Medicare Program; FY 2024 Inpatient Psychiatric Facilities Prospective Payment System-Rate Update, 21238-21314 [2023-07122]
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Federal Register / Vol. 88, No. 68 / Monday, April 10, 2023 / Proposed Rules
DEPARTMENT OF HEALTH AND
HUMAN SERVICES
Centers for Medicare & Medicaid
Services
42 CFR Part 412
[CMS–1783–P]
RIN 0938–AV06
Medicare Program; FY 2024 Inpatient
Psychiatric Facilities Prospective
Payment System—Rate Update
Centers for Medicare &
Medicaid Services (CMS), Department
of Health and Human Services (HHS).
ACTION: Proposed rule.
AGENCY:
This proposed rule would
update the prospective payment rates,
the outlier threshold, and the wage
index for Medicare inpatient hospital
services provided by Inpatient
Psychiatric Facilities (IPF), which
include psychiatric hospitals and
excluded psychiatric units of an acute
care hospital or critical access hospital.
These proposed changes would be
effective for IPF discharges occurring
during the Fiscal Year (FY) beginning
October 1, 2023 through September 30,
2024 (FY 2024). In addition, this
proposed rule discusses proposals on
quality measures and reporting
requirements under the Inpatient
Psychiatric Facilities Quality Reporting
(IPFQR) Program with proposed changes
beginning with the FY 2024 payment
determination through changes
beginning with the FY 2028 payment
determination.
SUMMARY:
To be assured consideration,
comments must be received at one of
the addresses provided below, by June
5, 2023.
ADDRESSES: In commenting, please refer
to file code CMS–1783–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 https://www.regulations.gov. Follow
the ‘‘Submit a comment’’ instructions.
2. By regular mail. You may mail
written comments to the following
address ONLY: Centers for Medicare &
Medicaid Services, Department of
Health and Human Services, Attention:
CMS–1783–P, P.O. Box 8010, Baltimore,
MD 21244–8010.
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
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DATES:
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following address ONLY: Centers for
Medicare & Medicaid Services,
Department of Health and Human
Services, Attention: CMS–1783–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:
Mollie Knight (410) 786–7948 or Bridget
Dickensheets (410) 786–8670, for
information regarding the market basket
update or the labor-related share.
Nick Brock (410) 786–5148 or Theresa
Bean (410) 786–2287, for information
regarding the regulatory impact
analysis.
Lauren Lowenstein-Turner, (410)
786–4507, for information regarding the
inpatient psychiatric facilities quality
reporting 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: https://
www.regulations.gov. Follow the search
instructions on that website to view
public comments. CMS will not post on
Regulations.gov public comments that
make threats to individuals or
institutions or suggest that the
individual will take actions to harm the
individual. CMS continues to encourage
individuals not to submit duplicative
comments. We will post acceptable
comments from multiple unique
commenters even if the content is
identical or nearly identical to other
comments.
Availability of Certain Tables
Exclusively Through the Internet on the
CMS Website
Addendum A to this proposed rule
summarizes the FY 2024 IPF PPS
payment rates, outlier threshold, cost of
living adjustment factors (COLA) for
Alaska and Hawaii, national and upper
limit cost-to-charge ratios, and
adjustment factors. In addition, the B
Addenda to this proposed rule shows
the complete listing of ICD–10 Clinical
Modification (CM) and Procedure
Coding System (PCS) codes, the FY
2024 IPF PPS comorbidity adjustment,
and electroconvulsive therapy (ECT)
procedure codes. The A and B Addenda
are available online at: https://
www.cms.gov/Medicare/Medicare-Fee-
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for-Service-Payment/
InpatientPsychFacilPPS/tools.html.
Tables setting forth the FY 2024 Wage
Index for Urban Areas Based on Core
Based Statistical Area (CBSA) Labor
Market Areas and the FY 2024 Wage
Index Based on CBSA Labor Market
Areas for Rural Areas are available
exclusively through the internet, on the
CMS website at https://www.cms.gov/
Medicare/Medicare-Fee-for-ServicePayment/IPFPPS/WageIndex.html.
I. Executive Summary
A. Purpose
This proposed rule would rebase and
revise the market basket for the
Inpatient Psychiatric Facility
Prospective Payment System (IPF PPS)
to reflect a 2021 base year, and update
the prospective payment rates, the
outlier threshold, and the wage index
for Medicare inpatient hospital services
provided by Inpatient Psychiatric
Facilities (IPFs) for discharges occurring
during Fiscal Year (FY) 2024, (beginning
October 1, 2023 through September 30,
2024). This rule also includes a proposal
to modify our regulations to make it
easier for hospitals to open new
excluded psychiatric units paid under
the IPF PPS. In addition, this proposed
rule includes a request for information
to inform revisions to the IPF PPS
adjustments for FY 2025, as required by
the Consolidated Appropriations Act,
2023 (hereafter referred to as CAA,
2023) (Pub. L. 116–260). Lastly, this
proposed rule discusses proposals on
quality measures and reporting
requirements under the Inpatient
Psychiatric Facilities Quality Reporting
(IPFQR) Program.
B. Summary of the Major Provisions
1. Inpatient Psychiatric Facilities
Prospective Payment System (IPF PPS)
For the IPF PPS, we propose to:
• Modify the regulations to allow the
status of a hospital psychiatric unit to be
changed from not excluded to excluded,
and therefore paid under the IPF PPS at
any time during a cost reporting period
if certain requirements are met.
• Solicit comments to inform
revisions to IPF PPS payments for FY
2025, as required by the CAA, 2023.
• Revise and rebase the IPF market
basket to reflect a 2021 base year.
• Make technical rate setting updates:
The IPF PPS payment rates would be
adjusted annually for inflation, as well
as statutory and other policy factors.
This rule proposes to update:
++ The IPF PPS Federal per diem base
rate from $865.63 to $892.58.
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++ The IPF PPS Federal per diem base
rate for providers who failed to report
quality data to $875.25.
++ The electroconvulsive therapy
(ECT) payment per treatment from
$372.67 to $384.27.
++ The ECT payment per treatment
for providers who failed to report
quality data to $376.81.
++ The labor-related share from 77.4
percent to 78.5 percent.
++ The wage index budget-neutrality
factor to 1.0011.
++ The fixed dollar loss threshold
amount from $24,630 to $34,750 to
maintain estimated outlier payments at
2 percent of total estimated aggregate
IPF PPS payments.
2. Inpatient Psychiatric Facilities
Quality Reporting (IPFQR) Program
For the IPFQR Program, we propose
to:
• Adopt the Facility Commitment to
Health Equity measure beginning with
the FY 2026 payment determination;
• Adopt the Screening for Social
Drivers of Health measure beginning
with voluntary reporting of CY 2024
data and beginning with required
reporting of CY 2025 data for the FY
2027 payment determination;
• Adopt the Screen Positive Rate for
Social Drivers of Health measure
beginning with voluntary reporting of
CY 2024 data and beginning with
required reporting of CY 2025 data for
the FY 2027 payment determination;
• Adopt the Psychiatric Inpatient
Experience (PIX) survey to measure
patient experience of care in the IPF
setting beginning with voluntary
reporting of CY 2025 data and beginning
with required reporting of CY 2026 data
for the FY 2028 payment determination;
• Modify the Coronavirus disease
2019 (COVID–19) Vaccination Coverage
Among Health Care Personnel (HCP)
measure to apply the Centers for Disease
Control and Prevention’s (CDC’s)
definition of ‘‘up-to-date’’ for COVID–19
vaccination, incorporating booster
doses, beginning with fourth quarter CY
2023 data for FY 2025 payment
determination and, following this first
single-quarter reporting period,
reporting for full calendar year
Provision description
FY 2024 IPF PPS payment
update.
FY 2024 IPFQR Program
update.
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C. Summary of Impacts
The overall economic impact of this proposed rule is an estimated $55 million in increased payments to IPFs during FY 2024.
The overall economic impact of the IPFQR Program proposals in this proposed rule is an estimated decrease of
505,247 hours in information collection burden resulting in a savings of $12,431,700.
A. Overview of the Legislative
Requirements of the IPF PPS
Section 124 of the Medicare,
Medicaid, and State Children’s Health
Insurance Program Balanced Budget
Refinement Act of 1999 (BBRA) (Pub. L.
106–113) required the establishment
and implementation of an IPF PPS.
Specifically, section 124 of the BBRA
mandated that the Secretary of the
Department of Health and Human
Services (the Secretary) develop a per
diem payment perspective system (PPS)
for inpatient hospital services furnished
in psychiatric hospitals and excluded
psychiatric units including an adequate
patient classification system that reflects
the differences in patient resource use
and costs among psychiatric hospitals
and excluded psychiatric units.
‘‘Excluded psychiatric unit’’ means a
psychiatric unit of an acute care
hospital or of a Critical Access Hospital
(CAH), which is excluded from payment
under the Inpatient Prospective
Payment System (IPPS) or CAH
payment system, respectively. These
excluded psychiatric units will be paid
under the IPF PPS.
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beginning with CY 2024 data for FY
2026 payment determination;
• Remove the following two measures
beginning with the FY 2025 payment
determination and subsequent years:
++ Patients Discharged on Multiple
Antipsychotic Medications with
Appropriate Justification (HBIPS–5);
and
++ Tobacco Use Brief Intervention
Provided or Offered and Tobacco Use
Brief Intervention Provided (TOB–2/2a)
measure;
• Adopt a data validation pilot
program starting with data submitted in
CY 2025 and continuing until a full data
validation program is proposed and
adopted in future rulemaking; and
• Codify the IPFQR Program’s
procedural requirements related to
statutory authority, participation and
withdrawal, data submission, quality
measure retention and removal,
extraordinary circumstances exceptions,
and public reporting at 42 CFR 412.433
Procedural requirements under the
IPFQR Program.
Total transfers & cost reductions
II. Background
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Section 405(g)(2) of the Medicare
Prescription Drug, Improvement, and
Modernization Act of 2003 (MMA) (Pub.
L. 108–173) extended the IPF PPS to
psychiatric distinct part units of CAHs.
Sections 3401(f) and 10322 of the
Patient Protection and Affordable Care
Act (Pub. L. 111–148) as amended by
section 10319(e) of that Act and by
section 1105(d) of the Health Care and
Education Reconciliation Act of 2010
(Pub. L. 111–152) (hereafter referred to
jointly as ‘‘the Affordable Care Act’’)
added subsection (s) to section 1886 of
the Social Security Act (the Act).
Section 1886(s)(1) of the Act titled,
‘‘Reference to Establishment and
Implementation of System,’’ refers to
section 124 of the BBRA, which relates
to the establishment of the IPF PPS.
Section 1886(s)(2)(A)(i) of the Act
requires the application of the
productivity adjustment described in
section 1886(b)(3)(B)(xi)(II) of the Act to
the IPF PPS for the rate year (RY)
beginning in 2012 (that is, a RY that
coincides with a FY) and each
subsequent RY.
Section 1886(s)(2)(A)(ii) of the Act
required the application of an ‘‘other
adjustment’’ that reduced any update to
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an IPF PPS base rate by a percentage
point amount specified in section
1886(s)(3) of the Act for the RY
beginning in 2010 through the RY
beginning in 2019. As noted in the FY
2020 IPF PPS final rule, for the RY
beginning in 2019, section 1886(s)(3)(E)
of the Act required that the other
adjustment reduction be equal to 0.75
percentage point; that was the final year
the statute required the application of
this adjustment. Because FY 2021 was a
RY beginning in 2020, FY 2021 was the
first-year section 1886(s)(2)(A)(ii) of the
Act did not apply since its enactment.
Sections 1886(s)(4)(A) through (D) of
the Act require that for RY 2014 and
each subsequent RY, IPFs that fail to
report required quality data with respect
to such a RY will have their annual
update to a standard Federal rate for
discharges reduced by 2.0 percentage
points. This may result in an annual
update being less than 0.0 for a RY, and
may result in payment rates for the
upcoming RY being less than such
payment rates for the preceding RY.
Any reduction for failure to report
required quality data will apply only to
the RY involved, and the Secretary will
not consider such reduction in
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computing the payment amount for a
subsequent RY. In addition, section
4125 of the CAA, 2023 requires that a
patients’ perspective of care quality
measure be added to the IPFQR Program
not later than for FY 2031. Additional
information about the specifics of the
current IPFQR Program is available in
the FY 2022 IPF PPS and Quality
Reporting Updates for FY Beginning
October 1, 2021 final rule (86 FR 42624
through 42661).
Section 4125 of the CAA, 2023 also
requires revisions to the Medicare
prospective payment system (PPS) for
psychiatric hospitals and psychiatric
units. Specifically, section 4125(a) of
the CAA, 2023 amends section 1886(s)
of the Act by adding a new paragraph
(5) that requires the Secretary to collect
data and information beginning no later
than October 1, 2023, as the Secretary
determines appropriate, to inform
revisions to IPF PPS payments. In
addition, the Secretary is required to
implement revisions to the methodology
for determining the payment rates under
the IPF PPS for FY 2025 as the Secretary
determines appropriate.
To implement and periodically
update the IPF PPS, we have published
various proposed and final rules and
notices in the Federal Register. For
more information regarding these
documents, see the CMS website at
https://www.cms.gov/Medicare/
Medicare-Fee-for-Service-Payment/
InpatientPsychFacilPPS/
index.html?redirect=/
InpatientPsychFacilPPS/.
B. Overview of the IPF PPS
On November 15, 2004, we published
the IPF PPS final rule in the Federal
Register (69 FR 66922). The November
2004 IPF PPS final rule established the
IPF PPS, as required by section 124 of
the BBRA and codified at 42 CFR part
412, subpart N. The November 2004 IPF
PPS final rule set forth the Federal per
diem base rate for the implementation
year (the 18-month period from January
1, 2005 through June 30, 2006), and
provided payment for the inpatient
operating and capital costs to IPFs for
covered psychiatric services they
furnish (that is, routine, ancillary, and
capital costs, but not costs of approved
educational activities, bad debts, and
other services or items that are outside
the scope of the IPF PPS). Covered
psychiatric services include services for
which benefits are provided under the
fee-for-service Part A (Hospital
Insurance Program) of the Medicare
program.
The IPF PPS established the Federal
per diem base rate for each patient day
in an IPF derived from the national
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average daily routine operating,
ancillary, and capital costs in IPFs in FY
2002. The average per diem cost was
updated to the midpoint of the first year
under the IPF PPS, standardized to
account for the overall positive effects of
the IPF PPS payment adjustments, and
adjusted for budget-neutrality.
The Federal per diem payment under
the IPF PPS is comprised of the Federal
per diem base rate described previously
and certain patient- and facility-level
payment adjustments for characteristics
that were found in the regression
analysis to be associated with
statistically significant per diem cost
differences; with statistical significance
defined as p less than 0.05. A complete
discussion of the regression analysis
that established the IPF PPS adjustment
factors can be found in the November
2004 IPF PPS final rule (69 FR 66933
through 66936).
The patient-level adjustments include
age, Diagnosis-Related Group (DRG)
assignment, and comorbidities, as well
as adjustments to reflect higher per
diem costs at the beginning of a
patient’s IPF stay and lower costs for
later days of the stay. Facility-level
adjustments include adjustments for the
IPF’s wage index, rural location,
teaching status, a cost-of-living
adjustment for IPFs located in Alaska
and Hawaii, and an adjustment for the
presence of a qualifying emergency
department (ED).
The IPF PPS has additional payment
policies for outlier cases, interrupted
stays, and a per treatment payment for
patients who undergo ECT. During the
IPF PPS mandatory 3-year transition
period, stop-loss payments were also
provided; however, since the transition
ended as of January 1, 2008, these
payments are no longer available.
C. Annual Requirements for Updating
the IPF PPS
Section 124 of the BBRA did not
specify an annual rate update strategy
for the IPF PPS and was broadly written
to give the Secretary discretion in
establishing an update methodology. In
the November 2004 IPF PPS final rule
(69 FR 66922), we implemented the IPF
PPS using the following update strategy:
• Calculate the final Federal per diem
base rate to be budget-neutral for the 18month period of January 1, 2005
through June 30, 2006.
• Use a July 1 through June 30 annual
update cycle.
• Allow the IPF PPS first update to be
effective for discharges on or after July
1, 2006 through June 30, 2007.
In developing the IPF PPS, and to
ensure that the IPF PPS can account
adequately for each IPF’s case-mix, we
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performed an extensive regression
analysis of the relationship between the
per diem costs and certain patient and
facility characteristics to determine
those characteristics associated with
statistically significant cost differences
on a per diem basis. That regression
analysis is described in detail in our
November 28, 2003 IPF PPS proposed
rule (68 FR 66923; 66928 through
66933) and our November 15, 2004 IPF
PPS final rule (69 FR 66933 through
66960). For characteristics with
statistically significant cost differences,
we used the regression coefficients of
those variables to determine the size of
the corresponding payment
adjustments.
In the November 2004 IPF PPS final
rule, we explained the reasons for
delaying an update to the adjustment
factors, derived from the regression
analysis, including waiting until we
have IPF PPS data that yields as much
information as possible regarding the
patient-level characteristics of the
population that each IPF serves. We
indicated that we did not intend to
update the regression analysis and the
patient-level and facility-level
adjustments until we complete that
analysis. Until that analysis is complete,
we stated our intention to publish a
notice in the Federal Register each
spring to update the IPF PPS (69 FR
66966).
On May 6, 2011, we published a final
rule in the Federal Register titled,
‘‘Inpatient Psychiatric Facilities
Prospective Payment System—Update
for Rate Year Beginning July 1, 2011 (RY
2012)’’ (76 FR 26432), which changed
the payment rate update period to a RY
that coincides with a FY update.
Therefore, final rules are now published
in the Federal Register in the summer
to be effective on October 1st. When
proposing changes in IPF payment
policy, a proposed rule would be issued
in the spring and the final rule in the
summer to be effective on October 1st.
For a detailed list of updates to the IPF
PPS, we refer readers to our regulations
at 42 CFR 412.428.
The most recent IPF PPS annual
update was published in a final rule on
July 29, 2022 in the Federal Register
titled, ‘‘Medicare Program; FY 2023
Inpatient Psychiatric Facilities
Prospective Payment System—Rate
Update and Quality Reporting—Request
for Information’’ (87 FR 46846), which
updated the IPF PPS payment rates for
FY 2023. That final rule updated the IPF
PPS Federal per diem base rates that
were published in the FY 2022 IPF PPS
Rate Update final rule (86 FR 42608) in
accordance with our established
policies.
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III. Provisions of the FY 2024 IPF PPS
Payment Update
A. Proposed Rebasing and Revising of
the Market Basket for the IPF PPS
1. Background
Originally, the input price index used
to develop the IPF PPS was the
Excluded Hospital with Capital market
basket. This market basket was based on
1997 Medicare cost reports for
Medicare-participating inpatient
rehabilitation facilities (IRFs), IPFs,
long-term care hospitals (LTCHs),
cancer hospitals, and children’s
hospitals. Although ‘‘market basket’’
technically describes the mix of goods
and services used in providing health
care at a given point in time, this term
is also commonly used to denote the
input price index (that is, cost category
weights and price proxies) derived from
that market basket. Accordingly, the
term ‘‘market basket,’’ as used in this
document, refers to an input price
index.
Since the IPF PPS inception, the
market basket used to update IPF PPS
payments has been rebased and revised
to reflect more recent data on IPF cost
structures. We last rebased and revised
the market basket applicable to the IPF
PPS in the FY 2020 IPF PPS final rule
(84 FR 38426 through 38447), where we
adopted a 2016-based IPF market basket.
The 2016-based IPF market basket used
Medicare cost report data for both
Medicare-participating freestanding
psychiatric hospitals and hospital-based
psychiatric units. References to the
historical market baskets used to update
IPF PPS payments are listed in the FY
2016 IPF PPS final rule (80 FR 46656).
For the FY 2024 IPF PPS proposed rule,
we propose to rebase and revise the IPF
market basket to reflect a 2021 base
year.
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2. Overview of the Proposed 2021-Based
IPF Market Basket
The proposed 2021-based IPF market
basket is a fixed-weight, Laspeyres-type
price index. A Laspeyres price index
measures the change in price, over time,
of the same mix of goods and services
purchased in the base period. Any
changes in the quantity or mix of goods
and services (that is, intensity)
purchased over time relative to a base
period are not measured.
The index itself is constructed in
three steps. First, a base period is
selected (in this proposed rule, we
propose to use 2021 as the base period)
and total base period costs are estimated
for a set of mutually exclusive and
exhaustive cost categories. Each
category is calculated as a proportion of
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total costs. These proportions are called
cost weights. Second, each cost category
is matched to an appropriate price or
wage variable, referred to as a price
proxy. In nearly every instance, these
price proxies are derived from publicly
available statistical series that are
published on a consistent schedule
(preferably at least on a quarterly basis).
Finally, the cost weight for each cost
category is multiplied by the level of its
respective price proxy. The sum of these
products (that is, the cost weights
multiplied by their price index levels)
for all cost categories yields the
composite index level of the market
basket in a given period. Repeating this
step for other periods produces a series
of market basket levels over time.
Dividing an index level for a given
period by an index level for an earlier
period produces a rate of growth in the
input price index over that timeframe.
As noted, the market basket is
described as a fixed-weight index
because it represents the change in price
over time of a constant mix (quantity
and intensity) of goods and services
needed to provide IPF services. The
effects on total costs resulting from
changes in the mix of goods and
services purchased subsequent to the
base period are not measured. For
example, an IPF hiring more nurses after
the base period to accommodate the
needs of patients would increase the
volume of goods and services purchased
by the IPF, but would not be factored
into the price change measured by a
fixed-weight IPF market basket. Only
when the index is rebased would
changes in the quantity and intensity be
captured, with those changes being
reflected in the cost weights. Therefore,
we rebase the market basket periodically
so that the cost weights reflect recent
changes in the mix of goods and
services that IPFs purchase to furnish
inpatient care between base periods.
3. Proposed Rebasing and Revising of
the IPF PPS Market Basket
As discussed in the FY 2020 IPF PPS
final rule (84 FR 38426 through 38447),
the 2016-based IPF market basket
reflects the Medicare cost reports for
both freestanding and hospital-based
IPFs. Beginning with FY 2024, we
propose to rebase and revise the IPF
market basket to a 2021 base year
reflecting the 2021 Medicare cost report
data submitted by both freestanding and
hospital-based IPFs. We provide a
detailed description of our proposed
methodology used to develop the 2021based IPF market basket below. This
proposed methodology is generally
similar to the methodology used to
develop the 2016-based IPF market
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basket. We solicit public comment on
our proposed methodology for
developing the 2021-based IPF market
basket.
a. Development of Cost Categories and
Weights for the Proposed 2021-Based
IPF Market Basket
(1) Use of Medicare Cost Report Data
We propose a 2021-based IPF market
basket that consists of seven major cost
categories and a residual derived from
the 2021 Medicare cost reports (CMS
Form 2552–10, OMB No. 0938–0050) for
freestanding and hospital-based IPFs.
The seven major cost categories are
Wages and Salaries, Employee Benefits,
Contract Labor, Pharmaceuticals,
Professional Liability Insurance (PLI),
Home Office/Related Organization
Contract Labor, and Capital. The cost
reports include providers whose cost
reporting period began on or after
October 1, 2020 and before October 1,
2021. As noted previously, the current
IPF market basket is based on 2016
Medicare cost reports and therefore,
reflects the 2016 cost structure for IPFs.
As described in the FY 2023 IPF PPS
final rule (87 FR 46849), we received
comments on the FY 2023 IPF PPS
proposed rule (87 FR 19418 through
19419) where stakeholders expressed
concern that the proposed market basket
update inadequately reflected the input
price inflation experienced by IPFs,
particularly as a result of the COVID–19
PHE. These commenters stated that the
PHE, along with inflation, has
significantly driven up operating costs.
Specifically, some commenters noted
changes to labor markets that led to the
use of more contract labor, a trend that
we verified in analyzing the Medicare
cost reports through 2021. Therefore, we
believe it is appropriate to incorporate
more recent data to reflect updated cost
structures for IPFs, and so we propose
to use 2021 as the base year because we
believe that the Medicare cost reports
for this year represent the most recent
complete set of Medicare cost report
data available for developing the
proposed IPF market basket at the time
of this rulemaking. Given the potential
impact of the PHE on the Medicare cost
report data, we will continue to monitor
these data going forward and any
changes to the IPF market basket would
be proposed in future rulemaking.
Similar to the Medicare cost report
data used to develop the 2016-based IPF
market basket, the Medicare cost report
data for 2021 show large differences
between some providers’ Medicare
length of stay (LOS) and total facility
LOS. Our goal has always been to
measure cost weights that are reflective
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of case mix and practice patterns
associated with providing services to
Medicare beneficiaries. Therefore, we
propose to limit our selection of
Medicare cost reports used in the
proposed 2021-based IPF market basket
to those facilities that had a Medicare
LOS within a comparable range of their
total facility average LOS. The Medicare
average LOS for freestanding IPFs is
calculated from data reported on line 14
of Worksheet S–3, part I. The Medicare
average LOS for hospital-based IPFs is
calculated from data reported on line 16
of Worksheet S–3, part I. To derive the
proposed 2021-based IPF market basket,
for those IPFs with an average facility
LOS of greater than or equal to 15 days,
we propose to include IPFs where the
Medicare LOS is within 50 percent
(higher or lower) of the average facility
LOS. For those IPFs whose average
facility LOS is less than 15 days, we
propose to include IPFs where the
Medicare LOS is within 95 percent
(higher or lower) of the facility LOS. We
propose to apply this LOS edit to the
data for IPFs to exclude providers that
serve a population whose LOS would
indicate that the patients served are not
consistent with a LOS of a typical
Medicare patient. This is the same LOS
edit applied to the 2016-based IPF
market basket.
Applying these trims to the
approximate 1,370 total cost reports
(freestanding and hospital-based)
resulted in roughly 1,250 IPF Medicare
cost reports with an average Medicare
LOS of 13 days, average facility LOS of
10 days, and Medicare utilization (as
measured by Medicare inpatient IPF
days as a percentage of total facility
days) of 16 percent. Providers excluded
from the proposed 2021-based IPF
market basket (about 120 Medicare cost
reports) had an average Medicare LOS of
21 days, average facility LOS of 41 days,
and a Medicare utilization of 3 percent.
Of those excluded, about 62 percent of
these were freestanding providers; on
the other hand, freestanding providers
represent about 38 percent of all IPFs.
We note that 70 percent of those
excluded from the 2016-based IPF
market basket using this LOS edit were
freestanding providers.
We then propose to use the cost
reports for IPFs that met this
requirement to calculate the costs for
the seven major cost categories (Wages
and Salaries, Employee Benefits,
Contract Labor, Professional Liability
Insurance, Pharmaceuticals, Home
Office/Related Organization Contract
Labor, and Capital) for the market
basket. These are the same categories
used for the 2016-based IPF market
basket. Also, as described in section
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III.A.3.a.(4) of this proposed rule, and as
done for the 2016-based IPF market
basket, we propose to use the Medicare
cost report data to calculate the detailed
capital cost weights for the
Depreciation, Interest, Lease, and Other
Capital-related cost categories. We also
propose to rename the Home Office
Contract Labor cost category to the
Home Office/Related Organization
Contract Labor cost category to be more
consistent with the Medicare cost report
instructions.
Similar to the 2016-based IPF market
basket major cost weights, for the
majority of the proposed 2021-based IPF
market basket cost weights, we propose
to divide the costs for each cost category
by total Medicare allowable costs
(routine, ancillary and capital)—costs
that are eligible for payment through the
IPF PPS (we note that we use total
facility medical care costs as the
denominator to derive both the PLI and
Home Office/Related Organization
Contract Labor cost weights). We next
describe our proposed methodology for
deriving the cost levels used to derive
the proposed 2021-based IPF market
basket.
(a) Total Medicare Allowable Costs
For freestanding IPFs, we propose that
total Medicare allowable costs would be
equal to the sum of total costs for the
Medicare allowable cost centers as
reported on Worksheet B, part I, column
26, lines 30 through 35, 50 through 76
(excluding 52 and 75), 90 through 91,
and 93.
For hospital-based IPFs, we propose
that total Medicare allowable costs
would be equal to the total costs for the
IPF inpatient unit after the allocation of
overhead costs (Worksheet B, part I,
column 26, line 40) and a proportion of
total ancillary costs reported on
Worksheet B, part I, column 26, lines 50
through 76 (excluding 52 and 75), 90
through 91, and 93.
We propose to calculate total ancillary
costs attributable to the hospital-based
IPF by first deriving an ‘‘IPF ancillary
ratio’’ for each ancillary cost center. The
IPF ancillary ratio is defined as the ratio
of IPF Medicare ancillary costs for the
cost center (as reported on Worksheet
D–3, column 3 for hospital-based IPFs)
to total Medicare ancillary costs for the
cost center (equal to the sum of
Worksheet D–3, column 3 for all
relevant PPSs [that is, IPPS, IRF, IPF
and skilled nursing facility (SNF)]). For
example, if hospital-based IPF Medicare
laboratory costs represent about 2
percent of the total Medicare laboratory
costs for the entire facility, then the IPF
ancillary ratio for laboratory costs
would be 2 percent. We believe it is
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appropriate to use only a portion of the
ancillary costs in the market basket cost
weight calculations since the hospitalbased IPF only utilizes a portion of the
facility’s ancillary services. We believe
the ratio of reported IPF Medicare costs
to reported total Medicare costs
provides a reasonable estimate of the
ancillary services utilized, and costs
incurred, by the hospital-based IPF. We
propose that this IPF ancillary ratio for
each cost center is also used to calculate
Wages and Salaries, and Capital costs as
described below.
Then, for each ancillary cost center,
we propose to multiply the IPF ancillary
ratio for the given cost center by the
total facility ancillary costs for that
specific cost center (as reported on
Worksheet B, part I, column 26) to
derive IPF ancillary costs. For example,
the 2 percent IPF ancillary ratio for
laboratory cost center would be
multiplied by the total ancillary costs
for laboratory (Worksheet B, part I,
column 26, line 60). The IPF ancillary
costs for each cost center are then added
to total costs for the IPF inpatient unit
after the allocation of overhead costs
(Worksheet B, part I, column 26, line 40)
to derive total Medicare allowable costs.
We propose to use these methods to
derive levels of total Medicare allowable
costs for IPF providers. This is the same
methodology used for the 2016-based
IPF market basket. We propose that
these total Medicare allowable costs for
the IPF will be the denominator for the
cost weight calculations for the Wages
and Salaries, Employee Benefits,
Contract Labor, Pharmaceuticals, and
Capital cost weights. With this work
complete, we then set about deriving
cost levels for the seven major cost
categories and then derive a residual
cost weight reflecting all other costs not
classified.
(b) Wages and Salaries Costs
For freestanding IPFs, we propose to
derive Wages and Salaries costs as the
sum of routine inpatient salaries
(Worksheet A, column 1, lines 30
through 35), ancillary salaries
(Worksheet A, column 1, lines 50
through 76 (excluding 52 and 75), 90
through 91, and 93), and a proportion of
overhead (or general service cost centers
in the Medicare cost reports) salaries.
Since overhead salary costs are
attributable to the entire IPF, we only
include the proportion attributable to
the Medicare allowable cost centers. We
propose to estimate the proportion of
overhead salaries that are attributed to
Medicare allowable costs centers by
multiplying the ratio of Medicare
allowable area salaries (Worksheet A,
column 1, lines 30 through 35, 50
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through 76 (excluding 52 and 75), 90
through 91, and 93) to total nonoverhead salaries (Worksheet A, column
1, line 200 less Worksheet A, column 1,
lines 4 through 18) times total overhead
salaries (Worksheet A, column 1, lines
4 through 18). This is a similar
methodology as used in the 2016-based
IPF market basket.
For hospital-based IPFs, we propose
to derive Wages and Salaries costs as the
sum of the following salaries
attributable to the hospital-based IPF:
Inpatient routine salary costs
(Worksheet A, column 1, line 40);
overhead salary costs; ancillary salary
costs; and a portion of overhead salary
costs attributable to the ancillary
departments.
(i) Overhead Salary Costs
We propose to calculate the portion of
overhead salary cost attributable to
hospital-based IPFs by first calculating
an IPF overhead salary ratio, which is
equal to the ratio of total facility
overhead salaries (as reported on
Worksheet A, column 1, lines 4–18) to
total facility noncapital overhead costs
(as reported on Worksheet A, column 1
and 2, lines 4–18). We then propose to
multiply this IPF overhead salary ratio
by total noncapital overhead costs (sum
of Worksheet B, part I, columns 4
through 18, line 40, less Worksheet B,
part II, columns 4 through 18, line 40).
This methodology assumes the
proportion of total costs related to
salaries for the overhead cost center is
similar for all inpatient units (that is,
acute inpatient or inpatient psychiatric).
ddrumheller on DSK120RN23PROD with PROPOSALS2
(ii) Ancillary Salary Costs
We propose to calculate hospitalbased IPF ancillary salary costs for a
specific cost center (Worksheet A,
column 1, lines 50 through 76
(excluding 52 and 75), 90 through 91,
and 93) as salary costs from Worksheet
A, column 1, multiplied by the IPF
ancillary ratio for each cost center as
described in section III.A.3.a.(1)(a) of
this proposed rule. The sum of these
costs represents hospital-based IPF
ancillary salary costs.
(iii) Overhead Salary Costs for Ancillary
Cost Centers
We propose to calculate the portion of
overhead salaries attributable to each
ancillary department (lines 50 through
76 (excluding 52 and 75), 90 through 91,
and 93) by first calculating total
noncapital overhead cost attributable to
each specific ancillary department (sum
of Worksheet B, part I, columns 4–18,
less Worksheet B, part II, column 26).
We then identify the portion of these
total noncapital overhead cost for each
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ancillary department that is attributable
to the hospital-based IPF by multiplying
these costs by the IPF ancillary ratio as
described in section III.A.3.a.(1)(a) of
this proposed rule. We then sum these
estimated IPF Medicare allowable
noncapital overhead costs for all
ancillary departments (cost centers 50
through 76, 90 through 91, and 93).
Finally, we then identify the portion of
these IPF Medicare allowable noncapital
overhead cost that are attributable to
Wages and Salaries by multiplying these
costs by the IPF overhead salary ratio as
described in section III.A.3.a.(1)(b)(i) of
this proposed rule. This is the same
methodology used to derive the 2016based IPF market basket.
(c) Employee Benefits Costs
Effective with the implementation of
CMS Form 2552–10, we began
collecting Employee Benefits and
Contract Labor data on Worksheet S–3,
part V.
For the 2021 Medicare cost report
data, the majority of IPF providers did
not report data on Worksheet S–3, part
V. Two percent of freestanding IPFs and
roughly 48 percent of hospital-based
IPFs reported Employee Benefits data on
Worksheet S–3, part V. Two percent of
freestanding IPFs and roughly 13
percent of hospital-based IPFs reported
Contract Labor data on Worksheet S–3,
part V. We continue to encourage all
providers to report these data on the
Medicare cost report.
For freestanding IPFs, we propose that
Employee Benefits cost would be equal
to the data reported on Worksheet S–3,
part V, column 2, line 2. We note that
while not required to do so, freestanding
IPFs also may report Employee Benefits
data on Worksheet S–3, part II, which is
applicable to only IPPS providers.
Similar to the method for the 2016based IPF market basket, for those
freestanding IPFs that report Worksheet
S–3, part II, data, but not Worksheet S–
3, part V, we propose to use the sum of
Worksheet S–3, part II, lines 17, 18, 20,
and 22, to derive Employee Benefits
costs.
For hospital-based IPFs, we propose
to calculate total benefit cost as the sum
of inpatient unit benefit cost, a portion
of ancillary departments benefit costs,
and a portion of overhead benefits
attributable to both the routine inpatient
unit and the ancillary departments. For
those hospital-based IPFs that report
Worksheet S–3, part V data, we propose
inpatient unit benefit costs be equal to
Worksheet S–3, part V, column 2, line
3. Given the limited reporting on
Worksheet S–3, part V, we propose that
for those hospital-based IPFs that do not
report these data, we calculate inpatient
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21243
unit benefits cost using a portion of
benefits cost reported for Excluded areas
on Worksheet S–3, part II. We propose
to calculate the ratio of inpatient unit
salaries (Worksheet A, column 1, line
40) to total excluded area salaries (sum
of Worksheet A, column 1, lines 20, 23,
40 through 42, 44, 45, 46, 94, 95, 98
through 101, 105 through 112, 114, 115
through 117, 190 through 194). We then
propose to apply this ratio to Excluded
area benefits (Worksheet S–3, part II,
column 4, line 19) to derive inpatient
unit benefits cost for those providers
that do not report benefit costs on
Worksheet S–3, part V.
We propose the ancillary departments
benefits and overhead benefits
(attributable to both the inpatient unit
and ancillary departments) costs are
derived by first calculating the sum of
hospital-based IPF overhead salaries as
described in section III.A.3.a.(1)(b)(i) of
this proposed rule, hospital-based IPF
ancillary salaries as described in section
III.A.3.a.(1)(b)(ii) of this proposed rule
and hospital-based IPF overhead
salaries for ancillary cost centers as
described in section III.A.3.a.(1)(b)(iii)
of this proposed rule. This sum is then
multiplied by the ratio of total facility
benefits to total facility salaries, where
total facility benefits is equal to the sum
of Worksheet S–3, part II, column 4,
lines 17–25, and total facility salaries is
equal to Worksheet S–3, part II, column
4, line 1.
(d) Contract Labor Costs
Contract Labor costs are primarily
associated with direct patient care
services. Contract labor costs for other
services such as accounting, billing, and
legal are calculated separately using
other government data sources as
described in section III.A.3.a.(3) of this
proposed rule. To derive contract labor
costs using Worksheet S–3, part V, data
for freestanding IPFs, we propose
Contract Labor costs be equal to
Worksheet S–3, part V, column 1, line
2. As we noted for Employee Benefits,
freestanding IPFs also may report
Contract Labor data on Worksheet S–3,
part II, which is applicable to only IPPS
providers. For those freestanding IPFs
that report Worksheet S–3, part II data,
but not Worksheet S–3, part V, we
propose to use the sum of Worksheet S–
3, part II, column 4, lines 11 and 13, to
derive Contract Labor costs.
For hospital-based IPFs, we propose
that Contract Labor costs be equal to
Worksheet S–3, part V, column 1, line
3. Reporting of this data continues to be
somewhat limited; therefore, we
continue to encourage all providers to
report these data on the Medicare cost
report. Given the limited reporting on
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ddrumheller on DSK120RN23PROD with PROPOSALS2
Worksheet S–3, part V, we propose that
for those hospital-based IPFs that do not
report these data, we calculate Contract
Labor costs using a portion of contract
labor costs reported on Worksheet S–3,
part II. We propose to calculate the ratio
of contract labor costs (Worksheet S–3,
part II, column 4, lines 11 and 13) to
PPS salaries (Worksheet S–3, part II,
column 4, line 1 less the sum of
Worksheet S–3, part II, column 4, lines
3, 401, 5, 6, 7, 701, 8, 9, 10 less
Worksheet A, column 1, line 20 and 23).
We then propose to apply this ratio to
total inpatient routine salary costs
(Worksheet A, column 1, line 40) to
derive contract labor costs for those
providers that do not report contract
labor costs on Worksheet S–3, part V.
(e) Pharmaceuticals Costs
For freestanding IPFs, we propose to
calculate pharmaceuticals costs using
non-salary costs reported on Worksheet
A, column 7, less Worksheet A, column
1, for the pharmacy cost center (line 15)
and drugs charged to patients cost
center (line 73).
For hospital-based IPFs, we propose
to calculate pharmaceuticals costs as the
sum of a portion of the non-salary
pharmacy costs and a portion of the
non-salary drugs charged to patient
costs reported for the total facility. We
propose that non-salary pharmacy costs
attributable to the hospital-based IPF
would be calculated by multiplying
total pharmacy costs attributable to the
hospital-based IPF (as reported on
Worksheet B, part I, column 15, line 40)
by the ratio of total non-salary pharmacy
costs (Worksheet A, column 2, line 15)
to total pharmacy costs (sum of
Worksheet A, columns 1 and 2 for line
15) for the total facility. We propose that
non-salary drugs charged to patient
costs attributable to the hospital-based
IPF would be calculated by multiplying
total non-salary drugs charged to patient
costs (Worksheet B, part I, column 0,
line 73 plus Worksheet B, part I, column
15, line 73 less Worksheet A, column 1,
line 73) for the total facility by the ratio
of Medicare drugs charged to patient
ancillary costs for the IPF unit (as
reported on Worksheet D–3 for hospitalbased IPFs, column 3, line 73) to total
Medicare drugs charged to patient
ancillary costs for the total facility
(equal to the sum of Worksheet D–3,
column 3, line 73 for all relevant PPS
[that is, IPPS, IRF, IPF and SNF]).
(f) Professional Liability Insurance Costs
For freestanding and hospital-based
IPFs, we propose that Professional
Liability Insurance (PLI) costs (often
referred to as malpractice costs) would
be equal to premiums, paid losses and
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self-insurance costs reported on
Worksheet S–2, columns 1 through 3,
line 118—the same data used for the
2016-based IPF market basket. For
hospital-based IPFs, we propose to
assume that the PLI weight for the total
facility is similar to the hospital-based
IPF unit since the only data reported on
this worksheet is for the entire facility,
as we currently have no means to
identify the proportion of total PLI costs
that are only attributable to the hospitalbased IPF. However, when we derive
the cost weight for PLI for both hospitalbased and freestanding IPFs, we use the
total facility medical care costs as the
denominator as opposed to total
Medicare allowable costs. For
freestanding IPFs and hospital-based
IPFs, we propose to derive total facility
medical care costs as the sum of total
costs (Worksheet B, part I, column 26,
line 202) less non-reimbursable costs
(Worksheet B, part I, column 26, lines
190 through 201). Our assumption is
that the same proportion of expenses are
used among each unit of the hospital.
(g) Home Office/Related Organization
Contract Labor Costs
For hospital-based IPFs, we propose
to calculate the Home Office/Related
Organization Contract Labor costs using
data reported on Worksheet S–3, part II,
column 4, lines 1401, 1402, 2550, and
2551. Similar to the PLI costs, these
costs are for the entire facility.
Therefore, when we derive the cost
weight for home office/related
organization contract labor costs, we use
the total facility medical care costs as
the denominator (reflecting the total
facility costs (Worksheet B, part I,
column 26, line 202) less the
nonreimbursable costs reported on lines
190 through 201).
(h) Capital Costs
For freestanding IPFs, we propose that
capital costs would be equal to
Medicare allowable capital costs as
reported on Worksheet B, part II,
column 26, lines 30 through 35, 50
through 76 (excluding 52 and 75), 90
through 91, and 93.
For hospital-based IPFs, we propose
that capital costs would be equal to IPF
inpatient capital costs (as reported on
Worksheet B, part II, column 26, line 40)
and a portion of IPF ancillary capital
costs. We calculate the portion of
ancillary capital costs attributable to the
hospital-based IPF for a given cost
center by multiplying total facility
ancillary capital costs for the specific
ancillary cost center (as reported on
Worksheet B, part II, column 26) by the
IPF ancillary ratio as described in
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section III.A.3.a.(1)(a) of this proposed
rule.
(2) Final Major Cost Category
Computation
After we derive costs for each of the
major cost categories and total Medicare
allowable costs for each provider using
the Medicare cost report data as
previously described, we propose to
address data outliers using the following
steps. First, for the Wages and Salaries,
Employee Benefits, Contract Labor,
Pharmaceuticals, and Capital cost
weights, we first divide the costs for
each of these five categories by total
Medicare allowable costs calculated for
the provider to obtain cost weights for
the universe of IPF providers. We then
propose to trim the data to remove
outliers (a standard statistical process)
by: (1) requiring that major expenses
(such as Wages and Salaries costs) and
total Medicare allowable operating costs
be greater than zero; and (2) excluding
the top and bottom 5 percent of the
major cost weight (for example, Wages
and Salaries costs as a percent of total
Medicare allowable operating costs). We
note that missing values are assumed to
be zero consistent with the methodology
for how missing values were treated in
the 2016-based IPF market basket. After
these outliers have been excluded, we
sum the costs for each category across
all remaining providers. We then divide
this by the sum of total Medicare
allowable costs across all remaining
providers to obtain a cost weight for the
proposed 2021-based IPF market basket
for the given category.
The proposed trimming methodology
for the Home Office/Related
Organization Contract Labor and PLI
cost weights are slightly different than
the proposed trimming methodology for
the other five cost categories as
described above. For these cost weights,
since we are using total facility medical
care costs rather than Medicare
allowable costs associated with IPF
services, we propose to trim the
freestanding and hospital-based IPF cost
weights separately.
For the PLI cost weight, for each of
the providers, we first divide the PLI
costs by total facility medical care costs
to obtain a PLI cost weight for the
universe of IPF providers. We then
propose to trim the data to remove
outliers by: (1) requiring that PLI costs
are greater than zero and are less than
total facility medical care costs; and (2)
excluding the top and bottom 5 percent
of the major cost weight trimming
freestanding and hospital-based
providers separately. After removing
these outliers, we are left with a
trimmed data set for both freestanding
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and hospital-based providers. We
propose to separately sum the costs for
each category (freestanding and
hospital-based) across all remaining
providers. We next divide this by the
sum of total facility medical care costs
across all remaining providers to obtain
both a freestanding cost weight and
hospital-based cost weight. Lastly, we
propose to weight these two cost
weights together using the Medicare
allowable costs from the sample of
freestanding and hospital-based IPFs
that passed the PLI trim (63 percent for
hospital-based and 37 percent for
freestanding IPFs) to derive a PLI cost
weight for the proposed 2021-based IPF
market basket.
For the Home Office/Related
Organization Contract Labor cost
weight, for each of the providers, we
first divide the home office/related
organization contract labor costs by total
facility medical care costs to obtain a
Home Office/Related Organization
Contract Labor cost weight for the
universe of IPF providers. Similar to the
other market basket costs weights, we
propose to trim the Home Office/Related
Organization Contract Labor cost weight
to remove outliers. Since not all
hospital-based IPFs will have home
office/related organization contract
labor costs (approximately 80 percent of
hospital-based IPFs report having a
home office), we propose to trim the top
one percent of the Home Office/Related
Organization Contract Labor cost
weight. Using this proposed
methodology, we calculate a Home
Office/Related Organization Contract
Labor cost weight for hospital-based
IPFs of 5.1 percent.
Freestanding IPFs are not required to
complete Worksheet S–3, part II.
Therefore, to estimate the Home Office/
Related Organization Contract Labor
cost weight for freestanding IPFs, we
propose the following methodology:
Step 1: Using hospital-based IPFs
with a home office and also passing the
1 percent trim as described, we
calculate the ratio of the Home Office/
Related Organization Contract Labor
cost weight to the Medicare allowable
non-salary, non-capital cost weight
(Medicare allowable non-salary, noncapital costs as a percent of total
Medicare allowable costs).
Step 2: We identify freestanding IPFs
that report a home office on Worksheet
S–2, line 140—roughly 87 percent of
freestanding IPFs. We propose to
calculate a Home Office/Related
Organization Contract Labor cost weight
for these freestanding IPFs by
multiplying the ratio calculated in Step
1 by the Medicare allowable non-salary,
noncapital cost weight for those
freestanding IPFs with a home office.
Step 3: We then calculate the
freestanding IPF cost weight by
multiplying the Home Office/Related
Organization Contract Labor cost weight
in Step 2 by the total Medicare
allowable costs for freestanding IPFs
with a home office as a percent of total
Medicare allowable costs for all
freestanding IPFs (87 percent), which
derives a freestanding Home Office/
Related Organization Contract Labor
cost weight of 4.2 percent.
To calculate the overall Home Office/
Related Organization Contract Labor
cost weight for the proposed 2021-based
IPF market basket, we propose to weight
together the freestanding Home Office/
Related Organization Contract Labor
cost weight (4.2 percent) and the
hospital-based Home Office Contract
Labor/Related Organization cost weight
(5.1 percent) using total Medicare
allowable costs from the sample of
hospital-based IPFs that passed the one
percent trim and the universe of
freestanding IPFs. The resulting overall
cost weight for Home Office/Related
Organization Contract Labor is 4.7
percent (4.2 percent × 44 percent + 5.1
percent × 56 percent). This is the same
methodology used to calculate the
Home Office/Related Organization
Contract Labor cost weight in the 2016based IPF market basket.
Finally, we propose to calculate the
residual ‘‘All Other’’ cost weight that
reflects all remaining costs that are not
captured in the seven cost categories
listed. See Table 1 for the resulting cost
weights for these major cost categories
that we obtain from the Medicare cost
reports.
TABLE 1—MAJOR COST CATEGORIES AS DERIVED FROM MEDICARE COST REPORTS
Proposed
2021-Based
IPF market
basket
(percent)
Major cost categories
ddrumheller on DSK120RN23PROD with PROPOSALS2
Wages and Salaries ................................................................................................................................................
Employee Benefits ...................................................................................................................................................
Contract Labor .........................................................................................................................................................
Professional Liability Insurance (Malpractice) .........................................................................................................
Pharmaceuticals ......................................................................................................................................................
Home Office/Related Organization Contract Labor .................................................................................................
Capital ......................................................................................................................................................................
All Other ...................................................................................................................................................................
As we did for the 2016-based IPF
market basket, we propose to allocate
the Contract Labor cost weight to the
Wages and Salaries and Employee
Benefits cost weights based on their
relative proportions under the
assumption that contract labor costs are
comprised of both wages and salaries,
and employee benefits. The Contract
Labor allocation proportion for Wages
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and Salaries is equal to the Wages and
Salaries cost weight as a percent of the
sum of the Wages and Salaries cost
weight and the Employee Benefits cost
weight. For this proposed rule, this
rounded percentage is 79 percent;
therefore, we propose to allocate 79
percent of the Contract Labor cost
weight to the Wages and Salaries cost
weight and 21 percent to the Employee
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50.4
13.7
2.8
1.0
3.6
4.7
7.2
16.7
2016-Based
IPF market
basket
(percent)
51.2
13.5
1.3
0.9
4.7
3.5
7.1
17.9
Benefits cost weight. This allocation
was 81/19 in the 2016-based IPF market
basket (84 FR 38430). Table 2 shows the
Wages and Salaries and Employee
Benefit cost weights after Contract Labor
cost weight allocation for both the
proposed 2021-based IPF market basket
and 2016-based IPF market basket.
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TABLE 2—WAGES AND SALARIES AND EMPLOYEE BENEFITS COST WEIGHTS AFTER CONTRACT LABOR ALLOCATION
Proposed
2021-Based
IPF market
basket
Major cost categories
ddrumheller on DSK120RN23PROD with PROPOSALS2
Wages and Salaries ................................................................................................................................................
Employee Benefits ...................................................................................................................................................
(3) Derivation of the Detailed Operating
Cost Weights
To further divide the ‘‘All Other’’
residual cost weight estimated from the
2021 Medicare cost report data into
more detailed cost categories, we
propose to use the 2012 Benchmark
Input-Output (I–O) ‘‘Use Tables/Before
Redefinitions/Purchaser Value’’ for
North American Industry Classification
System (NAICS) 622000, Hospitals,
published by the Bureau of Economic
Analysis (BEA). This data is publicly
available at https://www.bea.gov/
industry/io_annual.htmhttps://
www.bea.gov/industry/io_annual.htm.
For the 2016-based IPF market basket,
we also used the 2012 Benchmark I–O
data, the most recent data available at
the time (84 FR 38431).
The BEA Benchmark I–O data are
scheduled for publication every 5 years
with the most recent data available for
2012. The 2012 Benchmark I–O data are
derived from the 2012 Economic Census
and are the building blocks for BEA’s
economic accounts. Thus, they
represent the most comprehensive and
complete set of data on the economic
processes or mechanisms by which
output is produced and distributed.1
BEA also produces Annual I–O
estimates; however, while based on a
similar methodology, these estimates
reflect less comprehensive and less
detailed data sources and are subject to
revision when benchmark data becomes
available. Instead of using the less
detailed Annual I–O data, we propose to
inflate the 2012 Benchmark I–O data
forward to 2021 by applying the annual
price changes from the respective price
proxies to the appropriate market basket
cost categories that are obtained from
the 2012 Benchmark I–O data. We
repeat this practice for each year. We
then propose to calculate the cost shares
that each cost category represents of the
inflated 2012 data. These resulting 2021
cost shares are applied to the All Other
residual cost weight to obtain the
detailed cost weights for the proposed
2021-based IPF market basket. For
example, the cost for Food: Direct
Purchases represents 5.0 percent of the
1 https://www.bea.gov/papers/pdf/IOmanual_
092906.pdf.
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sum of the ‘‘All Other’’ 2012 Benchmark
I–O Hospital Expenditures inflated to
2021; therefore, the Food: Direct
Purchases cost weight represents 5.0
percent of the proposed 2021-based IPF
market basket’s ‘‘All Other’’ cost
category (16.7 percent), yielding a
‘‘final’’ Food: Direct Purchases cost
weight of 0.8 percent in the proposed
2021-based IPF market basket (0.05 *
16.7 percent = 0.8 percent).
Using this methodology, we propose
to derive seventeen detailed IPF market
basket cost category weights from the
proposed 2021-based IPF market basket
residual cost weight (16.7 percent).
These categories are: (1) Electricity and
Other Non-Fuel Utilities; (2) Fuel: Oil
and Gas; (3) Food: Direct Purchases; (4)
Food: Contract Services; (5) Chemicals;
(6) Medical Instruments; (7) Rubber and
Plastics; (8) Paper and Printing
Products; (9) Miscellaneous Products;
(10) Professional Fees: Labor-related;
(11) Administrative and Facilities
Support Services; (12) Installation,
Maintenance, and Repair Services; (13)
All Other Labor-related Services; (14)
Professional Fees: Nonlabor-related; (15)
Financial Services; (16) Telephone
Services; and (17) All Other Nonlaborrelated Services.
(4) Derivation of the Detailed Capital
Cost Weights
As described in section III.A.3.a.(2) of
this proposed rule, we propose a
Capital-Related cost weight of 7.2
percent as obtained from the 2021
Medicare cost reports for freestanding
and hospital-based IPF providers. We
propose to then separate this total
Capital-Related cost weight into more
detailed cost categories.
Using 2021 Medicare cost reports, we
are able to group Capital-Related costs
into the following categories:
Depreciation, Interest, Lease, and Other
Capital-Related costs. For each of these
categories, we propose to determine
separately for hospital-based IPFs and
freestanding IPFs what proportion of
total capital-related costs the category
represents.
For freestanding IPFs, using Medicare
Cost Report data on Worksheet A–7 part
III, we propose to derive the proportions
for Depreciation (column 9), Interest
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52.6
14.3
2016-Based
IPF market
basket
52.2
13.8
(column 11), Lease (column 10), and
Other Capital-related costs (column 12
through 14), which is similar to the
methodology used for the 2016-based
IPF market basket.
For hospital-based IPFs, data for these
four categories are not reported
separately for the hospital-based IPF;
therefore, we propose to derive these
proportions using data reported on
Worksheet A–7 for the total facility. We
are assuming the cost shares for the
overall hospital are representative for
the hospital-based IPF unit. For
example, if depreciation costs make up
60 percent of total capital costs for the
entire facility, we believe it is
reasonable to assume that the hospitalbased IPF would also have a 60 percent
proportion because it is a unit contained
within the total facility. This is the same
methodology used for the 2016-based
IPF market basket (84 FR 38431).
To combine each detailed capital cost
weight for freestanding and hospitalbased IPFs into a single capital cost
weight for the proposed 2021-based IPF
market basket, we propose to weight
together the shares for each of the
categories (Depreciation, Interest, Lease,
and Other Capital-related costs) based
on the share of total capital costs each
provider type represents of the total
capital costs for all IPFs for 2021.
Applying this methodology results in
proportions of total capital-related costs
for Depreciation, Interest, Lease and
Other Capital-related costs that are
representative of the universe of IPF
providers. This is the same methodology
used for the 2016-based IPF market
basket (84 FR 38432).
Lease costs are unique in that they are
not broken out as a separate cost
category in the proposed 2021-based IPF
market basket. Rather, we propose to
proportionally distribute these costs
among the cost categories of
Depreciation, Interest, and Other
Capital-Related costs, reflecting the
assumption that the underlying cost
structure of leases is similar to that of
capital-related costs in general. As was
done under the 2016-based IPF market
basket, we propose to assume that 10
percent of the lease costs as a proportion
of total capital-related costs represents
overhead and assign those costs to the
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Other Capital-Related cost category
accordingly. We propose to distribute
the remaining lease costs proportionally
across the three cost categories
(Depreciation, Interest, and Other
Capital-Related) based on the proportion
that these categories comprise of the
sum of the Depreciation, Interest, and
Other Capital-related cost categories
(excluding lease expenses). This would
result in three primary capital-related
cost categories in the proposed 2021based IPF market basket: Depreciation,
Interest, and Other Capital-Related
costs. This is the same methodology
used for the 2016-based IPF market
basket (84 FR 38432). The allocation of
these lease expenses is shown in Table
3.
Finally, we propose to further divide
the Depreciation and Interest cost
categories. We propose to separate
Depreciation into the following two
categories: (1) Building and Fixed
Equipment; and (2) Movable Equipment.
We propose to separate Interest into the
following two categories: (1)
Government/Nonprofit; and (2) Forprofit.
To disaggregate the Depreciation cost
weight, we need to determine the
percent of total Depreciation costs for
IPFs that is attributable to Building and
Fixed Equipment, which we hereafter
refer to as the ‘‘fixed percentage.’’ For
the proposed 2021-based IPF market
basket, we propose to use slightly
different methods to obtain the fixed
percentages for hospital-based IPFs
compared to freestanding IPFs.
For freestanding IPFs, we propose to
use depreciation data from Worksheet
A–7 of the 2021 Medicare cost reports.
However, for hospital-based IPFs, we
determined that the fixed percentage for
the entire facility may not be
representative of the hospital-based IPF
unit due to the entire facility likely
employing more sophisticated movable
assets that are not utilized by the
hospital-based IPF. Therefore, for
hospital-based IPFs, we propose to
calculate a fixed percentage using: (1)
building and fixture capital costs
allocated to the hospital-based IPF unit
as reported on Worksheet B, part I,
column 1, line 40; and (2) building and
fixture capital costs for the top five
ancillary cost centers utilized by
hospital-based IPFs accounting for 82
percent of hospital-based IPF ancillary
total costs: Clinic (Worksheet B, part I,
column 1, line 90), Drugs Charged to
Patients (Worksheet B, part I, column 1,
line 73), Emergency (Worksheet B, part
I, column 1, line 91), Laboratory
(Worksheet B, part I, column 1, line 60)
and Radiology—Diagnostic (Worksheet
B, part I, column 1, line 54). We propose
to weight these two fixed percentages
(inpatient and ancillary) using the
proportion that each capital cost type
represents of total capital costs in the
proposed 2021-based IPF market basket.
We propose to then weight the fixed
percentages for hospital-based and
freestanding IPFs together using the
proportion of total capital costs each
provider type represents. For both
freestanding and hospital-based IPFs,
this is the same methodology used for
the 2016-based IPF market basket (84 FR
38432).
To disaggregate the Interest cost
weight, we determined the percent of
total interest costs for IPFs that are
attributable to government and
nonprofit facilities, which is hereafter
referred to as the ‘‘nonprofit
percentage,’’ as price pressures
associated with these types of interest
costs tend to differ from those for forprofit facilities. For the 2021-based IPF
market basket, we propose to use
interest costs data from Worksheet A–7
of the 2021 Medicare cost reports for
both freestanding and hospital-based
IPFs. We propose to determine the
percent of total interest costs that are
attributed to government and nonprofit
IPFs separately for hospital-based and
freestanding IPFs. We then propose to
weight the nonprofit percentages for
hospital-based and freestanding IPFs
together using the proportion of total
capital costs that each provider type
represents.
Table 3 provides the proposed
detailed capital cost share composition
estimated from the 2021 IPF Medicare
cost reports. These detailed capital cost
share composition percentages are
applied to the total Capital-Related cost
weight of 7.2 percent explained in detail
in sections III.A.3.a.(1)(h) and
III.A.3.a.(2) of this proposed rule.
TABLE 3—CAPITAL COST SHARE COMPOSITION FOR THE PROPOSED 2021-BASED IPF MARKET BASKET
Capital
cost share
composition
before lease
expense
allocation
(percent)
Depreciation .............................................................................................................................................................
Building and Fixed Equipment .........................................................................................................................
Movable Equipment ..........................................................................................................................................
Interest .....................................................................................................................................................................
Government/Nonprofit ......................................................................................................................................
For Profit ...........................................................................................................................................................
Lease .......................................................................................................................................................................
Other Capital-related costs ......................................................................................................................................
ddrumheller on DSK120RN23PROD with PROPOSALS2
* Detail may not add to total due to rounding.
(5) Proposed 2021-Based IPF Market
Basket Cost Categories and Weights
based IPF market basket compared to
the 2016-based IPF market basket.
Table 4 compares the cost categories
and weights for the proposed 2021-
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10APP2
55
40
16
17
11
6
20
8
Capital
cost share
composition
after lease
expense
allocation
(percent)
68
48
19
21
13
7
........................
12
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TABLE 4—PROPOSED 2021-BASED IPF MARKET BASKET COST WEIGHTS COMPARED TO 2016-BASED IPF MARKET
BASKET COST WEIGHTS
Proposed
2021-based
IPF market
basket cost
weight
Cost category
Total .........................................................................................................................................................................
Compensation ......................................................................................................................................................
Wages and Salaries ..................................................................................................................................
Employee Benefits ....................................................................................................................................
Utilities ..................................................................................................................................................................
Electricity and Other Non-Fuel Utilities .....................................................................................................
Fuel: Oil and Gas ......................................................................................................................................
Professional Liability Insurance ...........................................................................................................................
All Other Products and Services ..........................................................................................................................
All Other Products ............................................................................................................................................
Pharmaceuticals ........................................................................................................................................
Food: Direct Purchases .............................................................................................................................
Food: Contract Services ............................................................................................................................
Chemicals ..................................................................................................................................................
Medical Instruments ..................................................................................................................................
Rubber and Plastics ..................................................................................................................................
Paper and Printing Products .....................................................................................................................
Miscellaneous Products ............................................................................................................................
All Other Services .............................................................................................................................................
Labor-Related Services ................................................................................................................................
Professional Fees: Labor-related ..............................................................................................................
Administrative and Facilities Support Services .........................................................................................
Installation, Maintenance, and Repair Services ........................................................................................
All Other: Labor-related Services ..............................................................................................................
Nonlabor-Related Services ...........................................................................................................................
Professional Fees: Nonlabor-related .........................................................................................................
Financial Services .....................................................................................................................................
Telephone Services ...................................................................................................................................
All Other: Nonlabor-related Services ........................................................................................................
Capital-Related Costs ..........................................................................................................................................
Depreciation ......................................................................................................................................................
Building and Fixed Equipment ..................................................................................................................
Movable Equipment ...................................................................................................................................
Interest Costs ...................................................................................................................................................
Government/Nonprofit ...............................................................................................................................
For Profit ....................................................................................................................................................
Other Capital-Related Costs ............................................................................................................................
100.0
66.9
52.6
14.3
1.2
0.7
0.4
1.0
23.8
9.1
3.6
0.8
1.0
0.3
2.0
0.3
0.5
0.6
14.7
7.9
4.7
0.6
1.2
1.4
6.8
4.9
0.7
0.2
0.9
7.2
4.9
3.5
1.4
1.5
1.0
0.5
0.8
2016-based
IPF market
basket cost
weight
100.0
66.0
52.2
13.8
1.1
0.8
0.3
0.9
24.9
10.7
4.7
0.9
1.0
0.3
2.3
0.3
0.5
0.7
14.2
7.7
4.4
0.6
1.3
1.4
6.5
4.5
0.8
0.3
1.0
7.1
5.3
3.7
1.5
1.2
0.9
0.3
0.7
* Detail may not add to total due to rounding.
ddrumheller on DSK120RN23PROD with PROPOSALS2
b. Selection of Price Proxies
After developing the cost weights for
the proposed 2021-based IPF market
basket, we select the most appropriate
wage and price proxies currently
available to represent the rate of price
change for each expenditure category.
For the majority of the cost weights, we
base the price proxies on Bureau of
Labor Statistics (BLS) data and grouped
them into one of the following BLS
categories:
• Employment Cost Indexes (ECIs):
measure the rate of change in
employment wage rates and employer
costs for employee benefits per hour
worked. These indexes are fixed-weight
indexes and strictly measure the change
in wage rates and employee benefits per
hour. ECIs are superior to Average
Hourly Earnings (AHE) as price proxies
for input price indexes because they are
not affected by shifts in occupation or
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industry mix, and because they measure
pure price change and are available by
both occupational group and by
industry. The industry ECIs are based
on the NAICS and the occupational ECIs
are based on the Standard Occupational
Classification System (SOC).
• Producer Price Indexes (PPI):
measure the average change over time in
the selling prices received by domestic
producers for their output. The prices
included in the PPI are from the first
commercial transaction for many
products and some services (https://
www.bls.gov/ppi/).
• Consumer Price Indexes (CPIs):
measure the average change over time in
the prices paid by urban consumers for
a market basket of consumer goods and
services (https://www.bls.gov/cpi/). CPIs
are only used when the purchases are
similar to those of retail consumers
rather than purchases at the wholesale
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level, or if no appropriate PPIs are
available.
We evaluated the price proxies using
the criteria of reliability, timeliness,
availability, and relevance:
• Reliability: indicates that the index
is based on valid statistical methods and
has low sampling variability. Widely
accepted statistical methods ensure that
the data were collected and aggregated
in a way that can be replicated. Low
sampling variability is desirable because
it indicates that the sample reflects the
typical members of the population.
(Sampling variability is variation that
occurs by chance because only a sample
was surveyed rather than the entire
population.)
• Timeliness: implies that the proxy
is published regularly, preferably at
least once a quarter. The market baskets
are updated quarterly and, therefore, it
is important for the underlying price
proxies to be up-to-date, reflecting the
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most recent data available. We believe
that using proxies that are published
regularly (at least quarterly, whenever
possible) helps to ensure that we are
using the most recent data available to
update the market basket. We strive to
use publications that are disseminated
frequently, because we believe that this
is an optimal way to stay abreast of the
most current data available.
• Availability: means that the proxy is
publicly available. We prefer that our
proxies are publicly available because
this will help ensure that our market
basket updates are as transparent to the
public as possible. In addition, this
enables the public to be able to obtain
the price proxy data on a regular basis.
• Relevance: means that the proxy is
applicable and representative of the cost
category weight to which it is applied.
The CPIs, PPIs, and ECIs that we
selected to propose in this regulation
meet these criteria. Therefore, we
believe that they continue to be the best
measure of price changes for the cost
categories to which they would be
applied.
Table 13 lists all price proxies that we
propose to use for the 2021-based IPF
market basket. A detailed explanation of
the price proxies we propose for each
cost category weight is provided below.
(1) Price Proxies for the Operating
Portion of the Proposed 2021-Based IPF
Market Basket
(a) Wages and Salaries
There is not a published wage proxy
that we believe represents the
occupational distribution of workers in
IPFs. To measure wage price growth in
the proposed 2021-based IPF market
basket, we propose to apply a proxy
blend based on six occupational
subcategories within the Wages and
Salaries category, which would reflect
the IPF occupational mix, as was done
for the 2016-based IPF market basket.
We propose to use the National
Industry-Specific Occupational
Employment and Wage estimates for
NAICS 622200, Psychiatric & Substance
Abuse Hospitals, published by the BLS
Occupational Employment and Wage
Statistics (OEWS) program, as the data
source for the wage cost shares in the
wage proxy blend. We note that in the
spring of 2021, the Occupational
Employment Statistics (OES) program
began using the name Occupational
Employment and Wage Statistics
(OEWS) to better reflect the range of
data available from the program. Data
released on or after March 31, 2021
reflect the new program name. We
propose to use May 2021 OEWS data.
Detailed information on the
methodology for the national industryspecific occupational employment and
wage estimates survey can be found at
https://www.bls.gov/oes/current/oes_
tec.htm. For the 2016-based IPF market
basket, we used May 2016 OES data.
Based on the OEWS data, there are six
wage subcategories: Management;
NonHealth Professional and Technical;
Health Professional and Technical;
Health Service; NonHealth Service; and
Clerical. Table 5 lists the 2021
occupational assignments for the six
wage subcategories; these are the same
occupational groups used in the 2016based IPF market basket.
TABLE 5—2021 OCCUPATIONAL ASSIGNMENTS FOR IPF WAGE BLEND
[2021 Occupational Groupings]
Group 1
Management
11–0000 ............
Management Occupations.
Group 2
13–0000
15–0000
19–0000
23–0000
25–0000
27–0000
NonHealth Professional & Technical
............
............
............
............
............
............
Business and Financial Operations Occupations.
Computer and Mathematical Occupations.
Life, Physical, and Social Science Occupations.
Legal Occupations.
Educational Instruction and Library Occupations.
Arts, Design, Entertainment, Sports, and Media Occupations.
ddrumheller on DSK120RN23PROD with PROPOSALS2
Group 3
29–1021
29–1031
29–1051
29–1071
29–1122
29–1123
29–1125
29–1126
29–1127
29–1129
29–1141
29–1171
29–1215
29–1216
29–1223
29–1229
29–1292
29–1299
Health Professional & Technical
............
............
............
............
............
............
............
............
............
............
............
............
............
............
............
............
............
............
Dentists, General.
Dietitians and Nutritionists.
Pharmacists.
Physician Assistants.
Occupational Therapists.
Physical Therapists.
Recreational Therapists.
Respiratory Therapists.
Speech-Language Pathologists.
Therapists, All Other.
Registered Nurses.
Nurse Practitioners.
Family Medicine Physicians.
General Internal Medicine Physicians.
Psychiatrists.
Physicians, All Other.
Dental Hygienists.
Healthcare Diagnosing or Treating Practitioners, All Other.
Group 4
21–0000
29–2010
29–2034
29–2042
29–2051
Health Service
............
............
............
............
............
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Community and Social Service Occupations.
Clinical Laboratory Technologists and Technicians.
Radiologic Technologists and Technicians.
Emergency Medical Technicians.
Dietetic Technicians.
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TABLE 5—2021 OCCUPATIONAL ASSIGNMENTS FOR IPF WAGE BLEND—Continued
[2021 Occupational Groupings]
Group 1
29–2052
29–2053
29–2061
29–2072
29–2099
29–9021
29–9099
31–0000
Management
............
............
............
............
............
............
............
............
Pharmacy Technicians.
Psychiatric Technicians.
Licensed Practical and Licensed Vocational Nurses.
Medical Records Specialists.
Health Technologists and Technicians, All Other.
Health Information Technologists and Medical Registrars.
Healthcare Practitioners and Technical Workers, All Other.
Healthcare Support Occupations.
Group 5
33–0000
35–0000
37–0000
39–0000
41–0000
47–0000
49–0000
51–0000
53–0000
NonHealth Service
............
............
............
............
............
............
............
............
............
Protective Service Occupations.
Food Preparation and Serving Related Occupations.
Building and Grounds Cleaning and Maintenance Occupations.
Personal Care and Service Occupations.
Sales and Related Occupations.
Construction and Extraction Occupations.
Installation, Maintenance, and Repair Occupations.
Production Occupations.
Transportation and Material Moving Occupations.
Group 6
Clerical
43–0000 ............
Office and Administrative Support Occupations.
Total expenditures by occupation
(that is, occupational assignment) were
calculated by taking the OEWS number
of employees multiplied by the OEWS
annual average salary. These
expenditures were aggregated based on
the six groups in Table 5. We next
calculated the proportion of each
group’s expenditures relative to the total
expenditures of all six groups. These
proportions, listed in Table 6, represent
the weights used in the wage proxy
blend. We then propose to use the
published wage proxies in Table 6 for
each of the six groups (that is, wage
subcategories) as we believe these six
price proxies are the most technically
appropriate indices available to measure
the price growth of the Wages and
Salaries cost category. These are the
same price proxies used in the 2016based IPF market basket (84 FR 38437).
TABLE 6—PROPOSED 2021-BASED IPF MARKET BASKET WAGE PROXY BLEND
Proposed
2021-based
wage blend
weights
(percent)
Wage subcategory
Healthcare Professional and
Technical.
Healthcare
Service.
NonHealthcare
Service.
NonHealthcare
Professional
and Technical.
Management ....
ddrumheller on DSK120RN23PROD with PROPOSALS2
BLS Series ID
34.9
ECI for Wages and Salaries for All Civilian workers in Hospitals
CIU1026220000000I.
34.4
36.3
CIU1026200000000I.
7.5
8.9
7.3
7.0
ECI for Wages and Salaries for All Civilian workers in
Healthcare and Social Assistance.
ECI for Wages and Salaries for Private Industry workers in
Service Occupations.
ECI for Wages and Salaries for Private Industry workers in Professional, Scientific, and Technical Services.
7.8
6.8
CIU2020000110000I.
6.1
6.1
ECI for Wages and Salaries for Private industry workers in
Management, Business, and Financial.
ECI for Wages and Salaries for Private Industry workers in Office and Administrative Support.
100.0
100.0
A comparison of the yearly changes
from FY 2021 to FY 2024 for the
proposed 2021-based IPF wage blend
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Price proxy
36.9
Administrative
Support and
Clerical.
Total ..........
2016-based
wage blend
weights
(percent)
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and the 2016-based IPF wage blend is
shown in Table 7. The average annual
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CIU2020000300000I.
CIU2025400000000I.
CIU2020000220000I.
growth rate is the same for both price
proxies over 2021–2024.
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TABLE 7—FISCAL YEAR GROWTH IN THE PROPOSED 2021-BASED IPF WAGE PROXY BLEND AND 2016-BASED IPF WAGE
PROXY BLEND
2021
Proposed 2021-based IPF Wage Proxy Blend ...........................................................
2016-based IPF Wage Proxy Blend ............................................................................
2022
3.0
3.1
2023
5.6
5.6
5.1
5.2
2024
Average
2021–
2024
3.7
3.7
4.4
4.4
** Source: IHS Global Inc., 4th Quarter 2022 forecast with historical data through 3rd Quarter 2022.
(b) Employee Benefits
To measure benefits price growth in
the proposed 2021-based IPF market
basket, we propose to apply a benefits
proxy blend based on the same six
subcategories and the same six blend
weights for the wage proxy blend. These
subcategories and blend weights are
listed in Table 8.
The benefit ECIs, listed in Table 8, are
not publicly available. Therefore, an
‘‘ECIs for Total Benefits’’ is calculated
using publicly available ‘‘ECIs for Total
Compensation’’ for each subcategory
and the relative importance of wages
within that subcategory’s total
compensation. This is the same benefits
ECI methodology that we implemented
in our 2016-based IPF market basket as
well as used in the IPPS, SNF, Home
Health Agency (HHA), IRF, LTCH, and
End-Stage Renal Disease (ESRD) market
baskets. We believe that the six price
proxies listed in Table 8 are the most
technically appropriate indices to
measure the price growth of the
Employee Benefits cost category in the
proposed 2021-based HHA IPF market
basket.
TABLE 8—PROPOSED 2021-BASED IPF MARKET BASKET BENEFITS PROXY BLEND AND 2016-BASED IPF BENEFIT PROXY
BLEND
Proposed
2021-based
benefit blend
weight
(percent)
Wage subcategory
2016-based
benefit blend
weight
(percent)
Price proxy
Healthcare Professional and Technical.
Healthcare Service ..........................
36.9
34.9
ECI for Total Benefits for All Civilian workers in Hospitals.
34.4
36.3
NonHealthcare Service ....................
7.5
8.9
NonHealthcare Professional and
Technical.
Management ....................................
7.3
7.0
7.8
6.8
Administrative Support and Clerical
6.1
6.1
ECI for Total Benefits for All Civilian workers in Healthcare and Social
Assistance.
ECI for Total Benefits for Private Industry workers in Service Occupations.
ECI for Total Benefits for Private Industry workers in Professional, Scientific, and Technical Services.
ECI for Total Benefits for Private industry workers in Management,
Business, and Financial.
ECI for Total Benefits for Private Industry workers in Office and Administrative Support.
100.0
100.0
Total ..........................................
A comparison of the yearly changes
from FY 2021 to FY 2024 for the
proposed 2021-based IPF benefit proxy
blend and the 2016-based IPF benefit
proxy is shown in Table 9. The average
annual growth rate is the same for both
price proxies over 2021 through 2024.
TABLE 9—FISCAL YEAR GROWTH IN THE PROPOSED 2021-BASED IPF BENEFIT PROXY BLEND AND 2016-BASED IPF
BENEFIT PROXY BLEND
2021
Proposed 2021-based IPF Benefit Proxy Blend ..........................................................
2016-based IPF Benefit Proxy Blend ..........................................................................
2022
2.4
2.4
4.4
4.4
2023
4.4
4.4
2024
3.6
3.6
Average
2021–
2024
3.7
3.7
ddrumheller on DSK120RN23PROD with PROPOSALS2
Source: IHS Global Inc., 4th Quarter 2022 forecast with historical data through 3rd Quarter 2022.
(c) Electricity and Other Non-Fuel
Utilities
We propose to use the PPI Commodity
Index for Commercial Electric Power
(BLS series code WPU0542) to measure
the price growth of this cost category
(which we propose to rename from
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Electricity to Electricity and Other NonFuel Utilities). This is the same price
proxy used in the 2016-based IPF
market basket (84 FR 38438).
(d) Fuel: Oil and Gas
Similar to the 2016-based IPF market
basket, for the 2021-based IPF market
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basket, we propose to use a blend of the
PPI for Petroleum Refineries and the PPI
Commodity for Natural Gas. Our
analysis of the Bureau of Economic
Analysis’ 2012 Benchmark Input-Output
data (use table before redefinitions,
purchaser’s value for NAICS 622000
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[Hospitals]), shows that Petroleum
Refineries expenses account for
approximately 90 percent and Natural
Gas expenses account for approximately
10 percent of Hospitals’ (NAICS 622000)
total Fuel: Oil and Gas expenses.
Therefore, we propose to use a blend of
90 percent of the PPI for Petroleum
Refineries (BLS series code
PCU324110324110) and 10 percent of
the PPI Commodity Index for Natural
Gas (BLS series code WPU0531) as the
price proxy for this cost category. This
is the same blend that was used for the
2016-based IPF market basket (84 FR
38438).
(f) Pharmaceuticals
We propose to use the PPI for
Pharmaceuticals for Human Use,
Prescription (BLS series code
WPUSI07003) to measure the price
growth of this cost category. This is the
same proxy used in the 2016-based IPF
market basket (84 FR 38438).
(e) Professional Liability Insurance
We propose to use the CMS Hospital
Professional Liability Index to measure
changes in PLI premiums. To generate
this index, we collect commercial
insurance premiums for a fixed level of
coverage while holding non-price
factors constant (such as a change in the
level of coverage). This is the same
proxy used in the 2016-based IPF
market basket (84 FR 38438).
(h) Food: Contract Purchases
We propose to use the CPI for Food
Away From Home (BLS series code
CUUR0000SEFV) to measure the price
growth of this cost category. This is the
same proxy used in the 2016-based IPF
market basket (84 FR 38438).
(g) Food: Direct Purchases
We propose to use the PPI for
Processed Foods and Feeds (BLS series
code WPU02) to measure the price
growth of this cost category. This is the
same proxy used in the 2016-based IPF
market basket (84 FR 38438).
(i) Chemicals
Similar to the 2016-based IPF market
basket, we propose to use a four-part
blended PPI as the proxy for the
chemical cost category in the proposed
2021-based IPF market basket. The
proposed blend is composed of the PPI
for Industrial Gas Manufacturing,
Primary Products (BLS series code
PCU325120325120P), the PPI for Other
Basic Inorganic Chemical
Manufacturing (BLS series code
PCU32518–32518-), the PPI for Other
Basic Organic Chemical Manufacturing
(BLS series code PCU32519–32519-),
and the PPI for Other Miscellaneous
Chemical Product Manufacturing (BLS
series code PCU325998325998). For the
proposed 2021-based IPF market basket,
we propose to derive the weights for the
PPIs using the 2012 Benchmark I–O
data.
Table 10 shows the weights for each
of the four PPIs used to create the
proposed blended Chemical proxy for
the proposed 2021-based IPF market
basket. This is the same blend that was
used for the 2016-based IPF market
basket (84 FR 38439).
TABLE 10—BLENDED CHEMICAL PPI WEIGHTS
Proposed
2021-based
IPF weights
(percent)
Name
PPI
PPI
PPI
PPI
for
for
for
for
Industrial Gas Manufacturing ......................................................................................................................
Other Basic Inorganic Chemical Manufacturing .........................................................................................
Other Basic Organic Chemical Manufacturing ............................................................................................
Other Miscellaneous Chemical Product Manufacturing ..............................................................................
(j) Medical Instruments
We propose to use a blended price
proxy for the Medical Instruments
category, as shown in Table 11. The
2012 Benchmark I–O data shows the
majority of medical instruments and
supply costs are for NAICS 339112—
Surgical and medical instrument
manufacturing costs (approximately 56
percent) and NAICS 339113—Surgical
appliance and supplies manufacturing
costs (approximately 43 percent).
Therefore, we propose to use a blend of
these two price proxies. To proxy the
price changes associated with NAICS
339112, we propose to use the PPI for
Surgical and medical instruments (BLS
series code WPU1562). This is the same
price proxy we used in the 2016-based
IPF market basket. To proxy the price
changes associated with NAICS 339113,
we propose to use a 50/50 blend of the
PPI for Medical and surgical appliances
and supplies (BLS series code
19
13
60
8
NAICS
325120
325180
325190
325998
WPU1563) and the PPI for
Miscellaneous products, Personal safety
equipment and clothing (BLS series
code WPU1571). We propose to include
the latter price proxy as it would reflect
personal protective equipment
including but not limited to face shields
and protective clothing. The 2012
Benchmark I–O data does not provide
specific expenses for these products;
however, we recognize that this category
reflects costs faced by IPFs.
TABLE 11—BLENDED MEDICAL INSTRUMENTS PPI WEIGHTS
Proposed
2021-based
IPF weights
(percent)
ddrumheller on DSK120RN23PROD with PROPOSALS2
Name
PPI—Commodity—Surgical and medical instruments ............................................................................................
PPI—Commodity—Medical and surgical appliances and supplies .........................................................................
PPI—Commodity—Miscellaneous products-Personal safety equipment and clothing ...........................................
(k) Rubber and Plastics
We propose to use the PPI for Rubber
and Plastic Products (BLS series code
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WPU07) to measure price growth of this
cost category. This is the same proxy
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56
22
22
NAICS
339112
........................
339113
used in the 2016-based IPF market
basket (84 FR 38439).
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(l) Paper and Printing Products
We propose to use the PPI for
Converted Paper and Paperboard
Products (BLS series code WPU0915) to
measure the price growth of this cost
category. This is the same proxy used in
the 2016-based IPF market basket (84 FR
38439).
(m) Miscellaneous Products
We propose to use the PPI for
Finished Goods Less Food and Energy
(BLS series code WPUFD4131) to
measure the price growth of this cost
category. This is the same proxy used in
the 2016-based IPF market basket (84 FR
38439).
(n) Professional Fees: Labor-Related
We propose to use the ECI for Total
Compensation for Private Industry
workers in Professional and Related
(BLS series code CIU2010000120000I) to
measure the price growth of this
category. This is the same proxy used in
the 2016-based IPF market basket (84 FR
38439).
(o) Administrative and Facilities
Support Services
We propose to use the ECI for Total
Compensation for Private Industry
workers in Office and Administrative
Support (BLS series code
CIU2010000220000I) to measure the
price growth of this category. This is the
same proxy used in the 2016-based IPF
market basket (84 FR 38439).
(p) Installation, Maintenance, and
Repair Services
We propose to use the ECI for Total
Compensation for Civilian workers in
Installation, Maintenance, and Repair
(BLS series code CIU1010000430000I) to
measure the price growth of this cost
category. This is the same proxy used in
the 2016-based IPF market basket (84 FR
38439).
ddrumheller on DSK120RN23PROD with PROPOSALS2
(q) All Other: Labor-Related Services
We propose to use the ECI for Total
Compensation for Private Industry
workers in Service Occupations (BLS
series code CIU2010000300000I) to
measure the price growth of this cost
category. This is the same proxy used in
the 2016-based IPF market basket (84 FR
38439).
(r) Professional Fees: Nonlabor-Related
We propose to use the ECI for Total
Compensation for Private Industry
workers in Professional and Related
(BLS series code CIU2010000120000I) to
measure the price growth of this
category. This is the same proxy used in
the 2016-based IPF market basket (84 FR
38439).
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(s) Financial Services
We propose to use the ECI for Total
Compensation for Private Industry
workers in Financial Activities (BLS
series code CIU201520A000000I) to
measure the price growth of this cost
category. This is the same proxy used in
the 2016-based IPF market basket (84 FR
38439).
(t) Telephone Services
We propose to use the CPI for
Telephone Services (BLS series code
CUUR0000SEED) to measure the price
growth of this cost category. This is the
same proxy used in the 2016-based IPF
market basket (84 FR 38439).
(u) All Other: Nonlabor-Related Services
We propose to use the CPI for All
Items Less Food and Energy (BLS series
code CUUR0000SA0L1E) to measure the
price growth of this cost category. This
is the same proxy used in the 2016based IPF market basket (84 FR 38439).
(2) Price Proxies for the Capital Portion
of the Proposed 2021-Based IPF Market
Basket
(a) Capital Price Proxies Prior to Vintage
Weighting
We propose to use the same price
proxies for the capital-related cost
categories in the proposed 2021-based
IPF market basket as were used in the
2016-based IPF market basket, which
are provided in Table 13 and described
below. Specifically, we propose to
proxy:
• Depreciation: Building and Fixed
Equipment cost category by BEA’s
Chained Price Index for Nonresidential
Construction for Hospitals and Special
Care Facilities (BEA Table 5.4.4. Price
Indexes for Private Fixed Investment in
Structures by Type).
• Depreciation: Movable Equipment
cost category by the PPI for Machinery
and Equipment (BLS series code
WPU11).
• Nonprofit Interest cost category by
the average yield on domestic municipal
bonds (Bond Buyer 20-bond index).
