the labor-related relative
importance for FY 2023 in four steps. First, we compute the FY 2023
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 2023 price index level for that cost category by the
total market basket price index level. Third, we determine the FY 2023
relative importance for each cost category by multiplying this ratio by
the base year (2018) weight. Finally, we add the FY 2023 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 2023
labor-related relative importance.
Table 7 summarizes the proposed labor-related share for FY 2023,
based on IGI's fourth quarter 2021 forecast of the 2018-based SNF
market basket, compared to the labor-related share that was used for
the FY 2022 SNF PPS final rule.
[GRAPHIC] [TIFF OMITTED] TP15AP22.014

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 2023
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 stakeholders 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 2023 (Federal rates
effective October 1, 2022), 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 2022 to the weighted average wage adjustment
factor for FY 2023. For this calculation, we would use the same FY 2021
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

[[Page 22731]]

neutrality factor for FY 2023 as set forth in this proposed rule is
1.0011.
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.

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 policies and proposals for the SNF VBP Program.

F. Adjusted Rate Computation Example

Tables 8 through 10 provide examples generally illustrating payment
calculations during FY 2023 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 proposed parity adjustment discussed in section
V.C. of this proposed rule) to compute the provider's case-mix adjusted
per diem rate for FY 2023, 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 2023 SNF PPS wage index that appears
in Table A available on the CMS website at <a href="http://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/SNFPPS/WageIndex.html">http://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/SNFPPS/WageIndex.html</a>. 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 8,
SNF XYZ's total PPS payment for this particular patient's stay would
equal $20,112.27.
BILLING CODE 4120-01-P
[GRAPHIC] [TIFF OMITTED] TP15AP22.015

[GRAPHIC] [TIFF OMITTED] TP15AP22.016

[[Page 22732]]

[GRAPHIC] [TIFF OMITTED] TP15AP22.017

BILLING CODE 4120-01-C

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 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/

[[Page 22733]]

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
(<a href="https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/SNFPPS/index.html">https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/SNFPPS/index.html</a>), 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).
A detailed discussion of the legislative history of the
consolidated billing provision is available on the SNF PPS website at
<a href="https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/SNFPPS/Downloads/Legislative_History_2018-10-01.pdf">https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/SNFPPS/Downloads/Legislative_History_2018-10-01.pdf</a>. 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 <a href="http://www.cms.gov/transmittals/downloads/ab001860.pdf">www.cms.gov/transmittals/downloads/ab001860.pdf</a>.
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. Rep. No. 106-479 at 854 (1999) (Conf. Rep.)) characterizes the
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 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,
new 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 described in that section.
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

[[Page 22734]]

requesting that the identified HCPCS code(s) be excluded.
We note that the original BBRA amendment and the CAA 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, July 1, 2020), as subsequently modified by the
Secretary. In addition, as noted above 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 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, 2022). 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
<a href="https://www.cms.gov/Medicare/Billing/SNFConsolidatedBilling">https://www.cms.gov/Medicare/Billing/SNFConsolidatedBilling</a>.

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 <a href="https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/SNFPPS/index.html">https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/SNFPPS/index.html</a>.

D. Revisions to the Regulation Text

We propose to make certain revisions in the regulation text itself.
Specifically, we propose to revise Sec. 413.337(b)(4) and add new
paragraphs (b)(4)(i) through (iii). These proposed revisions reflect
that the application of the wage index would be made on the basis of
the location of the facility in an urban or rural area as defined in
Sec. 413.333, and that starting on October 1, 2022, we would apply a
cap on decreases to the wage index such that the wage index applied to
a SNF is not less than 95 percent of the wage index applied to that SNF
in the prior FY, as discussed in section V.A. of this proposed rule.

V. Other SNF PPS Issues

A. Proposed Permanent Cap on Wage Index Decreases

As discussed above in section III.D. of this rule, we have proposed
and finalized temporary transition policies in the past to mitigate
significant changes to payments due to changes to the SNF PPS wage
index. Specifically, for FY 2015 (79 FR 45644 through 45646), we
implemented a 50/50 blend for all geographic areas consisting of the
wage index values computed using the then-current OMB area delineations
and the wage index values computed using new area delineations based on
OMB Bulletin No. 13-01. In FY 2021 (85 FR 47594, 47617), we implemented
a 1-year transition to mitigate any negative effects of wage index
changes by applying a 5 percent cap on any decrease in a SNF's wage
index from the final wage index from FY 2020. We explained that we
believed the 5-percent cap would provide greater transparency and would
be administratively less complex than the prior methodology of applying
a 50/50 blended wage index. We indicated that no cap would be applied
to the reduction in the wage index for FY 2022, and we noted that this
transition approach struck an appropriate balance by providing a
transition period to mitigate the resulting short-term instability and
negative impacts on providers and time for them to adjust to their new
labor market area delineations and wage index values.
In the FY 2022 final rule (86 FR 42424, 42439), commenters
recommended CMS extend the transition period adopted in the FY 2021 SNF
PPS final rule so that SNFs could offset the enormous cuts scheduled
for FY 2022. Because we did not propose to modify the transition policy
that was finalized in the FY 2021 SNF PPS final rule, we did not extend
the transition period for FY 2022. However, we acknowledged that
certain changes to wage index policy may significantly affect Medicare
payment. In addition, we reiterated that our policy principles with
regard to the wage index include generally using the most current data
and information available and providing that data and information, as
well as any approaches to addressing any significant effects on
Medicare payments resulting from these potential scenarios, in notice
and comment rulemaking. With these policy principles in mind for this
FY 2023 proposed rule, we considered how best to address the potential
scenarios about which commenters raised concerns in the FY 2022 final
rule around SNF payment volatility; that is, scenarios in which changes
to wage index policy may significantly affect Medicare payments.
In the past, we have established transition policies of limited
duration to phase in significant changes to labor market. In taking
this approach in the past, we have sought to strike an appropriate
balance between maintaining the accuracy of the overall labor market
area wage index system and mitigating short-term instability and
negative impacts on providers due to

[[Page 22735]]

wage index changes. In accordance with the requirements of the SNF PPS
wage index regulations at Sec. 413.337(a)(1), we use an appropriate
wage index based on the best available data, including the best
available labor market area delineations, to adjust SNF PPS payments
for wage differences. We have previously stated that, because the wage
index is a relative measure of the value of labor in prescribed labor
market areas, we believe it is important to implement new labor market
area delineations with as minimal a transition as is reasonably
possible. However, we recognize that changes to the wage index have the
potential to create instability and significant negative impacts on
certain providers even when labor market areas do not change. In
addition, year-to-year fluctuations in an area's wage index can occur
due to external factors beyond a provider's control, such as the COVID-
19 public health emergency (PHE). For an individual provider, these
fluctuations can be difficult to predict. So, we also recognize that
predictability in Medicare payments is important to enable providers to
budget and plan their operations.
In light of these considerations, we are proposing a permanent
approach to smooth year-to-year changes in providers' wage indexes. We
are proposing a policy that we believe increases the predictability of
SNF PPS payments for providers, and mitigates instability and
significant negative impacts to providers resulting from changes to the
wage index.
As previously discussed, we believed applying a 5-percent cap on
wage index decreases for FY 2021 provided greater transparency and was
administratively less complex than prior transition methodologies. In
addition, we believed this methodology mitigated short-term instability
and fluctuations that can negatively impact providers due to wage index
changes. Lastly, we have noted that we believed the 5-percent cap we
applied to all wage index decreases for FY 2021 provided an adequate
safeguard against significant payment reductions related to the
adoption of the revised CBSAs. However, we recognize there are
circumstances that a one-year mitigation policy, like the one adopted
for FY 2021, would not effectively address future years where providers
continue to be negatively affected by significant wage index decreases.
Typical year-to-year variation in the SNF PPS wage index has
historically been within 5 percent, and we expect this will continue to
be the case in future years. For FY 2023, the provider level impact
analysis indicates that approximately 97 percent of SNFs will
experience a wage index change within 5 percent. Because providers are
usually experienced with this level of wage index fluctuation, we
believe applying a 5-percent cap on all wage index decreases each year,
regardless of the reason for the decrease, would effectively mitigate
instability in SNF PPS payments due to any significant wage index
decreases that may affect providers in any year. We believe this
approach would address concerns about instability that commenters
raised in the FY 2022 SNF PPS rule. Additionally, we believe that
applying a 5-percent cap on all wage index decreases would support
increased predictability about SNF PPS payments for providers, enabling
them to more effectively budget and plan their operations. Lastly,
because applying a 5-percent cap on all wage index decreases would
represent a small overall impact on the labor market area wage index
system we believe it would ensure the wage index is a relative measure
of the value of labor in prescribed labor market wage areas. As
discussed in further detail in section XI.A.4. of this proposed rule,
we estimate that applying a 5-percent cap on all wage index decreases
will have a very small effect on the wage index budget neutrality
factor for FY 2023. Because the wage index is a measure of the value of
labor (wage and wage-related costs) in a prescribed labor market area
relative to the national average, we anticipate that in the absence of
proposed policy changes most providers will not experience year-to-year
wage index declines greater than 5 percent in any given year. We also
believe that when the 5-percent cap would be applied under this
proposal, it is likely that it would be applied similarly to all SNFs
in the same labor market area, as the hospital average hourly wage data
in the CBSA (and any relative decreases compared to the national
average hourly wage) would be similar. While this policy may result in
SNFs in a CBSA receiving a higher wage index than others in the same
area (such as situations when delineations change), we believe the
impact would be temporary. Therefore, we anticipate that the impact to
the wage index budget neutrality factor in future years would continue
to be minimal.
The Secretary has broad authority to establish appropriate payment
adjustments under the SNF PPS, including the wage index adjustment. As
discussed earlier in this section, the SNF PPS regulations require us
to use an appropriate wage index based on the best available data. For
the reasons discussed earlier in this section, we believe that a 5-
percent cap on wage index decreases would be appropriate for the SNF
PPS. Therefore, for FY 2023 and subsequent years, we are proposing to
apply a permanent 5-percent cap on any decrease to a provider's wage
index from its wage index in the prior year, regardless of the
circumstances causing the decline. That is, we are proposing that a
SNF's wage index for FY 2023 would not be less than 95 percent of its
final wage index for FY 2022, regardless of whether the SNF is part of
an updated CBSA, and that for subsequent years, a provider's wage index
would not be less than 95 percent of its wage index calculated in the
prior FY. This means, if a SNF's prior FY wage index is calculated with
the application of the 5-percent cap, then the following year's wage
index would not be less than 95 percent of the SNF's capped wage index
in the prior FY. For example, if a SNF's wage index for FY 2023 is
calculated with the application of the 5-percent cap, then its wage
index for FY 2024 would not be less than 95 percent of its capped wage
index in FY 2023. Lastly, we propose 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. As we have discussed in this
proposed rule, we believe this proposed methodology would maintain the
SNF PPS wage index as a relative measure of the value of labor in
prescribed labor market areas, increase the predictability of SNF PPS
payments for providers, and mitigate instability and significant
negative impacts to providers resulting from significant changes to the
wage index. In section XI. of this proposed rule, we estimate the
impact to payments for providers in FY 2023 based on this proposed
policy. We also note that we would examine the effects of this policy
on an ongoing basis in the future in order to assess its continued
appropriateness.
Subject to the aforementioned proposal becoming final, we are also
proposing to revise the regulation text at Sec. 413.337(a)(1) to
provide that starting October 1, 2022, we will apply a cap on decreases
to the wage index such that the wage index applied is not less than 95
percent of the wage index applied to that SNF in the prior year.
We invite public comments on this proposal.