• For-profit Interest cost category by
the iBoxx AAA Corporate Bond Yield
index
• Other Capital-Related cost category
by the CPI–U for Rent of Primary
Residence (BLS series code
CUUS0000SEHA).
We believe these are the most
appropriate proxies for IPF capitalrelated costs that meet our selection
criteria of relevance, timeliness,
availability, and reliability. We also
propose to vintage weight the capital
price proxies for Depreciation and
Interest to capture the long-term
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21253
consumption of capital. This vintage
weighting method is similar to the
method used for the 2016-based IPF
market basket (84 FR 38440) and is
described below.
(b) Vintage Weights for Price Proxies
Because capital is acquired and paid
for over time, capital-related expenses
in any given year are determined by
both past and present purchases of
physical and financial capital. The
vintage-weighted capital-related portion
of the proposed 2021-based IPF market
basket is intended to capture the longterm consumption of capital, using
vintage weights for depreciation
(physical capital) and interest (financial
capital). These vintage weights reflect
the proportion of capital-related
purchases attributable to each year of
the expected life of building and fixed
equipment, movable equipment, and
interest. We propose to use vintage
weights to compute vintage-weighted
price changes associated with
depreciation and interest expenses.
Capital-related costs are inherently
complicated and are determined by
complex capital-related purchasing
decisions, over time, based on such
factors as interest rates and debt
financing. In addition, capital is
depreciated over time instead of being
consumed in the same period it is
purchased. By accounting for the
vintage nature of capital, we are able to
provide an accurate and stable annual
measure of price changes. Annual nonvintage price changes for capital are
unstable due to the volatility of interest
rate changes, and therefore, do not
reflect the actual annual price changes
for IPF capital-related costs. The capitalrelated component of the proposed
2021-based IPF market basket reflects
the underlying stability of the capitalrelated acquisition process.
The methodology used to calculate
the vintage weights for the proposed
2021-based IPF market basket is the
same as that used for the 2016-based IPF
market basket (84 FR 38439 through
38441) with the only difference being
the inclusion of more recent data. To
calculate the vintage weights for
depreciation and interest expenses, we
first need a time series of capital-related
purchases for building and fixed
equipment and movable equipment. We
found no single source that provides an
appropriate time series of capital-related
purchases by hospitals for all of the
above components of capital purchases.
The early Medicare cost reports did not
have sufficient capital-related data to
meet this need. Data we obtained from
the American Hospital Association
(AHA) do not include annual capital-
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related purchases. However, we are able
to obtain data on total expenses back to
1963 from the AHA. Consequently, we
propose to use data from the AHA Panel
Survey and the AHA Annual Survey to
obtain a time series of total expenses for
hospitals. We then propose to use data
from the AHA Panel Survey
supplemented with the ratio of
depreciation to total hospital expenses
obtained from the Medicare cost reports
to derive a trend of annual depreciation
expenses for 1963 through 2020, which
is the latest year of AHA data available.
We propose to separate these
depreciation expenses into annual
amounts of building and fixed
equipment depreciation and movable
equipment depreciation as determined
earlier. From these annual depreciation
amounts, we derive annual end-of-year
book values for building and fixed
equipment and movable equipment
using the expected life for each type of
asset category. While data is not
available that is specific to IPFs, we
believe this information for all hospitals
serves as a reasonable alternative for the
pattern of depreciation for IPFs.
To continue to calculate the vintage
weights for depreciation and interest
expenses, we also need to account for
the expected lives for Building and
Fixed Equipment, Movable Equipment,
and Interest for the proposed 2021based IPF market basket. We propose to
calculate the expected lives using
Medicare cost report data from
freestanding and hospital-based IPFs.
The expected life of any asset can be
determined by dividing the value of the
asset (excluding fully depreciated
assets) by its current year depreciation
amount. This calculation yields the
estimated expected life of an asset if the
rates of depreciation were to continue at
current year levels, assuming straightline depreciation. We propose to
determine the expected life of building
and fixed equipment separately for
hospital-based IPFs and freestanding
IPFs, and then weight these expected
lives using the percent of total capital
costs each provider type represents. We
propose to apply a similar method for
movable equipment. Using these
proposed methods, we determined the
average expected life of building and
fixed equipment to be equal to 25 years,
and the average expected life of movable
equipment to be equal to 12 years. For
the expected life of interest, we believe
vintage weights for interest should
represent the average expected life of
building and fixed equipment because,
based on previous research described in
the FY 1997 IPPS final rule (61 FR
46198), the expected life of hospital
debt instruments and the expected life
of buildings and fixed equipment are
similar. We note that for the 2016-based
IPF market basket, the expected life of
building and fixed equipment is 22
years, and the expected life of movable
equipment is 11 years (84 FR 38441).
Multiplying these expected lives by
the annual depreciation amounts results
in annual year-end asset costs for
building and fixed equipment and
movable equipment. We then calculate
a time series, beginning in 1964, of
annual capital purchases by subtracting
the previous year’s asset costs from the
current year’s asset costs.
For the building and fixed equipment
and movable equipment vintage
weights, we propose to use the real
annual capital-related purchase
amounts for each asset type to capture
the actual amount of the physical
acquisition, net of the effect of price
inflation. These real annual capitalrelated purchase amounts are produced
by deflating the nominal annual
purchase amount by the associated price
proxy as provided earlier in this
proposed rule. For the interest vintage
weights, we propose to use the total
nominal annual capital-related purchase
amounts to capture the value of the debt
instrument (including, but not limited
to, mortgages and bonds). Using these
capital-related purchase time series
specific to each asset type, we propose
to calculate the vintage weights for
building and fixed equipment, for
movable equipment, and for interest.
The vintage weights for each asset
type are deemed to represent the
average purchase pattern of the asset
over its expected life (in the case of
building and fixed equipment and
interest, 25 years, and in the case of
movable equipment, 12 years). For each
asset type, we used the time series of
annual capital-related purchase
amounts available from 2020 back to
1964. These data allow us to derive
thirty-three 25-year periods of capitalrelated purchases for building and fixed
equipment and interest, and forty-six
12-year periods of capital-related
purchases for movable equipment. For
each 25-year period for building and
fixed equipment and interest, or 12-year
period for movable equipment, we
calculate annual vintage weights by
dividing the capital-related purchase
amount in any given year by the total
amount of purchases over the entire 25year or 12-year period. This calculation
is done for each year in the 25-year or
12-year period and for each of the
periods for which we have data. We
then calculate the average vintage
weight for a given year of the expected
life by taking the average of these
vintage weights across the multiple
periods of data. The vintage weights for
the capital-related portion of the
proposed 2021-based IPF market basket
and the 2016-based IPF market basket
are presented in Table 12.
TABLE 12—PROPOSED 2021-BASED IPF MARKET BASKET AND 2016-BASED IPF MARKET BASKET VINTAGE WEIGHTS
FOR CAPITAL-RELATED PRICE PROXIES
Building and fixed equipment
ddrumheller on DSK120RN23PROD with PROPOSALS2
Year *
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Interest
2021-based 25
years
2016-based 22
years
2021-based 12
years
2016-based 11
years
2021-based 25
years
2016-based 22
years
0.031
0.032
0.033
0.034
0.035
0.036
0.035
0.036
0.036
0.039
0.040
0.040
0.042
0.042
0.035
0.036
0.038
0.038
0.040
0.042
0.042
0.041
0.042
0.043
0.046
0.047
0.048
0.049
0.066
0.068
0.071
0.076
0.080
0.082
0.084
0.088
0.091
0.094
0.098
0.101
........................
........................
0.071
0.075
0.080
0.085
0.087
0.091
0.095
0.099
0.102
0.105
0.110
........................
........................
........................
0.018
0.019
0.021
0.023
0.024
0.026
0.026
0.028
0.029
0.033
0.035
0.037
0.040
0.042
0.021
0.023
0.025
0.026
0.029
0.031
0.033
0.033
0.036
0.038
0.042
0.045
0.048
0.052
1 ...............................................................
2 ...............................................................
3 ...............................................................
4 ...............................................................
5 ...............................................................
6 ...............................................................
7 ...............................................................
8 ...............................................................
9 ...............................................................
10 .............................................................
11 .............................................................
12 .............................................................
13 .............................................................
14 .............................................................
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TABLE 12—PROPOSED 2021-BASED IPF MARKET BASKET AND 2016-BASED IPF MARKET BASKET VINTAGE WEIGHTS
FOR CAPITAL-RELATED PRICE PROXIES—Continued
Building and fixed equipment
Year *
15
16
17
18
19
20
21
22
23
24
25
Movable equipment
Interest
2021-based 25
years
2016-based 22
years
2021-based 12
years
2016-based 11
years
2021-based 25
years
2016-based 22
years
.............................................................
.............................................................
.............................................................
.............................................................
.............................................................
.............................................................
.............................................................
.............................................................
.............................................................
.............................................................
.............................................................
0.042
0.043
0.044
0.045
0.045
0.045
0.045
0.045
0.045
0.045
0.044
0.050
0.050
0.051
0.053
0.053
0.053
0.052
0.052
........................
........................
........................
........................
........................
........................
........................
........................
........................
........................
........................
........................
........................
........................
........................
........................
........................
........................
........................
........................
........................
........................
........................
........................
........................
0.044
0.046
0.049
0.052
0.054
0.055
0.057
0.058
0.060
0.061
0.062
0.055
0.057
0.060
0.065
0.068
0.069
0.070
0.072
........................
........................
........................
Total ..................................................
1.000
1.000
1.000
1.000
1.000
1.000
Note: Numbers may not add to total due to rounding.
* Year 25 is applied to the most recent data point when creating the vintage-weighted price proxies.
The process of creating vintageweighted price proxies requires
applying the vintage weights to the
price proxy index where the last applied
vintage weight in Table 12 is applied to
the most recent data point. We have
provided on the CMS website an
example of how the vintage weighting
price proxies are calculated, using
example vintage weights and example
price indices. The example can be found
at https://www.cms.gov/ResearchStatistics-Data-and-Systems/StatisticsTrends-and-Reports/
MedicareProgramRatesStats/
MarketBasketResearch.html in the zip
file titled ‘‘Weight Calculations as
described in the IPPS FY 2010 Proposed
Rule.’’
(3) Summary of Price Proxies of the
Proposed 2021-Based IPF Market Basket
Table 13 shows both the operating
and capital price proxies for the
proposed 2021-based IPF market basket.
ddrumheller on DSK120RN23PROD with PROPOSALS2
TABLE 13—PRICE PROXIES FOR THE PROPOSED 2021-BASED IPF MARKET BASKET
Cost description
Price proxies
Total ..........................................................
Compensation ...........................................
Wages and Salaries ..........................
Employee Benefits .............................
Utilities ......................................................
Electricity and Other Non-Fuel Utilities.
Fuel: Oil and Gas ..............................
Professional Liability Insurance ................
Malpractice ........................................
All Other Products and Services ..............
All Other Products ....................................
Pharmaceuticals ................................
Food: Direct Purchases .....................
Food: Contract Services ....................
Chemicals ..........................................
Medical Instruments ..........................
Rubber and Plastics ..........................
Paper and Printing Products .............
Miscellaneous Products .....................
All Other Services .....................................
Labor-Related Services ............................
Professional Fees: Labor-related ......
Administrative and Facilities Support
Services.
Installation, Maintenance & Repair
Services.
All Other: Labor-related Services ......
Nonlabor-Related Services .......................
Professional Fees: Nonlabor-related
Financial Services .............................
Telephone Services ...........................
All Other: Nonlabor-related Services
Capital-Related Costs ...............................
Depreciation ..............................................
.......................................................................................................................................
.......................................................................................................................................
Blended Wages and Salaries Price Proxy ...................................................................
Blended Employee Benefits Price Proxy .....................................................................
.......................................................................................................................................
PPI for Commercial Electric Power .............................................................................
100.0
66.9
52.6
14.3
1.2
0.7
Blend of PPIs * .............................................................................................................
.......................................................................................................................................
CMS Hospital Professional Liability Insurance Premium Index ..................................
.......................................................................................................................................
.......................................................................................................................................
PPI for Pharmaceuticals for Human Use, Prescription ...............................................
PPI for Processed Foods and Feeds ..........................................................................
CPI–U for Food Away From Home ..............................................................................
Blend of PPIs* ..............................................................................................................
Blend of PPIs* ..............................................................................................................
PPI for Rubber and Plastic Products ...........................................................................
PPI for Converted Paper and Paperboard Products ...................................................
PPI for Finished Goods Less Food and Energy ..........................................................
.......................................................................................................................................
.......................................................................................................................................
ECI for Total compensation for Private industry workers in Professional and related
ECI for Total compensation for Private industry workers in Office and administrative
support.
ECI for Total compensation for Civilian workers in Installation, maintenance, and repair.
ECI for Total compensation for Private industry workers in Service occupations ......
.......................................................................................................................................
ECI for Total compensation for Private industry workers in Professional and related
ECI for Total compensation for Private industry workers in Financial activities .........
CPI–U for Telephone Services ....................................................................................
CPI–U for All Items Less Food and Energy ................................................................
.......................................................................................................................................
.......................................................................................................................................
0.4
1.0
1.0
23.8
9.1
3.6
0.8
1.0
0.3
2.0
0.3
0.5
0.6
14.7
7.9
4.7
0.6
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6.8
4.9
0.7
0.2
0.9
7.2
4.9
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TABLE 13—PRICE PROXIES FOR THE PROPOSED 2021-BASED IPF MARKET BASKET—Continued
Cost description
Price proxies
Building and Fixed Equipment ...........
Movable Equipment ...........................
Interest Costs ............................................
Government/Nonprofit .......................
For Profit ............................................
Other Capital-Related Costs .....................
Weight
BEA chained price index for nonresidential construction for hospitals and special
care facilities—vintage weighted (25 years).
PPI for machinery and equipment—vintage weighted (12 years) ...............................
.......................................................................................................................................
Average yield on domestic municipal bonds (Bond Buyer 20 bonds)—vintage
weighted (25 years).
Average Yield on iBoxx AAA Corporate Bonds—vintage weighted (25 years) ..........
CPI–U for Rent of primary residence ..........................................................................
3.5
1.4
1.5
1.0
0.5
0.8
Note: Totals may not sum to 100.0 percent due to rounding.
* Details on the series and weight for each price proxy used in the PPI blends is provided in section III.A.3.b.
We invite public comment on our
proposal to rebase and revise the IPF
market basket to reflect a 2021 base
year.
4. Proposed FY 2024 Market Basket
Update and Productivity Adjustment
a. Proposed FY 2024 Market Basket
Update
For FY 2024 (that is, beginning
October 1, 2023 and ending September
30, 2024), we propose to use an estimate
of the proposed 2021-based IPF market
basket increase factor to update the IPF
PPS base payment rate. Consistent with
historical practice, we estimate the
market basket update for the IPF PPS
based on IHS Global Inc.’s (IGI) forecast.
IGI is a nationally recognized economic
and financial forecasting firm with
which CMS contracts to forecast the
components of the market baskets.
Using IGI’s fourth quarter 2022
forecast with historical data through the
third quarter of 2022, the projected
proposed 2021-based IPF market basket
increase factor for FY 2024 is 3.2
percent. We propose that if more recent
data are subsequently available (for
example, a more recent estimate of the
market basket increase factor) we would
use such data, to determine the FY 2024
update in the final rule. For comparison,
the current 2016-based IPF market
basket is also projected to increase by
3.2 percent in FY 2024 based on IGI’s
fourth quarter 2022 forecast. Table 14
compares the proposed 2021-based IPF
market basket and the 2016-based IPF
market basket percent changes.
TABLE 14—PROPOSED 2021-BASED IPF MARKET BASKET AND 2016-BASED IPF MARKET BASKET PERCENT CHANGES,
FY 2019 THROUGH FY 2026
Proposed 2021-based
IPF market basket
index percent change
Fiscal year (FY)
2016-based IPF
market basket index
percent change
Historical data:
FY 2019 ............................................................................................................................
FY 2020 ............................................................................................................................
FY 2021 ............................................................................................................................
FY 2022 ............................................................................................................................
2.4
2.1
2.8
5.3
2.5
2.2
2.9
5.3
Average 2019–2022 ..............................................................................................
3.2
3.2
............................................................................................................................
............................................................................................................................
............................................................................................................................
............................................................................................................................
4.6
3.2
2.8
2.7
4.6
3.2
2.8
2.8
Average 2023–2026 ..............................................................................................
3.3
3.4
Forecast:
FY
FY
FY
FY
2023
2024
2025
2026
Note: These market basket percent changes do not include any further adjustments as may be statutorily required. Source: IHS Global Inc.
4th quarter 2022 forecast.
ddrumheller on DSK120RN23PROD with PROPOSALS2
b. Proposed Productivity Adjustment
Section 1886(s)(2)(A)(i) of the Act
requires the application of the
productivity adjustment described in
section 1886(b)(3)(B)(xi)(II) of the Act to
the IPF PPS for the RY beginning in
2012 (that is, a RY that coincides with
a FY) and each subsequent RY. The
statute defines the productivity
adjustment to be equal to the 10-year
moving average of changes in annual
economy-wide, private nonfarm
business multifactor productivity (as
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projected by the Secretary for the 10year period ending with the applicable
FY, year, cost reporting period, or other
annual period) (the ‘‘productivity
adjustment’’). The United States
Department of Labor’s Bureau of Labor
Statistics (BLS) publishes the official
measures of productivity for the United
States economy. 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.
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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
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unchanged. We refer readers to
www.bls.gov for the BLS historical
published TFP data. A complete
description of IGI’s TFP projection
methodology is available on the CMS
website at https://www.cms.gov/
research-statistics-data-and-systems/
statistics-trends-and-reports/
medicareprogramratesstats/
marketbasketresearch. In addition, in
the FY 2022 IPF final rule (86 FR
42611), we noted that effective with FY
2022 and forward, CMS changed the
name of this adjustment to refer to it as
the productivity adjustment rather than
the MFP adjustment.
Using IGI’s fourth quarter 2022
forecast, the 10-year moving average
growth of TFP for FY 2024 is projected
to be 0.2 percent. Thus, in accordance
with section 1886(s)(2)(A)(i) of the Act,
we propose to calculate the FY 2024
market basket update, which is used to
determine the applicable percentage
increase for the IPF payments, using
IGI’s fourth quarter 2022 forecast of the
proposed 2021-based IPF market basket.
We proposed to then reduce this
percentage increase by the estimated
productivity adjustment for FY 2024 of
0.2 percentage point (the 10-year
moving average growth of TFP for the
period ending FY 2024 based on IGI’s
fourth quarter 2022 forecast). Therefore,
the proposed FY 2024 IPF update is
equal to 3.0 percent (3.2 percent market
basket update reduced by the 0.2
percentage point productivity
adjustment). Furthermore, we propose
that if more recent data become
available after the publication of the
proposed rule and before the
publication of the final rule (for
example, a more recent estimate of the
market basket increase factor and/or
productivity adjustment), we would use
such data, if appropriate, to determine
the FY 2024 market basket update and
productivity adjustment in the final
rule.
We invite public comment on our
proposals for the FY 2024 market basket
update and productivity adjustment.
5. Proposed Labor-Related Share for FY
2024
Due to variations in geographic wage
levels and other labor-related costs, we
believe that payment rates under the IPF
PPS should continue to be adjusted by
a geographic wage index, which would
apply to the labor-related portion of the
Federal per diem base rate (hereafter
referred to as the labor-related share).
The labor-related share is determined by
identifying the national average
proportion of total costs that are related
to, influenced by, or vary with the local
labor market. We propose to continue to
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classify a cost category as labor-related
if the costs are labor intensive and vary
with the local labor market.
We propose to include in the laborrelated share the sum of the relative
importance of 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
portion of the Capital-Related cost
weight from the proposed 2021-based
IPF market basket. These are the same
categories as the 2016-based IPF market
basket.
Similar to the 2016-based IPF market
basket, the proposed 2021-based IPF
market basket includes two cost
categories for nonmedical Professional
fees (including but not limited to,
expenses for legal, accounting, and
engineering services). These are
Professional Fees: Labor-related and
Professional Fees: Nonlabor-related. For
the proposed 2021-based IPF market
basket, we propose to estimate the laborrelated percentage of non-medical
professional fees (and assign these
expenses to the Professional Fees:
Labor-related services cost category)
based on the same method that was
used to determine the labor-related
percentage of professional fees in the
2016-based IPF market basket.
As was done in the 2016-based IPF
market basket, we propose to determine
the proportion of legal, accounting and
auditing, engineering, and management
consulting services that meet our
definition of labor-related services based
on a survey of hospitals conducted by
CMS in 2008. We notified the public of
our intent to conduct this survey on
December 9, 2005 (70 FR 73250) and did
not receive any public comments in
response to the notice (71 FR 8588). A
discussion of the composition of the
survey and post-stratification can be
found in the FY 2010 IPPS/LTCH PPS
final rule (74 FR 43850 through 43856).
Based on the weighted results of the
survey, we determined that hospitals
purchase, on average, the following
portions of contracted professional
services outside of their local labor
market:
• 34 percent of accounting and
auditing services.
• 30 percent of engineering services.
• 33 percent of legal services.
• 42 percent of management
consulting services.
We propose to apply each of these
percentages to the respective 2012
Benchmark I–O cost category
underlying the professional fees cost
category to determine the Professional
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Fees: Nonlabor-related costs. The
Professional Fees: Labor-related costs
were determined to be the difference
between the total costs for each
Benchmark I–O category and the
Professional Fees: Nonlabor-related
costs. This is the same methodology that
we used to separate the 2016-based IPF
market basket professional fees category
into Professional Fees: Labor-related
and Professional Fees: Nonlabor-related
cost categories (84 FR 38445).
Effective for transmittal 18, (https://
www.cms.gov/Regulations-andGuidance/Guidance/Transmittals/
Transmittals/r18p240i) the hospital
Medicare cost report (CMS Form 2552–
10, OMB No. 0938–0050) is collecting
information on whether a hospital
purchased professional services (for
example, legal, accounting, tax
preparation, bookkeeping, payroll,
advertising, and/or management/
consulting services) from an unrelated
organization and if the majority of these
expenses were purchased from
unrelated organizations located outside
of the main hospital’s local area labor
market. We encourage all providers to
provide this information so we can
potentially use these data in future
rulemaking to determine the laborrelated share.
In the proposed 2021-based IPF
market basket, nonmedical professional
fees that were subject to allocation
based on these survey results represent
3.3 percent of total costs (and are
limited to those fees related to
Accounting & Auditing, Legal,
Engineering, and Management
Consulting services). Based on our
survey results, we proposed to
apportion 2.1 percentage points of the
3.3 percentage point figure into the
Professional Fees: Labor-related share
cost category and designate the
remaining 1.2 percentage point into the
Professional Fees: Nonlabor-related cost
category.
In addition to the professional
services listed, for the proposed 2021based IPF market basket, we propose to
allocate a proportion of the Home
Office/Related Organization Contract
Labor cost weight, calculated using the
Medicare cost reports, into the
Professional Fees: Labor-related and
Professional Fees: Nonlabor-related cost
categories. We propose to classify these
expenses as labor-related and nonlaborrelated as many facilities are not located
in the same geographic area as their
home office and, therefore, do not meet
our definition for the labor-related share
that requires the services to be
purchased in the local labor market.
Similar to the 2016-based IPF market
basket, we propose for the 2021-based
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IPF market basket to use the Medicare
cost reports for both freestanding IPF
providers and hospital-based IPF
providers to determine the home office
labor-related percentages. The Medicare
cost report requires a hospital to report
information regarding their home office
provider. Using information on the
Medicare cost report, we then compare
the location of the IPF with the location
of the IPF’s home office. We propose to
classify an IPF with a home office
located in their respective labor market
if the IPF and its home office are located
in the same metropolitan statistical area
(MSA). We then determine the
proportion of the Home Office/Related
Organization Contract Labor cost weight
that should be allocated to the laborrelated share based on the percent of
total Medicare allowable costs for those
IPFs that had home offices located in
their respective local labor markets of
total Medicare allowable costs for IPFs
with a home office. We determined an
IPF’s and its home office’s MSA using
their zip code information from the
Medicare cost report. Using this
methodology, we determined that 46
percent of IPFs’ Medicare allowable
costs were for home offices located in
their respective local labor markets.
Therefore, we are allocating 46 percent
of the Home Office/Related
Organization Contract Labor cost weight
(2.1 percentage points = 4.7 percent
times 46 percent) to the Professional
Fees: Labor-related cost weight and 54
percent of the Home Office/Related
Organization Contract Labor cost weight
to the Professional Fees: Nonlaborrelated cost weight (2.5 percentage
points = 4.7 percent times 54 percent).
The same methodology was used for the
2016-based IPF market basket (84 FR
38445).
In summary, we apportioned 2.1
percentage points of the non-medical
professional fees and 2.1 percentage
points of the Home Office/Related
Organization Contract Labor cost weight
into the Professional Fees: LaborRelated cost category. This amount was
added to the portion of professional fees
that we already identified as laborrelated using the I–O data such as
contracted advertising and marketing
costs (approximately 0.5 percentage
point of total costs) resulting in a
Professional Fees: Labor-Related cost
weight of 4.7 percent.
As stated, we propose to include in
the labor-related share the sum of the
relative importance of Wages and
Salaries, Employee Benefits,
Professional Fees: Labor-Related,
Administrative and Facilities Support
Services, Installation, Maintenance, and
Repair Services, All Other: Labor-related
Services, and a portion of the CapitalRelated cost weight from the proposed
2021-based IPF market basket. The
relative importance reflects the different
rates of price change for these cost
categories between the base year (2021)
and FY 2024. Based on IHS Global Inc.
4th quarter 2022 forecast of the
proposed 2021-based IPF market basket,
the sum of the FY 2024 relative
importance for Wages and Salaries,
Employee Benefits, Professional Fees:
Labor-related, Administrative and
Facilities Support Services, Installation
Maintenance & Repair Services, and All
Other: Labor-related Services is 75.4
percent. The portion of Capital costs
that is influenced by the local labor
market is estimated to be 46 percent,
which is the same percentage applied to
the 2016-based IPF market basket. Since
the relative importance for Capital is 6.8
percent of the proposed 2021-based IPF
market basket in FY 2024, we took 46
percent of 6.8 percent to determine the
proposed labor-related share of Capital
for FY 2024 of 3.1 percent. Therefore,
we propose a total labor-related share
for FY 2024 of 78.5 percent (the sum of
75.4 percent for the operating cost and
3.1 percent for the labor-related share of
Capital). Table 15 shows the FY 2024
labor-related share using the proposed
2021-based IPF market basket relative
importance and the FY 2023 laborrelated share using the 2016-based IPF
market basket.
TABLE 15—PROPOSED FY 2024 IPF LABOR-RELATED SHARE AND FY 2023 IPF LABOR-RELATED SHARE
FY 2024 Labor-related
share based on
proposed 2021-based
IPF market basket 1
FY 2023 Final laborrelated share based
on 2016-based
IPF market basket 2
Wages and Salaries ................................................................................................................
Employee Benefits ...................................................................................................................
Professional Fees: Labor-related 3 ..........................................................................................
Administrative and Facilities Support Services .......................................................................
Installation, Maintenance and Repair Services .......................................................................
All Other: Labor-related Services ............................................................................................
53.3
14.2
4.7
0.6
1.2
1.4
53.2
13.5
4.3
0.6
1.3
1.5
Subtotal .............................................................................................................................
75.4
74.4
Labor-related portion of capital (46%) ..............................................................................
3.1
3.0
Total LRS ..........................................................................................................................
78.5
77.4
1 IHS
Global Inc. 4th quarter 2022 forecast.
on IHS Global Inc. 2nd quarter 2022 forecast as published in the Federal Register (87 FR 46851).
3 Includes all contract advertising and marketing costs and a portion of accounting, architectural, engineering, legal, management consulting,
and home office/related organization contract labor costs.
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2 Based
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The FY 2024 labor-related share using
the proposed 2021-based IPF market
basket is about 1.0 percentage point
higher than the FY 2023 labor-related
share using the 2016-based IPF market
basket. This higher labor-related share is
primarily due to the incorporation of the
2021 Medicare cost report data, which
increased the Compensation cost weight
by 0.9 percentage point compared to the
2016-based IPF market basket as shown
in Table 1 and Table 2 in section
III.A.3.a.(2) of this proposed rule. We
invite public comment on the proposed
labor-related share for FY 2024.
ddrumheller on DSK120RN23PROD with PROPOSALS2
B. Proposed Updates to the IPF PPS
Rates for FY Beginning October 1, 2023
The IPF PPS is based on a
standardized Federal per diem base rate
calculated from the IPF average per
diem costs and adjusted for budget
neutrality in the implementation year.
The Federal per diem base rate is used
as the standard payment per day under
the IPF PPS and is adjusted by the
patient-level and facility-level
adjustments that are applicable to the
IPF stay. A detailed explanation of how
we calculated the average per diem cost
appears in the November 2004 IPF PPS
final rule (69 FR 66926).
1. Determining the Standardized
Budget-Neutral Federal per Diem Base
Rate
Section 124(a)(1) of the BBRA
required that we implement the IPF PPS
in a budget-neutral manner. In other
words, the amount of total payments
under the IPF PPS, including any
payment adjustments, must be projected
to be equal to the amount of total
payments that would have been made if
the IPF PPS were not implemented.
Therefore, we calculated the budget
neutrality factor by setting the total
estimated IPF PPS payments to be equal
to the total estimated payments that
would have been made under the Tax
Equity and Fiscal Responsibility Act of
1982 (TEFRA) (Pub. L. 97–248)
methodology had the IPF PPS not been
implemented. A step-by-step
description of the methodology used to
estimate payments under the Tax Equity
and Fiscal Responsibility Act (TEFRA)
payment system appears in the
November 2004 IPF PPS final rule (69
FR 66926).
Under the IPF PPS methodology, we
calculated the final Federal per diem
base rate to be budget-neutral during the
IPF PPS implementation period (that is,
the 18-month period from January 1,
2005 through June 30, 2006) using a July
1 update cycle. We updated the average
cost per day to the midpoint of the IPF
PPS implementation period (October 1,
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2005), and this amount was used in the
payment model to establish the budgetneutrality adjustment.
Next, we standardized the IPF PPS
Federal per diem base rate to account
for the overall positive effects of the IPF
PPS payment adjustment factors by
dividing total estimated payments under
the TEFRA payment system by
estimated payments under the IPF PPS.
The information concerning this
standardization can be found in the
November 2004 IPF PPS final rule (69
FR 66932) and the RY 2006 IPF PPS
final rule (71 FR 27045). We then
reduced the standardized Federal per
diem base rate to account for the outlier
policy, the stop loss provision, and
anticipated behavioral changes. A
complete discussion of how we
calculated each component of the
budget neutrality adjustment appears in
the November 2004 IPF PPS final rule
(69 FR 66932 through 66933) and in the
RY 2007 IPF PPS final rule (71 FR 27044
through 27046). The final standardized
budget-neutral Federal per diem base
rate established for cost reporting
periods beginning on or after January 1,
2005 was calculated to be $575.95.
The Federal per diem base rate has
been updated in accordance with
applicable statutory requirements and
§ 412.428 through publication of annual
notices or proposed and final rules. A
detailed discussion on the standardized
budget-neutral Federal per diem base
rate and the ECT payment per treatment
appears in the FY 2014 IPF PPS update
notice (78 FR 46738 through 46740).
These documents are available on the
CMS website at https://www.cms.gov/
Medicare/Medicare-Fee-for-ServicePayment/InpatientPsychFacilPPS/
index.html.
IPFs must include a valid procedure
code for ECT services provided to IPF
beneficiaries in order to bill for ECT
services, as described in our Medicare
Claims Processing Manual, Chapter 3,
Section 190.7.3 (available at https://
www.cms.gov/Regulations-andGuidance/Guidance/Manuals/
Downloads/clm104c03.pdf.) There were
no changes to the ECT procedure codes
used on IPF claims as a result of the
final update to the ICD–10–PCS code set
for FY 2024. Addendum B to this
proposed rule shows the ECT procedure
codes for FY 2024 and is available on
our website at https://www.cms.gov/
Medicare/Medicare-Fee-for-ServicePayment/InpatientPsychFacilPPS/
tools.html.
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2. Proposed Update of the Federal per
Diem Base Rate and Electroconvulsive
Therapy Payment per Treatment
The current (FY 2023) Federal per
diem base rate is $865.63 and the ECT
payment per treatment is $372.67. For
the proposed FY 2024 Federal per diem
base rate, we applied the payment rate
update of 3.0 percent—that is, the 2021based IPF market basket increase for FY
2024 of 3.2 percent less the productivity
adjustment of 0.2 percentage point—and
the wage index budget-neutrality factor
of 1.0011 (as discussed in section IV.D.1
of this proposed rule) to the FY 2023
Federal per diem base rate of $865.63,
yielding a proposed Federal per diem
base rate of $892.58 for FY 2024.
Similarly, we applied the proposed 3.0
percent payment rate update and the
1.0011 wage index budget-neutrality
factor to the FY 2023 ECT payment per
treatment of $372.67, yielding a
proposed ECT payment per treatment of
$384.27 for FY 2024.
Section 1886(s)(4)(A)(i) of the Act
requires that for RY 2014 and each
subsequent RY, in the case of an IPF
that fails to report required quality data
with respect to such RY, the Secretary
will reduce any annual update to a
standard Federal rate for discharges
during the RY by 2.0 percentage points.
Therefore, we propose to apply a 2.0
percentage points reduction to the
Federal per diem base rate and the ECT
payment per treatment as follows:
• For IPFs that fail requirements
under the IPFQR Program, we would
apply a proposed 1.0 percent payment
rate update—that is, the proposed IPF
market basket increase for FY 2024 of
3.2 percent less the proposed
productivity adjustment of 0.2
percentage point for a proposed update
of 3.0 percent, and further reduced by
2.0 percentage points in accordance
with section 1886(s)(4)(A)(i) of the
Act—and the proposed wage index
budget-neutrality factor of 1.0011 to the
FY 2024 Federal per diem base rate of
$892.58, yielding a proposed Federal
per diem base rate of $875.25 for FY
2024.
• For IPFs that fail to meet
requirements under the IPFQR Program,
we would apply the proposed 1.0
percent annual payment rate update and
the proposed 1.0011 wage index budgetneutrality factor to the FY 2024 ECT
payment per treatment of $384.27
yielding a proposed ECT payment per
treatment of $376.81 for FY 2024.
Lastly, we propose that if more recent
data become available, we would use
such data, if appropriate, to determine
the FY 2024 Federal per diem base rate
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and ECT payment per treatment for the
final rule.
C. Proposed Updates to the IPF PPS
Patient-Level Adjustment Factors
1. Overview of the IPF PPS Adjustment
Factors
The IPF PPS payment adjustments
were derived from a regression analysis
of 100 percent of the FY 2002 Medicare
Provider and Analysis Review
(MedPAR) data file, which contained
483,038 cases. For a more detailed
description of the data file used for the
regression analysis, see the November
2004 IPF PPS final rule (69 FR 66935
through 66936). We propose to use the
existing regression-derived adjustment
factors established in 2005 for FY 2024.
However, we have used more recent
claims data to simulate payments to
finalize the outlier fixed dollar loss
threshold amount and to assess the
impact of the IPF PPS updates.
2. IPF PPS Patient-Level Adjustments
The IPF PPS includes payment
adjustments for the following patientlevel characteristics: Medicare Severity
Diagnosis Related Groups (MS–DRGs)
assignment of the patient’s principal
diagnosis, selected comorbidities,
patient age, and the variable per diem
adjustments.
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a. Proposed Update to MS–DRG
Assignment
We believe it is important to maintain
for IPFs the same diagnostic coding and
Diagnosis Related Group (DRG)
classification used under the IPPS for
providing psychiatric care. For this
reason, when the IPF PPS was
implemented for cost reporting periods
beginning on or after January 1, 2005,
we adopted the same diagnostic code set
(ICD–9–CM) and DRG patient
classification system (MS–DRGs) that
were utilized at the time under the IPPS.
In the RY 2009 IPF PPS notice (73 FR
25709), we discussed CMS’ effort to
better recognize resource use and the
severity of illness among patients. CMS
adopted the new MS–DRGs for the IPPS
in the FY 2008 IPPS final rule with
comment period (72 FR 47130). In the
RY 2009 IPF PPS notice (73 FR 25716),
we provided a crosswalk to reflect
changes that were made under the IPF
PPS to adopt the new MS–DRGs. For a
detailed description of the mapping
changes from the original DRG
adjustment categories to the current
MS–DRG adjustment categories, we
refer readers to the RY 2009 IPF PPS
notice (73 FR 25714).
The IPF PPS includes payment
adjustments for designated psychiatric
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DRGs assigned to the claim based on the
patient’s principal diagnosis. The DRG
adjustment factors were expressed
relative to the most frequently reported
psychiatric DRG in FY 2002, that is,
DRG 430 (psychoses). The coefficient
values and adjustment factors were
derived from the regression analysis
discussed in detail in the November 28,
2003 IPF proposed rule (68 FR 66923;
66928 through 66933) and the
November 15, 2004 IPF final rule (69 FR
66933 through 66960). Mapping the
DRGs to the MS–DRGs resulted in the
current 17 IPF MS–DRGs, instead of the
original 15 DRGs, for which the IPF PPS
provides an adjustment. For FY 2024,
we are not proposing any changes to the
IPF MS–DRG adjustment factors and are
retaining the existing IPF MS–DRG
adjustment factors.
In the FY 2015 IPF PPS final rule
published August 6, 2014 in the Federal
Register titled, ‘‘Inpatient Psychiatric
Facilities Prospective Payment
System—Update for FY Beginning
October 1, 2014 (FY 2015)’’ (79 FR
45945 through 45947), we finalized
conversions of the ICD–9–CM-based
MS–DRGs to ICD–10–CM/PCS-based
MS–DRGs, which were implemented on
October 1, 2015. As discussed in the FY
2015 IPF PPS proposed rule (79 FR
26047) in more detail, every year,
changes to the ICD–10–CM and the ICD–
10–PCS coding system are addressed in
the IPPS proposed and final rules. The
changes to the codes are effective
October 1 of each year and must be used
by acute care hospitals as well as other
providers to report diagnostic and
procedure information. In accordance
with § 412.428(e), the IPF PPS has
always incorporated ICD–10–CM and
ICD–10–PCS coding changes made in
the annual IPPS update and will
continue to do so. We will continue to
publish coding changes in a
Transmittal/Change Request, similar to
how coding changes are announced by
the IPPS and LTCH PPS. The coding
changes relevant to the IPF PPS are also
published in the IPF PPS proposed and
final rules, or in IPF PPS update notices.
Further information on the ICD–10–CM/
PCS MS–DRG conversion project can be
found on the CMS ICD–10–CM website
at https://www.cms.gov/Medicare/
Coding/ICD10/ICD-10-MS-DRGConversion-Project.html.
For FY 2024, we propose to continue
making the existing payment adjustment
for psychiatric diagnoses that group to
one of the existing 17 IPF MS–DRGs
listed in Addendum A. Addendum A is
available on our website at https://
www.cms.gov/Medicare/Medicare-Feefor-Service-Payment/
InpatientPsychFacilPPS/tools.html.
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Psychiatric principal diagnoses that do
not group to one of the 17 designated
MS–DRGs will still receive the Federal
per diem base rate and all other
applicable adjustments, but the payment
will not include an MS–DRG
adjustment.
The diagnoses for each IPF MS–DRG
will be updated as of October 1, 2023,
using the final FY 2024 IPPS ICD–10–
CM/PCS code sets. The FY 2024 IPPS/
LTCH PPS final rule will include tables
of the changes to the ICD–10–CM/PCS
code sets, which underlie the FY 2024
IPF MS–DRGs. Both the FY 2024 IPPS
final rule and the tables of final changes
to the ICD–10–CM/PCS code sets, which
underlie the FY 2024 MS–DRGs, will be
available on the CMS IPPS website at
https://www.cms.gov/Medicare/
Medicare-Fee-for-Service-Payment/
AcuteInpatientPPS/.
Code First
As discussed in the ICD–10–CM
Official Guidelines for Coding and
Reporting, certain conditions have both
an underlying etiology and multiple
body system manifestations due to the
underlying etiology. For such
conditions, the ICD–10–CM has a
coding convention that requires the
underlying condition be sequenced first
followed by the manifestation.
Wherever such a combination exists,
there is a ‘‘use additional code’’ note at
the etiology code, and a ‘‘code first’’
note at the manifestation code. These
instructional notes indicate the proper
sequencing order of the codes (etiology
followed by manifestation). In
accordance with the ICD–10–CM
Official Guidelines for Coding and
Reporting, when a primary (psychiatric)
diagnosis code has a ‘‘code first’’ note,
the provider will follow the instructions
in the ICD–10–CM Tabular List. The
submitted claim goes through the CMS
processing system, which will identify
the principal diagnosis code as nonpsychiatric and search the secondary
codes for a psychiatric code to assign a
DRG code for adjustment. The system
will continue to search the secondary
codes for those that are appropriate for
comorbidity adjustment.
For more information on the code first
policy, we refer our readers to the
November 2004 IPF PPS final rule (69
FR 66945), and see sections I.A.13 and
I.B.7 of the FY 2020 ICD–10–CM Coding
Guidelines, available at https://
www.cdc.gov/nchs/data/icd/
10cmguidelines-FY2020_final.pdf. In
the FY 2015 IPF PPS final rule, we
provided a code first table for reference
that highlights the same or similar
manifestation codes where the code first
instructions apply in ICD–10–CM that
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were present in ICD–10–CM (79 FR
46009). In FY 2018, FY 2019 and FY
2020, there were no changes to the final
ICD–10–CM codes in the IPF Code First
table. For FY 2021 and FY 2022, there
were 18 ICD–10–CM codes deleted from
the final IPF Code First table. For FY
2023, there were 2 ICD–10–CM codes
deleted and 48 ICD–10–CM codes added
to the IPF Code First table. For FY 2024,
there are no proposed changes to the
Code First Table. The proposed FY 2024
Code First table is shown in Addendum
B on the CMS website at https://
www.cms.gov/Medicare/Medicare-Feefor-Service-Payment/
InpatientPsychFacilPPS/tools.html.
b. Proposed Payment for Comorbid
Conditions
The intent of the comorbidity
adjustments is to recognize the
increased costs associated with
comorbid conditions by providing
additional payments for certain existing
medical or psychiatric conditions that
are expensive to treat. In our RY 2012
IPF PPS final rule (76 FR 26451 through
26452), we explained that the IPF PPS
includes 17 comorbidity categories and
identified the new, revised, and deleted
ICD–9–CM diagnosis codes that generate
a comorbid condition payment
adjustment under the IPF PPS for RY
2012 (76 FR 26451).
Comorbidities are specific patient
conditions that are secondary to the
patient’s principal diagnosis and that
require treatment during the stay.
Diagnoses that relate to an earlier
episode of care and have no bearing on
the current hospital stay are excluded
and must not be reported on IPF claims.
Comorbid conditions must exist at the
time of admission or develop
subsequently, and affect the treatment
received, LOS, or both treatment and
LOS.
For each claim, an IPF may receive
only one comorbidity adjustment within
a comorbidity category, but it may
receive an adjustment for more than one
comorbidity category. Current billing
instructions for discharge claims, on or
after October 1, 2015, require IPFs to
enter the complete ICD–10–CM codes
for up to 24 additional diagnoses if they
co-exist at the time of admission, or
develop subsequently and impact the
treatment provided.
The comorbidity adjustments were
determined based on the regression
analysis using the diagnoses reported by
IPFs in FY 2002. The principal
diagnoses were used to establish the
DRG adjustments and were not
accounted for in establishing the
comorbidity category adjustments,
except where ICD–9–CM code first
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instructions applied. In a code first
situation, the submitted claim goes
through the CMS processing system,
which will identify the principal
diagnosis code as non-psychiatric and
search the secondary codes for a
psychiatric code to assign an MS–DRG
code for adjustment. The system will
continue to search the secondary codes
for those that are appropriate for
comorbidity adjustment.
As noted previously, it is our policy
to maintain the same diagnostic coding
set for IPFs that is used under the IPPS
for providing the same psychiatric care.
The 17 comorbidity categories formerly
defined using ICD–9–CM codes were
converted to ICD–10–CM/PCS in our FY
2015 IPF PPS final rule (79 FR 45947
through 45955). The goal for converting
the comorbidity categories is referred to
as replication, meaning that the
payment adjustment for a given patient
encounter is the same after ICD–10–CM
implementation as it will be if the same
record had been coded in ICD–9–CM
and submitted prior to ICD–10–CM/PCS
implementation on October 1, 2015. All
conversion efforts were made with the
intent of achieving this goal. For FY
2024, we propose to use the same
comorbidity adjustment factors in effect
in FY 2023. The proposed FY 2024
comorbidity adjustment factors are
found in Addendum A, available on the
CMS website at https://www.cms.gov/
Medicare/Medicare-Fee-for-ServicePayment/InpatientPsychFacilPPS/
tools.html.
For FY 2024, we propose to add 2
ICD–10–CM/PCS codes and remove 1
ICD–10–CM/PCS code from the Chronic
Renal Failure category. The proposed
FY 2024 comorbidity codes are shown
in Addenda B, available on the CMS
website at https://www.cms.gov/
Medicare/Medicare-Fee-for-ServicePayment/InpatientPsychFacilPPS/
tools.html.
In accordance with the policy
established in the FY 2015 IPF PPS final
rule (79 FR 45949 through 45952), we
reviewed all new FY 2024 ICD–10–CM
codes to remove codes that were site
‘‘unspecified’’ in terms of laterality from
the FY 2024 ICD–10–CM/PCS codes in
instances where more specific codes are
available. As we stated in the FY 2015
IPF PPS final rule, we believe that
specific diagnosis codes that narrowly
identify anatomical sites where disease,
injury, or a condition exists should be
used when coding patients’ diagnoses
whenever these codes are available. We
finalized in the FY 2015 IPF PPS rule,
that we would remove site
‘‘unspecified’’ codes from the IPF PPS
ICD–10–CM/PCS codes in instances
when laterality codes (site specified
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codes) are available, as the clinician
should be able to identify a more
specific diagnosis based on clinical
assessment at the medical encounter.
None of the finalized additions to the
FY 2024 ICD–10–CM/PCS codes were
site ‘‘unspecified’’ by laterality,
therefore, we are not removing any of
the new codes.
c. Proposed Patient Age Adjustments
As explained in the November 2004
IPF PPS final rule (69 FR 66922), we
analyzed the impact of age on per diem
cost by examining the age variable
(range of ages) for payment adjustments.
In general, we found that the cost per
day increases with age. The older age
groups are costlier than the under 45 age
group, the differences in per diem cost
increase for each successive age group,
and the differences are statistically
significant. For FY 2024, we propose to
use the patient age adjustments
currently in effect for FY 2023, as
shown in Addendum A of this proposed
rule (see https://www.cms.gov/
Medicare/Medicare-Fee-for-ServicePayment/InpatientPsychFacilPPS/
tools.html).
d. Proposed Variable per Diem
Adjustments
We explained in the November 2004
IPF PPS final rule (69 FR 66946) that the
regression analysis indicated that per
diem cost declines as the LOS increases.
The variable per diem adjustments to
the Federal per diem base rate account
for ancillary and administrative costs
that occur disproportionately in the first
days after admission to an IPF. As
discussed in the November 2004 IPF
PPS final rule, we used a regression
analysis to estimate the average
differences in per diem cost among stays
of different lengths (69 FR 66947
through 66950). As a result of this
analysis, we established variable per
diem adjustments that begin on day 1
and decline gradually until day 21 of a
patient’s stay. For day 22 and thereafter,
the variable per diem adjustment
remains the same each day for the
remainder of the stay. However, the
adjustment applied to day 1 depends
upon whether the IPF has a qualifying
ED. If an IPF has a qualifying ED, it
receives a 1.31 adjustment factor for day
1 of each stay. If an IPF does not have
a qualifying ED, it receives a 1.19
adjustment factor for day 1 of the stay.
The ED adjustment is explained in more
detail in section III.D.4 of this proposed
rule.
For FY 2024, we propose to use the
variable per diem adjustment factors
currently in effect in FY 2023, as shown
in Addendum A of this proposed rule
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(available at https://www.cms.gov/
Medicare/Medicare-Fee-for-ServicePayment/InpatientPsychFacilPPS/
tools.html). A complete discussion of
the variable per diem adjustments
appears in the November 2004 IPF PPS
final rule (69 FR 66946).
D. Proposed Updates to the IPF PPS
Facility-Level Adjustments
The IPF PPS includes facility-level
adjustments for the wage index, IPFs
located in rural areas, teaching IPFs,
cost of living adjustments for IPFs
located in Alaska and Hawaii, and IPFs
with a qualifying ED.
1. Wage Index Adjustment
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a. Background
As discussed in the RY 2007 IPF PPS
final rule (71 FR 27061), RY 2009 IPF
PPS (73 FR 25719) and the RY 2010 IPF
PPS notices (74 FR 20373), to provide
an adjustment for geographic wage
levels, the labor-related portion of an
IPF’s payment is adjusted using an
appropriate wage index. Currently, an
IPF’s geographic wage index value is
determined based on the actual location
of the IPF in an urban or rural area, as
defined in 42 CFR 412.64(b)(1)(ii)(A)
and (C).
Due to the variation in costs and
because of the differences in geographic
wage levels, in the November 15, 2004
IPF PPS final rule, we required that
payment rates under the IPF PPS be
adjusted by a geographic wage index.
We proposed and finalized a policy to
use the unadjusted, pre-floor, prereclassified IPPS hospital wage index to
account for geographic differences in
IPF labor costs. We implemented use of
the pre-floor, pre-reclassified IPPS
hospital wage data to compute the IPF
wage index since there was not an IPFspecific wage index available. We
believe that IPFs generally compete in
the same labor market as IPPS hospitals
so the pre-floor, pre-reclassified IPPS
hospital wage data should be reflective
of labor costs of IPFs. We believe this
pre-floor, pre-reclassified IPPS hospital
wage index to be the best available data
to use as proxy for an IPF specific wage
index. As discussed in the RY 2007 IPF
PPS final rule (71 FR 27061 through
27067), under the IPF PPS, the wage
index is calculated using the IPPS wage
index for the labor market area in which
the IPF is located, without considering
geographic reclassifications, floors, and
other adjustments made to the wage
index under the IPPS. For a complete
description of these IPPS wage index
adjustments, we refer readers to the FY
2019 IPPS/LTCH PPS final rule (83 FR
41362 through 41390). Our wage index
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policy at § 412.424(a)(2), requires that
we use the best Medicare data available
to estimate costs per day, including an
appropriate wage index to adjust for
wage differences.
When the IPF PPS was implemented
in the November 15, 2004 IPF PPS final
rule, with an effective date of January 1,
2005, the pre-floor, pre-reclassified IPPS
hospital wage index that was available
at the time was the FY 2005 pre-floor,
pre-reclassified IPPS hospital wage
index. Historically, the IPF wage index
for a given RY has used the pre-floor,
pre-reclassified IPPS hospital wage
index from the prior FY as its basis.
This has been due in part to the prefloor, pre-reclassified IPPS hospital
wage index data that were available
during the IPF rulemaking cycle, where
an annual IPF notice or IPF final rule
was usually published in early May.
This publication timeframe was
relatively early compared to other
Medicare payment rules because the IPF
PPS follows a RY, which was defined in
the implementation of the IPF PPS as
the 12-month period from July 1 to June
30 (69 FR 66927). Therefore, the best
available data at the time the IPF PPS
was implemented was the pre-floor, prereclassified IPPS hospital wage index
from the prior FY (for example, the RY
2006 IPF wage index was based on the
FY 2005 pre-floor, pre-reclassified IPPS
hospital wage index).
In the RY 2012 IPF PPS final rule, we
changed the reporting year timeframe
for IPFs from a RY to the FY, which
begins October 1 and ends September 30
(76 FR 26434 through 26435). In that RY
2012 IPF PPS final rule, we continued
our established policy of using the prefloor, pre-reclassified IPPS hospital
wage index from the prior year (that is,
from FY 2011) as the basis for the FY
2012 IPF wage index. This policy of
basing a wage index on the prior year’s
pre-floor, pre-reclassified IPPS hospital
wage index has been followed by other
Medicare payment systems, such as
hospice and inpatient rehabilitation
facilities. By continuing with our
established policy, we remained
consistent with other Medicare payment
systems.
In FY 2020, we finalized the IPF wage
index methodology to align the IPF PPS
wage index with the same wage data
timeframe used by the IPPS for FY 2020
and subsequent years. Specifically, we
finalized to use the pre-floor, prereclassified IPPS hospital wage index
from the FY concurrent with the IPF FY
as the basis for the IPF wage index. For
example, the FY 2020 IPF wage index
was based on the FY 2020 pre-floor, prereclassified IPPS hospital wage index
rather than on the FY 2019 pre-floor,
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pre-reclassified IPPS hospital wage
index.
We explained in the FY 2020
proposed rule (84 FR 16973), that using
the concurrent pre-floor-, prereclassified IPPS hospital wage index
will result in the most up-to-date wage
data being the basis for the IPF wage
index. It will also result in more
consistency and parity in the wage
index methodology used by other
Medicare payment systems. The
Medicare SNF PPS already used the
concurrent IPPS hospital wage index
data as the basis for the SNF PPS wage
index. Thus, the wage adjusted
Medicare payments of various provider
types will be based upon wage index
data from the same timeframe. CMS
proposed similar policies to use the
concurrent pre-floor, pre-reclassified
IPPS hospital wage index data in other
Medicare payment systems, such as
hospice and inpatient rehabilitation
facilities. For FY 2024, we propose to
continue using the concurrent pre-floor,
pre-reclassified IPPS hospital wage
index as the basis for the IPF wage
index.
We propose to apply the IPF wage
index adjustment to the labor-related
share of the national base rate and ECT
payment per treatment. The laborrelated share of the national rate and
ECT payment per treatment would
change from 77.4 percent in FY 2023 to
78.5 percent in FY 2024. This
percentage reflects the proposed laborrelated share of the proposed 2021based IPF market basket for FY 2024
(see section III.A of this proposed rule).
b. Office of Management and Budget
(OMB) Bulletins
i. Background
The wage index used for the IPF PPS
is calculated using the unadjusted, prereclassified and pre-floor IPPS wage
index data and is assigned to the IPF on
the basis of the labor market area in
which the IPF is geographically located.
IPF labor market areas are delineated
based on the Core Based Statistical Area
(CBSAs) established by the OMB.
Generally, OMB issues major
revisions to statistical areas every 10
years, based on the results of the
decennial census. However, OMB
occasionally issues minor updates and
revisions to statistical areas in the years
between the decennial censuses through
OMB Bulletins. These bulletins contain
information regarding CBSA changes,
including changes to CBSA numbers
and titles. OMB bulletins may be
accessed online at https://
www.whitehouse.gov/omb/informationfor-agencies/bulletins/. In accordance
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with our established methodology, the
IPF PPS has historically adopted any
CBSA changes that are published in the
OMB bulletin that corresponds with the
IPPS hospital wage index used to
determine the IPF wage index and,
when necessary and appropriate, has
proposed and finalized transition
policies for these changes.
In the RY 2007 IPF PPS final rule (71
FR 27061 through 27067), we adopted
the changes discussed in the OMB
Bulletin No. 03–04 (June 6, 2003),
which announced revised definitions
for Micropolitan Statistical Areas and
the creation of Micropolitan Statistical
Areas and Combined Statistical Areas.
In adopting the OMB CBSA geographic
designations in RY 2007, we did not
provide a separate transition for the
CBSA-based wage index since the IPF
PPS was already in a transition period
from TEFRA payments to PPS
payments.
In the RY 2009 IPF PPS notice, we
incorporated the CBSA nomenclature
changes published in the most recent
OMB bulletin that applied to the IPPS
hospital wage index used to determine
the current IPF wage index and stated
that we expected to continue to do the
same for all the OMB CBSA
nomenclature changes in future IPF PPS
rules and notices, as necessary (73 FR
25721).
Subsequently, CMS adopted the
changes that were published in past
OMB bulletins in the FY 2016 IPF PPS
final rule (80 FR 46682 through 46689),
the FY 2018 IPF PPS rate update (82 FR
36778 through 36779), the FY 2020 IPF
PPS final rule (84 FR 38453 through
38454), and the FY 2021 IPF PPS final
rule (85 FR 47051 through 47059). We
direct readers to each of these rules for
more information about the changes that
were adopted and any associated
transition policies.
In part due to the scope of changes
involved in adopting the CBSA
delineations for FY 2021, we finalized a
2-year transition policy consistent with
our past practice of using transition
policies to help mitigate negative
impacts on hospitals of certain wage
index policy changes. We applied a 5percent cap on wage index decreases to
all IPF providers that had any decrease
in their wage indexes, regardless of the
circumstance causing the decline, so
that an IPF’s final wage index for FY
2021 will not be less than 95 percent of
its final wage index for FY 2020,
regardless of whether the IPF was part
of an updated CBSA. We refer readers
to the FY 2021 IPF PPS final rule (85 FR
47058 through 47059) for a more
detailed discussion about the wage
index transition policy for FY 2021.
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On March 6, 2020 OMB issued OMB
Bulletin 20–01 (available on the web at
https://www.whitehouse.gov/wpcontent/uploads/2020/03/Bulletin-2001.pdf). In considering whether to adopt
this bulletin, we analyzed whether the
changes in this bulletin would have a
material impact on the IPF PPS wage
index. This bulletin creates only one
Micropolitan statistical area. As
discussed in further detail in section
III.D.1.b.ii of this proposed rule, since
Micropolitan areas are considered rural
for the IPF PPS wage index, this bulletin
has no material impact on the IPF PPS
wage index. That is, the constituent
county of the new Micropolitan area
was considered rural effective as of FY
2021 and would continue to be
considered rural if we adopted OMB
Bulletin 20–01. Therefore, we did not
propose to adopt OMB Bulletin 20–01 in
the FY 2022 IPF PPS proposed rule.
In the FY 2023 IPF PPS final rule (87
FR 46856 through 46859), we finalized
a permanent 5-percent cap on any
decrease to a provider’s wage index
from its wage index in the prior year,
and we stated that we would apply this
cap in a budget-neutral manner.
Additionally, we finalized a policy that
a new IPF 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 IPF
would not have a wage index in the
prior FY. We amended the IPF PPS
regulations at § 412.424(d)(1)(i) to reflect
this permanent cap on wage index
decreases. We refer readers to the FY
2023 IPF PPS final rule for a more
detailed discussion about this policy.
ii. Micropolitan Statistical Areas (MSA)
OMB defines a ‘‘Micropolitan
Statistical Area’’ as a CBSA associated
with at least one urban cluster that has
a population of at least 10,000, but less
than 50,000 (75 FR 37252). We refer to
these as Micropolitan Areas. After
extensive impact analysis, consistent
with the treatment of these areas under
the IPPS as discussed in the FY 2005
IPPS final rule (69 FR 49029 through
49032), we determined the best course
of action would be to treat Micropolitan
Areas as ‘‘rural’’ and include them in
the calculation of each State’s IPF PPS
rural wage index. We refer the reader to
the FY 2007 IPF PPS final rule (71 FR
27064 through 27065) for a complete
discussion regarding treating
Micropolitan Areas as rural.
c. Proposed Adjustment for Rural
Location
In the November 2004 IPF PPS final
rule, (69 FR 66954), we provided a 17
percent payment adjustment for IPFs
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21263
located in a rural area. This adjustment
was based on the regression analysis,
which indicated that the per diem cost
of rural facilities was 17 percent higher
than that of urban facilities after
accounting for the influence of the other
variables included in the regression.
This 17 percent adjustment has been
part of the IPF PPS each year since the
inception of the IPF PPS. For FY 2024,
we propose to apply a 17 percent
payment adjustment for IPFs located in
a rural area as defined at
§ 412.64(b)(1)(ii)(C) (see 69 FR 66954 for
a complete discussion of the adjustment
for rural locations).
d. Proposed Budget Neutrality
Adjustment
Changes to the wage index are made
in a budget-neutral manner so that
updates do not increase expenditures.
Therefore, for FY 2024, we propose to
apply a budget-neutrality adjustment in
accordance with our existing budgetneutrality policy. This policy requires
us to update the wage index in such a
way that total estimated payments to
IPFs for FY 2024 are the same with or
without the changes (that is, in a
budget-neutral manner) by applying a
budget-neutrality factor to the IPF PPS
rates. We use the following steps to
ensure that the rates reflect the FY 2024
update to the wage indexes (based on
the FY 2020 hospital cost report data)
and the labor-related share in a budgetneutral manner:
Step 1: Simulate estimated IPF PPS
payments, using the FY 2023 IPF wage
index values (available on the CMS
website) and labor-related share (as
published in the FY 2023 IPF PPS final
rule (87 FR 46846).
Step 2: Simulate estimated IPF PPS
payments using the proposed FY 2024
IPF wage index values (available on the
CMS website) and proposed FY 2024
labor-related share (based on the latest
available data as discussed previously).
Step 3: Divide the amount calculated
in step 1 by the amount calculated in
step 2. The resulting quotient is the
proposed FY 2024 budget-neutral wage
adjustment factor of 1.0011.
Step 4: Apply the FY 2024 budgetneutral wage adjustment factor from
step 3 to the FY 2023 IPF PPS Federal
per diem base rate after the application
of the market basket update described in
section III.A of this proposed rule, to
determine the FY 2024 IPF PPS Federal
per diem base rate.
2. Proposed Teaching Adjustment
a. Background
In the November 2004 IPF PPS final
rule, we implemented regulations at
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§ 412.424(d)(1)(iii) to establish a facilitylevel adjustment for IPFs that are, or are
part of, teaching hospitals. The teaching
adjustment accounts for the higher
indirect operating costs experienced by
hospitals that participate in graduate
medical education (GME) programs. The
payment adjustments are made based on
the ratio of the number of fulltime
equivalent (FTE) interns and residents
training in the IPF and the IPF’s average
daily census.
Medicare makes direct GME payments
(for direct costs such as resident and
teaching physician salaries, and other
direct teaching costs) to all teaching
hospitals including those paid under a
PPS, and those paid under the TEFRA
rate-of-increase limits. These direct
GME payments are made separately
from payments for hospital operating
costs and are not part of the IPF PPS.
The direct GME payments do not
address the estimated higher indirect
operating costs teaching hospitals may
face.
The results of the regression analysis
of FY 2002 IPF data established the
basis for the payment adjustments
included in the November 2004 IPF PPS
final rule. The results showed that the
indirect teaching cost variable is
significant in explaining the higher
costs of IPFs that have teaching
programs. We calculated the teaching
adjustment based on the IPF’s ‘‘teaching
variable’’, which is (1 + [the number of
FTE residents training in the IPF’s
average daily census]). The teaching
variable is then raised to the 0.5150
power to result in the teaching
adjustment. This formula is subject to
the limitations on the number of FTE
residents, which are described in this
section of this proposed rule.
We established the teaching
adjustment in a manner that limited the
incentives for IPFs to add FTE residents
for the purpose of increasing their
teaching adjustment. We imposed a cap
on the number of FTE residents that
may be counted for purposes of
calculating the teaching adjustment. The
cap limits the number of FTE residents
that teaching IPFs may count for the
purpose of calculating the IPF PPS
teaching adjustment, not the number of
residents teaching institutions can hire
or train. We calculated the number of
FTE residents that trained in the IPF
during a ‘‘base year’’ and used that FTE
resident number as the cap. An IPF’s
FTE resident cap is ultimately
determined based on the final
settlement of the IPF’s most recent cost
report filed before November 15, 2004
(69 FR 66955). A complete discussion of
the temporary adjustment to the FTE
cap to reflect residents due to hospital
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closure or residency program closure
appears in the RY 2012 IPF PPS
proposed rule (76 FR 5018 through
5020) and the RY 2012 IPF PPS final
rule (76 FR 26453 through 26456).
In the regression analysis, the
logarithm of the teaching variable had a
coefficient value of 0.5150. We
converted this cost effect to a teaching
payment adjustment by treating the
regression coefficient as an exponent
and raising the teaching variable to a
power equal to the coefficient value. We
note that the coefficient value of 0.5150
was based on the regression analysis
holding all other components of the
payment system constant. A complete
discussion of how the teaching
adjustment was calculated appears in
the November 2004 IPF PPS final rule
(69 FR 66954 through 66957) and the
RY 2009 IPF PPS notice (73 FR 25721).
As with other adjustment factors
derived through the regression analysis,
we do not plan to propose updates to
the teaching adjustment factors until we
more fully analyze IPF PPS data.
Therefore, in this FY 2024 proposed
rule, we propose to retain the coefficient
value of 0.5150 for the teaching
adjustment to the Federal per diem base
rate.
3. Proposed Cost of Living Adjustment
(COLA) for IPFs Located in Alaska and
Hawaii
The IPF PPS includes a payment
adjustment for IPFs located in Alaska
and Hawaii based upon the area in
which the IPF is located. As we
explained in the November 2004 IPF
PPS final rule, the FY 2002 data
demonstrated that IPFs in Alaska and
Hawaii had per diem costs that were
disproportionately higher than other
IPFs. Other Medicare prospective
payment systems (for example, the IPPS
and LTCH PPS) adopted a COLA to
account for the cost differential of care
furnished in Alaska and Hawaii.
We analyzed the effect of applying a
COLA to payments for IPFs located in
Alaska and Hawaii. The results of our
analysis demonstrated that a COLA for
IPFs located in Alaska and Hawaii will
improve payment equity for these
facilities. As a result of this analysis, we
provided a COLA in the November 2004
IPF PPS final rule.
A COLA for IPFs located in Alaska
and Hawaii is made by multiplying the
non-labor-related portion of the Federal
per diem base rate by the applicable
COLA factor based on the COLA area in
which the IPF is located.
The COLA factors through 2009 were
published by the Office of Personnel
Management (OPM), and the OPM
memo showing the 2009 COLA factors
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is available at https://www.chcoc.gov/
content/nonforeign-area-retirementequity-assurance-act.
We note that the COLA areas for
Alaska are not defined by county as are
the COLA areas for Hawaii. In 5 CFR
591.207, the OPM established the
following COLA areas:
• City of Anchorage, and 80-kilometer
(50-mile) radius by road, as measured
from the Federal courthouse.
• City of Fairbanks, and 80-kilometer
(50-mile) radius by road, as measured
from the Federal courthouse.
• City of Juneau, and 80-kilometer
(50-mile) radius by road, as measured
from the Federal courthouse.
• Rest of the State of Alaska.
As stated in the November 2004 IPF
PPS final rule, we update the COLA
factors according to updates established
by the OPM. However, sections 1911
through 1919 of the Non-foreign Area
Retirement Equity Assurance Act, as
contained in subtitle B of title XIX of the
National Defense Authorization Act
(NDAA) (Pub. L. 111–84, October 28,
2009), for FY 2010 transitions the
Alaska and Hawaii COLAs to locality
pay. Under section 1914 of NDAA,
locality pay was phased in over a 3-year
period beginning in January 2010, with
COLA rates frozen as of the date of
enactment, October 28, 2009, and then
proportionately reduced to reflect the
phase-in of locality pay.
When we published the proposed
COLA factors in the RY 2012 IPF PPS
proposed rule (76 FR 4998), we
inadvertently selected the FY 2010
COLA rates, which had been reduced to
account for the phase-in of locality pay.
We did not intend to propose the
reduced COLA rates because that would
have understated the adjustment. Since
the 2009 COLA rates did not reflect the
phase-in of locality pay, we finalized
the FY 2009 COLA rates for RY 2010
through RY 2014.
In the FY 2013 IPPS/LTCH final rule
(77 FR 53700 through 53701), we
established a new methodology to
update the COLA factors for Alaska and
Hawaii, and adopted this methodology
for the IPF PPS in the FY 2015 IPF final
rule (79 FR 45958 through 45960). We
adopted this new COLA methodology
for the IPF PPS because IPFs are
hospitals with a similar mix of
commodities and services. We believe it
is appropriate to have a consistent
policy approach with that of other
hospitals in Alaska and Hawaii.
Therefore, the IPF COLAs for FY 2015
through FY 2017 were the same as those
applied under the IPPS in those years.
As finalized in the FY 2013 IPPS/LTCH
PPS final rule (77 FR 53700 and 53701),
the COLA updates are determined every
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4 years, when the IPPS market basket
labor-related share is updated. Because
the labor-related share of the IPPS
market basket was updated for FY 2022,
the COLA factors were updated in FY
2022 IPPS/LTCH rulemaking (86 FR
45547). As such, we also updated the
IPF PPS COLA factors for FY 2022 (86
FR 42621 through 42622) to reflect the
updated COLA factors finalized in the
FY 2022 IPPS/LTCH rulemaking. Table
16 shows the proposed IPF PPS COLA
factors effective for FY 2022 through FY
2025.
TABLE 16—IPF PPS COST-OF-LIVING-ADJUSTMENT FACTORS: IPFS LOCATED IN ALASKA AND HAWAII
FY 2022 through
FY 2025
Area
Alaska:
City of Anchorage and 80-kilometer (50-mile) radius by road ....................................................................................................
City of Fairbanks and 80-kilometer (50-mile) radius by road ......................................................................................................
City of Juneau and 80-kilometer (50-mile) radius by road ..........................................................................................................
Rest of Alaska .............................................................................................................................................................................
Hawaii:
City and County of Honolulu .......................................................................................................................................................
County of Hawaii .........................................................................................................................................................................
County of Kauai ...........................................................................................................................................................................
County of Maui and County of Kalawao .....................................................................................................................................
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The proposed IPF PPS COLA factors
for FY 2024 are also shown in
Addendum A to this proposed rule, and
is available at https://www.cms.gov/
Medicare/Medicare-Fee-for-ServicePayment/InpatientPsychFacilPPS/
tools.html.
4. Proposed Adjustment for IPFs With a
Qualifying Emergency Department (ED)
The IPF PPS includes a facility-level
adjustment for IPFs with qualifying EDs.
We provide an adjustment to the
Federal per diem base rate to account
for the costs associated with
maintaining a full-service ED. The
adjustment is intended to account for
ED costs incurred by a psychiatric
hospital with a qualifying ED or an
excluded psychiatric unit of an IPPS
hospital or a CAH, for preadmission
services otherwise payable under the
Medicare Hospital Outpatient
Prospective Payment System (OPPS),
furnished to a beneficiary on the date of
the beneficiary’s admission to the
hospital and during the day
immediately preceding the date of
admission to the IPF (see § 413.40(c)(2)),
and the overhead cost of maintaining
the ED. This payment is a facility-level
adjustment that applies to all IPF
admissions (with one exception, which
we described), regardless of whether a
particular patient receives preadmission
services in the hospital’s ED.
The ED adjustment is incorporated
into the variable per diem adjustment
for the first day of each stay for IPFs
with a qualifying ED. Those IPFs with
a qualifying ED receive an adjustment
factor of 1.31 as the variable per diem
adjustment for day 1 of each patient
stay. If an IPF does not have a qualifying
ED, it receives an adjustment factor of
1.19 as the variable per diem adjustment
for day 1 of each patient stay.
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The ED adjustment is made on every
qualifying claim except as described in
this section of this proposed rule. As
specified in § 412.424(d)(1)(v)(B), the ED
adjustment is not made when a patient
is discharged from an IPPS hospital or
CAH and admitted to the same IPPS
hospital’s or CAH’s excluded
psychiatric unit. We clarified in the
November 2004 IPF PPS final rule (69
FR 66960) that an ED adjustment is not
made in this case because the costs
associated with ED services are reflected
in the DRG payment to the IPPS hospital
or through the reasonable cost payment
made to the CAH.
Therefore, when patients are
discharged from an IPPS hospital or
CAH and admitted to the same
hospital’s or CAH’s excluded
psychiatric unit, the IPF receives the
1.19 adjustment factor as the variable
per diem adjustment for the first day of
the patient’s stay in the IPF. For FY
2024, we propose to retain the 1.31
adjustment factor for IPFs with
qualifying EDs. A complete discussion
of the steps involved in the calculation
of the ED adjustment factors are in the
November 2004 IPF PPS final rule (69
FR 66959 through 66960) and the RY
2007 IPF PPS final rule (71 FR 27070
through 27072).
E. Other Proposed Payment
Adjustments and Policies
1. Outlier Payment Overview
The IPF PPS includes an outlier
adjustment to promote access to IPF
care for those patients who require
expensive care and to limit the financial
risk of IPFs treating unusually costly
patients. In the November 2004 IPF PPS
final rule, we implemented regulations
at § 412.424(d)(3)(i) to provide a per
case payment for IPF stays that are
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1.22
1.22
1.22
1.24
1.25
1.22
1.25
1.25
extraordinarily costly. Providing
additional payments to IPFs for
extremely costly cases strongly
improves the accuracy of the IPF PPS in
determining resource costs at the patient
and facility level. These additional
payments reduce the financial losses
that would otherwise be incurred in
treating patients who require costlier
care, and therefore, reduce the
incentives for IPFs to under-serve these
patients. We make outlier payments for
discharges in which an IPF’s estimated
total cost for a case exceeds a fixed
dollar loss threshold amount
(multiplied by the IPF’s facility-level
adjustments) plus the Federal per diem
payment amount for the case.
In instances when the case qualifies
for an outlier payment, we pay 80
percent of the difference between the
estimated cost for the case and the
adjusted threshold amount for days 1
through 9 of the stay (consistent with
the median LOS for IPFs in FY 2002),
and 60 percent of the difference for day
10 and thereafter. The adjusted
threshold amount is equal to the outlier
threshold amount adjusted for wage
area, teaching status, rural area, and the
COLA adjustment (if applicable), plus
the amount of the Medicare IPF
payment for the case. We established
the 80 percent and 60 percent loss
sharing ratios because we were
concerned that a single ratio established
at 80 percent (like other Medicare PPSs)
might provide an incentive under the
IPF per diem payment system to
increase LOS in order to receive
additional payments.
After establishing the loss sharing
ratios, we determined the current fixed
dollar loss threshold amount through
payment simulations designed to
compute a dollar loss beyond which
payments are estimated to meet the 2
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percent outlier spending target. Each
year when we update the IPF PPS, we
simulate payments using the latest
available data to compute the fixed
dollar loss threshold so that outlier
payments represent 2 percent of total
estimated IPF PPS payments.
2. Proposed Update to the Outlier Fixed
Dollar Loss Threshold Amount
In accordance with the update
methodology described in § 412.428(d),
we propose to update the fixed dollar
loss threshold amount used under the
IPF PPS outlier policy. Based on the
regression analysis and payment
simulations used to develop the IPF
PPS, we established a 2 percent outlier
policy, which strikes an appropriate
balance between protecting IPFs from
extraordinarily costly cases while
ensuring the adequacy of the Federal
per diem base rate for all other cases
that are not outlier cases.
Our longstanding methodology for
updating the outlier fixed dollar loss
threshold involves using the best
available data, which is typically the
most recent available data. For the FY
2022 IPF PPS final rule, we finalized the
use of FY 2019 claims rather than the
more recent FY 2020 claims for
updating the outlier fixed dollar loss
threshold (86 FR 42623). We noted that
our use of the FY 2019 claims to set the
final outlier fixed dollar loss threshold
for FY 2022 deviated from our
longstanding practice of using the most
recent available year of claims, but
remained otherwise consistent with the
established outlier update methodology.
We explained that we finalized our
proposal to deviate from our
longstanding practice of using the most
recent available year of claims only
because, and to the extent that, the
‘‘coronavirus disease 2019’’ (abbreviated
‘‘COVID–19’’) Public Health Emergency
(PHE) appeared to have significantly
impacted the FY 2020 IPF claims. We
further stated that we intended to
continue to analyze further data in order
to better understand both the short-term
and long-term effects of the COVID–19
PHE on IPFs (86 FR 42624).
In the FY 2023 IPF PPS final rule (87
FR 46862 through 46864) we noted that
we observed an overall increase in
average cost per day and an overall
decrease in the number of covered days.
However, we identified that some
providers had significant increases in
their charges, resulting in higher than
normal estimated cost per day that
would skew our estimate of outlier
payments for FY 2022 and FY 2023. We
finalized our proposal for FY 2023 to
use the latest available FY 2021 claims,
in accordance with our longstanding
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practice, to simulate payments for
determining the final FY 2023 IPF PPS
outlier fixed dollar loss threshold
amount. In addition, we finalized a
methodology for FY 2023 to exclude
providers from our impact simulations
whose change in simulated cost per day
is outside 3 standard deviations from
the mean.
For this FY 2024 IPF PPS proposed
rulemaking, consistent with our
longstanding practice, we analyzed the
most recent available data for simulating
IPF PPS payments in FY 2023. Based on
an analysis of these updated data, we
estimate that IPF outlier payments as a
percentage of total estimated payments
are approximately 3.0 percent in FY
2023. We analyzed the change in
providers’ charges from the FY 2021
claims that were used to simulate
payments for determining the final FY
2023 IPF PPS outlier threshold, and the
latest available FY 2022 claims. In
contrast to our analysis of FY 2021
claims for the FY 2023 IPF PPS
proposed and final rules, we did not
find the same level of significant
increases in charges in the FY 2022
claims that we believe would skew our
estimate of outlier payments for FY
2023 and FY 2024. Therefore, we
propose to update the outlier threshold
amount to $34,750. This would allow us
to maintain estimated outlier payments
at 2 percent of total estimated aggregate
IPF payments for FY 2024. This
proposed update is an increase from the
FY 2023 threshold of $24,630. We are
soliciting comments on this proposed
increase to the outlier threshold for FY
2024, and whether we should consider
alternative methodologies for FY 2024.
Specifically, we are interested in
understanding whether commenters
believe it would be appropriate to
exclude providers from our FY 2024
impact simulations whose change in
simulated cost per day is outside 3
standard deviations from the mean,
following the same methodology we
applied in FY 2023. We note that our
analysis for this FY 2024 proposed rule
shows that the FY 2024 outlier fixed
dollar loss threshold amount would be
closer to $30,000 if we were to exclude
providers based on the same
methodology finalized for FY 2023. We
are also interested in other
methodologies that commenters believe
might be appropriate to consider,
including why commenters believe
applying such a methodology would be
appropriate for establishing the outlier
threshold for FY 2024.
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3. Proposed Update to IPF Cost-toCharge Ratio Ceilings
Under the IPF PPS, an outlier
payment is made if an IPF’s cost for a
stay exceeds a fixed dollar loss
threshold amount plus the IPF PPS
amount. In order to establish an IPF’s
cost for a particular case, we multiply
the IPF’s reported charges on the
discharge bill by its overall cost-tocharge ratio (CCR). This approach to
determining an IPF’s cost is consistent
with the approach used under the IPPS
and other PPSs. In the FY 2004 IPPS
final rule (68 FR 34494), we
implemented changes to the IPPS policy
used to determine CCRs for IPPS
hospitals, because we became aware
that payment vulnerabilities resulted in
inappropriate outlier payments. Under
the IPPS, we established a statistical
measure of accuracy for CCRs to ensure
that aberrant CCR data did not result in
inappropriate outlier payments.
As indicated in the November 2004
IPF PPS final rule (69 FR 66961), we
believe that the IPF outlier policy is
susceptible to the same payment
vulnerabilities as the IPPS; therefore, we
adopted a method to ensure the
statistical accuracy of CCRs under the
IPF PPS. Specifically, we adopted the
following procedure in the November
2004 IPF PPS final rule:
• Calculated two national ceilings,
one for IPFs located in rural areas and
one for IPFs located in urban areas.
• Computed the ceilings by first
calculating the national average and the
standard deviation of the CCR for both
urban and rural IPFs using the most
recent CCRs entered in the most recent
Provider Specific File (PSF) available.
For FY 2024, we propose to continue
to follow this methodology.
To determine the rural and urban
ceilings, we multiplied each of the
standard deviations by 3 and added the
result to the appropriate national CCR
average (either rural or urban). The
upper threshold CCR for IPFs in FY
2024 is 2.0801 for rural IPFs, and 1.7864
for urban IPFs, based on CBSA-based
geographic designations. If an IPF’s CCR
is above the applicable ceiling, the ratio
is considered statistically inaccurate,
and we assign the appropriate national
(either rural or urban) median CCR to
the IPF.
We apply the national median CCRs
to the following situations:
• New IPFs that have not yet
submitted their first Medicare cost
report. We continue to use these
national median CCRs until the facility’s
actual CCR can be computed using the
first tentatively or final settled cost
report.
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• IPFs whose overall CCR is in excess
of three standard deviations above the
corresponding national geometric mean
(that is, above the ceiling).
• Other IPFs for which the Medicare
Administrative Contractor (MAC)
obtains inaccurate or incomplete data
with which to calculate a CCR.
We propose to update the FY 2024
national median and ceiling CCRs for
urban and rural IPFs based on the CCRs
entered in the latest available IPF PPS
PSF.
Specifically, for FY 2024, to be used
in each of the three situations listed
previously, using the most recent CCRs
entered in the CY 2022 PSF, we provide
an estimated national median CCR of
0.5720 for rural IPFs and a national
median CCR of 0.4200 for urban IPFs.
These calculations are based on the
IPF’s location (either urban or rural)
using the CBSA-based geographic
designations. A complete discussion
regarding the national median CCRs
appears in the November 2004 IPF PPS
final rule (69 FR 66961 through 66964).
4. Proposed Modification to the
Regulation for Excluded Psychiatric
Units Paid Under the IPF PPS
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a. Background
Under current regulation, in order to
be excluded from the IPPS and paid
under the IPF PPS or the IRF PPS, an
IPF or IRF unit of a hospital must meet
a number of requirements under 42 CFR
412.25. As discussed in the following
paragraphs, both this regulation and the
policies applying to excluded units
(which include excluded IRF units and
excluded IPF units) have been in effect
since before both the IPF PPS and IRF
PPS were established. Before the IRF
PPS and the IPF PPS were established,
excluded units were paid based on their
costs, as reported on their Medicare cost
reports, subject to certain facilityspecific cost limits. These cost-based
payments were determined separately
for operating and capital costs. Thus,
under cost-based payments, the process
of allocating costs to an IPF unit for
reimbursement created significant
administrative complexity. This
administrative complexity necessitated
strict regulations that allowed hospitals
to open a new IPPS-excluded unit only
at the start of a cost reporting period.
In the January 3, 1984 final rule (49
FR 235), CMS (then known as the
Health Care Financing Administration)
established policies and regulations for
hospitals and units subject to and
excluded from the IPPS. In that rule, we
explained that section 1886(d) of the
Act requires that the prospective
payment system apply to inpatient
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hospital services furnished by all
hospitals participating in the Medicare
program except those hospitals or units
specifically excluded by the law. We
further explained our expectation that a
hospital’s status (that is, whether it is
subject to, or excluded from, the
prospective payment system) would
generally be determined at the
beginning of each cost reporting period.
We also stated that this status would
continue throughout the period, which
is normally 1 year. Accordingly, we
stated that changes in a hospital’s (or
unit’s) status that result from meeting or
failing to meet the criteria for exclusion
would be implemented only at the start
of a cost reporting period. However, we
also acknowledged that under some
circumstances involving factors external
to the hospital, status changes could be
made at times other than the beginning
of the cost reporting period. For
example, a change in status could occur
if a hospital is first included under the
prospective payment system and, after
the start of its cost reporting period, is
excluded because of its participation in
an approved demonstration project or
State reimbursement control program
that begins after the hospital’s cost
reporting period has begun.
In the 1993 IPPS final rule (57 FR
39798 through 39799), we codified our
longstanding policies regarding when a
hospital unit can change its status from
not excluded to excluded. We explained
in that final rule that since the inception
of the PPS for operating costs of hospital
inpatient services in October 1983,
certain types of specialty-care hospitals
and hospital units have been excluded
from that system under section
1888(d)(1)(B) of the Act. We noted that
these currently include psychiatric and
rehabilitation hospitals and distinct part
units, children’s hospitals, and longterm care hospitals. We further
explained that section 6004(a)(1) of
Public Law 101–239 amended section
1886(d)(1)(B) of the Act to provide that
certain cancer hospitals are also
excluded. We noted that the preamble to
the January 3, 1984 final rule
implementing the PPS for operating
costs (49 FR 235) stated that the status
of a hospital or unit (that is, whether it
is subject to, or excluded from, the PPS)
will be determined at the beginning of
each cost reporting period. We noted
that that same 1984 final rule also
provided that changes in a hospital’s or
unit’s status that result from meeting or
failing to meet the criteria for exclusion
will be implemented prospectively only
at the start of a cost reporting period,
that is, starting with the beginning date
of the next cost reporting period (49 FR
PO 00000
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243). However, we noted that this policy
was not set forth in the regulations. In
that 1993 IPPS final rule, we stated that
we proposed revising §§ 412.22 and
412.25 to specify that changes in the
status of each hospital or hospital unit
would be recognized only at the start of
a cost reporting period. We stated that,
except in the case of retroactive
payment adjustments for excluded
rehabilitation units described in
§ 412.30(c), any change in a hospital’s or
unit’s compliance with the exclusion
criteria that occurs after the start of a
cost reporting period would not be
taken into consideration until the start
of the following period. We noted that
this policy would also apply to any unit
that is added to a hospital during the
hospital’s cost reporting period. We also
stated that we proposed revising
§ 412.25(a) to specify that as a
requirement for exclusion, a hospital
unit must be fully equipped and staffed,
and be capable of providing inpatient
psychiatric or rehabilitation care as of
the first day of the first cost reporting
period for which all other exclusion
requirements are met. We explained that
a unit that meets this requirement
would be considered open regardless of
whether there are any inpatients in the
unit.
In the same 1993 IPPS final rule, we
responded to commenters who objected
to this policy, stating that it
unnecessarily penalizes hospitals for
factors beyond their control, such as
construction delays, that it discourages
hospitals from making changes in their
programs to meet community needs, or
that it can place undue workload
demands on regulatory agencies during
certain time periods. In response, we
explained that we believed that
regulatory agencies, hospitals, and the
public generally would benefit from
policies that are clearly stated, can be
easily understood by both hospitals and
intermediaries, and can be simply
administered. We stated that
recognizing changes in status only at the
beginning of cost reporting periods is
consistent with these goals, while
recognizing changes in the middle of
cost reporting periods would introduce
added complexity to the administration
of the exclusion provisions. Therefore,
we did not revise the proposed changes
based on these comments.
In the FY 2000 IPPS final rule (64 FR
41531 through 41532), we amended the
regulations at § 412.25(c) to allow a
hospital unit to change from excluded to
not excluded at any time during the cost
reporting period. We explained the
statutory basis and rationale for this
change in the FY 2000 IPPS proposed
rule (64 FR 24740), and noted that a
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number of hospitals suggested that we
consider a change in our policy to
recognize, for purposes of exclusion
from the IPPS, reductions in number of
beds in, or entire closure of, units at any
time during a cost reporting period. In
that FY 2000 IPPS proposed rule, we
explained that hospitals indicated that
the bed capacity made available as a
result of these changes could be used as
needed to provide additional services to
meet patient needs in the acute care part
of the hospital that is paid under the
IPPS. We further explained that we
evaluated the concerns of the hospitals
and the effects on the administration of
the Medicare program and the health
care of beneficiaries of making these
payment changes. As a result of that
evaluation, we stated that we believed it
was reasonable to adopt a more flexible
policy in recognition of hospitals’
changes in the use of their facilities.
However, we noted that whenever a
hospital establishes an excluded unit
within the hospital, our Medicare fiscal
intermediary would need to be able to
determine costs of the unit separately
from costs of the part of the hospital
paid under the prospective payment
system. At that time, we stated that the
proper determination of costs ensured
that the hospital was paid the correct
amount for services in each part of the
facility, and that payments under the
IPPS did not duplicate payments made
under the rules that were applicable to
excluded hospitals and units, or vice
versa. For this reason, we did not
believe it would be appropriate to
recognize, for purposes of exclusion
from the IPPS, changes in the bed size
or status of an excluded unit that are so
frequent that they interfere with the
ability of the intermediary to accurately
determine costs. Moreover, we
explained that section 1886(d)(1)(B) of
the Act authorizes exclusion from the
IPPS of specific types of hospitals and
units, but not of specific admissions or
stays, such as admissions for
rehabilitation or psychiatric care, in a
hospital paid under the IPPS. We stated
that without limits on the frequency of
changes in excluded units for purposes
of proper Medicare payment, there was
the potential for some hospitals to
adjust the status or size of their
excluded units so frequently that the
units would no longer be distinct
entities and the exclusion would
effectively apply only to certain types of
care.
In the FY 2012 IRF PPS final rule (76
FR 47870), we began further efforts to
increase flexibilities for excluded IPF
and IRF units. In that rule, we explained
that cost-based reimbursement
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methodologies that were in place before
the IPF PPS and IRF PPS meant that the
facilities’ capital costs were determined,
in part, by their bed size and square
footage. Changes in the bed size and
square footage would complicate the
facilities’ capital cost allocation. Thus,
regulations at § 412.25 limited the
situations under which an IRF or IPF
could change its bed size and square
footage. In the FY 2012 IRF PPS final
rule, we revised § 412.25(b) to enable
IRFs and IPFs to more easily adjust to
beneficiary changes in demand for IRF
or IPF services, and improve beneficiary
access to these services. We believed
that the first requirement (that beds can
only be added at the start of a cost
reporting period) was difficult, and
potentially costly, for IRFs and IPFs that
were expanding through new
construction because the exact timing of
the end of a construction project is often
difficult to predict. In that same FY
2012 IRF PPS final rule, commenters
suggested that CMS allow new IRF units
or new IPF units to open and begin
being paid under their respective IRF
PPS or IPF PPS at any time during a cost
reporting period, rather than requiring
that they could only begin being paid
under the IRF PPS or the IPF PPS at the
start of a cost reporting period. We
believed that this suggestion was
outside the scope of the FY 2012 IRF
PPS proposed rule (76 FR 24214)
because we did not propose any changes
to the § 412.25(c). However, we stated
that we would consider this suggestion
for possible inclusion in future
rulemaking.
b. Current Challenges Related to
Excluded Hospital Units (§§ 412.25(c)(1)
and (c)(2))
Currently, under § 412.25(c)(1), a
hospital can only start being paid under
the IPF PPS or the IRF PPS for services
provided in an excluded hospital unit at
the start of a cost reporting period.
Specifically, § 412.25(c) limits when the
status of hospital units may change for
purposes of exclusion from the IPPS, as
specified in § 412.25(c)(1) and
§ 412.25(c)(2). Section 412.25(c)(1)
states that the status of a hospital unit
may be changed from not excluded to
excluded only at the start of the cost
reporting period. If a unit is added to a
hospital after the start of a cost reporting
period, it cannot be excluded from the
IPPS before the start of a hospital’s next
cost reporting period. Section
412.25(c)(2) states the status of a
hospital unit may be changed from
excluded to not excluded at any time
during a cost reporting period, but only
if the hospital notifies the fiscal
intermediary and the CMS Regional
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Office in writing of the change at least
30 days before the date of the change,
and maintains the information needed
to accurately determine costs that are or
are not attributable to the excluded unit.
A change in the status of a unit from
excluded to not excluded that is made
during a cost reporting period must
remain in effect for the rest of that cost
reporting period.
In recent years, interested parties,
such as hospitals, have written CMS to
express concerns about what they see as
the unnecessary restrictiveness of the
requirements at § 412.25(c). Based on
this feedback, we continued to explore
opportunities to reduce burden for
providers and clinicians, while keeping
patient-centered care a priority. For
instance, we considered whether this
regulation might create unnecessary
burden for hospitals and potentially
delay necessary psychiatric beds from
opening and being paid under the IPF
PPS. As we continued to review and
reconsider regulations to identify ways
to improve policy, we recognized that
the requirement at § 412.25(c)(1), that
hospital units can only be excluded at
the start of a cost reporting period, may
be challenging and potentially costly for
facilities under some circumstances, for
example, those that are expanding
through new construction. Hospitals
have indicated it is often difficult to
predict the exact timing of the end of a
construction project and construction
delays may hamper a hospital’s ability
to have the construction of an excluded
unit completed exactly at the start of a
cost reporting period, which hospitals
have said can lead to significant revenue
loss if they are unable to be paid under
the IPF PPS or IRF PPS until the start
of the next cost reporting period.
As previously stated, the
requirements at § 412.25(c) were
established to manage the
administrative complexity associated
with cost-based reimbursement for
excluded IPF and IRF units. Today,
however, because IPF units are paid
under the IPF PPS and IRF units are
paid under the IRF PPS, cost allocation
is not used for payment purposes.
Because advancements in technology
since the inception of the IPF PPS and
IRF PPS have simplified the cost
reporting process and enhanced
communication between providers,
Medicare contractors, and CMS, we are
reconsidering whether it is necessary to
continue to allow hospital units to
become excluded only at the start of a
cost reporting period.
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c. Proposed Changes to Excluded
Hospital Units (§§ 412.25(c)(1) and
(c)(2))
We are committed to continuing to
transform the health care delivery
system and the Medicare program by
putting additional focus on patientcentered care and working with
providers, physicians, and patients to
improve outcomes, while meeting
relevant health care priorities and
explore burden reduction.
In response to increased mental
health needs, including the need for
availability of inpatient psychiatric
beds, we propose changes to § 412.25(c)
to allow greater flexibility for hospitals
to open excluded units, while
minimizing the amount of effort
Medicare contractors would need to
spend administering the regulatory
requirements. Although we are
cognizant that there is need for mental
health services and support for
providers along a continuum of care,
including a robust investment in
community-based mental health
services, this propose rule is focused on
inpatient psychiatric facility settings.
We note that § 412.25(c) applies to
both IPFs and IRFs; therefore, revisions
to § 412.25(c) would also affect IRFs in
similar ways. Readers should refer to
the FY 2024 IRF PPS proposed rule for
discussion of proposed revisions to
§ 412.25(c) and unique considerations
applicable to IRF units. As previously
stated the current requirements at
§ 412.25(c)(1) were originally
established to manage the
administrative complexity associated
with cost-based reimbursement for
excluded IPF and IRF units. Because IPF
and IRF units are no longer paid under
cost-based reimbursement, but rather
under the IPF PPS and IRF PPS
respectively, we believe that the
restriction that limits an IPF or IRF unit
to being excluded only at the start of a
cost reporting period is no longer
necessary. We amended our regulations
in the FY 2012 IRF PPS final rule to
address a regulation that, similarly, was
previously necessary for cost-based
reimbursement, but was not material to
payment under the IRF PPS and IPF
PPS. In that final rule, we explained that
under cost-based payments, the
facilities’ capital costs were determined,
in part, by their bed size and square
footage. Changes in the bed size and
square footage would complicate the
facilities’ capital cost allocation. We
explained that under the IRF PPS and
IPF PPS, a facility’s bed size and square
footage were not relevant for
determining the individual facility’s
Medicare payment. Therefore, we
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believed it was appropriate to modify
some of the restrictions on a facility’s
ability to change its bed size and square
footage. Accordingly, we relaxed the
restrictions on a facility’s ability to
increase its bed size and square footage.
Under the revised requirements that we
adopted in the FY 2012 IRF PPS final
rule at § 412.25(b), an IRF or IPF can
change (either increase or decrease) its
bed size or square footage one time at
any point in a given cost reporting
period as long as it notifies the CMS
Regional Office (RO) at least 30 days
before the date of the proposed change,
and maintains the information needed
to accurately determine costs that are
attributable to the excluded units.
Similarly, in the case of the
establishment of new excluded IPF and
IRF units, we do not believe that the
timing of the establishment of the new
unit is material for determining the
individual facility’s Medicare payment
under the IPF PPS or IRF PPS. We
believe it would be appropriate to allow
a unit to become excluded at any time
in the cost reporting year. However, we
also believe it is important to minimize
the potential administrative complexity
associated with units changing their
excluded status.
Accordingly, we propose to modify
the requirements currently in regulation
at § 412.25(c)(1) to allow a hospital to
open a new IPF unit any time within the
cost reporting year, as long as the
hospital notifies the CMS Regional
Office and Medicare Administrative
Contractor (MAC) in writing of the
change at least 30 days before the date
of the change. Additionally, we propose
that if a unit becomes excluded during
a cost reporting year, the hospital must
notify the MAC and CMS Regional
Office in writing of the change at least
30 days before the change, and this
change would remain in effect for the
rest of that cost reporting year. We also
propose to maintain the current
requirements of § 412.25(c)(2) which
specify that, if an excluded unit
becomes not excluded during a cost
reporting year, the hospital must notify
the MAC and CMS Regional Office in
writing of the change at least 30 days
before the change, and this change
would remain in effect for the rest of
that cost reporting year. Finally, we
propose to consolidate the requirements
for § 412.25(c)(1) and § 412.25(c)(2) into
a new § 412.25(c)(2) that would apply to
IPF units and specify the requirements
for an IPF unit to become excluded or
not excluded. We believe this proposal
would provide greater flexibility to
hospitals to establish an excluded unit
at a time other than the start of a cost
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21269
reporting period. We welcome
comments on this proposed change.
As noted above, we propose an
identical policy for rehabilitation units
of hospitals in the FY 2024 IRF PPS
proposed rule. The regulatory provision
that would pertain to IRF units would
appear in § 412.25(c)(1). We propose
discrete regulations text for each of the
hospital unit types (that is, IRF units
and IPF units) in order to solicit
comments on issues that might impact
one hospital unit type and not the other.
However, we may consider adopting
one consolidated regulations text for
both IRF and IPF units in the final rules
if we finalize both of our proposals. We
solicit public comments on finalizing a
consolidated provision that would
pertain to both IRF and IPF units.
IV. Existing Data Collection and
Request for Information (RFI) To
Inform Revisions to the IPF PPS as
Required by the CAA, 2023
A. Changes to IPF PPS in the CAA, 2023
As discussed in section III.C.1 of this
proposed rule, we propose to continue
using the existing regression-derived
IPF PPS adjustment factors for FY 2024.
In the FY 2023 IPF PPS proposed rule
(87 FR 19428 through 19429), we
discussed the background of these
current IPF PPS patient-level and
facility-level adjustment factors, which
are the regression-derived adjustment
factors from the November 15, 2004 IPF
PPS final rule and briefly discussed past
analyses and areas of concern for future
refinement, about which we previously
solicited comments. Finally, in the FY
2023 proposed rule, we described the
results of the latest analysis of the IPF
PPS, which were summarized in a
technical report posted to the CMS
website 2 accompanying the rule, and
solicited comments on certain topics
from the report.
Section 4125 of the CAA, 2023
amended section 1886(s) of the Act to
add new paragraph 1886(s)(5), which
requires revisions to the methodology
for determining the payment rates under
the IPF PPS for FY 2025 and future
years as the Secretary determines
appropriate. Specifically, new section
1886(s)(5)(A) of the Act requires the
Secretary to collect data and
information as the Secretary as
determines appropriate to revise
payments under the IPF PPS. This data
collection is required to begin no later
than October 1, 2023, which is the start
of FY 2024. In addition, new section
1886(s)(5)(D) of the Act requires that the
2 https://www.cms.gov/files/document/technicalreport-medicare-program-inpatient-psychiatricfacilities-prospective-payment-system.pdf.
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Secretary implement by regulation
revisions to the methodology for
determining the payment rates for
psychiatric hospitals and psychiatric
units (that is, under the IPF PPS), for
rate year 2025 (FY 2025) and for
subsequent years if the Secretary
determines it appropriate. The revisions
may be based on a review of the data
and information collection.
As noted above, section 1886(s)(5)(A)
of the Act requires the Secretary to
begin collecting, by not later than
October 1, 2023, data and information as
appropriate to inform revisions to the
IPF PPS. New section 1886(s)(5)(B) of
the Act, as added by the CAA, 2023 lists
the following types of data and
information as a non-exhaustive list of
examples of what may be collected
under this authority:
• Charges, including those related to
ancillary services;
• The required intensity of behavioral
monitoring, such as cognitive deficit,
suicidal ideations, violent behavior, and
need for physical restraint; and
• Interventions, such as
detoxification services for substance
abuse, dependence on respirator, total
parenteral nutritional support,
dependence on renal dialysis, and burn
care.
We note that our extensive years-long
and ongoing data collection efforts are
consistent with the types of data the
CAA, 2023 suggests we might collect as
well as the purpose for which the CAA,
2023 requires the data collection, as
described in the following paragraphs.
B. Current Data and Information
Collection Requirements
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1. Charges, Including Those Related to
Ancillary Services
As specified at 42 CFR 413.20,
hospitals are required to file cost reports
on an annual basis, and maintain
sufficient financial records and
statistical data for proper determination
of costs payable under the Medicare
program. Currently, IPFs and
psychiatric units are required to report
ancillary charges on cost reports.
In general, most providers allocate
their Medicare costs using costs and
charges as described at 42 CFR
413.53(a)(1)(i) and referred to as the
Departmental Method. For cost
reporting periods beginning on or after
October 1, 1982, the Departmental
Method, which is the ratio of
beneficiary charges to total patient
charges for the services of each ancillary
department, is applied to apportion the
cost of the department. Added to this
amount is the cost of routine services for
program beneficiaries, determined on
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the basis of a separate average cost per
diem for all patients for general routine
patient care areas as required at
§ 413.53(a)(1)(i) and (e).
The Departmental Method for
apportioning allowable cost between
Medicare and non-Medicare patients
under the program is not readily
adaptable to those hospitals that do not
have a charge structure. Current cost
reporting rules allow hospitals that do
not have a charge structure to file an allinclusive cost report using an
alternative cost allocation method.
These alternative methods as described
in the CMS Pub. 15–1, chapter 22 of the
Provider Reimbursement Manual (PRM),
Methods A, B and E, in order of
preference, must be approved by the
MAC after considering the data
available and ascertaining which
method can be applied to achieve
equity, not merely greater
reimbursement, in the allocation of
costs for services rendered to Medicare
beneficiaries.
Method A (Departmental Statistical
Method) is used in the absence of charge
data and where adequate departmental
statistics are available. Where Method A
was not used, the MAC may have
granted specific permission for a
hospital to continue to use on a
temporary basis a less sophisticated
Method B (Sliding Scale) or E
(Percentage of Per Diem). A provider
that elects and is approved under
Method A, may not change to a Method
B or E in a subsequent year. These
alternative methods of apportionment
are limited and available only to those
hospitals that do not and never have
had a charge structure for individual
services rendered. Historically, most
hospitals that were approved to file allinclusive cost reports were Indian
Health Services hospitals, governmentowned psychiatric and acute care
hospitals, and nominal charge hospitals.
In the FY 2016 IPF PPS final rule (80
FR 46693 through 46694), we discussed
analysis conducted to better understand
IPF industry practices for future IPF PPS
refinements. This analysis revealed that
in 2012 to 2013, over 20 percent of IPF
stays show no reported ancillary costs,
such as laboratory and drug costs, on
cost reports or charges on claims. In the
FY 2016 IPF PPS final rule (80 FR
46694), FY 2017 IPF PPS final rule (81
FR 50513), FY 2018 IPF PPS final rule
(82 FR 36784), FY 2019 IPF PPS final
rule (83 FR 38588) and FY 2020 IPF PPS
final rule (84 FR 38458), we reminded
providers that we pay only the IPF for
services furnished to a Medicare
beneficiary who is an inpatient of that
IPF, except for certain professional
services, and payments are considered
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to be payments in full for all inpatient
hospital services provided directly or
under arrangement (see 42 CFR
412.404(d)), as specified in 42 CFR
409.10.
On November 17, 2017, we issued
Transmittal 12, which made changes to
the hospital cost report form CMS–
2552–10 (OMB No. 0938–0050), and
included cost report Level I edit 10710S,
effective for cost reporting periods
ending on or after August 31, 2017. Edit
10710S required that cost reports from
psychiatric hospitals include certain
ancillary costs, or the cost report will be
rejected. On January 30, 2018, we issued
Transmittal 13, which changed the
implementation date for Transmittal 12
to be for cost reporting periods ending
on or after September 30, 2017. CMS
suspended edit 10710S effective April
27, 2018, pending evaluation of the
application of the edit to all-inclusiverate providers. CMS issued Transmittal
15 on October 19, 2018, reinstating the
requirement that cost reports from
psychiatric hospitals, except allinclusive rate providers, include certain
ancillary costs. For details, we refer
readers to see these Transmittals, which
are available on the CMS website at
https://www.cms.gov/regulations-andguidance/guidance/transmittals.
2. Required Intensity of Behavioral
Monitoring and Interventions
As discussed in the November 2004
IPF PPS final rule (69 FR 66946), we
encourage IPFs to code all diagnoses
requiring active treatment during the
IPF stay. These include ICD–10–CM
codes that indicate the required
intensity of behavioral monitoring, such
as cognitive deficit, suicidal ideations,
violent behavior, and need for physical
restraint. The IPF PPS includes
comorbidity and MS–DRG adjustment
factors that increase IPF PPS payment
for stays that include these codes. For
example, ICD–10–CM codes X71
through X83 indicate self-harm. ICD–
10–CM codes under R45 indicate
emotional state including violent
behavior. These and other ICD–10–CM
codes indicate the required intensity of
behavioral monitoring and should be
reported on the IPF claims, if
applicable.
The presence of certain ICD–10–CM
codes as a principal or comorbid
condition is used to adjust IPF PPS
payments to reflect the resource
intensity associated with these
conditions. For example, codes that
group to MS–DRG 884 Organic
Disturbances & Intellectual Disabilities,
and codes that are included in the IPF
comorbidity category for Developmental
Disabilities, result in increased payment
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for IPF stays for patients with cognitive
deficit.
As we further discussed in the
November 2004 IPF PPS final rule (69
FR 66938 through 66944), we developed
comorbidity categories based on the
clinical expertise of physicians to
identify conditions that would require
comparatively more costly treatment
during an IPF stay than other comorbid
conditions. We used a regression
analysis of administrative claims and
cost report data to determine the
adjustment factors associated with each
comorbidity category. In addition, we
used the same regression analysis to
determine the adjustment factors
associated with the 17 MS–DRGs that
are included for payment adjustments
under the IPF PPS (as identified in
Addendum A). As discussed in section
III.C.2.b of this proposed rule, we
routinely update the ICD–10–CM codes
that are included in the MS–DRGs and
comorbidity categories.
We also collect relevant demographic
information such as patient age, and we
collect information and adjust payment
based on the length of IPF stays. Each
of these adjustments reflects the
difference in service intensity, as
measured by increased or decreased
costs, for different patients over the
course of an IPF stay.
In addition, IPFs and psychiatric units
report on claims the ICD–10–PCS codes
for interventions including oncology
treatment procedures, which is used for
adjusting payment under the oncology
comorbidity category, and ECT, which
is paid for using a per treatment amount
as discussed in section III.B.2 of this FY
2024 IPF PPS proposed rule. Other ICD–
10–CM diagnosis codes indicate the
need for certain interventions, such as
detoxification services or substance
abuse (for example, F10.121, which is
included in the drug and alcohol abuse
comorbidity category), dependence on
respirator (for example, Z99.11 included
in the COPD category), and dependence
on renal dialysis (for example, Z99.2
included in the chronic renal failure
category). We note that the IPS PPF does
not currently adjust for burn care, but
recognize there are ICD–10–CM/PCS
codes that denote conditions and
procedures related to burn care. As
discussed in the previous paragraph, the
IPF PPS includes comorbidity
adjustments that reflect the higher
relative costs for active treatment of
these conditions. IPF patients with these
conditions are costlier to treat primarily
because of the costs associated with
interventions and longer lengths of stay.
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3. Request for Information on Data and
Information Collection
As noted in section IV.A of this
proposed rule, our extensive years-long
and ongoing data collection efforts are
consistent with the types of data that the
CAA, 2023 suggests we might collect, as
well as aligns with the purpose for
which the CAA, 2023 requires the data
collection. In this proposed rule, we are
requesting information from the public
to inform revisions to the IPF PPS
required by section 4125(a) of the CAA,
2023. We are seeking information about
specific additional data and information
psychiatric hospitals and psychiatric
units might report that could be
appropriate and useful to help inform
possible revisions to the methodology
for payment rates under the IPF PPS for
FY 2025 and future years if determined
appropriate by the Secretary.
Section 1886(s)(5)(C) of the Act
provides that the Secretary may collect
additional data and information on cost
reports, claims, or otherwise. Therefore,
we are also seeking information about
potential available data and information
sources, including using additional
elements of the current cost reports,
claims, or other sources, taking into
consideration factors such as the timing
and availability of data, the quality of
the potential data and information to be
collected, and the potential
administrative burden on providers,
MACs, and CMS.
We are seeking comment on the
following topics:
• What other data and information
would be beneficial for informing
revisions to the IPF PPS payment
methodologies that are currently
obtainable through claims or cost report
information? What codes, conditions, or
other indicators should we examine in
order to potentially identify this data
from existing sources?
• What other data and information
would be beneficial for informing
revisions to the IPF PPS payment
methodologies that are not routinely
coded on claims or identifiable through
cost report information? What are some
potential alternative sources we could
consider for collecting these data and
information?
• What data and information that is
currently reported on claims data could
be used to inform revisions to the IPF
PPS payment methodologies?
• As we discussed earlier in this FY
2024 IPF PPS proposed rule, the current
IPF PPS payment adjustments were
derived from a regression analysis based
on the FY 2002 MedPAR data file. The
adjustment factors included for payment
were found in the regression analysis to
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be associated with statistically
significant per diem cost differences;
with statistical significance defined as p
less than 0.05. Are there alternative
methodological approaches or
considerations that we should consider
for future analysis?
• What if any additional data or
information should we consider
collecting that could address access to
care in rural and isolated communities?
4. Request for Information About
Charges for Ancillary Services
In conjunction with the FY 2023 IPF
PPS proposed rule (87 FR 19428
through 19429), we posted a report on
the CMS website that summarizes the
results of the latest analysis of more
recent IPF cost and claim information
for potential IPF PPS adjustments, and
requested comments about the results
summarized in the report. That report
showed that approximately 23 percent
of IPF stays were trimmed from the data
set used in that analysis because they
were stays at facilities where fewer than
5 percent of their stays had ancillary
charges. This report is available online
at https://www.cms.gov/Medicare/
Medicare-Fee-for-Service-Payment/
InpatientPsychFacilPPS.
In response to the comment
solicitation, we received a comment
from MedPAC regarding facilities that
do not report ancillary charges on most
or any of their claims. Ancillary services
are the services for which charges are
customarily made in addition to routine
services. These include services such as
labs, drugs, radiology, physical and
occupational therapy services, and other
types of services that typically vary
between stays. Generally, based on the
nature of IPF services and the
conditions of participation 3 applicable
to IPFs, we expect to see ancillary
services and correlating charges, such as
labs and drugs, on most IPF claims. Our
ongoing analysis has found that certain
providers, especially for-profit
freestanding IPFs, are consistently
reporting no ancillary charges or very
minimal ancillary charges. MedPAC
stated that it is not known: whether IPFs
fail to report ancillary charges
separately because they were
appropriately bundled with all other
charges into an all-inclusive per diem
rate; if no ancillary charges were
incurred because the IPF cares for a
3 IPFs are subject to all hospital conditions of
participation, including 42 CFR 482.25, which
specifies that ‘‘The hospital must have
pharmaceutical services that meet the needs of the
patients,’’ and 482.27, which specifies that ‘‘The
hospital must maintain, or have available, adequate
laboratory services to meet the needs of its
patients.’’
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patient mix with lower care needs or
inappropriately stints on care; or if
ancillary charges for services furnished
during the IPF stay are inappropriately
billed outside of the IPF base rate
(unbundling). MedPAC recommended
CMS conduct further investigation into
the lack of certain ancillary costs and
charges and whether IPFs are providing
necessary care and appropriately billing
for inpatient psychiatric services under
the IPF PPS.
As discussed in the previous section
of this FY 2024 IPF PPS proposed rule,
we are requesting information related to
the specific types of data and
information specified in the CAA, 2023,
including the reporting of charges for
ancillary services, such as labs and
drugs, on IPF claims. We are interested
in better understanding IPF industry
practices pertaining to the billing and
provision of ancillary services to inform
future IPF PPS refinements. We are
considering whether to require charges
for ancillary services to be reported on
claims and potentially reject claims if
no ancillary services are reported, and
whether to consider payment for such
claims to be inappropriate or erroneous
and subject to recoupment. Accordingly,
we are soliciting comments on the
following questions:
• What would be the appropriate
level of ancillary charges CMS should
expect to be reported on claims? Are
there specific reasons that an IPF stay
would include no ancillary services?
• What are the reasons that some
providers are not reporting ancillary
charges on their claims?
• Would it be appropriate for CMS to
require and reject claims if there are no
ancillary charges reported? Or should
CMS consider adjusting payment toto
providers that do not report ancillary
charges on their claims? For example,
does the lack of ancillary charges on
claims suggest a lack of reasonable and
necessary treatment during the IPF stay,
and would it be appropriate for CMS to
only apply the IPF PPS patient-level
adjustment factors for claims that
include ancillary charges?
C. Social Drivers of Health
Social drivers of health (SDOH), also
known as social determinants of health,
are the conditions in the environments
where people are born, live, learn, work,
play, worship, and age that affect a wide
range of health, functioning, and
quality-of-life outcomes and risks.4
Studies have shown that there is a
correlation between the effects of low
income and education and overall
4 https://health.gov/healthypeople/priority-areas/
social-determinants-health.
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health status. One study derived that the
lowest income and least educated
individuals were consistently least
healthy.5 We have previously
demonstrated our commitment to
advancing health equity and reducing
health disparities. In the past, and in
our ongoing efforts, we have strived to
identify and implement policies,
procedures, reporting protocols, and
other initiatives in a number of our
programs that address the impact of
SDOH on an individual’s health.
For the IPF Quality Reporting
Program, as discussed in section V.D
below of this proposed rule, we propose
to adopt the Facility Commitment to
Health Equity measure for the FY 2026
payment determination and subsequent
years, the Screening for Social Drivers of
Health measure beginning with
voluntary reporting of data beginning in
CY 2025 with required reporting for the
FY 2027 payment determination and
subsequent years, and the Screen
Positive Rate for Social Drivers of
Health measure beginning with
voluntary reporting of data beginning in
CY 2024 with required reporting for the
FY 2027 payment determination and
subsequent years.
Additionally, in the technical report 6
accompanying the FY 2023 IPF PPS
proposed rule, we explained that we
analyzed the costs associated with
SDOH, but found that our analysis was
confounded by a low frequency of IPF
claims reporting the applicable ICD–10
diagnosis codes. In response to the FY
2023 IPF PPS proposed rule we received
10 comments pertaining to the report on
the analysis of patient-level and facilitylevel adjustment factors, and areas of
interest for further research, including
additional SDOH analysis.
Working in collaboration with a
contractor, subsequent analysis has
shown that other SDOH codes, such as
Z59.9 Problem related to housing and
economic circumstances, unspecified,
are associated with statistically
significant, higher costs. In general, our
analysis found that claims that included
SDOH codes had lower costs than
claims that did not include such codes.
This finding is counterintuitive;
however, we note that studies have
found that there are disparities in the
reporting of SDOH codes, such as
5 Paula A. Braveman, Catherine Cubbin, Susan
Egerter, David R. Williams, and Elsie Pamuk, 2010:
Socioeconomic Disparities in Health in the United
States: What the Patterns Tell Us American Journal
of Public Health 100, S186_S196, https://doi.org/
10.2105/AJPH.2009.166082.
6 https://www.cms.gov/files/document/technicalreport-medicare-program-inpatient-psychiatricfacilities-prospective-payment-system.pdf.
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homelessness.7 Additionally, our
analysis found that certain codes were
associated with increased cost for IPF
treatment. Specifically, the below SDOH
codes in the analysis were found to be
statistically significant and had a stay
count of greater than 100. These codes
had an adjustment factor above 1,
suggesting that these conditions may
increase relative costliness of IPF stays:
• Z559 Problems related to
education and literacy, unspecified.
• Z599 Problems related to housing
and economic circumstances,
unspecified.
• Z600 Problems of adjustment to
life-cycle transitions.
• Z634 Disappearance and death of
family member.
• Z653 Problems related to other
legal circumstances.
• Z659 Problems related to
unspecified psychosocial
circumstances.
We are seeking comments on these
findings and information about whether
it would be appropriate to consider
incorporating these codes into the IPF
PPS in the future, for example as a
patient-level adjustment. Specifically,
for codes that are ‘‘unspecified,’’ we are
seeking information about what types of
conditions or circumstances these codes
might represent. We are seeking any
information that commenters can
provide about the reasons for including
these codes on claims. What factors do
commenters believe we should consider
in order to better understand the cost
regression results presented above?
V. Inpatient Psychiatric Facilities
Quality Reporting (IPFQR) Program
A. Background and Statutory Authority
The Inpatient Psychiatric Facility
Quality Reporting (IPFQR) Program is
authorized by section 1886(s)(4) of the
Act, and it applies to psychiatric
hospitals and psychiatric units paid by
Medicare under the IPF PPS (see section
V.B. of this proposed rule). Section
1886(s)(4)(A)(i) of the Act requires the
Secretary to reduce by 2 percentage
points the annual update to the standard
Federal rate for discharges for the IPF
occurring during such fiscal year 8 for
7 https://aspe.hhs.gov/reports/health-conditionsamong-individuals-history-homelessness-researchbrief-0.
8 We note that the statute uses the term ‘‘rate
year’’ (RY). However, beginning with the annual
update of the inpatient psychiatric facility
prospective payment system (IPF PPS) that took
effect on July 1, 2011 (RY 2012), we aligned the IPF
PPS update with the annual update of the ICD
codes, effective on October 1 of each year. This
change allowed for annual payment updates and
the ICD coding update to occur on the same
schedule and appear in the same Federal Register
document, promoting administrative efficiency. To
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any IPF that does not comply with
quality data submission requirements
under the IPFQR Program, set forth in
accordance with section 1886(s)(4)(C) of
the Act, with respect to an applicable
fiscal year.
Section 1886(s)(4)(C) of the Act
requires IPFs to submit to the Secretary
data on quality measures specified by
the Secretary under section
1886(s)(4)(D) of the Act. Except as
provided in section 1886(s)(4)(D)(ii) of
the Act, section 1886(s)(4)(D)(i) of the
Act requires that any measure specified
by the Secretary must have been
endorsed by the consensus-based entity
(CBE) with a contract under section
1890(a) of the Act. Section
1886(s)(4)(D)(ii) of the Act provides that,
in the case of a specified area or medical
topic determined appropriate by the
Secretary for which a feasible and
practical measure has not been endorsed
by the CBE with a contract under
section 1890(a) of the Act, the Secretary
may specify a measure that is not
endorsed as long as due consideration is
given to measures that have been
endorsed or adopted by a consensus
organization identified by the Secretary.
We refer readers to the FY 2019 IPF
PPS final rule (83 FR 38589) for a more
detailed discussion of the background
and statutory authority of the IPFQR
Program.
For the IPFQR Program, we refer to
the year in which an IPF would receive
the 2-percentage point reduction to the
annual update to the standard Federal
rate as the payment determination year.
An IPF generally meets IPFQR Program
requirements by submitting data on
specified quality measures in a specified
time and manner during a data
submission period that occurs prior to
the payment determination year. These
data reflect a period prior to the data
submission period during which the IPF
furnished care to patients; this period is
known as the performance period. For
example, for a measure for which CY
2024 is the performance period which is
required to be submitted in CY 2025 and
affects FY 2026 payment determination,
if an IPF did not submit the data for this
measure as specified during CY 2025
(and meets all other IPFQR Program
reflect the change to the annual payment rate
update cycle, we revised the regulations at 42 CFR
412.402 to specify that, beginning October 1, 2012,
the IPF PPS RY means the 12-month period from
October 1 through September 30, which we refer to
as a ‘‘fiscal year’’ (FY) (76 FR 26435). Therefore,
with respect to the IPFQR Program, the terms ‘‘rate
year,’’ as used in the statute, and ‘‘fiscal year’’ as
used in the regulation, both refer to the period from
October 1 through September 30. For more
information regarding this terminology change, we
refer readers to section III of the RY 2012 IPF PPS
final rule (76 FR 26434 through 26435).
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requirements for the FY 2026 payment
determination) we would reduce by 2percentage points that IPF’s update for
the FY 2026 payment determination
year.
In this proposed rule, we propose to
codify the IPFQR Program requirements
governing IPF reporting on quality
measures in a new regulation at
§ 412.433, which is the section
preceding our existing regulation
governing reconsideration and appeals
procedures for IPFQR Program decisions
in our regulations at § 412.434.
Specifically, we propose to codify a
general statement of the IPFQR Program
authority and structure at § 412.433(a).
If finalized, paragraph (a) would cite
section 1886(s)(4) of the Act, which
requires the Secretary to implement a
quality reporting program for inpatient
psychiatric hospitals and psychiatric
units. The proposed paragraph (a)
would also state that IPFs paid under
the IPF PPS as provided in section
1886(s)(1) of the Act that do not report
data required for the quality measures
selected by the Secretary in a form and
manner, and at a time specified by the
Secretary will incur a 2.0 percentage
point reduction to the annual update to
the standard Federal rate with respect to
the applicable fiscal year.
We welcome comments on this
proposal.
B. Covered Entities
In the FY 2013 IPPS/LTCH PPS final
rule (77 FR 53645), we established that
the IPFQR Program’s quality reporting
requirements cover those psychiatric
hospitals and psychiatric units paid by
Medicare under IPF PPS in accordance
with § 412.404(b). Generally, psychiatric
hospitals and psychiatric units within
acute care and critical access hospitals
(CAHs) that treat Medicare patients are
paid under the IPF PPS. Consistent with
previous regulations, we continue to use
the terms ‘‘facility’’ or ‘‘IPF’’ to refer to
both inpatient psychiatric hospitals and
psychiatric units. This usage follows the
terminology in our IPF PPS regulations
at § 412.402. For more information on
covered entities, we refer readers to the
FY 2013 IPPS/LTCH PPS final rule (77
FR 53645).
C. Previously Finalized Measures
The current IPFQR Program includes
14 measures for the FY 2024 payment
determination. For more information on
these measures, we refer readers to
Table 20 of this proposed rule (see
section V.G of this proposed rule).
D. Measure Adoption
We strive to put patients and
caregivers first, ensuring they are
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empowered to partner with their
clinicians in their healthcare decisionmaking using information from datadriven insights that are increasingly
aligned with meaningful quality
measures. We support technology that
reduces burden and allows clinicians to
focus on providing high-quality
healthcare for their patients. We also
support innovative approaches to
improve quality, accessibility, and
affordability of care while paying
particular attention to improving
clinicians’ and beneficiaries’
experiences when interacting with our
programs. In combination with other
efforts across HHS, we believe the
IPFQR Program helps to incentivize
IPFs to improve healthcare quality and
value while giving patients and
providers the tools and information
needed to make the best individualized
decisions. Consistent with these goals,
our objective in selecting quality
measures for the IPFQR Program is to
balance the need for information on the
full spectrum of care delivery and the
need to minimize the burden of data
collection and reporting. We have
primarily focused on measures that
evaluate critical processes of care that
have significant impact on patient
outcomes and support CMS and HHS
priorities for improved quality and
efficiency of care provided by IPFs.
When possible, we also propose to
incorporate measures that directly
evaluate patient outcomes and
experience. We refer readers to the CMS
National Quality Strategy,9 the
Behavioral Health Strategy,10 the
Framework for Health Equity,11 and the
Meaningful Measures Framework 12 for
information related to our priorities in
selecting quality measures.
1. Measure Selection Process
Section 1890A of the Act requires that
the Secretary establish and follow a prerulemaking process, in coordination
with the consensus-based entity (CBE)
9 Schreiber, M, Richards, A, et al. (2022). The
CMS National Quality Strategy: A Person-Centered
Approach to Improving Quality. Available at:
https://www.cms.gov/blog/cms-national-qualitystrategy-person-centered-approach-improvingquality. Accessed on February 20, 2023.
10 CMS. (2022). CMS Behavioral Health Strategy.
Available at https://www.cms.gov/cms-behavioralhealth-strategy. Accessed on February 20, 2023.
11 CMS. (2022). CMS Framework for Health
Equity 2022–2032. Available at https://
www.cms.gov/files/document/cms-frameworkhealth-equity-2022.pdf. Accessed on February 20,
2023.
12 CMS. (2022). Meaningful Measures 2.0: Moving
from Measure Reduction to Modernization.
Available at https://www.cms.gov/medicare/
meaningful-measures-framework/meaningfulmeasures-20-moving-measure-reductionmodernization. Accessed on February 20, 2023.
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with a contract under section 1890 of
the Act, to solicit input from certain
groups regarding the selection of quality
and efficiency measures for the IPFQR
Program. Before being proposed for
inclusion in the IPFQR Program,
measures are placed on a list of
Measures Under Consideration (MUC)
list, which is published annually on
behalf of CMS by the consensus-based
entity (CBE),13 with which the Secretary
must contract as required by section
1890(a) of the Act. Following
publication on the MUC list, the
Measure Applications Partnership
(MAP), a multi-stakeholder group
convened by the CBE, reviews the
measures under consideration for the
IPFQR Program, among other Federal
programs, and provides input on those
measures to the Secretary. We consider
the input and recommendations
provided by the MAP in selecting all
measures for the IPFQR Program.
Information about the MAP’s input on
each of our proposed measures is
described in the following subsections.
In our evaluation of the IPFQR Program
measure set, we identified four
measures that we believe are
appropriate for adoption for the IPFQR
Program:
• Facility Commitment to Health
Equity;
• Screening for Social Drivers of
Health;
• Screen Positive Rate for Social
Drivers of Health; and
• Psychiatric Inpatient Experience
(PIX) Survey.
These four measures are described in
the following subsections.
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2. Proposal To Adopt the Facility
Commitment to Health Equity Measure
Beginning With the CY 2024 Reporting
Period Reported in CY 2025/FY 2026
Payment Determination
a. Background
Significant and persistent disparities
in healthcare outcomes exist in the
United States. For example, belonging to
a racial or ethnic minority group, living
with a disability, being a member of the
lesbian, gay, bisexual, transgender, and
queer (LGBTQ+) community, being a
member of a religious minority, living in
a rural area, or being near or below the
poverty level, is often associated with
worse health
outcomes.14 15 16 17 18 19 20 21 22 23
13 In previous years, we referred to the consensusbased entity by corporate name. We have updated
this language to refer to the consensus-based entity
more generally.
14 Joynt KE, Orav E, Jha AK. (2011). Thirty-Day
Readmission Rates for Medicare Beneficiaries by
Race and Site of Care. JAMA, 305(7), 675 681.
Available at: https://jamanetwork.com/journals/
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Numerous studies have shown that
among Medicare beneficiaries, racial
and ethnic minority individuals often
receive clinical care of lower quality,
report having worse care experiences,
and experience more frequent hospital
readmissions and procedural
complications.24 25 26 27 28 29 Readmission
jama/fullarticle/645647. Accessed on February 13,
2023.
15 Lindenauer PK, Lagu T, Rothberg MB, et al.
(2013). Income Inequality and Thirty-Day Outcomes
After Acute Myocardial Infarction, Heart Failure,
and Pneumonia: Retrospective Cohort Study. BMJ,
346. Available at: https://doi.org/10.1136/bmj.f521.
Accessed on February 13, 2023.
16 Trivedi AN, Nsa W, Hausmann LRM, et al.
(2014). Quality and Equity of Care in U.S. Hospitals.
N Engl J Med, 371(24), 229 8-2308. Available at:
https://www.nejm.org/doi/10.1056/NEJMsa1405003.
Accessed on February 13, 2023.
17 Polyakova, M, Udalova V, et al. (2021). Racial
Disparities In Excess All-Cause Mortality During
The Early COVID–19 Pandemic Varied
Substantially Across States. Health Affairs, 40(2),
307–316. Available at: https://doi.org/10.1377/
hlthaff.2020.02142. Accessed on February 14, 2023.
18 Rural Health Research Gateway. (2018). Rural
Communities: Age, Income, and Health Status.
Rural Health Research Recap. Available at: https://
www.ruralhealthresearch.org/assets/2200-8536/
rural-communities-age-income-health-statusrecap.pdf. Accessed on February 14, 2023.
19 HHS Office of Minority Health. (2020). Progress
Report to Congress, 2020 Update on the Action Plan
to Reduce Racial and Ethnic Health Disparities.
Department of Health and Human Services.
Available at: https://www.minorityhealth.hhs.gov/
assets/PDF/UpdatelHHSlDisparitieslDeptFY2020.pdf. Accessed on February 14, 2023.
20 Heslin KC, Hall JE. (2021). Sexual Orientation
Disparities in Risk Factors for Adverse COVID–19–
Related Outcomes, by Race/Ethnicity—Behavioral
Risk Factor Surveillance System, United States,
2017-2019. MMWR Morb Mortal Wkly Rep, 70(5),
149. Available at: https://www.cdc.gov/mmwr/
volumes/70/wr/mm7005a1.htm. Accessed on
February 14, 2023.
21 Poteat TC, Reisner SL, Miller M, Wirtz AL.
(2020). COVID–19 Vulnerability of Transgender
Women With and Without HIV Infection in the
Eastern and Southern U.S. medRxiv. Available at:
https://www.medrxiv.org/content/10.1101/
2020.07.21.20159327v1.full.pdf. Accessed on
February 14, 2023.
22 Vu M, Azmat A, Radejko T, Padela AI. (2016).
Predictors of Delayed Healthcare Seeking Among
American Muslim Women. Journal of Women’s
Health, 25(6), 586–593. Available at: https://
www.ncbi.nlm.nih.gov/pmc/articles/PMC5912720/.
Accessed on February 14, 2023.
23 Nadimpalli SB, Cleland CM, Hutchinson MK,
Islam N, Barnes LL, Van Devanter N. (2016). The
Association Between Discrimination and the Health
of Sikh Asian Indians. Health Psychology, 35(4),
351–355. Available at: https://doi.org/10.1037/
hea0000268. Accessed on February 14, 2023.
24 CMS Office of Minority Health. (2020). Racial,
Ethnic, and Gender Disparities in Healthcare in
Medicare Advantage. Baltimore, MD: Centers for
Medicare & Medicaid Services. Available at: https://
www.cms.gov/files/document/2020-national-levelresults-race-ethnicity-and-gender-pdf.pdf. Accessed
on February 14, 2023.
25 CMS Office of Minority Health. (2018). Guide
to Reducing Disparities in Readmissions. Available
at: https://www.cms.gov/About-CMS/AgencyInformation/OMH/Downloads/
OMHlReadmissionslGuide.pdf. Accessed on
February 14, 2023.
26 Singh JA, Lu X, et al. (2014). Racial Disparities
in Knee and Hip Total Joint Arthroplasty: An 18-
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rates in the Hospital Readmissions
Reduction Program have been shown to
be higher among Black and Hispanic
Medicare beneficiaries with common
conditions, including congestive heart
failure and acute myocardial
infarction.30 31 32 33 34 Data indicate that,
even after accounting for factors such as
socioeconomic conditions, members of
racial and ethnic minority groups
reported experiencing lower quality of
healthcare.35 Evidence of differences in
quality of care received among people
from racial and ethnic minority groups
shows worse health outcomes,
year analysis of national Medicare data. Ann
Rheum Dis., 73(12), 2107–15. Available at: https://
ard.bmj.com/content/73/12/2107.full. Accessed on
February 14, 2023.
27 Rivera-Hernandez M, Rahman M, Mor V,
Trivedi AN. (2019). Racial Disparities in
Readmission Rates among Patients Discharged to
Skilled Nursing Facilities. J Am Geriatr Soc., 67(8),
1672–1679. Available at: https://doi.org/10.1111/
jgs.15960. Accessed on February 14, 2023.
28 Joynt KE, Orav E, Jha AK. (2011). Thirty-Day
Readmission Rates for Medicare Beneficiaries by
Race and Site of Care. JAMA, 305(7), 675–681.
Available at: https://jamanetwork.com/journals/
jama/fullarticle/645647. Accessed on February 13,
2023.
29 Tsai TC, Orav EJ, Joynt KE. (2014). Disparities
in Surgical 30-day Readmission Rates for Medicare
Beneficiaries by Race and Site of Care. Ann Surg.,
259(6), 1086–1090. Available at: https://
www.ncbi.nlm.nih.gov/pmc/articles/PMC4107654/.
Accessed on February 14, 2023.
30 Rodriguez F, Joynt KE, Lopez L, Saldana F, Jha
AK. (2011). Readmission Rates for Hispanic
Medicare Beneficiaries with Heart Failure and
Acute Myocardial Infarction. Am Heart J., 162(2),
254–261 e253. Available at: https://
www.sciencedirect.com/science/article/pii/
S0002870311003966?viewFullText=true. Accessed
on February 14, 2023.
31 Centers for Medicare & Medicaid Services.
(2014). Medicare Hospital Quality Chartbook:
Performance Report on Outcome Measures.
Available at: https://www.hhs.gov/guidance/sites/
default/files/hhs-guidance-documents/
YNHlChartbookl2014l
508CompliantlFINAL.pdf. Accessed on February
14, 2023.
32 CMS Office of Minority Health. (2018). Guide
to Reducing Disparities in Readmissions. Available
at: https://www.cms.gov/About-CMS/AgencyInformation/OMH/Downloads/
OMHlReadmissionslGuide.pdf. Accessed on
February 14, 2023.
33 Prieto-Centurion V, Gussin HA, Rolle AJ,
Krishnan JA. (2013). Chronic Obstructive
Pulmonary Disease Readmissions at Minority
Serving Institutions. Ann Am Thorac Soc., 10(6),
680–684. Available at: https://doi.org/10.1513/
AnnalsATS.201307-223OT. Accessed on February
14, 2023.
34 Joynt KE, Orav E, Jha AK. (2011). Thirty-Day
Readmission Rates for Medicare Beneficiaries by
Race and Site of Care. JAMA, 305(7), 675–681.
Available at: https://jamanetwork.com/journals/
jama/fullarticle/645647. Accessed on February 13,
2023.
35 Nelson AR. (2003). Unequal Treatment: Report
of the Institute of Medicine on Racial and Ethnic
Disparities in Healthcare. The Annals of Thoracic
Surgery, 76(4), S1377–S1381. https://
www.annalsthoracicsurgery.org/action/
showPdf?pii=S0003-4975%2803%2901205-0.
Accessed on February 14, 2023.
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including a higher incidence of diabetes
complications such as retinopathy.36
Additionally, inequities in the social
drivers of health (SDOH) affecting these
groups, such as poverty and healthcare
access, are interrelated and influence a
wide range of health and quality-of-life
outcomes and risks.37
Because we are working toward the
goal of all patients receiving highquality healthcare, regardless of
individual characteristics, we are
committed to supporting healthcare
organizations in building a culture of
safety and equity that focuses on
educating and empowering their
workforce to recognize and eliminate
health disparities. This includes
patients receiving the right care, at the
right time, in the right setting for their
condition(s), regardless of those
characteristics.
In the FY 2022 IPF PPS final rule (86
FR 42625 through 42632), we
summarized the comments we received
in response to our Request for
Information (RFI) on closing health
equity gaps in our quality programs,
specifically the IPFQR Program. In
response to this RFI, several
commenters recommended that we
consider a measure of organizational
commitment to health equity. These
commenters further described how
infrastructure supports delivery of
equitable care. In the FY 2023 IPF PPS
final rule (87 FR 46865 through 46873),
we described our RFI on overarching
principles for measuring equity and
healthcare quality across our quality
programs and summarized the
comments we received in response to
that RFI. Because we had specifically
solicited comments on the potential for
a structural measure assessing an IPF’s
commitment to health equity, many
commenters provided input on a
structural measure. While many
commenters supported the concept, one
commenter expressed concern with this
measure concept and stated that there is
no evidence that performance on this
measure would lead to improved patient
outcomes (87 FR 46872 through 46873).
However, we believe that strong and
committed leadership from IPF
executives and board members is
essential and can play a role in shifting
36 Peek, ME, Odoms-Young, A, et al. (2010). Race
and Shared Decision-Making: Perspectives of
African-Americans with diabetes. Social Science &
Medicine, 71(1), 1–9. Available at: https://
www.ncbi.nlm.nih.gov/pmc/articles/PMC2885527/.
Accessed on February 14, 2023.
37 Department of Health and Human Services.
(2023). Healthy People 2030: Social Determinants of
Health. Available at: https://health.gov/
healthypeople/priority-areas/social-determinantshealth. Accessed on February 20, 2023.
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organizational culture and advancing
equity goals.
Additionally, studies demonstrate
that facility leadership can positively
influence culture for better quality,
patient outcomes, and experience of
care.38 39 40 A systematic review of 122
published studies showed that strong
leadership that prioritized safety,
quality, and the setting of clear guidance
with measurable goals for improvement
resulted in high-performing facilities
with better patient outcomes.41
Therefore, we believe leadership
commitment to health equity will have
a parallel effect in contributing to a
reduction in health disparities.
Further, we note that the Agency for
Healthcare Research and Quality
(AHRQ) and The Joint Commission
(TJC) identified that facility leadership
plays an important role in promoting a
culture of quality and safety.42 43 44 For
instance, AHRQ research shows that a
facility’s board can influence quality
and safety in a variety of ways, not only
38 Bradley EH, Brewster AL, et al. (2018). How
Guiding Coalitions Promote Positive Culture
Change in Hospitals: A Longitudinal Mixed
Methods Interventional Study. BMJ Qual Saf., 27(3),
218–225. Available at: https://
qualitysafety.bmj.com/content/qhc/27/3/
218.full.pdf. Accessed on February 14, 2023.
39 Smith SA, Yount N, Sorra J. (2017). Exploring
Relationships Between Hospital Patient Safety
Culture and Consumer Reports Safety Scores. BMC
Health Services Research, 17(1), 143. Available at:
https://bmchealthservres.biomedcentral.com/
articles/10.1186/s12913-017-2078-6. Accessed on
February 14, 2023.
40 Keroack MA, Youngberg BJ, et al. (2007).
Organizational Factors Associated with High
Performance in Quality and Safety in Academic
Medical Centers. Acad Med., 82(12), 1178 86.
Available at: https://journals.lww.com/
academicmedicine/Fulltext/2007/12000/
OrganizationallFactorsl
AssociatedlwithlHigh.14.aspx. Accessed on
February 14, 2023.
41 Millar R, Mannion R, Freeman T, et al. (2013).
Hospital Board Oversight of Quality and Patient
Safety: A Narrative Review and Synthesis of Recent
Empirical Research. The Milbank Quarterly, 91(4),
738–70. Available at: https://
onlinelibrary.wiley.com/doi/10.1111/14680009.12032. Accessed February 14, 2023.
42 Agency for Healthcare Research and Quality.
Leadership Role in Improving Patient Safety.
Patient Safety Primer, September 2019. Available at:
https://psnet.ahrq.gov/primer/leadership-roleimproving-safety. Accessed on February 14, 2023.
43 Joint Commission on Accreditation of
Healthcare Organizations, USA. The essential role
of leadership in developing a safety culture.
Sentinel Event Alert. 2017 (Revised June 2021).
Available at: https://www.jointcommission.org/-/
media/tjc/documents/resources/patient-safetytopics/sentinel-event/sea-57-safety-culture-andleadership-final2.pdf. Accessed on February 15,
2023.
44 See information on launch of new ‘‘Health Care
Equity Certification’’ in July 2023 from Joint
Commission on Accreditation of Healthcare
Organizations, USA, available at: https://
www.jointcommission.org/our-priorities/healthcare-equity/health-care-equity-prepublication/.
Accessed on February 15, 2023.
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through strategic initiatives, but also
through more direct interactions with
frontline workers.45
In addition, the Institute of Healthcare
Improvement’s (IHI’s) research of 23
health systems throughout the United
States and Canada shows that health
equity must be a priority championed
by leadership teams to improve both
patient access to needed healthcare
services and outcomes among
populations that have been
disadvantaged by the healthcare
system.46 This IHI study specifically
identified concrete actions to make
advancing health equity a core strategy,
including establishing this goal as a
leader-driven priority alongside
organizational development structures
and processes.47
Based upon these findings, we believe
that IPF leadership can be instrumental
in setting specific, measurable,
attainable, realistic, and time-based
(SMART) goals to assess progress
towards achieving equity goals and
ensuring high-quality care is accessible
to all. Therefore, consistent with the
Hospital Inpatient Quality Reporting
(IQR) Program’s adoption of an
attestation-based structural measure in
the FY 2023 IPPS/LTCH PPS final rule
(87 FR 49191 through 49201), we
propose to adopt an attestation-based
structural measure, Facility
Commitment to Health Equity, to
address health equity beginning with
the CY 2024 reporting period/FY 2026
payment determination.
The first pillar of our strategic
priorities 48 reflects our deep
commitment to improvements in health
equity by addressing the health
disparities that underly our health
system. In line with this strategic pillar,
we developed this structural measure to
assess facility commitment to health
equity across five domains (described in
Table 17 in the section V.D.2.b of this
proposed rule) using a suite of
45 Agency for Healthcare Research and Quality.
Leadership Role in Improving Patient Safety.
Patient Safety Primer. (2019). Available at: https://
psnet.ahrq.gov/primer/leadership-role-improvingsafety. Accessed on February 14, 2023.
46 Mate KS and Wyatt R. (2017). Health Equity
Must Be a Strategic Priority. NEJM Catalyst.
Available at: https://catalyst.nejm.org/doi/full/
10.1056/CAT.17.0556. Accessed on February 15,
2023.
47 Mate KS and Wyatt R. (2017). Health Equity
Must Be a Strategic Priority. NEJM Catalyst.
Available at: https://catalyst.nejm.org/doi/full/
10.1056/CAT.17.0556. Accessed on February 15,
2023.
48 Brooks-LaSure, C. (2021). My First 100 Days
and Where We Go From Here: A Strategic Vision
for CMS. Centers for Medicare & Medicaid.
Available at: https://www.cms.gov/blog/my-first100-days-and-where-we-go-here-strategic-visioncms. Accessed on February 15, 2023.
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organizational competencies aimed at
achieving health equity for racial and
ethnic minority groups, people with
disabilities, members of the LGBTQ+
community, individuals with limited
English proficiency, rural populations,
religious minorities, and people facing
socioeconomic challenges. We believe
these elements are actionable focus
areas, and assessment of IPFs’
leadership commitment to them is
foundational.
We also believe adoption of the
proposed Facility Commitment to
Health Equity measure would
incentivize IPFs to collect and utilize
data to identify critical equity gaps,
implement plans to address these gaps,
and ensure that resources are dedicated
toward addressing health equity
initiatives. While many factors
contribute to health equity, we believe
this measure is an important step
toward assessing IPFs’ leadership
commitment, and a fundamental step
toward closing the gap in equitable care
for all populations. We note that this
measure is not intended to encourage
IPFs to act on any one data element or
domain, but instead encourages IPFs to
analyze their own findings to
understand if there are any demographic
factors (for example, race, national
origin, primary language, and ethnicity)
as well as SDOHs (for example, housing
status and food security) associated with
underlying inequities and, in turn,
develop solutions to deliver more
equitable care. Thus, the proposed
Facility Commitment to Health Equity
measure aims to support IPFs in
leveraging available data, pursuing
focused quality improvement activities,
and promoting efficient and effective
use of resources.
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The proposed Facility Commitment to
Health Equity measure aligns with the
measure previously adopted in the
Hospital IQR Program, and we refer
readers to the FY 2023 IPPS/LTCH PPS
final rule (87 FR 49191 through 49201)
for more information regarding the
measure’s adoption in the Hospital IQR
Program. The five domains of the
proposed measure are adapted from the
CMS Office of Minority Health’s
Building an Organizational Response to
Health Disparities framework, which
focuses on data collection, data analysis,
culture of equity, and quality
improvement.49
The proposed measure also aligns
with our efforts under the Meaningful
Measures Framework, which identifies
high-priority areas for quality
measurement and improvement to
assess core issues most critical to highquality healthcare and improving
patient outcomes.50 In 2021, we
launched Meaningful Measures 2.0 to
promote innovation and modernization
of all aspects of quality, and to address
a wide variety of settings, stakeholders,
and measure requirements.51 We are
49 CMS. (2021). Building an Organizational
Response to Health Disparities [Fact Sheet].
Available at: https://www.cms.gov/About-CMS/
Agency-Information/OMH/Downloads/HealthDisparities-Guide.pdf. Accessed on February 15,
2023.
50 Centers for Medicare & Medicaid Services.
Meaningful Measures Framework. Available at:
https://www.cms.gov/Medicare/Quality-InitiativesPatient-Assessment-Instruments/
QualityInitiativesGenInfo/CMS-Quality-Strategy.
Accessed on February 15, 2023.
51 CMS. (2022). Meaningful Measures 2.0: Moving
from Measure Reduction to Modernization.
Available at https://www.cms.gov/medicare/
meaningful-measures-framework/meaningfulmeasures-20-moving-measure-reductionmodernization. Accessed on February 20, 2023.
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addressing healthcare priorities and
gaps with Meaningful Measures 2.0 by
leveraging quality measures to promote
equity and close gaps in care. The
proposed Facility Commitment to
Health Equity measure supports these
efforts and is aligned with the
Meaningful Measures Area of ‘‘Equity of
Care’’ and the Meaningful Measures 2.0
goal to ‘‘Leverage Quality Measures to
Promote Equity and Close Gaps in
Care.’’ This proposed measure also
supports the Meaningful Measures 2.0
objective to commit to a patientcentered approach in quality measure
and value-based incentives programs to
ensure that quality and safety measures
address health equity.
b. Overview of Measure
The proposed Facility Commitment to
Health Equity measure would assess
IPFs’ commitment to health equity using
a suite of equity-focused organizational
competencies aimed at achieving health
equity for populations that have been
disadvantaged, marginalized, and
underserved by the healthcare system.
As previously noted, these populations
include, but are not limited to, racial
and ethnic minority groups, people with
disabilities, members of the LGBTQ+
community, individuals with limited
English proficiency, rural populations,
religious minorities, and people facing
socioeconomic challenges. Table 17 sets
forth the five attestation domains, and
the elements within each of those
domains, to which an IPF would
affirmatively attest for the IPF to receive
credit for that domain within the
proposed Facility Commitment to
Health Equity measure.
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TABLE 17—THE FACILITY COMMITMENT TO HEALTH EQUITY MEASURE FIVE ATTESTATIONS
Elements: Select all that apply
(Note: Affirmative attestation of all elements within a domain would be
required for the facility to receive a point for the domain in the
numerator)
Attestation
Domain 1: Equity is a Strategic Priority
Facility commitment to reducing healthcare disparities is strengthened when equity is a key organizational priority. Please attest
that your facility has a strategic plan for advancing health equity * and that it includes all the following elements.
Domain 2: Data Collection
Collecting valid and reliable demographic and SDOH data on patients served in a facility is an important step in identifying and
eliminating health disparities. Please attest that your facility engages in the following activities.
Domain 3: Data Analysis
Effective data analysis can provide insights into which factors contribute to health disparities and how to respond. Please attest
that your facility engages in the following activities.
Domain 4: Quality Improvement
Health disparities are evidence that high-quality care has not been
delivered equitably *** to all patients. Engagement in quality improvement activities can improve quality of care for all patients..
Domain 5: Leadership Engagement
Leaders and staff can improve their capacity to address disparities
by demonstrating routine and thorough attention to equity and
setting an organizational culture of equity. Please attest that
your facility engages in the following activities..
(A) Our facility strategic plan identifies priority populations who currently experience health disparities.
(B) Our facility strategic plan identifies health equity goals and discrete
action steps to achieving these goals.*
(C) Our facility strategic plan outlines specific resources which have
been dedicated to achieving our equity goals.
(D) Our facility strategic plan describes our approach for engaging key
stakeholders, such as community-based organizations.
(A) Our facility collects demographic information (such as self-reported
race, national origin, primary language, and ethnicity data) and/or social determinant of health information on the majority of our patients.**
(B) Our facility has training for staff in culturally sensitive collection of
demographic and/or SDOH information.
(C) Our facility inputs demographic and/or SDOH information collected
from patients into structured, interoperable data elements using a
certified electronic health record (EHR) technology.
(A) Our facility stratifies key performance indicators by demographic
and/or SDOH variables to identify equity gaps and includes this information on facility performance dashboards.
(A) Our facility participates in local, regional, or national quality improvement activities focused on reducing health disparities.
(A) Our facility senior leadership, including chief executives and the entire facility **** board of trustees, annually reviews our strategic plan
for achieving health equity.
(B) Our facility senior leadership, including chief executives and the entire facility board of trustees, annually reviews key performance indicators stratified by demographic and/or social factors.
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* After publication of the 2022 MUC List, we clarified the language in Domain 1 to refer to ‘‘health equity’’ instead of ‘‘healthcare equity.’’
** After publication of the 2022 MUC List, we clarified the language in Domain 2 to refer to example demographic information.
*** After publication of the 2022 MUC List, we clarified the language in Domain 4: ‘‘Health disparities are evidence that high quality care has
not been delivered equitably to all patients.’’
**** After publication of the 2022 MUC List, we identified that Domain 5 incorrectly referred to the ‘‘hospital board of trustees’’ instead of the
‘‘facility board of trustees.’’
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(1) Measure Calculation
The proposed Facility Commitment to
Health Equity measure consists of five
attestation-based questions, each
representing a separate domain of the
IPF’s commitment to addressing health
equity. Some of these domains have
multiple elements to which an IPF
would be required to attest. For an IPF
to affirmatively attest ‘‘yes’’ to a domain,
and receive credit for that domain, the
IPF would evaluate and determine
whether it engages in each of the
elements that comprise that domain.
Each of the domains would be
represented in the denominator as a
point, for a total of five points (that is,
one point per domain).
The numerator of the proposed
Facility Commitment to Health Equity
measure would capture the total number
of domain attestations that the IPF is
able to affirm. An IPF that affirmatively
attests to each element within the five
domains would receive the maximum
five points.
An IPF would only receive a point for
a domain if it attests ‘‘yes’’ to all related
elements within that domain. There is
no ‘‘partial credit’’ for elements. For
example, for Domain 1 (‘‘Facility
commitment to reducing healthcare
disparities is strengthened when equity
is a key organizational priority’’), an IPF
would evaluate and determine whether
its strategic plan meets each of the
elements described in (A) through (D)
(see Table 17 in section V.D.2.b of this
proposed rule). If the IPF’s strategic plan
meets all four of these elements, the IPF
would affirmatively attest ‘‘yes’’ to
Domain 1 and would receive one (1)
point for that attestation. An IPF would
not be able to receive partial credit for
a domain. For example, if the IPF’s
strategic plan meets elements (A) and
(B), but not (C) and (D), of Domain 1,
then the IPF would not be able to
affirmatively attest ‘‘yes’’ to Domain 1
and would not receive a point for that
attestation, and instead would receive
zero points for Doman 1.
In response to our RFI on the
potential for a structural measure
assessing an IPF’s commitment to health
equity, several commenters expressed
concern that such a measure would be
difficult for IPFs to report because of the
requirement to use certified electronic
health record (EHR) technology for
Domain 2 (87 FR 46972 through 46873).
We believe that use of certified EHR
technology is an important element of
collecting valid and reliable
demographic and social drivers of
health data on patients served in an IPF
and that use of this technology
facilitates data analytics to ensure
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consistent, high-quality, equitable care.
However, we recognize that some IPFs
may face challenges to adopting
certified EHR technology. We note that
the IPFQR Program is a pay-forreporting program, not a pay-forperformance program, and therefore
IPFs that do not have certified EHR
technology can attest that they satisfy
the other domains, as applicable, and
receive a score of 0–4 out of 5 without
any penalties.
(2) Review by the Measure Applications
Partnership (MAP)
We included the proposed Facility
Commitment to Health Equity measure
on the publicly available ‘‘List of
Measures Under Consideration for
December 1, 2022’’ (MUC List), a list of
measures under consideration for use in
various Medicare programs.52 The
specifications for the proposed Facility
Commitment to Health Equity measure,
which were available during the review
of the MUC List, are available on the
CMS website at: https://
mmshub.cms.gov/sites/default/files/
map-hospital-measure-specificationsmanual-2022.pdf.
The Consensus-Based Entity (CBE)
convened Measure Applications
Partnership (MAP) Health Equity
Advisory Group reviewed the MUC List
and the proposed Facility Commitment
to Health Equity measure (MUC 2022–
027) in detail on December 6 through 7,
2022.53 The MAP Health Equity
Advisory Group raised concerns that
this measure does not evaluate
outcomes and may not directly address
health inequities at a systemic level, but
generally agreed that a structural
measure such as this one represents
progress toward improving equitable
care.54
In addition, on December 8 through 9,
2022, the MAP Rural Health Advisory
Group reviewed the 2022 MUC List and
expressed support for this measure as a
step towards advancing access to and
quality of care with the caveat that
resource challenges exist in rural
communities.55
52 Centers
for Medicare & Medicaid Services. List
of Measures Under Consideration for December 1,
2022. Available at: https://mmshub.cms.gov/
measure-lifecycle/measure-implementation/prerulemaking/lists-and-reports.
53 Centers for Medicare & Medicaid Services.
2022–2023 MAP Final Recommendations. Available
at: https://mmshub.cms.gov/measure-lifecycle/
measure-implementation/pre-rulemaking/lists-andreports.
54 Centers for Medicare & Medicaid Services.
2022–2023 MAP Final Recommendations. Available
at: https://mmshub.cms.gov/measure-lifecycle/
measure-implementation/pre-rulemaking/lists-andreports.
55 Centers for Medicare & Medicaid Services.
2022–2023 MAP Final Recommendations. Available
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The MAP Hospital Workgroup
reviewed the 2022 MUC List on
December 13 through 14, 2022.56 The
MAP Hospital Workgroup recognized
that reducing health care disparities
would represent a substantial benefit to
overall quality of care but expressed
reservations about the measure’s link to
clinical outcomes. As stated in the MAP
recommendations document, the MAP
Hospital Workgroup members voted to
conditionally support the Facility
Commitment to Health Equity measure
for rulemaking pending: (1)
endorsement by the CBE; (2)
commitment to consideration of equity
related outcome measures in the future;
(3) provision of more clarity on the
Facility Commitment to Health Equity
measure and supplementing
interpretation with results; and (4)
verification of accurate attestation by
IPFs.57 Thereafter, the MAP
Coordinating Committee deliberated on
January 24 through 25, 2023 and
ultimately voted to uphold the MAP
Hospital Workgroup’s recommendation
to conditionally support the measure for
rulemaking.58
We believe that the proposed Facility
Commitment to Health Equity measure
establishes an important foundation for
prioritizing the achievement of health
equity among IPFs participating in the
IPFQR Program. Our approach to
developing health equity measures has
been incremental to date, but we see
inclusion of such measures in the
IPFQR Program as informing efforts to
advance and achieve health equity not
only among IPFs, but also other acute
care settings. We believe this proposed
measure to be a building block that lays
the groundwork for a future meaningful
suite of measures that would assess IPF
progress in providing high-quality
healthcare for all patients regardless of
social risk factors or demographic
characteristics.
(3) CBE Endorsement
We have not submitted this measure
for CBE endorsement at this time.
at: https://mmshub.cms.gov/measure-lifecycle/
measure-implementation/pre-rulemaking/lists-andreports.
56 Centers for Medicare & Medicaid Services.
2022–2023 MAP Final Recommendations. Available
at: https://mmshub.cms.gov/measure-lifecycle/
measure-implementation/pre-rulemaking/lists-andreports.
57 Centers for Medicare & Medicaid Services.
2022–2023 MAP Final Recommendations. Available
at: https://mmshub.cms.gov/measure-lifecycle/
measure-implementation/pre-rulemaking/lists-andreports.
58 Centers for Medicare & Medicaid Services.
2022–2023 MAP Final Recommendations. Available
at: https://mmshub.cms.gov/measure-lifecycle/
measure-implementation/pre-rulemaking/lists-andreports.
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Although section 1886(s)(4)(D)(i) of the
Act generally requires that measures
specified by the Secretary shall be
endorsed by the entity with a contract
under section 1890(a) of the Act, section
1886(s)(4)(D)(ii) of the Act states that, in
the case of a specified area or medical
topic determined appropriate by the
Secretary for which a feasible and
practical measure has not been endorsed
by the entity with a contract under
section 1890(a) of the Act, the Secretary
may specify a measure that is not so
endorsed as long as due consideration is
given to measures that have been
endorsed or adopted by a consensus
organization identified by the Secretary.
We reviewed CBE-endorsed measures
and were unable to identify any other
CBE-endorsed measures on this topic,
and therefore, we believe the exception
in section 1886(s)(4)(D)(ii) of the Act
applies.
c. Data Collection, Submission, and
Reporting
IPFs are required to submit
information for structural measures
once annually using a CMS-approved
web-based data collection tool available
within the Hospital Quality Reporting
(HQR) System. For more information
about our previously finalized policies
related to reporting of structural
measures, we refer readers to the FY
2014 IPPS/LTCH PPS final rule (78 FR
50890 through 50901) and the FY 2015
IPF PPS final rule (79 FR 45963 through
45964 and 45976). Given the role of
committed leadership in improving
health outcomes for all patients, we
propose to adopt this measure beginning
with attestation in CY 2025 reflecting
the CY 2024 reporting period and
affecting the FY 2026 payment
determination.
We invite comments on our proposed
adoption of the Facility Commitment to
Health Equity Measure beginning with
the FY 2026 payment determination.
ddrumheller on DSK120RN23PROD with PROPOSALS2
3. Proposal To Adopt the Screening for
Social Drivers of Health Measure
Beginning With Voluntary Reporting of
CY 2024 Data Followed by Required
Reporting Beginning With CY 2025
Data/FY 2027 Payment Determination
a. Background
Health-related social needs (HRSNs),
which we define as individual-level,
adverse social conditions that negatively
impact an individual person’s health or
healthcare, are significant risk factors
associated with worse health outcomes
as well as increased healthcare
utilization.59 We believe that
59 Centers for Medicare & Medicaid Services.
(2021). A Guide to Using the Accountable Health
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consistently pursuing identification of
HRSNs would have two significant
benefits. First, HRSNs
disproportionately impact people who
have historically been underserved by
the healthcare system 60 and screening
helps identify individuals who may
have HRSNs. Second, screening for
HRSNs could support ongoing IPF
quality improvement initiatives by
providing data with which to stratify
patient risk and organizational
performance. Further, we believe that
IPFs collecting patient-level HRSN data
through screening is essential for the
long-term in encouraging meaningful
collaboration between healthcare
providers and community-based
organizations and in implementing and
evaluating related innovations in health
and social care delivery.
Health disparities manifest primarily
as worse health outcomes in population
groups where access to care is
inequitable.61 62 63 64 65 Such differences
persist across geography and healthcare
settings irrespective of improvements in
quality of care over time.66 67 68
Communities Health-Related Social Needs
Screening Tool: Promising Practices and Key
Insights. June 2021. Available at: https://
innovation.cms.gov/media/document/ahcmscreeningtool-companion. Accessed on February 20,
2023.
60 American Hospital Association. (2020). Health
Equity, Diversity & Inclusion Measures for
Hospitals and Health System Dashboards. December
2020. Available at: https://ifdhe.aha.org/system/
files/media/file/2020/12/ifdhe_inclusion_
dashboard.pdf. Accessed on February 20, 2023.
61 Seligman, H.K., & Berkowitz, S.A. (2019).
Aligning Programs and Policies to Support Food
Security and Public Health Goals in the United
States. Annual Review of Public Health, 40(1), 319–
337. Available at: https://www.ncbi.nlm.nih.gov/
pmc/articles/PMC6784838/. Accessed on February
20, 2023.
62 The Physicians Foundation. (2020). Survey of
America’s Patients, Part Three. Available at: https://
physiciansfoundation.org/wp-content/uploads/
2020/10/2020-Physicians-Foundation-SurveyPart3.pdf. Accessed on February 20, 2023.
63 Office of the Assistant Secretary for Planning
and Evaluation (ASPE) (2020). Report to Congress:
Social Risk Factors and Performance Under
Medicare’s Value-Based Purchasing Program
(Second of Two Reports). Available at: https://
aspe.hhs.gov/pdf-report/second-impact-report-tocongress. Accessed on February 20, 2023.
64 Trivedi AN, Nsa W, Hausmann LRM, et al.
(2014). Quality and Equity of Care in U.S. Hospitals.
N Engl J Med, 371(24), 2298–2308. Available at:
https://www.nejm.org/doi/10.1056/NEJMsa1405003.
Accessed on February 13, 2023.
65 Billioux, A., Verlander, K., Anthony, S., &
Alley, D. (2017). Standardized Screening for Health
Related Social Needs in Clinical Settings: The
Accountable Health Communities Screening Tool.
NAM Perspectives, 7(5). Available at: https://
doi.org/10.31478/201705b. Accessed on February
20, 2023.
66 Office of the Assistant Secretary for Planning
and Evaluation (ASPE) (2020). Report to Congress:
Social Risk Factors and Performance Under
Medicare’s Value-Based Purchasing Program
(Second of Two Reports). Available at: https://
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21279
Assessment of HRSNs is an essential
mechanism for capturing the interaction
between social, community, and
environmental factors associated with
health status and health outcomes.69 70 71
Growing evidence demonstrates that
specific HRSNs are directly associated
with patient health outcomes as well as
healthcare utilization, costs, and
performance in quality-based payment
programs.72 73 While widespread interest
in addressing HRSNs exists, action is
inconsistent.74
While social risk factors account for
50 to 70 percent of health outcomes, the
mechanisms by which this connection
emerges are complex and
aspe.hhs.gov/pdf-report/second-impact-report-tocongress. Accessed on February 20, 2023.
67 Hill-Briggs, F. (2021). Social Determinants of
Health and Diabetes: A Scientific Review. Diabetes
Care. Available at: https://diabetesjournals.org/
care/article/44/1/258/33180/Social-Determinantsof-Health-and-Diabetes-A. Accessed on February
20, 2023.
68 Khullar, D., MD. (2020). Association Between
Patient Social Risk and Physician Performance
American academy of Family Physicians.
Addressing Social Determinants of Health in
Primary Care team-based approach for advancing
health equity. Available at: https://www.aafp.org/
dam/AAFP/documents/patient_care/everyone_
project/team-based-approach.pdf. Accessed on
February 20, 2023.
69 Institute of Medicine. (2014). Capturing Social
and Behavioral Domains and Measures in
Electronic Health Records: Phase 2. Washington,
DC: The National Academies Press. Available at:
https://doi.org/10.17226/18951. Accessed on
February 20, 2023.
70 Alley, D.E., C.N. Asomugha, P.H. Conway, and
D.M. Sanghavi. (2016). Accountable Health
Communities—Addressing Social Needs through
Medicare and Medicaid. The New England Journal
of Medicine 374(1):8–11. Available at: https://
doi.org/10.1056/NEJMp1512532. Accessed on
February 20, 2023.
71 Centers for Disease Control and Prevention.
CDC COVID–19 Response Health Equity Strategy:
Accelerating Progress Towards Reducing COVID–19
Disparities and Achieving Health Equity. July 2020.
Available at: https://www.cdc.gov/coronavirus/
2019-ncov/community/health-equity/cdcstrategy.html. Accessed on February 2, 2023.
72 Zhang Y, Li J, Yu J, Braun RT, Casalino LP
(2021). Social Determinants of Health and
Geographic Variation in Medicare per Beneficiary
Spending. JAMA Network Open.
2021;4(6):e2113212. https://jamanetwork.com/
journals/jamanetworkopen/fullarticle/2780864.
Accessed on February 20, 2023.
73 Khullar, D., Schpero, W.L., Bond, A.M., Qian,
Y., & Casalino, L.P. (2020). Association Between
Patient Social Risk and Physician Performance
Scores in the First Year of the Merit-based Incentive
Payment System. JAMA, 324(10), 975–983. https://
doi.org/10.1001/jama.2020.13129. Accessed on
February 20, 2023.
74 TK Fraze, AL Brewster, VA Lewis, LB Beidler,
GF Murray, CH Colla. Prevalence of screening for
food insecurity, housing instability, utility needs,
transportation needs, and interpersonal violence by
US physician practices and hospitals. JAMA
Network Open 2019; https://jamanetwork.com/
journals/jamanetworkopen/fullarticle/10.1001/
jamanetworkopen.2019.11514. Accessed on
February 20, 2023.
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multifaceted.75 76 77 78 The persistent
interactions among individuals’ HRSNs,
medical providers’ practices and
behaviors, and community resources
significantly impact healthcare access,
quality, and ultimately costs, as
described in the CMS Equity Plan for
Improving Quality in Medicare.79 80 In
their 2018 survey, to which more than
8,500 physicians responded, the
Physicians Foundation found that
almost 90 percent of these physician
respondents reported their patients had
a serious health problem linked to
poverty or other social conditions.81
Additionally, associations among
disproportionate health risk,
hospitalization, and adverse health
outcomes have been highlighted and
magnified by the COVID–19
pandemic.82 83
75 Kaiser Family Foundation. (2021). Racial and
Ethnic Health Inequities and Medicare. Available
at: https://www.kff.org/medicare/report/racial-andethnic-health-inequities-and-medicare/. Accessed
February 20, 2023.
76 Khullar, D., MD. (2020). Association Between
Patient Social Risk and Physician Performance
American academy of Family Physicians.
Addressing Social Determinants of Health in
Primary Care team-based approach for advancing
health equity. Available at: https://www.aafp.org/
dam/AAFP/documents/patient_care/everyone_
project/team-based-approach.pdf. Accessed on
February 20, 2023.
77 Hammond, G., Johnston, K., Huang, K., Joynt
Maddox, K. (2020). Social Determinants of Health
Improve Predictive Accuracy of Clinical Risk
Models for Cardiovascular Hospitalization, Annual
Cost, and Death. Circulation: Cardiovascular
Quality and Outcomes, 13 (6) 290–299. Available at:
https://doi.org/10.1161/CIRCOUTCOMES.120.
006752. Accessed on February 20, 2023.
78 The Physicians Foundation. (2021).
Viewpoints: Social Determinants of Health.
Available at: https://physiciansfoundation.org/wpcontent/uploads/2019/08/The-PhysiciansFoundation-SDOH-Viewpoints.pdf. Accessed on
February 20, 2023.
79 Centers for Medicare & Medicaid Services.
(2021). Paving the Way to Equity: A Progress
Report. Available at: https://www.cms.gov/files/
document/paving-way-equity-cms-omh-progressreport.pdf. Accessed on February 20, 2023.
80 Centers for Medicare & Medicaid Services
Office of Minority Health. (2021). The CMS Equity
Plan for Improving Quality in Medicare. 2015–2021.
Available at: https://www.cms.gov/About-CMS/
Agency-Information/OMH/OMH_Dwnld-CMS_
EquityPlanforMedicare_090615.pdf#:∼:text=
The%20Centers%20for%20Medicare%20
%26%20Medicaid%20Services%20%28CMS
%29,evidence%20base%2C%20identifying%
20opportunities%2C%20and%20gathering
%20stakeholder%20input. Accessed on February
20, 2023.
81 The Physicians Foundation. (2019).
Viewpoints: Social Determinants of Health.
Available at: https://physiciansfoundation.org/wpcontent/uploads/2019/08/The-PhysiciansFoundation-SDOH-Viewpoints.pdf. Accessed on
February 20, 2023.
82 Centers for Disease Control and Prevention.
(2020). CDC COVID–19 Response Health Equity
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In 2017, CMS’ Center for Medicare
and Medicaid Innovation (CMMI)
launched the Accountable Health
Communities (AHC) Model to test the
impact of systematically identifying and
addressing the HRSNs of Medicare and
Medicaid beneficiaries (that is, through
screening, referral, and community
navigation) on their health outcomes
and related healthcare utilization and
costs.84 85 86 87 The AHC Model is one of
the first Federal pilots to systematically
test whether identifying and addressing
core HRSNs improves healthcare costs,
utilization, and outcomes with over 600
clinical sites in 21 states.88 The AHC
Model had a 5-year period of
performance that began in May 2017
and ended in April 2022, with
beneficiary screening beginning in the
summer of 2018.89 90 Evaluation of the
AHC Model data is still underway.
Strategy: Accelerating Progress Towards Reducing
COVID–19 Disparities and Achieving Health Equity.
July 2020. Available at: https://www.cdc.gov/
coronavirus/2019-ncov/community/health-equity/
cdc-strategy.html. Accessed on February 20, 2023.
83 Kaiser Family Foundation. (2021). Racial and
Ethnic Health Inequities and Medicare. Available
at: https://www.kff.org/medicare/report/racial-andethnic-health-inequities-and-medicare/. Accessed
on February 20, 2023.
84 Centers for Medicare & Medicaid Services.
(2021). A Guide to Using the Accountable Health
Communities Health-Related Social Needs
Screening Tool: Promising Practices and Key
Insights. June 2021. Accessed: November 23, 2021.
Available at: https://innovation.cms.gov/media/
document/ahcm-screeningtool-companion.
Accessed on February 20, 2023.
85 Alley, D.E., Asomugha, C.N., et al. (2016).
Accountable Health Communities—Addressing
Social Needs through Medicare and Medicaid. The
New England Journal of Medicine 374(1):8–11.
Available at: https://doi.org/10.1056/
NEJMp1512532. Accessed on February 20, 2023.
86 Billioux, A., Verlander, K., Anthony, S., &
Alley, D. (2017). Standardized Screening for HealthRelated Social Needs in Clinical Settings: The
Accountable Health Communities Screening Tool.
NAM Perspectives, 7(5). Available at: https://
doi.org/10.31478/201705b. Accessed on February
20, 2023.
87 Centers for Medicare & Medicaid Services.
(2021). Accountable Health Communities Model.
Accountable Health Communities Model √ CMS
Innovation Center Available at: https://
innovation.cms.gov/innovation-models/ahcm.
Accessed on February 20, 2023.
88 RTI International. (2020). Accountable Health
Communities (AHC) Model Evaluation. Available
at: https://innovation.cms.gov/data-and-reports/
2020/ahc-first-eval-rpt. Accessed on February 20,
2023.
89 RTI International. (2020). Accountable Health
Communities (AHC) Model Evaluation. Available
at: https://innovation.cms.gov/data-and-reports/
2020/ahc-first-eval-rpt. Accessed on February 20,
2023.
90 We note that the model officially concluded in
April 2022, but many awardees have continued
with no-cost extensions to continue utilizing
unspent cooperative agreement funding and all
awardees will conclude by April 2023.
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Under the AHC Model, the following
five core domains were selected to
screen for HRSNs among Medicare and
Medicaid beneficiaries: (1) food
insecurity; (2) housing instability; (3)
transportation needs; (4) utility
difficulties; and (5) interpersonal safety.
These domains were chosen based upon
literature review and expert consensus
utilizing the following criteria: (1)
availability of high-quality scientific
evidence linking a given HRSN to
adverse health outcomes and increased
healthcare utilization, including
hospitalizations and associated costs; (2)
ability for a given HRSN to be screened
and identified in the inpatient setting
prior to discharge, addressed by
community-based services, and
potentially improve healthcare
outcomes, including reduced
readmissions; and (3) evidence that a
given HRSN is not systematically
addressed by healthcare providers.91 In
addition to established evidence of their
association with health status, risk, and
outcomes, these five domains were
selected because they can be assessed
across the broadest spectrum of
individuals in a variety of settings.92 93 94
These five evidence-based HRSN
domains, which informed development
of the two Social Drivers of Health
measures adopted in the Hospital IQR
Program and proposed here for the
IPFQR Program, are described in Table
18. We note that while the measures
were initially developed by The Health
Initiative (THI), CMS has since assumed
stewardship.
91 Billioux, A., Verlander, K., Anthony, S., &
Alley, D. (2017). Standardized Screening for HealthRelated Social Needs in Clinical Settings: The
Accountable Health Communities Screening Tool.
NAM Perspectives, 7(5). Available at: https://
doi.org/10.31478/201705b. Accessed on February
20, 2023.
92 Billioux, A., Verlander, K., Anthony, S., &
Alley, D. (2017). Standardized Screening for HealthRelated Social Needs in Clinical Settings: The
Accountable Health Communities Screening Tool.
NAM Perspectives, 7(5). Available at: https://
doi.org/10.31478/201705b. Accessed on February
20, 2023.
93 Centers for Medicare & Medicaid Services.
(2021). Accountable Health Communities Model.
Accountable Health Communities Model √ CMS
Innovation Center. Available at: https://
innovation.cms.gov/innovation-models/ahcm.