B. Technical Updates to PDPM ICD-10 Mappings

In the FY 2019 SNF PPS final rule (83 FR 39162), we finalized the

[[Page 22736]]

implementation of the Patient Driven Payment Model (PDPM), effective
October 1, 2019. The PDPM utilizes International Classification of
Diseases, Version 10 (ICD-10) codes in several ways, including to
assign patients to clinical categories under several PDPM components,
specifically the PT, OT, SLP and NTA components. The ICD-10 code
mappings and lists used under PDPM are available on the PDPM website at
<a href="https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/SNFPPS/PDPM">https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/SNFPPS/PDPM</a>.
Each year, the ICD-10 Coordination and Maintenance Committee, a
Federal interdepartmental committee that is chaired by representatives
from the National Center for Health Statistics (NCHS) and by
representatives from CMS, meets biannually and publishes updates to the
ICD-10 medical code data sets in June of each year. These changes
become effective October 1 of the year in which these updates are
issued by the committee. The ICD-10 Coordination and Maintenance
Committee also has the ability to make changes to the ICD-10 medical
code data sets effective on April 1 of each year.
In the FY 2020 SNF PPS final rule (84 FR 38750), we outlined the
process by which we maintain and update the ICD-10 code mappings and
lists associated with the PDPM, as well as the SNF Grouper software and
other such products related to patient classification and billing, so
as to ensure that they reflect the most up to date codes possible.
Beginning with the updates for FY 2020, we apply nonsubstantive changes
to the ICD-10 codes included on the PDPM code mappings and lists
through a subregulatory process consisting of posting updated code
mappings and lists on the PDPM website at <a href="https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/SNFPPS/PDPM">https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/SNFPPS/PDPM</a>. Such nonsubstantive
changes are limited to those specific changes that are necessary to
maintain consistency with the most current ICD-10 medical code data
set. On the other hand, substantive changes, or those that go beyond
the intention of maintaining consistency with the most current ICD-10
medical code data set, will be proposed through notice and comment
rulemaking. For instance, changes to the assignment of a code to a
comorbidity list or other changes that amount to changes in policy are
considered substantive changes for which we would undergo notice and
comment rulemaking.
We are proposing several changes to the PDPM ICD-10 code mappings
and lists. We would 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, but merely that there are more specific diagnoses
than those mapped to ``Return to Provider'' or that we do not believe
that the diagnosis should serve as the primary diagnosis for a Part-A
covered SNF stay. Our proposed changes are as follows:
On October 1, 2021, D75.839 ``Thrombocytosis, unspecified,'' took
effect and was mapped to the clinical category of ``Cardiovascular and
Coagulations.'' However, there are more specific codes to indicate why
a patient with thrombocytosis would require SNF care. If the cause is
unknown, the SNF could use D47.3, ``Essential (hemorrhagic)
thrombocythemia'' or D75.838, ``other thrombocytosis'' which is a new
code that took effect on October 1, 2021. Further, elevated platelet
count without other symptoms is not reason enough for SNF skilled care
so this would not be used as a primary diagnosis. For this reason, we
proposed to change the assignment of D75.839 to ``Return to Provider.''
On October 1, 2021, D89.44, ``Hereditary alpha tryptasemia'' went
into effect and was mapped to the clinical category, ``Medical
Management.'' However, this is not a diagnosis that would be treated as
a primary condition in the SNF, rather it would be treated in the
outpatient setting. Therefore, we propose to change the assignment of
D89.44 to ``Return to Provider.''
On October 1, 2021, F32.A, ``Depression, unspecified'' went into
effect and was mapped to ``Medical Management.'' However, there are
more specific codes that would more adequately capture the diagnosis of
depression. Further, 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
appropriate to treat a patient whose primary diagnosis is depression.
For this reason, we propose to change the assignment of F32.A to
``Return to Provider.''
On October 1, 2021, G92.9, ``Unspecified toxic encephalopathy''
took effect and was mapped to the clinical category of ``Acute
Neurologic.'' However, there are more specific codes that should be
used to describe encephalopathy treated in a SNF. Therefore, we propose
to change the assignment of G92.9 to ``Return to Provider.''
On October 1, 2021, M54.50, ``Low back pain, unspecified'' went
into effect and was mapped to the clinical category of ``Non-surgical
Orthopedic/Musculoskeletal.'' However, if low back pain were the
primary diagnosis, the SNF should have a greater understanding of what
is causing the pain. There are more specific codes to address this
condition. Therefore, we propose to change the assignment of M54.50 to
``Return to Provider.''
In the FY 2022 proposed rule (86 FR 19984 through 19985), we
proposed to reclassify K20.81, ``Other esophagitis with bleeding,''
K20.91, ``Esophagitis, unspecified with bleeding,'' and K21.01,
``Gastro-esophageal reflux disease with esophagitis, with bleeding''
from ``Return to Provider'' to ``Medical Management.'' Our rationale
for the change was a recognition that these codes represent these
esophageal conditions with more specificity than originally considered
because of the bleeding that is part of the conditions and that they
would more likely be found in SNF patients. We received one comment
suggesting additional changes to similar ICD-10 code mappings and
comorbidity lists that at the time were outside the scope of
rulemaking. This commenter suggested that we consider remapping the
following similar diagnosis codes that frequently require SNF skilled
care, from ``Return to Provider'' to ``Medical Management'': K22.11,
``Ulcer of esophagus with bleeding;'' K25.0, ``Acute gastric ulcer with
hemorrhage;'' K25.1, ``Acute gastric ulcer with perforation;'' K25.2,
``Acute gastric ulcer with both hemorrhage and perforation;'' K26.0,
``Acute duodenal ulcer with hemorrhage;'' K26.1, ``Acute duodenal ulcer
with perforation;'' K26.2, ``Acute duodenal ulcer with both hemorrhage
and perforation;'' K27.0 ``Acute peptic ulcer, site unspecified with
hemorrhage;'' K27.1, ``Acute peptic ulcer, site unspecified with
perforation;'' K27.2, ``Acute peptic ulcer, site unspecified with both
hemorrhage and perforation;'' K28.0, ``Acute gastrojejunal ulcer with
hemorrhage;'' K28.1, ``Acute gastrojejunal ulcer with perforation;''
K28.2, ``Acute gastrojejunal ulcer with both hemorrhage and
perforation;'' and K29.01, ``Acute gastritis with bleeding.'' Upon
review of these codes, we recognize that they represent conditions with
more specificity than originally considered because of the bleeding (or
perforation) that is part of the conditions and that they would more
likely be found in SNF patients.'' Therefore, we propose to remap these

[[Page 22737]]

ICD-10 codes to ``Medical Management.''
We also received a comment requesting we consider remapping M62.81,
``Muscle weakness (generalized)'' from ``Return to Provider'' to ``Non-
orthopedic Surgery'' with the rationale that there is currently no
sequela or late-effects ICD-10 code available when patients require
skilled nursing and therapy due to late effects of resolved infections
such as pneumonia or urinary tract infections. We considered the
request and determined that muscle weakness (generalized) is
nonspecific and if the original condition is resolved, but the
resulting muscle weakness persists as a result of the known original
diagnosis, there are more specific codes that exist that would account
for why the muscle weakness is on-going, such as muscle wasting or
atrophy. Therefore, we are not proposing this specific remapping. This
commenter also requested that that we consider remapping R62.7, ``Adult
failure to thrive'' from ``Return to Provider'' to ``Medical
Management.'' According to this commenter, physicians often diagnose
adult failure to thrive when a resident has been unable to have oral
intake sufficient for survival. Typically, this diagnosis is appended
when the physician has determined that a feeding tube should be
considered to provide sufficient intake for survival. According to the
commenter, it would then appropriately become the primary diagnosis for
a skilled stay. We considered this request and believe that R6.2 is a
nonspecific code and SNF primary diagnoses should be coded to the
highest level of specificity. If the patient has been unable to have
oral intake, the primary diagnosis (for example, Ulcerative Colitis)
for admission to a SNF should explain why the patient is unable to have
oral intake sufficient for survival. Therefore, we are not proposing
this specific remapping.
We invite comments on the proposed substantive changes to the ICD-
10 code mappings discussed previously in this section, as well as
comments on additional substantive and non-substantive changes that
commenters believe are necessary.

C. Recalibrating the PDPM Parity Adjustment

1. Background
On October 1, 2019, we implemented the Patient Driven Payment Model
(PDPM) under the SNF PPS, a new case-mix classification model that
replaced the prior case-mix classification model, the Resource
Utilization Groups, Version IV (RUG-IV). As discussed in the FY 2019
SNF PPS final rule (83 FR 39256), as with prior system transitions, we
proposed and finalized implementing PDPM in a budget neutral manner.
This means that the transition to PDPM, along with the related policies
finalized in the FY 2019 SNF PPS final rule, were not intended to
result in an increase or decrease in the aggregate amount of Medicare
Part A payment to SNFs. We believe ensuring parity is integral to the
process of providing ``for an appropriate adjustment to account for
case mix'' that is based on appropriate data in accordance with section
1888(e)(4)(G)(i) of the Act. Section V.I. of the FY 2019 SNF PPS final
rule (83 FR 39255 through 39256) discusses the methodology that we used
to implement PDPM in a budget neutral manner. Specifically, we
multiplied each of the PDPM case-mix indexes (CMIs) by an adjustment
factor that was calculated by comparing total payments under RUG-IV
using FY 2017 claims and assessment data (the most recent final claims
data available at the time) to what we expected total payments would be
under PDPM based on that same FY 2017 claims and assessment data. In
the FY 2020 SNF PPS final rule (84 FR 38734 through 38735), we
finalized an updated standardization multiplier and parity adjustment
based on FY 2018 claims and assessment data. This analysis resulted in
an adjustment factor of 1.46, by which all the PDPM CMIs were
multiplied so that total estimated payments under PDPM would be equal
to total actual payments under RUG-IV, assuming no changes in the
population, provider behavior, and coding. By multiplying each CMI by
1.46, the CMIs were inflated by 46 percent to achieve budget
neutrality.
We used a similar type of parity adjustment in FY 2011 when we
transitioned from RUG-III to RUG-IV. As discussed in the FY 2012 SNF
PPS final rule (76 FR 48492 through 48500), we observed that once
actual RUG-IV utilization data became available, the actual RUG-IV
utilization patterns differed significantly from those we had projected
using the historical data that grounded the RUG-IV parity adjustment.
We then used actual FY 2011 RUG-IV utilization data to recalibrate the
RUG-IV parity adjustment and decreased the nursing CMIs for all RUG-IV
therapy groups from an adjustment factor of 61 percent to an adjustment
factor of 19.84 percent, while maintaining the original 61 percent
total nursing CMI increase for all non-therapy RUG-IV groups. As a
result of this recalibration, FY 2012 SNF PPS rates were reduced by
12.5 percent, or $4.47 billion, in order to achieve budget neutrality
under RUG-IV prospectively.
Since PDPM implementation, we have closely monitored SNF
utilization data to determine if the parity adjustment finalized in the
FY 2020 SNF PPS final rule (84 FR 38734 through 38735) provided for a
budget neutral transition between RUG-IV and PDPM as intended. Similar
to what occurred in FY 2011 with RUG-IV implementation, we have
observed significant differences between the expected SNF PPS payments
and case-mix utilization based on historical data, and the actual SNF
PPS payments and case-mix utilization under PDPM, based on FY 2020 and
FY 2021 utilization data. As discussed in the FY 2022 SNF PPS final
rule (86 FR 42466 through 42469), it appears that PDPM may have
inadvertently triggered a significant increase in overall payment
levels under the SNF PPS of approximately 5 percent and that
recalibration of the parity adjustment may be warranted.
Following the methodology utilized in calculating the initial PDPM
parity adjustment, we would typically use claims and assessment data
for a given year to classify patients under both the current system and
the prior system to compare aggregate payments and determine an
appropriate adjustment factor to achieve parity. However, we
acknowledge that the typical methodology for recalibrating the parity
adjustment may not provide an accurate recalibration under PDPM for a
number of reasons. First, the ongoing COVID-19 PHE has had impacts on
nursing home care protocols and many other aspects of SNF operations
that affected utilization data in FY 2020 and FY 2021. Second, given
the significant differences in payment incentives and patient
assessment requirements between RUG-IV and PDPM, using the same
methodology that we have used in the past to calculate a recalibrated
PDPM parity adjustment could lead to a potential overcorrection in the
recalibration.
In the FY 2022 SNF PPS proposed rule (86 FR 19987 through 19989),
we solicited comments from stakeholders on a potential methodology for
recalibrating the PDPM parity adjustment to account for these potential
effects without compromising the accuracy of the adjustment. After
considering the feedback and recommendations received, summarized in
the FY 2022 SNF PPS final rule (86 FR 42469 through 42471), we are
proposing an updated recalibration methodology. We also present results