Accessed on February 20, 2023.
94 Kamyck, D., Senior Director of Marketing.
(2019). CMS releases standardized screening tool
for health-related social needs. Activate Care.
Available at: https://blog.activatecare.com/
standardized-screening-for-health-related-socialneeds-in-clinical-settings-the-accountable-healthcommunities-screening-tool/. Accessed on February
20, 2023.
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TABLE 18—THE FIVE CORE HRSN DOMAINS TO SCREEN FOR SOCIAL DRIVERS OF HEALTH
Domain
Description
Food Insecurity ......................
Food insecurity is defined as limited or uncertain access to adequate quality and quantity of food at the household level. It is associated with diminished mental and physical health and increased risk for chronic conditions.95 96 Individuals experiencing food insecurity often have inadequate access to healthier food options which can impede self-management of chronic diseases like diabetes
and heart disease, and require individuals to make personal trade-offs between food purchases and medical needs, including prescription medication refills and preventive health services.97 98 Food insecurity is associated with high-cost healthcare utilization including emergency department (ED) visits and hospitalizations.99 100 101 Evidence indicates that individuals with serious mental illness have a higher prevalence of food insecurity than the U.S. population as a whole (specifically 71% prevalence among patients
with severe mental illness versus 14.9% in the population as a whole).102
Housing instability encompasses multiple conditions ranging from inability to pay rent or mortgage, frequent changes in residence including temporary stays with friends and relatives, living in crowded conditions, and actual lack of sheltered housing in which an individual does not have a personal residence.103 104 Population surveys consistently show that people from some racial and ethnic
minority groups constitute the largest proportion of the U.S. population experiencing housing instability.105 Housing instability is associated with higher rates of chronic illnesses, injuries, and complications and more frequent utilization of high-cost healthcare services.106 107 Additionally, housing instability can exacerbate psychiatric conditions and individuals with psychiatric conditions are
more likely to have housing instability.108
Unmet transportation needs include limitations that impede transportation to destinations required for all aspects of daily living.109
Groups disproportionately affected include older adults (aged >65 years), people with lower incomes, people with impaired mobility,
residents of rural areas, and people from some racial and ethnic minority groups. Transportation needs contribute to postponement
of routine medical care and preventive services which ultimately lead to chronic illness exacerbation and more frequent utilization of
high-cost healthcare services including emergency medical services, EDs, and hospitalizations.110 111 112 113 Patients with serious
mental illness often lack access to transportation with many Medicaid eligible patients relying on Medicaid’s non-emergency medical transportation (NEMT) to access needed healthcare, though this does not provide access to transportation to other aspects of
daily living.114
Inconsistent availability of electricity, water, oil, and gas services is directly associated with housing instability and food insecurity.115
Specifically, interventions that increase or maintain access to such services have been associated with individual and populationlevel health improvements.116
Interpersonal safety affects individuals across the lifespan, from birth to old age, and is directly linked to mental and physical health.
Assessment for this domain includes screening for exposure to intimate partner violence, child abuse, and elder abuse.117 Exposure to violence and social isolation are reflective of individual-level social relations and living conditions that are directly associated
with injury, psychological distress, and death in all age groups.118 119 Research indicates that adults with mental illness are at an
increased risk of being victims of violence, noting that 30.9 percent were victims of violence within a six month period and recommending increased public health interventions to reduce violence in this vulnerable population.120
Housing Instability .................
Transportation Needs ............
Utility Difficulties ....................
Interpersonal Safety ..............
ddrumheller on DSK120RN23PROD with PROPOSALS2
As a first step towards leveraging the
opportunity to close equity gaps by
identifying patients’ HRSNs, we
95 Berkowitz SA, Seligman HK, Meigs JB, Basu S.
Food insecurity, healthcare utilization, and high
cost: a longitudinal cohort study. Am J Managed
Care. 2018 Sep;24(9):399–404. PMID: 30222918;
PMCID: PMC6426124. Available at https://
pubmed.ncbi.nlm.nih.gov/30222918/. Accessed on
February 20, 2023.
96 Hill-Briggs, F. (2021). Social Determinants of
Health and Diabetes: A Scientific Review. Diabetes
Care. Available at: https://diabetesjournals.org/
care/article/44/1/258/33180/Social-Determinantsof-Health-and-Diabetes-A. Accessed on February
20, 2023.
97 Seligman, H.K., & Berkowitz, S.A. (2019).
Aligning Programs and Policies to Support Food
Security and Public Health Goals in the United
States. Annual Review of Public Health, 40(1), 319–
337. Available at: https://pubmed.ncbi.nlm.nih.gov/
30444684/. Accessed on February 20, 2023.
98 National Academies of Sciences, Engineering,
and Medicine 2006. Executive Summary: CostBenefit Analysis of Providing Non-Emergency
Medical Transportation. Washington, DC: The
National Academies Press. Available at: https://
doi.org/10.17226/23285. Accessed on February 20,
2023.
99 Hill-Briggs, F. (2021). Social Determinants of
Health and Diabetes: A Scientific Review. Diabetes
Care. Available at: https://diabetesjournals.org/
care/article/44/1/258/33180/Social-Determinantsof-Health-and-Diabetes-A. Accessed on February
20, 2023.
100 Berkowitz SA, Seligman HK, Meigs JB, Basu
S. Food insecurity, healthcare utilization, and high
cost: a longitudinal cohort study. Am J Managed
Care. 2018 Sep;24(9):399–404. PMID: 30222918;
PMCID: PMC6426124. Available at https://
pubmed.ncbi.nlm.nih.gov/30222918/. Accessed on
February 20, 2023.
101 Dean, E.B., French, M.T., & Mortensen, K.
(2020a). Food insecurity, health care utilization,
and health care expenditures. Health Services
Research, 55(S2), 883–893. Available at: https://
doi.org/10.1111/1475-6773.13283. Accessed on
February 20, 2023.
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finalized the adoption of two evidencebased measures in the Hospital IQR
Program—the Screening for Social
Drivers of Health measure and the
102 https://ps.psychiatryonline.org/doi/10.1176/
appi.ps.201300022?url_ver=Z39.88-2003&rfr_
id=ori:rid:crossref.org&rfr_dat=cr_
pub%20%200pubmed. Accessed on February 20,
2023.
103 Larimer, M.E. (2009). Health Care and Public
Service Use and Costs Before and After Provision
of Housing for Chronically Homeless Persons with
Severe Alcohol Problems. JAMA, 301(13), 1349.
Available at: https://doi.org/10.1001/
jama.2009.414.
104 Hill-Briggs, F. (2021, January 1). Social
Determinants of Health and Diabetes: A Scientific
Review. Diabetes Care. Available at: https://
pubmed.ncbi.nlm.nih.gov/33139407/.
105 Henry, M., de Sousa, T., Roddey, C., Gayen,
S., Bednar, T.; Abt Associates. The 2020 Annual
Homeless Assessment Report (AHAR) to Congress;
Part 1: Point-in-Time Estimates of Homelessness,
January 2021. U.S. Department of Housing and
Urban Development. Accessed November 24, 2021.
Available at: https://www.huduser.gov/portal/sites/
default/files/pdf/2020-AHAR-Part-1.pdf.
106 Larimer, M.E. (2009). Health Care and Public
Service Use and Costs Before and After Provision
of Housing for Chronically Homeless Persons with
Severe Alcohol Problems. JAMA, 301(13), 1349.
Available at: https://doi.org/10.1001/
jama.2009.414.
107 Baxter, A., Tweed, E., Katikireddi, S.,
Thomson, H. (2019). Effects of Housing First
approaches on health and well-being of adults who
are homeless or at risk of homelessness: systematic
review and meta-analysis of randomized controlled
trials. Journal of Epidemiology and Community
Health, 73; 379–387. Available at: https://
jech.bmj.com/content/jech/73/5/379.full.pdf.
108 Housing Instability and Mental Health. UNC
Greensboro. May 7, 2021. Available at: https://
chcs.uncg.edu/housing-instability-mental-health/
#:∼:text=Mental%20health%20is%20
correlated%20with%20housing
%20in%20several,homeless
%20population%20in%20
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Screen Positive Rate for Social Drivers
of Health measure (collectively, Social
Drivers of Health measures)—and refer
readers to the FY 2023 IPPS/LTCH PPS
final rule (87 FR 49191 through 49220).
America%20suffer%20a%20mental%20illness.
Accessed on December 7, 2022.
109 National Academies of Sciences, Engineering,
and Medicine 2006. Executive Summary: CostBenefit Analysis of Providing Non-Emergency
Medical Transportation. Washington, DC: The
National Academies Press. Available at: https://
doi.org/10.17226/23285.
110 National Academies of Sciences, Engineering,
and Medicine 2006. Executive Summary: CostBenefit Analysis of Providing Non-Emergency
Medical Transportation. Washington, DC: The
National Academies Press. Available at: https://
doi.org/10.17226/23285.
111 Hill-Briggs, F. (2021, January 1). Social
Determinants of Health and Diabetes: A Scientific
Review. Diabetes Care. Available at: https://
pubmed.ncbi.nlm.nih.gov/33139407/.
112 Billioux, A., Verlander, K., Anthony, S., &
Alley, D. (2017). Standardized Screening for HealthRelated Social Needs in Clinical Settings: The
Accountable Health Communities Screening Tool.
NAM Perspectives, 7(5). Available at: https://
doi.org/10.31478/201705b.
113 Shier, G., Ginsburg, M., Howell, J., Volland, P.,
& Golden, R. (2013). Strong Social Support Services,
Such as Transportation And Help For Caregivers,
Can Lead To Lower Health Care Use And Costs.
Health Affairs, 32(3), 544–551. Available at: https://
doi.org/10.1377/hlthaff.2012.0170.
114 https://www.nami.org/Advocacy/PolicyPriorities/Supporting-Community-Inclusion-andNon-Discrimination/Medicaid-Non-EmergencyMedical-Transportation.
115 Baxter, A., Tweed, E., Katikireddi, S.,
Thomson, H. (2019). Effects of Housing First
approaches on health and well-being of adults who
are homeless or at risk of homelessness: systematic
review and meta-analysis of randomized controlled
trials. Journal of Epidemiology and Community
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If also adopted in the IPFQR Program,
these two Social Drivers of Health
measures (that is, the Screening for
Social Drivers of Health measure being
proposed for adoption in this section
and the Screen Positive Rate for Social
Drivers of Health measure being
proposed for adoption in section V.D.4
of this proposed rule) would support
identification of specific risk factors for
inadequate healthcare access and
adverse health outcomes among
patients. We note that these measures
would enable systematic collection of
HRSNs data. This activity aligns with
our other efforts beyond the acute care
setting, including the CY 2023 Medicare
Advantage and Part D final rule in
which we finalized the policy requiring
that all Special Needs Plans (SNPs)
include one or more questions on
housing stability, food security, and
access to transportation in their health
risk assessment using questions from a
list of screening instruments specified
in sub-regulatory guidance (87 FR 27726
through 27740) as well as the CY 2023
Physician Fee Schedule (PFS) final rule
in which we adopted the Screening for
Social Drivers of Health measure in the
Merit-based Incentive Payment System
(MIPS) Program (87 FR 70054 through
70055).
The proposed Social Drivers of Health
measures (as set forth in this section
V.D.3 and section V.D.4. of this
proposed rule) would encourage IPFs to
identify patients with HRSNs, who are
known to experience the greatest risk of
poor health outcomes, thereby
improving the accuracy of high-risk
prediction calculations. Improvement in
risk prediction has the potential to
Health, 73; 379–387. Available at: https://
jech.bmj.com/content/jech/73/5/379.full.pdf.
116 Wright, B.J., Vartanian, K.B., Li, H.F., Royal,
N., & Matson, J.K. (2016). Formerly Homeless
People Had Lower Overall Health Care
Expenditures After Moving into Supportive
Housing. Health Affairs, 35(1), 20–27. Available at:
https://doi.org/10.1377/hlthaff.2015.0393.
117 Billioux, A., Verlander, K., Anthony, S., &
Alley, D. (2017). Standardized Screening for HealthRelated Social Needs in Clinical Settings: The
Accountable Health Communities Screening Tool.
NAM Perspectives, 7(5). Available at: https://
doi.org/10.31478/201705b.
118 Henry M., de Sousa, T., Roddey, C., Gayen, S.,
Bednar, T.; Abt Associates. The 2020 Annual
Homeless Assessment Report (AHAR) to Congress;
Part 1: Point-in-Time Estimates of Homelessness,
January 2021. U.S. Department of Housing and
Urban Development. Accessed November 24, 2021.
Available at: https://www.huduser.gov/portal/sites/
default/files/pdf/2020-AHAR-Part-1.pdf.
119 Larimer, M.E. (2009). Health Care and Public
Service Use and Costs Before and After Provision
of Housing for Chronically Homeless Persons with
Severe Alcohol Problems. JAMA, 301(13), 1349.
Available at: https://doi.org/10.1001/
jama.2009.414.
120 https://ajph.aphapublications.org/doi/abs/
10.2105/AJPH.2013.301680.
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reduce healthcare access barriers,
address the disproportionate
expenditures attributed to people with
greatest risk, and improve the IPF’s
quality of care.121 122 123 124 Further, these
data could guide future public and
private resource allocation to promote
targeted collaboration among IPFs,
health systems, community-based
organizations, and others in support of
improving patient outcomes. We believe
that this screening is especially
important for IPF patients because
patients with psychiatric conditions
have an increased risk of having
HRSNs.125
In the FY 2023 IPF PPS final rule, we
observed that the Hospital IQR Program
had proposed two Social Drivers of
Health measures and stated that we
would consider these measures for the
IPFQR Program in the future (87 FR
46873). The first of these two measures
is the Screening for Social Drivers of
Health measure, which assesses the
percent of patients admitted to the
hospital who are 18 years or older at
time of admission and are screened for
food insecurity, housing instability,
transportation needs, utility difficulties,
and interpersonal safety.
Utilization of screening tools to
identify the burden of unmet HRSNs
can be a helpful first step for IPFs in
identifying necessary community
partners and connecting individuals to
resources in their communities. We
believe collecting data across the same
five HRSN domains that were screened
under the AHC Model and adopted for
acute care hospitals in the Hospital IQR
121 Baker, MC, Alberti, PM, et al. (2021). Social
Determinants Matter for Hospital Readmission
Policy: Insights From New York City. Health
Affairs, 40(4), 645–654. Available at: https://
doi.org/10.1377/hlthaff.2020.01742. Accessed on
February 20, 2023.
122 Hammond, G., Johnston, K., et al. (2020).
Social Determinants of Health Improve Predictive
Accuracy of Clinical Risk Models for
Cardiovascular Hospitalization, Annual Cost, and
Death. Circulation: Cardiovascular Quality and
Outcomes, 13 (6) 290–299. Available at: https://
doi.org/10.1161/CIRCOUTCOMES.120.006752.
Accessed on February 20, 2023.
123 Hill-Briggs, F. (2021). Social Determinants of
Health and Diabetes: A Scientific Review. Diabetes
Care. Available at: https://diabetesjournals.org/
care/article/44/1/258/33180/Social-Determinantsof-Health-and-Diabetes-A. Accessed on February
20, 2023.
124 Jaffrey, J.B., Safran, G.B., Addressing Social
Risk Factors in Value-Based Payment: Adjusting
Payment Not Performance to Optimize Outcomes
and Fairness. Health Affairs Blog, April 19, 2021.
Available at: https://www.healthaffairs.org/do/
10.1377/forefront.20210414.379479/full/. Accessed
on February 20, 2023.
125 Adepoju, OE, Liaw, W, et al. (2022)
Assessment of Unmet Health-Related Social Needs
Among Patients with Mental Illness Enrolled in
Medicare Advantage. Available at: https://
jamanetwork.com/journals/jamanetworkopen/
fullarticle/2798096. Accessed on December 7, 2022.
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Program would illuminate their impact
on health outcomes and disparities and
the healthcare cost burden for IPFs,
particularly for IPFs that serve patients
with disproportionately high levels of
social risk, given that patients with
serious mental illness are especially
vulnerable to and affected by HRSNs. In
addition, data collection in the IPF care
setting could inform meaningful and
sustainable solutions for provider-types
participating in other quality reporting
programs to close equity gaps among the
communities they serve.126 127 128 129 130
For data collection of the proposed
Screening for Social Drivers of Health
measure, IPFs could use a self-selected
screening tool and collect these data in
multiple ways, which can vary to
accommodate the population they serve
and their individual needs. One
example of a potential screening tool for
IPFs to collect data on the proposed
Screening for Social Drivers Health
Measure is the AHC Model’s standard
10-item AHC Health-Related Social
Needs Screening Tool (AHC HRSN
Screening Tool), which enables
providers to identify HRSNs in the five
core domains (described in Table 18)
among community-dwelling Medicare,
Medicaid, and dually eligible
beneficiaries. The AHC Model,
including its screening tool, was tested
across many care delivery sites in
diverse geographic locations across the
United States. More than one million
Medicare and Medicaid beneficiaries
have been screened using the AHC
HRSN Screening Tool, which was
evaluated psychometrically and
demonstrated evidence of both
reliability and validity, including interrater reliability and concurrent and
126 The Physicians Foundation: 2020 Survey of
America’s Patients, Part Three. Available at: https://
physiciansfoundation.org/wp-content/uploads/
2020/10/2020-Physicians-Foundation-SurveyPart3.pdf.
127 Office of the Assistant Secretary for Planning
and Evaluation (ASPE) (2020). Report to Congress:
Social Risk Factors and Performance Under
Medicare’s Value-Based Purchasing Program
(Second of Two Reports). Available at: https://
aspe.hhs.gov/pdf-report/second-impact-report-tocongress.
128 Billioux, A., Verlander, K., Anthony, S., &
Alley, D. (2017). Standardized Screening for HealthRelated Social Needs in Clinical Settings: The
Accountable Health Communities Screening Tool.
NAM Perspectives, 7(5). Available at: https://
doi.org/10.31478/201705b.
129 Baker, M.C., Alberti, P.M., Tsao, T.Y., Fluegge,
K., Howland, R.E., & Haberman, M. (2021). Social
Determinants Matter for Hospital Readmission
Policy: Insights From New York City. Health
Affairs, 40(4), 645–654. Available at: https://
doi.org/10.1377/hlthaff.2020.01742.
130 De Marchis, E., Knox, M., Hessler, D., WillardGrace, R., Oliyawola, JN, et al. (2019). Physician
Burnout and Higher Clinic Capacity to Address
Patients’ Social Needs. The Journal of the American
Board of Family Medicine, 32 (1), 69–78.
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predictive validity. Moreover, the AHC
HRSN Screening Tool can be
implemented in a variety of places
where patients seek healthcare,
including inpatient psychiatric
facilities.
The intent of the proposed Screening
for Social Drivers of Health measure is
to promote adoption of HRSN screening
by IPFs. We encourage IPFs to use the
screening as a basis for developing their
own individual action plans (for
example, navigation services and
subsequent referral), as well as an
opportunity to initiate or improve
partnerships with community-based
service providers. We believe that this
proposed measure would yield
actionable information to close equity
gaps by encouraging IPFs to identify
patients with HRSNs, with a reciprocal
goal of strengthening linkages between
IPFs and local community-based
partners to promptly connect patients
and families to the support they need.
Both the proposed Screening for
Social Drivers of Health measure and
the proposed Screen Positive Rate for
Social Drivers of Health measure,
discussed in V.D.4. of this proposed
rule, address our Meaningful Measures
Framework’s 131 quality priority of
‘‘Work with Communities to Promote
Best Practices of Healthy Living’’
through the Meaningful Measures Area
of ‘‘Equity of Care.’’ Additionally,
pursuant to our Meaningful Measures
2.0, these proposed Social Drivers of
Health measures address the equity
priority area and align with our
commitment to introduce plans to close
health equity gaps and promote equity
through quality measures, including to
‘‘develop and implement measures that
reflect social and economic
determinants.’’ 132 Development and
proposal of these measures also align
with our strategic pillar to advance
health equity by addressing the health
disparities that underlie our health
system.133 Further, proposal of these
measures aligns with these measures’
adoption in the Hospital IQR Program in
131 Centers for Medicare & Medicaid Services.
Meaningful Measures Framework. Available at:
https://www.cms.gov/Medicare/Quality-InitiativesPatient-Assessment-Instruments/
QualityInitiativesGenInfo/CMS-Quality-Strategy.
132 Centers for Medicare & Medicaid Services.
Meaningful Measures 2.0: Moving from Measure
Reduction to Modernization. Available at: https://
www.cms.gov/meaningful-measures-20-movingmeasure-reduction-modernization.
133 Brooks-LaSure, C. (2021). My First 100 Days
and Where We Go From Here: A Strategic Vision
for CMS. Available at: https://www.cms.gov/blog/
my-first-100-days-and-where-we-go-here-strategicvision-cms.
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the FY 2023 IPPS/LTCH final rule (87
FR 49202 through 49215).
The proposed Screening for Social
Drivers of Health measure (alongside the
proposed Screen Positive Rate for Social
Drivers of Health measure described in
section V.D.4 of this proposed rule)
would be the first measurement of social
drivers of health in the IPFQR Program.
We believe this proposed measure is
appropriate for measurement of the
quality of care furnished by IPFs.
Screening patients for HRSNs during
inpatient hospitalization in an IPF
would allow healthcare providers,
including IPFs, to identify and
potentially help address HRSNs for this
medically underserved patient
population as part of discharge planning
and contribute to long-term
improvements in patient outcomes.
Identifying and addressing HRSNs for
patients receiving care in IPFs could
have a direct and positive impact on
IPFs’ quality performance because of
improvements in patient outcomes that
could occur when patients’ HRSNs are
reduced. Moreover, collecting aggregate
data on the HRSNs of IPF patient
populations via this proposed measure
is crucial in informing design of future
measures that could enable us to set
appropriate performance targets for IPFs
with respect to closing the gap on health
equity.
b. Overview of Measure
The proposed Screening for Social
Drivers of Health measure would assess
whether an IPF implements screening
for all patients who are 18 years or older
at time of admission for food insecurity,
housing instability, transportation
needs, utility difficulties, and
interpersonal safety. To report on this
proposed measure, IPFs would provide:
(1) the number of inpatients admitted to
the facility who are 18 years or older at
time of admission and who are screened
for all of the five HRSNs (food
insecurity, housing instability,
transportation needs, utility difficulties,
and interpersonal safety); and (2) the
total number of patients who are
admitted to the facility who are 18 years
or older on the date they are admitted.
Measure specifications for the
proposed Screening for Social Drivers of
Health measure, which were available
during the review of the MUC List, are
available at https://mmshub.cms.gov/
sites/default/files/map-hospitalmeasure-specifications-manual2022.pdf.
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21283
(1) Measure Calculation
(a) Cohort
The proposed Screening for Social
Drivers of Health measure would assess
the total number of patients aged 18
years and older, screened for social risk
factors (specifically, food insecurity,
housing instability, transportation
needs, utility difficulties, and
interpersonal safety) during an IPF stay.
(b) Numerator
The numerator of the proposed
Screening for Social Drivers of Health
measure consists of the number of
patients admitted to an IPF stay who are
18 years or older on the date of
admission and are screened during their
IPF stay for all of the following five
HRSNs: food insecurity, housing
instability, transportation needs, utility
difficulties, and interpersonal safety.
(c) Denominator
The denominator of the proposed
Screening for Social Drivers of Health
measure consists of the number of
patients who are admitted to an IPF stay
and who are 18 years or older on the
date of admission. The following
patients would be excluded from the
denominator: (1) patients who opt-out of
screening; and (2) patients who are
themselves unable to complete the
screening during their inpatient stay
and have no legal guardian or caregiver
able to do so on the patient’s behalf
during their inpatient stay.
(d) Calculation
The proposed Screening for Social
Drivers of Health measure would be
calculated as the number of patients
admitted to an IPF stay who are 18 years
or older on the date of admission
screened for all five HRSNs (food
insecurity, housing instability,
transportation needs, utility difficulties,
and interpersonal safety) divided by the
number of patients 18 years or older on
the date of admission admitted to the
IPF.
(2) Review by the Measure Applications
Partnership
We included the proposed Screening
for Social Drivers of Health measure on
the publicly available ‘‘List of Measures
Under Consideration for December 1,
2022’’ (MUC List), a list of measures
under consideration for use in various
Medicare programs.134 The CBE134 Centers for Medicare & Medicaid Services. List
of Measures Under Consideration for December 1,
2022. Available at: https://mmshub.cms.gov/
measure-lifecycle/measure-implementation/prerulemaking/lists-and-reports.
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convened MAP Health Equity Advisory
Group reviewed the MUC List including
the proposed Screening for Social
Drivers of Health measure (MUC 2022–
053) in detail on December 6 through 7,
2022.135 The MAP Health Equity
Advisory Group expressed support for
the collection of data related to social
drivers of health, but raised concerns
regarding public reporting of these data
and potential repetition of asking
patients the same questions across
settings.136
In addition, on December 8 through 9,
2022, the MAP Rural Health Advisory
Group reviewed the 2022 MUC List and
the MAP Hospital Workgroup did so on
December 13 through 14, 2022.137 The
MAP Rural Health Advisory Group
noted some potential reporting
challenges including the potential
masking of health disparities that are
underrepresented in some areas and that
sample size and populations served may
be an issue, but expressed that the
proposed measure serves as a starting
point to determine where screening is
occurring. The MAP Hospital
Workgroup expressed strong support for
the measure but noted that
interoperability will be important and
cautioned about survey fatigue. The
MAP Hospital Workgroup members
conditionally supported the measure
pending: (1) testing of the measure’s
reliability and validity; (2) endorsement
by the CBE; (3) additional details on
how potential tools map to the
individual HRSNs, as well as best
practices; (4) identification of resources
that may be available to assist patients
with identified HRSNs; and (5) the
measure’s alignment with data
standards, particularly the GRAVITY
project.138 The GRAVITY project’s
mission statement is ‘‘to serve as the
open public collaborative advancing
health and social data standardization
for health equity.’’ 139 Thereafter, the
MAP Coordinating Committee
135 Centers for Medicare & Medicaid Services.
2022–2023 MAP Final Recommendations. Available
at: https://mmshub.cms.gov/measure-lifecycle/
measure-implementation/pre-rulemaking/lists-andreports.
136 Centers for Medicare & Medicaid Services.
2022–2023 MAP Final Recommendations. Available
at: https://mmshub.cms.gov/measure-lifecycle/
measure-implementation/pre-rulemaking/lists-andreports.
137 Centers for Medicare & Medicaid Services.
2022–2023 MAP Final Recommendations. Available
at: https://mmshub.cms.gov/measure-lifecycle/
measure-implementation/pre-rulemaking/lists-andreports.
138 Centers for Medicare & Medicaid Services.
2022–2023 MAP Final Recommendations. Available
at: https://mmshub.cms.gov/measure-lifecycle/
measure-implementation/pre-rulemaking/lists-andreports.
139 https://thegravityproject.net/.
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deliberated on January 24 through 25,
2023, and ultimately voted to uphold
the MAP Hospital Workgroup’s
recommendation to conditionally
support for rulemaking with the same
conditions.140
We believe this measure establishes
an important foundation for prioritizing
the achievement of health equity among
IPFs. Our approach to developing health
equity measures is incremental, and we
believe that health care equity outcomes
in the IPFQR Program will inform future
efforts to advance and achieve health
care equity by IPFs. We additionally
believe this measure to be a building
block that lays the groundwork for a
future meaningful suite of measures that
would assess IPF progress in providing
high-quality healthcare for all patients,
regardless of social risk factors or
demographic characteristics.
(3) CBE Endorsement
We have not submitted this measure
for CBE endorsement at this time.
Although section 1886(s)(4)(D)(i) of the
Act generally requires that measures
specified by the Secretary shall be
endorsed by the entity with a contract
under section 1890(a) of the Act, section
1886(s)(4)(D)(ii) of the Act, states that in
the case of a specified area or medical
topic determined appropriate by the
Secretary for which a feasible and
practical measure has not been endorsed
by the entity with a contract under
section 1890(a) of the Act, the Secretary
may specify a measure that is not so
endorsed as long as due consideration is
given to a measure that has been
endorsed or adopted by a consensus
organization identified by the Secretary.
We reviewed CBE-endorsed measures
and were unable to identify any other
CBE-endorsed measures on this topic,
and therefore, we believe the exception
in section 1886(s)(4)(D)(ii) of the Act
applies.
c. Data Collection, Submission and
Reporting
We believe incremental
implementation of the proposed
Screening for Social Drivers of Health
measure, by permitting one year of
voluntary reporting prior to required
reporting, would allow IPFs who are not
yet screening patients for HRSNs to get
experience with collecting data for this
proposed measure and equally allow
IPFs who already undertake screening
efforts to report data already being
collected. Therefore, we propose
140 Centers for Medicare & Medicaid Services.
2022–2023 MAP Final Recommendations. Available
at: https://mmshub.cms.gov/measure-lifecycle/
measure-implementation/pre-rulemaking/lists-andreports.
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voluntary reporting of this measure
beginning with the data collected in CY
2024, which would be reported to CMS
in CY 2025, followed by required
reporting beginning with data collected
in CY 2025, which would be reported to
CMS in CY 2026 for the FY 2027
payment determination.
Due to variability across IPFs and the
populations they serve, and in
alignment with the Hospital IQR
Program, we would allow IPFs
flexibility with selection of tools to
screen patients for food insecurity,
housing instability, transportation
needs, utility difficulties, and
interpersonal safety. Potential sources of
these data could include, for example,
administrative claims data, electronic
clinical data, standardized patient
assessments, or patient-reported data
and surveys.
Multiple screening tools for healthrelated social needs (HRSNs) already
exist. For additional information on
resources, we refer readers to evidencebased resources like the Social
Interventions Research and Evaluation
Network (SIREN) website, for example,
for comprehensive information about
the most widely used HRSN screening
tools.141 142 SIREN contains descriptions
of the content and characteristics of
various tools, including information
about intended populations, completion
time, and number of questions.
We would encourage IPFs to consider
digital standardized screening tools and
refer readers to the FY 2023 IPPS/LTCH
PPS final rule (87 FR 49207 through
49208) where we discuss how the use of
certified health information technology
(IT), including but not limited to
certified EHR technology, can support
capture of HRSN information in an
interoperable fashion so that these data
can be shared across the care continuum
to support coordinated care. We also
encourage readers to learn about the
United States Core Data for
Interoperability (USCDI) standard used
in certified health IT and how this
standard can support interoperable
exchange of health and HRSN
assessment data.143
141 Social Interventions Research & Evaluation
Network. (2019). Social Needs Screening Tool
Comparison Table. Available at: https://
sirenetwork.ucsf.edu/tools-resources/resources/
screening-tools-comparison. Accessed January 18,
2021.
142 The Social Interventions Research and
Evaluation Network (SIREN) at University of
California San Francisco was launched in the spring
of 2016 to synthesize, disseminate, and catalyze
research on SDOH and healthcare delivery.
143 Office of the National Coordinator for Health
IT (ONC). United States Core Data for
Interoperability. Accessed at: https://
www.healthit.gov/isa/united-states-core-datainteroperability-uscdi.
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We propose that IPFs would report
aggregate data on this measure, that is
IPFs would report aggregated data for
the numerator and the denominator to
CMS (as described in section
V.D.3.b.(1). of this proposed rule) but
would not be required to report patientlevel data. IPFs are required to submit
information for chart-abstracted
measures once annually using a CMSapproved web-based data collection tool
available within the HQR System
(previously referred to as the QualityNet
Secure Portal). We refer readers to
section V.I. of the preamble of this
proposed rule (Form, Manner, and
Timing of Quality Data Submission) for
more details on our previously finalized
data submission and deadline
requirements across measure types.
We invite public comment on this
proposal.
4. Proposal To Adopt the Screen
Positive Rate for Social Drivers of
Health Measure Beginning With
Voluntary Reporting of CY 2024 Data
and Followed by Required Reporting
Beginning With CY 2025 Data/FY 2027
Payment Determination
ddrumheller on DSK120RN23PROD with PROPOSALS2
a. Background
The impact of social risk factors on
health outcomes has been wellestablished in the
literature.144 145 146 147 148 The Physicians
Foundation reported that 73 percent of
the physician respondents to the 2021
iteration of their annual survey agreed
that social risk factors like housing
instability and food insecurity would
drive health services demand.149
144 Institute of Medicine 2014. Capturing Social
and Behavioral Domains and Measures in
Electronic Health Records: Phase 2. Washington,
DC: The National Academies Press. Available at:
https://doi.org/10.17226/18951.
145 Centers for Medicare & Medicaid Services.
(2021). Accountable Health Communities Model.
Accountable Health Communities Model √ CMS
Innovation Center. Available at: https://
innovation.cms.gov/innovation-models/ahcm.
Accessed November 23, 2021.
146 Kaiser Family Foundation. (2021). Racial and
Ethnic Health Inequities and Medicare. Available
at: https://www.kff.org/medicare/report/racial-andethnic-health-inequities-and-medicare/. Accessed
November 23, 2021.
147 Milkie Vu et al. Predictors of Delayed
Healthcare Seeking Among American Muslim
Women, Journal of Women’s Health 26(6) (2016) at
58; Nadimpalli SB, Cleland CM, Hutchinson MK,
Islam N, Barnes LL, Van Devanter N. (2016) The
Association between Discrimination and the Health
of Sikh Asian Indians. Health Psychology, 35(4),
351–355. https://doi.org/10.1037/hea0000268.
148 Office of the Assistant Secretary for Planning
and Evaluation (ASPE). (2020). Report to Congress:
Social Risk Factors and Performance Under
Medicare’s Value-Based Purchasing Program
(Second of Two Reports). Available at: https://
aspe.hhs.gov/pdf-report/second-impact-report-tocongress.
149 The Physicians Foundation. (2020) 2020
Survey of America’s Patients, Part Three. Available
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Recognizing the need for a more
comprehensive approach to eliminating
the health equity gap, we have
prioritized quality measures that would
capture social risk factors and facilitate
assessment of their impact on health
outcomes and disparities and healthcare
utilization and costs.150 151 152
Specifically, in the inpatient setting, we
aim to encourage systematic
identification of patients’ HRSNs (as
defined in section V.D.3.a. of this
proposed rule) as part of discharge
planning with the intention of
promoting linkages with relevant
community-based services that address
those needs and support improvements
in health outcomes following discharge
from the IPF.
While the Screening for Social Drivers
of Health measure (discussed previously
in section V.D.3. of this proposed rule)
enables identification of individuals
with HRSNs, use of the proposed Screen
Positive Rate for Social Drivers of
Health measure would allow IPFs to
capture the magnitude of these needs
and even estimate the impact of
individual-level HRSNs on healthcare
utilization when evaluating quality of
care.153 154 155 The proposed Screen
Positive Rate for Social Drivers of
Health measure would require IPFs to
report the rates of patients who screened
positive for each of the five core HRSNs.
at: https://physiciansfoundation.org/wp-content/
uploads/2020/10/2020-Physicians-FoundationSurvey-Part3.pdf.
150 Alley, D.E., C.N. Asomugha, P.H. Conway, and
D.M. Sanghavi. 2016. Accountable Health
Communities—Addressing Social Needs through
Medicare and Medicaid. The New England Journal
of Medicine 374(1):8–11. Available at: https://
doi.org/10.1056/NEJMp1512532.
151 Centers for Medicare & Medicaid Services.
(2021). Accountable Health Communities Model.
Accountable Health Communities Model CMS
Innovation Center. Available at: https://
innovation.cms.gov/innovation-models/ahcm.
Accessed November 23, 2021.
152 Billioux, A., Verlander, K., Anthony, S., &
Alley, D. (2017). Standardized Screening for HealthRelated Social Needs in Clinical Settings: The
Accountable Health Communities Screening Tool.
NAM Perspectives, 7(5). Available at: https://
doi.org/10.31478/201705b.
153 Baker, M.C., Alberti, P.M., Tsao, T.Y., Fluegge,
K., Howland, R.E., & Haberman, M. (2021). Social
Determinants Matter for Hospital Readmission
Policy: Insights From New York City. Health
Affairs, 40(4), 645–654. Available at: https://
doi.org/10.1377/hlthaff.2020.01742.
154 CMS. Accountable Health Communities
Model. Accountable Health Communities Model
CMS Innovation Center. Available at: https://
innovation.cms.gov/innovation-models/ahcm.
Accessed November 23, 2021.
155 Hammond, G., Johnston, K., Huang, K., Joynt
Maddox, K. (2020). Social Determinants of Health
Improve Predictive Accuracy of Clinical Risk
Models for Cardiovascular Hospitalization, Annual
Cost, and Death. Circulation: Cardiovascular
Quality and Outcomes, 13 (6) 290–299. Available at:
https://doi.org/10.1161/
CIRCOUTCOMES.120.006752.
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Reporting the screen positive rate for
each of the five core HRSNs would
inform actionable planning by IPFs
towards closing health equity gaps
unique to the populations they serve
and enable the development of
individual patient action plans
(including navigation and referral
services).
In the FY 2022 IPF PPS final rule (86
FR 42625 through 42632) and the FY
2023 IPF PPS final rule (87 FR 46865
through 46873), we discussed our
ongoing consideration of potential
approaches that could be implemented
to address health equity through the
IPFQR Program. As a result of the
feedback we received, we identified the
Screen Positive Rate for Social Drivers
of Health measure to help inform efforts
to address health equity.
This proposed measure would assess
the percent of patients admitted to the
IPF who are 18 years or older at time of
admission who were screened for
HRSNs and who screen positive for one
or more of the core HRSNs, including
food insecurity, housing instability,
transportation needs, utility difficulties,
or interpersonal safety (reported as five
separate rates).156
We refer readers to section V.D.3 of
this proposed rule where we previously
discussed the screening and
identification process resulting in the
selection of these five domains
associated with the proposed Screen for
Social Drivers of Health measure. The
proposed Screening for Social Drivers of
Health measure forms the basis of this
proposed Screen Positive Rate for Social
Drivers of Health measure. That is, the
number of patients screened for all five
HRSNs in the Screening for Social
Drivers of Health measure is the
denominator of the Screen Positive for
Social Drivers of Health measure
described here.
The COVID–19 pandemic
underscored the overwhelming impact
that these five core domains of HRSNs
have on disparities, health risk,
healthcare access, and health outcomes,
including premature mortality.157 158
156 Billioux, A., Verlander, K., Anthony, S., &
Alley, D. (2017). Standardized Screening for Health
Related Social Needs in Clinical Settings: The
Accountable Health Communities Screening Tool.
NAM Perspectives, 7(5). Available at: https://
doi.org/10.31478/201705b.
157 Kaiser Family Foundation. (2021). Racial and
Ethnic Health Inequities and Medicare. Available
at: https://www.kff.org/medicare/report/racial-andethnic-health-inequities-and-medicare/. Accessed
November 23, 2021.
158 Centers for Disease Control and Prevention.
(2019). CDC COVID–19 Response Health Equity
Strategy: Accelerating Progress Towards Reducing
COVID–19 Disparities and Achieving Health Equity.
July 2020. Available at: https://www.cdc.gov/
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ddrumheller on DSK120RN23PROD with PROPOSALS2
Adoption of the Screen Positive Rate for
Social Drivers of Health measure would
encourage IPFs to track prevalence of
specific HRSNs among patients over
time and use the data to stratify risk as
part of quality performance
improvement efforts. This proposed
measure may also prove useful for
patients by providing data transparency
and signifying IPFs’ familiarity,
expertise, and commitment regarding
these health equity issues. This
proposed measure also has the potential
to reduce healthcare provider burden
and burnout, including among IPFs and
their staff, by both acknowledging
patients’ non-clinical needs that
nevertheless greatly contribute to
adverse clinical outcomes and linking
providers with community-based
organizations to enhance patientcentered treatment and discharge
planning.159 160 161 Finally, we believe
the proposed Screen Positive Rate for
Social Drivers of Health measure has the
potential to facilitate data-informed
collaboration with community-based
services and focused community
investments, including the development
of pathways and infrastructure to
connect patients to local community
resources.
Ultimately, we are focused on
supporting effective and sustainable
collaboration between healthcare
delivery and local community-based
services organizations to meet the
unmet needs of people they serve.
Reporting data from both the Screening
for Social Drivers of Health and the
Screen Positive Rate for Social Drivers
of Health measures would enable both
identification and quantification of the
levels of HRSNs among communities
served by IPFs. These two Social Drivers
of Health measures harmonize, as it is
important to know both whether
screening occurred and the results from
the screening in order to develop
sustainable solutions. We believe that
there are multiple benefits to increasing
IPFs’ understanding of their patients’
HRSNs. First, we believe that this could
lead to increased clinical-community
coronavirus/2019-ncov/community/health-equity/
cdc-strategy.html. Accessed November 17, 2021.
159 The Physicians Foundation. (2020). Survey of
America’s Patients, Part Three. Available at: https://
physiciansfoundation.org/wp-content/uploads/
2020/10/2020-Physicians-Foundation-SurveyPart3.pdf.
160 De Marchis, E., Knox, M., Hessler, D.,
WillardGrace, R., Oliyawola, JN, et al. (2019).
Physician Burnout and Higher Clinic Capacity to
Address Patients’ Social Needs. The Journal of the
American Board of Family Medicine, 32 (1), 69–78.
161 Kung, A., Cheung, T., Knox, M., WillardGrace, R., Halpern, J., et.al, (2019). Capacity to
Address Social Needs Affect Primary Care Clinician
Burnout. Annals of Family Medicine. 17 (6), 487–
494. Available at: https://doi.org/10.1370/afm.2470.
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collaborations and an associated
increase in system capacity and
community investments. Second, we
believe this in turn could yield a net
reduction in costly healthcare
utilization by promoting more
appropriate healthcare service
consumption.162
Pursuant to our Meaningful Measures
2.0 Framework and in alignment with
the measures previously adopted for
hospitals participating in the Hospital
IQR Program, the proposed Screen
Positive Rate for Social Drivers of
Health measure would address the
equity priority area and align with our
commitment to introduce plans to close
health equity gaps and promote equity
through quality measures, including to
‘‘develop and implement measures that
reflect social and economic
determinants.’’ 163 Under our
Meaningful Measures Framework, the
Screen Positive Rate for Social Drivers
of Health measure would address the
quality priority of ‘‘Work with
Communities to Promote Best Practices
of Healthy Living’’ through the
Meaningful Measures Area of ‘‘Equity of
Care.’’ 164 Adoption of this proposed
measure would also align with our
strategic pillar to advance health equity
by addressing the health disparities that
underlie our health system.165
b. Overview of Measure
The proposed Screen Positive Rate for
Social Drivers of Health measure is
intended to enhance standardized data
collection that can identify individuals
who are at higher risk for poor health
outcomes related to HRSNs who would
benefit from connection via the IPF to
targeted community-based services.166
162 Centers for Medicare & Medicaid Services.
(2021). Accountable Health Communities Model.
Accountable Health Communities Model | CMS
Innovation Center. Available at: https://
innovation.cms.gov/innovation-models/ahcm.
Accessed November 23, 2021.
163 Centers for Medicare & Medicaid Services.
Meaningful Measures 2.0: Moving from Measure
Reduction to Modernization. Available at: https://
www.cms.gov/meaningful-measures-20-movingmeasure-reduction-modernization.
164 Centers for Medicare & Medicaid Services.
(2021). CMS Measures Management System
Blueprint (Blueprint v 17.0). Available at: https://
www.cms.gov/Medicare/Quality-Initiatives-PatientAssessment-Instruments/MMS/MMS-Blueprint.
165 Brooks-LaSure, C. (2021). My First 100 Days
and Where We Go From Here: A Strategic Vision
for CMS. Available at: https://www.cms.gov/blog/
my-first-100-days-and-where-we-go-here-strategicvision-cms.
166 Centers for Medicare & Medicaid Services.
(2021). A Guide to Using the Accountable Health
Communities Health-Related Social Needs
Screening Tool: Promising Practices and Key
Insights (June 2021). Available at: https://
innovation.cms.gov/media/document/ahcmscreeningtool-companion. Accessed November 23,
2021.
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The proposed measure would identify
the proportion of patients who screened
positive for one or more of the following
five HRSNs on the date of admission to
the IPF: food insecurity, housing
instability, transportation needs, utility
difficulties, and interpersonal safety.
Consistent with the Hospital IQR
Program, which adopted this measure in
the FY 2023 IPPS/LTCH PPS final rule
(87 FR 49215 through 49220), we would
require IPFs to report this measure as
five separate rates. Specifically, IPFs
would report the number of patients
who screened positive for food
insecurity, the number of patients who
screened positive for housing
instability, the number of patients who
screened positive for transportation
needs, the number of patients who
screened positive for utility difficulties,
and the number of patients who
screened positive for interpersonal
safety. We note that this measure is
intended to provide information to IPFs
on the level of unmet HRSNs among
patients served, and not for comparison
between IPFs.
The specifications for the proposed
Screen Positive Rate for Social Drivers
of Health measure, which were available
during the review of the MUC List, are
available at: https://mmshub.cms.gov/
sites/default/files/map-hospitalmeasure-specifications-manual2022.pdf.
(1) Measure Calculation
(a) Cohort
The proposed Screen Positive Rate for
Social Drivers of Health is a process
measure that would provide information
on the percent of patients, 18 years or
older on the date of admission for an
IPF stay, who were screened for an
HRSN, and who screen positive for one
or more of the following five HRSNs:
food insecurity; housing instability;
transportation needs; utility difficulties;
or interpersonal safety.
(b) Numerator
The numerator would consist of the
number of patients admitted for an IPF
stay who are 18 years or older on the
date of admission, who were screened
for an HRSN, and who screen positive
for having an unmet need in one or
more of the following five HRSNs
(calculated separately): The number of
patients who screened positive for food
insecurity, the number of patients who
screened positive for housing
instability, the number of patients who
screened positive for transportation
needs, the number of patients who
screened positive for utility difficulties,
and the number of patients who
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screened positive for interpersonal
safety. IPFs would report the number of
patients who screened positive for
having unmet needs in each of the five
HRSNs as a separate numerator. A
patient who screened positive for more
than one unmet HRSN would be
included in the numerator for each of
those HRSNs. For example, a patient
who screened positive for food
insecurity, housing instability, and
transportation needs would be included
in each of these numerators.
(c) Denominator
The denominator would consist of the
number of patients admitted for an IPF
stay who are 18 years or older on the
date of admission and are screened for
an HRSN (food insecurity, housing
instability, transportation needs, utility
difficulties and interpersonal safety)
during their IPF stay. The following
patients would be excluded from the
denominator: (1) patients who opt-out of
screening; and (2) patients who are
themselves unable to complete the
screening during their inpatient stay
and have no caregiver able to do so on
the patient’s behalf during their
inpatient stay.
(d) Calculation
The result of this measure would be
calculated as five separate rates. Each
rate is derived from the number of
patients admitted for an IPF stay and
who are 18 years or older on the date
of admission, screened for an HRSN,
and who screen positive for each of the
five HRSNs (that is, the number of
patients who screened positive for food
insecurity, the number of patients who
screened positive for housing
instability, the number of patients who
screened positive for transportation
needs, the number of patients who
screened positive for utility difficulties,
and the number of patients who
screened positive for interpersonal
safety) divided by the number of
patients 18 years or older on the date of
admission screened for all five HRSNs.
The measure is reported as five separate
rates—one for each HRSN, each
calculated with the same denominator.
ddrumheller on DSK120RN23PROD with PROPOSALS2
(2) Review by the Measure Applications
Partnership
We included the proposed Screen
Positive Rate for Social Drivers of
Health measure on the publicly
available MUC List, a list of measures
under consideration for use in various
Medicare programs.167 The CBE167 Centers for Medicare & Medicaid Services. List
of Measures Under Consideration for December 1,
2022. Available at: https://mmshub.cms.gov/
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convened MAP Health Equity Advisory
Group reviewed the MUC List and the
Screen Positive Rate for Social Drivers
of Health measure (MUC 2022–050) in
detail on December 6 through 7,
2022.168 The MAP Health Equity
Advisory Group expressed support for
the collection of data related to social
drivers of health, but raised concerns
regarding public reporting of these data
and potential repetition of asking
patients the same questions across
settings.169
In addition, on December 8 through 9,
2022, the MAP Rural Health Advisory
Group reviewed the 2022 MUC List,
which was also reviewed by the MAP
Hospital Workgroup on December 13
through 14, 2022.170 The MAP Rural
Health Advisory Group noted potential
reporting challenges including the
potential masking of health disparities
that are underrepresented in some areas
and that sample size and populations
served may be an issue, but also
expressed support that the measure
seeks to advance the drivers of health
and serves as a starting point to
determine where screening is occurring.
The MAP Hospital Workgroup
recommended conditional support of
the measure for rulemaking pending: (1)
endorsement by the CBE to address
reliability and validity concerns; (2)
attentiveness to how results are shared
and contextualized for public reporting;
and (3) examination of any differences
in reported rates by reporting process
(that is, to assess whether reported rates
are the same or different across IPFs and
other facilities that may use different
processes to report their data).171
Thereafter, the MAP Coordinating
Committee deliberated on January 24
through 25, 2023, and ultimately voted
to conditionally support the Screen
Positive Rate for Social Drivers of
measure-lifecycle/measure-implementation/prerulemaking/lists-and-reports.
168 Centers for Medicare & Medicaid Services.
2022–2023 MAP Final Recommendations. Available
at: https://mmshub.cms.gov/measure-lifecycle/
measure-implementation/pre-rulemaking/lists-andreports.
169 Centers for Medicare & Medicaid Services.
2022–2023 MAP Final Recommendations. Available
at: https://mmshub.cms.gov/measure-lifecycle/
measure-implementation/pre-rulemaking/lists-andreports.
170 Centers for Medicare & Medicaid Services.
2022–2023 MAP Final Recommendations. Available
at: https://mmshub.cms.gov/measure-lifecycle/
measure-implementation/pre-rulemaking/lists-andreports.
171 Centers for Medicare & Medicaid Services.
2022–2023 MAP Final Recommendations. Available
at: https://mmshub.cms.gov/measure-lifecycle/
measure-implementation/pre-rulemaking/lists-andreports.
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Health measure for rulemaking with the
same conditions.172
We agree with the MAP Coordinating
Committee’s support for the proposed
Screen Positive Rate for Social Drivers
of Health measure. We believe this
measure, alongside the Screening for
Social Drivers of Health measure,
establishes an important foundation to
prioritizing the achievement of health
equity among IPFs participating in the
IPFQR Program. Our approach to
developing health equity measures is
incremental, and we believe that health
equity outcomes in the IPFQR Program
will inform future efforts to advance and
achieve health equity by IPFs. We
believe this measure to be a building
block that lays the groundwork for a
future meaningful suite of measures that
would assess IPF progress in providing
high-quality healthcare for all patients,
regardless of social risk factors or
demographic characteristics.
(3) CBE Endorsement
We have not submitted this measure
for CBE endorsement at this time.
Although section 1886(s)(4)(D)(i) of the
Act generally requires that measures
specified by the Secretary shall be
endorsed by the entity with a contract
under section 1890(a) of the Act, section
1886(s)(4)(D)(ii) of the Act states that in
the case of a specified area or medical
topic determined appropriate by the
Secretary for which a feasible and
practical measure has not been endorsed
by the entity with a contract under
section 1890(a) of the Act, the Secretary
may specify a measure that is not so
endorsed as long as due consideration is
given to a measure that has been
endorsed or adopted by a consensus
organization identified by the Secretary.
We reviewed CBE-endorsed measures
and were unable to identify any other
CBE-endorsed measures on this topic;
therefore, we believe the exception in
section 1886(s)(4)(D)(ii) of the Act
applies.
c. Data Collection, Submission, and
Reporting
We believe incremental
implementation of the proposed Screen
Positive Rate for Social Drivers of
Health measure, by permitting one year
of voluntary reporting prior to required
reporting, would allow IPFs who are not
yet screening patients for HRSNs to get
experience with the measure and
equally allow IPFs who already
undertake screening efforts to report
172 Centers for Medicare & Medicaid Services.
2022–2023 MAP Final Recommendations. Available
at: https://mmshub.cms.gov/measure-lifecycle/
measure-implementation/pre-rulemaking/lists-andreports.
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data already being collected. Therefore,
we propose voluntary reporting of this
measure, along with the Screening for
Social Drivers of Health measure
described in section V.D.3 of this
proposed rule, beginning with the data
collected in CY 2024, which would be
reported to CMS in 2025 followed by
required reporting beginning with data
collected in CY 2025, which would be
reported to CMS in 2026 and affect FY
2027 payment determination.
While this measure would require
IPFs to collect patient-level data on their
patients’ social drivers of health
screening results, we propose to adopt
this measure as an aggregate measure
(that is, IPFs would be required to
submit only numerator results for each
of the five screening areas and the
number of patients screened for all five
of the HRSNs). IPFs are required to
submit information for aggregate chartabstracted measures once annually
using a CMS-approved web-based data
collection tool available within the HQR
System (previously referred to as the
QualityNet Secure Portal). We refer
readers to section V.I of this proposed
rule (Form, Manner, and Timing of
Quality Data Submission) for more
details on our previously finalized data
submission and deadline requirements
across measure types.
We invite public comment on this
proposal.
5. Proposal To Adopt the Psychiatric
Inpatient Experience (PIX) Survey
Beginning With Voluntary Reporting of
CY 2025 Data and Required Reporting
Beginning With CY 2026 Data/FY 2028
Payment Determination
ddrumheller on DSK120RN23PROD with PROPOSALS2
a. Background
We believe that a comprehensive
approach to quality must include
directly reported feedback regarding
facility, provider, and payer
performance. Therefore, we have
consistently stated our commitment to
identifying an appropriate patient
experience of care measure for the IPF
setting and adopting this measure in the
IPFQR Program at the first opportunity
(77 FR 53646, 78 FR 50897, 79 FR 45964
through 45965, 80 FR 46714 through
46715, 82 FR 38470 through 38471, 83
FR 38596, 84 FR 38467, 85 FR 47043,
86 FR 42654 through 42656, and 87 FR
46846).
In the FY 2014 IPPS/LTCH PPS final
rule, we adopted a voluntary
information collection regarding
whether IPFs participating in the IPFQR
Program assess patient experience of
inpatient behavioral health services
using a standardized instrument and for
IPFs that answer ‘‘Yes’’ to indicate the
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name of the survey that they administer
(78 FR 50896 through 50897). In the FY
2015 IPF PPS final rule, we adopted this
information collection as the
Assessment of Patient Experience of
Care measure beginning with the FY
2016 payment determination (79 FR
45964 through 45965). Data for CY 2016
showed that while the majority of IPFs
(approximately 76 percent) were
collecting patient experience of care
data through a standardized instrument,
there was a wide variation in the
instrument being used. The data for CY
2016 indicated that the most widely
used survey instrument was not in the
public domain and was used by less
than 30 percent of the IPFs that used a
patient experience survey. In the FY
2015 IPF PPS final rule, we indicated
our intention to adopt a standardized
measure of patient experience of care for
the IPFQR Program.
In the FY 2019 IPF PPS final rule, we
removed the Assessment of Patient
Experience of Care measure from the
IPFQR Program because we believed
that we had collected sufficient
information to inform development of a
patient experience of care measure (83
FR 38596 through 38597). In the FY
2020 IPF PPS final rule, we summarized
our request for comments on our
analysis of the results of the Assessment
of Patient Experience of Care measure
and feedback on potential adoption of
the Hospital Consumer Assessment of
Healthcare Providers and Systems
(HCAHPS) survey for the IPFQR
Program (84 FR 38467). In response to
our request, many commenters
expressed concern that HCAHPS was
not specified for the IPF setting and
recommended that CMS identify a
survey that has been developed for and
tested in the IPF setting. Furthermore, in
the FY 2021 IPF PPS proposed rule, we
did not propose any updates to the
IPFQR Program; however, we received
many comments requesting that we
adopt a patient experience of care
measure in the IPFQR Program, which
we summarized in the FY 2021 IPF PPS
final rule (85 FR 47043). We received
similar input strongly advocating for a
patient experience of care measure for
the IPFQR Program in response to a
solicitation of comments on potential
measures for the IPFQR Program in the
FY 2022 IPF PPS proposed rule, which
we summarized in the FY 2022 IPF PPS
final rule (86 FR 42654 through 42656).
Many of these comments were from
patients and their families and
described how meaningful such a
measure would be for individuals who
receive services from IPFs. Though we
did not solicit input on a patient
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experience of care measure in the FY
2023 IPF PPS proposed rule, we
received many comments strongly
recommending that we adopt such a
measure, which we summarized in the
FY 2023 IPF PPS final rule (87 FR
46846). Since publication of the FY
2023 IPF PPS final rule, section 4125(c)
of the Consolidated Appropriations Act,
2023 (Pub. L. 117–328) was enacted,
which amends section 1886(s)(4) of the
Act to require that the quality measures
specified for the IPFQR Program shall
include a quality measure of patients’
perspective on care not later than the FY
2031 payment determination.
We have continued to review publicly
available patient experience of care
instruments to identify such an
instrument specified for, and tested in,
the IPF setting. In our review, we
identified the Psychiatric Inpatient
Experience (PIX) survey as a publicly
available survey instrument developed
for and tested in the IPF setting.
Pursuant to the Meaningful Measures
2.0 Framework, this measure addresses
the ‘‘Person-Centered’’ priority area, as
well as the ‘‘Individual and Caregiver
Voice’’ foundation and aligns with our
commitment to prioritize outcome and
patient-reported measures.173 This
measure also aligns with the CMS
National Quality Strategy Goal 4 ‘‘Foster
Engagement.’’ It also supports the
Behavioral Health Strategy goal of
‘‘Strengthen Equity and Quality in
Behavioral Health Care.’’ 174
Furthermore, this measure supports the
new Universal Foundation domain of
‘‘Person-Centered Care.’’ 175
b. Overview of Measure
The PIX survey was developed by a
team at the Yale University, Yale New
Haven Psychiatric Hospital to address
the gap in available experience of care
surveys, specifically the lack of publicly
available, minimally burdensome,
psychometrically validated surveys
specified for the IPF setting.176 The
interdisciplinary team that developed
this survey, including researchers and
clinicians, conducted the following
steps in developing the survey: (1)
173 Centers for Medicare & Medicaid Services.
Meaningful Measures 2.0: Moving from Measure
Reduction to Modernization. Available at: https://
www.cms.gov/meaningful-measures-20-movingmeasure-reduction-modernization.
174 CMS. (2022). CMS Behavioral Health Strategy.
Available at https://www.cms.gov/cms-behavioralhealth-strategy. Accessed on February 20, 2023.
175 https://www.nejm.org/doi/full/10.1056/
NEJMp2215539.
176 Klemanski DH, Barnes T, Bautista C, Tancreti
C, Klink B, Dix E. Development and Validation of
the Psychiatric Inpatient Experience (PIX) Survey:
A Novel Measure of Patient Experience Quality
Improvement. Journal of Patient Experience.
2022;9. doi:10.1177/23743735221105671.
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literature review; (2) patient focus
groups; (3) solicitation of input from a
patient and family advisory council; (4)
review of content validity with an
expert panel; (5) development of survey;
and (6) survey testing within the Yale
New Haven Psychiatric Hospital
system.177
The resulting survey contains 23
items in four domains. Patients can
respond to each of the 23 items using a
five-point Likert scale (that is, strongly
disagree, somewhat disagree, neutral,
somewhat agree, strongly agree) or
choose that the item does not apply. The
four domains are:
• Relationship with Treatment Team;
• Nursing Presence;
• Treatment Effectiveness; and
• Healing Environment.178
The PIX survey is distributed to
patients by administrative staff at a time
beginning 24 hours prior to planned
discharge. The survey, which is
available in both English and Spanish,
can be completed prior to discharge
using either a paper copy of the survey
or an electronic version of the survey
via tablet computer.179 For a complete
list of survey questions, including
which questions are elements of each
domain, we refer readers to the
description of the survey in the Journal
of Patient Experience: https://
journals.sagepub.com/doi/full/10.1177/
23743735221105671.
(1) Measure Calculation
(a) Cohort
ddrumheller on DSK120RN23PROD with PROPOSALS2
The cohort for this measure is all
patients discharged from an IPF during
the reporting period who do not meet
one of the following exclusions: (1)
patients who are under 13 years of age
at time of discharge, and (2) patients
who are unable to complete the survey
due to cognitive or intellectual
limitations. Our proposed sampling
procedures that IPFs could apply to the
PIX survey measure are described in
section V.I.6 of the preamble of this
proposed rule.
177 Klemanski DH, Barnes T, Bautista C, Tancreti
C, Klink B, Dix E. Development and Validation of
the Psychiatric Inpatient Experience (PIX) Survey:
A Novel Measure of Patient Experience Quality
Improvement. Journal of Patient Experience.
2022;9. doi:10.1177/23743735221105671.
178 Klemanski DH, Barnes T, Bautista C, Tancreti
C, Klink B, Dix E. Development and Validation of
the Psychiatric Inpatient Experience (PIX) Survey:
A Novel Measure of Patient Experience Quality
Improvement. Journal of Patient Experience.
2022;9. doi:10.1177/23743735221105671
179 Klemanski DH, Barnes T, Bautista C, Tancreti
C, Klink B, Dix E. Development and Validation of
the Psychiatric Inpatient Experience (PIX) Survey:
A Novel Measure of Patient Experience Quality
Improvement. Journal of Patient Experience.
2022;9. doi:10.1177/23743735221105671
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(b) Calculation
The measure would be reported as
five separate rates, one for each of the
four domains of the PIX survey and one
overall rate. Each of these rates would
be calculated from patient responses on
the PIX survey and then publicly
reported on the Care Compare website
(or successor CMS website). We would
report the mean rates for each domain
as well the overall mean rate on the Care
Compare website (or successor CMS
website). To calculate the mean scores,
we would assign a numerical value
ranging from 1 (Strongly Disagree) to 5
(Strongly Agree). We would then
calculate the average response by
adding the values of all responses and
dividing that value by the number of
responses, excluding questions that
were omitted or to which the patient
selected ‘‘Does Not Apply.’’
The MAP Hospital workgroup
reviewed the 2022 MUC List on
December 13 through 14, 2022. The
MAP Hospital workgroup conditionally
supported the measure for rulemaking,
while emphasizing the importance of
including patient reported experience of
care data in the IPFQR Program. The
MAP Hospital workgroup’s conditions
for support included endorsement by
the CBE and additional testing data for
this measure, specifically: (1) data from
testing of the measure in a variety of
settings (including urban, rural, safety
net providers, and others), (2) data
regarding survey results depending on
the timing of survey administration
(pre- versus post-discharge), (3) data
regarding patient factors (for example,
voluntary versus involuntary
admissions), and (4) data regarding of
mode of administration (for example,
email versus mail) that may affect
(2) Review by the Measure Applications performance.183 Thereafter, the MAP
Partnership (MAP)
Coordinating Committee deliberated on
January 24 through 25, 2023 and
We included the PIX survey measure
ultimately voted to uphold the Hospital
on the publicly available ‘‘List of
Workgroup’s recommendation to
Measures Under Consideration for
conditionally support the PIX survey
December 1, 2022’’ (MUC List), a list of
measures under consideration for use in measure for rulemaking pending the
as the MAP Hospital
various Medicare programs.180 The CBE- same conditions
workgroup.184
convened Measure Applications
We believe that the testing that has
Partnership (MAP) reviewed the MUC
been
conducted on the PIX survey
List and discussed the potential use of
demonstrates that it is a valid and
the PIX survey for the IPFQR Program.
reliable tool for measuring patient
The MAP Health Equity Advisory
experience of care in IPFs, and that the
Group agreed that well-constructed
results from this initial testing are
patient experience of care measures are
generalizable across IPFs. However, we
an important indicator of quality care.
agree with the MAP Hospital workgroup
Overall, the MAP Health Equity
that additional testing of this measure
Advisory Group expressed that this
measure is a ‘‘step in the right direction could help better understand measure
results, including any differences in
for behavioral health.’’ 181
In addition, on December 8 through 9, measure results that were not analyzed
2022, the MAP Rural Health Workgroup during the PIX survey’s initial testing.
Therefore, we intend to conduct
reviewed the 2022 MUC List and
additional testing of the PIX survey
expressed support for this measure,
prior to public reporting of the measure
with patient support being especially
strong. Some members of the MAP Rural data, and we are proposing two years of
Health Advisory Group were concerned voluntary reporting before beginning
mandatory reporting of the PIX survey.
about operational challenges,
specifically costs related to
(3) CBE Endorsement
implementation and maintenance and
The measure developer has not
potential bias if the surveying occurs
submitted this measure for CBE
182
prior to discharge.
endorsement at this time. The developer
does intend to submit this measure for
180 Centers for Medicare & Medicaid Services. List
endorsement in the future, following
of Measures Under Consideration for December 1,
additional testing as recommended by
2022. Available at: https://mmshub.cms.gov/
the MAP Hospital workgroup. Although
measure-lifecycle/measure-implementation/prerulemaking/lists-and-reports.
181 Centers for Medicare & Medicaid Services.
2022–2023 MAP Final Recommendations. Available
at: https://mmshub.cms.gov/measure-lifecycle/
measure-implementation/pre-rulemaking/lists-andreports.
182 Centers for Medicare & Medicaid Services.
2022–2023 MAP Final Recommendations. Available
at: https://mmshub.cms.gov/measure-lifecycle/
measure-implementation/pre-rulemaking/lists-andreports.
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183 Centers for Medicare & Medicaid Services.
2022–2023 MAP Final Recommendations. Available
at: https://mmshub.cms.gov/measure-lifecycle/
measure-implementation/pre-rulemaking/lists-andreports.
184 Centers for Medicare & Medicaid Services.
2022–2023 MAP Final Recommendations. Available
at: https://mmshub.cms.gov/measure-lifecycle/
measure-implementation/pre-rulemaking/lists-andreports.
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section 1886(s)(4)(D)(i) of the Act
generally requires that measures
specified by the Secretary shall be
endorsed by the entity with a contract
under section 1890(a) of the Act, section
1886(s)(4)(D)(ii) of the Act states that in
the case of a specified area or medical
topic determined appropriate by the
Secretary for which a feasible and
practical measure has not been endorsed
by the entity with a contract under
section 1890(a) of the Act, the Secretary
may specify a measure that is not so
endorsed as long as due consideration is
given to a measure that has been
endorsed or adopted by a consensus
organization identified by the Secretary.
We reviewed CBE-endorsed measures
and were unable to identify any other
CBE-endorsed measures on this topic.
We did identify the Experience of Care
and Health Outcomes (ECHO) Survey
measure (CBE #008); however, this
measure has had its endorsement
removed as of the spring 2020 cycle.
Additionally, this survey was developed
and tested for outpatient behavioral
health, not the inpatient setting.
Additionally, we identified the Patient
Experience of Psychiatric Care as
Measured by the Inpatient Consumer
Survey (ICS) measure (CBE #0726). This
measure has also had its endorsement
removed as of the spring 2018 cycle. As
neither of these two measures are
endorsed at this time, we believe the
exception in section 1886(s)(4)(D)(ii) of
the Act applies.
(c) Data Collection, Submission and
Reporting
IPFs would be responsible for
administering the survey and collecting
data on survey responses because the
PIX survey is administered beginning 24
hours prior to a patient’s planned
discharge. Therefore, IPFs would collect
the data in a manner similar to the
collection of data for chart-abstracted
measures or other patient screening
measures. That is, the IPFs would
collect data in the facility and then
report these data to CMS using the
methods described in section V.I.4 of
this proposed rule, that is ‘‘Data
Submission Requirements’’ under
‘‘Procedural Requirements.’’
Because we anticipate that many IPFs,
which already administer different
patient experience of care survey
instruments to their patients, would
need to transition to the PIX survey, we
are proposing a voluntary reporting
period beginning with data from CY
2025, which would be reported to CMS
in CY 2026. We would then require IPFs
to report data for the PIX survey
measure beginning with data collected
during CY 2026, to be reported to CMS
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during CY 2027 and affect the FY 2028
payment determination.
We invite comments on our proposal.
E. Proposed Modification of the COVID–
19 Vaccination Coverage Among
Healthcare Personnel (HCP) Measure
Beginning With the Quarter 4 CY 2023
Reporting Period/FY 2025 Payment
Determination
1. Background
On January 31, 2020, the Secretary of
the Department of Health and Human
Services declared a public health
emergency (PHE) for the United States
in response to the global outbreak of
SARS–COV–2, a novel (new)
coronavirus that causes a disease named
‘‘coronavirus disease 2019’’ (COVID–
19).185 Subsequently, multiple quality
reporting programs including the
Hospital IQR Program (86 FR 45374)
and the IPFQR Program (86 FR 42633
through 42640) adopted the COVID–19
Vaccination Coverage among Healthcare
Personnel (HCP) measure. The COVID–
19 Vaccination Coverage Among
Healthcare Personnel (HCP) measure
adopted in the IPFQR Program in the FY
2022 IPF PPS final rule (86 FR 42633
through 42650) requires each IPF to
calculate the percentage of HCP eligible
to work in the IPF for at least one day
during the reporting period, excluding
persons with contraindications to the
COVID–19 vaccine, who have received
a complete vaccination course against
SARS–CoV–2 (86 FR 42633 through
42640).
COVID–19 has continued to spread
domestically and around the world with
more than 102.7 million cases and 1.1
million deaths in the United States as of
February 13, 2023.186 In recognition of
the ongoing significance and complexity
of COVID–19, the Secretary has renewed
the PHE on April 21, 2020, July 23,
2020, October 2, 2020, January 7, 2021,
April 15, 2021, July 19, 2021, October
15, 2021, January 14, 2022, April 12,
2022, July 15, 2022, October 13, 2022,
January 11, and February 9, 2023.187
The President has announced that the
185 U.S. Dept of Health and Human Services,
Office of the Assistant Secretary for Preparedness
and Response. (2020). Determination that a Public
Health Emergency Exists. Available at: https://
www.phe.gov/emergency/news/healthactions/phe/
Pages/2019-nCoV.aspx.
186 Centers for Disease Control and Prevention.
COVID Data Tracker. Accessed February 13, 2023.
Available at: https://covid.cdc.gov/covid-datatracker/#datatracker-home.
187 U.S. Dept. of Health and Human Services.
Office of the Assistant Secretary for Preparedness
and Response. (2023). Renewal of Determination
that a Public Health Emergency Exists. Available at:
https://aspr.hhs.gov/legal/PHE/Pages/covid1911Jan23.aspx.
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PHE will end on May 11, 2023,188 and
HHS has stated that the public health
response to COVID–19 remains a public
health priority with a whole of
government approach to combatting the
virus, including through vaccination
efforts.189
In the FY 2022 IPF PPS final rule (86
FR 42633 through 42635) and in our
Revised Guidance for Staff Vaccination
Requirements,190 we stated that
vaccination is a critical part of the
nation’s strategy to effectively counter
the spread of COVID–19. We continue to
believe it is important to incentivize and
track HCP vaccination through quality
measurement across care settings,
including IPFs, in order to protect HCP,
patients, and caregivers, and to help
sustain the ability of HCP to continue
serving their communities throughout
the PHE and beyond.
At the time we issued the FY 2022 IPF
PPS final rule, the Food and Drug
Administration (FDA) had issued
emergency use authorizations (EUAs)
for initial and primary adult vaccines
manufactured by Pfizer-BioNTech,191
Moderna,192 and Janssen.193 On August
23, 2021, the FDA issued an approval
for the Pfizer-BioNTech vaccine, now
marketed as Comirnaty.194 The FDA
issued approval for the Moderna
vaccine, marketed as Spikevax, on
188 https://www.whitehouse.gov/wp-content/
uploads/2023/01/SAP-H.R.-382-H.J.-Res.-7.pdf.
189 U.S. Dept. of Health and Human Services. Fact
Sheet: COVID–19 Public Health Emergency
Transition Roadmap. February 9, 2023. Available at:
https://www.hhs.gov/about/news/2023/02/09/factsheet-covid-19-public-health-emergency-transitionroadmap.html.
190 Centers for Medicare & Medicaid Services.
Revised Guidance for Staff Vaccination
Requirements QSO–23–02–ALL. October 26, 2022.
Available at: https://www.cms.gov/files/document/
qs0-23-02-all.pdf.
191 Food and Drug Administration. (December
2020). FDA Takes Key Action in Fight Against
COVID–19 By Issuing Emergency Use Authorization
for First COVID–19 Vaccine. Available at: https://
www.fda.gov/news-events/press-announcements/
fda-takes-key-action-fight-against-covid-19-issuingemergency-use-authorization-first-covid-19.
192 Food and Drug Administration. (December
2020). FDA Takes Additional Action in Fight
Against COVID–19 By Issuing Emergency Use
Authorization for Second COVID–19 Vaccine.
Available at: https://www.fda.gov/news-events/
press-announcements/fda-takes-additional-actionfight-against-covid-19-issuing-emergency-useauthorization-second-covid.
193 Food and Drug Administration. (February
2021). FDA Issues Emergency Use Authorization for
Third COVID–19 Vaccine. Available at: https://
www.fda.gov/news-events/press-announcements/
fda-issues-emergency-use-authorization-thirdcovid-19-vaccine.
194 Food and Drug Administration. (August 2021).
FDA Approves First COVID–19 Vaccine. Available
at: https://www.fda.gov/news-events/pressannouncements/fda-approves-first-covid-19vaccine.
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January 31, 2022 195 and an EUA for the
Novavax adjuvanted vaccine on July 13,
2022.196 The FDA also issued EUAs for
COVID–19 single vaccine booster doses
in September 2021 197 and October
2021 198 for certain populations and in
November 2021 199 for all individuals 18
years of age and older. EUAs were
subsequently issued for a second
vaccine booster dose in March 2022 200
and for bivalent or ‘‘updated’’ booster
doses in August 2022.201
In the FY 2022 IPF PPS final rule, we
stated that data demonstrating the
effectiveness of COVID–19 vaccines to
prevent asymptomatic infection or
transmission of SARS–COV–2, the novel
(new) coronavirus that causes COVID–
19, were limited (86 FR 42634). While
the impact of COVID–19 vaccines on
asymptomatic infection and
transmission was not yet fully known at
the time of the FY 2022 IPF PPS final
rule, there were robust data available on
COVID–19 vaccine effectiveness across
multiple populations against
195 Food and Drug Administration. (January
2022). Coronavirus (COVID–19) Update: FDA Takes
Key Action by Approving Second COVID–19
Vaccine. Available at: https://www.fda.gov/newsevents/press-announcements/coronavirus-covid-19update-fda-takes-key-action-approving-secondcovid-19-vaccine.
196 Food and Drug Administration. (July 2022).
Coronavirus (COVID–19) Update: FDA Authorizes
Emergency Use of Novavax COVID–19 Vaccine,
Adjuvanted. Available at: https://www.fda.gov/
news-events/press-announcements/coronaviruscovid-19-update-fda-authorizes-emergency-usenovavax-covid-19-vaccine-adjuvanted.
197 Food and Drug Administration. (September
2021). FDA Authorizes Booster Dose of PfizerBioNTech COVID–19 Vaccine for Certain
Populations. Available at: https://www.fda.gov/
news-events/press-announcements/fda-authorizesbooster-dose-pfizer-biontech-covid-19-vaccinecertain-populations.
198 Food and Drug Administration. (October
2021). Coronavirus (COVID–19) Update: FDA Takes
Additional Actions on the Use of a Booster Dose for
COVID–19 Vaccines. Available at: https://
www.fda.gov/news-events/press-announcements/
coronavirus-covid-19-update-fda-takes-additionalactions-use-booster-dose-covid-19-vaccines.
199 Food and Drug Administration. (November
2021). Coronavirus (COVID–19) Update: FDA
Expands Eligibility for COVID–19 Vaccine Boosters.
Available at: https://www.fda.gov/news-events/
press-announcements/coronavirus-covid-19update-fda-expands-eligibility-covid-19-vaccineboosters.
200 Food and Drug Administration. (March 2022).
Coronavirus (COVID–19) Update: FDA Authorizes
Second Booster Dose of Two COVID–19 Vaccines
for Older and Immunocompromised Individuals.
Available at: https://www.fda.gov/news-events/
press-announcements/coronavirus-covid-19update-fda-authorizes-second-booster-dose-twocovid-19-vaccines-older-and.
201 Food and Drug Administration. (August 2022).
Coronavirus (COVID–19) Update: FDA Authorizes
Moderna, Pfizer-BioNTech Bivalent COVID–19
Vaccines for Use as a Booster Dose. Available at:
https://www.fda.gov/news-events/pressannouncements/coronavirus-covid-19-update-fdaauthorizes-moderna-pfizer-biontech-bivalent-covid19-vaccines-use.
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symptomatic infection, hospitalization,
and death. Two-dose COVID–19
vaccines from Pfizer-BioNTech and
Moderna had been found to be 88
percent and 93 percent effective against
hospitalization for COVID–19,
respectively, over 6 months for adults
over age 18 without
immunocompromising conditions. 202
During a SARS–COV–2 surge in the
spring and summer of 2021, 92 percent
of COVID–19 hospitalizations and 91
percent of COVID–19-associated deaths
were reported among persons not fully
vaccinated.203 Real-world studies of
population-level vaccine effectiveness
indicated similarly high rates of
effectiveness in preventing SARS–COV–
2 infection among frontline workers in
multiple industries, with a 90 percent
effectiveness in preventing symptomatic
and asymptomatic infection from
December 2020 through August 2021.204
Vaccines have also been highly effective
in real-world conditions (that is,
vaccines have continued to be highly
effective in conditions other than
clinical trials) at preventing COVID–19
in HCP with up to 96 percent
effectiveness for fully vaccinated HCP,
including those at risk for severe
infection and those in racial and ethnic
groups disproportionately affected by
COVID–19.205 In the presence of high
community prevalence of COVID–19,
residents of nursing homes with low
staff vaccination coverage had cases of
COVID–19-related deaths 195 percent
higher than those among residents of
nursing homes with high staff
202 Centers for Disease Control and Prevention.
(September 24, 2021). Morbidity and Mortality
Weekly Report (MMWR). Comparative Effectiveness
of Moderna, Pfizer-BioNTech, and Janssen (Johnson
& Johnson) Vaccines in Preventing COVID–19
Hospitalizations Among Adults Without
Immunocompromising Conditions—United States,
March-August 2021. Available at: https://cdc.gov/
mmwr/volumes/70/wr/mm7038e1.htm?s_
cid=mm7038e1_w.
203 Centers for Disease Control and Prevention.
(September 10, 2021). Morbidity and Mortality
Weekly Report (MMWR). Monitoring Incidence of
COVID–19 Cases, Hospitalizations, and Deaths, by
Vaccination Status—13 U.S. Jurisdictions, April 4July 17, 2021. Available at: https://cdc.gov.mmwr/
volumes/70/wr/mm7037e1.htm?s_cid=mm7037e1_
w.
204 Centers for Disease Control and Prevention.
(August 27, 2021). Morbidity and Mortality Weekly
Report (MMWR). Effectiveness of COVID–19
Vaccines in Preventing SARS–COV–2 Infection
Among Frontline Workers Before and During
B.1.617.2 (Delta) Variant Predominance—Eight U.S.
Locations, December 2020–August 2021. Available
at: https://cdc.gov/mmwr/volume/70/wr/
mm7034e4.htm?s_cid=mm7034e4_w.
205 Pilishivi, T. et al. (December 2022).
Effectiveness of mRNA Covid–19 Vaccine among
U.S. Health Care Personnel. New England Journal
of Medicine. 2021 Dec 16;385(25):e90. Available
online at: https://pubmed.ncbi.nlm.nih.gov/
34551224/.
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21291
vaccination coverage.206 Currently
available data demonstrate that COVID–
19 vaccines are effective and prevent
severe disease, including
hospitalization, and death.
As SARS–COV–2 persists and
evolves, our COVID–19 vaccination
strategy must remain responsive. When
we adopted the COVID–19 Vaccination
Coverage Among HCP measure in the
FY 2022 IPF PPS final rule, we stated
that the need for booster doses of the
COVID–19 vaccine had not been
established and no additional doses had
been recommended (86 FR 42639). We
also stated that we believed the
numerator was sufficiently broad to
include potential future boosters as part
of a ‘‘complete vaccination course’’ and
that the measure was sufficiently
specified to address boosters (86 FR
42639). Since we adopted the COVID–
19 Vaccination Coverage Among HCP
measure in the FY 2022 IPF PPS final
rule, new variants of SARS–COV–2 have
emerged around the world and within
the United States. Specifically, the
Omicron variant (and its related
subvariants) is listed as a variant of
concern by the Centers for Disease
Control and Prevention (CDC) because it
spreads more easily than earlier
variants.207 Vaccine manufacturers have
responded to the Omicron variant by
developing bivalent COVID–19
vaccines, which include a component of
the original virus strain to provide broad
protection against COVID–19 and a
component of the Omicron variant to
provide better protection against
COVID–19 caused by the Omicron
variant.208 These booster doses of the
bivalent COVID–19 vaccine have been
shown to increase immune response to
SARS–COV–2 variants, including
Omicron, particularly in individuals
who are more than 6 months removed
from receipt of their primary series.209
The FDA issued EUAs for two bivalent
COVID–19 vaccine booster doses, one
from Pfizer-BioNTech 210 and one from
206 McGarry BE et al. (January 2022). Nursing
Home Staff Vaccination and Covid–19 Outcomes.
New England Journal of Medicine. 2022 Jan
27;386(4):397–398. Available online at: https://
pubmed.ncbi.nlm.nih.gov/34879189/.
207 Centers for Disease Control and Prevention.
(August 2021). Variants of the Virus. Available at:
https://www.cdc.gov/coronavirus/2019-ncov/
variants/.
208 Food and Drug Administration. (November
2022). COVID–19 Bivalent Vaccine Boosters.
209 Chalkias, S et al. (October 2022). A Bivalent
Omicron-Containing Booster Vaccine against
Covid–19. N Engl J Med 2022; 387:1279–1291.
Available online at: https://www.nejm.org/doi/full/
10.1056/NEJMoa2208343.
210 Food and Drug Administration. (November
2022). Pfizer-BioNTech COVID–19 Vaccines.
Available at: https://www.fda.gov/emergency-
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Moderna,211 and strongly encourages
anyone who is eligible to consider
receiving a booster dose with a bivalent
COVID–19 vaccine to provide better
protection against currently circulating
variants.212 COVID–19 booster doses are
associated with a greater reduction in
infections among HCP and their patients
relative to those who only received
primary series vaccination. One study
showed a rate of breakthrough
infections among HCP who received
only the two-dose regimen of the
COVID–19 vaccine of 21.4 percent
compared to a rate of 0.7 percent among
HCP who received a third dose of the
COVID–19 vaccine.213
Despite the efficacy of COVID–19
vaccination generally, data submitted to
the CDC via the National Health Safety
Network (NHSN) demonstrate clinically
significant variation in booster dose
vaccination rates across facilities,
including IPFs. During the first quarter
of 2022, IPFs reported a median
coverage rate of booster or additional
dose(s) of 19.1 percent, with an
interquartile range of 8.7 percent to 37.9
percent. These data, which show a
performance gap in booster coverage,
indicate that there is opportunity to
improve booster vaccination coverage
among HCP in IPFs.214
We believe that vaccination remains
the most effective means to prevent the
worst consequences of COVID–19,
including severe illness, hospitalization,
and death. Given the availability of
vaccine efficacy data, EUAs issued by
the FDA for bivalent boosters, the
continued presence of SARS–COV–2 in
the United States, and variance among
rates of booster dose vaccination, it is
important to modify the COVID–19
Vaccination Coverage Among HCP
measure to reflect recent guidance that
preparedness-and-response/coronavirus-disease2019-Covid-19/pfizer-biontech-covid-19-vaccines.
211 Food and Drug Administration. (November
2022). Moderna COVID–19 Vaccines. Available at:
https://www.fda.gov/emergency-preparedness-andresponse/coronavirus-disease-2019-covid-19/
moderna-covid-19-vaccines.
212 Food and Drug Administration. (August 2022).
Coronavirus (COVID–19) Update: FDA Authorizes
Moderna, Pfizer-BioNTech Bivalent COVID–19
Vaccines for Use as a Booster Dose. Available at:
https://www.fda.gov/news-events/pressannouncements/coronavirus-covid-19-update-fdaauthorizes-moderna-pfizer-biontech-bivalent-covid19-vaccines-use.
213 Oster Y et al. (May 2022). The effect of a third
BNT162b2 vaccine on breakthrough infections in
health care workers: a cohort analysis. Clin
Microbiol Infect. 2022 May;28(5):735.e1–735.e3.
Available online at: https://
pubmed.ncbi.nlm.nih.gov/35143997/.
214 Measure Applications Partnership (MAP)
Hospital Workgroup Preliminary Analyses.
Available at: https://mmshub.cms.gov/sites/default/
files/map-hospital-measure-specifications-manual2022.pdf.
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explicitly specifies for HCP to receive
primary series and booster vaccine
doses in a timely manner. Given the
persistent spread of COVID–19, we
continue to believe that monitoring and
surveillance is important and provides
patients, beneficiaries, and their
caregivers with information to support
informed decision-making.
Beginning with the fourth quarter of
the CY 2023 reporting period/FY 2025
payment determination, we propose to
modify the COVID–19 Vaccination
Coverage Among HCP measure to
replace the term ‘‘complete vaccination
course’’ with the term ‘‘up-to-date’’ in
the HCP vaccination definition. We also
propose to update the numerator to
specify the time frames within which an
HCP is considered ‘‘up-to-date’’ with
recommended COVID–19 vaccines,
including booster doses.
In the FY 2022 IPF PPS final rule (86
FR 42638), we stated, and reiterate now,
that the COVID–19 Vaccination
Coverage Among HCP measure is a
process measure that assesses HCP
vaccination coverage rates. Unlike
outcome measures, process measures do
not assess a particular outcome.
2. Overview of Measure
The proposed COVID–19 Vaccination
Coverage Among HCP measure is a
process measure developed by the CDC
to track COVID–19 vaccination coverage
among HCP in settings such as acute
care facilities, including IPFs, and postacute care facilities.
We refer readers to the FY 2022 IPF
PPS final rule (86 FR 42635 through
42636) for more information on the
initial review of the current COVID–19
Vaccination Coverage Among HCP
measure by the Measure Applications
Partnership (MAP). We included an
updated version of the proposed
modification of the COVID–19
Vaccination Coverage Among HCP
measure on the list of measures under
consideration (MUC List), which is
published annually on behalf of CMS by
the CBE with which the Secretary must
contract as required by section 1890(a)
of the Act, for the 2022 to 2023 prerulemaking cycle for consideration by
the MAP.