[[Page 22738]]

from our data monitoring efforts to provide transparency on our efforts
to parse out the effects of PDPM implementation from the effects of the
COVID-19 PHE. We invite comments on this proposal for recalibrating the
PDPM parity adjustment, that is discussed throughout the subsequent
sections of this proposed rule, to ensure that PDPM is implemented in a
budget neutral manner, as originally intended.
2. Methodology for Recalibrating the PDPM Parity Adjustment
a. Effect of COVID-19 Public Health Emergency
FY 2020 was a year of significant change under the SNF PPS. In
addition to implementing PDPM on October 1, 2019, a national COVID-19
PHE was declared beginning January 27, 2020. With the announcement of
the COVID-19 PHE, and under authority granted us by section 1812(f) of
the Act, we issued two temporary modifications to the limitations of
section 1861(i) of the Act beginning March 1, 2020 that affected SNF
coverage. The 3-day prior hospitalization modification allows a SNF to
furnish Medicare Part A services without requiring a 3-day qualifying
hospital stay, and the benefit period exhaustion modification allows a
one-time renewal of benefits for an additional 100 days of Part A SNF
coverage without a 60-day break in spell of illness. These COVID-19
PHE-related modifications allowed coverage for beneficiaries who would
not typically be able to access the Part A SNF benefit, such as
community and long-term care nursing home patients without a prior
qualifying hospitalization.
We acknowledge that the COVID-19 PHE had significant impacts on
nursing home care protocols and many other aspects of SNF operations.
For months, infection and mortality rates were high among nursing home
residents. Additionally, facilities were often unable to access testing
and affordable personal protective equipment (PPE), and were required
to be closed to visitors and barred from conducting communal events to
help control infections (March 2021 MedPAC Report to Congress, 204,
available at <a href="https://www.medpac.gov/wp-content/uploads/2021/10/mar21_medpac_report_ch7_sec.pdf">https://www.medpac.gov/wp-content/uploads/2021/10/mar21_medpac_report_ch7_sec.pdf</a>). As described in the FY 2022 SNF PPS
final rule (86 FR 42427), many commenters voiced concerns about
additional costs due to the COVID-19 PHE that could be permanent due to
changes in patient care, infection control staff and equipment,
personal protective equipment, reporting requirements, increased wages,
increased food prices, and other necessary costs. Some commenters who
received CARES Act Provider Relief funds indicated that those funds
were not enough to cover these additional costs. Additionally, a few
commenters from rural areas stated that their facilities were heavily
impacted from the additional costs, particularly the need to raise
wages, and that this could affect patients' access to care.
However, we note that the relevant issue for a recalibration of the
PDPM parity adjustment is whether or not the COVID-19 PHE caused
changes in the SNF case-mix distribution. In other words, the issue is
whether patient classification, or the relative percentages of
beneficiaries in each PDPM group, was different than what it would have
been if not for the COVID-19 PHE. We remind commenters that the parity
adjustment refers only to the transition between case-mix
classification models (in this case, from RUG-IV to PDPM) and is not
intended to include other unrelated SNF policies such as the market
basket increase, which is intended to address such issues as the
additional costs described previously. A key aspect of our
recalibration methodology, described in further detail later in this
section, involves parsing out the impacts of the COVID-19 PHE and the
PHE-related modifications from those which occurred solely, or at least
principally, due to the implementation of PDPM.
b. Effect of PDPM Implementation
As discussed in the FY 2022 SNF PPS final rule (86 FR 42467), we
presented evidence that the transition to PDPM impacted certain aspects
of SNF patient classification and care provision prior to the beginning
of the COVID-19 PHE. For example, according to the latest data
available, SNF patients received an average of approximately 93 therapy
minutes per utilization day in FY 2019. Between October 2019 and
December 2019, the 3 months after PDPM implementation and before the
onset of the COVID-19 PHE, the average number of therapy minutes SNF
patients received per day dropped to approximately 68 minutes per
utilization day, a decrease of approximately 27 percent. Given this
reduction in therapy provision since PDPM implementation, we found that
using patient assessment data collected under PDPM would lead to a
significant underestimation of what RUG-IV case-mix and payments would
have been (for example, the Ultra-High and Very-High Rehabilitation
assignments are not nearly as prevalent using PDPM-reported data),
which would in turn lead to an overcorrection in the parity adjustment.
Additionally, there were significant changes in the patient assessment
schedule such as the removal of the Change of Therapy Other Medicare
Required Assessment. Without having an interim assessment between the
5-day assessment and the patient's discharge from the facility, we are
unable to determine if the RUG-IV group into which the patient
classified on the 5-day assessment changed during the stay, or if the
patient continued to receive an amount of therapy services consistent
with the initial RUG-IV classification.
Therefore, given the significant differences in payment incentives
and patient assessment requirements between RUG-IV and PDPM, using the
same methodology that we have used in the past to calculate a
recalibrated PDPM parity adjustment could lead to a potential
overcorrection in the recalibration. In the FY 2022 SNF PPS proposed
rule (86 FR 19988), we described an alternative recalibration
methodology that used FY 2019 RUG-IV case-mix distribution as a proxy
for what total RUG-IV payments would have been absent PDPM
implementation. We believed that this methodology provides a more
accurate representation of what RUG-IV payments would have been, were
it not for the changes precipitated by PDPM implementation, than using
data reported under PDPM to reclassify these patients under RUG-IV. We
solicited comments from stakeholders on this aspect of our potential
methodology for recalibrating the PDPM parity adjustment and they were
generally receptive to our approach.
c. FY 2022 SNF PPS Proposed Rule Potential Parity Adjustment
Methodology and Comments
In the FY 2022 SNF PPS proposed rule (86 FR 19986 through 19987),
we presented a potential methodology that attempted to account for the
effects of the COVID-19 PHE by removing those stays with a COVID-19
diagnosis and those stays using a PHE-related modification from our
data set, and we solicited comment on how stakeholders believed the
COVID-19 PHE affected the distribution of patient case-mix in ways that
were not sufficiently captured by our subset population methodology.
According to the latest data available, 10 percent of SNF stays in FY
2020 and 17 percent of SNF stays in FY 2021 included a COVID-19 ICD-10
diagnosis code either as a primary or secondary diagnosis, while 17
percent of SNF stays in FY 2020 and 27 percent of SNF stays in FY 2021
utilized a PHE-related

[[Page 22739]]

modification (with the majority of these cases using the prior
hospitalization modification), as identified by the presence of a
``Disaster Relief (DR)'' condition code on the SNF claim. As compared
to prior years, when approximately 98 percent of SNF beneficiaries had
a qualifying prior hospital stay, approximately 86 percent and 81
percent of SNF beneficiaries had a qualifying prior hospitalization in
FY 2020 and FY 2021, respectively. These general statistics are
important, as they highlight that while the PHE for COVID-19 certainly
impacted many aspects of nursing home operations, the large majority of
SNF beneficiaries entered into Part A SNF stays in FY 2020 and FY 2021
as they would have in any other year; that is, without using a PHE-
related modification, with a prior hospitalization, and without a
COVID-19 diagnosis.
Moreover, as discussed FY 2022 SNF PPS proposed rule (86 FR 19988),
we found that even after removing those using a PHE-related
modification and those with a COVID-19 diagnosis from our data set, the
observed inadvertent increase in SNF payments since PDPM was
implemented was approximately the same. To calculate expected total
payments under RUG-IV, we used the percentage of stays in each RUG-IV
group in FY 2019 and multiplied these percentages by the total number
of FY 2020 days of service. We then multiplied the number of days for
each RUG-IV group by the RUG-IV per diem rate, which we obtained by
inflating the FY 2019 SNF PPS RUG-IV rates by the FY 2020 market basket
update factor. The total payments under RUG-IV also accounted for the
human immunodeficiency virus/acquired immunodeficiency syndrome (HIV/
AIDS) add-on of a 128 percent increase in the PPS per diem payment
under RUG-IV, and a provider's FY 2020 urban or rural status. To
calculate the actual total payments under PDPM, we used data reported
on FY 2020 claims. Specifically, we used the Health Insurance
Prospective Payment System (HIPPS) code on the SNF claim to identify
the patient's case-mix assignment and associated CMIs, utilization days
on the claim to calculate stay payments and the variable per diem
adjustment, the presence of an HIV diagnosis on the claim to account
for the PDPM AIDS add-on of 18 percent to the nursing component, and
the highest point value (8 points) to the NTA component, and a
provider's urban or rural status. Using this approach, and as described
in the FY 2022 SNF PPS proposed rule (86 FR 19988), we identified a 5.3
percent increase in aggregate spending under PDPM as compared to
expected total payments under RUG-IV for FY 2020 when considering the
full SNF population, and a 5 percent increase in aggregate spending
under PDPM for FY 2020 when considering the subset population. This
finding suggests that a large portion of the changes observed in SNF
utilization are due to PDPM and not the PHE for COVID-19, as the
``new'' population of SNF beneficiaries (that is, COVID-19 patients and
those using a PHE-related modification) did not appear to be the main
cause of the increase in SNF payments after implementation of PDPM.
Although these results are similar, we believed it would be more
appropriate to pursue a potential recalibration using the subset
population.
Some commenters agreed with our approach, stating that our subset
population was a reasonable method to account for the effect of the
COVID-19 PHE, and made a few suggestions for improvements. They stated
that our analysis may have undercounted COVID-19 patients because there
was no COVID-19 specific diagnosis code available before April 2020 and
a shortage of tests at the beginning of the PHE led to SNFs being
unable to report COVID-19 cases. To address these issues, commenters
suggested that CMS consider using non-specific respiratory diagnoses or
depression as proxies for COVID-19 cases. We considered this option,
though we believe that such a change would overestimate the population
to be excluded due to the non-specific nature of those diagnoses.
Additionally, because we did not provide our COVID-19 population
definition in the FY 2022 SNF PPS proposed or final rules, commenters
were concerned that our methodology did not include COVID-19 diagnoses
from the Minimum Data Set (MDS) patient assessments in addition to SNF
claims. Commenters were also concerned that we did not exclude
transitional stays resulting from CMS' instruction to assess all
patients anew in October 2019 using the PDPM MDS assessment, even
though some patients were in the middle or end of their Medicare Part A
coverage. We address these concerns by sharing a revised COVID-19
population definition in section V.C.2.d. of this rule.
However, many commenters expressed concern that our subset
population methodology would not accurately represent what the SNF
patient case-mix would look like outside of the COVID-19 PHE
environment, stating that data collected during the PHE was entirely
too laden with COVID-19 related effects on the entire SNF population to
be utilized and pointing to multiple reasons for greater clinical
acuity even among our subset population. For example, because elective
surgeries were halted, those admitted were the most compromised who
could not be cared for at home. Additionally, limitations regarding
visitation and other infection control protocols led to higher levels
of mood distress, cognitive decline, functional decline, compromised
skin integrity, change in appetite, and weight loss requiring diet
modifications. In response to these comments, we have conducted
comprehensive data analysis and monitoring to identify changes in
provider behavior and payments since implementing PDPM, and present a
revised parity adjustment methodology in section V.C.2.d. of this rule
that we believe more accurately accounts for these changes while
excluding the effect of the COVID-19 PHE on the SNF population.
d. FY 2023 SNF PPS Proposed Parity Adjustment Methodology
In this section, we propose a revised methodology for the
calculating the parity adjustment that takes into account the comments
received in response to the potential methodology described in the FY
2022 SNF PPS proposed rule (86 FR 19986 through 19987). In response to
the comments received about the subset population methodology, we
modified our definition of COVID-19, which we derived from the Centers
for Disease Control and Prevention (CDC) coding guidelines, to align
with the definition used by publicly available datasets from CMS's
Office of Enterprise Data and Analytics (OEDA) and found no significant
impact on our calculations. For the FY 2022 SNF proposed rule, we
defined the COVID-19 population to include stays that have either the
interim COVID-19 code B97.29 recorded as a primary or secondary
diagnosis in addition to one of the symptom codes J12.89, J20.8, J22,
or J80, or the new COVID-19 code U07.1 recorded as a primary or
secondary diagnosis on their SNF claims or MDS 5-day admission
assessments. For the FY 2023 SNF proposed rule, we define the COVID-19
population to include stays that have the interim COVID-19 code B97.29
from January 1, 2020 to March 31, 2020 or the new COVID-19 code U07.1
from April 1, 2020 onward recorded as a primary or secondary diagnosis
on their SNF claims, MDS 5-day admission assessments, or MDS interim
payment assessments. Both FY

[[Page 22740]]

2022 and FY 2023 definitions of the COVID-19 population exclude
transitional stays. We note that we found no significant impact on our
calculations, as the COVID-19 population definition change only
increased the stay count of our subset population by less than 1
percent.
In response to the comments described previously and based on
additional data collection through FY 2021, we have identified a
recalibration methodology that we believe better accounts for COVID-19
related effects. We propose to use the same type of subset population
discussed earlier in section V.C.2.c.of this proposed rule, which
excludes stays that either used a section 1812(f) of the Act
modification or that included a COVID-19 diagnosis, with a 1-year
``control period'' derived from both FY 2020 and FY 2021 data.
Specifically, we used 6 months of FY 2020 data from October 2019
through March 2020 and 6 months of FY 2021 data from April 2021 through
September 2021 (which our data suggests were periods with relatively
low COVID-19 prevalence) to create a full 1-year period with no
repeated months to account for seasonality effects. As shown in Table
11, we believe this combined approach provides the most accurate
representation of what the SNF case-mix distribution would look like
under PDPM outside of a COVID-19 PHE environment. While using the
subset population method alone for FY 2020 and FY 2021 data results in
differences of 0.31 percent and 0.40 percent between the full and
subset populations, respectively, introducing the control period closes
the gap between the full and subset population adjustment factors to
0.02 percent, suggesting that the control period captures additional
COVID-19 related effects on patient acuity that the subset population
method alone does not. Accordingly, the combined methodology of using
the subset population with data from the control period results in the
lowest parity adjustment factor. Table 12 shows that while using the
subset population method would lead to a 4.9 percent adjustment factor
($1.8 billion) using FY 2020 data and a 5.3 percent adjustment factor
($1.9 billion) using FY 2021 data, introducing the control period
reduces the adjustment factor to 4.6 percent ($1.7 billion). The
robustness of the control period approach is further demonstrated by
the fact that using data from the control period, with either the full
or subset population, would lead to approximately the same parity
adjustment factor of 4.58 percent as compared to 4.6 percent. We invite
comments on our proposed combined methodology of using the subset
population and data from the control period for the purposes of
calculating the recalibrated parity adjustment factor.
[GRAPHIC] [TIFF OMITTED] TP15AP22.018