In December 2022, the MAP Hospital
Workgroup discussed the proposed
modification of the COVID–19
Vaccination Coverage Among HCP
measure. The MAP Hospital Workgroup
stated that the proposed modification of
the current measure captures ‘‘up-todate’’ vaccination information in
accordance with the CDC’s
recommendations, which have been
updated since their initial development.
Additionally, the MAP Hospital
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Workgroup appreciated that the
proposed modified measure’s
denominator is broader and simplified
from seven categories of healthcare
personnel to four.215
During review on December 6 and 7,
2022, the MAP Health Equity Advisory
Group highlighted the importance of
COVID–19 measures and asked whether
the proposed modified measure
excludes individuals with
contraindications to Food and Drug
Administration (FDA) authorized or
approved COVID–19 vaccines, and
whether the measure will be stratified
by demographic factors.216 The CDC, the
measure developer for this measure,
responded to the question regarding
individuals with contraindications by
confirming that HCP with
contraindications to the vaccines are
excluded from the measure
denominator. The CDC further
explained that the proposed modified
measure will not be stratified since the
data are submitted at an aggregate rather
than an individual level.
During review on December 8 through
9, 2022, the MAP Rural Health Advisory
Group expressed concerns about data
collection burden, citing that collection
is performed manually and that small
rural hospitals may not have employee
health software.217 The measure
developer (that is, the CDC)
acknowledged the challenge of getting
adequate documentation and
emphasized the goal to ensure the
measure does not present a burden on
providers. The measure developer also
noted that the model used for this
measure is based on the Influenza
Vaccination Coverage Among HCP
measure (CBE #0431), and it intends to
utilize a similar approach to the
modified COVID–19 Vaccination
Coverage Among HCP measure if
vaccination strategy becomes seasonal.
The proposed modified COVID–19
Vaccination Coverage Among HCP
measure received conditional support
for rulemaking pending testing
indicating the measure is reliable and
valid, and endorsement by the CBE. The
MAP noted that the previous version of
215 Centers for Medicare & Medicaid Services.
2022–2023 MAP Final Recommendations. Available
at: https://mmshub.cms.gov/measure-lifecycle/
measure-implementation/pre-rulemaking/lists-andreports.
216 Centers for Medicare & Medicaid Services.
2022–2023 MAP Final Recommendations. Available
at: https://mmshub.cms.gov/measure-lifecycle/
measure-implementation/pre-rulemaking/lists-andreports.
217 Centers for Medicare & Medicaid Services.
2022–2023 MAP Final Recommendations. Available
at: https://mmshub.cms.gov/measure-lifecycle/
measure-implementation/pre-rulemaking/lists-andreports.
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the measure received endorsement from
the CBE (CBE #3636) 218 and that the
CDC intends to submit the proposed
updated measure for endorsement.
ddrumheller on DSK120RN23PROD with PROPOSALS2
a. Measure Specifications
The proposed modification of the
COVID–19 Vaccination Coverage
Among HCP measure would require that
IPFs collect data at least one week each
month for each of the three months in
a quarter.
The denominator would be the
number of HCP eligible to work in the
facility for at least one day during the
reporting period, excluding persons
with contraindications to COVID–19
vaccination that are described by the
CDC.219 There are not any proposed
changes to the denominator exclusions
for the current COVID–19 Vaccination
Coverage Among HCP measure, and the
proposed modified COVID–19
Vaccination Coverage Among HCP
measure would continue to exclude
otherwise denominator-eligible HCPs
with contraindications as defined by the
CDC.220 IPFs report the following four
categories of HCP to NHSN; 221 the first
three categories are included in the
measure denominator:
1. Employees: This category includes
all persons who receive a direct
paycheck from the IPF (that is, on the
IPF’s payroll), regardless of clinical
responsibility or patient contact.
2. Licensed independent practitioners
(LIPs): This category includes
physicians (MD, DO), advanced practice
nurses, and physician assistants who are
affiliated with the IPF but are not
directly employed by it (that is, they do
not receive a paycheck from the IPF),
regardless of clinical responsibility or
patient contact. Post-residency fellows
are also included in this category if they
are not on the IPF’s payroll.
3. Adult students/trainees and
volunteers: This category includes
medical, nursing, or other health
professional students, interns, medical
residents, or volunteers aged 18 or older
218 Centers for Medicare & Medicaid Services.
2022–2023 MAP Final Recommendations. Available
at: https://mmshub.cms.gov/measure-lifecycle/
measure-implementation/pre-rulemaking/lists-andreports. and CMS Measures Inventory Tool.
Available at: https://cmit.cms.gov/cmit/#/
MeasureView?variantId=5273§ionNumber=1.
219 Centers for Disease Control and Prevention.
(2022). Contraindications and precautions.
Available at: https://www.cdc.gov/vaccines/covid19/clinical-considerations/interim-considerationsus.html#contraindications.
220 Centers for Disease Control and Prevention.
(2022). Contraindications and precautions.
Available at: https://www.cdc.gov/vaccines/covid19/clinical-considerations/interim-considerationsus.html#contraindications.
221 https://www.cdc.gov/nhsn/pdfs/nqf/covid-vaxhcpcoverage-rev-2023-508.pdf.
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who are affiliated with the healthcare
facility, but are not directly employed
by it (that is, they do not receive a
paycheck from the facility), regardless of
clinical responsibility or patient contact.
4. Other contract personnel: Contract
personnel are defined as persons
providing care, treatment, or services at
the IPF through a contract who do not
fall into any of the previously discussed
denominator categories. Please note that
this also includes vendors providing
care, treatment, or services at the facility
who may or may not be paid through a
contract. Facilities are required to enter
data on other contract personnel for
submission in the NHSN application,
but reporting for this category is not
included in the COVID–19 Vaccination
Coverage Among HCP measure.
The numerator would be the
cumulative number of HCP in the
denominator population who are ‘‘upto-date’’ with CDC recommended
COVID–19 vaccines. IPFs should refer to
the CDC’s guidance, to determine the
then-applicable definition of ‘‘up-todate,’’ as of the first day of the
applicable reporting quarter. The CDC’s
guidance can be found at: https://
www.cdc.gov/nhsn/pdfs/hps/covidvax/
UpToDateGuidance-508.pdf. For
purposes of NHSN surveillance, the
CDC used the following definition of
‘‘up-to-date’’ during the fourth quarter
of CY 2022 surveillance period
(September 26, 2022 through December
25, 2022):
1. Individuals who received an
updated bivalent 222 booster dose, or
2a. Individuals who received their last
booster dose less than 2 months ago, or
2b. Individuals who completed their
primary series 223 less than 2 months
ago.
We refer readers to https://
www.cdc.gov/nhsn/nqf/ for
more details on the proposed modified
measure specifications.
We propose that public reporting of
the modified version of the COVID–19
Vaccination Coverage Among HCP
measure would begin with the October
2024 Care Compare refresh, or as soon
as technically feasible after that refresh.
b. CBE Endorsement
The current version of the COVID–19
Vaccination Coverage Among HCP
measure received CBE endorsement
222 The updated (bivalent) Moderna and PfizerBioNTech boosters target the most recent Omicron
subvariants. The updated (bivalent) boosters were
recommended by the CDC on 9/2/2022. As of this
date, the original, monovalent mRNA vaccines are
no longer authorized as a booster dose for people
ages 12 years and older.
223 Completing a primary series means receiving
a two-dose series of a COVID–19 vaccine or a single
dose of Janssen/J&J COVID–19 vaccine.
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(CBE #3636, ‘‘Quarterly Reporting of
COVID–19 Vaccination Coverage among
Healthcare Personnel’’) on July 26,
2022.224
Although section 1886(s)(4)(D)(i) of
the Act generally requires that measures
specified by the Secretary shall be
endorsed by the entity with a contract
under section 1890(a) of the Act, section
1886(s)(4)(D)(ii) of the Act states that in
the case of a specified area or medical
topic determined appropriate by the
Secretary for which a feasible and
practical measure has not been endorsed
by the entity with a contract under
section 1890(a) of the Act, the Secretary
may specify a measure that is not so
endorsed as long as due consideration is
given to a measure that has been
endorsed or adopted by a consensus
organization identified by the Secretary.
We reviewed CBE-endorsed measures
and were unable to identify any other
CBE-endorsed measures on this topic;
therefore, we believe the exception in
section 1886(s)(4)(D)(ii) of the Act
applies. The CDC, as the measure
developer, is currently pursuing
endorsement for the modified version of
the measure as the current version of the
measure has already received
endorsement.
3. Data Collection, Submission, and
Reporting
We refer readers to the FY 2022 IPF
PPS final rule (86 FR 42636 through
42640) for information on data
submission and reporting of the current
COVID–19 Vaccination Coverage
Among HCP measure. While we do not
propose any changes to the data
submission or reporting process, we
propose that reporting of the updated
measure would begin with the fourth
quarter of CY 2023 reporting period for
FY 2025 payment determination.
Beginning with the FY 2026 payment
determination, we propose that IPFs
would be required to submit data for the
entire calendar year.
Under the data submission and
reporting process, IPFs would collect
the numerator and denominator for the
COVID–19 Vaccination Coverage
Among HCP measure for at least one
self-selected week during each month of
the reporting quarter and submit the
data to the CDC’s National Health Safety
Network (NHSN) Healthcare Personal
Safety (HPS) Component before the
quarterly deadline. If an IPF submits
more than one week of data in a month,
the CDC would use most recent week’s
224 CMS Measures Inventor Tool. COVDI–19
Vaccination Coverage among Healthcare Personnel.
Available at: https://cmit.cms.gov/cmit/#/
MeasureView?variantId=5273§ionNumber=1.
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data to calculate the measure results
which would be publicly reported. Each
quarter, the CDC would calculate a
single quarterly COVID–19 HCP
vaccination coverage rate for each IPF,
which would be calculated by taking the
average of the data from the three
weekly rates submitted by the IPF for
that quarter. CMS would publicly report
each quarterly COVID–19 HCP
vaccination coverage rate as calculated
by the CDC based on the data IPFs
submit to the NHSN (86 FR 42636
through 42640).
We invite public comment on this
proposal.
ddrumheller on DSK120RN23PROD with PROPOSALS2
F. Removal or Retention of IPFQR
Program Measures
1. Background
In the FY 2018 IPPS/LTCH PPS final
rule (82 FR 38463 through 38465) and
FY 2019 IPF PPS final rule (83 FR 38591
through 38593), we adopted several
considerations for removing or retaining
measures within the IPFQR Program.
Specifically, we have adopted eight
factors that we consider when
evaluating whether to propose a
measure for removal from the IPFQR
Program. These factors are: (1) measure
performance among IPFs is so high and
unvarying that meaningful distinctions
and improvements in performance can
no longer be made (‘‘topped out’’
measures); (2) measure does not align
with current clinical guidelines or
practice; (3) measure can be replaced by
a more broadly applicable measure
(across setting or populations) or a
measure that is more proximal in time
to desired patient outcomes for the
particular topic; (4) measure
performance or improvement does not
result in better patient outcomes; (5)
measure can be replaced by a measure
more strongly associated with desired
patient outcomes for the particular
topic; (6) measure collection or public
reporting leads to negative intended
consequences other than patient harm;
(7) measure is not feasible to implement
as specified; and (8) the costs associated
with a measure outweigh the benefit of
its continued use in the program. For
measure removal factor one, we
specified that a measure is ‘‘topped out’’
if it meets the following criteria: (1)
statistically indistinguishable
performance at the 75th and 90th
percentiles; and (2) the truncated
coefficient of variation is less than or
equal to 0.10.
We also adopted three factors for
consideration in determining whether to
retain a measure in the IPFQR Program,
even if the measure meets one or more
factors for removal. These retention
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factors are: (1) measure aligns with other
CMS and HHS policy goals, such as
those delineated in the National Quality
Strategy and CMS Quality Strategy; (2)
measure aligns with other CMS
programs, including other quality
reporting programs; and (3) measure
supports efforts to move IPFs towards
reporting electronic measures. In the FY
2018 IPPS/LTCH PPS final rule (82 FR
38464), we stated that these removal
and retention factors are considerations
that we take into account in balancing
the benefits and drawbacks of removing
or retaining measures on a case-by-case
basis.
Since adoption, we have not proposed
any changes to these policies for
removal or retention and refer readers to
the FY 2018 IPPS/LTCH PPS final rule
(82 FR 38463 through 38465) and the FY
2019 IPF PPS final rule (83 FR 38591
through 38593) for more information.
We do not propose any updates to these
measure retention and removal policies.
We propose to codify these previously
adopted policies at § 412.433(e).
We welcome comments on this
proposal.
2. Proposed Measures for Removal
We continue to evaluate our measure
set against these removal and retention
factors on an ongoing basis. In this
continual evaluation of the IPFQR
Program measure set under our
Meaningful Measures Framework and
according to our measure removal and
retention factors, we identified two
measures that we believe are
appropriate to propose removing from
the IPFQR Program beginning with the
FY 2025 payment determination. Our
discussion of these measures follows.
a. Proposed Removal of the Patients
Discharged on Multiple Antipsychotic
Medications With Appropriate
Justification (HBIPS–5) (Previously
Endorsed Under CBE #0560) Measure
Beginning With FY 2025 Payment
Determination
As we assessed our existing measure
set to ensure that it remains appropriate
for the IPFQR Program, we determined
that measure removal factor two (that is,
measure does not align with current
clinical guidelines or practice) applies
to the Patients Discharged on Multiple
Antipsychotic Medications with
Appropriate Justification (HBIPS–5)
(CBE #560) measure due to the
American Psychiatric Association’s
(APA’s) updated guidelines for patients
with schizophrenia.
We adopted the HBIPS–5 measure in
the FY 2013 IPPS/LTCH PPS final rule
as part of a set with the Patients
Discharged on Multiple Antipsychotic
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Medications (HBIPS–4) (previously
endorsed under CBE #0552) measure
because of the belief that these two
measures would help reduce
unnecessary use of multiple
antipsychotics, which would lead to
better clinical outcomes and reduced
side effects for patients (77 FR 53649
through 53650). We subsequently
removed the HBIPS–4 measure in the
FY 2016 IPF PPS final rule (80 FR 46695
through 46696). As we described in that
final rule, following our adoption of
these measures, some experts, including
the CBE, provided input that the
HBIPS–4 measure did not provide
meaningful information about the
quality of care received by IPF patients.
This led to the removal of the HBIPS–
4 measure’s CBE endorsement in
January 2014. During the CBE’s review
of the HBIPS–4 measure in 2014, the
CBE observed that the HBIPS–4 and
HBIPS–5 measures could be collected
and reported separately and expressed
that the HBIPS–5 measure should be
retained in the IPFQR Program as it
continued to provide meaningful quality
of care information (80 FR 046695
through 46696).
Evidence supporting development
and adoption of the HBIPS–5 measure
included the APA Workgroup on
Schizophrenia’s 2004 Practice Guideline
for the Treatment of Patients with
Schizophrenia. These guidelines stated
that the ‘‘combinations of antipsychotics
. . . should be justified by strong
documentation that the patient is not
equally benefited by monotherapy.’’ 225
In December 2019, the APA Board of
Trustees approved updated guidelines
for treatment of patients with
schizophrenia.226 The updated
guidelines are based on evolving
clinical knowledge and have increased
focus and specificity of
recommendations for the use of
pharmacotherapy; they also underscore
the importance of patient preference
and shared-decision making.227 These
guidelines no longer contain the
recommendation that combinations of
antipsychotics should be justified by
strong documentation that patients are
not equally benefited by monotherapy.
Therefore, the guidelines that originally
supported the HBIPS–5 measure have
changed substantially, and the HBIPS–
225 https://www.researchgate.net/publication/
298561608_Practice_guideline_for_the_treatment_
of_patients_with_schizophrenia_second_edition.
226 https://ajp.psychiatryonline.org/doi/10.1176/
appi.ajp.2020.177901.
227 The American Psychiatric Association.
Practice Guideline for the Treatment of Patients
with Schizophrenia, Third Edition. Available at:
https://psychiatryonline.org/doi/book/10.1176/
appi.books.9780890424841. Accessed on February
15, 2023.
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5 measure is no longer aligned with
current clinical guidelines and practice.
Furthermore, the HBIPS–5 measure is
no longer supported by the measure
steward (that is, The Joint Commission),
who withdrew it from the CBE
endorsement process in 2019. As a
result, the HBIPS–5 measure lost its CBE
endorsement in October 2019.228
Subsequent to this, the CBE-convened
MAP’s discussion of measure set
removal for 2021–2022 included a
discussion of this measure. Because the
HBIPS–5 measure no longer aligns with
clinical guidelines and is no longer CBE
endorsed due to lack of support from
the measure developer, the MAP
recommended that the measure should
be removed from the IPFQR Program.229
We agree with the MAP’s assessment
that the measure no longer aligns with
clinical guidelines and therefore
propose to remove the measure from the
IPFQR Program beginning with FY 2025
payment determination. We note that
data for the FY 2024 payment
determination represents care provided
in CY 2022 and will be reported to CMS
prior to the publication of the FY 2024
IPF PPS final rule; therefore, the FY
2025 payment determination is the first
period for which we can remove this
measure.
We invite comments on our proposal.
ddrumheller on DSK120RN23PROD with PROPOSALS2
b. Proposed Removal of the Tobacco Use
Brief Intervention Provided or Offered
and Tobacco Use Brief Intervention
(TOB–2/2a) for FY 2025 and Subsequent
Years
We adopted the Tobacco Use Brief
Intervention Provided or Offered and
Tobacco Use Brief Intervention (TOB–2/
2a) measure in the FY 2015 IPF PPS
final rule (79 FR 45971 through 45972)
because of our belief that it is important
to address the common comorbidity of
tobacco use among IPF patients. The
TOB–2/2a measure requires IPFs to
chart-abstract measure data on a sample
of IPF patient records, in accordance
with established sampling policies (80
FR 46717 through 46719). When we
introduced the TOB–2/2a measure to
the IPFQR Program, the benefits of this
measure were high because IPF
performance was not consistent with
respect to, and there were no other
measures addressing, provision of
tobacco use cessation counseling or
treatment. At the time, the TOB–2/2a
measure provided a means of
distinguishing IPF performance
regarding, and incentivized facilities to
228 CMS Measures Inventory Tool. Patients
Discharged on multiple antipsychotic medications
with appropriate justification. Available at: https://
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improve rates of, treatment for this
common comorbidity. To further
address tobacco use, we subsequently
adopted the Tobacco Use Treatment
Provided or Offered at Discharge and
Tobacco Use Treatment at Discharge
(TOB–3/3a) measure in the FY 2016 IPF
PPS final rule (80 FR 46696 through
46699).
In the FY 2022 IPF PPS proposed rule,
we proposed to remove the Tobacco Use
Brief Intervention Provided or Offered
and Tobacco Use Brief Intervention
(TOB–2/2a) measure from the IPFQR
Program beginning with the FY 2024
payment determination under our
measure removal factor 8, the costs
associated with a measure outweigh the
benefit of its continued use in the
program (86 FR 19508 through 19509).
We expressed our belief that the quality
improvement benefits from the TOB–2/
2a measure had greatly diminished
because performance had leveled off,
that is overall performance on the
measure was no longer improving. We
took this to mean that most IPFs
routinely offer tobacco use brief
interventions.
In the FY 2022 IPF PPS proposed rule,
we also expressed our belief that the
costs of maintaining this measure are
high because costs are multi-faceted and
include not only the IPFs’ burden
associated with reporting, but also our
costs associated with implementing and
maintaining the measure (86 FR 19508
through 19509). Additionally, we must
expend resources in maintaining
information collection systems,
analyzing reported data, and providing
public reporting of the collected
information. We expressed that, for this
measure, IPF information collection
burden and related costs associated with
reporting this measure to CMS were
high because the measure is a chartabstracted measure. Furthermore, we
observed CMS incurs costs associated
with the program oversight of the
measure for public display.
However, in the FY 2022 IPF PPS
final rule, we did not finalize our
proposal to remove the Tobacco Use
Brief Intervention Provided or Offered
and Tobacco Use Brief Intervention
(TOB–2/2a) measure (86 FR 42648
through 42651). We stated that,
following review of the public
comments we received, we believed the
benefits of continuing to encourage
facilities to offer tobacco use brief
interventions were greater than we had
estimated. We noted that these benefits
included the potential for IPFs to
continue improving performance on the
TOB–2/2a measure, the importance of
tobacco use interventions due to
increased tobacco use during the
COVID–19 pandemic, and this
measure’s potential influence on other
quality improvement activities related
to tobacco use.
In our continual evaluation of the
IPFQR Program measure set under our
Meaningful Measures Framework and
according to our measure removal and
retention factors, we observed that
having two measures addressing tobacco
use, which are both associated with
relatively high information collection
burden, may not appropriately balance
costs and benefits within the program.
While we believe that both the TOB–2/
2a measure and the TOB–3/3a measure
address clinically important
interventions to address smoking in this
population, we believe that the overall
cost associated with retaining both of
these measures outweighs the benefit of
having two measures to address
treatment for the same comorbidity
among the same patient population.
Both measures capture information
about tobacco cessation counseling and
FDA-approved tobacco cessation
medications. The difference between the
measures is that the TOB–2/2a measure
captures whether the tobacco cessation
counseling and FDA-approved tobacco
cessation medications were offered or
refused during the inpatient stay, while
the TOB–3/3a measure captures
whether a referral to outpatient tobacco
cessation counseling and FDA-approved
tobacco cessation medications were
offered or refused at the time of the
patient’s discharge.
As we considered each of these
measures, we determined that it would
be more appropriate to retain the TOB–
3/3a measure in the IPFQR Program,
that is, to propose to remove the TOB–
2/2a measure instead of the TOB–3/3a
measure, because there is more
opportunity for improvement on the
TOB–3/3a measure. Specifically, the
performance on the TOB–3/3a measure
is lower than performance on the TOB–
2/2a measure. National performance on
TOB–2 and 2a measure and TOB–3 and
3a measure for the last five payment
determination years in the IPFQR
Program is presented in Table 19. Given
the relatively high performance on the
TOB–2/2a measure compared to the
TOB–3/3a measure, we believe that
retaining the TOB–3/3a measure, and
cmit.cms.gov/cmit/#/
MeasureView?variantId=1141§ionNumber=1.
229 MAP 2021–2022 Considerations for
Implementing Measures in Federal Programs.
Available at: https://mmshub.cms.gov/sites/default/
files/map_2021-2022_considerations_for_
implementing_measures_in_federal_programs_
final_report.pdf.
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removing the TOB–2/2a measure, would
provide more opportunity to drive
improvement among IPFs; therefore,
would potentially impact more patients.
TABLE 19—NATIONAL PERFORMANCE ON TOB–2 AND TOB–2A AND TOB–3 AND TOB–3A FROM CY 2017 THROUGH CY
2022
TOB–2
performance
(%)
Payment determination year
FY
FY
FY
FY
FY
2019
2020
2021
2022
2023
...........................................................................................................
...........................................................................................................
...........................................................................................................
...........................................................................................................
...........................................................................................................
As described earlier in this section
V.F.2.b of this proposed rule, because
the TOB–2/2a measure has a high cost
(especially due to its high information
collection burden), we believe that these
high costs are no longer greater than the
benefits of retaining this measure.
Therefore, we believe measure removal
factor 8 (that is, the costs associated
with a measure outweigh the benefit of
its continued use in the IPFQR
Program), applies to the TOB–2/2a
measure.
Furthermore, the TOB–2/2a measure
is no longer supported by the measure
steward (that is, the Joint Commission),
who withdrew it from the CBE
endorsement process in 2018. Therefore,
the TOB–2/2a measure has not been
CBE endorsed since October 2018.230
Subsequent to this, the CBE-convened
MAP’s discussion of measure set
TOB–2a
performance
(%)
79.7
81.0
82.0
80.4
72.2
removal for 2021and 2022 included a
discussion of this measure. Because the
TOB–2/2a measure is a high-cost
measure and is no longer CBE endorsed,
the MAP recommended that we remove
the measure from the IPFQR Program.231
We agree with the MAP that this is a
high-cost measure. Furthermore, we
recognize that it is similar to the other
tobacco use measure in the IPFQR
Program measure set (that is, the TOB–
3/3a measure) which we do not propose
to remove. Therefore, we propose to
remove Tobacco Use Brief Intervention
Provided or Offered and Tobacco Use
Brief Intervention (TOB–2/2a) measure
under our measure removal factor 8,
‘‘the costs associated with a measure
outweigh the benefit of its continued
use in the program,’’ beginning with FY
2025 payment determination. We note
that data for the FY 2024 payment
44.9
46.2
46.8
44.9
39.0
TOB–3
performance
(%)
TOB–3a
performance
(%)
54.1
57.5
59.9
60.7
57.4
15.0
17.8
21.6
21.7
18.3
determination represents care provided
in CY 2022 and will be reported to CMS
prior to the publication of the FY 2024
IPF PPS final rule; therefore, the FY
2025 payment determination is the first
period for which we can remove this
measure.
We welcome public comment on this
proposal.
G. Summary of IPFQR Program
Measures
1. IPFQR Program Measures for the FY
2024 Payment Determination
We do not propose any changes to our
measure set for the FY 2024 payment
determination. The 14 measures which
will be in the program for FY 2024
payment determination are shown in
Table 20.
ddrumheller on DSK120RN23PROD with PROPOSALS2
TABLE 20—IPFQR PROGRAM MEASURE SET FOR THE FY 2024 PAYMENT DETERMINATION
CBE No.
Measure ID
Measure
0640 ..............
0641 ..............
0560 * ............
N/A ................
N/A * ..............
N/A * ..............
HBIPS–2 .............................
HBIPS–3 .............................
HBIPS–5 .............................
FAPH ..................................
SUB–2 and SUB–2a ..........
SUB–3 and SUB–3a ..........
N/A * ..............
N/A * ..............
TOB–2 and TOB–2a ..........
TOB–3 and TOB–3a ..........
1659 ..............
N/A * ..............
IMM–2 ................................
N/A .....................................
N/A ................
2860 ..............
N/A .....................................
N/A .....................................
3205 ..............
Med Cont. ...........................
Hours of Physical Restraint Use.
Hours of Seclusion Use.
Patients Discharged on Multiple Antipsychotic Medications with Appropriate Justification.
Follow-Up After Psychiatric Hospitalization.
Alcohol Use Brief Intervention Provided or Offered and SUB–2a Alcohol Use Brief Intervention.
Alcohol and Other Drug Use Disorder Treatment Provided or Offered at Discharge and SUB–3a
Alcohol and Other Drug Use Disorder Treatment at Discharge.
Tobacco Use Treatment Provided or Offered and TOB–2a Tobacco Use Treatment.
Tobacco Use Treatment Provided or Offered at Discharge and TOB–3a Tobacco Use Treatment
at Discharge.
Influenza Immunization.
Transition Record with Specified Elements Received by Discharged Patients (Discharges from an
Inpatient Facility to Home/Self Care or Any Other Site of Care).
Screening for Metabolic Disorders.
Thirty-Day All-Cause Unplanned Readmission Following Psychiatric Hospitalization in an Inpatient
Psychiatric Facility.
Medication Continuation Following Inpatient Psychiatric Discharge.
230 CMS Measures Inventory Tool. Tobacco Use
Treatment Provided or Offered. Available at:
https://cmit.cms.gov/cmit/#/
MeasureView?variantId=1818§ionNumber=1.
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231 MAP 2021–2022 Considerations for
Implementing Measures in Federal Programs.
Available at: https://mmshub.cms.gov/sites/default/
files/map_2021-2022_considerations_for_
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TABLE 20—IPFQR PROGRAM MEASURE SET FOR THE FY 2024 PAYMENT DETERMINATION—Continued
CBE No.
Measure ID
Measure
3636 ..............
N/A .....................................
COVID–19 Healthcare Personnel (HCP) Vaccination Measure.
* Measure is no longer endorsed by the CBE but was endorsed at the time of adoption. We note that although section 1886(s)(4)(D)(i) of the
Act generally requires measures specified by the Secretary be endorsed by the entity with a contract under section be endorsed by the entity
with a contract under section 1890(a) of the Act, section 1886(s)(4)(D)(ii) states that in the case of a specified area or medical topic determined
appropriate by the Secretary for which a feasible and practical measure has not been endorsed by the entity with a contract under section
1890(a) of the Act, the Secretary may specify a measure that is not so endorsed as long as due consideration is given to measures that have
been endorsed or adopted by a consensus organization identified by the Secretary. We attempted to find available measures for each of these
clinical topics that have been endorsed or adopted by a consensus organization and found no other feasible and practical measures on the topics for the IPF setting.
2. IPFQR Program Measures for the FY
2025 Payment Determination
In this proposed rule, we propose to
remove two measures for the FY 2025
payment determination and subsequent
years. We also propose to modify one
measure for the FY 2025 payment
determination and subsequent years.
The 12 measures, which would be in the
program for FY 2025 payment
determination if we finalize these
proposals, are shown Table 21.
TABLE 21—IPFQR PROGRAM MEASURE SET FOR THE FY 2025 PAYMENT DETERMINATION IF PROPOSALS TO MODIFY
AND REMOVE MEASURES ARE FINALIZED
CBE No.
Measure ID
Measure
0640 ..............
0641 ..............
N/A ................
1659 ..............
N/A * ..............
N/A * ..............
HBIPS–2 .............................
HBIPS–3 .............................
FAPH ..................................
IMM–2 ................................
SUB–2 and SUB–2a ..........
SUB–3 and SUB–3a ..........
N/A * ..............
TOB–3 and TOB–3a ..........
N/A * ..............
N/A .....................................
N/A ................
2860 ..............
N/A .....................................
N/A .....................................
3205 ..............
N/A ................
Med Cont. ...........................
N/A .....................................
Hours of Physical Restraint Use.
Hours of Seclusion Use.
Follow-Up After Psychiatric Hospitalization.
Influenza Immunization.
Alcohol Use Brief Intervention Provided or Offered and SUB–2a Alcohol Use Brief Intervention.
Alcohol and Other Drug Use Disorder Treatment Provided or Offered at Discharge and SUB–3a
Alcohol and Other Drug Use Disorder Treatment at Discharge.
Tobacco Use Treatment Provided or Offered at Discharge and TOB–3a Tobacco Use Treatment
at Discharge.
Transition Record with Specified Elements Received by Discharged Patients (Discharges from an
Inpatient Facility to Home/Self Care or Any Other Site of Care).
Screening for Metabolic Disorders.
Thirty-Day All-Cause Unplanned Readmission Following Psychiatric Hospitalization in an Inpatient
Psychiatric Facility.
Medication Continuation Following Inpatient Psychiatric Discharge.
Modified COVID–19 Vaccination Coverage Among Healthcare Personnel (HCP)1.
* Measure is no longer endorsed by the CBE but was endorsed at the time of adoption. We note that although section 1886(s)(4)(D)(i) of the
Act generally requires measures specified by the Secretary be endorsed by the entity with a contract under section 1890(a) of the Act, section
1886(s)(4)(D)(ii) states that in the case of a specified area or medical topic determined appropriate by the Secretary for which a feasible and
practical measure has not been endorsed by the entity with a contract under section 1890(a) of the Act, the Secretary may specify a measure
that is not so endorsed as long as due consideration is given to measures that have been endorsed or adopted by a consensus organization
identified by the Secretary. We attempted to find available measures for each of these clinical topics that have been endorsed or adopted by a
consensus organization and found no other feasible and practical measures on the topics for the IPF setting.
1 We have proposed updates to the COVID–19 HCP measure in section V.E. of this proposed rule.
3. IPFQR Program Measures for the FY
2026 Payment Determination
If we finalize our proposals for the FY
2026 payment determination and
subsequent years, the measure set
would include 13 required and two
voluntary measures. This includes the
12 required measures discussed in
section V.G.2 of this proposed rule for
the FY 2025 payment determination and
subsequent years, as well as the one
required measure and two voluntary
measures we proposed for the FY 2026
payment determination and subsequent
years. The measures which would be in
the program for FY 2026 payment
determination if we finalize these four
proposals are shown Table 22.
TABLE 22—IPFQR PROGRAM MEASURE SET FOR THE FY 2026 PAYMENT DETERMINATION IF PROPOSALS TO ADOPT
NEW REQUIRED AND VOLUNTARY MEASURES ARE FINALIZED
ddrumheller on DSK120RN23PROD with PROPOSALS2
CBE No.
Measure ID
Measure
Required Measures
0640 ..............
0641 ..............
N/A ................
1659 ..............
N/A * ..............
N/A * ..............
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HBIPS–2 .............................
HBIPS–3 .............................
FAPH ..................................
IMM–2 ................................
SUB–2 and SUB–2a ..........
SUB–3 and SUB–3a ..........
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Hours of Physical Restraint Use.
Hours of Seclusion Use.
Follow-Up After Psychiatric Hospitalization.
Influenza Immunization.
Alcohol Use Brief Intervention Provided or Offered and SUB–2a Alcohol Use Brief Intervention.
Alcohol and Other Drug Use Disorder Treatment Provided or Offered at Discharge and SUB–3a
Alcohol and Other Drug Use Disorder Treatment at Discharge.
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TABLE 22—IPFQR PROGRAM MEASURE SET FOR THE FY 2026 PAYMENT DETERMINATION IF PROPOSALS TO ADOPT
NEW REQUIRED AND VOLUNTARY MEASURES ARE FINALIZED—Continued
CBE No.
Measure ID
Measure
N/A * ..............
TOB–3 and TOB–3a ..........
N/A * ..............
N/A .....................................
N/A ................
2860 ..............
N/A .....................................
N/A .....................................
3205 ..............
N/A ................
N/A ................
Med Cont. ...........................
N/A .....................................
Facility Commitment. ..........
Tobacco Use Treatment Provided or Offered at Discharge and TOB–3a Tobacco Use Treatment
at Discharge.
Transition Record with Specified Elements Received by Discharged Patients (Discharges from an
Inpatient Facility to Home/Self Care or Any Other Site of Care).
Screening for Metabolic Disorders.
Thirty-Day All-Cause Unplanned Readmission Following Psychiatric Hospitalization in an Inpatient
Psychiatric Facility.
Medication Continuation Following Inpatient Psychiatric Discharge.
Modified COVID–19 Vaccination Coverage Among Healthcare Personnel (HCP).1
Facility Commitment to Health Equity.2
Voluntary Measures
N/A ................
N/A ................
Screening for SDOH ..........
Screen Positive ..................
Screening for Social Drivers of Health.3
Screen Positive Rate for Social Drivers of Health.4
* Measure is no longer endorsed by the CBE but was endorsed at time of adoption. We note that although section 1886(s)(4)(D)(i) of the Act
generally requires measures specified by the Secretary be endorsed by the entity with a contract under section 1890(a) of the Act, section
1886(s)(4)(D)(ii) states that in the case of a specified area or medical topic determined appropriate by the Secretary for which a feasible and
practical measure has not been endorsed by the entity with a contract under section 1890(a) of the Act, the Secretary may specify a measure
that is not so endorsed as long as due consideration is given to measures that have been endorsed or adopted by a consensus organization
identified by the Secretary. We attempted to find available measures for each of these clinical topics that have been endorsed or adopted by a
consensus organization and found no other feasible and practical measures on the topics for the IPF setting.
1 We have proposed updates to the COVID–HCP measure in section V.E. of this proposed rule.
2 We have proposed adoption of the Facility Commitment measure in section V.D.2. of this proposed rule.
3 We have proposed voluntary reporting of the Screening for SDOH measure in section V.D.3. of this proposed rule.
4 We have proposed voluntary reporting of the Screen Positive Rate for SDOH measure in section V.D.4 of this proposed rule.
4. IPFQR Program Measures for the FY
2027 IPFQR Program’s Payment
Determination
If we finalize our proposals for the FY
2027 payment determination and
subsequent years, the measure set
would include 15 required measures
and one voluntary measure. This
includes the 13 required measures
discussed in section V.G.3 of this
proposed rule for the FY 2026 payment
determination and subsequent years, as
well as the two measures which we
proposed to require for the FY 2027
payment determination and subsequent
years. It also includes the one new
voluntary measure proposed in section
V.D.5. of this proposed rule. The
measures which would be in the
program for the FY 2027 payment
determination and subsequent years if
we finalize these proposals are shown
Table 23.
TABLE 23—IPFQR PROGRAM MEASURE SET FOR THE FY 2027 PAYMENT DETERMINATION IF PROPOSALS TO ADOPT
NEW REQUIRED AND VOLUNTARY MEASURES ARE FINALIZED
CBE No.
Measure ID
Measure
ddrumheller on DSK120RN23PROD with PROPOSALS2
Required Measures
0640 ..............
0641 ..............
N/A ................
1659 ..............
N/A * ..............
N/A * ..............
HBIPS–2 .............................
HBIPS–3 .............................
FAPH ..................................
IMM–2 ................................
SUB–2 and SUB–2a ..........
SUB–3 and SUB–3a ..........
N/A * ..............
TOB–3 and TOB–3a ..........
N/A * ..............
N/A .....................................
N/A ................
2860 ..............
N/A .....................................
N/A .....................................
3205 ..............
N/A ................
N/A ................
N/A ................
N/A ................
Med Cont ............................
N/A .....................................
Facility Commitment ...........
Screening for SDOH ..........
Screen Positive ..................
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Hours of Physical Restraint Use.
Hours of Seclusion Use.
Follow-Up After Psychiatric Hospitalization.
Influenza Immunization.
Alcohol Use Brief Intervention Provided or Offered and SUB–2a Alcohol Use Brief Intervention.
Alcohol and Other Drug Use Disorder Treatment Provided or Offered at Discharge and SUB–3a
Alcohol and Other Drug Use Disorder Treatment at Discharge.
Tobacco Use Treatment Provided or Offered at Discharge and TOB–3a Tobacco Use Treatment
at Discharge.
Transition Record with Specified Elements Received by Discharged Patients (Discharges from an
Inpatient Facility to Home/Self Care or Any Other Site of Care).
Screening for Metabolic Disorders.
Thirty-Day All-Cause Unplanned Readmission Following Psychiatric Hospitalization in an Inpatient
Psychiatric Facility.
Medication Continuation Following Inpatient Psychiatric Discharge.
Modified COVID–19 Vaccination Coverage Among Healthcare Personnel (HCP).1
Facility Commitment to Health Equity.2
Screening for Social Drivers of Health.3
Screen Positive Rate for Social Drivers of Health.4
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TABLE 23—IPFQR PROGRAM MEASURE SET FOR THE FY 2027 PAYMENT DETERMINATION IF PROPOSALS TO ADOPT
NEW REQUIRED AND VOLUNTARY MEASURES ARE FINALIZED—Continued
CBE No.
Measure ID
Measure
Voluntary Measure
N/A ................
PIX ......................................
Psychiatric Inpatient Experience Survey.5
* Measure is no longer endorsed by the CBE but was endorsed at time of adoption. Although section 1886(s)(4)(D)(i) of the Act generally requires that any measures specified by the Secretary shall be endorsed by the entity with a contract under section 1890(a) of the Act, section
1886(s)(4)(D)(ii) states that in the case of a specified area or medical topic determined appropriate by the Secretary for which a feasible and
practical measure has not been endorsed by the entity with a contract under section 1890(a) of the Act, the Secretary may specify a measure
that is not so endorsed as long as due consideration is given to measures that have been endorsed or adopted by a consensus organization
identified by the Secretary. We attempted to find available measures for each of these clinical topics that have been endorsed or adopted by a
consensus organization and found no other feasible and practical measures on the topics for the IPF setting.
1 We have proposed updates to the COVID–HCP measure in Section V.E. of this proposed rule.
2 We have proposed adoption of the Facility Commitment measure in section V.D.2. of this proposed rule.
3 We have proposed adoption of the Screening for SDOH measure in section V.D.3. of this proposed rule.
4 We have proposed adoption of the Screen Positive measure in section V.D.4. of this proposed rule.
5 We have proposed voluntary reporting of the Psychiatric Inpatient Experience measure in section V.D.5. of this proposed rule.
5. IPFQR Program Measures for the FY
2028 Payment Determination
If we finalize our proposals for the FY
2028 payment determination and
subsequent years, the measure set
would include 16 required measures.
This includes the 15 required measures
discussed in section V.G.4 and V.G.5 of
this proposed rule for the FY 2027
payment determination as well as the
measure which we proposed to require
beginning with the FY 2028 payment
determination. The measures which
would be in the program beginning with
the FY 2028 payment determination if
we finalize these proposals are shown
Table 24.
ddrumheller on DSK120RN23PROD with PROPOSALS2
TABLE 24—IPFQR PROGRAM MEASURE SET FOR THE FY 2029 PAYMENT DETERMINATION IF PROPOSALS TO ADOPT
NEW REQUIRED AND VOLUNTARY MEASURES ARE FINALIZED
CBE No.
Measure ID
Measure
0640 ..............
0641 ..............
N/A ................
1659 ..............
N/A* ..............
N/A* ..............
HBIPS–2 .............................
HBIPS–3 .............................
FAPH ..................................
IMM–2 ................................
SUB–2 and SUB–2a ..........
SUB–3 and SUB–3a ..........
N/A* ..............
TOB–3 and TOB–3a ..........
N/A* ..............
N/A .....................................
N/A ................
2860 ..............
N/A .....................................
N/A .....................................
3205 ..............
N/A ................
N/A ................
N/A ................
N/A ................
N/A ................
Med Cont ............................
N/A .....................................
Facility Commitment ...........
Screening for SDOH ..........
Screen Positive ..................
PIX ......................................
Hours of Physical Restraint Use.
Hours of Seclusion Use.
Follow-Up After Psychiatric Hospitalization.
Influenza Immunization.
Alcohol Use Brief Intervention Provided or Offered and SUB–2a Alcohol Use Brief Intervention.
Alcohol and Other Drug Use Disorder Treatment Provided or Offered at Discharge and SUB–3a
Alcohol and Other Drug Use Disorder Treatment at Discharge.
Tobacco Use Treatment Provided or Offered at Discharge and TOB–3a Tobacco Use Treatment
at Discharge.
Transition Record with Specified Elements Received by Discharged Patients (Discharges from an
Inpatient Facility to Home/Self Care or Any Other Site of Care).
Screening for Metabolic Disorders.
Thirty-Day All-Cause Unplanned Readmission Following Psychiatric Hospitalization in an Inpatient
Psychiatric Facility.
Medication Continuation Following Inpatient Psychiatric Discharge.
Modified COVID–19 Vaccination Coverage Among Healthcare Personnel (HCP).1
Facility Commitment to Health Equity.2
Screening for Social Drivers of Health.3
Screen Positive Rate for Social Drivers of Health.4
Psychiatric Inpatient Experience Survey.5
* Measure is no longer endorsed by the CBE but was endorsed at time of adoption. Although section 1886(s)(4)(D)(i) of the Act generally requires that any measures specified by the Secretary shall be endorsed by the entity with a contract under section 1890(a) of the Act, section
1886(s)(4)(D)(ii) states that in the case of a specified area or medical topic determined appropriate by the Secretary for which a feasible and
practical measure has not been endorsed by the entity with a contract under section 1890(a) of the Act, the Secretary may specify a measure
that is not so endorsed as long as due consideration is given to measures that have been endorsed or adopted by a consensus organization
identified by the Secretary. We attempted to find available measures for each of these clinical topics that have been endorsed or adopted by a
consensus organization and found no other feasible and practical measures on the topics for the IPF setting.
1 We have proposed updates to the COVID–HCP measure in Section V.E. of this proposed rule.
2 We have proposed adoption of the Facility Commitment measure in section V.D.2. of this proposed rule.
3 We have proposed adoption of the Screening for SDOH measure in section V.D.3. of this proposed rule.
4 We have proposed adoption of the Screen Positive measure in section V.D.4. of this proposed rule.
5 We have proposed required reporting of the Psychiatric Inpatient Experience measure in section V.D.5. of this proposed rule.
H. Public Display and Review
Requirements
In the FY 2013 IPPS/LTCH PPS final
rule (77 FR 53653 through 53654), we
adopted procedures for making data
submitted under the IPFQR Program
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available to the public, after an IPF has
the opportunity to review such data
prior to public display, as required by
section 1886(s)(4)(E) of the Act. We
adopted modifications to these
procedural requirements in the FY 2014
IPPS/LTCH PPS final rule (78 FR 50897
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through 50898), and the FY 2017 IPPS/
LTCH PPS final rule (81 FR 57248
through 57249).
Specifically, the IPFQR Program
adopted a policy to provide IPFs a 30day period to review their data, and
submit corrections to errors resulting
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from CMS calculations, prior to public
display on a CMS website. The IPFQR
Program notifies IPFs of the exact
timeframes for this preview period and
public display through subregulatory
guidance. We do not propose any
changes to these requirements.
We propose to codify the procedural
requirements for public reporting of
IPFQR Program data at § 412.433(g). If
finalized, paragraph (g) would provide
that IPFs will have a period of 30 days
to review data on quality measures that
CMS received under the IPFQR
Program, and submit corrections to
errors resulting from CMS calculations,
prior to CMS publishing this data on a
CMS website.
We welcome comments on our
proposals to codify these policies.
I. Form, Manner, and Timing of Quality
Data Submission for the FY 2024
Payment Determination and Subsequent
Years
Procedural Requirements for the FY
2024 Payment Determination and
Subsequent Years
ddrumheller on DSK120RN23PROD with PROPOSALS2
We refer readers to the FY 2013 IPPS/
LTCH PPS final rule (77 FR 53654
through 53655), the FY 2014 IPPS/LTCH
PPS final rule (78 FR 50898 through
50899), the FY 2018 IPPS/LTCH PPS
final rule (82 FR 38471 through 38472),
and the FY 2022 IPF PPS final rule (86
FR 42656 through 42657) for our
previously finalized procedural
requirements for participation in, and
withdrawal from, the IPFQR Program, as
well as data submission requirements.
We do not propose any changes to our
previously finalized procedural
requirements.
We propose to codify these
procedural requirements for
participation in the IPFQR Program at
§ 412.433(b) through (d). If finalized,
paragraphs (b) through (d) would set
forth the procedural requirements for an
IPF to register for, or withdraw from,
participation in the IPFQR Program and
to submit the required data on measures
in a form and manner and time
specified by CMS.
We welcome comments on our
proposal to codify these policies.
2. Data Submission Requirements for
the FY 2025 Payment Determination
and Subsequent Years
We refer readers to the FY 2013 IPPS/
LTCH PPS final rule (77 FR 53655
through 53657), the FY 2014 IPPS/LTCH
PPS final rule (78 FR 50899 through
50900), the FY 2018 IPPS/LTCH PPS
final rule (82 FR 38472 through 38473),
and the FY 2022 IPF PPS final rule (86
FR 42657 through 42661) for our
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previously finalized data submission
requirements.
The measure we propose to modify
beginning with the FY 2025 payment
determination—the COVID–19
Vaccination Coverage Among HCP
measure—requires facilities to report
data on the number of HCP who have
received a complete vaccination course
of a COVID–19 vaccine through the
Centers for Disease Control and
Prevention’s (CDC’s) National
Healthcare Safety Network (NHSN). We
propose to update this measure to no
longer refer to ‘‘complete vaccination
course’’ but instead to refer to ‘‘up-todate’’ vaccination, as described in
section V.E. of this proposed rule.
We do not propose any updates to the
form, manner, and timing of data
submission for the COVID–19
Vaccination Coverage Among HCP
measure and refer readers to the FY
2022 IPF PPS final rule (86 FR 42657)
for these policies.
3. Data Submission Requirements for
the FY 2026 Payment Determination
and Subsequent Years
In sections V.D 3 and V.D.4 of this
proposed rule, we propose to adopt
measures for voluntary reporting for the
FY 2026 IPFQR Program and required
reporting for the FY 2027 IPFQR
Program’s payment determination and
subsequent years. These measures are
the Screening for Social Drivers of
Health measure and Screen Positive
Rate for Social Drivers of Health
measure. We propose that our
previously finalized data submission
requirements, specifically, our
previously finalized data submission
requirements for aggregate data
reporting described in the FY 2018
IPPS/LTCH PPS final rule (82 FR 38472
through 38473) would apply to these
measures.
We invite public comment on this
proposal.
4. Data Submission Requirements for
the FY 2027 Payment Determination
and Subsequent Years
In section V.D.5. of this proposed
rule, we are proposing to adopt one
patient-reported measure, Psychiatric
Inpatient Experience (PIX) measure for
voluntary reporting beginning in the FY
2027 program year and required
reporting beginning with the FY 2028
payment determination. Because, unlike
other patient experience of care
measures, this measure is collected by
facilities prior to discharge, we are
proposing that facilities would report
these data using the patient-level data
reporting described in the FY 2022 IPF
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PPS final rule (86 FR 42658 through
42661).
5. Proposed Data Validation Pilot
Beginning With Data Submitted in 2025
As discussed in the FY 2019 IPF PPS
final rule (83 FR 28607) and in the FY
2022 IPF PPS final rule (86 FR 42661),
we are concerned that the ability to
detect error is lower for aggregate
measure data reporting than for patientlevel data reporting (that is, data
regarding each patient included in a
measure and, for example, whether the
patient was included in the numerator
and denominator of the measure). In the
FY 2022 IPF PPS final rule, we noted
that adoption of patient-level data
requirements would enable us to adopt
a data validation policy for the IPFQR
Program in the future (86 FR 42661). We
believe that it would be appropriate to
develop such a policy incrementally
through adoption of a data validation
pilot prior to national implementation
of data validation within the IPFQR
Program. We sought public input on a
potential data validation pilot, and
many commenters supported the
concept of data validation following
implementation of patient-level
reporting (86 FR 42661). In the FY 2022
IPF PPS final rule, we adopted required
patient-level reporting beginning with
data submitted in CY 2023 affecting the
FY 2024 payment determination and
reflecting care provided during CY 2022
(86 FR 42658 through 42661).
We now propose a data validation
pilot beginning with data submitted in
CY 2024 (reflecting care provided
during CY 2023). When we sought
public comment on a data validation
pilot in the FY 2022 IPF PPS proposed
rule (86 FR 19515), we requested input
on potential elements of such a pilot,
including the number of measures and
the number of participating IPFs. As
summarized in the FY 2022 IPF PPS
final rule (86 FR 42661), one commenter
recommended selecting two measures
and 200 IPFs for this pilot. We
considered that recommendation;
however, to align with validation
policies in our other quality reporting
programs, we decided to request a
specific number of charts. Specifically,
we are proposing to request eight charts
per quarter from each IPF as opposed to
requesting all of the charts that each
facility used to calculate one or more
specific measures. We also decided to
initiate our pilot with fewer IPFs than
the commenter recommended to limit
the burden associated with this pilot.
We also reviewed the validation
policies of other quality reporting
programs. We specifically reviewed the
Hospital IQR Program’s chart-abstracted
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ddrumheller on DSK120RN23PROD with PROPOSALS2
measure validation policies described in
the FY 2017 IPPS/LTCH PPS final rule
(81 FR 57179 through 57180), the
Hospital IQR Program’s pilot for eCQM
validation described in the FY 2015
IPPS/LTCH PPS final rule (79 FR 50262
through 50273), the Hospital Outpatient
Quality Reporting (OQR) Program’s
planned pilot of data validation as
described in the CY 2009 OPPS/ASC
final rule (73 FR 68502), and the
Hospital OQR Program’s finalized
validation policies as described in the
CY 2012 OPPS/ASC final rule (76 FR
74485) and the CY 2018 OPPS/ASC
final rule (82 FR 59441 through 5944)
because these programs are also pay-forreporting programs, like the IPFQR
Program.
Following our review of the
validation policies within these
programs, we propose a validation pilot
in which we would randomly select on
an annual basis up to 100 IPFs and
request each selected IPF to provide to
CMS eight charts per quarter, a total of
32 charts per year, used to calculate all
chart-based measures beginning with
data submitted in CY 2025. We believe
that randomly selecting up to 100 IPFs
would provide a sufficiently large set of
IPFs to meaningfully test our validation
procedures while minimizing burden
for IPFs. We would specify the timeline
and mechanism for submitting data in
our data requests to individual IPFs that
have been selected to participate in the
validation pilot. We note that consistent
with the Hospital IQR Program, we
would reimburse IPFs for the cost of
submitting charts for validation at a rate
of $3.00 per chart (85 FR 58949).
Because this is a voluntary pilot, we
recognize that some selected IPFs would
not participate; however, we believe
that this pilot would be beneficial for
IPFs that do participate as an
opportunity to receive education and
feedback on the data they submit prior
to future proposal and adoption of a
validation requirement in the IPFQR
Program.
We invite comment on our proposal.
6. Quality Measure Sampling
Requirements
We refer readers to the FY 2013 IPPS/
LTCH PPS final rule (77 FR 53657
through 53658), the FY 2014 IPPS/LTCH
PPS final rule (78 FR 50901 through
50902), the FY 2016 IPF PPS final rule
(80 FR 46717 through 46719), and the
FY 2019 IPF PPS final rule (83 FR 38607
through 38608) for discussions of our
previously finalized sampling policies.
Because the Facility Commitment to
Health Equity measure proposed in
section V.D.2 of this proposed rule is a
structural attestation measure, these
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policies would not apply to that
measure. Additionally, because the
Screening for Social Drivers of Health
measure (described in section V.D.3 of
this proposed rule) would apply to all
patients and the Screen Positive Rate for
Social Drivers of Health measure
(described in section V.D.4 of this
proposed rule) would apply to all
patients who had been screened for
health-related social needs (HRSNs), our
previously finalized sampling policies
would not apply to these two measures.
As described in the FY 2022 IPF PPS
final rule, our sampling policies do not
apply to the COVID–19 Vaccination
Coverage Among Healthcare Personnel
measure because the denominator is all
healthcare personnel (86 FR 42661).
Generally, we have applied our
sampling procedures to chart-abstracted
measures, where appropriate (that is,
where the measure does not require
application to the entire patient
population). However, because the PIX
survey measure is a patient reported
measure, we have considered whether
our sampling procedures for chartabstracted measures are appropriate for
this measure. After consideration of our
current sampling procedures and
sampling for patient reported measures
in other quality reporting programs
(specifically, the requirements for
reporting the HCAHPS measure), we are
proposing that the PIX survey measure
(described in section V.D.5 of this
proposed rule) would be eligible for
sampling but would not be included in
the global sample. Instead, we are
proposing that sampling for this
measure would align with sampling for
the HCAHPS survey measure in acute
care hospitals and the Hospital IQR
Program as described in the HCAHPS
Quality Assurance Guidelines.232
Specifically, we are proposing to require
IPFs to develop sampling plans that
ensure that IPFs are able to submit data
for 300 completed PIX surveys per year.
IPFs would be required to sample from
every month throughout the entire
reporting period and not stop sampling
or curtail ongoing interview activities
once a certain number of completed
surveys has been attained. IPFs that are
unable to reach 300 completed surveys
through sampling would be required to
submit data on survey results for all
eligible patient discharges.
We invite public comment on our
proposal.
232 HCHAPS Quality Assurance Guidelines,
Version 17.0. March 2022. Available at: https://
hcahpsonline.org/globalassets/hcahps/qualityassurance/2022_qag_v17.0.pdf.
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7. Non-Measure Data Collection
We refer readers to the FY 2015 IPF
PPS final rule (79 FR 45973), the FY
2016 IPF PPS final rule (80 FR 46717),
and the FY 2019 IPF PPS final rule (83
FR 38608) for our previously finalized
non-measure data collection policies.
We do not propose any changes to these
policies.
8. Accuracy and Completeness
Acknowledgement (DACA)
Requirements
We refer readers to the FY 2013 IPPS/
LTCH PPS final rule (77 FR 53658) for
our previously finalized DACA
requirements. We do not propose any
changes to these policies.
J. Reconsideration and Appeals
Procedures
We refer readers to 42 CFR 412.434
for the IPFQR Program’s reconsideration
and appeals procedures. We do not
propose any changes to these policies.
K. Extraordinary Circumstances
Exceptions (ECE) Policy
We refer readers to the FY 2013 IPPS/
LTCH PPS final rule (77 FR 53659
through 53660), the FY 2014 IPPS/LTCH
PPS final rule (78 FR 50903), the FY
2015 IPF PPS final rule (79 FR 45978),
and the FY 2018 IPPS/LTCH PPS final
rule (82 FR 38473 through 38474) for
our previously finalized Extraordinary
Circumstances Exceptions policies. We
do not propose any changes to these
policies.
We propose to codify the ECE policies
at § 412.433(f). If finalized, paragraph (f)
would provide that we may grant an
exception to one or more data
submission deadlines and requirements
in the event of extraordinary
circumstances beyond the control of the
IPF either in response to a request by
the IPF or at our discretion if we
determine an extraordinary
circumstance occurred.
We welcome comments on our
proposal to codify these policies.
VI. Collection of Information
Requirements
Under the Paperwork Reduction Act
of 1995 (PRA) (44 U.S.C. 3501 et seq.),
we are required to provide 60-day notice
in the Federal Register and solicit
public comment before a ‘‘collection of
information’’ requirement is submitted
to the Office of Management and Budget
(OMB) for review and approval. For the
purposes of the PRA and this section of
the preamble, collection of information
is defined under 5 CFR 1320.3(c) of the
PRA’s implementing regulations.
To fairly evaluate whether an
information collection should be
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approved by OMB, section 3506(c)(2)(A)
of the Paperwork Reduction Act of 1995
requires that we solicit comment on the
following issues:
• The need for the information
collection and its usefulness in carrying
out the proper functions of our agency.
• The accuracy of our estimate of the
information collection burden.
• The quality, utility, and clarity of
the information to be collected.
• Recommendations to minimize the
information collection burden on the
affected public, including automated
collection techniques.
We are soliciting public comment (see
section VI.C of this proposed rule) on
each of these issues for the following
sections of this document that contain
information collection requirements.
Comments, if received, will be
responded to within the subsequent
final rule.
A. Wage Estimates
To derive average costs, we used data
from the U.S. Bureau of Labor Statistics’
(BLS’) May 202/1 National Occupational
Employment and Wage Estimates for all
salary estimates (https://www.bls.gov/
oes/current/oes_nat.htm). In this regard,
Table 25 presents BLS’ mean hourly
wage for Medical Records and Health
Information Technicians (the
occupation title that we have estimated
is appropriate for completing data
collection and reporting under the
IPFQR Program), our estimated cost of
fringe benefits and other indirect costs
(calculated at 100 percent of salary), and
our adjusted hourly wage.
ddrumheller on DSK120RN23PROD with PROPOSALS2
TABLE 25—WAGE ASSUMPTIONS FOR THE IPFQR PROGRAM
Occupation title
Occupation
code
Median
hourly wage
($/hr.)
Fringe benefits
and other
indirect costs
($/hr.)
Adjusted
hourly
wage
($/hr.)
Medical Records and Health Information Technician .............................................
29–2071
22.43
22.43
44.86
As indicated, we are adjusting our
hourly wage estimates by a factor of 100
percent. This is necessarily a rough
adjustment, both because fringe benefits
and other indirect costs vary
significantly from employer to
employer, and because methods of
estimating these costs vary widely from
study to study. Nonetheless, we believe
that doubling the hourly wage to
estimate the total cost is a reasonably
accurate estimation method.
In the FY 2022 IPF PPS final rule (86
FR 42662), which was the most recent
rule in which we adopted updates to the
IPFQR Program, we estimated that
reporting measures for the IPFQR
Program could be accomplished by a
Medical Records and Health
Information Technician (BLS
Occupation Code: 29–2071) with a
median hourly wage of $20.50/hour
(BLS, May 2019). While we are not
changing the respondent’s occupation
title or occupation code, we are
proposing to adjust our cost estimates
using BLS’ May 2021 median wage rate
figure of $22.43/hour, an increase of
$1.93/hour ($22.43/hour¥$20.50/hour).
When factoring in our overhead and
other indirect cost adjustments, the
wage is increased by $3.86/hour
($44.86/hour¥$41.00/hour).
We have also estimated the average
hourly cost for beneficiaries undertaking
administrative and other tasks on their
own time. Based on recommendations
from the Valuing Time in U.S.
Department of Health and Human
Services Regulatory Impact Analyses 233
guidance we have estimated a post-tax
wage of $20.71/hr. The Valuing Time in
U.S. Department of Health and Human
Services Regulatory Impact Analyses:
Conceptual Framework and Best
Practices identifies the approach for
valuing time when individuals
undertake activities on their own time.
To derive the costs for beneficiaries, a
measurement of the usual weekly
earnings of wage and salary workers of
$998, divided by 40 hours to calculate
an hourly pre-tax wage rate of $24.95/
hours. This rate is adjusted downwards
by an estimate of the effective tax rate
for median income households of about
17 percent, resulting in the post-tax
hourly wage rate of $20.71/hour. Unlike
our State and private sector wage
adjustments, we are not adjusting
beneficiary wages for fringe benefits and
other indirect costs since the
individuals’ activities, if any, would
occur outside the scope of their
employment.
B. Proposed Information Collection
Requirements (ICRs) Regarding the
IPFQR Program
The following proposed requirement
and burden changes will be submitted
to OMB for review under control
number 0938–1171 (CMS–10432). We
are not proposing changes that will
affect any of data collection instruments
that are currently approved under that
control number. In section VI.B.1 of this
proposed rule, we restate our currently
approved burden estimates. In section
VI.B.2 of this proposed rule, we estimate
the changes in burden associated with
the policies proposed in this rule and
updated estimates for wage rates,
facility counts, and case counts. Then in
section VI.B.3 of this proposed rule, we
provide an overview of the total
estimated burden.
1. Currently Approved Burden
For a detailed discussion of the
burden for the IPFQR Program
requirements that we have previously
adopted, we refer readers to the
following rules:
• The FY 2013 IPPS/LTCH PPS final
rule (77 FR 53673);
• The FY 2014 IPPS/LTCH PPS final
rule (78 FR 50964);
• The FY 2015 IPF PPS final rule (79
FR 45978 through 45980);
• The FY 2016 IPF PPS final rule (80
FR 46720 through 46721);
• The FY 2017 IPPS/LTCH PPS final
rule (81 FR 57265 through 57266);
• The FY 2018 IPPS/LTCH PPS final
rule (82 FR 38507 through 38508);
• The FY 2019 IPF PPS final rule (83
FR 38609 through 38612);
• The FY 2020 IPF PPS final rule (84
FR 38468 through 38476); and
• The FY 2022 IPF PPS final rule (86
FR 42661 through 42672).
Table 26 provides an overview of our
currently approved burden estimates.
233 https://aspe.hhs.gov/sites/default/files/
private/pdf/257746/VOT.pdf.
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TABLE 26—CURRENTLY APPROVED BURDEN OMB CONTROL NUMBER 0938–1171
[CMS–10432]
Number
respondents
(facilities)
Measure/response description
Hours of Physical Restraint Use .................................
Hours of Seclusion Use ..............................................
Patients Discharged on Multiple Antipsychotic Medications with Appropriate Justification ......................
Alcohol Use Brief Intervention Provided or Offered
(SUB–2 and SUB–2a) .............................................
Alcohol and Other Drug Use Disorder Treatment
Provided or Offered at Discharge and Alcohol and
Other Drug Use Disorder Treatment at Discharge
(SUB–3 and SUB–3a) .............................................
Tobacco Use Treatment Provided or Offered and Tobacco Use Treatment (TOB–2 and TOB–2a) .........
Tobacco Use Treatment Provided or Offered at Discharge and Tobacco Use Treatment at Discharge
(TOB–3 and TOB–3a) .............................................
Influenza Immunization ...............................................
Transition Record with Specified Elements Received
by Discharged Patients (Discharges from an Inpatient Facility to Home/Self Care or Any Other Site
of Care) ....................................................................
Screening for Metabolic Disorders ..............................
Thirty-day all-cause unplanned readmission following
psychiatric hospitalization in an IPF ........................
Medication Continuation Following Inpatient Psychiatric Discharge ....................................................
COVID–19 Vaccination Rate Among Healthcare Personnel ......................................................................
Follow-Up After Psychiatric Hospitalization ................
Estimated
responses
per facility
Total
annual
responses
Time per
response
(hours)
Annual time
per facility
(hours)
Total
annual time
(hours)
Total annual
cost
($)
1,634
1,634
1,346
1,346
2,199,364
2,199,364
0.25
0.25
336.50
336.50
549,841
549,841
22,543,481
22,543,481
1,634
* 609
995,106
0.25
152.25
248,776.5
10,199,836.50
1,634
* 609
995,106
0.25
152.25
248,776.5
10,199,836.50
1,634
* 609
995,106
0.25
152.25
248,776.5
10,199,836.50
1,634
* 609
995,106
0.25
152.25
248,776.5
10,199,836.50
1,634
1,634
* 609
* 609
995,106
995,106
0.25
0.25
152.25
152.25
248,776.5
248,776.5
10,199,836.50
10,199,836.50
1,634
1,634
* 609
* 609
995,106
995,106
0.25
0.25
152.25
152.25
248,776.5
248,776.5
10,199,836.50
10,199,836.50
0
** 0
0
0
0
0
0
0
** 0
0
0
0
0
0
0
0
*** 0
** 0
0
0
0
0
0
0
0
0
0
0
Subtotal ................................................................
1,634
7,564
12,359,576
N/A
1,891
3,089,894
126,685,654
Non-Measure Data Collection and Reporting .............
1,634
4
6,536
0.5
2.0
3,268
133,988
Total .....................................................................
1,634
7,568
12,366,112
Varies
1,893
3,093,162
126,819,642
ddrumheller on DSK120RN23PROD with PROPOSALS2
* Under our previously finalized ‘‘global sample’’ (80 FR 46717 through 46718) we allow facilities to apply the same sampling methodology to all measures eligible
for sampling. In the FY 2016 IPF PPS final rule (80 FR 46718), we finalized that facilities with between 609 and 3,056 cases that choose to participate in the global
sample would be required to report data for 609 cases. Because facilities are only required to submit data on a number specified by the global sampling methodology,
rather than abstracting data for all patients or applying measure specific sampling methodologies, we believe that the number of cases under the global sample is a
good approximation of facility burden associated with these measures. Therefore, for the average IPF discharge rate of 1,346 discharges the global sample requires
abstraction of 609 records.
** CMS will collect these data using Medicare Part A and Part B claims; therefore, these measures will not require facilities to submit data on any cases.
*** The COVID–19 HCP measure will be calculated using data submitted to the CDC under a separate OMB control number (0920–1317).
2. Adjustments Due to Changes in This
Proposed Rule
In this proposed rule, we propose
provisions that impact policies
beginning with the FY 2025 through FY
2028 payment determinations. For the
purposes of calculating burden, we
attribute the costs to the year in which
the costs begin. For example, data
submission for the measures that affect
the FY 2025 payment determination
occurs during CY 2024 and generally
reflects are provided during CY 2023.
The following discussion describes the
burden changes for proposals attributed
to the year in which the costs begin. For
the proposals in this proposed rule,
those years are CY 2023 through CY
2027.
Additionally, in the FY 2022 IPF PPS
final rule (86 FR 42661 through 42672),
which is the most recent rule that
updated the IPFQR Program policies, we
estimated that there were 1,634
participating IPFs and that (for measures
that require reporting on the entire
patient population) these IPFs will
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report on an average of 1,346 cases per
IPF. In this FY 2024 IPF PPS proposed
rule, we are proposing to adjust our IPF
count and case estimates by using the
most recent data available. Specifically,
we estimate that there are now
approximately 1,596 facilities (a
decrease of 38 facilities) and an average
of 1,261 cases per facility (a decrease of
85 cases per facility). We will update
our estimates, as applicable, using these
revised estimates in the following
subsections.
a. Proposals Affecting Data Reporting
Beginning in CY 2023
In section V.E of this proposed rule,
we propose to modify the COVID–19
Vaccination Coverage Among
Healthcare Personnel measure
beginning with data reflecting the fourth
quarter of CY 2023 affecting the FY 2025
payment determination. We do not
believe that the proposed modification
(that is, a change in terminology to refer
to ‘‘up-to-date’’ instead of ‘‘complete
vaccination course’’) would impact our
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currently approved IPF information
collection requirements or reporting
burden. Furthermore, the modified
COVID–19 Vaccination Coverage
Among HCP measure would be
calculated using data submitted to the
CDC for healthcare safety surveillance
under the CDC’s OMB control number
0920–1317. In this regard, the CDC
owns the requirements and burden that
fall under that control number.
b. Proposals Affecting Burden Beginning
With CY 2024
(1) Proposed Updates Affecting Facility
Reporting Burden
In section V.F.2 of this proposed rule,
we propose to remove two measures
beginning with the FY 2025 payment
determination. Data for these measures
would be submitted in CY 2024, so we
are estimating the reduced burden to
occur in CY 2024. These two measures
are:
• Patients Discharged on Multiple
Antipsychotic Medications with
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Appropriate Justification (HBIPS–5);
and
• Tobacco Use Treatment Provided or
Offered and Tobacco Use Treatment
(TOB–2 and TOB–2a).
Using our currently approved burden
estimates, the change in total burden
associated with these proposed measure
removals would be minus 1,990,212
responses, minus 497,553 hours, and
minus $20,339,673 as depicted in Table
27.
TABLE 27—UPDATES TO BURDEN ASSOCIATED WITH PROPOSED MEASURE REMOVALS
Measure/response description
Number
respondents
(facilities)
Estimated
responses per
facility
Total annual
responses
Time per
response
(hours)
Annual time
per facility
(hours)
Total annual
time
(hours)
Total annual cost
($)
(a)
(b)
(c) = (a) × (b)
(d)
(e) = (b) × (d)
(f) = (a) × (e)
(g) = (f) × $41.00/hr
Patients
Discharged
on
Multiple
Antipsychotic Medications with Appropriate Justification .........................
Tobacco Use Treatment Provided or
Offered and Tobacco Use Treatment
(TOB–2 and TOB–2a) .......................
Total ...................................................
1,634
(* 609)
(995,106)
0.25
(152.25)
(248,776.5)
(10,199,836.50)
1,634
(* 609)
(995,106)
0.25
(152.25)
(248,776.5)
(10,199,836.50)
1,634
(1,218)
(1,990,212)
0.25
(304.5)
(497,553)
(20,339,673)
* Under our previously finalized ‘‘global sample’’ (80 FR 46717 through 46718) we allow facilities to apply the same sampling methodology to all measures eligible
for sampling. In the FY 2016 IPF PPS final rule (80 FR 46718), we finalized that facilities with between 609 and 3,056 cases that choose to participate in the global
sample would be required to report data for 609 cases. Because facilities are only required to submit data on a number specified by the global sampling methodology,
rather than abstracting data for all patients or applying measure specific sampling methodologies, we believe that the number of cases under the global sample is a
good approximation of facility burden associated with these measures. Therefore, for the average IPF discharge rate of 1,346 discharges the global sample requires
abstraction of 609 records.
Additionally, we are applying our
updated wage rate, case count, and
facility counts to the remaining measure
set and program requirements for data
submission in CY 2024. See Table 28
and 29 for information on the effects of
these updates. Specifically, we estimate
that there are now approximately 1,596
facilities (a decrease of 38 facilities) and
an average of 1,261 cases per facility (a
decrease of 85 cases per facility). We
also estimate a wage increase of $3.86/
hour as described in section VI.A of this
proposed rule. Our previous estimate
shows that the two measures which do
not allow sampling had 1,346 cases per
measure and the six remaining measures
which do allow sampling require 609
cases per measure per facility. We have
estimated that these measures would
take 0.25 hours per case. The effects of
the updated wage rate are depicted in
Table 28.
TABLE 28—EFFECTS OF UPDATED WAGE RATE
Number of
measures
Data collection type
Total number
of cases
per facility
Effort per case
(hours)
Total effort per
facility
(hours)
Change
in cost per
facility
($(effort *
3.86/hour
wage change)
No-sampling measures ............................
Sampling measures .................................
Non-Measure Data ...................................
2
6
1
1,346
609
4
2,692
3,654
4
0.25
0.25
0.5
673
913.5
2
2,597.78
3,526.11
7.72
Total Change per Facility .................
........................
........................
........................
........................
........................
6,131.61
The remaining calculations will use
the updated wage rate to calculate the
effects of other updates.
We have previously estimated 1,346
cases for measures which do not allow
sampling. Based on more recent data,
we are updating our estimate for
measures that do not allow sampling to
1,261 cases per IPF (a change of +85
cases for each of these 2 measures). This
ddrumheller on DSK120RN23PROD with PROPOSALS2
Number of
estimated
cases per
measure per
facility
is equivalent to 138,890 cases across the
1,634 IPFs (85 cases * 1,634 IPFs) in our
previous estimate for each measure. We
are not changing our estimated case
counts for measures that allow
sampling. We continue to assume an
average of 0.25 hours of effort per case.
Therefore, this change in cases reflects
a total annual effort of 42.5 hours per
facility (2 measures * 85 cases per
measure * 0.25 hours per case) at a cost
of $1,906.55 (42.5 hours * $44.86/hour).
As indicated above we estimate a
reduction of 38 facilities based on
updated numbers. Table 29 shows the
effects of this reduction in facilities on
the reporting burden associated with
each measure type.
TABLE 29—EFFECTS OF UPDATED FACILITY COUNTS
Measure type
No Sampling ..................................
Sampling ........................................
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Number of
estimated cases
(per measure
per facility)
Number of
measures
2
6
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facility
1,261 .................
609 ....................
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3,654
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Effort per
facility
0.25 ...................
0.25 ...................
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630.5
913.5
10APP2
Change in
annual
effort for
removing
38 facilities
(hours)
(23,959)
(34,713)
Change in
annual
effort for
removing
38 facilities
(dollars)
(1,074,800.74)
(1,557,225.18)
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TABLE 29—EFFECTS OF UPDATED FACILITY COUNTS—Continued
Number of
estimated cases
(per measure
per facility)
Number of
measures
Measure type
Cases per
facility
Effort
per case
Change in
annual
effort for
removing
38 facilities
(hours)
Effort per
facility
Change in
annual
effort for
removing
38 facilities
(dollars)
Non-Measure Data Collection .......
1
4 ........................
4
0.5 .....................
2
(76)
(3,409.36)
Total ........................................
9
Varies ................
6,180
Varies ................
1,546
(58,748)
(2,635,435.28)
We note that at 6,180 cases per
facility, removing 38 facilities from our
estimate removes a total of 234,840
cases (6,180 cases per facility * 38
facilities).
The total effects of changes for the CY
2024 calendar year on our burden
estimates are summarized in Table 30.
TABLE 30—TOTAL CY 2024 FACILITY INFORMATION COLLECTION BURDEN CHANGES
Total
annual time
(hours)
Total
responses
Total
annual cost
($)
Remove Two Measures .......................................................................................................
Update Wage Estimate ........................................................................................................
Update Case Estimate .........................................................................................................
Update Facility Estimate ......................................................................................................
(1,990,212)
N/A
(277,280)
(234,840)
(497,553)
N/A
(69,445)
(58,748)
(20,339,673)
8,253,147.06
(3,115,302.70)
(2,635,435.28)
Total ..............................................................................................................................
(2,502,332)
(625,746)
(17,837,263.92)
(b) Proposed Updates Affecting Patient
Survey Burden
In section V.D.3 of this proposed rule,
we propose to adopt the Screening for
Social Drivers of Health measure
beginning with a voluntary data
submission in CY 2025 (reflecting care
provided in CY 2024). In this regard,
IPFs would be able to collect data and
report the measure via multiple
methods. For additional information on
these methods, we refer readers to
section V.D.3.c of this proposed rule.
We believe that most IPFs would likely
collect data during the patient intake
process. Because this measure reflects
care provided in CY 2024, the burden
for administering the screening to
patients would occur during CY 2024.
The Hospital IQR Program, which
adopted the Screening for Social Drivers
of Health measure, estimated the
information collection burden
associated with patients responding to
the selected screening instrument would
require two minutes per patient to
complete the screening in the FY 2022
IPPS/LTCH PPS final rule (87 FR 49385
through 49386) under OMB Control
Number 0938–1022 (CMS–10210). The
Hospital IQR Program also estimated
that during the voluntary reporting
period roughly 50 percent of hospitals
would survey 50 percent of patients (87
FR 49385 through 49386).
We agree with these estimates and
believe that a similar proportion of IPFs
will participate in the voluntary
reporting period. As described in
section VI.A of this proposed rule, we
estimate the cost of patients’ time for
completing surveys to be $20.71/hour.
Using these estimates, we believe that
during the voluntary reporting period
the annual burden of surveying IPF
patients would be 16,603.59 hours
[(1,596 facilities × 50 percent of
facilities) × (1,261 patients per facility ×
50 percent of patients) × 0.033 hours/
response] at a cost of $343,860.29
(16,603.59 hours × 20.71/hour). These
estimates are summarized in Table 31.
ddrumheller on DSK120RN23PROD with PROPOSALS2
TABLE 31—TOTAL CY 2024 PATIENT SURVEY BURDEN CHANGES
Total
responses
Total
annual time
(hours)
Total
annual cost
($)
Screening for SDOH ....................................................................................................................
503,139
16,603.59
343,860.29
(c) Proposals Affecting Burden
Beginning with CY 2025
many IPFs would require less than 10
minutes. In addition, we believe that
many IPFs will be able to submit similar
responses in future years. Using the
estimate of 10 minutes per IPF per year
at $44.86/hour for a medical records and
health information technician, we
estimate that this policy would result in
a total annual burden increase of 267
hours across all participating IPFs
(0.167 hours × 1,596 IPFs) at a cost of
$11,956.63 (267 hours × $44.86/hour).
(1) Proposed Updates Affecting Facility
Reporting Burden
In section V.D.2. of this proposed
rule, we propose to adopt the Facility
Commitment to Health Equity measure
beginning with the FY 2026 payment
determination. Data for this attestation
measure would be submitted during CY
2025. Consistent with our burden
estimate from the Hospital IQR Program,
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when we adopted the similar Hospital
Commitment to Health Equity measure
in the FY 2023 IPPS/LTCH PPS final
rule, we estimate an average of 10
minutes per facility for a medical
records and health information
technician to collect and report this
information (87 FR 49385). We
recognize that some IPFs may take more
than 10 minutes to collect this
information, especially in the first year
of reporting; however, we believe that
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In sections V.D.3 and V.D.4 of this
proposed rule, we propose to adopt the
Screening for Social Drivers of Health
measure and the associated Screen
Positive Rate for Social Drivers of
Health measure beginning with a
voluntary data submission in CY 2025
(reflecting care provided in CY 2024).
We described our anticipated burden for
administering the screening in the
previous section because this burden
would accrue during CY 2024. The
burden associated with reporting each
of these measures to CMS would occur
during CY 2025. We anticipate that the
burden for reporting the two measures
would be consistent with the burden for
other web-based submissions, such as
the Facility Commitment to Health
Equity measure described previously in
this section and for similar measures
adopted in the Ambulatory Surgical
Center Quality Reporting (ASCQR)
Program (OMB control number 0938–
1270; CMS–10530), which we have
estimated to have a reporting burden of
0.167 hours per IPF. We note that for the
voluntary reporting year we have
estimated only 50 percent of IPFs would
report these data. Therefore, we estimate
the burden associated with reporting of
each of these measures to be 133 hours
(0.167 hr. × 798 IPFs) at a cost of $5,966
(133 hr. × $44.86/hr. for a medical
records and health information
technician) for the voluntary reporting
period. These estimates are summarized
in Table 32.
A summary of our estimated changes
in information collection burden for CY
2025 is shown in Table 32.
TABLE 32—TOTAL CY 2025 FACILITY INFORMATION COLLECTION BURDEN CHANGES
Number
respondents
(facilities)
Measure/response description
Facility Commitment to Health Equity ...........
Screening for Social Drivers of .....................
Estimated
responses per
facility
1,596
798
Time per
response
(hours)
Total annual
responses
1
1
Annual time
per facility
(hours)
Total annual
time (hours)
Total annual
cost
($)
1,596
798
0.167
0.167
0.167
0.167
267
133
11,956.63
5,966.38
Health
Screen Positive Rate for Social Drivers of
Health ........................................................
798
1
798
0.167
0.167
133
5,966.38
Totals .....................................................
1,596
3
3,192
0.167
0.167
533
23,889.39
(2) Proposed Updates Affecting Patient
Survey Burden
Beginning with CY 2025, IPFs would
need to screen 100 percent of their
patients to prepare for required
reporting of the Screening for SDOH
measure in CY 2026 (for the FY 2027
payment determination). Therefore, we
estimate that 100 percent of IPFs would
screen 100 percent of their patients. We
recognize that this may be an
overestimate as some IPFs may choose
not to participate and some patients
may opt out of screening or be unable
to provide responses; however, we
believe that the numbers of IPFs and
patients opting out will be relatively
small and therefore 100 percent will be
a reasonable approximation.
Using the facility counts, patient
counts, and average hourly earnings
described previously, we estimate the
burden of surveying IPF patients for
health-related social needs (HRSNs)
under the Screening for Social Drivers
of Health and Screen Positive Rate for
Social Drivers of Health measures will
be 66,414 hours (1,596 facilities × 1,261
patients per facility × 0.033 hours) at a
cost of $1,375,433.94 (66,414 hours ×
$20.71/hour). We note that 16,603.59
hours and $343,960.29 of this burden
was previously accounted for in our
analysis of the burden of the voluntary
reporting period. Therefore, the
incremental burden of switching to
required reporting is 49,810.41 hours
and $1,031,473.65.
Additionally, in section V.D.5 of this
proposed rule, we are proposing to
adopt the Psychiatric Inpatient
Experience (PIX) survey measure
beginning with voluntary data
submission in CY 2026. To prepare for
data submission in 2026, IPFs would
begin administering this survey in CY
2025. We believe 50 percent of IPFs
would begin collecting these data for the
voluntary data submission period. We
note that we have proposed to allow
IPFs with more than 300 eligible
discharges to sample, which would
require these facilities to survey 300
patients. Because the questions on the
PIX survey are similar in content and
response options to the questions on the
Hospital Consumer Assessment of
Healthcare Providers and Systems
(HCAHPS) survey, we believe that it
would take patients a similar amount of
time to respond to these questions. In
the Information Collection Request
associated with OMB control number
0938–0981 (CMS–10102), we have
estimated this time to be 7.25 minutes.
Therefore, we believe that the burden
associated with conducting the PIX
survey in CY 2025 would be 28,967.4
hours (50 percent of 1,596 facilities ×
300 patients/facility × 0.121 hours) at a
cost of $599,914.85 (28,967.4hours ×
$20.71/hour).
Our estimates for the CY 2025 total
patient survey burden changes are
summarized in Table 33.
TABLE 33—TOTAL CY 2025 PATIENT SURVEY BURDEN CHANGES
ddrumheller on DSK120RN23PROD with PROPOSALS2
Total
responses
Total annual
time (hours)
Total annual
cost
($)
Screening for SDOH ....................................................................................................................
PIX ...............................................................................................................................................
1,509,417
239,400
49,810.41
28,967.4
1,031,473.65
599,914.85
Totals ....................................................................................................................................
1,748,817
78,777.81
1,631,388.5
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(d) Proposals Affecting Burden
Beginning With CY 2026
(1) Proposed Updates Affecting Facility
Reporting Burden
Beginning with CY 2026 data
submission (affecting the FY 2027
payment determination), we estimate
that 100 percent of IPFs would submit
data on the Screening for Social Drivers
of Health measure and Screen Positive
Rate for Social Drivers of Health
measure. Because we have already
accounted for 50 percent of facilities
submitting voluntary data on these
measures, the incremental burden is the
burden associated with the remaining
50 percent of facilities submitting data;
that is, we estimate this burden to be
266 hours at a cost of $11,932.76. We
also believe that 50 percent of facilities
will submit data on the PIX measure for
the voluntary reporting period in CY
2025. Because the data for this measure
would require calculating an average of
scores across a sample of patient
surveys, we anticipate that the
information collection and reporting
burden for this measure would be
approximately 15 minutes (0.25 hours)
per patient for whom they are reporting
data. The burden associated with
reporting the Screening for Social
Drivers of Health measure, the Screen
Positive Rate for Social Drivers of
Health measure, and the PIX survey
measure to CMS is described in Table
34.
TABLE 34—TOTAL CY 2026 FACILITY INFORMATION COLLECTION BURDEN CHANGES
Number
respondents
(facilities)
Measure/response description
Estimated
responses per
facility
Time per
response
(hours)
Total annual
responses
Annual time
per facility
(hours)
Total annual
time
(hours)
Total annual
cost
($)
Screening for Social Drivers of Health .........
Screen Positive Rate for Social ‘Drivers of
Health ........................................................
PIX Survey ....................................................
798
1
798
0.167
0.167
133
5,966.38
798
798
1
300
798
239,400
0.167
0.25
0.167
75
133
59,850
5,966.38
2,684,871.00
Totals .....................................................
798
302
240,996
Varies
75.33
60,116
2,696,803.76
(2) Proposed Updates Affecting Patient
Survey Burden
Because reporting the PIX measure
would be required for FY 2028 payment
determination, the remaining 50 percent
of facilities (those which did not
participate in the voluntary reporting
period) would begin surveying patients
in CY 2026. To prepare for data
submission of the PIX survey measure
in CY 2027, IPFs that had not previously
begun administering the PIX survey
would begin administering this survey
in CY 2026. The incremental burden of
these 50 percent of facilities
administering the survey would be
equivalent to the burden associated with
the 50 percent of facilities that
participated in the voluntary reporting
in CY 2025. These estimates are
summarized in Table 35.
TABLE 35—TOTAL CY 2026 PATIENT SURVEY BURDEN CHANGES
Total
responses
Total annual
time
(hours)
Total annual
cost
($)
PIX ...............................................................................................................................................
239,400
28,967.4
599,914.85
(e.) Proposals Affecting Facility
Reporting Burden Beginning With CY
2027
For data submission occurring in CY
2027, submission on the PIX survey
measure would be required, therefore,
increase in burden for IPFs associated
with this requirement would be
reporting by the 50 percent of facilities
that had not previously reported the PIX
survey measure. This burden is depicted
in Table 36.
we believe that an additional 50 percent
of facilities would report the measure
(that is, the 50 percent of facilities not
previously accounted for under the
voluntary reporting period). Therefore,
we estimate that the incremental
TABLE 36—TOTAL CY 2027 FACILITY INFORMATION COLLECTION BURDEN CHANGES
Measure/response
description
Number
respondents
(facilities)
Estimated
responses per
facility
Total annual
responses
Time per
response
(hours)
Annual time
per facility
(hours)
Total annual
time
(hours)
Total annual
cost
($)
PIX Survey ...................