[GRAPHIC] [TIFF OMITTED] TP15AP22.019

Our data analysis and monitoring efforts provides further support
for the accuracy and appropriateness of a 4.6 percent parity adjustment
factor, as we have identified numerous changes that demonstrate the
different impacts of PDPM implementation and the COVID-19 PHE on
reported patient clinical acuity. As described earlier, commenters
stated that limitations regarding visitation and other infection
control protocols due to the PHE led to higher levels of mood distress,
cognitive decline, functional decline, compromised skin integrity,
change in appetite, and weight loss requiring diet modifications among
the non-COVID population. However, our data shows that most of these
metrics, with the exception of functional decline and compromised skin
integrity, had already exhibited clear changes concurrent with PDPM
implementation and well before the start of the COVID-19 PHE. For
example, in regard to higher levels of mood distress and cognitive
decline, we observed an average of 4 percent of stays with depression
and 40 percent of stays with cognitive impairment, with an average mood
score of 1.9, in the fiscal year prior to PDPM implementation (FY
2019). In the 3 months directly following PDPM implementation and
before the start of the COVID-19 PHE (October 2019 to December 2019),
these averages increased to 11 percent of stays with depression and 44
percent of stays with cognitive impairment, with an average mood scale
of 2.9. As for change in appetite and weight loss requiring diet
modifications, we observed an average of 15 percent of stays with any
SLP comorbidity, 5 percent of stays with a swallowing disorder, and 22
percent of stays with a mechanically altered diet in FY 2019. In the 3
months directly following PDPM implementation, these averages increased
to 19 percent of stays with any SLP comorbidity, 17 percent of stays
with a swallowing disorder, and 25 percent of stays with a mechanically
altered diet. Notably, we also observed that the percentage of stays
with a swallowing disorder that did not also receive a mechanically
altered diet increased from 1 percent in FY 2019 to 5 percent in the 3
months directly

[[Page 22741]]

following PDPM implementation. While many of these metrics increased
further after the start of the COVID-19 PHE, they remained elevated at
around their post-PDPM implementation levels even during periods of low
COVID-19 prevalence. As a result, our parity adjustment calculations
remained much the same even during months when rates of COVID-19 cases
were quite low, suggesting that patient case mix classification has
stabilized independent of the ongoing COVID-19 PHE.
Another reason that commenters cited to explain the greater
clinical acuity among the subset population is that, because elective
surgeries were halted, patients who were admitted were more severely
ill and could not be treated at home. We acknowledge that the subset
population methodology, or any method predicated on data from the
COVID-19 PHE period, may not accurately represent what SNF patient
case-mix would look like outside of the COVID-19 PHE environment
because while we can remove data that we believe are due to COVID
impacts, it is more difficult to add data back in that was missing due
to the COVID-19 PHE.
However, we believe that the addition of the control period to the
subset population methodology helps to resolve this issue. For example,
there likely would have been more joint replacements were it not for
the COVID-19 PHE. Our data show that the rate of major joint
replacement or spinal surgery decreased from 7.6 percent of stays in FY
2019, to 5.5 percent of stays in FY 2021, to 5.2 percent of stays in FY
2022. Similarly, rates of orthopedic surgery decreased from 9.1 percent
of stays in FY 2019, to 9.0 percent of stays in FY 2021, to 8.8 percent
of stays in FY 2022. Using the control period, which excludes the
periods of highest COVID-19 prevalence and lowest rates of elective
surgeries, we arrive at rates of 6.4 percent of stays with major joint
replacement or spinal surgery, and 9.5 percent of stays with orthopedic
surgery. Therefore, we believe that using the control period is a
closer representation of SNF patient case-mix outside of a COVID-19 PHE
environment than using either FY 2021 or FY 2022 data alone.
Given the results of our data analyses, we propose adopting the
methodology based upon the subset population during the control period,
and lowering the PDPM parity adjustment factor from 46 percent to 38
percent for each of the PDPM case-mix adjusted components. If we
applied this methodology for FY 2023, we estimated a reduction in
aggregate SNF spending of 4.6 percent, or approximately $1.7 billion.
We note that the parity adjustment is calculated and applied at a
systemic level to all facilities paid under the SNF PPS, and there may
be variation between facilities based on their unique patient
population, share of non-case-mix component payment, and urban or rural
status. We invite comments on the methodology described in this section
of the proposed rule for recalibrating the PDPM parity adjustment, as
well as the findings of our analysis described throughout this section.
To assist commenters in providing comments on this issue, we have also
posted a file on the CMS website, at <a href="https://www.cms.gov/medicare/medicare-fee-for-service-payment/snfpps">https://www.cms.gov/medicare/medicare-fee-for-service-payment/snfpps</a>, which provides the FY 2019 RUG
IV case-mix distribution and calculation of total payments under RUG-
IV, as well as PDPM case-mix utilization data at the case mix group and
component level to demonstrate the calculation of total payments under
PDPM.
3. Methodology for Applying the Recalibrated PDPM Parity Adjustment
As discussed in the FY 2022 SNF PPS proposed rule (86 FR 19988), we
believe it would be appropriate to apply the recalibrated parity
adjustment across all PDPM CMIs in equal measure, as the initial
increase to the PDPM CMIs to achieve budget neutrality was applied
equally, and therefore, this method would properly implement and
maintain the integrity of the PDPM classification methodology as it was
originally designed. Tables 5 and 6 in section III.C. of this proposed
rule set forth what the PDPM CMIs and case-mix adjusted rates would be
if we apply the recalibration methodology in equal measure in FY 2023.
We acknowledge that we received several comments in response to
last year's rule objecting to this approach given that our data
analysis, presented in Table 23 of the FY 2022 SNF PPS proposed rule
(86 FR 19987), showed significant increases in the average CMI for the
SLP, Nursing, and NTA components for both the full and subset FY 2020
populations as compared to what was expected, with increases of 22.6
percent, 16.8 percent, and 5.6 percent, respectively, for the full FY
2020 SNF population. As described in the FY 2022 SNF PPS final rule (86
FR 42471), some commenters disagreed with adjusting the CMIs across all
case-mix adjusted components in equal measure, suggesting that this
approach would harm patient care by further reducing PT and OT therapy
minutes. Instead, the commenters recommended a targeted approach that
focuses the parity adjustment on the SLP, Nursing, and NTA components
in proportion to how they are driving the unintended increase observed
under PDPM.
We considered these comments but believe that it would be most
appropriate to propose applying the parity adjustment across all
components equally. First, as described earlier, the initial increase
to the PDPM CMIs to achieve budget neutrality was applied across all
components, and therefore, it would be appropriate to implement a
revision to the CMIs in the same way. Second, the reason we do not
observe the same magnitude of change in the PT and OT components is
that, in designing the PDPM payment system, the data used to help
determine what payment groups SNF patients would classify into under
PDPM was collected under the prior payment model (RUG-IV), which
included incentives that encouraged significant amounts of PT and OT.
Given that PT and OT were furnished in such high amounts under RUG-IV,
we had already assumed that a significant portion of patients would be
classified into the higher paying PT and OT groups corresponding to
having a Section GG function score of 10 to 23. Therefore, this left
little room for additional increases in PT and OT classification after
PDPM implementation. In other words, the PT and OT components results
were as expected according to the original design of PDPM, while the
SLP, Nursing, and NTA results were not.
However, to fully explore the alternative targeted approach that
commenters suggested, we have updated our analysis of the average CMI
by PDPM component from Table 23 of the FY 2022 SNF PPS proposed rule
(86 FR 19987) and found that a similar pattern still holds when
comparing the expected average CMIs for FY 2019 and the expected actual
CMIs for the subset population during the control period. Table 13
shows significant increases in average case-mix of 18.6 percent for the
SLP component and the 10.8 percent for the Nursing component, a
moderate increase of 3.0 percent for the NTA component, and a slight
increase of 0.4 percent for the PT and OT components, respectively. We
also provide Table 14 to show the potential impact of applying the
recalibrated PDPM parity adjustment to the PDPM CMIs in a targeted
manner, instead of an equal approach as presented in Tables 5 and 6 in
section III.C. of this proposed rule. We invite comments on whether
stakeholders believe a targeted approach is preferable to our proposed
equal approach.
BILLING CODE 4120-01-P

[[Page 22742]]

[GRAPHIC] [TIFF OMITTED] TP15AP22.020

[GRAPHIC] [TIFF OMITTED] TP15AP22.021

BILLING CODE 4120-01-C
4. Delayed and Phased Implementation
As we noted in the FY 2012 SNF PPS final rule (76 FR 48493), we
believe it is imperative that we act in a well-considered but expedient
manner once excess payments are identified, as we did in FY 2012.
However, we acknowledged that applying a reduction in payments without
time to prepare could create a financial burden for providers,
particularly considering the ongoing COVID-19 PHE. Therefore, in the FY
2022 SNF PPS proposed rule (86 FR 19988 through 19990), we solicited
comments on two potential mitigation strategies to ease the transition
to prospective budget neutrality: Delayed implementation and phased
implementation, both of which are described later in this section. We
noted that for either of these options, the adjustment would be applied
prospectively, and the CMIs would not be adjusted to account for
deviations from budget neutrality in years before the payment
adjustments are implemented.
A delayed implementation strategy would mean that we would
implement the reduction in payment in a later year than the year the
reduction is finalized. For example, considering the 4.6 percent
reduction discussed previously in this preamble, if this reduction is
finalized in FY 2023 with a 1-year delayed implementation, this would
mean that the full 4.6 percent reduction

[[Page 22743]]

will be applied prospectively applied to the PDPM CMIs in FY 2024. By
comparison, a phased implementation strategy would mean that the amount
of the reduction would be spread out over some number of years. For
example, if we were to use a 2-year phased implementation approach to
the 4.6 percent reduction discussed previously in this proposed rule
with no delayed implementation, this would mean that the PDPM CMIs
would be reduced by 2.3 percent in the first year of implementation in
FY 2023 and then reduced by the remaining 2.3 percent in the second and
final year of implementation in FY 2024. We could also use a
combination of both mitigation strategies, such as a 1-year delayed
implementation with a 2-year phased approach, would mean that the PDPM
CMIs would be reduced by 2.3 percent in the first year of
implementation in FY 2024 and then reduced by the remaining 2.3 percent
in the second and final year of implementation in FY 2025.
In the FY 2022 SNF PPS proposed rule (86 FR 19988 through 19990),
we solicited comments on the possibility of combining the delayed and
phased implementation approaches and what stakeholders believe would be
appropriate to appropriately mitigate the impact of the reduction in
SNF PPS payments. As described in the FY 2022 SNF PPS final rule (86 FR
42470 through 42471), the majority of commenters supported combining
both mitigation strategies of delayed implementation of 2 years and a
gradual phase-in of no more than 1 percent per year. In its comments to
the FY 2022 SNF PPS proposed rule, MedPAC supported delayed
implementation, but did not believe a phased-in approach was warranted
given the high level of aggregate payment to SNFs.
As stated in the FY 2022 SNF PPS proposed rule (86 FR 19989) and FY
2022 SNF PPS final rule (86 FR 42471), we believe it is imperative that
we act in a well-considered but expedient manner once excess payments
are identified. Additionally, we stated that we would consider whether
the delayed and phased implementation approaches were warranted to
mitigate potential negative impacts on providers resulting from
implementation of such a reduction in the SNF PPS rates entirely within
a single year. After careful consideration, we are proposing to
recalibrate the parity adjustment in FY 2023 with no delayed
implementation or phase-in period, particularly after considering that
we have already granted a 1-year delayed implementation by not
proposing or finalizing the parity adjustment in the FY 2022 SNF PPS
proposed and final rules. This proposal would lead to a prospective
reduction in Medicare Part A SNF payments of approximately 4.6 percent
(-$1.7 billion) in FY 2023. We would note that this reduction would be
substantially mitigated by the proposed FY 2023 net SNF market basket
update factor of 3.9 percent, which reflects a market basket increase
factor of 2.8 percent, adjusted upward to account for the 1.5
percentage point forecast error correction and adjusted downward to
account for the 0.4 percentage point productivity adjustment, as
discussed in section III.B. of this proposed rule. Taken together, the
preliminary net budget impact in FY 2023 would be an estimated decrease
of $320 million in aggregate payment to SNFs if the parity adjustment
is implemented in one year.
While we note many commenters supported both mitigation strategies
of delayed implementation and phased implementation, we emphasize that
we have already granted a 1-year delayed implementation by not
proposing or finalizing the parity adjustment in the FY 2022 SNF PPS
proposed and final rules, and instead taking a year to solicit and
consider comments on our parity adjustment methodology. As stated in
the FY 2022 final rule, we estimated a reduction in SNF spending of 5
percent, or approximately $1.7 billion, if we had implemented the
parity adjustment in FY 2022 (86 FR 42471). Moreover, in light of the
potential reduction in payments associated with each possible option
outlined in Table 2, the SNF PPS has been paying in excess of budget
neutrality at a rate of approximately $1.7 billion per year since PDPM
was implemented in FY 2020. We therefore believe that delaying the
implementation of the proposed recalibration or phasing the
recalibration in over some amount of time would only serve to prolong
these payments in excess of the intended policy.
Further, MedPAC's March 2022 Report to Congress (available at
<a href="https://www.medpac.gov/wp-content/uploads/2022/03/Mar22_MedPAC_ReportToCongress_Ch7_SEC.pdf">https://www.medpac.gov/wp-content/uploads/2022/03/Mar22_MedPAC_ReportToCongress_Ch7_SEC.pdf</a>) has found that since 2000,
the aggregate Medicare margin for freestanding SNFs has consistently
been above 10 percent each year. In 2020, the aggregate Medicare margin
was 16.5 percent, a sizable increase from 11.9 percent in 2019.
Additionally, the aggregate Medicare margin in 2020 increased to an
estimated 19.2 percent when including Federal relief funds for the
COVID-19 PHE (March 2022 MedPAC Report to Congress, 251-252). Given
these high Medicare margins, we do not believe that a delayed
implementation or a phase-in approach is needed. Rather, these
mitigation strategies would continue to pay facilities at levels that
significantly exceed intended SNF payments, had PDPM been implemented
in a budget neutral manner as finalized by CMS in the FY 2019 SNF PPS
final rule (83 FR 39256). It is also important to note that the parity
adjustment recalibration would serve to remove an unintended increase
in payments from moving to a new case mix classification system, rather
than decreasing an otherwise appropriate payment amount. Thus, we do
not believe that the recalibration should negatively affect facilities,
beneficiaries, and quality of care, or create an undue hardship on
providers.
We continue to believe that in implementing PDPM, it is essential
that we stabilize the baseline as quickly as possible without creating
a significant adverse effect on the industry or to beneficiaries. We
invite comments on our proposal to recalibrate the parity adjustment by
4.6 percent in FY 2023, and whether stakeholders believe delayed
implementation or phase-in period is warranted or not, in light of the
data analysis and policy considerations presented previously.

D. Request for Information: Infection Isolation

Under the SNF PPS, various patient characteristics are used to
classify patients in Medicare-covered SNF stays into payment groups.
One of these characteristics is isolation due to an active infection.
In order for a patient to qualify to be coded as being isolated for an
active infectious disease, the patient must meet all of the following
criteria:
1. The patient has active infection with highly transmissible or
epidemiologically significant pathogens that have been acquired by
physical contact or airborne or droplet transmission.
2. Precautions are over and above standard precautions. That is,
transmission-based precautions (contact, droplet, and/or airborne) must
be in effect.
3. The patient is in a room alone because of active infection and
cannot have a roommate. This means that the resident must be in the
room alone and not cohorted with a roommate regardless of whether the
roommate has a similar active infection that requires isolation.
4. The patient must remain in his or her room. This requires that
all services be brought to the resident (for example, rehabilitation,
activities, dining, etc.).

[[Page 22744]]

Being coded for infection isolation can have a significant impact
on the Medicare payment rate for a patient's SNF stay. The increase in
a SNF patient's payment rate as a result of being coded under infection
isolation is driven by the increase in the relative costliness of
treating a patient who must be isolated due to an infection. More
specifically, in 2005, we initiated a national nursing home staff time
measurement (STM) study, the Staff Time and Resource Intensity
Verification (STRIVE) Project. The STRIVE project was the first
nationwide time study for nursing homes in the United States to be
conducted since 1997, and the data collected were used to establish
payment systems for Medicare skilled nursing facilities (SNFs) as well
as Medicaid nursing facilities (NFs).
In the STRIVE project final report, titled ``Staff Time and
Resource Intensity Verification Project Phase II'' section 4.8
(available at <a href="https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/SNFPPS/TimeStudy">https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/SNFPPS/TimeStudy</a>), we discussed how infection isolation was
categorized into the Extensive Services RUG-III category based on the
high resource intensity that was required for treating patients for
whom facilities would code this category on the MDS. The significant
increase in payment associated with this item is intended to account
for the increase in relative resource utilization and costs associated
with treating a patient isolated due to an active infection, as well as
the PPE and additional protocols which must be followed treating such a
patient, which are significantly greater than treating patients outside
of such an environment.
During the COVID-19 PHE, a number of stakeholders raised concerns
with the definition of ``infection isolation'', as it relates to the
treatment of SNF patients being cohorted due to either the diagnosis or
suspected diagnosis of COVID-19. Specifically, stakeholders took issue
with criterion 1, which requires that the patient have an active
infection, rather than suspicion of an active infection, and criterion
3, which requires that the patient be in the room alone, rather than
being cohorted with other patients. To this point, we have maintained
that the definition of ``infection isolation'' is appropriate and
should not be changed in response to the circumstances of the COVID-19
PHE. Due to the ubiquitous nature of the PHE and precautions that are
being taken throughout SNFs with regard to PPE and other COVID-19
related needs, we understand that the general costs for treating all
SNF patients may have increased. However, as the case-mix
classification model is intended to adjust payments based on relative
differences in the cost of treating different SNF patients, we are
unclear on if the relative increase in resource intensity for each
patient being treated within a cohorted environment is the same
relative increase as it would be for treating a single patient isolated
due to an active infection.
We would like to take this opportunity to invite the public to
submit their comments about isolation due to active infection and how
the PHE has affected the relative staff time resources necessary for
treating these patients. Specifically, we invite comments on whether or
not the relative increase in resource utilization for each of the
patients within a cohorted room, all with an active infection, is the
same or comparable to that of the relative increase in resource
utilization associated with a patient that is isolated due to an active
infection.

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 update described
in section 1888(e)(5)(B)(i) of the Act applicable to a SNF for a fiscal
year, 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 fiscal year. For
more information on the requirements we have adopted for the SNF QRP,
we refer readers to the FY 2016 SNF PPS final rule (80 FR 46427 through
46429), FY 2017 SNF PPS final rule (81 FR 52009 through 52010), FY 2018
SNF PPS final rule (82 FR 36566 through 36605), FY 2019 SNF PPS final
rule (83 FR 39162 through 39272), and FY 2020 SNF PPS final rule (84 FR
38728 through 38820).

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 2023 SNF QRP
The SNF QRP currently has 15 measures for the FY 2023 SNF QRP,
which are outlined in Table 15. 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)(3).
BILLING CODE 4120-01-P

[[Page 22745]]

[GRAPHIC] [TIFF OMITTED] TP15AP22.022

BILLING CODE 4120-01-C

C. SNF QRP Quality Measure Proposals Beginning With the FY 2025 SNF QRP

Section 1899B(h)(1) of the Act permits the Secretary to remove,
suspend, or add quality measures or resource use or other measures
described in sections 1899B(c)(1) and (d)(1) of the Act, respectively,
so long as the Secretary publishes in the Federal Register (with a
notice and comment period) a justification for such removal, suspension
or addition. Section 1899B(a)(1)(B) of the Act requires that all of the
data that must be reported in accordance with section 1899B(a)(1)(A) of
the Act (including resource use or other measure data under section
1899B(d)(1) of the Act) be standardized and interoperable to allow for
the exchange of the information among post-acute care (PAC) providers
and other providers and the use by such providers of such data to
enable access to longitudinal information and to facilitate coordinated
care.
We propose to adopt one new measure for the SNF QRP beginning with
the FY 2025 SNF QRP: The Influenza Vaccination Coverage among
Healthcare Personnel (HCP) (NQF #0431) measure as an ``other measure''
under section 1899B(d)(1) of the Act. In accordance with section
1899B(a)(1)(B) of the Act, the data used to calculate this measure are
standardized and interoperable. The proposed measure supports the
``Preventive Care'' Meaningful Measure area and the ``Promote Effective
Prevention and Treatment of Chronic Disease'' healthcare priority.\9\
The Influenza Vaccination Coverage among HCP measure is a process
measure, developed by the Centers for Disease Control and Prevention
(CDC), and reports on the percentage of HCP who receive the influenza
vaccination. This measure is currently used in other post-acute care
(PAC) Quality Reporting Programs (QRPs), including the Inpatient
Rehabilitation Facility (IRF) QRP and the Long-Term Care Hospital
(LTCH) QRP. The measure is described in more detail in section VI.C.1.
of this proposed rule.
---------------------------------------------------------------------------

\9\ CMS Measures Inventory Tool. (2022). Influenza Vaccination
Coverage among Healthcare Personnel. Retrieved from <a href="https://cmit.cms.gov/CMIT_public/ReportMeasure?measureId=854">https://cmit.cms.gov/CMIT_public/ReportMeasure?measureId=854</a>.
---------------------------------------------------------------------------

In addition, we propose to revise the compliance date for the
collection of the Transfer of Health (TOH) Information to the Provider-
PAC measure, the TOH Information to the Patient-PAC measure, and
certain standardized patient assessment data elements from October 1st
of the year that is at least 2 full fiscal years after the end of the
COVID-19

[[Page 22746]]

PHE to October 1, 2023. We believe the COVID-19 PHE revealed why the
TOH Information measures and standardized patient assessment data
elements are important to the SNF QRP. The new data elements will
facilitate communication and coordination across care settings as well
as provide information to support our mission of analyzing the impact
of the COVID-19 PHE on patients to improve the quality of care in SNFs.
We describe this proposal in more detail in section VI.C.2. of this
proposed rule.
Finally, we propose to make certain revisions to regulation text at
Sec. 413.360 to include a new paragraph to reflect all the data
completion thresholds required for SNFs to meet the compliance
threshold for the annual payment update, as well as certain conforming
revisions. We describe this proposal in more detail in section VI.C.3.
of this proposed rule.
1. Influenza Vaccination Coverage Among Healthcare Personnel (NQF
#0431) Measure Beginning With the FY 2025 SNF QRP
a. Background
The CDC Advisory Committee on Immunization Practices (ACIP)
recommends that all persons 6 months of age and older, including HCP
and persons training for professions in health care, should be
vaccinated annually against influenza.\10\ The basis of this
recommendation stems from the spells of illness, hospitalizations, and
mortality associated with the influenza virus. Between 2010 and 2020,
the influenza virus resulted in 12,000 to 52,000 deaths in the United
States each year, depending on the severity of the
strain.11 12 Preliminary estimates from the CDC revealed 35
million cases, 380,000 hospitalizations, and 20,000 deaths linked to
influenza in the United States during the 2019 to 2020 influenza
season.\13\ Persons aged 65 years and older are at higher risk for
experiencing burdens related to severe influenza due to the changes in
immune defenses that come with increasing age.14 15 The CDC
estimates that 70 to 85 percent of seasonal influenza-related deaths
occur among people aged 65 years and older, and 50 to 70 percent of
influenza-related hospitalizations occur among this age group.\16\
Residents of long-term care facilities, who are often of older age,
have greater susceptibility for acquiring influenza due to general
frailty and comorbidities, close contact with other residents,
interactions with visitors, and exposure to staff who rotate between
multiple facilities.17 18 19 Therefore, monitoring and
reporting influenza vaccination rates among HCP is important as HCP are
at risk for acquiring influenza from residents and exposing influenza
to residents.\20\ For example, one early report of HCP influenza
infections during the 2009 H1N1 influenza pandemic estimated 50 percent
of HCP had contracted the influenza virus from patients or coworkers
within the health care setting.\21\
---------------------------------------------------------------------------