798
300
239,400
0.25
75
59,850
2,684,871.00
ddrumheller on DSK120RN23PROD with PROPOSALS2
3. Overall Burden Summary
Table 37 summarizes the incremental
changes in burden for IPFs associated
with proposed policies for data
collection and submission in CYs 2024
through 2027 as well as updates to our
estimated wage rate, facility counts, and
case counts.
TABLE 37—PROPOSED INCREMENTAL CHANGES IN FACILITY BURDEN
Total
responses
Changes Associated with CY 2024 Updates ..............................................................................
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(2,502,332)
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10APP2
Total annual
time
(hours)
(625,746)
Total annual
cost
($)
(17,837,264)
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TABLE 37—PROPOSED INCREMENTAL CHANGES IN FACILITY BURDEN—Continued
Total
responses
Total annual
time
(hours)
Total annual
cost
($)
Changes Associated with CY 2025 Updates ..............................................................................
Changes Associated with CY 2026 Updates ..............................................................................
Changes Associated with CY 2027 Updates ..............................................................................
3,192
240,996
239,400
533
60,116
59,850
23,889
2,696,804
2,684,871
Total ......................................................................................................................................
(2,018,744)
(505,247)
(12,431,700)
Table 38 summarizes the incremental
changes in burden for patients due to
data collection associated with
proposed policies for data collection
and submission in CYs 2024 through CY
2026.
TABLE 38—PROPOSED INCREMENTAL CHANGES IN SURVEY BURDEN FOR PATIENTS
Changes Associated with CY 2024 Updates ..............................................................................
Changes Associated with CY 2025 Updates ..............................................................................
Changes Associated with CY 2026 Updates ..............................................................................
503,139
1,748,817
239,400
16,604
78,778
28,967
343,860
1,631,339
599,915
Totals ....................................................................................................................................
2,491,356
124,349
2,575,114
ddrumheller on DSK120RN23PROD with PROPOSALS2
C. Submission of PRA-Related
Comments
We have submitted a copy of this
proposed rule’s information collection
requirements to OMB for their review.
The requirements are not effective until
they have been approved by OMB.
To obtain copies of the supporting
statement and any related forms for the
proposed collections discussed above,
please visit the CMS website at https://
www.cms.gov/regulations-andguidance/legislation/
paperworkreductionactof1995/pralisting, or call the Reports Clearance
Office at 410–786–1326.
We invite public comments on these
potential information collection
requirements. If you wish to comment,
please submit your comments
electronically as specified in the DATES
and ADDRESSES sections of this
proposed rule and identify the rule
(CMS–1783–P), the ICR’s CFR citation,
and OMB control number.
VII. Response to Comments
Because of the large number of public
comments, we normally receive on
Federal Register documents, we are not
able to acknowledge or respond to them
individually. We will consider all
comments we receive by the date and
time specified in the DATES section of
this preamble, and, when we proceed
with a subsequent document, we will
respond to the comments in the
preamble to that document.
VIII. Regulatory Impact Analysis
A. Statement of Need
This rule proposes updates to the
prospective payment rates for Medicare
inpatient hospital services provided by
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IPFs for discharges occurring during FY
2024 (October 1, 2023 through
September 30, 2024). We propose to
apply the proposed 2021-based IPF
market basket increase of 3.2 percent,
less the productivity adjustment of 0.2
percentage point as required by
1886(s)(2)(A)(i) of the Act for a proposed
total FY 2024 payment rate update of
3.0 percent. In this proposed rule, we
propose to update the outlier fixed
dollar loss threshold amount, update the
IPF labor-related share, and update the
IPF wage index to reflect the FY 2024
hospital inpatient wage index.
B. Overall Impact
We have examined the impacts of this
rule as required by Executive Order
12866 on Regulatory Planning and
Review (September 30, 1993), Executive
Order 13563 on Improving Regulation
and Regulatory Review (January 18,
2011), the Regulatory Flexibility Act
(RFA) (September 19, 1980, Pub. L. 96–
354), section 1102(b) of the Social
Security Act, section 202 of the
Unfunded Mandates Reform Act of 1995
(March 22, 1995; Pub. L. 104–4),
Executive Order 13132 on Federalism
(August 4, 1999), and the Congressional
Review Act (5 U.S.C. 804(2)).
Executive Orders 12866 and 13563
direct agencies to assess all costs and
benefits of available regulatory
alternatives and, if regulation is
necessary, to select regulatory
approaches that maximize net benefits
(including potential economic,
environmental, public health and safety
effects, distributive impacts, and
equity). Section 3(f) of Executive Order
12866 defines a ‘‘significant regulatory
action’’ as an action that is likely to
result in a rule: (1) having an annual
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effect on the economy of $100 million
or more in any 1 year, or adversely and
materially affecting a sector of the
economy, productivity, competition,
jobs, the environment, public health or
safety, or State, local or Tribal
governments or communities; (2)
creating a serious inconsistency or
otherwise interfering with an action
taken or planned by another agency; (3)
materially altering the budgetary
impacts of entitlement grants, user fees,
or loan programs or the rights and
obligations of recipients thereof; or (4)
raising novel legal or policy issues
arising out of legal mandates, the
President’s priorities, or the principles
set forth in the Executive Order.
A regulatory impact analysis (RIA)
must be prepared for major rules with
significant regulatory action/s and/or
with significant effects as per section
3(f)(1) ($100 million or more in any 1
year). We estimate that the total impact
of these changes for FY 2024 payments
compared to FY 2023 payments will be
a net increase of approximately $55
million. This reflects a $85 million
increase from the update to the payment
rates (+$90 million from the 4th quarter
2022 IGI forecast of the proposed 2021based IPF market basket of 3.2 percent,
and -$5 million for the productivity
adjustment of 0.2 percentage point), as
well as a $30 million decrease as a
result of the update to the outlier
threshold amount. Outlier payments are
estimated to change from 3.0 percent in
FY 2023 to 2.0 percent of total estimated
IPF payments in FY 2024.
Based on our estimates, OMB’s Office
of Information and Regulatory Affairs
has determined that this rulemaking is
‘‘significant.’’ ’’ per section 3(f)(1) as
measured by the $100 million threshold
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or more in any 1 year. Accordingly, we
have prepared a Regulatory Impact
Analysis that to the best of our ability
presents the costs and benefits of the
rulemaking. Therefore, OMB has
reviewed these proposed regulations,
and we have provided the following
assessment of their impact.
C. Detailed Economic Analysis
In this section, we discuss the
historical background of the IPF PPS
and the impact of this proposed rule on
the Federal Medicare budget and on
IPFs.
1. Budgetary Impact
As discussed in the November 2004
and RY 2007 IPF PPS final rules, we
applied a budget neutrality factor to the
Federal per diem base rate and ECT
payment per treatment to ensure that
total estimated payments under the IPF
PPS in the implementation period
would equal the amount that would
have been paid if the IPF PPS had not
been implemented. This Budget
neutrality factor included the following
components: Outlier adjustment, stop
loss adjustment, and the behavioral
offset. As discussed in the RY 2009 IPF
PPS notice (73 FR 25711), the stop-loss
adjustment is no longer applicable
under the IPF PPS.
As discussed in section III.D.1 of this
proposed rule, we propose to update the
wage index and labor-related share in a
budget neutral manner by applying a
wage index budget neutrality factor to
the Federal per diem base rate and ECT
payment per treatment. Therefore, the
budgetary impact to the Medicare
program of this proposed rule would be
due to the market basket update for FY
2024 of 3.2 percent (see section III.A.2
of this proposed rule) less the
productivity adjustment of 0.2
percentage point required by section
1886(s)(2)(A)(i) of the Act and the
update to the outlier fixed dollar loss
threshold amount.
We estimate that the FY 2024 impact
will be a net increase of $55 million in
payments to IPF providers. This reflects
an estimated $85 million increase from
the update to the payment rates and a
$30 million decrease due to the update
to the outlier threshold amount to set
total estimated outlier payments at 2.0
percent of total estimated payments in
FY 2024. This estimate does not include
the implementation of the required 2.0
percentage point reduction of the
productivity-adjusted market basket
update factor for any IPF that fails to
meet the IPF quality reporting
requirements (as discussed in section
III.B.2. of this proposed rule).
2. Impact on Providers
To show the impact on providers of
the changes to the IPF PPS discussed in
this proposed rule, we compare
estimated payments under the proposed
IPF PPS rates and factors for FY 2024
versus those under FY 2023. We
determined the percent change in the
estimated FY 2024 IPF PPS payments
compared to the estimated FY 2023 IPF
PPS payments for each category of IPFs.
In addition, for each category of IPFs,
we have included the estimated percent
change in payments resulting from the
proposed update to the outlier fixed
dollar loss threshold amount; the
updated wage index data including the
proposed labor-related share; and the
proposed market basket update for FY
2024, as reduced by the proposed
productivity adjustment according to
section 1886(s)(2)(A)(i) of the Act.
To illustrate the impacts of the
proposed FY 2024 changes in this
proposed rule, our analysis begins with
FY 2022 IPF PPS claims (based on the
2022 MedPAR claims, December 2022
update). We estimate FY 2024 IPF PPS
payments using these 2022 claims, the
finalized FY 2023 IPF PPS Federal per
diem base rates, and the finalized FY
2023 IPF PPS patient and facility level
adjustment factors (as published in the
FY 2023 IPF PPS final rule (87 FR
46846). We then estimate the FY 2024
outlier payments based on these
simulated FY 2023 IPF PPS payments
using the same methodology as the same
methodology that we used to set the
initial outlier threshold amount in the
RY 2007 IPF PPS final rule (71 FR 27072
and 27073), which is also the same
methodology that we used to update the
outlier threshold amounts for years 2008
through 2022, where total outlier
payments are maintained at 2 percent of
total estimated FY 2023 IPF PPS
payments. We note that in the FY 2023
final rule (87 FR 46862 through 46864)
we excluded providers from our
simulation of IPF PPS payments for FY
2022 and FY 2023 if their change in
estimated average cost per day was
outside 3 standard deviations from the
mean. As discussed in section III.E.2 of
this FY 2024 IPF PPS proposed rule, we
are not proposing to apply this
methodology for FY 2024.
Each of the following changes is
added incrementally to this baseline
model in order for us to isolate the
effects of each change:
• The proposed update to the outlier
fixed dollar loss threshold amount.
• The proposed FY 2024 IPF wage
index, and the proposed FY 2024 laborrelated share.
• The proposed market basket update
for FY 2024 of 3.2 percent less the
proposed productivity adjustment of 0.2
percentage point in accordance with
section 1886(s)(2)(A)(i) of the Act for a
payment rate update of 3.0 percent.
Our proposed column comparison in
Table 39 illustrates the percent change
in payments from FY 2023 (that is,
October 1, 2022, to September 30, 2023)
to FY 2024 (that is, October 1, 2023, to
September 30, 2024) including all the
proposed payment policy changes.
ddrumheller on DSK120RN23PROD with PROPOSALS2
TABLE 39—FY 2024 IPF PPS PROPOSED PAYMENT IMPACTS
Facility by type
Number of
facilities
Outlier
Wage index
FY24, LRS,
and 5% Cap
Total percent
change1
(1)
(2)
(3)
(4)
(5)
All Facilities ......................................................................................................
Total Urban ......................................................................................................
Urban unit .................................................................................................
Urban hospital ..........................................................................................
Total Rural .......................................................................................................
Rural unit ..................................................................................................
Rural hospital ............................................................................................
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1,481
1,209
695
514
272
211
61
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¥1.0
¥1.1
¥1.6
¥0.5
¥0.6
¥0.6
¥0.7
10APP2
0.0
0.1
0.2
0.0
¥0.8
¥0.8
¥0.9
1.9
2.0
1.6
2.5
1.5
1.6
1.3
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TABLE 39—FY 2024 IPF PPS PROPOSED PAYMENT IMPACTS—Continued
Facility by type
Number of
facilities
Outlier
Wage index
FY24, LRS,
and 5% Cap
Total percent
change1
(1)
(2)
(3)
(4)
(5)
By Type of Ownership:
Freestanding IPFs
Urban Psychiatric Hospitals
Government ..............................................................................................
Non-Profit ..................................................................................................
For-Profit ...................................................................................................
Rural Psychiatric Hospitals
Government ..............................................................................................
Non-Profit ..................................................................................................
For-Profit ...................................................................................................
117
98
299
¥1.8
¥0.5
¥0.3
0.1
0.5
¥0.2
1.2
3.0
2.5
31
13
17
¥1.3
¥2.4
0.0
¥0.6
¥0.2
¥1.3
1.1
0.3
1.6
100
455
140
¥2.9
¥1.5
¥0.7
0.6
0.4
¥0.6
0.6
1.9
1.6
51
118
42
¥0.4
¥0.7
¥0.4
¥0.7
¥0.7
¥1.1
1.9
1.6
1.4
1,283
101
67
30
¥0.8
¥1.8
¥2.4
¥2.1
¥0.2
0.9
0.4
0.5
2.0
2.1
1.0
1.4
105
204
228
243
149
105
215
106
126
¥1.4
¥1.7
¥0.6
¥0.6
¥0.7
¥1.9
¥0.6
¥0.6
¥1.3
¥0.7
1.1
0.1
¥0.3
¥0.8
¥0.3
¥0.1
¥0.9
0.4
0.9
2.4
2.5
2.1
1.4
0.7
2.3
1.4
2.1
92
84
86
313
¥0.8
¥0.2
¥0.1
¥0.6
¥0.4
¥0.8
¥0.2
0.1
1.7
2.1
2.7
2.5
487
241
106
72
¥1.1
¥1.2
¥1.8
¥2.2
¥0.3
0.3
0.0
0.7
1.6
2.1
1.1
1.5
IPF Units
Urban
Government ..............................................................................................
Non-Profit ..................................................................................................
For-Profit ...................................................................................................
Rural
Government ..............................................................................................
Non-Profit ..................................................................................................
For-Profit ...................................................................................................
By Teaching Status:
Non-teaching ....................................................................................................
Less than 10% interns and residents to beds .................................................
10% to 30% interns and residents to beds .....................................................
More than 30% interns and residents to beds ................................................
By Region:
New England ...................................................................................................
Mid-Atlantic ......................................................................................................
South Atlantic ...................................................................................................
East North Central ...........................................................................................
East South Central ..........................................................................................
West North Central ..........................................................................................
West South Central .........................................................................................
Mountain ..........................................................................................................
Pacific ..............................................................................................................
By Bed Size:
Psychiatric Hospitals
Beds: 0–24 ...............................................................................................
Beds: 25–49 .............................................................................................
Beds: 50–75 .............................................................................................
Beds: 76+ .................................................................................................
Psychiatric Units
Beds: 0–24 ...............................................................................................
Beds: 25–49 .............................................................................................
Beds: 50–75 .............................................................................................
Beds: 76+ .................................................................................................
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1 This column includes the impact of the updates in columns (3) through (4) above, and of the proposed IPF market basket update factor for
FY 2024 (3.2 percent), reduced by 0.2 percentage point for the productivity adjustment as required by section 1886(s)(2)(A)(i) of the Act.
3. Impact Results
Table 39 displays the results of our
analysis. The table groups IPFs into the
categories listed here based on
characteristics provided in the Provider
of Services file, the IPF PSF, and cost
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report data from the Healthcare Cost
Report Information System:
• Facility Type.
• Location.
• Teaching Status Adjustment.
• Census Region.
• Size.
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The top row of the table shows the
overall impact on the 1,481 IPFs
included in the analysis. In column 2,
we present the number of facilities of
each type that had information available
in the PSF, had claims in the MedPAR
dataset for FY 2022.
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In column 3, we present the effects of
the update to the outlier fixed dollar
loss threshold amount. We estimate that
IPF outlier payments as a percentage of
total IPF payments are 3.0 percent in FY
2023. Therefore, we propose to adjust
the outlier threshold amount to set total
estimated outlier payments equal to 2.0
percent of total payments in FY 2024.
The estimated change in total IPF
payments for FY 2024, therefore,
includes an approximate 1.0 percent
decrease in payments because we would
expect the outlier portion of total
payments to decrease from
approximately 3.0 percent to 2.0
percent.
The overall impact of the estimated
decrease to payments due to updating
the outlier fixed dollar loss threshold (as
shown in column 3 of Table 3), across
all hospital groups, is a 1.0 percent
decrease. The largest decrease in
payments due to this change is
estimated to be 2.9 percent for urban
government unit IPFs.
In column 4, we present the effects of
the proposed budget-neutral update to
the IPF wage index, the proposed LaborRelated Share (LRS), and the 5-percent
cap on any decrease to a provider’s
wage index from its wage index in the
prior year. This represents the effect of
using the concurrent hospital wage data
as discussed in section III.D.1.a of this
proposed rule. That is, the impact
represented in this column reflects the
proposed update from the FY 2023 IPF
wage index to the proposed FY 2024 IPF
wage index, which includes basing the
FY 2024 IPF wage index on the FY 2024
pre-floor, pre-reclassified IPPS hospital
wage index data, applying a 5-percent
cap on any decrease to a provider’s
wage index from its wage index in the
prior year, and updating the LRS from
77.4 percent in FY 2023 to 78.5 percent
in FY 2024. We note that there is no
projected change in aggregate payments
to IPFs, as indicated in the first row of
column 4; however, there would be
distributional effects among different
categories of IPFs. For example, we
estimate the largest increase in
payments to be 1.1 percent for MidAtlantic IPFs, and the largest decrease
in payments to be 1.3 percent for
freestanding rural for-profit IPFs.
Column 5 incorporates the proposed
market basket update of 3.2 percent
reduced by 0.2 percentage point for the
productivity adjustment as required by
section 1886(s)(2)(A)(i) of the Act. This
includes the proposal to rebase the IPF
PPS market basket to reflect a 2021 base
year.
Overall, IPFs are estimated to
experience a net increase in payments
as a result of the updates in this
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proposed rule. IPF payments are
estimated to increase by 2.0 percent in
urban areas and 1.5 percent in rural
areas. The largest payment increases are
estimated at 3.0 percent for freestanding
urban non-profit IPFs.
4. Effect on Beneficiaries
Under the FY 2024 IPF PPS, IPFs will
continue to receive payment based on
the average resources consumed by
patients for each day. Our longstanding
payment methodology reflects the
differences in patient resource use and
costs among IPFs, as required under
section 124 of the BBRA. We expect that
updating IPF PPS rates in this proposed
rule will improve or maintain
beneficiary access to high quality care
by ensuring that payment rates reflect
the best available data on the resources
involved in inpatient psychiatric care
and the costs of these resources. We
continue to expect that paying
prospectively for IPF services under the
FY 2024 IPF PPS will enhance the
efficiency of the Medicare program.
As discussed in sections V.D.3 and
V.D.4 of this proposed rule, we expect
that additional proposed IPFQR
Program measures will support
improving care for patients with healthrelated social needs. We also believe
that our proposed data validation pilot
is an important step towards ensuring
that the data beneficiaries and their
caregivers access on Care Compare (or a
successor CMS website) are accurate
and reliable. Based on the input from
patients and their caregivers regarding
the importance of having a patient
experience care measure for the IPF
setting in which they note many
benefits (including, but not limited to
helping patients select facilities in
which to receive care, providing
patients an opportunity to be heard, and
increasing alignment between general
acute and acute psychiatric settings).
We believe that our proposed PIX
survey measure will have positive
effects on patients and their caregivers.
Therefore, we expect that the proposed
updates to the IPFQR Program will
improve quality for beneficiaries.
5. Effects of the Updates to the IPFQR
Program
In section V.D.3 of this proposed rule,
we propose to adopt the Screening for
Social Drivers of Health measure for the
IPFQR Program beginning with
voluntary reporting of CY 2024 data,
and with required reporting of CY 2025
data for the FY 2027 payment
determination. For IPFs that are not
currently administering some screening
mechanism and elect to begin doing so
as a result of this policy, there will be
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21311
some non-recurring costs associated
with changes in workflow and
information systems to collect the data.
The extent of these costs is difficult to
quantify as different facilities may
utilize different modes of data collection
(for example, paper-based,
electronically patient-directed and
clinician-facilitated). In addition,
depending on the method of data
collection utilized, the time required to
complete the survey may add a
negligible amount of time to patient
visits.
In section V.D.5 of this proposed rule,
we are proposing to adopt the
Psychiatric Inpatient Experience (PIX)
survey measure. There may be some
non-recurring costs associated with
changes in workflow and information
systems to administer this survey and
collect the data. The extent of these
costs is difficult to quantify as different
facilities currently have different
practices for surveying patients to gather
information on their experiences of care.
In addition, for the IPFQR Program,
we propose to adopt the Facility
Commitment to Health Equity measure
and the Screen Positive for Social
Drivers of Health measure, as well as to
update the COVID–19 Vaccination
Coverage Among HCP measure. These
updates would not impact providers
workflows or information systems to
collect or report the data, and because
they represent processes of care or
structural data that the IPFs would
already have in place, we do not believe
they would incur costs for providers
beyond the recurring information
collection costs (described in section
VI.A of this proposed rule).
Finally, we propose to remove two
chart-abstracted measures from the
IPFQR Program. We believe that the
impact of removing the Tobacco Use
Brief Intervention Provided or Offered
and Tobacco Use Brief Intervention
Provided (TOB–2/2a) measure would be
minimal as we do not believe that IPFs
would update their workflow to no
longer provide brief tobacco cessation
interventions to patients who use
tobacco. However, we believe that there
may be some simplification of
workflows and clinical documentation
associated with the removal of the
Patients Discharged on Multiple
Antipsychotic Medications with
Appropriate Justification (HBIPS–5)
measure because IPFs would no longer
have to ensure the presence of
appropriate documentation for the use
of multiple antipsychotics. For more
information on the updated clinical
guidelines regarding polypharmacy for
patients with schizophrenia, we refer
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readers to section V.F.2.a of this
proposed rule.
As discussed in section III.B.2 of this
proposed rule and in accordance with
section 1886(s)(4)(A)(i) of the Act, we
will apply a 2-percentage point
reduction to the FY 2024 market basket
update for IPFs that have failed to
comply with the IPFQR Program
requirements for FY 2024, including
reporting on the required measures. In
section III.B.2 of this proposed rule, we
discuss how the 2-percentage point
reduction will be applied. For the FY
2023 payment determination, of the
1,596 IPFs eligible for the IPFQR
Program, 6 IPFs did not receive the full
market basket update because of the
IPFQR Program; 2 of these IPFs chose
not to participate and 4 did not meet the
requirements of the program. Thus, we
estimate that the IPFQR Program will
have a negligible impact on overall IPF
payments for FY 2024.
Based on the IPFQR Program
proposals in this proposed rule, we
estimate a total decrease in burden of
505,247 hours across all IPFs, resulting
in a total decrease in information
collection cost of $12,431,700 across all
IPFs. Further information on these
estimates can be found in section VI.A
of this proposed rule.
We intend to closely monitor the
effects of the IPFQR Program on IPFs
and help facilitate successful reporting
outcomes through ongoing stakeholder
education, national trainings, and a
technical help desk.
6. Regulatory Review Costs
If regulations impose administrative
costs on private entities, such as the
time needed to read and interpret this
proposed rule, we should estimate the
cost associated with regulatory review.
Due to the uncertainty involved with
accurately quantifying the number of
entities that will be directly impacted
and will review this proposed rule, we
assume that the total number of unique
commenters on the most recent IPF
proposed rule will be the number of
reviewers of this proposed rule. For this
FY 2024 IPF PPS proposed rule, the
most recent IPF proposed rule was the
FY 2023 IPF PPS proposed rule, and we
received 396 unique comments on this
proposed rule. We acknowledge that
this assumption may understate or
overstate the costs of reviewing this
proposed rule. It is possible that not all
commenters reviewed the FY 2023 IPF
proposed rule in detail, and it is also
possible that some reviewers chose not
to comment on that proposed rule. For
these reasons, we thought that the
number of commenters would be a fair
estimate of the number of reviewers
who are directly impacted by this
proposed rule. We are soliciting
comments on this assumption.
We also recognize that different types
of entities are in many cases affected by
mutually exclusive sections of this
proposed rule; therefore, for the
purposes of our estimate, we assume
that each reviewer reads approximately
50 percent of this proposed rule. Using
the May, 2021 mean (average) wage
information from the BLS for medical
and health service managers (Code 11–
9111), we estimate that the cost of
reviewing this proposed rule is $115.22
per hour, including overhead and fringe
benefits https://www.bls.gov/oes/
current/oes119111.htm. Assuming an
average reading speed of 250 words per
minute, we estimate that it would take
approximately 138 minutes (2.30 hours)
for the staff to review half of this
proposed rule (34,500), which contains
a total of approximately 69,000 words.
For each IPF that reviews the proposed
rule, the estimated cost is (2.30 ×
$115.22) or $265.01. Therefore, we
estimate that the total cost of reviewing
this proposed rule is $104,943.96
($265.01 × 396 reviewers).
D. Alternatives Considered
The statute does not specify an update
strategy for the IPF PPS and is broadly
written to give the Secretary discretion
in establishing an update methodology.
We continue to believe it is appropriate
to routinely update the IPF PPS so that
it reflects the best available data about
differences in patient resource use and
costs among IPFs as required by the
statute. Therefore, we propose to:
Update the IPF PPS using the
methodology published in the
November 2004 IPF PPS final rule;
apply the proposed 2021-based IPF PPS
market basket update for FY 2024 of 3.2
percent, reduced by the statutorily
required proposed productivity
adjustment of 0.2 percentage point along
with the proposed wage index budget
neutrality adjustment to update the
payment rates; and use a FY 2024 IPF
wage index which uses the FY 2024 prefloor, pre-reclassified IPPS hospital
wage index as its basis.
Lastly, we considered and are
soliciting comments on alternative
methodologies that could be appropriate
for establishing the FY 2024 outlier
fixed dollar loss threshold.
E. Accounting Statement
As required by OMB Circular A–4
(www.whitehous.gov/sites/
whitehouse.gov/files/omb/circulars/A4/
A-4/pdf), in Table 40, we have prepared
an accounting statement showing the
classification of the expenditures
associated with the updates to the IPF
wage index and payment rates in this
proposed rule. Table 40 provides our
best estimate of the increase in Medicare
payments under the IPF PPS as a result
of the changes presented in this
proposed rule and is based on 1,481
IPFs with data available in the PSF and
with claims in our FY 2022 MedPAR
claims dataset. Lastly, Table 40 also
includes our best estimate of the costs
of reviewing and understanding this
proposed rule.
TABLE 40—ACCOUNTING STATEMENT: CLASSIFICATION OF ESTIMATED COSTS AND TRANSFERS
ddrumheller on DSK120RN23PROD with PROPOSALS2
Regulatory Review Costs ..........................................................................................
Annualized Monetized Transfers from Federal Government to IPF Medicare Providers.
F. Regulatory Flexibility Act
The RFA requires agencies to analyze
options for regulatory relief of small
entities if a rule has a significant impact
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Units
Primary
estimate
($million/year)
Category
.11
55
on a substantial number of small
entities. For purposes of the RFA, small
entities include small businesses,
nonprofit organizations, and small
governmental jurisdictions. Most IPFs
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Year dollars
FY 2021 ..................
FY 2024 ..................
Period
covered
FY 2024.
FY 2024.
and most other providers and suppliers
are small entities, either by nonprofit
status or having revenues of $8 million
to $41.5 million or less in any 1 year.
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Individuals and states are not included
in the definition of a small entity.
Because we lack data on individual
hospital receipts, we cannot determine
the number of small proprietary IPFs or
the proportion of IPFs’ revenue derived
from Medicare payments. Therefore, we
assume that all IPFs are considered
small entities.
The Department of Health and Human
Services generally uses a revenue
impact of 3 to 5 percent as a significance
threshold under the RFA. As shown in
Table 39, we estimate that the overall
revenue impact of this proposed rule on
all IPFs is to increase estimated
Medicare payments by approximately
1.9 percent. As a result, since the
estimated impact of this proposed rule
is a net increase in revenue across
almost all categories of IPFs, the
Secretary has determined that this
proposed rule will have a positive
revenue impact on a substantial number
of small entities.
In addition, section 1102(b) of the Act
requires us to prepare a regulatory
impact analysis if a rule may have a
significant impact on the operations of
a substantial number of small rural
hospitals. This analysis must conform to
the provisions of section 603 of the
RFA. For purposes of section 1102(b) of
the Act, we define a small rural hospital
as a hospital that is located outside of
a metropolitan statistical area and has
fewer than 100 beds. As discussed in
section VIII.C.2 of this proposed rule,
the rates and policies set forth in this
proposed rule will not have an adverse
impact on the rural hospitals based on
the data of the 211 rural excluded
psychiatric units and 61 rural
psychiatric hospitals in our database of
1,481 IPFs for which data were
available. Therefore, the Secretary has
determined that this proposed rule will
not have a significant impact on the
operations of a substantial number of
small rural hospitals.
G. Unfunded Mandate Reform Act
(UMRA)
Section 202 of the Unfunded
Mandates Reform Act of 1995 (UMRA)
also requires that agencies assess
anticipated costs and benefits before
issuing any rule whose mandates
require spending in any 1 year of $100
million in 1995 dollars, updated
annually for inflation. In 2023, that
threshold is approximately $177
million. This proposed rule does not
mandate any requirements for State,
local, or Tribal governments, or for the
private sector. This proposed rule
would not impose a mandate that will
result in the expenditure by State, local,
and Tribal governments, in the
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aggregate, or by the private sector, of
more than $177 million in any 1 year.
H. Federalism
Executive Order 13132 establishes
certain requirements that an agency
must meet when it promulgates a
proposed rule that imposes substantial
direct requirement costs on State and
local governments, preempts State law,
or otherwise has Federalism
implications. This proposed rule does
not impose substantial direct costs on
State or local governments or preempt
State law.
Chiquita Brooks-LaSure,
Administrator of the Centers for
Medicare & Medicaid Services,
approved this document on March 30,
2023.
List of Subjects in 42 CFR Part 412
Administrative practice and
procedure, Health facilities, Medicare,
Puerto Rico, Reporting and
recordkeeping requirements.
For the reasons set forth in the
preamble, the Centers for Medicare &
Medicaid Services proposes to amend
42 CFR part 412 as set forth below:
PART 412—PROSPECTIVE PAYMENT
SYSTEMS PROSPECTIVE PAYMENT
SYSTEMS FOR INPATIENT HOSPITAL
SERVICES
1. The authority citation for part 412
continues to read as follows:
■
Authority: 42 U.S.C. 1302 and 1395hh.
2. Section 412.25 is amended by
revising paragraph (c)(2) to read as
follows:
■
§ 412.25 Excluded hospital units: Common
requirements.
*
*
*
*
*
(c) * * *
(2) The status of an IPF unit may be
changed from not excluded to excluded
or excluded to not excluded at any time
during a cost reporting period, but only
if the hospital notifies the fiscal
intermediary and the CMS Regional
Office in writing of the change at least
30 days before the date of the change,
and maintains the information needed
to accurately determine costs that are or
are not attributable to the IPF unit. A
change in the status of an IPF unit from
not excluded to excluded or excluded to
not excluded that is made during a cost
reporting period must remain in effect
for the rest of that cost reporting period.
*
*
*
*
*
■ 3. Section 412.433 is added to read as
follows:
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21313
§ 412.433 Procedural requirements under
the IPFQR Program.
(a) Statutory authority. Section
1886(s)(4) of the Act requires the
Secretary to implement a quality
reporting program for inpatient
psychiatric hospitals and psychiatric
units. Under section 1886(s)(4) of the
act, for an IPF paid under the IPF PPS
that fails to submit data required for the
quality measures selected by the
Secretary in a form and manner and at
a time specified by the Secretary, we
reduce the otherwise applicable annual
update to the standard Federal rate by
2.0 percentage points with respect to the
applicable fiscal year.
(b) Participation in the IPFQR
Program. To participate in the IPFQR
Program, an IPF (as defined under
§ 412.402) that is paid under the IPF
PPS must:
(1) Register on the QualityNet website
before beginning to report data;
(2) Identify and register a QualityNet
security official as part of the
registration process under paragraph
(b)(1) of this section; and
(3) Submit a notice of participation
(NOP).
(c) Withdrawal from the IPFQR
Program. An IPF may withdraw from
the IPFQR Program by changing the
NOP status in the secure portion of the
QualityNet website. The IPF may
withdraw at any time up to and
including August 15 before the
beginning of each respective payment
determination year. A withdrawn IPF is
subject to a reduced annual payment
update as specified under paragraph (a)
of this section and is required to renew
participation as specified in paragraph
(b) of this section in order to participate
in any future year of the IPFQR
Program.
(d) Submission of IPFQR Program
data. General rule. Except as provided
in paragraph (f) of this section, IPFs that
participate in the IPFQR Program must
submit to CMS data on measures
selected under section 1886(s)(4)(D) of
the Act and specified non-measure data
in a form and manner, and at a time
specified by CMS.
(e) Quality measure updates,
retention, and removal. (1) CMS uses
rulemaking to make substantive updates
to the specifications of measures used in
the IPFQR Program
(2) General rule for the retention of
Quality Measures. Quality measures
adopted for the IPFQR Program measure
set for a previous payment
determination year are retained for use
in subsequent payment determination
years, except when they are removed,
suspended, or modified as set forth in
paragraph (3) of this section.
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(3) Measure removal, suspension, or
modification through the rulemaking
process. CMS will use the regular
rulemaking process to remove, suspend,
or modify quality measures in the
IPFQR Program to allow for public
comment.
(i) Factors for consideration in
removal or replacement of quality
measures. CMS will weigh whether to
remove or modify measures based on
the following factors:
(A) Factor 1: Measure performance
among IPFs is so high and unvarying
that meaningful distinctions and
improvements in performance can no
longer be made;
(B) Factor 2: Measure does not align
with current clinical guidelines or
practice;
(C) Factor 3: Measure can be replaced
by a more broadly applicable measure
(across settings or populations) or a
measure that is more proximal in time
to desired patient outcomes for the
particular topic;
(D) Factor 4: Measure performance or
improvement does not result in better
patient outcomes;
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(E) Factor 5: Measure can be replaced
by a measure that is more strongly
associated with desired patient
outcomes for the particular topic;
(F) Factor 6: Measure collection or
public reporting leads to negative
unintended consequences other than
patient harm;
(G) Factor 7: Measure is not feasible
to implement as specified; and
(H) Factor 8: The costs associated
with a measure outweigh the benefit of
its continued use in the program.
(ii) Retention. CMS may retain a
quality measure that meets one or more
of the measure removal factors
described in paragraph (i) of this
subsection if the continued collection of
data on the quality measure would align
with other CMS and HHS policy goals,
align with other CMS programs, or
support efforts to move IPFs toward
reporting electronic measures.
(f) Extraordinary circumstances
exception. CMS may grant an exception
to one or more data submissions
deadlines and requirements in the event
of extraordinary circumstances beyond
the control of the IPF, such as when an
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act of nature affects an entire region or
locale or a systemic problem with one
of CMS’s data collection systems
directly or indirectly affects data
submission. CMS may grant an
exception as follows:
(1) Upon request by the IPF.
(2) At the discretion of CMS. CMS
may grant exceptions to IPFs that have
not requested them when CMS
determines that an extraordinary
circumstance has occurred.
(g) Public reporting of IPFQR Program
data. Data that an IPF submits to CMS
for the IPFQR Program will be made
publicly available on a CMS website
after providing the IPF an opportunity
to review the data to be made public.
IPFs will have a period of 30 days to
review and submit corrections to errors
resulting from CMS calculations prior to
the data being made public.
Dated: March 31, 2023.
Xavier Becerra,
Secretary, Department of Health and Human
Services.
[FR Doc. 2023–07122 Filed 4–4–23; 4:15 pm]
BILLING CODE 4120–01–P
E:\FR\FM\10APP2.SGM
10APP2
Agencies
[Federal Register Volume 88, Number 68 (Monday, April 10, 2023)]
[Proposed Rules]
[Pages 21238-21314]
From the Federal Register Online via the Government Publishing Office [www.gpo.gov]
[FR Doc No: 2023-07122]
[[Page 21237]]
Vol. 88
Monday,
No. 68
April 10, 2023
Part II
Department of Health and Human Services
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Centers for Medicare & Medicaid Services
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42 CFR Part 412
Medicare Program; FY 2024 Inpatient Psychiatric Facilities Prospective
Payment System--Rate Update; Proposed Rule
Federal Register / Vol. 88 , No. 68 / Monday, April 10, 2023 /
Proposed Rules
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DEPARTMENT OF HEALTH AND HUMAN SERVICES
Centers for Medicare & Medicaid Services
42 CFR Part 412
[CMS-1783-P]
RIN 0938-AV06
Medicare Program; FY 2024 Inpatient Psychiatric Facilities
Prospective Payment System--Rate Update
AGENCY: Centers for Medicare & Medicaid Services (CMS), Department of
Health and Human Services (HHS).
ACTION: Proposed rule.
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SUMMARY: This proposed rule would update the prospective payment rates,
the outlier threshold, and the wage index for Medicare inpatient
hospital services provided by Inpatient Psychiatric Facilities (IPF),
which include psychiatric hospitals and excluded psychiatric units of
an acute care hospital or critical access hospital. These proposed
changes would be effective for IPF discharges occurring during the
Fiscal Year (FY) beginning October 1, 2023 through September 30, 2024
(FY 2024). In addition, this proposed rule discusses proposals on
quality measures and reporting requirements under the Inpatient
Psychiatric Facilities Quality Reporting (IPFQR) Program with proposed
changes beginning with the FY 2024 payment determination through
changes beginning with the FY 2028 payment determination.
DATES: To be assured consideration, comments must be received at one of
the addresses provided below, by June 5, 2023.
ADDRESSES: In commenting, please refer to file code CMS-1783-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 https://www.regulations.gov. Follow the ``Submit a
comment'' instructions.
2. By regular mail. You may mail written comments to the following
address ONLY: Centers for Medicare & Medicaid Services, Department of
Health and Human Services, Attention: CMS-1783-P, P.O. Box 8010,
Baltimore, MD 21244-8010.
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-1783-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: Mollie Knight (410) 786-7948 or
Bridget Dickensheets (410) 786-8670, for information regarding the
market basket update or the labor-related share.
Nick Brock (410) 786-5148 or Theresa Bean (410) 786-2287, for
information regarding the regulatory impact analysis.
Lauren Lowenstein-Turner, (410) 786-4507, for information regarding
the inpatient psychiatric facilities quality reporting 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: https://www.regulations.gov. Follow the search instructions on that website to
view public comments. CMS will not post on Regulations.gov public
comments that make threats to individuals or institutions or suggest
that the individual will take actions to harm the individual. CMS
continues to encourage individuals not to submit duplicative comments.
We will post acceptable comments from multiple unique commenters even
if the content is identical or nearly identical to other comments.
Availability of Certain Tables Exclusively Through the Internet on the
CMS Website
Addendum A to this proposed rule summarizes the FY 2024 IPF PPS
payment rates, outlier threshold, cost of living adjustment factors
(COLA) for Alaska and Hawaii, national and upper limit cost-to-charge
ratios, and adjustment factors. In addition, the B Addenda to this
proposed rule shows the complete listing of ICD-10 Clinical
Modification (CM) and Procedure Coding System (PCS) codes, the FY 2024
IPF PPS comorbidity adjustment, and electroconvulsive therapy (ECT)
procedure codes. The A and B Addenda are available online at: https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/InpatientPsychFacilPPS/tools.html.
Tables setting forth the FY 2024 Wage Index for Urban Areas Based
on Core Based Statistical Area (CBSA) Labor Market Areas and the FY
2024 Wage Index Based on CBSA Labor Market Areas for Rural Areas are
available exclusively through the internet, on the CMS website at
https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/IPFPPS/WageIndex.html.
I. Executive Summary
A. Purpose
This proposed rule would rebase and revise the market basket for
the Inpatient Psychiatric Facility Prospective Payment System (IPF PPS)
to reflect a 2021 base year, and update the prospective payment rates,
the outlier threshold, and the wage index for Medicare inpatient
hospital services provided by Inpatient Psychiatric Facilities (IPFs)
for discharges occurring during Fiscal Year (FY) 2024, (beginning
October 1, 2023 through September 30, 2024). This rule also includes a
proposal to modify our regulations to make it easier for hospitals to
open new excluded psychiatric units paid under the IPF PPS. In
addition, this proposed rule includes a request for information to
inform revisions to the IPF PPS adjustments for FY 2025, as required by
the Consolidated Appropriations Act, 2023 (hereafter referred to as
CAA, 2023) (Pub. L. 116-260). Lastly, this proposed rule discusses
proposals on quality measures and reporting requirements under the
Inpatient Psychiatric Facilities Quality Reporting (IPFQR) Program.
B. Summary of the Major Provisions
1. Inpatient Psychiatric Facilities Prospective Payment System (IPF
PPS)
For the IPF PPS, we propose to:
Modify the regulations to allow the status of a hospital
psychiatric unit to be changed from not excluded to excluded, and
therefore paid under the IPF PPS at any time during a cost reporting
period if certain requirements are met.
Solicit comments to inform revisions to IPF PPS payments
for FY 2025, as required by the CAA, 2023.
Revise and rebase the IPF market basket to reflect a 2021
base year.
Make technical rate setting updates: The IPF PPS payment
rates would be adjusted annually for inflation, as well as statutory
and other policy factors.
This rule proposes to update:
++ The IPF PPS Federal per diem base rate from $865.63 to $892.58.
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++ The IPF PPS Federal per diem base rate for providers who failed
to report quality data to $875.25.
++ The electroconvulsive therapy (ECT) payment per treatment from
$372.67 to $384.27.
++ The ECT payment per treatment for providers who failed to report
quality data to $376.81.
++ The labor-related share from 77.4 percent to 78.5 percent.
++ The wage index budget-neutrality factor to 1.0011.
++ The fixed dollar loss threshold amount from $24,630 to $34,750
to maintain estimated outlier payments at 2 percent of total estimated
aggregate IPF PPS payments.
2. Inpatient Psychiatric Facilities Quality Reporting (IPFQR) Program
For the IPFQR Program, we propose to:
Adopt the Facility Commitment to Health Equity measure
beginning with the FY 2026 payment determination;
Adopt the Screening for Social Drivers of Health measure
beginning with voluntary reporting of CY 2024 data and beginning with
required reporting of CY 2025 data for the FY 2027 payment
determination;
Adopt the Screen Positive Rate for Social Drivers of
Health measure beginning with voluntary reporting of CY 2024 data and
beginning with required reporting of CY 2025 data for the FY 2027
payment determination;
Adopt the Psychiatric Inpatient Experience (PIX) survey to
measure patient experience of care in the IPF setting beginning with
voluntary reporting of CY 2025 data and beginning with required
reporting of CY 2026 data for the FY 2028 payment determination;
Modify the Coronavirus disease 2019 (COVID-19) Vaccination
Coverage Among Health Care Personnel (HCP) measure to apply the Centers
for Disease Control and Prevention's (CDC's) definition of ``up-to-
date'' for COVID-19 vaccination, incorporating booster doses, beginning
with fourth quarter CY 2023 data for FY 2025 payment determination and,
following this first single-quarter reporting period, reporting for
full calendar year beginning with CY 2024 data for FY 2026 payment
determination;
Remove the following two measures beginning with the FY
2025 payment determination and subsequent years:
++ Patients Discharged on Multiple Antipsychotic Medications with
Appropriate Justification (HBIPS-5); and
++ Tobacco Use Brief Intervention Provided or Offered and Tobacco
Use Brief Intervention Provided (TOB-2/2a) measure;
Adopt a data validation pilot program starting with data
submitted in CY 2025 and continuing until a full data validation
program is proposed and adopted in future rulemaking; and
Codify the IPFQR Program's procedural requirements related
to statutory authority, participation and withdrawal, data submission,
quality measure retention and removal, extraordinary circumstances
exceptions, and public reporting at 42 CFR 412.433 Procedural
requirements under the IPFQR Program.
C. Summary of Impacts
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Provision description Total transfers & cost reductions
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FY 2024 IPF PPS payment The overall economic impact of this
update. proposed rule is an estimated $55
million in increased payments to IPFs
during FY 2024.
FY 2024 IPFQR Program update. The overall economic impact of the IPFQR
Program proposals in this proposed rule
is an estimated decrease of 505,247
hours in information collection burden
resulting in a savings of $12,431,700.
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II. Background
A. Overview of the Legislative Requirements of the IPF PPS
Section 124 of the Medicare, Medicaid, and State Children's Health
Insurance Program Balanced Budget Refinement Act of 1999 (BBRA) (Pub.
L. 106-113) required the establishment and implementation of an IPF
PPS. Specifically, section 124 of the BBRA mandated that the Secretary
of the Department of Health and Human Services (the Secretary) develop
a per diem payment perspective system (PPS) for inpatient hospital
services furnished in psychiatric hospitals and excluded psychiatric
units including an adequate patient classification system that reflects
the differences in patient resource use and costs among psychiatric
hospitals and excluded psychiatric units. ``Excluded psychiatric unit''
means a psychiatric unit of an acute care hospital or of a Critical
Access Hospital (CAH), which is excluded from payment under the
Inpatient Prospective Payment System (IPPS) or CAH payment system,
respectively. These excluded psychiatric units will be paid under the
IPF PPS.
Section 405(g)(2) of the Medicare Prescription Drug, Improvement,
and Modernization Act of 2003 (MMA) (Pub. L. 108-173) extended the IPF
PPS to psychiatric distinct part units of CAHs.
Sections 3401(f) and 10322 of the Patient Protection and Affordable
Care Act (Pub. L. 111-148) as amended by section 10319(e) of that Act
and by section 1105(d) of the Health Care and Education Reconciliation
Act of 2010 (Pub. L. 111-152) (hereafter referred to jointly as ``the
Affordable Care Act'') added subsection (s) to section 1886 of the
Social Security Act (the Act).
Section 1886(s)(1) of the Act titled, ``Reference to Establishment
and Implementation of System,'' refers to section 124 of the BBRA,
which relates to the establishment of the IPF PPS.
Section 1886(s)(2)(A)(i) of the Act requires the application of the
productivity adjustment described in section 1886(b)(3)(B)(xi)(II) of
the Act to the IPF PPS for the rate year (RY) beginning in 2012 (that
is, a RY that coincides with a FY) and each subsequent RY.
Section 1886(s)(2)(A)(ii) of the Act required the application of an
``other adjustment'' that reduced any update to an IPF PPS base rate by
a percentage point amount specified in section 1886(s)(3) of the Act
for the RY beginning in 2010 through the RY beginning in 2019. As noted
in the FY 2020 IPF PPS final rule, for the RY beginning in 2019,
section 1886(s)(3)(E) of the Act required that the other adjustment
reduction be equal to 0.75 percentage point; that was the final year
the statute required the application of this adjustment. Because FY
2021 was a RY beginning in 2020, FY 2021 was the first-year section
1886(s)(2)(A)(ii) of the Act did not apply since its enactment.
Sections 1886(s)(4)(A) through (D) of the Act require that for RY
2014 and each subsequent RY, IPFs that fail to report required quality
data with respect to such a RY will have their annual update to a
standard Federal rate for discharges reduced by 2.0 percentage points.
This may result in an annual update being less than 0.0 for a RY, and
may result in payment rates for the upcoming RY being less than such
payment rates for the preceding RY. Any reduction for failure to report
required quality data will apply only to the RY involved, and the
Secretary will not consider such reduction in
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computing the payment amount for a subsequent RY. In addition, section
4125 of the CAA, 2023 requires that a patients' perspective of care
quality measure be added to the IPFQR Program not later than for FY
2031. Additional information about the specifics of the current IPFQR
Program is available in the FY 2022 IPF PPS and Quality Reporting
Updates for FY Beginning October 1, 2021 final rule (86 FR 42624
through 42661).
Section 4125 of the CAA, 2023 also requires revisions to the
Medicare prospective payment system (PPS) for psychiatric hospitals and
psychiatric units. Specifically, section 4125(a) of the CAA, 2023
amends section 1886(s) of the Act by adding a new paragraph (5) that
requires the Secretary to collect data and information beginning no
later than October 1, 2023, as the Secretary determines appropriate, to
inform revisions to IPF PPS payments. In addition, the Secretary is
required to implement revisions to the methodology for determining the
payment rates under the IPF PPS for FY 2025 as the Secretary determines
appropriate.
To implement and periodically update the IPF PPS, we have published
various proposed and final rules and notices in the Federal Register.
For more information regarding these documents, see the CMS website at
https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/InpatientPsychFacilPPS/?redirect=/InpatientPsychFacilPPS/.
B. Overview of the IPF PPS
On November 15, 2004, we published the IPF PPS final rule in the
Federal Register (69 FR 66922). The November 2004 IPF PPS final rule
established the IPF PPS, as required by section 124 of the BBRA and
codified at 42 CFR part 412, subpart N. The November 2004 IPF PPS final
rule set forth the Federal per diem base rate for the implementation
year (the 18-month period from January 1, 2005 through June 30, 2006),
and provided payment for the inpatient operating and capital costs to
IPFs for covered psychiatric services they furnish (that is, routine,
ancillary, and capital costs, but not costs of approved educational
activities, bad debts, and other services or items that are outside the
scope of the IPF PPS). Covered psychiatric services include services
for which benefits are provided under the fee-for-service Part A
(Hospital Insurance Program) of the Medicare program.
The IPF PPS established the Federal per diem base rate for each
patient day in an IPF derived from the national average daily routine
operating, ancillary, and capital costs in IPFs in FY 2002. The average
per diem cost was updated to the midpoint of the first year under the
IPF PPS, standardized to account for the overall positive effects of
the IPF PPS payment adjustments, and adjusted for budget-neutrality.
The Federal per diem payment under the IPF PPS is comprised of the
Federal per diem base rate described previously and certain patient-
and facility-level payment adjustments for characteristics that were
found in the regression analysis to be associated with statistically
significant per diem cost differences; with statistical significance
defined as p less than 0.05. A complete discussion of the regression
analysis that established the IPF PPS adjustment factors can be found
in the November 2004 IPF PPS final rule (69 FR 66933 through 66936).
The patient-level adjustments include age, Diagnosis-Related Group
(DRG) assignment, and comorbidities, as well as adjustments to reflect
higher per diem costs at the beginning of a patient's IPF stay and
lower costs for later days of the stay. Facility-level adjustments
include adjustments for the IPF's wage index, rural location, teaching
status, a cost-of-living adjustment for IPFs located in Alaska and
Hawaii, and an adjustment for the presence of a qualifying emergency
department (ED).
The IPF PPS has additional payment policies for outlier cases,
interrupted stays, and a per treatment payment for patients who undergo
ECT. During the IPF PPS mandatory 3-year transition period, stop-loss
payments were also provided; however, since the transition ended as of
January 1, 2008, these payments are no longer available.
C. Annual Requirements for Updating the IPF PPS
Section 124 of the BBRA did not specify an annual rate update
strategy for the IPF PPS and was broadly written to give the Secretary
discretion in establishing an update methodology. In the November 2004
IPF PPS final rule (69 FR 66922), we implemented the IPF PPS using the
following update strategy:
Calculate the final Federal per diem base rate to be
budget-neutral for the 18-month period of January 1, 2005 through June
30, 2006.
Use a July 1 through June 30 annual update cycle.
Allow the IPF PPS first update to be effective for
discharges on or after July 1, 2006 through June 30, 2007.
In developing the IPF PPS, and to ensure that the IPF PPS can
account adequately for each IPF's case-mix, we performed an extensive
regression analysis of the relationship between the per diem costs and
certain patient and facility characteristics to determine those
characteristics associated with statistically significant cost
differences on a per diem basis. That regression analysis is described
in detail in our November 28, 2003 IPF PPS proposed rule (68 FR 66923;
66928 through 66933) and our November 15, 2004 IPF PPS final rule (69
FR 66933 through 66960). For characteristics with statistically
significant cost differences, we used the regression coefficients of
those variables to determine the size of the corresponding payment
adjustments.
In the November 2004 IPF PPS final rule, we explained the reasons
for delaying an update to the adjustment factors, derived from the
regression analysis, including waiting until we have IPF PPS data that
yields as much information as possible regarding the patient-level
characteristics of the population that each IPF serves. We indicated
that we did not intend to update the regression analysis and the
patient-level and facility-level adjustments until we complete that
analysis. Until that analysis is complete, we stated our intention to
publish a notice in the Federal Register each spring to update the IPF
PPS (69 FR 66966).
On May 6, 2011, we published a final rule in the Federal Register
titled, ``Inpatient Psychiatric Facilities Prospective Payment System--
Update for Rate Year Beginning July 1, 2011 (RY 2012)'' (76 FR 26432),
which changed the payment rate update period to a RY that coincides
with a FY update. Therefore, final rules are now published in the
Federal Register in the summer to be effective on October 1st. When
proposing changes in IPF payment policy, a proposed rule would be
issued in the spring and the final rule in the summer to be effective
on October 1st. For a detailed list of updates to the IPF PPS, we refer
readers to our regulations at 42 CFR 412.428.
The most recent IPF PPS annual update was published in a final rule
on July 29, 2022 in the Federal Register titled, ``Medicare Program; FY
2023 Inpatient Psychiatric Facilities Prospective Payment System--Rate
Update and Quality Reporting--Request for Information'' (87 FR 46846),
which updated the IPF PPS payment rates for FY 2023. That final rule
updated the IPF PPS Federal per diem base rates that were published in
the FY 2022 IPF PPS Rate Update final rule (86 FR 42608) in accordance
with our established policies.
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III. Provisions of the FY 2024 IPF PPS Payment Update
A. Proposed Rebasing and Revising of the Market Basket for the IPF PPS
1. Background
Originally, the input price index used to develop the IPF PPS was
the Excluded Hospital with Capital market basket. This market basket
was based on 1997 Medicare cost reports for Medicare-participating
inpatient rehabilitation facilities (IRFs), IPFs, long-term care
hospitals (LTCHs), cancer hospitals, and children's hospitals. Although
``market basket'' technically describes the mix of goods and services
used in providing health care at a given point in time, this term is
also commonly used to denote the input price index (that is, cost
category weights and price proxies) derived from that market basket.
Accordingly, the term ``market basket,'' as used in this document,
refers to an input price index.
Since the IPF PPS inception, the market basket used to update IPF
PPS payments has been rebased and revised to reflect more recent data
on IPF cost structures. We last rebased and revised the market basket
applicable to the IPF PPS in the FY 2020 IPF PPS final rule (84 FR
38426 through 38447), where we adopted a 2016-based IPF market basket.
The 2016-based IPF market basket used Medicare cost report data for
both Medicare-participating freestanding psychiatric hospitals and
hospital-based psychiatric units. References to the historical market
baskets used to update IPF PPS payments are listed in the FY 2016 IPF
PPS final rule (80 FR 46656). For the FY 2024 IPF PPS proposed rule, we
propose to rebase and revise the IPF market basket to reflect a 2021
base year.
2. Overview of the Proposed 2021-Based IPF Market Basket
The proposed 2021-based IPF market basket is a fixed-weight,
Laspeyres-type price index. A Laspeyres price index measures the change
in price, over time, of the same mix of goods and services purchased in
the base period. Any changes in the quantity or mix of goods and
services (that is, intensity) purchased over time relative to a base
period are not measured.
The index itself is constructed in three steps. First, a base
period is selected (in this proposed rule, we propose to use 2021 as
the base period) and total base period costs are estimated for a set of
mutually exclusive and exhaustive cost categories. Each category is
calculated as a proportion of total costs. These proportions are called
cost weights. Second, each cost category is matched to an appropriate
price or wage variable, referred to as a price proxy. In nearly every
instance, these price proxies are derived from publicly available
statistical series that are published on a consistent schedule
(preferably at least on a quarterly basis). Finally, the cost weight
for each cost category is multiplied by the level of its respective
price proxy. The sum of these products (that is, the cost weights
multiplied by their price index levels) for all cost categories yields
the composite index level of the market basket in a given period.
Repeating this step for other periods produces a series of market
basket levels over time. Dividing an index level for a given period by
an index level for an earlier period produces a rate of growth in the
input price index over that timeframe.
As noted, the market basket is described as a fixed-weight index
because it represents the change in price over time of a constant mix
(quantity and intensity) of goods and services needed to provide IPF
services. The effects on total costs resulting from changes in the mix
of goods and services purchased subsequent to the base period are not
measured. For example, an IPF hiring more nurses after the base period
to accommodate the needs of patients would increase the volume of goods
and services purchased by the IPF, but would not be factored into the
price change measured by a fixed-weight IPF market basket. Only when
the index is rebased would changes in the quantity and intensity be
captured, with those changes being reflected in the cost weights.
Therefore, we rebase the market basket periodically so that the cost
weights reflect recent changes in the mix of goods and services that
IPFs purchase to furnish inpatient care between base periods.
3. Proposed Rebasing and Revising of the IPF PPS Market Basket
As discussed in the FY 2020 IPF PPS final rule (84 FR 38426 through
38447), the 2016-based IPF market basket reflects the Medicare cost
reports for both freestanding and hospital-based IPFs. Beginning with
FY 2024, we propose to rebase and revise the IPF market basket to a
2021 base year reflecting the 2021 Medicare cost report data submitted
by both freestanding and hospital-based IPFs. We provide a detailed
description of our proposed methodology used to develop the 2021-based
IPF market basket below. This proposed methodology is generally similar
to the methodology used to develop the 2016-based IPF market basket. We
solicit public comment on our proposed methodology for developing the
2021-based IPF market basket.
a. Development of Cost Categories and Weights for the Proposed 2021-
Based IPF Market Basket
(1) Use of Medicare Cost Report Data
We propose a 2021-based IPF market basket that consists of seven
major cost categories and a residual derived from the 2021 Medicare
cost reports (CMS Form 2552-10, OMB No. 0938-0050) for freestanding and
hospital-based IPFs. The seven major cost categories are Wages and
Salaries, Employee Benefits, Contract Labor, Pharmaceuticals,
Professional Liability Insurance (PLI), Home Office/Related
Organization Contract Labor, and Capital. The cost reports include
providers whose cost reporting period began on or after October 1, 2020
and before October 1, 2021. As noted previously, the current IPF market
basket is based on 2016 Medicare cost reports and therefore, reflects
the 2016 cost structure for IPFs. As described in the FY 2023 IPF PPS
final rule (87 FR 46849), we received comments on the FY 2023 IPF PPS
proposed rule (87 FR 19418 through 19419) where stakeholders expressed
concern that the proposed market basket update inadequately reflected
the input price inflation experienced by IPFs, particularly as a result
of the COVID-19 PHE. These commenters stated that the PHE, along with
inflation, has significantly driven up operating costs. Specifically,
some commenters noted changes to labor markets that led to the use of
more contract labor, a trend that we verified in analyzing the Medicare
cost reports through 2021. Therefore, we believe it is appropriate to
incorporate more recent data to reflect updated cost structures for
IPFs, and so we propose to use 2021 as the base year because we believe
that the Medicare cost reports for this year represent the most recent
complete set of Medicare cost report data available for developing the
proposed IPF market basket at the time of this rulemaking. Given the
potential impact of the PHE on the Medicare cost report data, we will
continue to monitor these data going forward and any changes to the IPF
market basket would be proposed in future rulemaking.
Similar to the Medicare cost report data used to develop the 2016-
based IPF market basket, the Medicare cost report data for 2021 show
large differences between some providers' Medicare length of stay (LOS)
and total facility LOS. Our goal has always been to measure cost
weights that are reflective
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of case mix and practice patterns associated with providing services to
Medicare beneficiaries. Therefore, we propose to limit our selection of
Medicare cost reports used in the proposed 2021-based IPF market basket
to those facilities that had a Medicare LOS within a comparable range
of their total facility average LOS. The Medicare average LOS for
freestanding IPFs is calculated from data reported on line 14 of
Worksheet S-3, part I. The Medicare average LOS for hospital-based IPFs
is calculated from data reported on line 16 of Worksheet S-3, part I.
To derive the proposed 2021-based IPF market basket, for those IPFs
with an average facility LOS of greater than or equal to 15 days, we
propose to include IPFs where the Medicare LOS is within 50 percent
(higher or lower) of the average facility LOS. For those IPFs whose
average facility LOS is less than 15 days, we propose to include IPFs
where the Medicare LOS is within 95 percent (higher or lower) of the
facility LOS. We propose to apply this LOS edit to the data for IPFs to
exclude providers that serve a population whose LOS would indicate that
the patients served are not consistent with a LOS of a typical Medicare
patient. This is the same LOS edit applied to the 2016-based IPF market
basket.
Applying these trims to the approximate 1,370 total cost reports
(freestanding and hospital-based) resulted in roughly 1,250 IPF
Medicare cost reports with an average Medicare LOS of 13 days, average
facility LOS of 10 days, and Medicare utilization (as measured by
Medicare inpatient IPF days as a percentage of total facility days) of
16 percent. Providers excluded from the proposed 2021-based IPF market
basket (about 120 Medicare cost reports) had an average Medicare LOS of
21 days, average facility LOS of 41 days, and a Medicare utilization of
3 percent. Of those excluded, about 62 percent of these were
freestanding providers; on the other hand, freestanding providers
represent about 38 percent of all IPFs. We note that 70 percent of
those excluded from the 2016-based IPF market basket using this LOS
edit were freestanding providers.
We then propose to use the cost reports for IPFs that met this
requirement to calculate the costs for the seven major cost categories
(Wages and Salaries, Employee Benefits, Contract Labor, Professional
Liability Insurance, Pharmaceuticals, Home Office/Related Organization
Contract Labor, and Capital) for the market basket. These are the same
categories used for the 2016-based IPF market basket. Also, as
described in section III.A.3.a.(4) of this proposed rule, and as done
for the 2016-based IPF market basket, we propose to use the Medicare
cost report data to calculate the detailed capital cost weights for the
Depreciation, Interest, Lease, and Other Capital-related cost
categories. We also propose to rename the Home Office Contract Labor
cost category to the Home Office/Related Organization Contract Labor
cost category to be more consistent with the Medicare cost report
instructions.
Similar to the 2016-based IPF market basket major cost weights, for
the majority of the proposed 2021-based IPF market basket cost weights,
we propose to divide the costs for each cost category by total Medicare
allowable costs (routine, ancillary and capital)--costs that are
eligible for payment through the IPF PPS (we note that we use total
facility medical care costs as the denominator to derive both the PLI
and Home Office/Related Organization Contract Labor cost weights). We
next describe our proposed methodology for deriving the cost levels
used to derive the proposed 2021-based IPF market basket.
(a) Total Medicare Allowable Costs
For freestanding IPFs, we propose that total Medicare allowable
costs would be equal to the sum of total costs for the Medicare
allowable cost centers as reported on Worksheet B, part I, column 26,
lines 30 through 35, 50 through 76 (excluding 52 and 75), 90 through
91, and 93.
For hospital-based IPFs, we propose that total Medicare allowable
costs would be equal to the total costs for the IPF inpatient unit
after the allocation of overhead costs (Worksheet B, part I, column 26,
line 40) and a proportion of total ancillary costs reported on
Worksheet B, part I, column 26, lines 50 through 76 (excluding 52 and
75), 90 through 91, and 93.
We propose to calculate total ancillary costs attributable to the
hospital-based IPF by first deriving an ``IPF ancillary ratio'' for
each ancillary cost center. The IPF ancillary ratio is defined as the
ratio of IPF Medicare ancillary costs for the cost center (as reported
on Worksheet D-3, column 3 for hospital-based IPFs) to total Medicare
ancillary costs for the cost center (equal to the sum of Worksheet D-3,
column 3 for all relevant PPSs [that is, IPPS, IRF, IPF and skilled
nursing facility (SNF)]). For example, if hospital-based IPF Medicare
laboratory costs represent about 2 percent of the total Medicare
laboratory costs for the entire facility, then the IPF ancillary ratio
for laboratory costs would be 2 percent. We believe it is appropriate
to use only a portion of the ancillary costs in the market basket cost
weight calculations since the hospital-based IPF only utilizes a
portion of the facility's ancillary services. We believe the ratio of
reported IPF Medicare costs to reported total Medicare costs provides a
reasonable estimate of the ancillary services utilized, and costs
incurred, by the hospital-based IPF. We propose that this IPF ancillary
ratio for each cost center is also used to calculate Wages and
Salaries, and Capital costs as described below.
Then, for each ancillary cost center, we propose to multiply the
IPF ancillary ratio for the given cost center by the total facility
ancillary costs for that specific cost center (as reported on Worksheet
B, part I, column 26) to derive IPF ancillary costs. For example, the 2
percent IPF ancillary ratio for laboratory cost center would be
multiplied by the total ancillary costs for laboratory (Worksheet B,
part I, column 26, line 60). The IPF ancillary costs for each cost
center are then added to total costs for the IPF inpatient unit after
the allocation of overhead costs (Worksheet B, part I, column 26, line
40) to derive total Medicare allowable costs.
We propose to use these methods to derive levels of total Medicare
allowable costs for IPF providers. This is the same methodology used
for the 2016-based IPF market basket. We propose that these total
Medicare allowable costs for the IPF will be the denominator for the
cost weight calculations for the Wages and Salaries, Employee Benefits,
Contract Labor, Pharmaceuticals, and Capital cost weights. With this
work complete, we then set about deriving cost levels for the seven
major cost categories and then derive a residual cost weight reflecting
all other costs not classified.
(b) Wages and Salaries Costs
For freestanding IPFs, we propose to derive Wages and Salaries
costs as the sum of routine inpatient salaries (Worksheet A, column 1,
lines 30 through 35), ancillary salaries (Worksheet A, column 1, lines
50 through 76 (excluding 52 and 75), 90 through 91, and 93), and a
proportion of overhead (or general service cost centers in the Medicare
cost reports) salaries. Since overhead salary costs are attributable to
the entire IPF, we only include the proportion attributable to the
Medicare allowable cost centers. We propose to estimate the proportion
of overhead salaries that are attributed to Medicare allowable costs
centers by multiplying the ratio of Medicare allowable area salaries
(Worksheet A, column 1, lines 30 through 35, 50
[[Page 21243]]
through 76 (excluding 52 and 75), 90 through 91, and 93) to total non-
overhead salaries (Worksheet A, column 1, line 200 less Worksheet A,
column 1, lines 4 through 18) times total overhead salaries (Worksheet
A, column 1, lines 4 through 18). This is a similar methodology as used
in the 2016-based IPF market basket.
For hospital-based IPFs, we propose to derive Wages and Salaries
costs as the sum of the following salaries attributable to the
hospital-based IPF: Inpatient routine salary costs (Worksheet A, column
1, line 40); overhead salary costs; ancillary salary costs; and a
portion of overhead salary costs attributable to the ancillary
departments.
(i) Overhead Salary Costs
We propose to calculate the portion of overhead salary cost
attributable to hospital-based IPFs by first calculating an IPF
overhead salary ratio, which is equal to the ratio of total facility
overhead salaries (as reported on Worksheet A, column 1, lines 4-18) to
total facility noncapital overhead costs (as reported on Worksheet A,
column 1 and 2, lines 4-18). We then propose to multiply this IPF
overhead salary ratio by total noncapital overhead costs (sum of
Worksheet B, part I, columns 4 through 18, line 40, less Worksheet B,
part II, columns 4 through 18, line 40). This methodology assumes the
proportion of total costs related to salaries for the overhead cost
center is similar for all inpatient units (that is, acute inpatient or
inpatient psychiatric).
(ii) Ancillary Salary Costs
We propose to calculate hospital-based IPF ancillary salary costs
for a specific cost center (Worksheet A, column 1, lines 50 through 76
(excluding 52 and 75), 90 through 91, and 93) as salary costs from
Worksheet A, column 1, multiplied by the IPF ancillary ratio for each
cost center as described in section III.A.3.a.(1)(a) of this proposed
rule. The sum of these costs represents hospital-based IPF ancillary
salary costs.
(iii) Overhead Salary Costs for Ancillary Cost Centers
We propose to calculate the portion of overhead salaries
attributable to each ancillary department (lines 50 through 76
(excluding 52 and 75), 90 through 91, and 93) by first calculating
total noncapital overhead cost attributable to each specific ancillary
department (sum of Worksheet B, part I, columns 4-18, less Worksheet B,
part II, column 26). We then identify the portion of these total
noncapital overhead cost for each ancillary department that is
attributable to the hospital-based IPF by multiplying these costs by
the IPF ancillary ratio as described in section III.A.3.a.(1)(a) of
this proposed rule. We then sum these estimated IPF Medicare allowable
noncapital overhead costs for all ancillary departments (cost centers
50 through 76, 90 through 91, and 93). Finally, we then identify the
portion of these IPF Medicare allowable noncapital overhead cost that
are attributable to Wages and Salaries by multiplying these costs by
the IPF overhead salary ratio as described in section
III.A.3.a.(1)(b)(i) of this proposed rule. This is the same methodology
used to derive the 2016-based IPF market basket.
(c) Employee Benefits Costs
Effective with the implementation of CMS Form 2552-10, we began
collecting Employee Benefits and Contract Labor data on Worksheet S-3,
part V.
For the 2021 Medicare cost report data, the majority of IPF
providers did not report data on Worksheet S-3, part V. Two percent of
freestanding IPFs and roughly 48 percent of hospital-based IPFs
reported Employee Benefits data on Worksheet S-3, part V. Two percent
of freestanding IPFs and roughly 13 percent of hospital-based IPFs
reported Contract Labor data on Worksheet S-3, part V. We continue to
encourage all providers to report these data on the Medicare cost
report.
For freestanding IPFs, we propose that Employee Benefits cost would
be equal to the data reported on Worksheet S-3, part V, column 2, line
2. We note that while not required to do so, freestanding IPFs also may
report Employee Benefits data on Worksheet S-3, part II, which is
applicable to only IPPS providers. Similar to the method for the 2016-
based IPF market basket, for those freestanding IPFs that report
Worksheet S-3, part II, data, but not Worksheet S-3, part V, we propose
to use the sum of Worksheet S-3, part II, lines 17, 18, 20, and 22, to
derive Employee Benefits costs.
For hospital-based IPFs, we propose to calculate total benefit cost
as the sum of inpatient unit benefit cost, a portion of ancillary
departments benefit costs, and a portion of overhead benefits
attributable to both the routine inpatient unit and the ancillary
departments. For those hospital-based IPFs that report Worksheet S-3,
part V data, we propose inpatient unit benefit costs be equal to
Worksheet S-3, part V, column 2, line 3. Given the limited reporting on
Worksheet S-3, part V, we propose that for those hospital-based IPFs
that do not report these data, we calculate inpatient unit benefits
cost using a portion of benefits cost reported for Excluded areas on
Worksheet S-3, part II. We propose to calculate the ratio of inpatient
unit salaries (Worksheet A, column 1, line 40) to total excluded area
salaries (sum of Worksheet A, column 1, lines 20, 23, 40 through 42,
44, 45, 46, 94, 95, 98 through 101, 105 through 112, 114, 115 through
117, 190 through 194). We then propose to apply this ratio to Excluded
area benefits (Worksheet S-3, part II, column 4, line 19) to derive
inpatient unit benefits cost for those providers that do not report
benefit costs on Worksheet S-3, part V.
We propose the ancillary departments benefits and overhead benefits
(attributable to both the inpatient unit and ancillary departments)
costs are derived by first calculating the sum of hospital-based IPF
overhead salaries as described in section III.A.3.a.(1)(b)(i) of this
proposed rule, hospital-based IPF ancillary salaries as described in
section III.A.3.a.(1)(b)(ii) of this proposed rule and hospital-based
IPF overhead salaries for ancillary cost centers as described in
section III.A.3.a.(1)(b)(iii) of this proposed rule. This sum is then
multiplied by the ratio of total facility benefits to total facility
salaries, where total facility benefits is equal to the sum of
Worksheet S-3, part II, column 4, lines 17-25, and total facility
salaries is equal to Worksheet S-3, part II, column 4, line 1.
(d) Contract Labor Costs
Contract Labor costs are primarily associated with direct patient
care services. Contract labor costs for other services such as
accounting, billing, and legal are calculated separately using other
government data sources as described in section III.A.3.a.(3) of this
proposed rule. To derive contract labor costs using Worksheet S-3, part
V, data for freestanding IPFs, we propose Contract Labor costs be equal
to Worksheet S-3, part V, column 1, line 2. As we noted for Employee
Benefits, freestanding IPFs also may report Contract Labor data on
Worksheet S-3, part II, which is applicable to only IPPS providers. For
those freestanding IPFs that report Worksheet S-3, part II data, but
not Worksheet S-3, part V, we propose to use the sum of Worksheet S-3,
part II, column 4, lines 11 and 13, to derive Contract Labor costs.
For hospital-based IPFs, we propose that Contract Labor costs be
equal to Worksheet S-3, part V, column 1, line 3. Reporting of this
data continues to be somewhat limited; therefore, we continue to
encourage all providers to report these data on the Medicare cost
report. Given the limited reporting on
[[Page 21244]]
Worksheet S-3, part V, we propose that for those hospital-based IPFs
that do not report these data, we calculate Contract Labor costs using
a portion of contract labor costs reported on Worksheet S-3, part II.
We propose to calculate the ratio of contract labor costs (Worksheet S-
3, part II, column 4, lines 11 and 13) to PPS salaries (Worksheet S-3,
part II, column 4, line 1 less the sum of Worksheet S-3, part II,
column 4, lines 3, 401, 5, 6, 7, 701, 8, 9, 10 less Worksheet A, column
1, line 20 and 23). We then propose to apply this ratio to total
inpatient routine salary costs (Worksheet A, column 1, line 40) to
derive contract labor costs for those providers that do not report
contract labor costs on Worksheet S-3, part V.
(e) Pharmaceuticals Costs
For freestanding IPFs, we propose to calculate pharmaceuticals
costs using non-salary costs reported on Worksheet A, column 7, less
Worksheet A, column 1, for the pharmacy cost center (line 15) and drugs
charged to patients cost center (line 73).
For hospital-based IPFs, we propose to calculate pharmaceuticals
costs as the sum of a portion of the non-salary pharmacy costs and a
portion of the non-salary drugs charged to patient costs reported for
the total facility. We propose that non-salary pharmacy costs
attributable to the hospital-based IPF would be calculated by
multiplying total pharmacy costs attributable to the hospital-based IPF
(as reported on Worksheet B, part I, column 15, line 40) by the ratio
of total non-salary pharmacy costs (Worksheet A, column 2, line 15) to
total pharmacy costs (sum of Worksheet A, columns 1 and 2 for line 15)
for the total facility. We propose that non-salary drugs charged to
patient costs attributable to the hospital-based IPF would be
calculated by multiplying total non-salary drugs charged to patient
costs (Worksheet B, part I, column 0, line 73 plus Worksheet B, part I,
column 15, line 73 less Worksheet A, column 1, line 73) for the total
facility by the ratio of Medicare drugs charged to patient ancillary
costs for the IPF unit (as reported on Worksheet D-3 for hospital-based
IPFs, column 3, line 73) to total Medicare drugs charged to patient
ancillary costs for the total facility (equal to the sum of Worksheet
D-3, column 3, line 73 for all relevant PPS [that is, IPPS, IRF, IPF
and SNF]).
(f) Professional Liability Insurance Costs
For freestanding and hospital-based IPFs, we propose that
Professional Liability Insurance (PLI) costs (often referred to as
malpractice costs) would be equal to premiums, paid losses and self-
insurance costs reported on Worksheet S-2, columns 1 through 3, line
118--the same data used for the 2016-based IPF market basket. For
hospital-based IPFs, we propose to assume that the PLI weight for the
total facility is similar to the hospital-based IPF unit since the only
data reported on this worksheet is for the entire facility, as we
currently have no means to identify the proportion of total PLI costs
that are only attributable to the hospital-based IPF. However, when we
derive the cost weight for PLI for both hospital-based and freestanding
IPFs, we use the total facility medical care costs as the denominator
as opposed to total Medicare allowable costs. For freestanding IPFs and
hospital-based IPFs, we propose to derive total facility medical care
costs as the sum of total costs (Worksheet B, part I, column 26, line
202) less non-reimbursable costs (Worksheet B, part I, column 26, lines
190 through 201). Our assumption is that the same proportion of
expenses are used among each unit of the hospital.
(g) Home Office/Related Organization Contract Labor Costs
For hospital-based IPFs, we propose to calculate the Home Office/
Related Organization Contract Labor costs using data reported on
Worksheet S-3, part II, column 4, lines 1401, 1402, 2550, and 2551.
Similar to the PLI costs, these costs are for the entire facility.
Therefore, when we derive the cost weight for home office/related
organization contract labor costs, we use the total facility medical
care costs as the denominator (reflecting the total facility costs
(Worksheet B, part I, column 26, line 202) less the nonreimbursable
costs reported on lines 190 through 201).
(h) Capital Costs
For freestanding IPFs, we propose that capital costs would be equal
to Medicare allowable capital costs as reported on Worksheet B, part
II, column 26, lines 30 through 35, 50 through 76 (excluding 52 and
75), 90 through 91, and 93.
For hospital-based IPFs, we propose that capital costs would be
equal to IPF inpatient capital costs (as reported on Worksheet B, part
II, column 26, line 40) and a portion of IPF ancillary capital costs.
We calculate the portion of ancillary capital costs attributable to the
hospital-based IPF for a given cost center by multiplying total
facility ancillary capital costs for the specific ancillary cost center
(as reported on Worksheet B, part II, column 26) by the IPF ancillary
ratio as described in section III.A.3.a.(1)(a) of this proposed rule.
(2) Final Major Cost Category Computation
After we derive costs for each of the major cost categories and
total Medicare allowable costs for each provider using the Medicare
cost report data as previously described, we propose to address data
outliers using the following steps. First, for the Wages and Salaries,
Employee Benefits, Contract Labor, Pharmaceuticals, and Capital cost
weights, we first divide the costs for each of these five categories by
total Medicare allowable costs calculated for the provider to obtain
cost weights for the universe of IPF providers. We then propose to trim
the data to remove outliers (a standard statistical process) by: (1)
requiring that major expenses (such as Wages and Salaries costs) and
total Medicare allowable operating costs be greater than zero; and (2)
excluding the top and bottom 5 percent of the major cost weight (for
example, Wages and Salaries costs as a percent of total Medicare
allowable operating costs). We note that missing values are assumed to
be zero consistent with the methodology for how missing values were
treated in the 2016-based IPF market basket. After these outliers have
been excluded, we sum the costs for each category across all remaining
providers. We then divide this by the sum of total Medicare allowable
costs across all remaining providers to obtain a cost weight for the
proposed 2021-based IPF market basket for the given category.
The proposed trimming methodology for the Home Office/Related
Organization Contract Labor and PLI cost weights are slightly different
than the proposed trimming methodology for the other five cost
categories as described above. For these cost weights, since we are
using total facility medical care costs rather than Medicare allowable
costs associated with IPF services, we propose to trim the freestanding
and hospital-based IPF cost weights separately.
For the PLI cost weight, for each of the providers, we first divide
the PLI costs by total facility medical care costs to obtain a PLI cost
weight for the universe of IPF providers. We then propose to trim the
data to remove outliers by: (1) requiring that PLI costs are greater
than zero and are less than total facility medical care costs; and (2)
excluding the top and bottom 5 percent of the major cost weight
trimming freestanding and hospital-based providers separately. After
removing these outliers, we are left with a trimmed data set for both
freestanding
[[Page 21245]]
and hospital-based providers. We propose to separately sum the costs
for each category (freestanding and hospital-based) across all
remaining providers. We next divide this by the sum of total facility
medical care costs across all remaining providers to obtain both a
freestanding cost weight and hospital-based cost weight. Lastly, we
propose to weight these two cost weights together using the Medicare
allowable costs from the sample of freestanding and hospital-based IPFs
that passed the PLI trim (63 percent for hospital-based and 37 percent
for freestanding IPFs) to derive a PLI cost weight for the proposed
2021-based IPF market basket.
For the Home Office/Related Organization Contract Labor cost
weight, for each of the providers, we first divide the home office/
related organization contract labor costs by total facility medical
care costs to obtain a Home Office/Related Organization Contract Labor
cost weight for the universe of IPF providers. Similar to the other
market basket costs weights, we propose to trim the Home Office/Related
Organization Contract Labor cost weight to remove outliers. Since not
all hospital-based IPFs will have home office/related organization
contract labor costs (approximately 80 percent of hospital-based IPFs
report having a home office), we propose to trim the top one percent of
the Home Office/Related Organization Contract Labor cost weight. Using
this proposed methodology, we calculate a Home Office/Related
Organization Contract Labor cost weight for hospital-based IPFs of 5.1
percent.
Freestanding IPFs are not required to complete Worksheet S-3, part
II. Therefore, to estimate the Home Office/Related Organization
Contract Labor cost weight for freestanding IPFs, we propose the
following methodology:
Step 1: Using hospital-based IPFs with a home office and also
passing the 1 percent trim as described, we calculate the ratio of the
Home Office/Related Organization Contract Labor cost weight to the
Medicare allowable non-salary, non-capital cost weight (Medicare
allowable non-salary, non-capital costs as a percent of total Medicare
allowable costs).
Step 2: We identify freestanding IPFs that report a home office on
Worksheet S-2, line 140--roughly 87 percent of freestanding IPFs. We
propose to calculate a Home Office/Related Organization Contract Labor
cost weight for these freestanding IPFs by multiplying the ratio
calculated in Step 1 by the Medicare allowable non-salary, noncapital
cost weight for those freestanding IPFs with a home office.
Step 3: We then calculate the freestanding IPF cost weight by
multiplying the Home Office/Related Organization Contract Labor cost
weight in Step 2 by the total Medicare allowable costs for freestanding
IPFs with a home office as a percent of total Medicare allowable costs
for all freestanding IPFs (87 percent), which derives a freestanding
Home Office/Related Organization Contract Labor cost weight of 4.2
percent.
To calculate the overall Home Office/Related Organization Contract
Labor cost weight for the proposed 2021-based IPF market basket, we
propose to weight together the freestanding Home Office/Related
Organization Contract Labor cost weight (4.2 percent) and the hospital-
based Home Office Contract Labor/Related Organization cost weight (5.1
percent) using total Medicare allowable costs from the sample of
hospital-based IPFs that passed the one percent trim and the universe
of freestanding IPFs. The resulting overall cost weight for Home
Office/Related Organization Contract Labor is 4.7 percent (4.2 percent
x 44 percent + 5.1 percent x 56 percent). This is the same methodology
used to calculate the Home Office/Related Organization Contract Labor
cost weight in the 2016-based IPF market basket.
Finally, we propose to calculate the residual ``All Other'' cost
weight that reflects all remaining costs that are not captured in the
seven cost categories listed. See Table 1 for the resulting cost
weights for these major cost categories that we obtain from the
Medicare cost reports.
Table 1--Major Cost Categories as Derived From Medicare Cost Reports
------------------------------------------------------------------------
Proposed 2021-
Based IPF 2016-Based IPF
Major cost categories market basket market basket
(percent) (percent)
------------------------------------------------------------------------
Wages and Salaries...................... 50.4 51.2
Employee Benefits....................... 13.7 13.5
Contract Labor.......................... 2.8 1.3
Professional Liability Insurance 1.0 0.9
(Malpractice)..........................
Pharmaceuticals......................... 3.6 4.7
Home Office/Related Organization 4.7 3.5
Contract Labor.........................
Capital................................. 7.2 7.1
All Other............................... 16.7 17.9
------------------------------------------------------------------------
As we did for the 2016-based IPF market basket, we propose to
allocate the Contract Labor cost weight to the Wages and Salaries and
Employee Benefits cost weights based on their relative proportions
under the assumption that contract labor costs are comprised of both
wages and salaries, and employee benefits. The Contract Labor
allocation proportion for Wages and Salaries is equal to the Wages and
Salaries cost weight as a percent of the sum of the Wages and Salaries
cost weight and the Employee Benefits cost weight. For this proposed
rule, this rounded percentage is 79 percent; therefore, we propose to
allocate 79 percent of the Contract Labor cost weight to the Wages and
Salaries cost weight and 21 percent to the Employee Benefits cost
weight. This allocation was 81/19 in the 2016-based IPF market basket
(84 FR 38430). Table 2 shows the Wages and Salaries and Employee
Benefit cost weights after Contract Labor cost weight allocation for
both the proposed 2021-based IPF market basket and 2016-based IPF
market basket.
[[Page 21246]]
Table 2--Wages and Salaries and Employee Benefits Cost Weights After
Contract Labor Allocation
------------------------------------------------------------------------
Proposed 2021-
Major cost categories Based IPF 2016-Based IPF
market basket market basket
------------------------------------------------------------------------
Wages and Salaries...................... 52.6 52.2
Employee Benefits....................... 14.3 13.8
------------------------------------------------------------------------
(3) Derivation of the Detailed Operating Cost Weights
To further divide the ``All Other'' residual cost weight estimated
from the 2021 Medicare cost report data into more detailed cost
categories, we propose to use the 2012 Benchmark Input-Output (I-O)
``Use Tables/Before Redefinitions/Purchaser Value'' for North American
Industry Classification System (NAICS) 622000, Hospitals, published by
the Bureau of Economic Analysis (BEA). This data is publicly available
at https://www.bea.gov/industry/io_annual.htmhttps://www.bea.gov/industry/io_annual.htm. For the 2016-based IPF market basket, we also
used the 2012 Benchmark I-O data, the most recent data available at the
time (84 FR 38431).
The BEA Benchmark I-O data are scheduled for publication every 5
years with the most recent data available for 2012. The 2012 Benchmark
I-O data are derived from the 2012 Economic Census and are the building
blocks for BEA's economic accounts. Thus, they represent the most
comprehensive and complete set of data on the economic processes or
mechanisms by which output is produced and distributed.\1\ BEA also
produces Annual I-O estimates; however, while based on a similar
methodology, these estimates reflect less comprehensive and less
detailed data sources and are subject to revision when benchmark data
becomes available. Instead of using the less detailed Annual I-O data,
we propose to inflate the 2012 Benchmark I-O data forward to 2021 by
applying the annual price changes from the respective price proxies to
the appropriate market basket cost categories that are obtained from
the 2012 Benchmark I-O data. We repeat this practice for each year. We
then propose to calculate the cost shares that each cost category
represents of the inflated 2012 data. These resulting 2021 cost shares
are applied to the All Other residual cost weight to obtain the
detailed cost weights for the proposed 2021-based IPF market basket.