\10\ Grohskopf, L.A., Alyanak, E., Broder, K.R., Walter, E.B.,
Fry, A.M., & Jernigan, D.B. (2019). Prevention and Control of
Seasonal Influenza with Vaccines: Recommendations of the Advisory
Committee on Immunization Practices--United States, 2019-20
Influenza Season. MMWR Recomm Rep, 68(No. RR-3), 1-21. <a href="https://www.cdc.gov/mmwr/volumes/68/rr/rr6803a1.htm?s_cid=rr6803a1_w">https://www.cdc.gov/mmwr/volumes/68/rr/rr6803a1.htm?s_cid=rr6803a1_w</a>.
\11\ Centers for Disease Control and Prevention (CDC). (2021).
Disease Burden of Flu. Retrieved from <a href="https://www.cdc.gov/flu/about/burden/index.html?CDC_AA_refVal=https%3A%2F%2Fwww.cdc.gov%2Fflu%2Fabout%2Fdisease%2Fus_flu-related_deaths.htm">https://www.cdc.gov/flu/about/burden/index.html?CDC_AA_refVal=https%3A%2F%2Fwww.cdc.gov%2Fflu%2Fabout%2Fdisease%2Fus_flu-related_deaths.htm</a>.
\12\ Frentzel, E., Jump, R., Archbald-Pannone, L., Nace, D.A.,
Schweon, S.J., Gaur, S., Naqvi, F., Pandya, N., Mercer, W., &
Infection Advisory Subcommittee of AMDA, The Society for Post-Acute
and Long-Term Care Medicine (2020). Recommendations for Mandatory
Influenza Vaccinations for Health Care Personnel From AMDA's
Infection Advisory Subcommittee. Journal of the American Medical
Directors Association, 21(1), 25-28.e2. <a href="https://doi.org/10.1016/j.jamda.2019.11.008">https://doi.org/10.1016/j.jamda.2019.11.008</a>.
\13\ Centers for Disease Control and Prevention (CDC). (2021).
Estimated Flu-Related Illnesses, Medical visits, Hospitalizations,
and Deaths in the United States--2019-2020 Flu Season. Retrieved
from <a href="https://www.cdc.gov/flu/about/burden/2019-2020.html">https://www.cdc.gov/flu/about/burden/2019-2020.html</a>.
\14\ Centers for Disease Control and Prevention (CDC). (2021).
Retrieved from Flu & People 65 Years and Older: <a href="https://www.cdc.gov/flu/highrisk/65over.htm">https://www.cdc.gov/flu/highrisk/65over.htm</a>?CDC_AA_refVal=https%3A%2F%2Fwww.cdc.gov%2Fflu%2Fabout%2Fdi
sease%2F65over.htm.
\15\ Frentzel, E., Jump, R., Archbald-Pannone, L., Nace, D.A.,
Schweon, S.J., Gaur, S., Naqvi, F., Pandya, N., Mercer, W., &
Infection Advisory Subcommittee of AMDA, The Society for Post-Acute
and Long-Term Care Medicine (2020). Recommendations for Mandatory
Influenza Vaccinations for Health Care Personnel From AMDA's
Infection Advisory Subcommittee. Journal of the American Medical
Directors Association, 21(1), 25-28.e2. <a href="https://doi.org/10.1016/j.jamda.2019.11.008">https://doi.org/10.1016/j.jamda.2019.11.008</a>.
\16\ Centers for Disease Control and Prevention (CDC). (2021).
Retrieved from Flu & People 65 Years and Older: <a href="https://www.cdc.gov/flu/highrisk/65over.htm">https://www.cdc.gov/flu/highrisk/65over.htm</a>?CDC_AA_refVal=https%3A%2F%2Fwww.cdc.gov%2Fflu%2Fabout%2Fdi
sease%2F65over.htm.
\17\ Lansbury, L.E., Brown, C.S., &
Nguyen[hyphen]Van[hyphen]Tam, J.S. (2017). Influenza in
long[hyphen]term care facilities. Influenza Other Respir Viruses,
11(5), 356-366. <a href="https://dx.doi.org/10.1111%2Firv.12464">https://dx.doi.org/10.1111%2Firv.12464</a>.
\18\ Pop-Vicas, A., & Gravenstein, S. (2011). Influenza in the
elderly: A mini-review. Gerontology, 57(5), 397-404. <a href="https://doi.org/10.1159/000319033">https://doi.org/10.1159/000319033</a>.
\19\ Strausbaugh, L.J., Sukumar, S.R., & Joseph, C.L. (2003).
Infectious disease outbreaks in nursing homes: an unappreciated
hazard for frail elderly persons. Clinical infectious diseases: an
official publication of the Infectious Diseases Society of America,
36(7), 870-876. <a href="https://doi.org/10.1086/368197">https://doi.org/10.1086/368197</a>.
\20\ Wilde, J.A., McMillan, J.A., Serwint, J., Butta, J.,
O'Riordan, M.A., & Steinhoff, M.C. (1999). Effectiveness of
influenza vaccine in health care professionals: a randomized trial.
JAMA, 281(10), 908-913. <a href="https://doi.org/10.1001/jama.281.10.908">https://doi.org/10.1001/jama.281.10.908</a>.
\21\ Harriman K, Rosenberg J, Robinson S, et al. (2009). Novel
influenza A (H1N1) virus infections among health-care personnel--
United States, April-May 2009. MMWR Morb Mortal Wkly Rep, 58(23),
641-645. Retrieved from <a href="https://www.cdc.gov/mmwr/preview/mmwrhtml/mm5823a2.htm">https://www.cdc.gov/mmwr/preview/mmwrhtml/mm5823a2.htm</a>.
---------------------------------------------------------------------------

Despite the fact that influenza commonly spreads between HCP and
SNF residents, vaccine hesitancy and organizational barriers often
prevent influenza vaccination. For example, although the CDC emphasizes
the importance for HCP to receive the influenza vaccine, the 2017 to
2018 influenza season shows higher influenza vaccination coverage among
HCP working in hospitals (approximately 92 percent) and lower coverage
among those working in long-term care facilities (approximately 68
percent).22 23 HCP working in long-term care facilities,
including SNFs, have expressed concerns about the influenza vaccine's
effectiveness and safety, fearing potential side effects and adverse
reactions.\24\ Other HCP believe healthy individuals are not
susceptible to infection and therefore find vaccination
unnecessary.\25\ In addition, many HCP do not prioritize influenza
vaccination, expressing a lack of time to get vaccinated.\26\ Lower HCP
influenza vaccination in long-term care facilities also stems from
organizational barriers, such as inadequate vaccine record keeping,
frequent staff turnover, an

[[Page 22747]]

absence of influenza vaccine mandates, a lack of communication about
vaccination rates, and a lack of incentives encouraging HCP flu
vaccination.\27\ Given the fact that influenza vaccination coverage
among HCP is typically lower in long-term care settings, such as SNFs,
when compared to other care settings, we believe the proposed measure
has the potential to increase influenza vaccination coverage in SNFs,
promote patient safety, and increase the transparency of quality of
care in the SNF setting.
---------------------------------------------------------------------------

\22\ Black, C.L., Yue, X., Ball, S.W., Fink, R.V., de Perio,
M.A., Laney, A.S., Williams, W.W., Graitcer, S.B., Fiebelkorn, A.P.,
Lu, P.J., & Devlin, R. (2018). Influenza Vaccination Coverage Among
Health Care Personnel--United States, 2017-18 Influenza Season.
MMWR. Morbidity and mortality weekly report, 67(38), 1050-1054.
<a href="https://doi.org/10.15585/mmwr.mm6738a2">https://doi.org/10.15585/mmwr.mm6738a2</a>.
\23\ Jaklevic M.C. (2020). Flu Vaccination Urged During COVID-19
Pandemic. JAMA. 324(10),926-927. <a href="https://doi.org/10.1001/jama.2020.15444">https://doi.org/10.1001/jama.2020.15444</a>.
\24\ Frentzel, E., Jump, R., Archbald-Pannone, L., Nace, D.A.,
Schweon, S.J., Gaur, S., Naqvi, F., Pandya, N., Mercer, W., &
Infection Advisory Subcommittee of AMDA, The Society for Post-Acute
and Long-Term Care Medicine (2020). Recommendations for Mandatory
Influenza Vaccinations for Health Care Personnel From AMDA's
Infection Advisory Subcommittee. Journal of the American Medical
Directors Association, 21(1), 25-28.e2. <a href="https://doi.org/10.1016/j.jamda.2019.11.008">https://doi.org/10.1016/j.jamda.2019.11.008</a>.
\25\ Kenny, E., McNamara, [Aacute]., Noone, C., & Byrne, M.
(2020). Barriers to seasonal influenza vaccine uptake among health
care workers in long-term care facilities: A cross-sectional
analysis. British journal of health psychology, 25(3), 519-539.
<a href="https://doi.org/10.1111/bjhp.12419">https://doi.org/10.1111/bjhp.12419</a>.
\26\ Kose, S., Mandiracioglu, A., Sahin, S., Kaynar, T., Karbus,
O., & Ozbel, Y. (2020). Vaccine hesitancy of the COVID-19 by health
care personnel. Int J Clin Pract, 75(5), e13917. <a href="https://doi.org/10.1111/ijcp.13917">https://doi.org/10.1111/ijcp.13917</a>.
\27\ Ofstead, C.L., Amelang, M.R., Wetzler, H.P., & Tan, L.
(2017). Moving the needle on nursing staff influenza vaccination in
long-term care: Results of an evidence-based intervention. Vaccine,
35(18), 2390-2395. <a href="https://doi.org/10.1016/j.vaccine.2017.03.041">https://doi.org/10.1016/j.vaccine.2017.03.041</a>.
---------------------------------------------------------------------------

Although concerns about vaccine effectiveness often prevent some
HCP from getting the influenza vaccine, the CDC notes that higher
influenza vaccination rates reduce the risk of influenza-related
illness between 40 to 60 percent among the overall population during
seasons when the circulating influenza virus is well-matched to viruses
used to make influenza vaccines.\28\ During the 2019 to 2020 influenza
season, vaccinations prevented 7.5 million influenza-related illnesses,
105,000 influenza-related hospitalizations, and 6,300 deaths.\29\
Additionally, among adults with influenza-associated hospitalization,
influenza vaccination is also associated with a 26 percent lower risk
of intensive care unit admission, and 31 percent lower risk of
influenza-related deaths compared to individuals who were unvaccinated
against influenza.\30\ Several cluster-randomized trials comparing HCP
influenza vaccination groups to control groups demonstrate reductions
in long-term care resident mortality rates as related to HCP influenza
vaccination.31 32 33 34 To reduce vaccine hesitancy and
organizational barriers to influenza vaccination, several strategies
can be used to increase influenza vaccination among HCP. These include
availability of on-site influenza vaccinations and educational
campaigns about influenza risks and vaccination
benefits.35 36 37
---------------------------------------------------------------------------