For example, the cost for Food: Direct Purchases represents 5.0 percent
of the sum of the ``All Other'' 2012 Benchmark I-O Hospital
Expenditures inflated to 2021; therefore, the Food: Direct Purchases
cost weight represents 5.0 percent of the proposed 2021-based IPF
market basket's ``All Other'' cost category (16.7 percent), yielding a
``final'' Food: Direct Purchases cost weight of 0.8 percent in the
proposed 2021-based IPF market basket (0.05 * 16.7 percent = 0.8
percent).
---------------------------------------------------------------------------
\1\ https://www.bea.gov/papers/pdf/IOmanual_092906.pdf.
---------------------------------------------------------------------------
Using this methodology, we propose to derive seventeen detailed IPF
market basket cost category weights from the proposed 2021-based IPF
market basket residual cost weight (16.7 percent). These categories
are: (1) Electricity and Other Non-Fuel Utilities; (2) Fuel: Oil and
Gas; (3) Food: Direct Purchases; (4) Food: Contract Services; (5)
Chemicals; (6) Medical Instruments; (7) Rubber and Plastics; (8) Paper
and Printing Products; (9) Miscellaneous Products; (10) Professional
Fees: Labor-related; (11) Administrative and Facilities Support
Services; (12) Installation, Maintenance, and Repair Services; (13) All
Other Labor-related Services; (14) Professional Fees: Nonlabor-related;
(15) Financial Services; (16) Telephone Services; and (17) All Other
Nonlabor-related Services.
(4) Derivation of the Detailed Capital Cost Weights
As described in section III.A.3.a.(2) of this proposed rule, we
propose a Capital-Related cost weight of 7.2 percent as obtained from
the 2021 Medicare cost reports for freestanding and hospital-based IPF
providers. We propose to then separate this total Capital-Related cost
weight into more detailed cost categories.
Using 2021 Medicare cost reports, we are able to group Capital-
Related costs into the following categories: Depreciation, Interest,
Lease, and Other Capital-Related costs. For each of these categories,
we propose to determine separately for hospital-based IPFs and
freestanding IPFs what proportion of total capital-related costs the
category represents.
For freestanding IPFs, using Medicare Cost Report data on Worksheet
A-7 part III, we propose to derive the proportions for Depreciation
(column 9), Interest (column 11), Lease (column 10), and Other Capital-
related costs (column 12 through 14), which is similar to the
methodology used for the 2016-based IPF market basket.
For hospital-based IPFs, data for these four categories are not
reported separately for the hospital-based IPF; therefore, we propose
to derive these proportions using data reported on Worksheet A-7 for
the total facility. We are assuming the cost shares for the overall
hospital are representative for the hospital-based IPF unit. For
example, if depreciation costs make up 60 percent of total capital
costs for the entire facility, we believe it is reasonable to assume
that the hospital-based IPF would also have a 60 percent proportion
because it is a unit contained within the total facility. This is the
same methodology used for the 2016-based IPF market basket (84 FR
38431).
To combine each detailed capital cost weight for freestanding and
hospital-based IPFs into a single capital cost weight for the proposed
2021-based IPF market basket, we propose to weight together the shares
for each of the categories (Depreciation, Interest, Lease, and Other
Capital-related costs) based on the share of total capital costs each
provider type represents of the total capital costs for all IPFs for
2021. Applying this methodology results in proportions of total
capital-related costs for Depreciation, Interest, Lease and Other
Capital-related costs that are representative of the universe of IPF
providers. This is the same methodology used for the 2016-based IPF
market basket (84 FR 38432).
Lease costs are unique in that they are not broken out as a
separate cost category in the proposed 2021-based IPF market basket.
Rather, we propose to proportionally distribute these costs among the
cost categories of Depreciation, Interest, and Other Capital-Related
costs, reflecting the assumption that the underlying cost structure of
leases is similar to that of capital-related costs in general. As was
done under the 2016-based IPF market basket, we propose to assume that
10 percent of the lease costs as a proportion of total capital-related
costs represents overhead and assign those costs to the
[[Page 21247]]
Other Capital-Related cost category accordingly. We propose to
distribute the remaining lease costs proportionally across the three
cost categories (Depreciation, Interest, and Other Capital-Related)
based on the proportion that these categories comprise of the sum of
the Depreciation, Interest, and Other Capital-related cost categories
(excluding lease expenses). This would result in three primary capital-
related cost categories in the proposed 2021-based IPF market basket:
Depreciation, Interest, and Other Capital-Related costs. This is the
same methodology used for the 2016-based IPF market basket (84 FR
38432). The allocation of these lease expenses is shown in Table 3.
Finally, we propose to further divide the Depreciation and Interest
cost categories. We propose to separate Depreciation into the following
two categories: (1) Building and Fixed Equipment; and (2) Movable
Equipment. We propose to separate Interest into the following two
categories: (1) Government/Nonprofit; and (2) For-profit.
To disaggregate the Depreciation cost weight, we need to determine
the percent of total Depreciation costs for IPFs that is attributable
to Building and Fixed Equipment, which we hereafter refer to as the
``fixed percentage.'' For the proposed 2021-based IPF market basket, we
propose to use slightly different methods to obtain the fixed
percentages for hospital-based IPFs compared to freestanding IPFs.
For freestanding IPFs, we propose to use depreciation data from
Worksheet A-7 of the 2021 Medicare cost reports. However, for hospital-
based IPFs, we determined that the fixed percentage for the entire
facility may not be representative of the hospital-based IPF unit due
to the entire facility likely employing more sophisticated movable
assets that are not utilized by the hospital-based IPF. Therefore, for
hospital-based IPFs, we propose to calculate a fixed percentage using:
(1) building and fixture capital costs allocated to the hospital-based
IPF unit as reported on Worksheet B, part I, column 1, line 40; and (2)
building and fixture capital costs for the top five ancillary cost
centers utilized by hospital-based IPFs accounting for 82 percent of
hospital-based IPF ancillary total costs: Clinic (Worksheet B, part I,
column 1, line 90), Drugs Charged to Patients (Worksheet B, part I,
column 1, line 73), Emergency (Worksheet B, part I, column 1, line 91),
Laboratory (Worksheet B, part I, column 1, line 60) and Radiology--
Diagnostic (Worksheet B, part I, column 1, line 54). We propose to
weight these two fixed percentages (inpatient and ancillary) using the
proportion that each capital cost type represents of total capital
costs in the proposed 2021-based IPF market basket. We propose to then
weight the fixed percentages for hospital-based and freestanding IPFs
together using the proportion of total capital costs each provider type
represents. For both freestanding and hospital-based IPFs, this is the
same methodology used for the 2016-based IPF market basket (84 FR
38432).
To disaggregate the Interest cost weight, we determined the percent
of total interest costs for IPFs that are attributable to government
and nonprofit facilities, which is hereafter referred to as the
``nonprofit percentage,'' as price pressures associated with these
types of interest costs tend to differ from those for for-profit
facilities. For the 2021-based IPF market basket, we propose to use
interest costs data from Worksheet A-7 of the 2021 Medicare cost
reports for both freestanding and hospital-based IPFs. We propose to
determine the percent of total interest costs that are attributed to
government and nonprofit IPFs separately for hospital-based and
freestanding IPFs. We then propose to weight the nonprofit percentages
for hospital-based and freestanding IPFs together using the proportion
of total capital costs that each provider type represents.
Table 3 provides the proposed detailed capital cost share
composition estimated from the 2021 IPF Medicare cost reports. These
detailed capital cost share composition percentages are applied to the
total Capital-Related cost weight of 7.2 percent explained in detail in
sections III.A.3.a.(1)(h) and III.A.3.a.(2) of this proposed rule.
Table 3--Capital Cost Share Composition for the Proposed 2021-Based IPF
Market Basket
------------------------------------------------------------------------
Capital cost Capital cost
share share
composition composition
before lease after lease
expense expense
allocation allocation
(percent) (percent)
------------------------------------------------------------------------
Depreciation............................ 55 68
Building and Fixed Equipment........ 40 48
Movable Equipment................... 16 19
Interest................................ 17 21
Government/Nonprofit................ 11 13
For Profit.......................... 6 7
Lease................................... 20 ..............
Other Capital-related costs............. 8 12
------------------------------------------------------------------------
* Detail may not add to total due to rounding.
(5) Proposed 2021-Based IPF Market Basket Cost Categories and Weights
Table 4 compares the cost categories and weights for the proposed
2021-based IPF market basket compared to the 2016-based IPF market
basket.
[[Page 21248]]
Table 4--Proposed 2021-Based IPF Market Basket Cost Weights Compared to
2016-Based IPF Market Basket Cost Weights
------------------------------------------------------------------------
Proposed 2021-
based IPF 2016-based IPF
Cost category market basket market basket
cost weight cost weight
------------------------------------------------------------------------
Total................................... 100.0 100.0
Compensation.......................... 66.9 66.0
Wages and Salaries.............. 52.6 52.2
Employee Benefits............... 14.3 13.8
Utilities............................. 1.2 1.1
Electricity and Other Non-Fuel 0.7 0.8
Utilities......................
Fuel: Oil and Gas............... 0.4 0.3
Professional Liability Insurance...... 1.0 0.9
All Other Products and Services....... 23.8 24.9
All Other Products.................. 9.1 10.7
Pharmaceuticals................. 3.6 4.7
Food: Direct Purchases.......... 0.8 0.9
Food: Contract Services......... 1.0 1.0
Chemicals....................... 0.3 0.3
Medical Instruments............. 2.0 2.3
Rubber and Plastics............. 0.3 0.3
Paper and Printing Products..... 0.5 0.5
Miscellaneous Products.......... 0.6 0.7
All Other Services.................. 14.7 14.2
Labor-Related Services............ 7.9 7.7
Professional Fees: Labor-related 4.7 4.4
Administrative and Facilities 0.6 0.6
Support Services...............
Installation, Maintenance, and 1.2 1.3
Repair Services................
All Other: Labor-related 1.4 1.4
Services.......................
Nonlabor-Related Services......... 6.8 6.5
Professional Fees: Nonlabor- 4.9 4.5
related........................
Financial Services.............. 0.7 0.8
Telephone Services.............. 0.2 0.3
All Other: Nonlabor-related 0.9 1.0
Services.......................
Capital-Related Costs................. 7.2 7.1
Depreciation........................ 4.9 5.3
Building and Fixed Equipment.... 3.5 3.7
Movable Equipment............... 1.4 1.5
Interest Costs...................... 1.5 1.2
Government/Nonprofit............ 1.0 0.9
For Profit...................... 0.5 0.3
Other Capital-Related Costs......... 0.8 0.7
------------------------------------------------------------------------
* Detail may not add to total due to rounding.
b. Selection of Price Proxies
After developing the cost weights for the proposed 2021-based IPF
market basket, we select the most appropriate wage and price proxies
currently available to represent the rate of price change for each
expenditure category. For the majority of the cost weights, we base the
price proxies on Bureau of Labor Statistics (BLS) data and grouped them
into one of the following BLS categories:
Employment Cost Indexes (ECIs): measure the rate of change
in employment wage rates and employer costs for employee benefits per
hour worked. These indexes are fixed-weight indexes and strictly
measure the change in wage rates and employee benefits per hour. ECIs
are superior to Average Hourly Earnings (AHE) as price proxies for
input price indexes because they are not affected by shifts in
occupation or industry mix, and because they measure pure price change
and are available by both occupational group and by industry. The
industry ECIs are based on the NAICS and the occupational ECIs are
based on the Standard Occupational Classification System (SOC).
Producer Price Indexes (PPI): measure the average change
over time in the selling prices received by domestic producers for
their output. The prices included in the PPI are from the first
commercial transaction for many products and some services (https://www.bls.gov/ppi/).
Consumer Price Indexes (CPIs): measure the average change
over time in the prices paid by urban consumers for a market basket of
consumer goods and services (https://www.bls.gov/cpi/). CPIs are only
used when the purchases are similar to those of retail consumers rather
than purchases at the wholesale level, or if no appropriate PPIs are
available.
We evaluated the price proxies using the criteria of reliability,
timeliness, availability, and relevance:
Reliability: indicates that the index is based on valid
statistical methods and has low sampling variability. Widely accepted
statistical methods ensure that the data were collected and aggregated
in a way that can be replicated. Low sampling variability is desirable
because it indicates that the sample reflects the typical members of
the population. (Sampling variability is variation that occurs by
chance because only a sample was surveyed rather than the entire
population.)
Timeliness: implies that the proxy is published regularly,
preferably at least once a quarter. The market baskets are updated
quarterly and, therefore, it is important for the underlying price
proxies to be up-to-date, reflecting the
[[Page 21249]]
most recent data available. We believe that using proxies that are
published regularly (at least quarterly, whenever possible) helps to
ensure that we are using the most recent data available to update the
market basket. We strive to use publications that are disseminated
frequently, because we believe that this is an optimal way to stay
abreast of the most current data available.
Availability: means that the proxy is publicly available.
We prefer that our proxies are publicly available because this will
help ensure that our market basket updates are as transparent to the
public as possible. In addition, this enables the public to be able to
obtain the price proxy data on a regular basis.
Relevance: means that the proxy is applicable and
representative of the cost category weight to which it is applied. The
CPIs, PPIs, and ECIs that we selected to propose in this regulation
meet these criteria. Therefore, we believe that they continue to be the
best measure of price changes for the cost categories to which they
would be applied.
Table 13 lists all price proxies that we propose to use for the
2021-based IPF market basket. A detailed explanation of the price
proxies we propose for each cost category weight is provided below.
(1) Price Proxies for the Operating Portion of the Proposed 2021-Based
IPF Market Basket
(a) Wages and Salaries
There is not a published wage proxy that we believe represents the
occupational distribution of workers in IPFs. To measure wage price
growth in the proposed 2021-based IPF market basket, we propose to
apply a proxy blend based on six occupational subcategories within the
Wages and Salaries category, which would reflect the IPF occupational
mix, as was done for the 2016-based IPF market basket.
We propose to use the National Industry-Specific Occupational
Employment and Wage estimates for NAICS 622200, Psychiatric & Substance
Abuse Hospitals, published by the BLS Occupational Employment and Wage
Statistics (OEWS) program, as the data source for the wage cost shares
in the wage proxy blend. We note that in the spring of 2021, the
Occupational Employment Statistics (OES) program began using the name
Occupational Employment and Wage Statistics (OEWS) to better reflect
the range of data available from the program. Data released on or after
March 31, 2021 reflect the new program name. We propose to use May 2021
OEWS data. Detailed information on the methodology for the national
industry-specific occupational employment and wage estimates survey can
be found at https://www.bls.gov/oes/current/oes_tec.htm. For the 2016-
based IPF market basket, we used May 2016 OES data.
Based on the OEWS data, there are six wage subcategories:
Management; NonHealth Professional and Technical; Health Professional
and Technical; Health Service; NonHealth Service; and Clerical. Table 5
lists the 2021 occupational assignments for the six wage subcategories;
these are the same occupational groups used in the 2016-based IPF
market basket.
Table 5--2021 Occupational Assignments for IPF Wage Blend
[2021 Occupational Groupings]
------------------------------------------------------------------------
Group 1 Management
------------------------------------------------------------------------
11-0000.................. Management Occupations.
------------------------------------------------------------------------
Group 2 NonHealth Professional & Technical
------------------------------------------------------------------------
13-0000.................. Business and Financial Operations
Occupations.
15-0000.................. Computer and Mathematical Occupations.
19-0000.................. Life, Physical, and Social Science
Occupations.
23-0000.................. Legal Occupations.
25-0000.................. Educational Instruction and Library
Occupations.
27-0000.................. Arts, Design, Entertainment, Sports, and
Media Occupations.
------------------------------------------------------------------------
Group 3 Health Professional & Technical
------------------------------------------------------------------------
29-1021.................. Dentists, General.
29-1031.................. Dietitians and Nutritionists.
29-1051.................. Pharmacists.
29-1071.................. Physician Assistants.
29-1122.................. Occupational Therapists.
29-1123.................. Physical Therapists.
29-1125.................. Recreational Therapists.
29-1126.................. Respiratory Therapists.
29-1127.................. Speech-Language Pathologists.
29-1129.................. Therapists, All Other.
29-1141.................. Registered Nurses.
29-1171.................. Nurse Practitioners.
29-1215.................. Family Medicine Physicians.
29-1216.................. General Internal Medicine Physicians.
29-1223.................. Psychiatrists.
29-1229.................. Physicians, All Other.
29-1292.................. Dental Hygienists.
29-1299.................. Healthcare Diagnosing or Treating
Practitioners, All Other.
------------------------------------------------------------------------
Group 4 Health Service
------------------------------------------------------------------------
21-0000.................. Community and Social Service Occupations.
29-2010.................. Clinical Laboratory Technologists and
Technicians.
29-2034.................. Radiologic Technologists and Technicians.
29-2042.................. Emergency Medical Technicians.
29-2051.................. Dietetic Technicians.
[[Page 21250]]
29-2052.................. Pharmacy Technicians.
29-2053.................. Psychiatric Technicians.
29-2061.................. Licensed Practical and Licensed Vocational
Nurses.
29-2072.................. Medical Records Specialists.
29-2099.................. Health Technologists and Technicians, All
Other.
29-9021.................. Health Information Technologists and Medical
Registrars.
29-9099.................. Healthcare Practitioners and Technical
Workers, All Other.
31-0000.................. Healthcare Support Occupations.
------------------------------------------------------------------------
Group 5 NonHealth Service
------------------------------------------------------------------------
33-0000.................. Protective Service Occupations.
35-0000.................. Food Preparation and Serving Related
Occupations.
37-0000.................. Building and Grounds Cleaning and Maintenance
Occupations.
39-0000.................. Personal Care and Service Occupations.
41-0000.................. Sales and Related Occupations.
47-0000.................. Construction and Extraction Occupations.
49-0000.................. Installation, Maintenance, and Repair
Occupations.
51-0000.................. Production Occupations.
53-0000.................. Transportation and Material Moving
Occupations.
------------------------------------------------------------------------
Group 6 Clerical
------------------------------------------------------------------------
43-0000.................. Office and Administrative Support
Occupations.
------------------------------------------------------------------------
Total expenditures by occupation (that is, occupational assignment)
were calculated by taking the OEWS number of employees multiplied by
the OEWS annual average salary. These expenditures were aggregated
based on the six groups in Table 5. We next calculated the proportion
of each group's expenditures relative to the total expenditures of all
six groups. These proportions, listed in Table 6, represent the weights
used in the wage proxy blend. We then propose to use the published wage
proxies in Table 6 for each of the six groups (that is, wage
subcategories) as we believe these six price proxies are the most
technically appropriate indices available to measure the price growth
of the Wages and Salaries cost category. These are the same price
proxies used in the 2016-based IPF market basket (84 FR 38437).
Table 6--Proposed 2021-Based IPF Market Basket Wage Proxy Blend
--------------------------------------------------------------------------------------------------------------------------------------------------------
Proposed 2021- 2016-based
based wage wage blend
Wage subcategory blend weights weights Price proxy BLS Series ID
(percent) (percent)
--------------------------------------------------------------------------------------------------------------------------------------------------------
Healthcare Professional and Technical.... 36.9 34.9 ECI for Wages and Salaries for CIU1026220000000I.
All Civilian workers in
Hospitals.
Healthcare Service....................... 34.4 36.3 ECI for Wages and Salaries for CIU1026200000000I.
All Civilian workers in
Healthcare and Social Assistance.
NonHealthcare Service.................... 7.5 8.9 ECI for Wages and Salaries for CIU2020000300000I.
Private Industry workers in
Service Occupations.
NonHealthcare Professional and Technical. 7.3 7.0 ECI for Wages and Salaries for CIU2025400000000I.
Private Industry workers in
Professional, Scientific, and
Technical Services.
Management............................... 7.8 6.8 ECI for Wages and Salaries for CIU2020000110000I.
Private industry workers in
Management, Business, and
Financial.
Administrative Support and Clerical...... 6.1 6.1 ECI for Wages and Salaries for CIU2020000220000I.
Private Industry workers in
Office and Administrative
Support.
--------------------------------
Total................................ 100.0 100.0
--------------------------------------------------------------------------------------------------------------------------------------------------------
A comparison of the yearly changes from FY 2021 to FY 2024 for the
proposed 2021-based IPF wage blend and the 2016-based IPF wage blend is
shown in Table 7. The average annual growth rate is the same for both
price proxies over 2021-2024.
[[Page 21251]]
Table 7--Fiscal Year Growth in the Proposed 2021-Based IPF Wage Proxy Blend and 2016-Based IPF Wage Proxy Blend
----------------------------------------------------------------------------------------------------------------
Average
2021 2022 2023 2024 2021-2024
----------------------------------------------------------------------------------------------------------------
Proposed 2021-based IPF Wage Proxy Blend................. 3.0 5.6 5.1 3.7 4.4
2016-based IPF Wage Proxy Blend.......................... 3.1 5.6 5.2 3.7 4.4
----------------------------------------------------------------------------------------------------------------
** Source: IHS Global Inc., 4th Quarter 2022 forecast with historical data through 3rd Quarter 2022.
(b) Employee Benefits
To measure benefits price growth in the proposed 2021-based IPF
market basket, we propose to apply a benefits proxy blend based on the
same six subcategories and the same six blend weights for the wage
proxy blend. These subcategories and blend weights are listed in Table
8.
The benefit ECIs, listed in Table 8, are not publicly available.
Therefore, an ``ECIs for Total Benefits'' is calculated using publicly
available ``ECIs for Total Compensation'' for each subcategory and the
relative importance of wages within that subcategory's total
compensation. This is the same benefits ECI methodology that we
implemented in our 2016-based IPF market basket as well as used in the
IPPS, SNF, Home Health Agency (HHA), IRF, LTCH, and End-Stage Renal
Disease (ESRD) market baskets. We believe that the six price proxies
listed in Table 8 are the most technically appropriate indices to
measure the price growth of the Employee Benefits cost category in the
proposed 2021-based HHA IPF market basket.
Table 8--Proposed 2021-Based IPF Market Basket Benefits Proxy Blend and 2016-Based IPF Benefit Proxy Blend
----------------------------------------------------------------------------------------------------------------
Proposed 2021- 2016-based
based benefit benefit blend
Wage subcategory blend weight weight Price proxy
(percent) (percent)
----------------------------------------------------------------------------------------------------------------
Healthcare Professional and Technical...... 36.9 34.9 ECI for Total Benefits for All
Civilian workers in Hospitals.
Healthcare Service......................... 34.4 36.3 ECI for Total Benefits for All
Civilian workers in Healthcare and
Social Assistance.
NonHealthcare Service...................... 7.5 8.9 ECI for Total Benefits for Private
Industry workers in Service
Occupations.
NonHealthcare Professional and Technical... 7.3 7.0 ECI for Total Benefits for Private
Industry workers in Professional,
Scientific, and Technical
Services.
Management................................. 7.8 6.8 ECI for Total Benefits for Private
industry workers in Management,
Business, and Financial.
Administrative Support and Clerical........ 6.1 6.1 ECI for Total Benefits for Private
Industry workers in Office and
Administrative Support.
--------------------------------
Total.................................. 100.0 100.0 ...................................
----------------------------------------------------------------------------------------------------------------
A comparison of the yearly changes from FY 2021 to FY 2024 for the
proposed 2021-based IPF benefit proxy blend and the 2016-based IPF
benefit proxy is shown in Table 9. The average annual growth rate is
the same for both price proxies over 2021 through 2024.
Table 9--Fiscal Year Growth in the Proposed 2021-Based IPF Benefit Proxy Blend and 2016-Based IPF Benefit Proxy
Blend
----------------------------------------------------------------------------------------------------------------
Average
2021 2022 2023 2024 2021-2024
----------------------------------------------------------------------------------------------------------------
Proposed 2021-based IPF Benefit Proxy Blend.............. 2.4 4.4 4.4 3.6 3.7
2016-based IPF Benefit Proxy Blend....................... 2.4 4.4 4.4 3.6 3.7
----------------------------------------------------------------------------------------------------------------
Source: IHS Global Inc., 4th Quarter 2022 forecast with historical data through 3rd Quarter 2022.
(c) Electricity and Other Non-Fuel Utilities
We propose to use the PPI Commodity Index for Commercial Electric
Power (BLS series code WPU0542) to measure the price growth of this
cost category (which we propose to rename from Electricity to
Electricity and Other Non-Fuel Utilities). This is the same price proxy
used in the 2016-based IPF market basket (84 FR 38438).
(d) Fuel: Oil and Gas
Similar to the 2016-based IPF market basket, for the 2021-based IPF
market basket, we propose to use a blend of the PPI for Petroleum
Refineries and the PPI Commodity for Natural Gas. Our analysis of the
Bureau of Economic Analysis' 2012 Benchmark Input-Output data (use
table before redefinitions, purchaser's value for NAICS 622000
[[Page 21252]]
[Hospitals]), shows that Petroleum Refineries expenses account for
approximately 90 percent and Natural Gas expenses account for
approximately 10 percent of Hospitals' (NAICS 622000) total Fuel: Oil
and Gas expenses. Therefore, we propose to use a blend of 90 percent of
the PPI for Petroleum Refineries (BLS series code PCU324110324110) and
10 percent of the PPI Commodity Index for Natural Gas (BLS series code
WPU0531) as the price proxy for this cost category. This is the same
blend that was used for the 2016-based IPF market basket (84 FR 38438).
(e) Professional Liability Insurance
We propose to use the CMS Hospital Professional Liability Index to
measure changes in PLI premiums. To generate this index, we collect
commercial insurance premiums for a fixed level of coverage while
holding non-price factors constant (such as a change in the level of
coverage). This is the same proxy used in the 2016-based IPF market
basket (84 FR 38438).
(f) Pharmaceuticals
We propose to use the PPI for Pharmaceuticals for Human Use,
Prescription (BLS series code WPUSI07003) to measure the price growth
of this cost category. This is the same proxy used in the 2016-based
IPF market basket (84 FR 38438).
(g) Food: Direct Purchases
We propose to use the PPI for Processed Foods and Feeds (BLS series
code WPU02) to measure the price growth of this cost category. This is
the same proxy used in the 2016-based IPF market basket (84 FR 38438).
(h) Food: Contract Purchases
We propose to use the CPI for Food Away From Home (BLS series code
CUUR0000SEFV) to measure the price growth of this cost category. This
is the same proxy used in the 2016-based IPF market basket (84 FR
38438).
(i) Chemicals
Similar to the 2016-based IPF market basket, we propose to use a
four-part blended PPI as the proxy for the chemical cost category in
the proposed 2021-based IPF market basket. The proposed blend is
composed of the PPI for Industrial Gas Manufacturing, Primary Products
(BLS series code PCU325120325120P), the PPI for Other Basic Inorganic
Chemical Manufacturing (BLS series code PCU32518-32518-), the PPI for
Other Basic Organic Chemical Manufacturing (BLS series code PCU32519-
32519-), and the PPI for Other Miscellaneous Chemical Product
Manufacturing (BLS series code PCU325998325998). For the proposed 2021-
based IPF market basket, we propose to derive the weights for the PPIs
using the 2012 Benchmark I-O data.
Table 10 shows the weights for each of the four PPIs used to create
the proposed blended Chemical proxy for the proposed 2021-based IPF
market basket. This is the same blend that was used for the 2016-based
IPF market basket (84 FR 38439).
Table 10--Blended Chemical PPI Weights
------------------------------------------------------------------------
Proposed 2021-
based IPF
Name weights NAICS
(percent)
------------------------------------------------------------------------
PPI for Industrial Gas Manufacturing.... 19 325120
PPI for Other Basic Inorganic Chemical 13 325180
Manufacturing..........................
PPI for Other Basic Organic Chemical 60 325190
Manufacturing..........................
PPI for Other Miscellaneous Chemical 8 325998
Product Manufacturing..................
------------------------------------------------------------------------
(j) Medical Instruments
We propose to use a blended price proxy for the Medical Instruments
category, as shown in Table 11. The 2012 Benchmark I-O data shows the
majority of medical instruments and supply costs are for NAICS 339112--
Surgical and medical instrument manufacturing costs (approximately 56
percent) and NAICS 339113--Surgical appliance and supplies
manufacturing costs (approximately 43 percent). Therefore, we propose
to use a blend of these two price proxies. To proxy the price changes
associated with NAICS 339112, we propose to use the PPI for Surgical
and medical instruments (BLS series code WPU1562). This is the same
price proxy we used in the 2016-based IPF market basket. To proxy the
price changes associated with NAICS 339113, we propose to use a 50/50
blend of the PPI for Medical and surgical appliances and supplies (BLS
series code WPU1563) and the PPI for Miscellaneous products, Personal
safety equipment and clothing (BLS series code WPU1571). We propose to
include the latter price proxy as it would reflect personal protective
equipment including but not limited to face shields and protective
clothing. The 2012 Benchmark I-O data does not provide specific
expenses for these products; however, we recognize that this category
reflects costs faced by IPFs.
Table 11--Blended Medical Instruments PPI Weights
------------------------------------------------------------------------
Proposed 2021-
based IPF
Name weights NAICS
(percent)
------------------------------------------------------------------------
PPI--Commodity--Surgical and medical 56 339112
instruments............................
PPI--Commodity--Medical and surgical 22 ..............
appliances and supplies................
PPI--Commodity--Miscellaneous products- 22 339113
Personal safety equipment and clothing.
------------------------------------------------------------------------
(k) Rubber and Plastics
We propose to use the PPI for Rubber and Plastic Products (BLS
series code WPU07) to measure price growth of this cost category. This
is the same proxy used in the 2016-based IPF market basket (84 FR
38439).
[[Page 21253]]
(l) Paper and Printing Products
We propose to use the PPI for Converted Paper and Paperboard
Products (BLS series code WPU0915) to measure the price growth of this
cost category. This is the same proxy used in the 2016-based IPF market
basket (84 FR 38439).
(m) Miscellaneous Products
We propose to use the PPI for Finished Goods Less Food and Energy
(BLS series code WPUFD4131) to measure the price growth of this cost
category. This is the same proxy used in the 2016-based IPF market
basket (84 FR 38439).
(n) Professional Fees: Labor-Related
We propose to use the ECI for Total Compensation for Private
Industry workers in Professional and Related (BLS series code
CIU2010000120000I) to measure the price growth of this category. This
is the same proxy used in the 2016-based IPF market basket (84 FR
38439).
(o) Administrative and Facilities Support Services
We propose to use the ECI for Total Compensation for Private
Industry workers in Office and Administrative Support (BLS series code
CIU2010000220000I) to measure the price growth of this category. This
is the same proxy used in the 2016-based IPF market basket (84 FR
38439).
(p) Installation, Maintenance, and Repair Services
We propose to use the ECI for Total Compensation for Civilian
workers in Installation, Maintenance, and Repair (BLS series code
CIU1010000430000I) to measure the price growth of this cost category.
This is the same proxy used in the 2016-based IPF market basket (84 FR
38439).
(q) All Other: Labor-Related Services
We propose to use the ECI for Total Compensation for Private
Industry workers in Service Occupations (BLS series code
CIU2010000300000I) to measure the price growth of this cost category.
This is the same proxy used in the 2016-based IPF market basket (84 FR
38439).
(r) Professional Fees: Nonlabor-Related
We propose to use the ECI for Total Compensation for Private
Industry workers in Professional and Related (BLS series code
CIU2010000120000I) to measure the price growth of this category. This
is the same proxy used in the 2016-based IPF market basket (84 FR
38439).
(s) Financial Services
We propose to use the ECI for Total Compensation for Private
Industry workers in Financial Activities (BLS series code
CIU201520A000000I) to measure the price growth of this cost category.
This is the same proxy used in the 2016-based IPF market basket (84 FR
38439).
(t) Telephone Services
We propose to use the CPI for Telephone Services (BLS series code
CUUR0000SEED) to measure the price growth of this cost category. This
is the same proxy used in the 2016-based IPF market basket (84 FR
38439).
(u) All Other: Nonlabor-Related Services
We propose to use the CPI for All Items Less Food and Energy (BLS
series code CUUR0000SA0L1E) to measure the price growth of this cost
category. This is the same proxy used in the 2016-based IPF market
basket (84 FR 38439).
(2) Price Proxies for the Capital Portion of the Proposed 2021-Based
IPF Market Basket
(a) Capital Price Proxies Prior to Vintage Weighting
We propose to use the same price proxies for the capital-related
cost categories in the proposed 2021-based IPF market basket as were
used in the 2016-based IPF market basket, which are provided in Table
13 and described below. Specifically, we propose to proxy:
Depreciation: Building and Fixed Equipment cost category
by BEA's Chained Price Index for Nonresidential Construction for
Hospitals and Special Care Facilities (BEA Table 5.4.4. Price Indexes
for Private Fixed Investment in Structures by Type).
Depreciation: Movable Equipment cost category by the PPI
for Machinery and Equipment (BLS series code WPU11).
Nonprofit Interest cost category by the average yield on
domestic municipal bonds (Bond Buyer 20-bond index).
For-profit Interest cost category by the iBoxx AAA
Corporate Bond Yield index
Other Capital-Related cost category by the CPI-U for Rent
of Primary Residence (BLS series code CUUS0000SEHA).
We believe these are the most appropriate proxies for IPF capital-
related costs that meet our selection criteria of relevance,
timeliness, availability, and reliability. We also propose to vintage
weight the capital price proxies for Depreciation and Interest to
capture the long-term consumption of capital. This vintage weighting
method is similar to the method used for the 2016-based IPF market
basket (84 FR 38440) and is described below.
(b) Vintage Weights for Price Proxies
Because capital is acquired and paid for over time, capital-related
expenses in any given year are determined by both past and present
purchases of physical and financial capital. The vintage-weighted
capital-related portion of the proposed 2021-based IPF market basket is
intended to capture the long-term consumption of capital, using vintage
weights for depreciation (physical capital) and interest (financial
capital). These vintage weights reflect the proportion of capital-
related purchases attributable to each year of the expected life of
building and fixed equipment, movable equipment, and interest. We
propose to use vintage weights to compute vintage-weighted price
changes associated with depreciation and interest expenses.
Capital-related costs are inherently complicated and are determined
by complex capital-related purchasing decisions, over time, based on
such factors as interest rates and debt financing. In addition, capital
is depreciated over time instead of being consumed in the same period
it is purchased. By accounting for the vintage nature of capital, we
are able to provide an accurate and stable annual measure of price
changes. Annual non-vintage price changes for capital are unstable due
to the volatility of interest rate changes, and therefore, do not
reflect the actual annual price changes for IPF capital-related costs.
The capital-related component of the proposed 2021-based IPF market
basket reflects the underlying stability of the capital-related
acquisition process.
The methodology used to calculate the vintage weights for the
proposed 2021-based IPF market basket is the same as that used for the
2016-based IPF market basket (84 FR 38439 through 38441) with the only
difference being the inclusion of more recent data. To calculate the
vintage weights for depreciation and interest expenses, we first need a
time series of capital-related purchases for building and fixed
equipment and movable equipment. We found no single source that
provides an appropriate time series of capital-related purchases by
hospitals for all of the above components of capital purchases. The
early Medicare cost reports did not have sufficient capital-related
data to meet this need. Data we obtained from the American Hospital
Association (AHA) do not include annual capital-
[[Page 21254]]
related purchases. However, we are able to obtain data on total
expenses back to 1963 from the AHA. Consequently, we propose to use
data from the AHA Panel Survey and the AHA Annual Survey to obtain a
time series of total expenses for hospitals. We then propose to use
data from the AHA Panel Survey supplemented with the ratio of
depreciation to total hospital expenses obtained from the Medicare cost
reports to derive a trend of annual depreciation expenses for 1963
through 2020, which is the latest year of AHA data available. We
propose to separate these depreciation expenses into annual amounts of
building and fixed equipment depreciation and movable equipment
depreciation as determined earlier. From these annual depreciation
amounts, we derive annual end-of-year book values for building and
fixed equipment and movable equipment using the expected life for each
type of asset category. While data is not available that is specific to
IPFs, we believe this information for all hospitals serves as a
reasonable alternative for the pattern of depreciation for IPFs.
To continue to calculate the vintage weights for depreciation and
interest expenses, we also need to account for the expected lives for
Building and Fixed Equipment, Movable Equipment, and Interest for the
proposed 2021-based IPF market basket. We propose to calculate the
expected lives using Medicare cost report data from freestanding and
hospital-based IPFs. The expected life of any asset can be determined
by dividing the value of the asset (excluding fully depreciated assets)
by its current year depreciation amount. This calculation yields the
estimated expected life of an asset if the rates of depreciation were
to continue at current year levels, assuming straight-line
depreciation. We propose to determine the expected life of building and
fixed equipment separately for hospital-based IPFs and freestanding
IPFs, and then weight these expected lives using the percent of total
capital costs each provider type represents. We propose to apply a
similar method for movable equipment. Using these proposed methods, we
determined the average expected life of building and fixed equipment to
be equal to 25 years, and the average expected life of movable
equipment to be equal to 12 years. For the expected life of interest,
we believe vintage weights for interest should represent the average
expected life of building and fixed equipment because, based on
previous research described in the FY 1997 IPPS final rule (61 FR
46198), the expected life of hospital debt instruments and the expected
life of buildings and fixed equipment are similar. We note that for the
2016-based IPF market basket, the expected life of building and fixed
equipment is 22 years, and the expected life of movable equipment is 11
years (84 FR 38441).
Multiplying these expected lives by the annual depreciation amounts
results in annual year-end asset costs for building and fixed equipment
and movable equipment. We then calculate a time series, beginning in
1964, of annual capital purchases by subtracting the previous year's
asset costs from the current year's asset costs.
For the building and fixed equipment and movable equipment vintage
weights, we propose to use the real annual capital-related purchase
amounts for each asset type to capture the actual amount of the
physical acquisition, net of the effect of price inflation. These real
annual capital-related purchase amounts are produced by deflating the
nominal annual purchase amount by the associated price proxy as
provided earlier in this proposed rule. For the interest vintage
weights, we propose to use the total nominal annual capital-related
purchase amounts to capture the value of the debt instrument
(including, but not limited to, mortgages and bonds). Using these
capital-related purchase time series specific to each asset type, we
propose to calculate the vintage weights for building and fixed
equipment, for movable equipment, and for interest.
The vintage weights for each asset type are deemed to represent the
average purchase pattern of the asset over its expected life (in the
case of building and fixed equipment and interest, 25 years, and in the
case of movable equipment, 12 years). For each asset type, we used the
time series of annual capital-related purchase amounts available from
2020 back to 1964. These data allow us to derive thirty-three 25-year
periods of capital-related purchases for building and fixed equipment
and interest, and forty-six 12-year periods of capital-related
purchases for movable equipment. For each 25-year period for building
and fixed equipment and interest, or 12-year period for movable
equipment, we calculate annual vintage weights by dividing the capital-
related purchase amount in any given year by the total amount of
purchases over the entire 25-year or 12-year period. This calculation
is done for each year in the 25-year or 12-year period and for each of
the periods for which we have data. We then calculate the average
vintage weight for a given year of the expected life by taking the
average of these vintage weights across the multiple periods of data.
The vintage weights for the capital-related portion of the proposed
2021-based IPF market basket and the 2016-based IPF market basket are
presented in Table 12.
Table 12--Proposed 2021-Based IPF Market Basket and 2016-Based IPF Market Basket Vintage Weights for Capital-Related Price Proxies
--------------------------------------------------------------------------------------------------------------------------------------------------------
Building and fixed equipment Movable equipment Interest
-----------------------------------------------------------------------------------------------
Year * 2021-based 25 2016-based 22 2021-based 12 2016-based 11 2021-based 25 2016-based 22
years years years years years years
--------------------------------------------------------------------------------------------------------------------------------------------------------
1....................................................... 0.031 0.035 0.066 0.071 0.018 0.021
2....................................................... 0.032 0.036 0.068 0.075 0.019 0.023
3....................................................... 0.033 0.038 0.071 0.080 0.021 0.025
4....................................................... 0.034 0.038 0.076 0.085 0.023 0.026
5....................................................... 0.035 0.040 0.080 0.087 0.024 0.029
6....................................................... 0.036 0.042 0.082 0.091 0.026 0.031
7....................................................... 0.035 0.042 0.084 0.095 0.026 0.033
8....................................................... 0.036 0.041 0.088 0.099 0.028 0.033
9....................................................... 0.036 0.042 0.091 0.102 0.029 0.036
10...................................................... 0.039 0.043 0.094 0.105 0.033 0.038
11...................................................... 0.040 0.046 0.098 0.110 0.035 0.042
12...................................................... 0.040 0.047 0.101 .............. 0.037 0.045
13...................................................... 0.042 0.048 .............. .............. 0.040 0.048
14...................................................... 0.042 0.049 .............. .............. 0.042 0.052
[[Page 21255]]
15...................................................... 0.042 0.050 .............. .............. 0.044 0.055
16...................................................... 0.043 0.050 .............. .............. 0.046 0.057
17...................................................... 0.044 0.051 .............. .............. 0.049 0.060
18...................................................... 0.045 0.053 .............. .............. 0.052 0.065
19...................................................... 0.045 0.053 .............. .............. 0.054 0.068
20...................................................... 0.045 0.053 .............. .............. 0.055 0.069
21...................................................... 0.045 0.052 .............. .............. 0.057 0.070
22...................................................... 0.045 0.052 .............. .............. 0.058 0.072
23...................................................... 0.045 .............. .............. .............. 0.060 ..............
24...................................................... 0.045 .............. .............. .............. 0.061 ..............
25...................................................... 0.044 .............. .............. .............. 0.062 ..............
-----------------------------------------------------------------------------------------------
Total............................................... 1.000 1.000 1.000 1.000 1.000 1.000
--------------------------------------------------------------------------------------------------------------------------------------------------------
Note: Numbers may not add to total due to rounding.
* Year 25 is applied to the most recent data point when creating the vintage-weighted price proxies.
The process of creating vintage-weighted price proxies requires
applying the vintage weights to the price proxy index where the last
applied vintage weight in Table 12 is applied to the most recent data
point. We have provided on the CMS website an example of how the
vintage weighting price proxies are calculated, using example vintage
weights and example price indices. The example can be found at https://www.cms.gov/Research-Statistics-Data-and-Systems/Statistics-Trends-and-Reports/MedicareProgramRatesStats/MarketBasketResearch.html in the zip
file titled ``Weight Calculations as described in the IPPS FY 2010
Proposed Rule.''
(3) Summary of Price Proxies of the Proposed 2021-Based IPF Market
Basket
Table 13 shows both the operating and capital price proxies for the
proposed 2021-based IPF market basket.
Table 13--Price Proxies for the Proposed 2021-based IPF Market Basket
----------------------------------------------------------------------------------------------------------------
Cost description Price proxies Weight
----------------------------------------------------------------------------------------------------------------
Total.................................... ..................................................... 100.0
Compensation............................. ..................................................... 66.9
Wages and Salaries................... Blended Wages and Salaries Price Proxy............... 52.6
Employee Benefits.................... Blended Employee Benefits Price Proxy................ 14.3
Utilities................................ ..................................................... 1.2
Electricity and Other Non-Fuel PPI for Commercial Electric Power.................... 0.7
Utilities.
Fuel: Oil and Gas.................... Blend of PPIs *...................................... 0.4
Professional Liability Insurance......... ..................................................... 1.0
Malpractice.......................... CMS Hospital Professional Liability Insurance Premium 1.0
Index.
All Other Products and Services.......... ..................................................... 23.8
All Other Products....................... ..................................................... 9.1
Pharmaceuticals...................... PPI for Pharmaceuticals for Human Use, Prescription.. 3.6
Food: Direct Purchases............... PPI for Processed Foods and Feeds.................... 0.8
Food: Contract Services.............. CPI-U for Food Away From Home........................ 1.0
Chemicals............................ Blend of PPIs*....................................... 0.3
Medical Instruments.................. Blend of PPIs*....................................... 2.0
Rubber and Plastics.................. PPI for Rubber and Plastic Products.................. 0.3
Paper and Printing Products.......... PPI for Converted Paper and Paperboard Products...... 0.5
Miscellaneous Products............... PPI for Finished Goods Less Food and Energy.......... 0.6
All Other Services....................... ..................................................... 14.7
Labor-Related Services................... ..................................................... 7.9
Professional Fees: Labor-related..... ECI for Total compensation for Private industry 4.7
workers in Professional and related.
Administrative and Facilities Support ECI for Total compensation for Private industry 0.6
Services. workers in Office and administrative support.
Installation, Maintenance & Repair ECI for Total compensation for Civilian workers in 1.2
Services. Installation, maintenance, and repair.
All Other: Labor-related Services.... ECI for Total compensation for Private industry 1.4
workers in Service occupations.
Nonlabor-Related Services................ ..................................................... 6.8
Professional Fees: Nonlabor-related.. ECI for Total compensation for Private industry 4.9
workers in Professional and related.
Financial Services................... ECI for Total compensation for Private industry 0.7
workers in Financial activities.
Telephone Services................... CPI-U for Telephone Services......................... 0.2
All Other: Nonlabor-related Services. CPI-U for All Items Less Food and Energy............. 0.9
Capital-Related Costs.................... ..................................................... 7.2
Depreciation............................. ..................................................... 4.9
[[Page 21256]]
Building and Fixed Equipment......... BEA chained price index for nonresidential 3.5
construction for hospitals and special care
facilities--vintage weighted (25 years).
Movable Equipment.................... PPI for machinery and equipment--vintage weighted (12 1.4
years).
Interest Costs........................... ..................................................... 1.5
Government/Nonprofit................. Average yield on domestic municipal bonds (Bond Buyer 1.0
20 bonds)--vintage weighted (25 years).
For Profit........................... Average Yield on iBoxx AAA Corporate Bonds--vintage 0.5
weighted (25 years).
Other Capital-Related Costs.............. CPI-U for Rent of primary residence.................. 0.8
----------------------------------------------------------------------------------------------------------------
Note: Totals may not sum to 100.0 percent due to rounding.
* Details on the series and weight for each price proxy used in the PPI blends is provided in section III.A.3.b.
We invite public comment on our proposal to rebase and revise the
IPF market basket to reflect a 2021 base year.
4. Proposed FY 2024 Market Basket Update and Productivity Adjustment
a. Proposed FY 2024 Market Basket Update
For FY 2024 (that is, beginning October 1, 2023 and ending
September 30, 2024), we propose to use an estimate of the proposed
2021-based IPF market basket increase factor to update the IPF PPS base
payment rate. Consistent with historical practice, we estimate the
market basket update for the IPF PPS based on IHS Global Inc.'s (IGI)
forecast. IGI is a nationally recognized economic and financial
forecasting firm with which CMS contracts to forecast the components of
the market baskets.
Using IGI's fourth quarter 2022 forecast with historical data
through the third quarter of 2022, the projected proposed 2021-based
IPF market basket increase factor for FY 2024 is 3.2 percent. We
propose that if more recent data are subsequently available (for
example, a more recent estimate of the market basket increase factor)
we would use such data, to determine the FY 2024 update in the final
rule. For comparison, the current 2016-based IPF market basket is also
projected to increase by 3.2 percent in FY 2024 based on IGI's fourth
quarter 2022 forecast. Table 14 compares the proposed 2021-based IPF
market basket and the 2016-based IPF market basket percent changes.
Table 14--Proposed 2021-Based IPF Market Basket and 2016-Based IPF Market Basket Percent Changes, FY 2019
Through FY 2026
----------------------------------------------------------------------------------------------------------------
Proposed 2021-based IPF 2016-based IPF market
Fiscal year (FY) market basket index basket index percent
percent change change
----------------------------------------------------------------------------------------------------------------
Historical data:
FY 2019................................................... 2.4 2.5
FY 2020................................................... 2.1 2.2
FY 2021................................................... 2.8 2.9
FY 2022................................................... 5.3 5.3
-------------------------------------------------
Average 2019-2022................................... 3.2 3.2
-------------------------------------------------
Forecast:
----------------------------------------------------------------------------------------------------------------
FY 2023................................................... 4.6 4.6
FY 2024................................................... 3.2 3.2
FY 2025................................................... 2.8 2.8
FY 2026................................................... 2.7 2.8
-------------------------------------------------
Average 2023-2026................................... 3.3 3.4
----------------------------------------------------------------------------------------------------------------
Note: These market basket percent changes do not include any further adjustments as may be statutorily required.
Source: IHS Global Inc. 4th quarter 2022 forecast.
b. Proposed Productivity Adjustment
Section 1886(s)(2)(A)(i) of the Act requires the application of the
productivity adjustment described in section 1886(b)(3)(B)(xi)(II) of
the Act to the IPF PPS for the RY beginning in 2012 (that is, a RY that
coincides with a FY) and each subsequent RY. The statute defines the
productivity adjustment to be equal to the 10-year moving average of
changes in annual economy-wide, private nonfarm business multifactor
productivity (as projected by the Secretary for the 10-year period
ending with the applicable FY, year, cost reporting period, or other
annual period) (the ``productivity adjustment''). The United States
Department of Labor's Bureau of Labor Statistics (BLS) publishes the
official measures of productivity for the United States economy. 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
[[Page 21257]]
unchanged. We refer readers to www.bls.gov for the BLS historical
published TFP data. A complete description of IGI's TFP projection
methodology is available on the CMS website at https://www.cms.gov/research-statistics-data-and-systems/statistics-trends-and-reports/medicareprogramratesstats/marketbasketresearch. In addition, in the FY
2022 IPF final rule (86 FR 42611), we noted that effective with FY 2022
and forward, CMS changed the name of this adjustment to refer to it as
the productivity adjustment rather than the MFP adjustment.
Using IGI's fourth quarter 2022 forecast, the 10-year moving
average growth of TFP for FY 2024 is projected to be 0.2 percent. Thus,
in accordance with section 1886(s)(2)(A)(i) of the Act, we propose to
calculate the FY 2024 market basket update, which is used to determine
the applicable percentage increase for the IPF payments, using IGI's
fourth quarter 2022 forecast of the proposed 2021-based IPF market
basket. We proposed to then reduce this percentage increase by the
estimated productivity adjustment for FY 2024 of 0.2 percentage point
(the 10-year moving average growth of TFP for the period ending FY 2024
based on IGI's fourth quarter 2022 forecast). Therefore, the proposed
FY 2024 IPF update is equal to 3.0 percent (3.2 percent market basket
update reduced by the 0.2 percentage point productivity adjustment).
Furthermore, we propose that if more recent data become available after
the publication of the proposed rule and before the publication of the
final rule (for example, a more recent estimate of the market basket
increase factor and/or productivity adjustment), we would use such
data, if appropriate, to determine the FY 2024 market basket update and
productivity adjustment in the final rule.
We invite public comment on our proposals for the FY 2024 market
basket update and productivity adjustment.
5. Proposed Labor-Related Share for FY 2024
Due to variations in geographic wage levels and other labor-related
costs, we believe that payment rates under the IPF PPS should continue
to be adjusted by a geographic wage index, which would apply to the
labor-related portion of the Federal per diem base rate (hereafter
referred to as the labor-related share). The labor-related share is
determined by identifying the national average proportion of total
costs that are related to, influenced by, or vary with the local labor
market. We propose to continue to classify a cost category as labor-
related if the costs are labor intensive and vary with the local labor
market.
We propose to include in the labor-related share the sum of the
relative importance of 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 portion of the Capital-Related cost weight from the proposed
2021-based IPF market basket. These are the same categories as the
2016-based IPF market basket.
Similar to the 2016-based IPF market basket, the proposed 2021-
based IPF market basket includes two cost categories for nonmedical
Professional fees (including but not limited to, expenses for legal,
accounting, and engineering services). These are Professional Fees:
Labor-related and Professional Fees: Nonlabor-related. For the proposed
2021-based IPF market basket, we propose to estimate the labor-related
percentage of non-medical professional fees (and assign these expenses
to the Professional Fees: Labor-related services cost category) based
on the same method that was used to determine the labor-related
percentage of professional fees in the 2016-based IPF market basket.
As was done in the 2016-based IPF market basket, we propose to
determine the proportion of legal, accounting and auditing,
engineering, and management consulting services that meet our
definition of labor-related services based on a survey of hospitals
conducted by CMS in 2008. We notified the public of our intent to
conduct this survey on December 9, 2005 (70 FR 73250) and did not
receive any public comments in response to the notice (71 FR 8588). A
discussion of the composition of the survey and post-stratification can
be found in the FY 2010 IPPS/LTCH PPS final rule (74 FR 43850 through
43856). Based on the weighted results of the survey, we determined that
hospitals purchase, on average, the following portions of contracted
professional services outside of their local labor market:
34 percent of accounting and auditing services.
30 percent of engineering services.
33 percent of legal services.
42 percent of management consulting services.
We propose to apply each of these percentages to the respective
2012 Benchmark I-O cost category underlying the professional fees cost
category to determine the Professional Fees: Nonlabor-related costs.
The Professional Fees: Labor-related costs were determined to be the
difference between the total costs for each Benchmark I-O category and
the Professional Fees: Nonlabor-related costs. This is the same
methodology that we used to separate the 2016-based IPF market basket
professional fees category into Professional Fees: Labor-related and
Professional Fees: Nonlabor-related cost categories (84 FR 38445).
Effective for transmittal 18, (https://www.cms.gov/Regulations-and-Guidance/Guidance/Transmittals/Transmittals/r18p240i) the hospital
Medicare cost report (CMS Form 2552-10, OMB No. 0938-0050) is
collecting information on whether a hospital purchased professional
services (for example, legal, accounting, tax preparation, bookkeeping,
payroll, advertising, and/or management/consulting services) from an
unrelated organization and if the majority of these expenses were
purchased from unrelated organizations located outside of the main
hospital's local area labor market. We encourage all providers to
provide this information so we can potentially use these data in future
rulemaking to determine the labor-related share.
In the proposed 2021-based IPF market basket, nonmedical
professional fees that were subject to allocation based on these survey
results represent 3.3 percent of total costs (and are limited to those
fees related to Accounting & Auditing, Legal, Engineering, and
Management Consulting services). Based on our survey results, we
proposed to apportion 2.1 percentage points of the 3.3 percentage point
figure into the Professional Fees: Labor-related share cost category
and designate the remaining 1.2 percentage point into the Professional
Fees: Nonlabor-related cost category.
In addition to the professional services listed, for the proposed
2021-based IPF market basket, we propose to allocate a proportion of
the Home Office/Related Organization Contract Labor cost weight,
calculated using the Medicare cost reports, into the Professional Fees:
Labor-related and Professional Fees: Nonlabor-related cost categories.
We propose to classify these expenses as labor-related and nonlabor-
related as many facilities are not located in the same geographic area
as their home office and, therefore, do not meet our definition for the
labor-related share that requires the services to be purchased in the
local labor market.
Similar to the 2016-based IPF market basket, we propose for the
2021-based
[[Page 21258]]
IPF market basket to use the Medicare cost reports for both
freestanding IPF providers and hospital-based IPF providers to
determine the home office labor-related percentages. The Medicare cost
report requires a hospital to report information regarding their home
office provider. Using information on the Medicare cost report, we then
compare the location of the IPF with the location of the IPF's home
office. We propose to classify an IPF with a home office located in
their respective labor market if the IPF and its home office are
located in the same metropolitan statistical area (MSA). We then
determine the proportion of the Home Office/Related Organization
Contract Labor cost weight that should be allocated to the labor-
related share based on the percent of total Medicare allowable costs
for those IPFs that had home offices located in their respective local
labor markets of total Medicare allowable costs for IPFs with a home
office. We determined an IPF's and its home office's MSA using their
zip code information from the Medicare cost report. Using this
methodology, we determined that 46 percent of IPFs' Medicare allowable
costs were for home offices located in their respective local labor
markets. Therefore, we are allocating 46 percent of the Home Office/
Related Organization Contract Labor cost weight (2.1 percentage points
= 4.7 percent times 46 percent) to the Professional Fees: Labor-related
cost weight and 54 percent of the Home Office/Related Organization
Contract Labor cost weight to the Professional Fees: Nonlabor-related
cost weight (2.5 percentage points = 4.7 percent times 54 percent). The
same methodology was used for the 2016-based IPF market basket (84 FR
38445).
In summary, we apportioned 2.1 percentage points of the non-medical
professional fees and 2.1 percentage points of the Home Office/Related
Organization Contract Labor cost weight into the Professional Fees:
Labor-Related cost category. This amount was added to the portion of
professional fees that we already identified as labor-related using the
I-O data such as contracted advertising and marketing costs
(approximately 0.5 percentage point of total costs) resulting in a
Professional Fees: Labor-Related cost weight of 4.7 percent.
As stated, we propose to include in the labor-related share the sum
of the relative importance of Wages and Salaries, Employee Benefits,
Professional Fees: Labor-Related, Administrative and Facilities Support
Services, Installation, Maintenance, and Repair Services, All Other:
Labor-related Services, and a portion of the Capital-Related cost
weight from the proposed 2021-based IPF market basket. The relative
importance reflects the different rates of price change for these cost
categories between the base year (2021) and FY 2024. Based on IHS
Global Inc. 4th quarter 2022 forecast of the proposed 2021-based IPF
market basket, the sum of the FY 2024 relative importance for Wages and
Salaries, Employee Benefits, Professional Fees: Labor-related,
Administrative and Facilities Support Services, Installation
Maintenance & Repair Services, and All Other: Labor-related Services is
75.4 percent. The portion of Capital costs that is influenced by the
local labor market is estimated to be 46 percent, which is the same
percentage applied to the 2016-based IPF market basket. Since the
relative importance for Capital is 6.8 percent of the proposed 2021-
based IPF market basket in FY 2024, we took 46 percent of 6.8 percent
to determine the proposed labor-related share of Capital for FY 2024 of
3.1 percent. Therefore, we propose a total labor-related share for FY
2024 of 78.5 percent (the sum of 75.4 percent for the operating cost
and 3.1 percent for the labor-related share of Capital). Table 15 shows
the FY 2024 labor-related share using the proposed 2021-based IPF
market basket relative importance and the FY 2023 labor-related share
using the 2016-based IPF market basket.
Table 15--Proposed FY 2024 IPF Labor-related share and FY 2023 IPF Labor-Related Share
----------------------------------------------------------------------------------------------------------------
FY 2024 Labor-related FY 2023 Final labor-
share based on proposed related share based on
2021-based IPF market 2016-based IPF market
basket \1\ basket \2\
----------------------------------------------------------------------------------------------------------------
Wages and Salaries............................................ 53.3 53.2
Employee Benefits............................................. 14.2 13.5
Professional Fees: Labor-related \3\.......................... 4.7 4.3
Administrative and Facilities Support Services................ 0.6 0.6
Installation, Maintenance and Repair Services................. 1.2 1.3
All Other: Labor-related Services............................. 1.4 1.5
-------------------------------------------------
Subtotal.................................................. 75.4 74.4
----------------------------------------------------------------------------------------------------------------
Labor-related portion of capital (46%).................... 3.1 3.0
-------------------------------------------------
Total LRS................................................. 78.5 77.4
----------------------------------------------------------------------------------------------------------------
\1\ IHS Global Inc. 4th quarter 2022 forecast.
\2\ Based on IHS Global Inc. 2nd quarter 2022 forecast as published in the Federal Register (87 FR 46851).
\3\ Includes all contract advertising and marketing costs and a portion of accounting, architectural,
engineering, legal, management consulting, and home office/related organization contract labor costs.
[[Page 21259]]
The FY 2024 labor-related share using the proposed 2021-based IPF
market basket is about 1.0 percentage point higher than the FY 2023
labor-related share using the 2016-based IPF market basket. This higher
labor-related share is primarily due to the incorporation of the 2021
Medicare cost report data, which increased the Compensation cost weight
by 0.9 percentage point compared to the 2016-based IPF market basket as
shown in Table 1 and Table 2 in section III.A.3.a.(2) of this proposed
rule. We invite public comment on the proposed labor-related share for
FY 2024.
B. Proposed Updates to the IPF PPS Rates for FY Beginning October 1,
2023
The IPF PPS is based on a standardized Federal per diem base rate
calculated from the IPF average per diem costs and adjusted for budget
neutrality in the implementation year. The Federal per diem base rate
is used as the standard payment per day under the IPF PPS and is
adjusted by the patient-level and facility-level adjustments that are
applicable to the IPF stay. A detailed explanation of how we calculated
the average per diem cost appears in the November 2004 IPF PPS final
rule (69 FR 66926).
1. Determining the Standardized Budget-Neutral Federal per Diem Base
Rate
Section 124(a)(1) of the BBRA required that we implement the IPF
PPS in a budget-neutral manner. In other words, the amount of total
payments under the IPF PPS, including any payment adjustments, must be
projected to be equal to the amount of total payments that would have
been made if the IPF PPS were not implemented. Therefore, we calculated
the budget neutrality factor by setting the total estimated IPF PPS
payments to be equal to the total estimated payments that would have
been made under the Tax Equity and Fiscal Responsibility Act of 1982
(TEFRA) (Pub. L. 97-248) methodology had the IPF PPS not been
implemented. A step-by-step description of the methodology used to
estimate payments under the Tax Equity and Fiscal Responsibility Act
(TEFRA) payment system appears in the November 2004 IPF PPS final rule
(69 FR 66926).
Under the IPF PPS methodology, we calculated the final Federal per
diem base rate to be budget-neutral during the IPF PPS implementation
period (that is, the 18-month period from January 1, 2005 through June
30, 2006) using a July 1 update cycle. We updated the average cost per
day to the midpoint of the IPF PPS implementation period (October 1,
2005), and this amount was used in the payment model to establish the
budget-neutrality adjustment.
Next, we standardized the IPF PPS Federal per diem base rate to
account for the overall positive effects of the IPF PPS payment
adjustment factors by dividing total estimated payments under the TEFRA
payment system by estimated payments under the IPF PPS. The information
concerning this standardization can be found in the November 2004 IPF
PPS final rule (69 FR 66932) and the RY 2006 IPF PPS final rule (71 FR
27045). We then reduced the standardized Federal per diem base rate to
account for the outlier policy, the stop loss provision, and
anticipated behavioral changes. A complete discussion of how we
calculated each component of the budget neutrality adjustment appears
in the November 2004 IPF PPS final rule (69 FR 66932 through 66933) and
in the RY 2007 IPF PPS final rule (71 FR 27044 through 27046). The
final standardized budget-neutral Federal per diem base rate
established for cost reporting periods beginning on or after January 1,
2005 was calculated to be $575.95.
The Federal per diem base rate has been updated in accordance with
applicable statutory requirements and Sec. 412.428 through publication
of annual notices or proposed and final rules. A detailed discussion on
the standardized budget-neutral Federal per diem base rate and the ECT
payment per treatment appears in the FY 2014 IPF PPS update notice (78
FR 46738 through 46740). These documents are available on the CMS
website at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/InpatientPsychFacilPPS/.
IPFs must include a valid procedure code for ECT services provided
to IPF beneficiaries in order to bill for ECT services, as described in
our Medicare Claims Processing Manual, Chapter 3, Section 190.7.3
(available at https://www.cms.gov/Regulations-and-Guidance/Guidance/Manuals/Downloads/clm104c03.pdf.) There were no changes to the ECT
procedure codes used on IPF claims as a result of the final update to
the ICD-10-PCS code set for FY 2024. Addendum B to this proposed rule
shows the ECT procedure codes for FY 2024 and is available on our
website at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/InpatientPsychFacilPPS/tools.html.
2. Proposed Update of the Federal per Diem Base Rate and
Electroconvulsive Therapy Payment per Treatment
The current (FY 2023) Federal per diem base rate is $865.63 and the
ECT payment per treatment is $372.67. For the proposed FY 2024 Federal
per diem base rate, we applied the payment rate update of 3.0 percent--
that is, the 2021-based IPF market basket increase for FY 2024 of 3.2
percent less the productivity adjustment of 0.2 percentage point--and
the wage index budget-neutrality factor of 1.0011 (as discussed in
section IV.D.1 of this proposed rule) to the FY 2023 Federal per diem
base rate of $865.63, yielding a proposed Federal per diem base rate of
$892.58 for FY 2024. Similarly, we applied the proposed 3.0 percent
payment rate update and the 1.0011 wage index budget-neutrality factor
to the FY 2023 ECT payment per treatment of $372.67, yielding a
proposed ECT payment per treatment of $384.27 for FY 2024.
Section 1886(s)(4)(A)(i) of the Act requires that for RY 2014 and
each subsequent RY, in the case of an IPF that fails to report required
quality data with respect to such RY, the Secretary will reduce any
annual update to a standard Federal rate for discharges during the RY
by 2.0 percentage points. Therefore, we propose to apply a 2.0
percentage points reduction to the Federal per diem base rate and the
ECT payment per treatment as follows:
For IPFs that fail requirements under the IPFQR Program,
we would apply a proposed 1.0 percent payment rate update--that is, the
proposed IPF market basket increase for FY 2024 of 3.2 percent less the
proposed productivity adjustment of 0.2 percentage point for a proposed
update of 3.0 percent, and further reduced by 2.0 percentage points in
accordance with section 1886(s)(4)(A)(i) of the Act--and the proposed
wage index budget-neutrality factor of 1.0011 to the FY 2024 Federal
per diem base rate of $892.58, yielding a proposed Federal per diem
base rate of $875.25 for FY 2024.
For IPFs that fail to meet requirements under the IPFQR
Program, we would apply the proposed 1.0 percent annual payment rate
update and the proposed 1.0011 wage index budget-neutrality factor to
the FY 2024 ECT payment per treatment of $384.27 yielding a proposed
ECT payment per treatment of $376.81 for FY 2024. Lastly, we propose
that if more recent data become available, we would use such data, if
appropriate, to determine the FY 2024 Federal per diem base rate
[[Page 21260]]
and ECT payment per treatment for the final rule.
C. Proposed Updates to the IPF PPS Patient-Level Adjustment Factors
1. Overview of the IPF PPS Adjustment Factors
The IPF PPS payment adjustments were derived from a regression
analysis of 100 percent of the FY 2002 Medicare Provider and Analysis
Review (MedPAR) data file, which contained 483,038 cases. For a more
detailed description of the data file used for the regression analysis,
see the November 2004 IPF PPS final rule (69 FR 66935 through 66936).
We propose to use the existing regression-derived adjustment factors
established in 2005 for FY 2024. However, we have used more recent
claims data to simulate payments to finalize the outlier fixed dollar
loss threshold amount and to assess the impact of the IPF PPS updates.
2. IPF PPS Patient-Level Adjustments
The IPF PPS includes payment adjustments for the following patient-
level characteristics: Medicare Severity Diagnosis Related Groups (MS-
DRGs) assignment of the patient's principal diagnosis, selected
comorbidities, patient age, and the variable per diem adjustments.
a. Proposed Update to MS-DRG Assignment
We believe it is important to maintain for IPFs the same diagnostic
coding and Diagnosis Related Group (DRG) classification used under the
IPPS for providing psychiatric care. For this reason, when the IPF PPS
was implemented for cost reporting periods beginning on or after
January 1, 2005, we adopted the same diagnostic code set (ICD-9-CM) and
DRG patient classification system (MS-DRGs) that were utilized at the
time under the IPPS. In the RY 2009 IPF PPS notice (73 FR 25709), we
discussed CMS' effort to better recognize resource use and the severity
of illness among patients. CMS adopted the new MS-DRGs for the IPPS in
the FY 2008 IPPS final rule with comment period (72 FR 47130). In the
RY 2009 IPF PPS notice (73 FR 25716), we provided a crosswalk to
reflect changes that were made under the IPF PPS to adopt the new MS-
DRGs. For a detailed description of the mapping changes from the
original DRG adjustment categories to the current MS-DRG adjustment
categories, we refer readers to the RY 2009 IPF PPS notice (73 FR
25714).
The IPF PPS includes payment adjustments for designated psychiatric
DRGs assigned to the claim based on the patient's principal diagnosis.
The DRG adjustment factors were expressed relative to the most
frequently reported psychiatric DRG in FY 2002, that is, DRG 430
(psychoses). The coefficient values and adjustment factors were derived
from the regression analysis discussed in detail in the November 28,
2003 IPF proposed rule (68 FR 66923; 66928 through 66933) and the
November 15, 2004 IPF final rule (69 FR 66933 through 66960). Mapping
the DRGs to the MS-DRGs resulted in the current 17 IPF MS-DRGs, instead
of the original 15 DRGs, for which the IPF PPS provides an adjustment.
For FY 2024, we are not proposing any changes to the IPF MS-DRG
adjustment factors and are retaining the existing IPF MS-DRG adjustment
factors.
In the FY 2015 IPF PPS final rule published August 6, 2014 in the
Federal Register titled, ``Inpatient Psychiatric Facilities Prospective
Payment System--Update for FY Beginning October 1, 2014 (FY 2015)'' (79
FR 45945 through 45947), we finalized conversions of the ICD-9-CM-based
MS-DRGs to ICD-10-CM/PCS-based MS-DRGs, which were implemented on
October 1, 2015. As discussed in the FY 2015 IPF PPS proposed rule (79
FR 26047) in more detail, every year, changes to the ICD-10-CM and the
ICD-10-PCS coding system are addressed in the IPPS proposed and final
rules. The changes to the codes are effective October 1 of each year
and must be used by acute care hospitals as well as other providers to
report diagnostic and procedure information. In accordance with Sec.
412.428(e), the IPF PPS has always incorporated ICD-10-CM and ICD-10-
PCS coding changes made in the annual IPPS update and will continue to
do so. We will continue to publish coding changes in a Transmittal/
Change Request, similar to how coding changes are announced by the IPPS
and LTCH PPS. The coding changes relevant to the IPF PPS are also
published in the IPF PPS proposed and final rules, or in IPF PPS update
notices. Further information on the ICD-10-CM/PCS MS-DRG conversion
project can be found on the CMS ICD-10-CM website at https://www.cms.gov/Medicare/Coding/ICD10/ICD-10-MS-DRG-Conversion-Project.html.
For FY 2024, we propose to continue making the existing payment
adjustment for psychiatric diagnoses that group to one of the existing
17 IPF MS-DRGs listed in Addendum A. Addendum A is available on our
website at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/InpatientPsychFacilPPS/tools.html. Psychiatric principal
diagnoses that do not group to one of the 17 designated MS-DRGs will
still receive the Federal per diem base rate and all other applicable
adjustments, but the payment will not include an MS-DRG adjustment.
The diagnoses for each IPF MS-DRG will be updated as of October 1,
2023, using the final FY 2024 IPPS ICD-10-CM/PCS code sets. The FY 2024
IPPS/LTCH PPS final rule will include tables of the changes to the ICD-
10-CM/PCS code sets, which underlie the FY 2024 IPF MS-DRGs. Both the
FY 2024 IPPS final rule and the tables of final changes to the ICD-10-
CM/PCS code sets, which underlie the FY 2024 MS-DRGs, will be available
on the CMS IPPS website at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/.
Code First
As discussed in the ICD-10-CM Official Guidelines for Coding and
Reporting, certain conditions have both an underlying etiology and
multiple body system manifestations due to the underlying etiology. For
such conditions, the ICD-10-CM has a coding convention that requires
the underlying condition be sequenced first followed by the
manifestation. Wherever such a combination exists, there is a ``use
additional code'' note at the etiology code, and a ``code first'' note
at the manifestation code. These instructional notes indicate the
proper sequencing order of the codes (etiology followed by
manifestation). In accordance with the ICD-10-CM Official Guidelines
for Coding and Reporting, when a primary (psychiatric) diagnosis code
has a ``code first'' note, the provider will follow the instructions in
the ICD-10-CM Tabular List. The submitted claim goes through the CMS
processing system, which will identify the principal diagnosis code as
non-psychiatric and search the secondary codes for a psychiatric code
to assign a DRG code for adjustment. The system will continue to search
the secondary codes for those that are appropriate for comorbidity
adjustment.
For more information on the code first policy, we refer our readers
to the November 2004 IPF PPS final rule (69 FR 66945), and see sections
I.A.13 and I.B.7 of the FY 2020 ICD-10-CM Coding Guidelines, available
at https://www.cdc.gov/nchs/data/icd/10cmguidelines-FY2020_final.pdf.
In the FY 2015 IPF PPS final rule, we provided a code first table for
reference that highlights the same or similar manifestation codes where
the code first instructions apply in ICD-10-CM that
[[Page 21261]]
were present in ICD-10-CM (79 FR 46009). In FY 2018, FY 2019 and FY
2020, there were no changes to the final ICD-10-CM codes in the IPF
Code First table. For FY 2021 and FY 2022, there were 18 ICD-10-CM
codes deleted from the final IPF Code First table. For FY 2023, there
were 2 ICD-10-CM codes deleted and 48 ICD-10-CM codes added to the IPF
Code First table. For FY 2024, there are no proposed changes to the
Code First Table. The proposed FY 2024 Code First table is shown in
Addendum B on the CMS website at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/InpatientPsychFacilPPS/tools.html.
b. Proposed Payment for Comorbid Conditions
The intent of the comorbidity adjustments is to recognize the
increased costs associated with comorbid conditions by providing
additional payments for certain existing medical or psychiatric
conditions that are expensive to treat. In our RY 2012 IPF PPS final
rule (76 FR 26451 through 26452), we explained that the IPF PPS
includes 17 comorbidity categories and identified the new, revised, and
deleted ICD-9-CM diagnosis codes that generate a comorbid condition
payment adjustment under the IPF PPS for RY 2012 (76 FR 26451).
Comorbidities are specific patient conditions that are secondary to
the patient's principal diagnosis and that require treatment during the
stay. Diagnoses that relate to an earlier episode of care and have no
bearing on the current hospital stay are excluded and must not be
reported on IPF claims. Comorbid conditions must exist at the time of
admission or develop subsequently, and affect the treatment received,
LOS, or both treatment and LOS.
For each claim, an IPF may receive only one comorbidity adjustment
within a comorbidity category, but it may receive an adjustment for
more than one comorbidity category. Current billing instructions for
discharge claims, on or after October 1, 2015, require IPFs to enter
the complete ICD-10-CM codes for up to 24 additional diagnoses if they
co-exist at the time of admission, or develop subsequently and impact
the treatment provided.
The comorbidity adjustments were determined based on the regression
analysis using the diagnoses reported by IPFs in FY 2002. The principal
diagnoses were used to establish the DRG adjustments and were not
accounted for in establishing the comorbidity category adjustments,
except where ICD-9-CM code first instructions applied. In a code first
situation, the submitted claim goes through the CMS processing system,
which will identify the principal diagnosis code as non-psychiatric and
search the secondary codes for a psychiatric code to assign an MS-DRG
code for adjustment. The system will continue to search the secondary
codes for those that are appropriate for comorbidity adjustment.
As noted previously, it is our policy to maintain the same
diagnostic coding set for IPFs that is used under the IPPS for
providing the same psychiatric care. The 17 comorbidity categories
formerly defined using ICD-9-CM codes were converted to ICD-10-CM/PCS
in our FY 2015 IPF PPS final rule (79 FR 45947 through 45955). The goal
for converting the comorbidity categories is referred to as
replication, meaning that the payment adjustment for a given patient
encounter is the same after ICD-10-CM implementation as it will be if
the same record had been coded in ICD-9-CM and submitted prior to ICD-
10-CM/PCS implementation on October 1, 2015. All conversion efforts
were made with the intent of achieving this goal. For FY 2024, we
propose to use the same comorbidity adjustment factors in effect in FY
2023. The proposed FY 2024 comorbidity adjustment factors are found in
Addendum A, available on the CMS website at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/InpatientPsychFacilPPS/tools.html.
For FY 2024, we propose to add 2 ICD-10-CM/PCS codes and remove 1
ICD-10-CM/PCS code from the Chronic Renal Failure category. The
proposed FY 2024 comorbidity codes are shown in Addenda B, available on
the CMS website at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/InpatientPsychFacilPPS/tools.html.
In accordance with the policy established in the FY 2015 IPF PPS
final rule (79 FR 45949 through 45952), we reviewed all new FY 2024
ICD-10-CM codes to remove codes that were site ``unspecified'' in terms
of laterality from the FY 2024 ICD-10-CM/PCS codes in instances where
more specific codes are available. As we stated in the FY 2015 IPF PPS
final rule, we believe that specific diagnosis codes that narrowly
identify anatomical sites where disease, injury, or a condition exists
should be used when coding patients' diagnoses whenever these codes are
available. We finalized in the FY 2015 IPF PPS rule, that we would
remove site ``unspecified'' codes from the IPF PPS ICD-10-CM/PCS codes
in instances when laterality codes (site specified codes) are
available, as the clinician should be able to identify a more specific
diagnosis based on clinical assessment at the medical encounter. None
of the finalized additions to the FY 2024 ICD-10-CM/PCS codes were site
``unspecified'' by laterality, therefore, we are not removing any of
the new codes.
c. Proposed Patient Age Adjustments
As explained in the November 2004 IPF PPS final rule (69 FR 66922),
we analyzed the impact of age on per diem cost by examining the age
variable (range of ages) for payment adjustments. In general, we found
that the cost per day increases with age. The older age groups are
costlier than the under 45 age group, the differences in per diem cost
increase for each successive age group, and the differences are
statistically significant. For FY 2024, we propose to use the patient
age adjustments currently in effect for FY 2023, as shown in Addendum A
of this proposed rule (see https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/InpatientPsychFacilPPS/tools.html).
d. Proposed Variable per Diem Adjustments
We explained in the November 2004 IPF PPS final rule (69 FR 66946)
that the regression analysis indicated that per diem cost declines as
the LOS increases. The variable per diem adjustments to the Federal per
diem base rate account for ancillary and administrative costs that
occur disproportionately in the first days after admission to an IPF.
As discussed in the November 2004 IPF PPS final rule, we used a
regression analysis to estimate the average differences in per diem
cost among stays of different lengths (69 FR 66947 through 66950). As a
result of this analysis, we established variable per diem adjustments
that begin on day 1 and decline gradually until day 21 of a patient's
stay. For day 22 and thereafter, the variable per diem adjustment
remains the same each day for the remainder of the stay. However, the
adjustment applied to day 1 depends upon whether the IPF has a
qualifying ED. If an IPF has a qualifying ED, it receives a 1.31
adjustment factor for day 1 of each stay. If an IPF does not have a
qualifying ED, it receives a 1.19 adjustment factor for day 1 of the
stay. The ED adjustment is explained in more detail in section III.D.4
of this proposed rule.
For FY 2024, we propose to use the variable per diem adjustment
factors currently in effect in FY 2023, as shown in Addendum A of this
proposed rule
[[Page 21262]]
(available at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/InpatientPsychFacilPPS/tools.html). A complete discussion of
the variable per diem adjustments appears in the November 2004 IPF PPS
final rule (69 FR 66946).
D. Proposed Updates to the IPF PPS Facility-Level Adjustments
The IPF PPS includes facility-level adjustments for the wage index,
IPFs located in rural areas, teaching IPFs, cost of living adjustments
for IPFs located in Alaska and Hawaii, and IPFs with a qualifying ED.
1. Wage Index Adjustment
a. Background
As discussed in the RY 2007 IPF PPS final rule (71 FR 27061), RY
2009 IPF PPS (73 FR 25719) and the RY 2010 IPF PPS notices (74 FR
20373), to provide an adjustment for geographic wage levels, the labor-
related portion of an IPF's payment is adjusted using an appropriate
wage index. Currently, an IPF's geographic wage index value is
determined based on the actual location of the IPF in an urban or rural
area, as defined in 42 CFR 412.64(b)(1)(ii)(A) and (C).
Due to the variation in costs and because of the differences in
geographic wage levels, in the November 15, 2004 IPF PPS final rule, we
required that payment rates under the IPF PPS be adjusted by a
geographic wage index. We proposed and finalized a policy to use the
unadjusted, pre-floor, pre-reclassified IPPS hospital wage index to
account for geographic differences in IPF labor costs. We implemented
use of the pre-floor, pre-reclassified IPPS hospital wage data to
compute the IPF wage index since there was not an IPF-specific wage
index available. We believe that IPFs generally compete in the same
labor market as IPPS hospitals so the pre-floor, pre-reclassified IPPS
hospital wage data should be reflective of labor costs of IPFs. We
believe this pre-floor, pre-reclassified IPPS hospital wage index to be
the best available data to use as proxy for an IPF specific wage index.
As discussed in the RY 2007 IPF PPS final rule (71 FR 27061 through
27067), under the IPF PPS, the wage index is calculated using the IPPS
wage index for the labor market area in which the IPF is located,
without considering geographic reclassifications, floors, and other
adjustments made to the wage index under the IPPS. For a complete
description of these IPPS wage index adjustments, we refer readers to
the FY 2019 IPPS/LTCH PPS final rule (83 FR 41362 through 41390). Our
wage index policy at Sec. 412.424(a)(2), requires that we use the best
Medicare data available to estimate costs per day, including an
appropriate wage index to adjust for wage differences.
When the IPF PPS was implemented in the November 15, 2004 IPF PPS
final rule, with an effective date of January 1, 2005, the pre-floor,
pre-reclassified IPPS hospital wage index that was available at the
time was the FY 2005 pre-floor, pre-reclassified IPPS hospital wage
index. Historically, the IPF wage index for a given RY has used the
pre-floor, pre-reclassified IPPS hospital wage index from the prior FY
as its basis. This has been due in part to the pre-floor, pre-
reclassified IPPS hospital wage index data that were available during
the IPF rulemaking cycle, where an annual IPF notice or IPF final rule
was usually published in early May. This publication timeframe was
relatively early compared to other Medicare payment rules because the
IPF PPS follows a RY, which was defined in the implementation of the
IPF PPS as the 12-month period from July 1 to June 30 (69 FR 66927).
Therefore, the best available data at the time the IPF PPS was
implemented was the pre-floor, pre-reclassified IPPS hospital wage
index from the prior FY (for example, the RY 2006 IPF wage index was
based on the FY 2005 pre-floor, pre-reclassified IPPS hospital wage
index).
In the RY 2012 IPF PPS final rule, we changed the reporting year
timeframe for IPFs from a RY to the FY, which begins October 1 and ends
September 30 (76 FR 26434 through 26435). In that RY 2012 IPF PPS final
rule, we continued our established policy of using the pre-floor, pre-
reclassified IPPS hospital wage index from the prior year (that is,
from FY 2011) as the basis for the FY 2012 IPF wage index. This policy
of basing a wage index on the prior year's pre-floor, pre-reclassified
IPPS hospital wage index has been followed by other Medicare payment
systems, such as hospice and inpatient rehabilitation facilities. By
continuing with our established policy, we remained consistent with
other Medicare payment systems.
In FY 2020, we finalized the IPF wage index methodology to align
the IPF PPS wage index with the same wage data timeframe used by the
IPPS for FY 2020 and subsequent years. Specifically, we finalized to
use the pre-floor, pre-reclassified IPPS hospital wage index from the
FY concurrent with the IPF FY as the basis for the IPF wage index. For
example, the FY 2020 IPF wage index was based on the FY 2020 pre-floor,
pre-reclassified IPPS hospital wage index rather than on the FY 2019
pre-floor, pre-reclassified IPPS hospital wage index.
We explained in the FY 2020 proposed rule (84 FR 16973), that using
the concurrent pre-floor-, pre-reclassified IPPS hospital wage index
will result in the most up-to-date wage data being the basis for the
IPF wage index. It will also result in more consistency and parity in
the wage index methodology used by other Medicare payment systems. The
Medicare SNF PPS already used the concurrent IPPS hospital wage index
data as the basis for the SNF PPS wage index. Thus, the wage adjusted
Medicare payments of various provider types will be based upon wage
index data from the same timeframe. CMS proposed similar policies to
use the concurrent pre-floor, pre-reclassified IPPS hospital wage index
data in other Medicare payment systems, such as hospice and inpatient
rehabilitation facilities. For FY 2024, we propose to continue using
the concurrent pre-floor, pre-reclassified IPPS hospital wage index as
the basis for the IPF wage index.
We propose to apply the IPF wage index adjustment to the labor-
related share of the national base rate and ECT payment per treatment.
The labor-related share of the national rate and ECT payment per
treatment would change from 77.4 percent in FY 2023 to 78.5 percent in
FY 2024. This percentage reflects the proposed labor-related share of
the proposed 2021-based IPF market basket for FY 2024 (see section
III.A of this proposed rule).
b. Office of Management and Budget (OMB) Bulletins
i. Background
The wage index used for the IPF PPS is calculated using the
unadjusted, pre-reclassified and pre-floor IPPS wage index data and is
assigned to the IPF on the basis of the labor market area in which the
IPF is geographically located. IPF labor market areas are delineated
based on the Core Based Statistical Area (CBSAs) established by the
OMB.
Generally, OMB issues major revisions to statistical areas every 10
years, based on the results of the decennial census. However, OMB
occasionally issues minor updates and revisions to statistical areas in
the years between the decennial censuses through OMB Bulletins. These
bulletins contain information regarding CBSA changes, including changes
to CBSA numbers and titles. OMB bulletins may be accessed online at
https://www.whitehouse.gov/omb/information-for-agencies/bulletins/. In
accordance
[[Page 21263]]
with our established methodology, the IPF PPS has historically adopted
any CBSA changes that are published in the OMB bulletin that
corresponds with the IPPS hospital wage index used to determine the IPF
wage index and, when necessary and appropriate, has proposed and
finalized transition policies for these changes.
In the RY 2007 IPF PPS final rule (71 FR 27061 through 27067), we
adopted the changes discussed in the OMB Bulletin No. 03-04 (June 6,
2003), which announced revised definitions for Micropolitan Statistical
Areas and the creation of Micropolitan Statistical Areas and Combined
Statistical Areas. In adopting the OMB CBSA geographic designations in
RY 2007, we did not provide a separate transition for the CBSA-based
wage index since the IPF PPS was already in a transition period from
TEFRA payments to PPS payments.
In the RY 2009 IPF PPS notice, we incorporated the CBSA
nomenclature changes published in the most recent OMB bulletin that
applied to the IPPS hospital wage index used to determine the current
IPF wage index and stated that we expected to continue to do the same
for all the OMB CBSA nomenclature changes in future IPF PPS rules and
notices, as necessary (73 FR 25721).