\28\ Centers for Disease Control and Prevention (CDC). (2021).
Retrieved from Vaccine Effectiveness: How Well Do Flu Vaccines
Work?: <a href="https://www.cdc.gov/flu/vaccines-work/vaccineeffect.htm">https://www.cdc.gov/flu/vaccines-work/vaccineeffect.htm</a>.
\29\ Centers for Disease Control and Prevention (CDC). (2021).
Retrieved from Vaccine Effectiveness: How Well Do Flu Vaccines
Work?: <a href="https://www.cdc.gov/flu/vaccines-work/vaccineeffect.htm">https://www.cdc.gov/flu/vaccines-work/vaccineeffect.htm</a>.
\30\ Ferdinands, J.M., Thompson, M.G., Blanton, L., Spencer, S.,
Grant, L., & Fry, A.M. (2021). Does influenza vaccination attenuate
the severity of breakthrough infections? A narrative review and
recommendations for further research. Vaccine, 39(28), 3678-3695.
<a href="https://doi.org/10.1016/j.vaccine.2021.05.011">https://doi.org/10.1016/j.vaccine.2021.05.011</a>.
\31\ Carman, W.F., Elder, A.G., Wallace, L.A., McAulay, K.,
Walker, A., Murray, G.D., & Stott, D.J. (2000). Effects of influenza
vaccination of health-care workers on mortality of elderly people in
long-term care: a randomised controlled trial. Lancet (London,
England), 355(9198), 93-97. <a href="https://doi.org/10.1016/S0140-6736">https://doi.org/10.1016/S0140-6736</a>(99)05190-9.
\32\ Hayward, A.C., Harling, R., Wetten, S., Johnson, A.M.,
Munro, S., Smedley, J., Murad, S., & Watson, J.M. (2006).
Effectiveness of an influenza vaccine programme for care home staff
to prevent death, morbidity, and health service use among residents:
cluster randomised controlled trial. BMJ (Clinical research ed.),
333(7581), 1241. <a href="https://doi.org/10.1136/bmj.39010.581354.55">https://doi.org/10.1136/bmj.39010.581354.55</a>.
\33\ Lemaitre, M., Meret, T., Rothan-Tondeur, M., Belmin, J.,
Lejonc, J.L., Luquel, L., Piette, F., Salom, M., Verny, M., Vetel,
J.M., Veyssier, P., & Carrat, F. (2009). Effect of influenza
vaccination of nursing home staff on mortality of residents: a
cluster-randomized trial. Journal of the American Geriatrics
Society, 57(9), 1580-1586. <a href="https://doi.org/10.1111/j.1532-5415.2009.02402.x">https://doi.org/10.1111/j.1532-5415.2009.02402.x</a>.
\34\ Potter, J., Stott, D.J., Roberts, M.A., Elder, A.G.,
O'Donnell, B., Knight, P.V., & Carman, W.F. (1997). Influenza
vaccination of health care workers in long-term-care hospitals
reduces the mortality of elderly patients. The Journal of infectious
diseases, 175(1), 1-6. <a href="https://doi.org/10.1093/infdis/175.1.1">https://doi.org/10.1093/infdis/175.1.1</a>.
\35\ Bechini, A., Lorini, C., Zanobini, P., Mand[ograve]
Tacconi, F., Boccalini, S., Grazzini, M., Bonanni, P., & Bonaccorsi,
G. (2020). Utility of Healthcare System-Based Interventions in
Improving the Uptake of Influenza Vaccination in Healthcare Workers
at Long-Term Care Facilities: A Systematic Review. Vaccines, 8(2),
165. <a href="https://doi.org/10.3390/vaccines8020165">https://doi.org/10.3390/vaccines8020165</a>.
\36\ Ofstead, C.L., Amelang, M.R., Wetzler, H.P., & Tan, L.
(2017). Moving the needle on nursing staff influenza vaccination in
long-term care: Results of an evidence-based intervention. Vaccine,
35(18), 2390-2395. <a href="https://doi.org/10.1016/j.vaccine.2017.03.041">https://doi.org/10.1016/j.vaccine.2017.03.041</a>.
\37\ Yue, X., Black, C., Ball, S., Donahue, S., de Perio, M.A.,
Laney, A.S., & Greby, S. (2019). Workplace Interventions and
Vaccination-Related Attitudes Associated With Influenza Vaccination
Coverage Among Healthcare Personnel Working in Long-Term Care
Facilities, 2015-2016 Influenza Season. Journal of the American
Medical Directors Association, 20(6), 718-724. <a href="https://doi.org/10.1016/j.jamda.2018.11.029">https://doi.org/10.1016/j.jamda.2018.11.029</a>.
---------------------------------------------------------------------------

Addressing HCP influenza vaccination in SNFs is particularly
important as vulnerable populations often reside in SNFs. Vulnerable
populations are less likely to receive the influenza vaccine, and thus,
are susceptible to contracting the virus. For example, not only are
Black residents more likely to receive care from facilities with lower
overall influenza vaccination rates, but Black residents are also less
likely to be offered and receive influenza vaccinations in comparison
to White residents.38 39 40 41 Racial and ethnic disparities
in influenza vaccination, specifically among Black and Hispanic
populations, are also higher among short-stay residents receiving care
for less than 100 days in the nursing home.\42\ Additionally, Medicare
fee-for-service beneficiaries of Black, Hispanic, rural, and lower-
income populations are less likely to receive inactivated influenza
vaccines, and non-White beneficiaries are generally less likely to
receive high-dose influenza vaccines in comparison to White
beneficiaries.43 44 45 Therefore, the proposed measure has
the potential to increase influenza vaccination coverage of HCP in
SNFs, as well as prevent the spread of the influenza virus to
vulnerable populations who are less likely to receive influenza
vaccinations.
---------------------------------------------------------------------------

\38\ Cai, S., Feng, Z., Fennell, M.L., & Mor, V. (2011). Despite
small improvement, black nursing home residents remain less likely
than whites to receive flu vaccine. Health affairs (Project Hope),
30(10), 1939-1946. <a href="https://doi.org/10.1377/hlthaff.2011.0029">https://doi.org/10.1377/hlthaff.2011.0029</a>.
\39\ Luo, H., Zhang, X., Cook, B., Wu, B., & Wilson, M.R.
(2014). Racial/Ethnic Disparities in Preventive Care Practice Among
U.S. Nursing Home Residents. Journal of Aging and Health, 26(4),
519-539. <a href="https://doi.org/10.1177/0898264314524436">https://doi.org/10.1177/0898264314524436</a>.
\40\ Mauldin, R.L., Sledge, S.L., Kinney, E.K., Herrera, S., &
Lee, K. (2021). Addressing Systemic Factors Related to Racial and
Ethnic Disparities among Older Adults in Long-Term Care Facilities.
IntechOpen.
\41\ Travers, J.L., Dick, A.W., & Stone, P.W. (2018). Racial/
Ethnic Differences in Receipt of Influenza and Pneumococcal
Vaccination among Long-Stay Nursing Home Residents. Health services
research, 53(4), 2203-2226. <a href="https://doi.org/10.1111/1475-6773.12759">https://doi.org/10.1111/1475-6773.12759</a>.
\42\ Riester, M.R., Bosco, E., Bardenheier, B.H., Moyo, P.,
Baier, R.R., Eliot, M., Silva, J.B., Gravenstein, S., van Aalst, R.,
Chit, A., Loiacono, M.M., & Zullo, A.R. (2021). Decomposing Racial
and Ethnic Disparities in Nursing Home Influenza Vaccination.
Journal of the American Medical Directors Association, 22(6), 1271-
1278.e3. <a href="https://doi.org/10.1016/j.jamda.2021.03.003">https://doi.org/10.1016/j.jamda.2021.03.003</a>.
\43\ Hall, L.L., Xu, L., Mahmud, S.M., Puckrein, G.A., Thommes,
E.W., & Chit, A. (2020). A Map of Racial and Ethnic Disparities in
Influenza Vaccine Uptake in the Medicare Fee-for-Service Program.
Advances in therapy, 37(5), 2224-2235. <a href="https://doi.org/10.1007/s12325-020-01324-y">https://doi.org/10.1007/s12325-020-01324-y</a>.
\44\ Inactivated vaccines use the killed version of the germ
that causes a disease. Inactivated vaccines usually don't provide
immunity (protection) that is as strong as the live vaccines. For
more information regarding inactivated vaccines we refer readers to
the following web page: <a href="https://hhs.gov/immunization/basics/types/index.html">https://hhs.gov/immunization/basics/types/index.html</a>.
\45\ High dose flu vaccines contain four times the amount of
antigen (the inactivated virus that promotes a protective immune
response) as a regular flu shot. It is associated with a stronger
immune response following vaccination. For more information
regarding high dose flu vaccines, we refer readers to the following
web page: <a href="https://www.cdc.gov/flu/highrisk/65over.htm">https://www.cdc.gov/flu/highrisk/65over.htm</a>.
---------------------------------------------------------------------------

The COVID-19 pandemic has exposed the importance of implementing
infection prevention strategies, including the promotion of HCP
influenza vaccination. Activity of the influenza virus has been lower
during the COVID-19 pandemic as several strategies to reduce the spread
of COVID-19 have also reduced the spread of influenza, including mask
mandates, social distancing, and increased hand hygiene.\46\ However,
even though more

[[Page 22748]]

people are receiving COVID-19 vaccines, it is still important to
encourage annual HCP influenza vaccination to prevent health care
systems from getting overwhelmed by the co-circulation of COVID-19 and
influenza viruses. A 2020 literature search revealed several studies in
which those with severe cases of COVID-19, requiring hospitalization,
were less likely to be vaccinated against influenza.\47\ HCP
vaccinations against influenza may prevent the spread of illness
between HCP and residents, thus reducing resident morbidities
associated with influenza and pressure on already stressed health care
systems. In fact, several thousand nursing homes voluntarily reported
weekly influenza vaccination coverage through an NHSN module based on
the NQF #0431 measure during the overlapping 2020 to 2021 influenza
season and COVID-19 pandemic. Even after the COVID-19 pandemic ends,
promoting HCP influenza vaccination is important in preventing
morbidity and mortality associated with influenza.
---------------------------------------------------------------------------

\46\ Wang, X., Kulkarni, D., Dozier, M., Hartnup, K., Paget, J.,
Campbell, H., Nair, H., & Usher Network for COVID-19 Evidence
Reviews (UNCOVER) group (2020). Influenza vaccination strategies for
2020-21 in the context of COVID-19. Journal of global health, 10(2),
021102. <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7719353/">https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7719353/</a>.
\47\ Del Riccio, M., Lorini, C., Bonaccorsi, G., Paget, J., &
Caini, S. (2020). The Association between Influenza Vaccination and
the Risk of SARS-CoV-2 Infection, Severe Illness, and Death: A
Systematic Review of the Literature. International journal of
environmental research and public health, 17(21), 7870. <a href="https://doi.org/10.3390/ijerph17217870">https://doi.org/10.3390/ijerph17217870</a>.
---------------------------------------------------------------------------

Variation in influenza vaccination coverage rates indicate the
proposed measure's usability and use. A CDC analysis during the 2020 to
2021 influenza season revealed that among 16,535 active, CMS-certified
nursing homes, 17.3 percent voluntarily submitted data for the proposed
measure through the National Healthcare Safety Network (NHSN). Average
staff influenza vaccination coverage was approximately 64 percent,
ranging from 0.3 percent to 100 percent with an interquartile range of
40 to 93.9 percent. Variation in influenza vaccination coverage rates
by facility demonstrates the utility of the measure for resident choice
of facility. Variation in influenza vaccination rates by type of HCP
demonstrates the utility of the proposed measure for targeted quality
improvement efforts.
For these reasons, we propose to adopt the CDC developed Influenza
Vaccination Coverage among Healthcare Personnel (NQF #0431) measure for
the SNF QRP, as collected through the CDC's NHSN, to report the
percentage of HCP who receive the influenza vaccine. We believe this
measure will encourage HCP to receive the influenza vaccine, resulting
in fewer cases, less hospitalizations, and lower mortality associated
with the virus.
b. Stakeholder Input and Pilot Testing
In the development and specification of this measure, a transparent
process was employed to seek input from stakeholders and national
experts and engage in a process that allows for pre-rulemaking input in
accordance with section 1890A of the Act. To meet this requirement,
opportunities were provided for stakeholder input by a Delphi panel and
Steering Committee through the measure's pilot testing. The measure's
pilot testing assessed reliability and validity among 234 facilities
and five facility types (that is, long-term care facilities, acute care
hospitals, ambulatory surgery centers, physician practices, and
dialysis centers) across four jurisdictions (that is, California, New
Mexico, New York City, and western Pennsylvania) between 2010 and
2011.48 49
---------------------------------------------------------------------------

\48\ Libby T.E., Lindley M.C., Lorick S.A., MacCannell T., Lee
S.J., Smith C, Geevarughese A., Makvandi M., Nace D.A., Ahmed F.
(2013). Reliability and validity of a standardized measure of
influenza vaccination coverage among healthcare personnel. Infect
Control Hosp Epidemiol, 34(4),335-45. <a href="https://doi.org/10.1086/669859">https://doi.org/10.1086/669859</a>.
\49\ The Libby et al. (2013) article (preceding footnote) is
referenced throughout the entirety of section VI.C.1.b. of this
rule.
---------------------------------------------------------------------------

Two methods were used to conduct reliability testing, including
interrater reliability testing and the use of case studies. Interrater
reliability was assessed among 96 facilities, including 19 long-term
care facilities, by comparing agreement between two raters: Facility
staff and project staff. Project staff reviewed individual-level
records from randomly selected facilities to assess agreement with how
facility staff classified HCP into numerator and denominator
categories. For more information regarding numerator and denominator
definitions, refer to section VI.C.1.e. of this proposed rule.
Interrater reliability results demonstrated high adjusted agreement
between facility and project staff for numerator data (91 percent) and
denominator data (96 percent). Most numerator disagreements resulted
from health care facilities reporting verbal declinations in the
``declined vaccination'' numerator rather than categorizing verbal
declinations as ``missing/unknown'' as there was no written
documentation of the declination. There was also numerator disagreement
related to contraindications as HCP did not properly cite true medical
contraindications. Adhering to true medical contraindications and
tracking declinations of the influenza vaccine among HCP should
additionally improve reliability.
Case studies were also used to assess reliability. Facilities
received a series of 23 vignettes, in which they were instructed to
select appropriate numerator and denominator categories for the
hypothetical cases described in each vignette. Most numerator and
denominator elements were categorized correctly. For example, 95.6
percent of facility staff correctly categorized employees that were
vaccinated at the facility, 88.6 percent correctly categorized
employees vaccinated elsewhere, etc.\50\ However, problematic
denominator elements included poor facility understanding of how to
classify physician-owners of health care facilities who work part-time
and physicians who were credentialed by a facility but had not admitted
patients in the past 12 months. Problematic numerator elements were
related to confusion about reporting persistent deferrals of
vaccination and verbal vaccine declinations for non-medical reasons.
---------------------------------------------------------------------------

\50\ For a full list of case study categorization results,
please refer to the following study: Libby T.E., Lindley M.C.,
Lorick S.A., MacCannell T., Lee S.J., Smith C., Geevarughese A.,
Makvandi M., Nace D.A., Ahmed F. (2013). Reliability and validity of
a standardized measure of influenza vaccination coverage among
healthcare personnel. Infect Control Hosp Epidemiol, 34(4),335-45.
<a href="https://doi.org/10.1086/669859">https://doi.org/10.1086/669859</a>.
---------------------------------------------------------------------------

Two methods were also used for validity testing: Convergent
validity assessments and face validity assessment. Convergent validity
examined the association between the number of evidence-based
strategies used by a health care facility to promote influenza
vaccination and the facility's reported vaccination rate among each HCP
denominator group. The association between employee vaccination rates
and the number of strategies used was borderline significant. The
association between credentialed non-employee vaccination rates and the
number of strategies used was significant, and the association between
other non-employee vaccination rates and the number of strategies used
was also significant, demonstrating convergent validity.
Face validity was assessed through a Delphi panel, which convened
in June 2011 and provided stakeholder input on the proposed measure.
The Delphi panel, comprised of nine experts in influenza vaccination
measurement and quality improvement from several public and private
organizations, rated elements of the proposed measure using a Likert
scale. The Delphi panel

[[Page 22749]]

discussed pilot testing results from the first round of ratings during
a one-hour moderated telephone conference. After the conference
concluded, panelists individually rated a revised set of elements.
Ultimately, the Delphi panel reached a consensus that the majority of
the proposed measure's numerator definitions had strong face validity.
However, the panel raised concerns regarding the accuracy of self-
reported data and deemed validity lowest for denominator categories of
credentialed and other nonemployees of the facility.
After the conclusion of measure testing, the proposed measure's
specifications were revised in alignment with the Delphi panel's
ratings and with guidance from a Steering Committee. The CDC-convened
Steering Committee was comprised of representatives from several
institutions, including CMS, the Joint Commission, the Federation of
American Hospitals, the American Osteopathic Association, the American
Medical Association, and others. To address concerns raised through
pilot testing and to reduce institutional barriers to reporting,
denominator specifications were revised to include a more limited
number of HCP among whom vaccination could be measured with greater
reliability and accuracy: Employees, licensed independent
practitioners, and adult students/trainees and volunteers. The measure
was also revised to require vaccinations received outside of the
facility to be documented, but allow for self-report of declinations
and medical contraindications. Verbal declinations were assigned to the
``declined'' numerator category, and an ``unknown'' category was added
to give facilities actionable data on unvaccinated HCP who may not have
purposefully declined. For more information regarding pilot testing
results and measure input from the Delphi panel and Steering Committee,
refer to the article published in the Infection Control & Hospital
Epidemiology journal by the measure developer.\51\
---------------------------------------------------------------------------

\51\ Libby T.E,. Lindley M.C., Lorick S.A., MacCannell T, Lee
S.J., Smith C., Geevarughese A., Makvandi M., Nace D.A., Ahmed F.
(2013). Reliability and validity of a standardized measure of
influenza vaccination coverage among healthcare personnel. Infect
Control Hosp Epidemiol, 34(4),335-45. <a href="https://doi.org/10.1086/669859">https://doi.org/10.1086/669859</a>.
---------------------------------------------------------------------------

c. Measure Applications Partnership (MAP) Review
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
through the Federal rulemaking process for use in Medicare programs.
This allows multi-stakeholder groups to provide recommendations to the
Secretary on the measures included in the list.
We included the Influenza Vaccination Coverage among HCP measure
under the SNF QRP Program in the publicly available ``List of Measures
Under Consideration for December 1, 2021'' (MUC List).\52\ Shortly
after, several National Quality Forum (NQF)-convened Measures
Applications Partnership (MAP) workgroups met virtually to provide
input on the proposed measure. First, the MAP Rural Health Workgroup
convened on December 8, 2021. Members generally agreed that the
proposed measure would be suitable for use by rural providers within
the SNF QRP program, noting the measure's rural relevance. Likewise,
the MAP Health Equity workgroup met on December 9, 2021, in which the
majority of voting members agreed that the proposed measure has
potential for decreasing health disparities. The MAP Post-Acute Care/
Long-Term Care (PAC/LTC) workgroup met on December 16, 2021, in which
the majority of voting workgroup members supported rulemaking of the
proposed measure. Finally, the MAP Coordinating Committee convened on
January 19, 2022, in which the committee agreed with the MAP's
preliminary measure recommendation of support for rulemaking.
---------------------------------------------------------------------------

\52\ Centers for Medicare and Medicaid Services. (2021). List of
Measures Under Consideration for December 1, 2021. <a href="http://CMS.gov">CMS.gov</a>. <a href="https://www.cms.gov/files/document/measures-under-consideration-list-2020-report.pdf">https://www.cms.gov/files/document/measures-under-consideration-list-2020-report.pdf</a>.
---------------------------------------------------------------------------

In addition to receiving feedback from MAP workgroup and committee
members, NQF received four comments by industry stakeholders during the
proposed measure's MAP pre-rulemaking process. Commenters were
generally supportive of the measure as SNF QRP adoption would promote
measure interoperability, encourage vaccination, and likely decrease
the spread of infection. One commenter was not supportive of the
measure due to burdens of NHSN data submission.
Overall, the MAP offered support for rulemaking, noting that the
measure aligns with the IRF and LTCH PAC QRPs and adds value to the
current SNF QRP measure set since influenza vaccination among HCP is
not currently addressed within the SNF QRP program. The MAP noted the
importance of vaccination coverage among HCP as an actionable strategy
that can decrease viral transmission, morbidity, and mortality within
SNFs. The final MAP report is available at <a href="https://www.qualityforum.org/Publications/2022/03/MAP_2021-2022_Considerations_for_Implementing_Measures_Final_Report_-_Clinicians,_Hospitals,_and_PAC-LTC.aspx">https://www.qualityforum.org/Publications/2022/03/MAP_2021-2022_Considerations_for_Implementing_Measures_Final_Report_-_Clinicians,_Hospitals,_and_PAC-LTC.aspx</a>.
d. 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 the entity with
a contract under section 1890(a) of the Act, currently the NQF. In the
case of a specified area or medical topic determined appropriate by the
Secretary for which a feasible and practical measure has not been
endorsed, section 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
consensus organization identified by the Secretary.
The proposed Influenza Vaccination Coverage among HCP measure
initially received NQF endorsement in 2008 as NQF #0431. Measure
endorsement was renewed in 2017, and the measure is due for maintenance
in the spring 2022 cycle. The measure was originally tested in nursing
homes and has been endorsed by NQF for use in nursing home settings
since the measure was first endorsed. No additional modifications were
made to the proposed measure for the spring 2022 measure maintenance
cycle, but as noted in section VI.C.1.a. of this proposed rule that
several thousand nursing homes voluntarily reported weekly influenza
vaccination coverage through an NHSN module based on the NQF #0431
measure during the overlapping 2020 to 2021 influenza season and COVID-
19 pandemic. The measure is currently used in several of our programs,
including the Hospital Inpatient and Prospective Payment System (PPS)-
Exempt Cancer Hospital QRPs. Among PAC programs, the proposed measure
is also reported in the IRF and LTCH QRPs as adopted in the FY 2014 IRF
PPS final rule (78 FR 47905 through 47906) and the FY 2013 Inpatient
Prospective Payment System (IPPS)/LTCH PPS final rule (77 FR 53630
through 53631), respectively.
After review of the NQF's consensus-endorsed measures, we were
unable to identify any NQF-endorsed measures for SNFs focused on
capturing influenza vaccinations among HCP. For example, although the
Percent of Residents or Patients Who Were Assessed and Appropriately
Given the Seasonal Influenza Vaccine (Short Stay) (NQF #0680) and the
Percent of Residents

[[Page 22750]]

Assessed and Appropriately Given the Seasonal Influenza Vaccine (Long
Stay) (NQF #0681) measures are both NQF-endorsed and assess rates of
influenza vaccination, they assess vaccination rates among residents in
the nursing home rather than HCP in the SNF. Additionally, the Percent
of Programs of All-Inclusive Care for the Elderly (PACE) Healthcare
Personnel with Influenza Immunization measure resembles the proposed
measure since it assesses influenza vaccination among HCP; however, it
is not NQF endorsed and is not specific to the SNF setting.
Therefore, after consideration of other available measures, we find
the NQF endorsed Influenza Vaccination Coverage among HCP measure
appropriate for the SNF QRP, and are proposing the measure beginning
with the FY 2025 SNF QRP. Application of the Influenza Vaccination
Coverage among HCP measure within the SNF QRP promotes measure
harmonization across quality reporting programs that also report this
measure. This proposed measure has the potential to generate actionable
data on vaccination rates that can be used to target quality
improvement among SNF providers.
e. Quality Measure Calculation
The Influenza Vaccination Coverage among HCP measure is a process
measure developed by the CDC to track influenza vaccination coverage
among HCP in facilities such as SNFs. The measure reports on the
percentage of HCP who receive influenza vaccination. The term
``healthcare personnel'' refers to all paid and unpaid persons working
in a health care setting, contractual staff not employed by the health
care facility, and persons not directly involved in patient care but
potentially exposed to infectious agents that can be transmitted to and
from HCP. Since the proposed measure is a process measure, rather than
an outcome measure, it does not require risk-adjustment.
The proposed measure's denominator is the number of HCP who are
physically present in the health care facility for at least 1 working
day between October 1 and March 31 of the following year, regardless of
clinical responsibility or patient contact. The proposed measure's
reporting period is October 1 through March 31; this reporting period
refers to the proposed measure's denominator only. The denominator
would be calculated separately for three required categories:
Employees, meaning all persons who receive a direct paycheck from the
reporting facility (that is, on the SNF's payroll); Licensed
independent practitioners,\53\ such as physicians, advanced practice
nurses, and physician assistants who are affiliated with the reporting
facility, who do not receive a direct paycheck from the reporting
facility; and Adult students/trainees and volunteers who do not receive
a direct paycheck from the reporting facility. A denominator can be
calculated for an optional category as well: Other contract personnel,
defined as persons providing care, treatment, or services at the
facility through a contract who do not fall into any of the three
required denominator categories.
---------------------------------------------------------------------------

\53\ Refer to the proposed measure's specifications in The
National Healthcare Safety Network (NSHN) Manual Healthcare
Personnel Safety Component Protocol--Healthcare Personnel
Vaccination Module: Influenza Vaccination Summary linked at <a href="https://www.cdc.gov/nhsn/pdfs/hps-manual/vaccination/hps-flu-vaccine-protocol.pdf">https://www.cdc.gov/nhsn/pdfs/hps-manual/vaccination/hps-flu-vaccine-protocol.pdf</a> for an exhaustive list of those included in the
licensed independent practitioners definition.
---------------------------------------------------------------------------

The proposed measure's numerator consists of all HCP included in
the denominator population who received an influenza vaccine any time
from when it first became available (such as August or September)
through March 31 of the following year and who fall into one of the
following categories: (a) Received an influenza vaccination
administered at the health care facility; (b) reported in writing
(paper or electronic) or provided documentation that an influenza
vaccination was received elsewhere, (c) were determined to have a
medical contraindication/condition of severe allergic reaction to eggs
or other component(s) of the vaccine, or a history of Guillain-Barre
(GBS) within 6 weeks after a previous influenza vaccination; (d) were
offered but declined the influenza vaccination; or (e) had an unknown
vaccination status or did not meet any of the definitions of the other
numerator categories (a through d). As described in the FY 2014 IRF PPS
final rule, measure numerator data is required based on data collected
from October 1st or whenever the vaccine becomes available.\54\
Therefore, if the vaccine is available prior to October 1st, any
vaccine given before October 1st is credited towards vaccination
coverage. Likewise, if the vaccine becomes available after October 1st,
the vaccination counts are to begin as soon as possible after October
1st.
---------------------------------------------------------------------------

\54\ 78 FR 47906.
---------------------------------------------------------------------------

We propose that SNFs submit data for the measure through the CDC/
NHSN data collection and submission framework.\55\ In alignment with
the data submission frameworks utilized for this measure in the IRF and
LTCH QRPs, SNFs would use the HCP influenza data reporting module in
the NHSN HPS Component and complete two forms. SNFs would complete the
first form (CDC 57.203) to i

[…truncated; see source link]

View on FederalRegister.gov →Plain-text source

Indexed from Federal Register on April 15, 2022.

This is legal information, not legal advice. Laws vary by jurisdiction and change frequently. Always verify current law with official sources and consult a licensed attorney in your jurisdiction for advice on your specific situation.