Subsequently, CMS adopted the changes that were published in past
OMB bulletins in the FY 2016 IPF PPS final rule (80 FR 46682 through
46689), the FY 2018 IPF PPS rate update (82 FR 36778 through 36779),
the FY 2020 IPF PPS final rule (84 FR 38453 through 38454), and the FY
2021 IPF PPS final rule (85 FR 47051 through 47059). We direct readers
to each of these rules for more information about the changes that were
adopted and any associated transition policies.
In part due to the scope of changes involved in adopting the CBSA
delineations for FY 2021, we finalized a 2-year transition policy
consistent with our past practice of using transition policies to help
mitigate negative impacts on hospitals of certain wage index policy
changes. We applied a 5-percent cap on wage index decreases to all IPF
providers that had any decrease in their wage indexes, regardless of
the circumstance causing the decline, so that an IPF's final wage index
for FY 2021 will not be less than 95 percent of its final wage index
for FY 2020, regardless of whether the IPF was part of an updated CBSA.
We refer readers to the FY 2021 IPF PPS final rule (85 FR 47058 through
47059) for a more detailed discussion about the wage index transition
policy for FY 2021.
On March 6, 2020 OMB issued OMB Bulletin 20-01 (available on the
web at https://www.whitehouse.gov/wp-content/uploads/2020/03/Bulletin-20-01.pdf). In considering whether to adopt this bulletin, we analyzed
whether the changes in this bulletin would have a material impact on
the IPF PPS wage index. This bulletin creates only one Micropolitan
statistical area. As discussed in further detail in section
III.D.1.b.ii of this proposed rule, since Micropolitan areas are
considered rural for the IPF PPS wage index, this bulletin has no
material impact on the IPF PPS wage index. That is, the constituent
county of the new Micropolitan area was considered rural effective as
of FY 2021 and would continue to be considered rural if we adopted OMB
Bulletin 20-01. Therefore, we did not propose to adopt OMB Bulletin 20-
01 in the FY 2022 IPF PPS proposed rule.
In the FY 2023 IPF PPS final rule (87 FR 46856 through 46859), we
finalized a permanent 5-percent cap on any decrease to a provider's
wage index from its wage index in the prior year, and we stated that we
would apply this cap in a budget-neutral manner. Additionally, we
finalized a policy that a new IPF 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 IPF would not have a wage
index in the prior FY. We amended the IPF PPS regulations at Sec.
412.424(d)(1)(i) to reflect this permanent cap on wage index decreases.
We refer readers to the FY 2023 IPF PPS final rule for a more detailed
discussion about this policy.
ii. Micropolitan Statistical Areas (MSA)
OMB defines a ``Micropolitan Statistical Area'' as a CBSA
associated with at least one urban cluster that has a population of at
least 10,000, but less than 50,000 (75 FR 37252). We refer to these as
Micropolitan Areas. After extensive impact analysis, consistent with
the treatment of these areas under the IPPS as discussed in the FY 2005
IPPS final rule (69 FR 49029 through 49032), we determined the best
course of action would be to treat Micropolitan Areas as ``rural'' and
include them in the calculation of each State's IPF PPS rural wage
index. We refer the reader to the FY 2007 IPF PPS final rule (71 FR
27064 through 27065) for a complete discussion regarding treating
Micropolitan Areas as rural.
c. Proposed Adjustment for Rural Location
In the November 2004 IPF PPS final rule, (69 FR 66954), we provided
a 17 percent payment adjustment for IPFs located in a rural area. This
adjustment was based on the regression analysis, which indicated that
the per diem cost of rural facilities was 17 percent higher than that
of urban facilities after accounting for the influence of the other
variables included in the regression. This 17 percent adjustment has
been part of the IPF PPS each year since the inception of the IPF PPS.
For FY 2024, we propose to apply a 17 percent payment adjustment for
IPFs located in a rural area as defined at Sec. 412.64(b)(1)(ii)(C)
(see 69 FR 66954 for a complete discussion of the adjustment for rural
locations).
d. Proposed Budget Neutrality Adjustment
Changes to the wage index are made in a budget-neutral manner so
that updates do not increase expenditures. Therefore, for FY 2024, we
propose to apply a budget-neutrality adjustment in accordance with our
existing budget-neutrality policy. This policy requires us to update
the wage index in such a way that total estimated payments to IPFs for
FY 2024 are the same with or without the changes (that is, in a budget-
neutral manner) by applying a budget-neutrality factor to the IPF PPS
rates. We use the following steps to ensure that the rates reflect the
FY 2024 update to the wage indexes (based on the FY 2020 hospital cost
report data) and the labor-related share in a budget-neutral manner:
Step 1: Simulate estimated IPF PPS payments, using the FY 2023 IPF
wage index values (available on the CMS website) and labor-related
share (as published in the FY 2023 IPF PPS final rule (87 FR 46846).
Step 2: Simulate estimated IPF PPS payments using the proposed FY
2024 IPF wage index values (available on the CMS website) and proposed
FY 2024 labor-related share (based on the latest available data as
discussed previously).
Step 3: Divide the amount calculated in step 1 by the amount
calculated in step 2. The resulting quotient is the proposed FY 2024
budget-neutral wage adjustment factor of 1.0011.
Step 4: Apply the FY 2024 budget-neutral wage adjustment factor
from step 3 to the FY 2023 IPF PPS Federal per diem base rate after the
application of the market basket update described in section III.A of
this proposed rule, to determine the FY 2024 IPF PPS Federal per diem
base rate.
2. Proposed Teaching Adjustment
a. Background
In the November 2004 IPF PPS final rule, we implemented regulations
at
[[Page 21264]]
Sec. 412.424(d)(1)(iii) to establish a facility-level adjustment for
IPFs that are, or are part of, teaching hospitals. The teaching
adjustment accounts for the higher indirect operating costs experienced
by hospitals that participate in graduate medical education (GME)
programs. The payment adjustments are made based on the ratio of the
number of fulltime equivalent (FTE) interns and residents training in
the IPF and the IPF's average daily census.
Medicare makes direct GME payments (for direct costs such as
resident and teaching physician salaries, and other direct teaching
costs) to all teaching hospitals including those paid under a PPS, and
those paid under the TEFRA rate-of-increase limits. These direct GME
payments are made separately from payments for hospital operating costs
and are not part of the IPF PPS. The direct GME payments do not address
the estimated higher indirect operating costs teaching hospitals may
face.
The results of the regression analysis of FY 2002 IPF data
established the basis for the payment adjustments included in the
November 2004 IPF PPS final rule. The results showed that the indirect
teaching cost variable is significant in explaining the higher costs of
IPFs that have teaching programs. We calculated the teaching adjustment
based on the IPF's ``teaching variable'', which is (1 + [the number of
FTE residents training in the IPF's average daily census]). The
teaching variable is then raised to the 0.5150 power to result in the
teaching adjustment. This formula is subject to the limitations on the
number of FTE residents, which are described in this section of this
proposed rule.
We established the teaching adjustment in a manner that limited the
incentives for IPFs to add FTE residents for the purpose of increasing
their teaching adjustment. We imposed a cap on the number of FTE
residents that may be counted for purposes of calculating the teaching
adjustment. The cap limits the number of FTE residents that teaching
IPFs may count for the purpose of calculating the IPF PPS teaching
adjustment, not the number of residents teaching institutions can hire
or train. We calculated the number of FTE residents that trained in the
IPF during a ``base year'' and used that FTE resident number as the
cap. An IPF's FTE resident cap is ultimately determined based on the
final settlement of the IPF's most recent cost report filed before
November 15, 2004 (69 FR 66955). A complete discussion of the temporary
adjustment to the FTE cap to reflect residents due to hospital closure
or residency program closure appears in the RY 2012 IPF PPS proposed
rule (76 FR 5018 through 5020) and the RY 2012 IPF PPS final rule (76
FR 26453 through 26456).
In the regression analysis, the logarithm of the teaching variable
had a coefficient value of 0.5150. We converted this cost effect to a
teaching payment adjustment by treating the regression coefficient as
an exponent and raising the teaching variable to a power equal to the
coefficient value. We note that the coefficient value of 0.5150 was
based on the regression analysis holding all other components of the
payment system constant. A complete discussion of how the teaching
adjustment was calculated appears in the November 2004 IPF PPS final
rule (69 FR 66954 through 66957) and the RY 2009 IPF PPS notice (73 FR
25721). As with other adjustment factors derived through the regression
analysis, we do not plan to propose updates to the teaching adjustment
factors until we more fully analyze IPF PPS data. Therefore, in this FY
2024 proposed rule, we propose to retain the coefficient value of
0.5150 for the teaching adjustment to the Federal per diem base rate.
3. Proposed Cost of Living Adjustment (COLA) for IPFs Located in Alaska
and Hawaii
The IPF PPS includes a payment adjustment for IPFs located in
Alaska and Hawaii based upon the area in which the IPF is located. As
we explained in the November 2004 IPF PPS final rule, the FY 2002 data
demonstrated that IPFs in Alaska and Hawaii had per diem costs that
were disproportionately higher than other IPFs. Other Medicare
prospective payment systems (for example, the IPPS and LTCH PPS)
adopted a COLA to account for the cost differential of care furnished
in Alaska and Hawaii.
We analyzed the effect of applying a COLA to payments for IPFs
located in Alaska and Hawaii. The results of our analysis demonstrated
that a COLA for IPFs located in Alaska and Hawaii will improve payment
equity for these facilities. As a result of this analysis, we provided
a COLA in the November 2004 IPF PPS final rule.
A COLA for IPFs located in Alaska and Hawaii is made by multiplying
the non-labor-related portion of the Federal per diem base rate by the
applicable COLA factor based on the COLA area in which the IPF is
located.
The COLA factors through 2009 were published by the Office of
Personnel Management (OPM), and the OPM memo showing the 2009 COLA
factors is available at https://www.chcoc.gov/content/nonforeign-area-retirement-equity-assurance-act.
We note that the COLA areas for Alaska are not defined by county as
are the COLA areas for Hawaii. In 5 CFR 591.207, the OPM established
the following COLA areas:
City of Anchorage, and 80-kilometer (50-mile) radius by
road, as measured from the Federal courthouse.
City of Fairbanks, and 80-kilometer (50-mile) radius by
road, as measured from the Federal courthouse.
City of Juneau, and 80-kilometer (50-mile) radius by road,
as measured from the Federal courthouse.
Rest of the State of Alaska.
As stated in the November 2004 IPF PPS final rule, we update the
COLA factors according to updates established by the OPM. However,
sections 1911 through 1919 of the Non-foreign Area Retirement Equity
Assurance Act, as contained in subtitle B of title XIX of the National
Defense Authorization Act (NDAA) (Pub. L. 111-84, October 28, 2009),
for FY 2010 transitions the Alaska and Hawaii COLAs to locality pay.
Under section 1914 of NDAA, locality pay was phased in over a 3-year
period beginning in January 2010, with COLA rates frozen as of the date
of enactment, October 28, 2009, and then proportionately reduced to
reflect the phase-in of locality pay.
When we published the proposed COLA factors in the RY 2012 IPF PPS
proposed rule (76 FR 4998), we inadvertently selected the FY 2010 COLA
rates, which had been reduced to account for the phase-in of locality
pay. We did not intend to propose the reduced COLA rates because that
would have understated the adjustment. Since the 2009 COLA rates did
not reflect the phase-in of locality pay, we finalized the FY 2009 COLA
rates for RY 2010 through RY 2014.
In the FY 2013 IPPS/LTCH final rule (77 FR 53700 through 53701), we
established a new methodology to update the COLA factors for Alaska and
Hawaii, and adopted this methodology for the IPF PPS in the FY 2015 IPF
final rule (79 FR 45958 through 45960). We adopted this new COLA
methodology for the IPF PPS because IPFs are hospitals with a similar
mix of commodities and services. We believe it is appropriate to have a
consistent policy approach with that of other hospitals in Alaska and
Hawaii. Therefore, the IPF COLAs for FY 2015 through FY 2017 were the
same as those applied under the IPPS in those years. As finalized in
the FY 2013 IPPS/LTCH PPS final rule (77 FR 53700 and 53701), the COLA
updates are determined every
[[Page 21265]]
4 years, when the IPPS market basket labor-related share is updated.
Because the labor-related share of the IPPS market basket was updated
for FY 2022, the COLA factors were updated in FY 2022 IPPS/LTCH
rulemaking (86 FR 45547). As such, we also updated the IPF PPS COLA
factors for FY 2022 (86 FR 42621 through 42622) to reflect the updated
COLA factors finalized in the FY 2022 IPPS/LTCH rulemaking. Table 16
shows the proposed IPF PPS COLA factors effective for FY 2022 through
FY 2025.
Table 16--IPF PPS Cost-of-Living-Adjustment Factors: IPFs Located in
Alaska and Hawaii
------------------------------------------------------------------------
FY 2022 through FY
Area 2025
------------------------------------------------------------------------
Alaska:
City of Anchorage and 80-kilometer (50-mile) radius 1.22
by road............................................
City of Fairbanks and 80-kilometer (50-mile) radius 1.22
by road............................................
City of Juneau and 80-kilometer (50-mile) radius by 1.22
road...............................................
Rest of Alaska...................................... 1.24
Hawaii:
City and County of Honolulu......................... 1.25
County of Hawaii.................................... 1.22
County of Kauai..................................... 1.25
County of Maui and County of Kalawao................ 1.25
------------------------------------------------------------------------
The proposed IPF PPS COLA factors for FY 2024 are also shown in
Addendum A to this proposed rule, and is available at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/InpatientPsychFacilPPS/tools.html.
4. Proposed Adjustment for IPFs With a Qualifying Emergency Department
(ED)
The IPF PPS includes a facility-level adjustment for IPFs with
qualifying EDs. We provide an adjustment to the Federal per diem base
rate to account for the costs associated with maintaining a full-
service ED. The adjustment is intended to account for ED costs incurred
by a psychiatric hospital with a qualifying ED or an excluded
psychiatric unit of an IPPS hospital or a CAH, for preadmission
services otherwise payable under the Medicare Hospital Outpatient
Prospective Payment System (OPPS), furnished to a beneficiary on the
date of the beneficiary's admission to the hospital and during the day
immediately preceding the date of admission to the IPF (see Sec.
413.40(c)(2)), and the overhead cost of maintaining the ED. This
payment is a facility-level adjustment that applies to all IPF
admissions (with one exception, which we described), regardless of
whether a particular patient receives preadmission services in the
hospital's ED.
The ED adjustment is incorporated into the variable per diem
adjustment for the first day of each stay for IPFs with a qualifying
ED. Those IPFs with a qualifying ED receive an adjustment factor of
1.31 as the variable per diem adjustment for day 1 of each patient
stay. If an IPF does not have a qualifying ED, it receives an
adjustment factor of 1.19 as the variable per diem adjustment for day 1
of each patient stay.
The ED adjustment is made on every qualifying claim except as
described in this section of this proposed rule. As specified in Sec.
412.424(d)(1)(v)(B), the ED adjustment is not made when a patient is
discharged from an IPPS hospital or CAH and admitted to the same IPPS
hospital's or CAH's excluded psychiatric unit. We clarified in the
November 2004 IPF PPS final rule (69 FR 66960) that an ED adjustment is
not made in this case because the costs associated with ED services are
reflected in the DRG payment to the IPPS hospital or through the
reasonable cost payment made to the CAH.
Therefore, when patients are discharged from an IPPS hospital or
CAH and admitted to the same hospital's or CAH's excluded psychiatric
unit, the IPF receives the 1.19 adjustment factor as the variable per
diem adjustment for the first day of the patient's stay in the IPF. For
FY 2024, we propose to retain the 1.31 adjustment factor for IPFs with
qualifying EDs. A complete discussion of the steps involved in the
calculation of the ED adjustment factors are in the November 2004 IPF
PPS final rule (69 FR 66959 through 66960) and the RY 2007 IPF PPS
final rule (71 FR 27070 through 27072).
E. Other Proposed Payment Adjustments and Policies
1. Outlier Payment Overview
The IPF PPS includes an outlier adjustment to promote access to IPF
care for those patients who require expensive care and to limit the
financial risk of IPFs treating unusually costly patients. In the
November 2004 IPF PPS final rule, we implemented regulations at Sec.
412.424(d)(3)(i) to provide a per case payment for IPF stays that are
extraordinarily costly. Providing additional payments to IPFs for
extremely costly cases strongly improves the accuracy of the IPF PPS in
determining resource costs at the patient and facility level. These
additional payments reduce the financial losses that would otherwise be
incurred in treating patients who require costlier care, and therefore,
reduce the incentives for IPFs to under-serve these patients. We make
outlier payments for discharges in which an IPF's estimated total cost
for a case exceeds a fixed dollar loss threshold amount (multiplied by
the IPF's facility-level adjustments) plus the Federal per diem payment
amount for the case.
In instances when the case qualifies for an outlier payment, we pay
80 percent of the difference between the estimated cost for the case
and the adjusted threshold amount for days 1 through 9 of the stay
(consistent with the median LOS for IPFs in FY 2002), and 60 percent of
the difference for day 10 and thereafter. The adjusted threshold amount
is equal to the outlier threshold amount adjusted for wage area,
teaching status, rural area, and the COLA adjustment (if applicable),
plus the amount of the Medicare IPF payment for the case. We
established the 80 percent and 60 percent loss sharing ratios because
we were concerned that a single ratio established at 80 percent (like
other Medicare PPSs) might provide an incentive under the IPF per diem
payment system to increase LOS in order to receive additional payments.
After establishing the loss sharing ratios, we determined the
current fixed dollar loss threshold amount through payment simulations
designed to compute a dollar loss beyond which payments are estimated
to meet the 2
[[Page 21266]]
percent outlier spending target. Each year when we update the IPF PPS,
we simulate payments using the latest available data to compute the
fixed dollar loss threshold so that outlier payments represent 2
percent of total estimated IPF PPS payments.
2. Proposed Update to the Outlier Fixed Dollar Loss Threshold Amount
In accordance with the update methodology described in Sec.
412.428(d), we propose to update the fixed dollar loss threshold amount
used under the IPF PPS outlier policy. Based on the regression analysis
and payment simulations used to develop the IPF PPS, we established a 2
percent outlier policy, which strikes an appropriate balance between
protecting IPFs from extraordinarily costly cases while ensuring the
adequacy of the Federal per diem base rate for all other cases that are
not outlier cases.
Our longstanding methodology for updating the outlier fixed dollar
loss threshold involves using the best available data, which is
typically the most recent available data. For the FY 2022 IPF PPS final
rule, we finalized the use of FY 2019 claims rather than the more
recent FY 2020 claims for updating the outlier fixed dollar loss
threshold (86 FR 42623). We noted that our use of the FY 2019 claims to
set the final outlier fixed dollar loss threshold for FY 2022 deviated
from our longstanding practice of using the most recent available year
of claims, but remained otherwise consistent with the established
outlier update methodology. We explained that we finalized our proposal
to deviate from our longstanding practice of using the most recent
available year of claims only because, and to the extent that, the
``coronavirus disease 2019'' (abbreviated ``COVID-19'') Public Health
Emergency (PHE) appeared to have significantly impacted the FY 2020 IPF
claims. We further stated that we intended to continue to analyze
further data in order to better understand both the short-term and
long-term effects of the COVID-19 PHE on IPFs (86 FR 42624).
In the FY 2023 IPF PPS final rule (87 FR 46862 through 46864) we
noted that we observed an overall increase in average cost per day and
an overall decrease in the number of covered days. However, we
identified that some providers had significant increases in their
charges, resulting in higher than normal estimated cost per day that
would skew our estimate of outlier payments for FY 2022 and FY 2023. We
finalized our proposal for FY 2023 to use the latest available FY 2021
claims, in accordance with our longstanding practice, to simulate
payments for determining the final FY 2023 IPF PPS outlier fixed dollar
loss threshold amount. In addition, we finalized a methodology for FY
2023 to exclude providers from our impact simulations whose change in
simulated cost per day is outside 3 standard deviations from the mean.
For this FY 2024 IPF PPS proposed rulemaking, consistent with our
longstanding practice, we analyzed the most recent available data for
simulating IPF PPS payments in FY 2023. Based on an analysis of these
updated data, we estimate that IPF outlier payments as a percentage of
total estimated payments are approximately 3.0 percent in FY 2023. We
analyzed the change in providers' charges from the FY 2021 claims that
were used to simulate payments for determining the final FY 2023 IPF
PPS outlier threshold, and the latest available FY 2022 claims. In
contrast to our analysis of FY 2021 claims for the FY 2023 IPF PPS
proposed and final rules, we did not find the same level of significant
increases in charges in the FY 2022 claims that we believe would skew
our estimate of outlier payments for FY 2023 and FY 2024. Therefore, we
propose to update the outlier threshold amount to $34,750. This would
allow us to maintain estimated outlier payments at 2 percent of total
estimated aggregate IPF payments for FY 2024. This proposed update is
an increase from the FY 2023 threshold of $24,630. We are soliciting
comments on this proposed increase to the outlier threshold for FY
2024, and whether we should consider alternative methodologies for FY
2024. Specifically, we are interested in understanding whether
commenters believe it would be appropriate to exclude providers from
our FY 2024 impact simulations whose change in simulated cost per day
is outside 3 standard deviations from the mean, following the same
methodology we applied in FY 2023. We note that our analysis for this
FY 2024 proposed rule shows that the FY 2024 outlier fixed dollar loss
threshold amount would be closer to $30,000 if we were to exclude
providers based on the same methodology finalized for FY 2023. We are
also interested in other methodologies that commenters believe might be
appropriate to consider, including why commenters believe applying such
a methodology would be appropriate for establishing the outlier
threshold for FY 2024.
3. Proposed Update to IPF Cost-to-Charge Ratio Ceilings
Under the IPF PPS, an outlier payment is made if an IPF's cost for
a stay exceeds a fixed dollar loss threshold amount plus the IPF PPS
amount. In order to establish an IPF's cost for a particular case, we
multiply the IPF's reported charges on the discharge bill by its
overall cost-to-charge ratio (CCR). This approach to determining an
IPF's cost is consistent with the approach used under the IPPS and
other PPSs. In the FY 2004 IPPS final rule (68 FR 34494), we
implemented changes to the IPPS policy used to determine CCRs for IPPS
hospitals, because we became aware that payment vulnerabilities
resulted in inappropriate outlier payments. Under the IPPS, we
established a statistical measure of accuracy for CCRs to ensure that
aberrant CCR data did not result in inappropriate outlier payments.
As indicated in the November 2004 IPF PPS final rule (69 FR 66961),
we believe that the IPF outlier policy is susceptible to the same
payment vulnerabilities as the IPPS; therefore, we adopted a method to
ensure the statistical accuracy of CCRs under the IPF PPS.
Specifically, we adopted the following procedure in the November 2004
IPF PPS final rule:
Calculated two national ceilings, one for IPFs located in
rural areas and one for IPFs located in urban areas.
Computed the ceilings by first calculating the national
average and the standard deviation of the CCR for both urban and rural
IPFs using the most recent CCRs entered in the most recent Provider
Specific File (PSF) available.
For FY 2024, we propose to continue to follow this methodology.
To determine the rural and urban ceilings, we multiplied each of
the standard deviations by 3 and added the result to the appropriate
national CCR average (either rural or urban). The upper threshold CCR
for IPFs in FY 2024 is 2.0801 for rural IPFs, and 1.7864 for urban
IPFs, based on CBSA-based geographic designations. If an IPF's CCR is
above the applicable ceiling, the ratio is considered statistically
inaccurate, and we assign the appropriate national (either rural or
urban) median CCR to the IPF.
We apply the national median CCRs to the following situations:
New IPFs that have not yet submitted their first Medicare
cost report. We continue to use these national median CCRs until the
facility's actual CCR can be computed using the first tentatively or
final settled cost report.
[[Page 21267]]
IPFs whose overall CCR is in excess of three standard
deviations above the corresponding national geometric mean (that is,
above the ceiling).
Other IPFs for which the Medicare Administrative
Contractor (MAC) obtains inaccurate or incomplete data with which to
calculate a CCR.
We propose to update the FY 2024 national median and ceiling CCRs
for urban and rural IPFs based on the CCRs entered in the latest
available IPF PPS PSF.
Specifically, for FY 2024, to be used in each of the three
situations listed previously, using the most recent CCRs entered in the
CY 2022 PSF, we provide an estimated national median CCR of 0.5720 for
rural IPFs and a national median CCR of 0.4200 for urban IPFs. These
calculations are based on the IPF's location (either urban or rural)
using the CBSA-based geographic designations. A complete discussion
regarding the national median CCRs appears in the November 2004 IPF PPS
final rule (69 FR 66961 through 66964).
4. Proposed Modification to the Regulation for Excluded Psychiatric
Units Paid Under the IPF PPS
a. Background
Under current regulation, in order to be excluded from the IPPS and
paid under the IPF PPS or the IRF PPS, an IPF or IRF unit of a hospital
must meet a number of requirements under 42 CFR 412.25. As discussed in
the following paragraphs, both this regulation and the policies
applying to excluded units (which include excluded IRF units and
excluded IPF units) have been in effect since before both the IPF PPS
and IRF PPS were established. Before the IRF PPS and the IPF PPS were
established, excluded units were paid based on their costs, as reported
on their Medicare cost reports, subject to certain facility-specific
cost limits. These cost-based payments were determined separately for
operating and capital costs. Thus, under cost-based payments, the
process of allocating costs to an IPF unit for reimbursement created
significant administrative complexity. This administrative complexity
necessitated strict regulations that allowed hospitals to open a new
IPPS-excluded unit only at the start of a cost reporting period.
In the January 3, 1984 final rule (49 FR 235), CMS (then known as
the Health Care Financing Administration) established policies and
regulations for hospitals and units subject to and excluded from the
IPPS. In that rule, we explained that section 1886(d) of the Act
requires that the prospective payment system apply to inpatient
hospital services furnished by all hospitals participating in the
Medicare program except those hospitals or units specifically excluded
by the law. We further explained our expectation that a hospital's
status (that is, whether it is subject to, or excluded from, the
prospective payment system) would generally be determined at the
beginning of each cost reporting period. We also stated that this
status would continue throughout the period, which is normally 1 year.
Accordingly, we stated that changes in a hospital's (or unit's) status
that result from meeting or failing to meet the criteria for exclusion
would be implemented only at the start of a cost reporting period.
However, we also acknowledged that under some circumstances involving
factors external to the hospital, status changes could be made at times
other than the beginning of the cost reporting period. For example, a
change in status could occur if a hospital is first included under the
prospective payment system and, after the start of its cost reporting
period, is excluded because of its participation in an approved
demonstration project or State reimbursement control program that
begins after the hospital's cost reporting period has begun.
In the 1993 IPPS final rule (57 FR 39798 through 39799), we
codified our longstanding policies regarding when a hospital unit can
change its status from not excluded to excluded. We explained in that
final rule that since the inception of the PPS for operating costs of
hospital inpatient services in October 1983, certain types of
specialty-care hospitals and hospital units have been excluded from
that system under section 1888(d)(1)(B) of the Act. We noted that these
currently include psychiatric and rehabilitation hospitals and distinct
part units, children's hospitals, and long-term care hospitals. We
further explained that section 6004(a)(1) of Public Law 101-239 amended
section 1886(d)(1)(B) of the Act to provide that certain cancer
hospitals are also excluded. We noted that the preamble to the January
3, 1984 final rule implementing the PPS for operating costs (49 FR 235)
stated that the status of a hospital or unit (that is, whether it is
subject to, or excluded from, the PPS) will be determined at the
beginning of each cost reporting period. We noted that that same 1984
final rule also provided that changes in a hospital's or unit's status
that result from meeting or failing to meet the criteria for exclusion
will be implemented prospectively only at the start of a cost reporting
period, that is, starting with the beginning date of the next cost
reporting period (49 FR 243). However, we noted that this policy was
not set forth in the regulations. In that 1993 IPPS final rule, we
stated that we proposed revising Sec. Sec. 412.22 and 412.25 to
specify that changes in the status of each hospital or hospital unit
would be recognized only at the start of a cost reporting period. We
stated that, except in the case of retroactive payment adjustments for
excluded rehabilitation units described in Sec. 412.30(c), any change
in a hospital's or unit's compliance with the exclusion criteria that
occurs after the start of a cost reporting period would not be taken
into consideration until the start of the following period. We noted
that this policy would also apply to any unit that is added to a
hospital during the hospital's cost reporting period. We also stated
that we proposed revising Sec. 412.25(a) to specify that as a
requirement for exclusion, a hospital unit must be fully equipped and
staffed, and be capable of providing inpatient psychiatric or
rehabilitation care as of the first day of the first cost reporting
period for which all other exclusion requirements are met. We explained
that a unit that meets this requirement would be considered open
regardless of whether there are any inpatients in the unit.
In the same 1993 IPPS final rule, we responded to commenters who
objected to this policy, stating that it unnecessarily penalizes
hospitals for factors beyond their control, such as construction
delays, that it discourages hospitals from making changes in their
programs to meet community needs, or that it can place undue workload
demands on regulatory agencies during certain time periods. In
response, we explained that we believed that regulatory agencies,
hospitals, and the public generally would benefit from policies that
are clearly stated, can be easily understood by both hospitals and
intermediaries, and can be simply administered. We stated that
recognizing changes in status only at the beginning of cost reporting
periods is consistent with these goals, while recognizing changes in
the middle of cost reporting periods would introduce added complexity
to the administration of the exclusion provisions. Therefore, we did
not revise the proposed changes based on these comments.
In the FY 2000 IPPS final rule (64 FR 41531 through 41532), we
amended the regulations at Sec. 412.25(c) to allow a hospital unit to
change from excluded to not excluded at any time during the cost
reporting period. We explained the statutory basis and rationale for
this change in the FY 2000 IPPS proposed rule (64 FR 24740), and noted
that a
[[Page 21268]]
number of hospitals suggested that we consider a change in our policy
to recognize, for purposes of exclusion from the IPPS, reductions in
number of beds in, or entire closure of, units at any time during a
cost reporting period. In that FY 2000 IPPS proposed rule, we explained
that hospitals indicated that the bed capacity made available as a
result of these changes could be used as needed to provide additional
services to meet patient needs in the acute care part of the hospital
that is paid under the IPPS. We further explained that we evaluated the
concerns of the hospitals and the effects on the administration of the
Medicare program and the health care of beneficiaries of making these
payment changes. As a result of that evaluation, we stated that we
believed it was reasonable to adopt a more flexible policy in
recognition of hospitals' changes in the use of their facilities.
However, we noted that whenever a hospital establishes an excluded unit
within the hospital, our Medicare fiscal intermediary would need to be
able to determine costs of the unit separately from costs of the part
of the hospital paid under the prospective payment system. At that
time, we stated that the proper determination of costs ensured that the
hospital was paid the correct amount for services in each part of the
facility, and that payments under the IPPS did not duplicate payments
made under the rules that were applicable to excluded hospitals and
units, or vice versa. For this reason, we did not believe it would be
appropriate to recognize, for purposes of exclusion from the IPPS,
changes in the bed size or status of an excluded unit that are so
frequent that they interfere with the ability of the intermediary to
accurately determine costs. Moreover, we explained that section
1886(d)(1)(B) of the Act authorizes exclusion from the IPPS of specific
types of hospitals and units, but not of specific admissions or stays,
such as admissions for rehabilitation or psychiatric care, in a
hospital paid under the IPPS. We stated that without limits on the
frequency of changes in excluded units for purposes of proper Medicare
payment, there was the potential for some hospitals to adjust the
status or size of their excluded units so frequently that the units
would no longer be distinct entities and the exclusion would
effectively apply only to certain types of care.
In the FY 2012 IRF PPS final rule (76 FR 47870), we began further
efforts to increase flexibilities for excluded IPF and IRF units. In
that rule, we explained that cost-based reimbursement methodologies
that were in place before the IPF PPS and IRF PPS meant that the
facilities' capital costs were determined, in part, by their bed size
and square footage. Changes in the bed size and square footage would
complicate the facilities' capital cost allocation. Thus, regulations
at Sec. 412.25 limited the situations under which an IRF or IPF could
change its bed size and square footage. In the FY 2012 IRF PPS final
rule, we revised Sec. 412.25(b) to enable IRFs and IPFs to more easily
adjust to beneficiary changes in demand for IRF or IPF services, and
improve beneficiary access to these services. We believed that the
first requirement (that beds can only be added at the start of a cost
reporting period) was difficult, and potentially costly, for IRFs and
IPFs that were expanding through new construction because the exact
timing of the end of a construction project is often difficult to
predict. In that same FY 2012 IRF PPS final rule, commenters suggested
that CMS allow new IRF units or new IPF units to open and begin being
paid under their respective IRF PPS or IPF PPS at any time during a
cost reporting period, rather than requiring that they could only begin
being paid under the IRF PPS or the IPF PPS at the start of a cost
reporting period. We believed that this suggestion was outside the
scope of the FY 2012 IRF PPS proposed rule (76 FR 24214) because we did
not propose any changes to the Sec. 412.25(c). However, we stated that
we would consider this suggestion for possible inclusion in future
rulemaking.
b. Current Challenges Related to Excluded Hospital Units (Sec. Sec.
412.25(c)(1) and (c)(2))
Currently, under Sec. 412.25(c)(1), a hospital can only start
being paid under the IPF PPS or the IRF PPS for services provided in an
excluded hospital unit at the start of a cost reporting period.
Specifically, Sec. 412.25(c) limits when the status of hospital units
may change for purposes of exclusion from the IPPS, as specified in
Sec. 412.25(c)(1) and Sec. 412.25(c)(2). Section 412.25(c)(1) states
that the status of a hospital unit may be changed from not excluded to
excluded only at the start of the cost reporting period. If a unit is
added to a hospital after the start of a cost reporting period, it
cannot be excluded from the IPPS before the start of a hospital's next
cost reporting period. Section 412.25(c)(2) states the status of a
hospital unit may be changed from excluded to not excluded at any time
during a cost reporting period, but only if the hospital notifies the
fiscal intermediary and the CMS Regional Office in writing of the
change at least 30 days before the date of the change, and maintains
the information needed to accurately determine costs that are or are
not attributable to the excluded unit. A change in the status of a unit
from excluded to not excluded that is made during a cost reporting
period must remain in effect for the rest of that cost reporting
period.
In recent years, interested parties, such as hospitals, have
written CMS to express concerns about what they see as the unnecessary
restrictiveness of the requirements at Sec. 412.25(c). Based on this
feedback, we continued to explore opportunities to reduce burden for
providers and clinicians, while keeping patient-centered care a
priority. For instance, we considered whether this regulation might
create unnecessary burden for hospitals and potentially delay necessary
psychiatric beds from opening and being paid under the IPF PPS. As we
continued to review and reconsider regulations to identify ways to
improve policy, we recognized that the requirement at Sec.
412.25(c)(1), that hospital units can only be excluded at the start of
a cost reporting period, may be challenging and potentially costly for
facilities under some circumstances, for example, those that are
expanding through new construction. Hospitals have indicated it is
often difficult to predict the exact timing of the end of a
construction project and construction delays may hamper a hospital's
ability to have the construction of an excluded unit completed exactly
at the start of a cost reporting period, which hospitals have said can
lead to significant revenue loss if they are unable to be paid under
the IPF PPS or IRF PPS until the start of the next cost reporting
period.
As previously stated, the requirements at Sec. 412.25(c) were
established to manage the administrative complexity associated with
cost-based reimbursement for excluded IPF and IRF units. Today,
however, because IPF units are paid under the IPF PPS and IRF units are
paid under the IRF PPS, cost allocation is not used for payment
purposes. Because advancements in technology since the inception of the
IPF PPS and IRF PPS have simplified the cost reporting process and
enhanced communication between providers, Medicare contractors, and
CMS, we are reconsidering whether it is necessary to continue to allow
hospital units to become excluded only at the start of a cost reporting
period.
[[Page 21269]]
c. Proposed Changes to Excluded Hospital Units (Sec. Sec. 412.25(c)(1)
and (c)(2))
We are committed to continuing to transform the health care
delivery system and the Medicare program by putting additional focus on
patient-centered care and working with providers, physicians, and
patients to improve outcomes, while meeting relevant health care
priorities and explore burden reduction.
In response to increased mental health needs, including the need
for availability of inpatient psychiatric beds, we propose changes to
Sec. 412.25(c) to allow greater flexibility for hospitals to open
excluded units, while minimizing the amount of effort Medicare
contractors would need to spend administering the regulatory
requirements. Although we are cognizant that there is need for mental
health services and support for providers along a continuum of care,
including a robust investment in community-based mental health
services, this propose rule is focused on inpatient psychiatric
facility settings.
We note that Sec. 412.25(c) applies to both IPFs and IRFs;
therefore, revisions to Sec. 412.25(c) would also affect IRFs in
similar ways. Readers should refer to the FY 2024 IRF PPS proposed rule
for discussion of proposed revisions to Sec. 412.25(c) and unique
considerations applicable to IRF units. As previously stated the
current requirements at Sec. 412.25(c)(1) were originally established
to manage the administrative complexity associated with cost-based
reimbursement for excluded IPF and IRF units. Because IPF and IRF units
are no longer paid under cost-based reimbursement, but rather under the
IPF PPS and IRF PPS respectively, we believe that the restriction that
limits an IPF or IRF unit to being excluded only at the start of a cost
reporting period is no longer necessary. We amended our regulations in
the FY 2012 IRF PPS final rule to address a regulation that, similarly,
was previously necessary for cost-based reimbursement, but was not
material to payment under the IRF PPS and IPF PPS. In that final rule,
we explained that under cost-based payments, the facilities' capital
costs were determined, in part, by their bed size and square footage.
Changes in the bed size and square footage would complicate the
facilities' capital cost allocation. We explained that under the IRF
PPS and IPF PPS, a facility's bed size and square footage were not
relevant for determining the individual facility's Medicare payment.
Therefore, we believed it was appropriate to modify some of the
restrictions on a facility's ability to change its bed size and square
footage. Accordingly, we relaxed the restrictions on a facility's
ability to increase its bed size and square footage. Under the revised
requirements that we adopted in the FY 2012 IRF PPS final rule at Sec.
412.25(b), an IRF or IPF can change (either increase or decrease) its
bed size or square footage one time at any point in a given cost
reporting period as long as it notifies the CMS Regional Office (RO) at
least 30 days before the date of the proposed change, and maintains the
information needed to accurately determine costs that are attributable
to the excluded units.
Similarly, in the case of the establishment of new excluded IPF and
IRF units, we do not believe that the timing of the establishment of
the new unit is material for determining the individual facility's
Medicare payment under the IPF PPS or IRF PPS. We believe it would be
appropriate to allow a unit to become excluded at any time in the cost
reporting year. However, we also believe it is important to minimize
the potential administrative complexity associated with units changing
their excluded status.
Accordingly, we propose to modify the requirements currently in
regulation at Sec. 412.25(c)(1) to allow a hospital to open a new IPF
unit any time within the cost reporting year, as long as the hospital
notifies the CMS Regional Office and Medicare Administrative Contractor
(MAC) in writing of the change at least 30 days before the date of the
change. Additionally, we propose that if a unit becomes excluded during
a cost reporting year, the hospital must notify the MAC and CMS
Regional Office in writing of the change at least 30 days before the
change, and this change would remain in effect for the rest of that
cost reporting year. We also propose to maintain the current
requirements of Sec. 412.25(c)(2) which specify that, if an excluded
unit becomes not excluded during a cost reporting year, the hospital
must notify the MAC and CMS Regional Office in writing of the change at
least 30 days before the change, and this change would remain in effect
for the rest of that cost reporting year. Finally, we propose to
consolidate the requirements for Sec. 412.25(c)(1) and Sec.
412.25(c)(2) into a new Sec. 412.25(c)(2) that would apply to IPF
units and specify the requirements for an IPF unit to become excluded
or not excluded. We believe this proposal would provide greater
flexibility to hospitals to establish an excluded unit at a time other
than the start of a cost reporting period. We welcome comments on this
proposed change.
As noted above, we propose an identical policy for rehabilitation
units of hospitals in the FY 2024 IRF PPS proposed rule. The regulatory
provision that would pertain to IRF units would appear in Sec.
412.25(c)(1). We propose discrete regulations text for each of the
hospital unit types (that is, IRF units and IPF units) in order to
solicit comments on issues that might impact one hospital unit type and
not the other. However, we may consider adopting one consolidated
regulations text for both IRF and IPF units in the final rules if we
finalize both of our proposals. We solicit public comments on
finalizing a consolidated provision that would pertain to both IRF and
IPF units.
IV. Existing Data Collection and Request for Information (RFI) To
Inform Revisions to the IPF PPS as Required by the CAA, 2023
A. Changes to IPF PPS in the CAA, 2023
As discussed in section III.C.1 of this proposed rule, we propose
to continue using the existing regression-derived IPF PPS adjustment
factors for FY 2024. In the FY 2023 IPF PPS proposed rule (87 FR 19428
through 19429), we discussed the background of these current IPF PPS
patient-level and facility-level adjustment factors, which are the
regression-derived adjustment factors from the November 15, 2004 IPF
PPS final rule and briefly discussed past analyses and areas of concern
for future refinement, about which we previously solicited comments.
Finally, in the FY 2023 proposed rule, we described the results of the
latest analysis of the IPF PPS, which were summarized in a technical
report posted to the CMS website \2\ accompanying the rule, and
solicited comments on certain topics from the report.
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\2\ https://www.cms.gov/files/document/technical-report-medicare-program-inpatient-psychiatric-facilities-prospective-payment-system.pdf.
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Section 4125 of the CAA, 2023 amended section 1886(s) of the Act to
add new paragraph 1886(s)(5), which requires revisions to the
methodology for determining the payment rates under the IPF PPS for FY
2025 and future years as the Secretary determines appropriate.
Specifically, new section 1886(s)(5)(A) of the Act requires the
Secretary to collect data and information as the Secretary as
determines appropriate to revise payments under the IPF PPS. This data
collection is required to begin no later than October 1, 2023, which is
the start of FY 2024. In addition, new section 1886(s)(5)(D) of the Act
requires that the
[[Page 21270]]
Secretary implement by regulation revisions to the methodology for
determining the payment rates for psychiatric hospitals and psychiatric
units (that is, under the IPF PPS), for rate year 2025 (FY 2025) and
for subsequent years if the Secretary determines it appropriate. The
revisions may be based on a review of the data and information
collection.
As noted above, section 1886(s)(5)(A) of the Act requires the
Secretary to begin collecting, by not later than October 1, 2023, data
and information as appropriate to inform revisions to the IPF PPS. New
section 1886(s)(5)(B) of the Act, as added by the CAA, 2023 lists the
following types of data and information as a non-exhaustive list of
examples of what may be collected under this authority:
Charges, including those related to ancillary services;
The required intensity of behavioral monitoring, such as
cognitive deficit, suicidal ideations, violent behavior, and need for
physical restraint; and
Interventions, such as detoxification services for
substance abuse, dependence on respirator, total parenteral nutritional
support, dependence on renal dialysis, and burn care.
We note that our extensive years-long and ongoing data collection
efforts are consistent with the types of data the CAA, 2023 suggests we
might collect as well as the purpose for which the CAA, 2023 requires
the data collection, as described in the following paragraphs.
B. Current Data and Information Collection Requirements
1. Charges, Including Those Related to Ancillary Services
As specified at 42 CFR 413.20, hospitals are required to file cost
reports on an annual basis, and maintain sufficient financial records
and statistical data for proper determination of costs payable under
the Medicare program. Currently, IPFs and psychiatric units are
required to report ancillary charges on cost reports.
In general, most providers allocate their Medicare costs using
costs and charges as described at 42 CFR 413.53(a)(1)(i) and referred
to as the Departmental Method. For cost reporting periods beginning on
or after October 1, 1982, the Departmental Method, which is the ratio
of beneficiary charges to total patient charges for the services of
each ancillary department, is applied to apportion the cost of the
department. Added to this amount is the cost of routine services for
program beneficiaries, determined on the basis of a separate average
cost per diem for all patients for general routine patient care areas
as required at Sec. 413.53(a)(1)(i) and (e).
The Departmental Method for apportioning allowable cost between
Medicare and non-Medicare patients under the program is not readily
adaptable to those hospitals that do not have a charge structure.
Current cost reporting rules allow hospitals that do not have a charge
structure to file an all-inclusive cost report using an alternative
cost allocation method. These alternative methods as described in the
CMS Pub. 15-1, chapter 22 of the Provider Reimbursement Manual (PRM),
Methods A, B and E, in order of preference, must be approved by the MAC
after considering the data available and ascertaining which method can
be applied to achieve equity, not merely greater reimbursement, in the
allocation of costs for services rendered to Medicare beneficiaries.
Method A (Departmental Statistical Method) is used in the absence
of charge data and where adequate departmental statistics are
available. Where Method A was not used, the MAC may have granted
specific permission for a hospital to continue to use on a temporary
basis a less sophisticated Method B (Sliding Scale) or E (Percentage of
Per Diem). A provider that elects and is approved under Method A, may
not change to a Method B or E in a subsequent year. These alternative
methods of apportionment are limited and available only to those
hospitals that do not and never have had a charge structure for
individual services rendered. Historically, most hospitals that were
approved to file all-inclusive cost reports were Indian Health Services
hospitals, government-owned psychiatric and acute care hospitals, and
nominal charge hospitals.
In the FY 2016 IPF PPS final rule (80 FR 46693 through 46694), we
discussed analysis conducted to better understand IPF industry
practices for future IPF PPS refinements. This analysis revealed that
in 2012 to 2013, over 20 percent of IPF stays show no reported
ancillary costs, such as laboratory and drug costs, on cost reports or
charges on claims. In the FY 2016 IPF PPS final rule (80 FR 46694), FY
2017 IPF PPS final rule (81 FR 50513), FY 2018 IPF PPS final rule (82
FR 36784), FY 2019 IPF PPS final rule (83 FR 38588) and FY 2020 IPF PPS
final rule (84 FR 38458), we reminded providers that we pay only the
IPF for services furnished to a Medicare beneficiary who is an
inpatient of that IPF, except for certain professional services, and
payments are considered to be payments in full for all inpatient
hospital services provided directly or under arrangement (see 42 CFR
412.404(d)), as specified in 42 CFR 409.10.
On November 17, 2017, we issued Transmittal 12, which made changes
to the hospital cost report form CMS-2552-10 (OMB No. 0938-0050), and
included cost report Level I edit 10710S, effective for cost reporting
periods ending on or after August 31, 2017. Edit 10710S required that
cost reports from psychiatric hospitals include certain ancillary
costs, or the cost report will be rejected. On January 30, 2018, we
issued Transmittal 13, which changed the implementation date for
Transmittal 12 to be for cost reporting periods ending on or after
September 30, 2017. CMS suspended edit 10710S effective April 27, 2018,
pending evaluation of the application of the edit to all-inclusive-rate
providers. CMS issued Transmittal 15 on October 19, 2018, reinstating
the requirement that cost reports from psychiatric hospitals, except
all-inclusive rate providers, include certain ancillary costs. For
details, we refer readers to see these Transmittals, which are
available on the CMS website at https://www.cms.gov/regulations-and-guidance/guidance/transmittals.
2. Required Intensity of Behavioral Monitoring and Interventions
As discussed in the November 2004 IPF PPS final rule (69 FR 66946),
we encourage IPFs to code all diagnoses requiring active treatment
during the IPF stay. These include ICD-10-CM codes that indicate the
required intensity of behavioral monitoring, such as cognitive deficit,
suicidal ideations, violent behavior, and need for physical restraint.
The IPF PPS includes comorbidity and MS-DRG adjustment factors that
increase IPF PPS payment for stays that include these codes. For
example, ICD-10-CM codes X71 through X83 indicate self-harm. ICD-10-CM
codes under R45 indicate emotional state including violent behavior.
These and other ICD-10-CM codes indicate the required intensity of
behavioral monitoring and should be reported on the IPF claims, if
applicable.
The presence of certain ICD-10-CM codes as a principal or comorbid
condition is used to adjust IPF PPS payments to reflect the resource
intensity associated with these conditions. For example, codes that
group to MS-DRG 884 Organic Disturbances & Intellectual Disabilities,
and codes that are included in the IPF comorbidity category for
Developmental Disabilities, result in increased payment
[[Page 21271]]
for IPF stays for patients with cognitive deficit.
As we further discussed in the November 2004 IPF PPS final rule (69
FR 66938 through 66944), we developed comorbidity categories based on
the clinical expertise of physicians to identify conditions that would
require comparatively more costly treatment during an IPF stay than
other comorbid conditions. We used a regression analysis of
administrative claims and cost report data to determine the adjustment
factors associated with each comorbidity category. In addition, we used
the same regression analysis to determine the adjustment factors
associated with the 17 MS-DRGs that are included for payment
adjustments under the IPF PPS (as identified in Addendum A). As
discussed in section III.C.2.b of this proposed rule, we routinely
update the ICD-10-CM codes that are included in the MS-DRGs and
comorbidity categories.
We also collect relevant demographic information such as patient
age, and we collect information and adjust payment based on the length
of IPF stays. Each of these adjustments reflects the difference in
service intensity, as measured by increased or decreased costs, for
different patients over the course of an IPF stay.
In addition, IPFs and psychiatric units report on claims the ICD-
10-PCS codes for interventions including oncology treatment procedures,
which is used for adjusting payment under the oncology comorbidity
category, and ECT, which is paid for using a per treatment amount as
discussed in section III.B.2 of this FY 2024 IPF PPS proposed rule.
Other ICD-10-CM diagnosis codes indicate the need for certain
interventions, such as detoxification services or substance abuse (for
example, F10.121, which is included in the drug and alcohol abuse
comorbidity category), dependence on respirator (for example, Z99.11
included in the COPD category), and dependence on renal dialysis (for
example, Z99.2 included in the chronic renal failure category). We note
that the IPS PPF does not currently adjust for burn care, but recognize
there are ICD-10-CM/PCS codes that denote conditions and procedures
related to burn care. As discussed in the previous paragraph, the IPF
PPS includes comorbidity adjustments that reflect the higher relative
costs for active treatment of these conditions. IPF patients with these
conditions are costlier to treat primarily because of the costs
associated with interventions and longer lengths of stay.
3. Request for Information on Data and Information Collection
As noted in section IV.A of this proposed rule, our extensive
years-long and ongoing data collection efforts are consistent with the
types of data that the CAA, 2023 suggests we might collect, as well as
aligns with the purpose for which the CAA, 2023 requires the data
collection. In this proposed rule, we are requesting information from
the public to inform revisions to the IPF PPS required by section
4125(a) of the CAA, 2023. We are seeking information about specific
additional data and information psychiatric hospitals and psychiatric
units might report that could be appropriate and useful to help inform
possible revisions to the methodology for payment rates under the IPF
PPS for FY 2025 and future years if determined appropriate by the
Secretary.
Section 1886(s)(5)(C) of the Act provides that the Secretary may
collect additional data and information on cost reports, claims, or
otherwise. Therefore, we are also seeking information about potential
available data and information sources, including using additional
elements of the current cost reports, claims, or other sources, taking
into consideration factors such as the timing and availability of data,
the quality of the potential data and information to be collected, and
the potential administrative burden on providers, MACs, and CMS.
We are seeking comment on the following topics:
What other data and information would be beneficial for
informing revisions to the IPF PPS payment methodologies that are
currently obtainable through claims or cost report information? What
codes, conditions, or other indicators should we examine in order to
potentially identify this data from existing sources?
What other data and information would be beneficial for
informing revisions to the IPF PPS payment methodologies that are not
routinely coded on claims or identifiable through cost report
information? What are some potential alternative sources we could
consider for collecting these data and information?
What data and information that is currently reported on
claims data could be used to inform revisions to the IPF PPS payment
methodologies?
As we discussed earlier in this FY 2024 IPF PPS proposed
rule, the current IPF PPS payment adjustments were derived from a
regression analysis based on the FY 2002 MedPAR data file. The
adjustment factors included for payment were found in the regression
analysis to be associated with statistically significant per diem cost
differences; with statistical significance defined as p less than 0.05.
Are there alternative methodological approaches or considerations that
we should consider for future analysis?
What if any additional data or information should we
consider collecting that could address access to care in rural and
isolated communities?
4. Request for Information About Charges for Ancillary Services
In conjunction with the FY 2023 IPF PPS proposed rule (87 FR 19428
through 19429), we posted a report on the CMS website that summarizes
the results of the latest analysis of more recent IPF cost and claim
information for potential IPF PPS adjustments, and requested comments
about the results summarized in the report. That report showed that
approximately 23 percent of IPF stays were trimmed from the data set
used in that analysis because they were stays at facilities where fewer
than 5 percent of their stays had ancillary charges. This report is
available online at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/InpatientPsychFacilPPS.
In response to the comment solicitation, we received a comment from
MedPAC regarding facilities that do not report ancillary charges on
most or any of their claims. Ancillary services are the services for
which charges are customarily made in addition to routine services.
These include services such as labs, drugs, radiology, physical and
occupational therapy services, and other types of services that
typically vary between stays. Generally, based on the nature of IPF
services and the conditions of participation \3\ applicable to IPFs, we
expect to see ancillary services and correlating charges, such as labs
and drugs, on most IPF claims. Our ongoing analysis has found that
certain providers, especially for-profit freestanding IPFs, are
consistently reporting no ancillary charges or very minimal ancillary
charges. MedPAC stated that it is not known: whether IPFs fail to
report ancillary charges separately because they were appropriately
bundled with all other charges into an all-inclusive per diem rate; if
no ancillary charges were incurred because the IPF cares for a
[[Page 21272]]
patient mix with lower care needs or inappropriately stints on care; or
if ancillary charges for services furnished during the IPF stay are
inappropriately billed outside of the IPF base rate (unbundling).
MedPAC recommended CMS conduct further investigation into the lack of
certain ancillary costs and charges and whether IPFs are providing
necessary care and appropriately billing for inpatient psychiatric
services under the IPF PPS.
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\3\ IPFs are subject to all hospital conditions of
participation, including 42 CFR 482.25, which specifies that ``The
hospital must have pharmaceutical services that meet the needs of
the patients,'' and 482.27, which specifies that ``The hospital must
maintain, or have available, adequate laboratory services to meet
the needs of its patients.''
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As discussed in the previous section of this FY 2024 IPF PPS
proposed rule, we are requesting information related to the specific
types of data and information specified in the CAA, 2023, including the
reporting of charges for ancillary services, such as labs and drugs, on
IPF claims. We are interested in better understanding IPF industry
practices pertaining to the billing and provision of ancillary services
to inform future IPF PPS refinements. We are considering whether to
require charges for ancillary services to be reported on claims and
potentially reject claims if no ancillary services are reported, and
whether to consider payment for such claims to be inappropriate or
erroneous and subject to recoupment. Accordingly, we are soliciting
comments on the following questions:
What would be the appropriate level of ancillary charges
CMS should expect to be reported on claims? Are there specific reasons
that an IPF stay would include no ancillary services?
What are the reasons that some providers are not reporting
ancillary charges on their claims?
Would it be appropriate for CMS to require and reject
claims if there are no ancillary charges reported? Or should CMS
consider adjusting payment toto providers that do not report ancillary
charges on their claims? For example, does the lack of ancillary
charges on claims suggest a lack of reasonable and necessary treatment
during the IPF stay, and would it be appropriate for CMS to only apply
the IPF PPS patient-level adjustment factors for claims that include
ancillary charges?
C. Social Drivers of Health
Social drivers of health (SDOH), also known as social determinants
of health, are the conditions in the environments where people are
born, live, learn, work, play, worship, and age that affect a wide
range of health, functioning, and quality-of-life outcomes and
risks.\4\ Studies have shown that there is a correlation between the
effects of low income and education and overall health status. One
study derived that the lowest income and least educated individuals
were consistently least healthy.\5\ We have previously demonstrated our
commitment to advancing health equity and reducing health disparities.
In the past, and in our ongoing efforts, we have strived to identify
and implement policies, procedures, reporting protocols, and other
initiatives in a number of our programs that address the impact of SDOH
on an individual's health.
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\4\ https://health.gov/healthypeople/priority-areas/social-determinants-health.
\5\ Paula A. Braveman, Catherine Cubbin, Susan Egerter, David R.
Williams, and Elsie Pamuk, 2010: Socioeconomic Disparities in Health
in the United States: What the Patterns Tell Us American Journal of
Public Health 100, S186_S196, https://doi.org/10.2105/AJPH.2009.166082.
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For the IPF Quality Reporting Program, as discussed in section V.D
below of this proposed rule, we propose to adopt the Facility
Commitment to Health Equity measure for the FY 2026 payment
determination and subsequent years, the Screening for Social Drivers of
Health measure beginning with voluntary reporting of data beginning in
CY 2025 with required reporting for the FY 2027 payment determination
and subsequent years, and the Screen Positive Rate for Social Drivers
of Health measure beginning with voluntary reporting of data beginning
in CY 2024 with required reporting for the FY 2027 payment
determination and subsequent years.
Additionally, in the technical report \6\ accompanying the FY 2023
IPF PPS proposed rule, we explained that we analyzed the costs
associated with SDOH, but found that our analysis was confounded by a
low frequency of IPF claims reporting the applicable ICD-10 diagnosis
codes. In response to the FY 2023 IPF PPS proposed rule we received 10
comments pertaining to the report on the analysis of patient-level and
facility-level adjustment factors, and areas of interest for further
research, including additional SDOH analysis.
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\6\ https://www.cms.gov/files/document/technical-report-medicare-program-inpatient-psychiatric-facilities-prospective-payment-system.pdf.
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Working in collaboration with a contractor, subsequent analysis has
shown that other SDOH codes, such as Z59.9 Problem related to housing
and economic circumstances, unspecified, are associated with
statistically significant, higher costs. In general, our analysis found
that claims that included SDOH codes had lower costs than claims that
did not include such codes. This finding is counterintuitive; however,
we note that studies have found that there are disparities in the
reporting of SDOH codes, such as homelessness.\7\ Additionally, our
analysis found that certain codes were associated with increased cost
for IPF treatment. Specifically, the below SDOH codes in the analysis
were found to be statistically significant and had a stay count of
greater than 100. These codes had an adjustment factor above 1,
suggesting that these conditions may increase relative costliness of
IPF stays:
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\7\ https://aspe.hhs.gov/reports/health-conditions-among-individuals-history-homelessness-research-brief-0.
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Z559 Problems related to education and literacy,
unspecified.
Z599 Problems related to housing and economic
circumstances, unspecified.
Z600 Problems of adjustment to life-cycle transitions.
Z634 Disappearance and death of family member.
Z653 Problems related to other legal circumstances.
Z659 Problems related to unspecified psychosocial
circumstances.
We are seeking comments on these findings and information about
whether it would be appropriate to consider incorporating these codes
into the IPF PPS in the future, for example as a patient-level
adjustment. Specifically, for codes that are ``unspecified,'' we are
seeking information about what types of conditions or circumstances
these codes might represent. We are seeking any information that
commenters can provide about the reasons for including these codes on
claims. What factors do commenters believe we should consider in order
to better understand the cost regression results presented above?
V. Inpatient Psychiatric Facilities Quality Reporting (IPFQR) Program
A. Background and Statutory Authority
The Inpatient Psychiatric Facility Quality Reporting (IPFQR)
Program is authorized by section 1886(s)(4) of the Act, and it applies
to psychiatric hospitals and psychiatric units paid by Medicare under
the IPF PPS (see section V.B. of this proposed rule). Section
1886(s)(4)(A)(i) of the Act requires the Secretary to reduce by 2
percentage points the annual update to the standard Federal rate for
discharges for the IPF occurring during such fiscal year \8\ for
[[Page 21273]]
any IPF that does not comply with quality data submission requirements
under the IPFQR Program, set forth in accordance with section
1886(s)(4)(C) of the Act, with respect to an applicable fiscal year.
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\8\ We note that the statute uses the term ``rate year'' (RY).
However, beginning with the annual update of the inpatient
psychiatric facility prospective payment system (IPF PPS) that took
effect on July 1, 2011 (RY 2012), we aligned the IPF PPS update with
the annual update of the ICD codes, effective on October 1 of each
year. This change allowed for annual payment updates and the ICD
coding update to occur on the same schedule and appear in the same
Federal Register document, promoting administrative efficiency. To
reflect the change to the annual payment rate update cycle, we
revised the regulations at 42 CFR 412.402 to specify that, beginning
October 1, 2012, the IPF PPS RY means the 12-month period from
October 1 through September 30, which we refer to as a ``fiscal
year'' (FY) (76 FR 26435). Therefore, with respect to the IPFQR
Program, the terms ``rate year,'' as used in the statute, and
``fiscal year'' as used in the regulation, both refer to the period
from October 1 through September 30. For more information regarding
this terminology change, we refer readers to section III of the RY
2012 IPF PPS final rule (76 FR 26434 through 26435).
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Section 1886(s)(4)(C) of the Act requires IPFs to submit to the
Secretary data on quality measures specified by the Secretary under
section 1886(s)(4)(D) of the Act. Except as provided in section
1886(s)(4)(D)(ii) of the Act, section 1886(s)(4)(D)(i) of the Act
requires that any measure specified by the Secretary must have been
endorsed by the consensus-based entity (CBE) with a contract under
section 1890(a) of the Act. Section 1886(s)(4)(D)(ii) of the Act
provides that, in the case of a specified area or medical topic
determined appropriate by the Secretary for which a feasible and
practical measure has not been endorsed by the CBE with a contract
under section 1890(a) of the Act, the Secretary may specify a measure
that is not endorsed as long as due consideration is given to measures
that have been endorsed or adopted by a consensus organization
identified by the Secretary.
We refer readers to the FY 2019 IPF PPS final rule (83 FR 38589)
for a more detailed discussion of the background and statutory
authority of the IPFQR Program.
For the IPFQR Program, we refer to the year in which an IPF would
receive the 2-percentage point reduction to the annual update to the
standard Federal rate as the payment determination year. An IPF
generally meets IPFQR Program requirements by submitting data on
specified quality measures in a specified time and manner during a data
submission period that occurs prior to the payment determination year.
These data reflect a period prior to the data submission period during
which the IPF furnished care to patients; this period is known as the
performance period. For example, for a measure for which CY 2024 is the
performance period which is required to be submitted in CY 2025 and
affects FY 2026 payment determination, if an IPF did not submit the
data for this measure as specified during CY 2025 (and meets all other
IPFQR Program requirements for the FY 2026 payment determination) we
would reduce by 2-percentage points that IPF's update for the FY 2026
payment determination year.
In this proposed rule, we propose to codify the IPFQR Program
requirements governing IPF reporting on quality measures in a new
regulation at Sec. 412.433, which is the section preceding our
existing regulation governing reconsideration and appeals procedures
for IPFQR Program decisions in our regulations at Sec. 412.434.
Specifically, we propose to codify a general statement of the IPFQR
Program authority and structure at Sec. 412.433(a). If finalized,
paragraph (a) would cite section 1886(s)(4) of the Act, which requires
the Secretary to implement a quality reporting program for inpatient
psychiatric hospitals and psychiatric units. The proposed paragraph (a)
would also state that IPFs paid under the IPF PPS as provided in
section 1886(s)(1) of the Act that do not report data required for the
quality measures selected by the Secretary in a form and manner, and at
a time specified by the Secretary will incur a 2.0 percentage point
reduction to the annual update to the standard Federal rate with
respect to the applicable fiscal year.
We welcome comments on this proposal.
B. Covered Entities
In the FY 2013 IPPS/LTCH PPS final rule (77 FR 53645), we
established that the IPFQR Program's quality reporting requirements
cover those psychiatric hospitals and psychiatric units paid by
Medicare under IPF PPS in accordance with Sec. 412.404(b). Generally,
psychiatric hospitals and psychiatric units within acute care and
critical access hospitals (CAHs) that treat Medicare patients are paid
under the IPF PPS. Consistent with previous regulations, we continue to
use the terms ``facility'' or ``IPF'' to refer to both inpatient
psychiatric hospitals and psychiatric units. This usage follows the
terminology in our IPF PPS regulations at Sec. 412.402. For more
information on covered entities, we refer readers to the FY 2013 IPPS/
LTCH PPS final rule (77 FR 53645).
C. Previously Finalized Measures
The current IPFQR Program includes 14 measures for the FY 2024
payment determination. For more information on these measures, we refer
readers to Table 20 of this proposed rule (see section V.G of this
proposed rule).
D. Measure Adoption
We strive to put patients and caregivers first, ensuring they are
empowered to partner with their clinicians in their healthcare
decision-making using information from data-driven insights that are
increasingly aligned with meaningful quality measures. We support
technology that reduces burden and allows clinicians to focus on
providing high-quality healthcare for their patients. We also support
innovative approaches to improve quality, accessibility, and
affordability of care while paying particular attention to improving
clinicians' and beneficiaries' experiences when interacting with our
programs. In combination with other efforts across HHS, we believe the
IPFQR Program helps to incentivize IPFs to improve healthcare quality
and value while giving patients and providers the tools and information
needed to make the best individualized decisions. Consistent with these
goals, our objective in selecting quality measures for the IPFQR
Program is to balance the need for information on the full spectrum of
care delivery and the need to minimize the burden of data collection
and reporting. We have primarily focused on measures that evaluate
critical processes of care that have significant impact on patient
outcomes and support CMS and HHS priorities for improved quality and
efficiency of care provided by IPFs. When possible, we also propose to
incorporate measures that directly evaluate patient outcomes and
experience. We refer readers to the CMS National Quality Strategy,\9\
the Behavioral Health Strategy,\10\ the Framework for Health
Equity,\11\ and the Meaningful Measures Framework \12\ for information
related to our priorities in selecting quality measures.
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\9\ Schreiber, M, Richards, A, et al. (2022). The CMS National
Quality Strategy: A Person-Centered Approach to Improving Quality.
Available at: https://www.cms.gov/blog/cms-national-quality-strategy-person-centered-approach-improving-quality. Accessed on
February 20, 2023.
\10\ CMS. (2022). CMS Behavioral Health Strategy. Available at
https://www.cms.gov/cms-behavioral-health-strategy. Accessed on
February 20, 2023.
\11\ CMS. (2022). CMS Framework for Health Equity 2022-2032.
Available at https://www.cms.gov/files/document/cms-framework-health-equity-2022.pdf. Accessed on February 20, 2023.
\12\ CMS. (2022). Meaningful Measures 2.0: Moving from Measure
Reduction to Modernization. Available at https://www.cms.gov/medicare/meaningful-measures-framework/meaningful-measures-20-moving-measure-reduction-modernization. Accessed on February 20,
2023.
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1. Measure Selection Process
Section 1890A of the Act requires that the Secretary establish and
follow a pre-rulemaking process, in coordination with the consensus-
based entity (CBE)
[[Page 21274]]
with a contract under section 1890 of the Act, to solicit input from
certain groups regarding the selection of quality and efficiency
measures for the IPFQR Program. Before being proposed for inclusion in
the IPFQR Program, measures are placed on a list of Measures Under
Consideration (MUC) list, which is published annually on behalf of CMS
by the consensus-based entity (CBE),\13\ with which the Secretary must
contract as required by section 1890(a) of the Act. Following
publication on the MUC list, the Measure Applications Partnership
(MAP), a multi-stakeholder group convened by the CBE, reviews the
measures under consideration for the IPFQR Program, among other Federal
programs, and provides input on those measures to the Secretary. We
consider the input and recommendations provided by the MAP in selecting
all measures for the IPFQR Program.
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\13\ In previous years, we referred to the consensus-based
entity by corporate name. We have updated this language to refer to
the consensus-based entity more generally.
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Information about the MAP's input on each of our proposed measures
is described in the following subsections. In our evaluation of the
IPFQR Program measure set, we identified four measures that we believe
are appropriate for adoption for the IPFQR Program:
Facility Commitment to Health Equity;
Screening for Social Drivers of Health;
Screen Positive Rate for Social Drivers of Health; and
Psychiatric Inpatient Experience (PIX) Survey.
These four measures are described in the following subsections.
2. Proposal To Adopt the Facility Commitment to Health Equity Measure
Beginning With the CY 2024 Reporting Period Reported in CY 2025/FY 2026
Payment Determination
a. Background
Significant and persistent disparities in healthcare outcomes exist
in the United States. For example, belonging to a racial or ethnic
minority group, living with a disability, being a member of the
lesbian, gay, bisexual, transgender, and queer (LGBTQ+) community,
being a member of a religious minority, living in a rural area, or
being near or below the poverty level, is often associated with worse
health outcomes.14 15 16 17 18 19 20 21 22 23 Numerous
studies have shown that among Medicare beneficiaries, racial and ethnic
minority individuals often receive clinical care of lower quality,
report having worse care experiences, and experience more frequent
hospital readmissions and procedural
complications.24 25 26 27 28 29 Readmission rates in the
Hospital Readmissions Reduction Program have been shown to be higher
among Black and Hispanic Medicare beneficiaries with common conditions,
including congestive heart failure and acute myocardial
infarction.30 31 32 33 34 Data indicate that, even after
accounting for factors such as socioeconomic conditions, members of
racial and ethnic minority groups reported experiencing lower quality
of healthcare.\35\ Evidence of differences in quality of care received
among people from racial and ethnic minority groups shows worse health
outcomes,
[[Page 21275]]
including a higher incidence of diabetes complications such as
retinopathy.\36\ Additionally, inequities in the social drivers of
health (SDOH) affecting these groups, such as poverty and healthcare
access, are interrelated and influence a wide range of health and
quality-of-life outcomes and risks.\37\
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\14\ Joynt KE, Orav E, Jha AK. (2011). Thirty-Day Readmission
Rates for Medicare Beneficiaries by Race and Site of Care. JAMA,
305(7), 675 681. Available at: https://jamanetwork.com/journals/jama/fullarticle/645647. Accessed on February 13, 2023.
\15\ Lindenauer PK, Lagu T, Rothberg MB, et al. (2013). Income
Inequality and Thirty-Day Outcomes After Acute Myocardial
Infarction, Heart Failure, and Pneumonia: Retrospective Cohort
Study. BMJ, 346. Available at: https://doi.org/10.1136/bmj.f521.
Accessed on February 13, 2023.
\16\ Trivedi AN, Nsa W, Hausmann LRM, et al. (2014). Quality and
Equity of Care in U.S. Hospitals. N Engl J Med, 371(24), 229 8-2308.
Available at: https://www.nejm.org/doi/10.1056/NEJMsa1405003.
Accessed on February 13, 2023.
\17\ Polyakova, M, Udalova V, et al. (2021). Racial Disparities
In Excess All-Cause Mortality During The Early COVID-19 Pandemic
Varied Substantially Across States. Health Affairs, 40(2), 307-316.
Available at: https://doi.org/10.1377/hlthaff.2020.02142. Accessed
on February 14, 2023.
\18\ Rural Health Research Gateway. (2018). Rural Communities:
Age, Income, and Health Status. Rural Health Research Recap.
Available at: https://www.ruralhealthresearch.org/assets/2200-8536/rural-communities-age-income-health-status-recap.pdf. Accessed on
February 14, 2023.
\19\ HHS Office of Minority Health. (2020). Progress Report to
Congress, 2020 Update on the Action Plan to Reduce Racial and Ethnic
Health Disparities. Department of Health and Human Services.
Available at: https://www.minorityhealth.hhs.gov/assets/PDF/Update_HHS_Disparities_Dept-FY2020.pdf. Accessed on February 14, 2023.
\20\ Heslin KC, Hall JE. (2021). Sexual Orientation Disparities
in Risk Factors for Adverse COVID-19-Related Outcomes, by Race/
Ethnicity--Behavioral Risk Factor Surveillance System, United
States, 2017-2019. MMWR Morb Mortal Wkly Rep, 70(5), 149. Available
at: https://www.cdc.gov/mmwr/volumes/70/wr/mm7005a1.htm. Accessed on
February 14, 2023.
\21\ Poteat TC, Reisner SL, Miller M, Wirtz AL. (2020). COVID-19
Vulnerability of Transgender Women With and Without HIV Infection in
the Eastern and Southern U.S. medRxiv. Available at: https://www.medrxiv.org/content/10.1101/2020.07.21.20159327v1.full.pdf.
Accessed on February 14, 2023.
\22\ Vu M, Azmat A, Radejko T, Padela AI. (2016). Predictors of
Delayed Healthcare Seeking Among American Muslim Women. Journal of
Women's Health, 25(6), 586-593. Available at: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5912720/. Accessed on February
14, 2023.
\23\ Nadimpalli SB, Cleland CM, Hutchinson MK, Islam N, Barnes
LL, Van Devanter N. (2016). The Association Between Discrimination
and the Health of Sikh Asian Indians. Health Psychology, 35(4), 351-
355. Available at: https://doi.org/10.1037/hea0000268. Accessed on
February 14, 2023.
\24\ CMS Office of Minority Health. (2020). Racial, Ethnic, and
Gender Disparities in Healthcare in Medicare Advantage. Baltimore,
MD: Centers for Medicare & Medicaid Services. Available at: https://www.cms.gov/files/document/2020-national-level-results-race-ethnicity-and-gender-pdf.pdf. Accessed on February 14, 2023.
\25\ CMS Office of Minority Health. (2018). Guide to Reducing
Disparities in Readmissions. Available at: https://www.cms.gov/About-CMS/Agency-Information/OMH/Downloads/OMH_Readmissions_Guide.pdf. Accessed on February 14, 2023.
\26\ Singh JA, Lu X, et al. (2014). Racial Disparities in Knee
and Hip Total Joint Arthroplasty: An 18-year analysis of national
Medicare data. Ann Rheum Dis., 73(12), 2107-15. Available at:
https://ard.bmj.com/content/73/12/2107.full. Accessed on February
14, 2023.
\27\ Rivera-Hernandez M, Rahman M, Mor V, Trivedi AN. (2019).
Racial Disparities in Readmission Rates among Patients Discharged to
Skilled Nursing Facilities. J Am Geriatr Soc., 67(8), 1672-1679.
Available at: https://doi.org/10.1111/jgs.15960. Accessed on
February 14, 2023.
\28\ Joynt KE, Orav E, Jha AK. (2011). Thirty-Day Readmission
Rates for Medicare Beneficiaries by Race and Site of Care. JAMA,
305(7), 675-681. Available at: https://jamanetwork.com/journals/jama/fullarticle/645647. Accessed on February 13, 2023.
\29\ Tsai TC, Orav EJ, Joynt KE. (2014). Disparities in Surgical
30-day Readmission Rates for Medicare Beneficiaries by Race and Site
of Care. Ann Surg., 259(6), 1086-1090. Available at: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4107654/. Accessed on February
14, 2023.
\30\ Rodriguez F, Joynt KE, Lopez L, Saldana F, Jha AK. (2011).
Readmission Rates for Hispanic Medicare Beneficiaries with Heart
Failure and Acute Myocardial Infarction. Am Heart J., 162(2), 254-
261 e253. Available at: https://www.sciencedirect.com/science/article/pii/S0002870311003966?viewFullText=true. Accessed on
February 14, 2023.
\31\ Centers for Medicare & Medicaid Services. (2014). Medicare
Hospital Quality Chartbook: Performance Report on Outcome Measures.
Available at: https://www.hhs.gov/guidance/sites/default/files/hhs-guidance-documents/YNH_Chartbook_2014_508Compliant_FINAL.pdf.
Accessed on February 14, 2023.
\32\ CMS Office of Minority Health. (2018). Guide to Reducing
Disparities in Readmissions. Available at: https://www.cms.gov/About-CMS/Agency-Information/OMH/Downloads/OMH_Readmissions_Guide.pdf. Accessed on February 14, 2023.
\33\ Prieto-Centurion V, Gussin HA, Rolle AJ, Krishnan JA.
(2013). Chronic Obstructive Pulmonary Disease Readmissions at
Minority Serving Institutions. Ann Am Thorac Soc., 10(6), 680-684.
Available at: https://doi.org/10.1513/AnnalsATS.201307-223OT.
Accessed on February 14, 2023.
\34\ Joynt KE, Orav E, Jha AK. (2011). Thirty-Day Readmission
Rates for Medicare Beneficiaries by Race and Site of Care. JAMA,
305(7), 675-681. Available at: https://jamanetwork.com/journals/jama/fullarticle/645647. Accessed on February 13, 2023.
\35\ Nelson AR. (2003). Unequal Treatment: Report of the
Institute of Medicine on Racial and Ethnic Disparities in
Healthcare. The Annals of Thoracic Surgery, 76(4), S1377-S1381.
https://www.annalsthoracicsurgery.org/action/showPdf?pii=S0003-4975%2803%2901205-0. Accessed on February 14, 2023.
\36\ Peek, ME, Odoms-Young, A, et al. (2010). Race and Shared
Decision-Making: Perspectives of African-Americans with diabetes.
Social Science & Medicine, 71(1), 1-9. Available at: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2885527/. Accessed on February
14, 2023.
\37\ Department of Health and Human Services. (2023). Healthy
People 2030: Social Determinants of Health. Available at: https://health.gov/healthypeople/priority-areas/social-determinants-health.
Accessed on February 20, 2023.
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Because we are working toward the goal of all patients receiving
high-quality healthcare, regardless of individual characteristics, we
are committed to supporting healthcare organizations in building a
culture of safety and equity that focuses on educating and empowering
their workforce to recognize and eliminate health disparities. This
includes patients receiving the right care, at the right time, in the
right setting for their condition(s), regardless of those
characteristics.
In the FY 2022 IPF PPS final rule (86 FR 42625 through 42632), we
summarized the comments we received in response to our Request for
Information (RFI) on closing health equity gaps in our quality
programs, specifically the IPFQR Program. In response to this RFI,
several commenters recommended that we consider a measure of
organizational commitment to health equity. These commenters further
described how infrastructure supports delivery of equitable care. In
the FY 2023 IPF PPS final rule (87 FR 46865 through 46873), we
described our RFI on overarching principles for measuring equity and
healthcare quality across our quality programs and summarized the
comments we received in response to that RFI. Because we had
specifically solicited comments on the potential for a structural
measure assessing an IPF's commitment to health equity, many commenters
provided input on a structural measure. While many commenters supported
the concept, one commenter expressed concern with this measure concept
and stated that there is no evidence that performance on this measure
would lead to improved patient outcomes (87 FR 46872 through 46873).
However, we believe that strong and committed leadership from IPF
executives and board members is essential and can play a role in
shifting organizational culture and advancing equity goals.
Additionally, studies demonstrate that facility leadership can
positively influence culture for better quality, patient outcomes, and
experience of care.38 39 40 A systematic review of 122
published studies showed that strong leadership that prioritized
safety, quality, and the setting of clear guidance with measurable
goals for improvement resulted in high-performing facilities with
better patient outcomes.\41\ Therefore, we believe leadership
commitment to health equity will have a parallel effect in contributing
to a reduction in health disparities.
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\38\ Bradley EH, Brewster AL, et al. (2018). How Guiding
Coalitions Promote Positive Culture Change in Hospitals: A
Longitudinal Mixed Methods Interventional Study. BMJ Qual Saf.,
27(3), 218-225. Available at: https://qualitysafety.bmj.com/content/qhc/27/3/218.full.pdf. Accessed on February 14, 2023.
\39\ Smith SA, Yount N, Sorra J. (2017). Exploring Relationships
Between Hospital Patient Safety Culture and Consumer Reports Safety
Scores. BMC Health Services Research, 17(1), 143. Available at:
https://bmchealthservres.biomedcentral.com/articles/10.1186/s12913-017-2078-6. Accessed on February 14, 2023.
\40\ Keroack MA, Youngberg BJ, et al. (2007). Organizational
Factors Associated with High Performance in Quality and Safety in
Academic Medical Centers. Acad Med., 82(12), 1178 86. Available at:
https://journals.lww.com/academicmedicine/Fulltext/2007/12000/Organizational_Factors_Associated_with_High.14.aspx. Accessed on
February 14, 2023.
\41\ Millar R, Mannion R, Freeman T, et al. (2013). Hospital
Board Oversight of Quality and Patient Safety: A Narrative Review
and Synthesis of Recent Empirical Research. The Milbank Quarterly,
91(4), 738-70. Available at: https://onlinelibrary.wiley.com/doi/10.1111/1468-0009.12032. Accessed February 14, 2023.
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Further, we note that the Agency for Healthcare Research and
Quality (AHRQ) and The Joint Commission (TJC) identified that facility
leadership plays an important role in promoting a culture of quality
and safety.42 43 44 For instance, AHRQ research shows that
a facility's board can influence quality and safety in a variety of
ways, not only through strategic initiatives, but also through more
direct interactions with frontline workers.\45\
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\42\ Agency for Healthcare Research and Quality. Leadership Role
in Improving Patient Safety. Patient Safety Primer, September 2019.
Available at: https://psnet.ahrq.gov/primer/leadership-role-improving-safety. Accessed on February 14, 2023.
\43\ Joint Commission on Accreditation of Healthcare
Organizations, USA. The essential role of leadership in developing a
safety culture. Sentinel Event Alert. 2017 (Revised June 2021).
Available at: https://www.jointcommission.org/-/media/tjc/documents/resources/patient-safety-topics/sentinel-event/sea-57-safety-culture-and-leadership-final2.pdf. Accessed on February 15, 2023.
\44\ See information on launch of new ``Health Care Equity
Certification'' in July 2023 from Joint Commission on Accreditation
of Healthcare Organizations, USA, available at: https://www.jointcommission.org/our-priorities/health-care-equity/health-care-equity-prepublication/. Accessed on February 15, 2023.
\45\ Agency for Healthcare Research and Quality. Leadership Role
in Improving Patient Safety. Patient Safety Primer. (2019).
Available at: https://psnet.ahrq.gov/primer/leadership-role-improving-safety. Accessed on February 14, 2023.
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In addition, the Institute of Healthcare Improvement's (IHI's)
research of 23 health systems throughout the United States and Canada
shows that health equity must be a priority championed by leadership
teams to improve both patient access to needed healthcare services and
outcomes among populations that have been disadvantaged by the
healthcare system.\46\ This IHI study specifically identified concrete
actions to make advancing health equity a core strategy, including
establishing this goal as a leader-driven priority alongside
organizational development structures and processes.\47\
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\46\ Mate KS and Wyatt R. (2017). Health Equity Must Be a
Strategic Priority. NEJM Catalyst. Available at: https://catalyst.nejm.org/doi/full/10.1056/CAT.17.0556. Accessed on February
15, 2023.
\47\ Mate KS and Wyatt R. (2017). Health Equity Must Be a
Strategic Priority. NEJM Catalyst. Available at: https://catalyst.nejm.org/doi/full/10.1056/CAT.17.0556. Accessed on February
15, 2023.
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Based upon these findings, we believe that IPF leadership can be
instrumental in setting specific, measurable, attainable, realistic,
and time-based (SMART) goals to assess progress towards achieving
equity goals and ensuring high-quality care is accessible to all.
Therefore, consistent with the Hospital Inpatient Quality Reporting
(IQR) Program's adoption of an attestation-based structural measure in
the FY 2023 IPPS/LTCH PPS final rule (87 FR 49191 through 49201), we
propose to adopt an attestation-based structural measure, Facility
Commitment to Health Equity, to address health equity beginning with
the CY 2024 reporting period/FY 2026 payment determination.
The first pillar of our strategic priorities \48\ reflects our deep
commitment to improvements in health equity by addressing the health
disparities that underly our health system. In line with this strategic
pillar, we developed this structural measure to assess facility
commitment to health equity across five domains (described in Table 17
in the section V.D.2.b of this proposed rule) using a suite of
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organizational competencies aimed at achieving health equity for racial
and ethnic minority groups, people with disabilities, members of the
LGBTQ+ community, individuals with limited English proficiency, rural
populations, religious minorities, and people facing socioeconomic
challenges. We believe these elements are actionable focus areas, and
assessment of IPFs' leadership commitment to them is foundational.
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\48\ Brooks-LaSure, C. (2021). My First 100 Days and Where We Go
From Here: A Strategic Vision for CMS. Centers for Medicare &
Medicaid. Available at: https://www.cms.gov/blog/my-first-100-days-and-where-we-go-here-strategic-vision-cms. Accessed on February 15,
2023.
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We also believe adoption of the proposed Facility Commitment to
Health Equity measure would incentivize IPFs to collect and utilize
data to identify critical equity gaps, implement plans to address these
gaps, and ensure that resources are dedicated toward addressing health
equity initiatives. While many factors contribute to health equity, we
believe this measure is an important step toward assessing IPFs'
leadership commitment, and a fundamental step toward closing the gap in
equitable care for all populations. We note that this measure is not
intended to encourage IPFs to act on any one data element or domain,
but instead encourages IPFs to analyze their own findings to understand
if there are any demographic factors (for example, race, national
origin, primary language, and ethnicity) as well as SDOHs (for example,
housing status and food security) associated with underlying inequities
and, in turn, develop solutions to deliver more equitable care. Thus,
the proposed Facility Commitment to Health Equity measure aims to
support IPFs in leveraging available data, pursuing focused quality
improvement activities, and promoting efficient and effective use of
resources.
The proposed Facility Commitment to Health Equity measure aligns
with the measure previously adopted in the Hospital IQR Program, and we
refer readers to the FY 2023 IPPS/LTCH PPS final rule (87 FR 49191
through 49201) for more information regarding the measure's adoption in
the Hospital IQR Program. The five domains of the proposed measure are
adapted from the CMS Office of Minority Health's Building an
Organizational Response to Health Disparities framework, which focuses
on data collection, data analysis, culture of equity, and quality
improvement.\49\
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\49\ CMS. (2021). Building an Organizational Response to Health
Disparities [Fact Sheet]. Available at: https://www.cms.gov/About-CMS/Agency-Information/OMH/Downloads/Health-Disparities-Guide.pdf.
Accessed on February 15, 2023.
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The proposed measure also aligns with our efforts under the
Meaningful Measures Framework, which identifies high-priority areas for
quality measurement and improvement to assess core issues most critical
to high-quality healthcare and improving patient outcomes.\50\ In 2021,
we launched Meaningful Measures 2.0 to promote innovation and
modernization of all aspects of quality, and to address a wide variety
of settings, stakeholders, and measure requirements.\51\ We are
addressing healthcare priorities and gaps with Meaningful Measures 2.0
by leveraging quality measures to promote equity and close gaps in
care. The proposed Facility Commitment to Health Equity measure
supports these efforts and is aligned with the Meaningful Measures Area
of ``Equity of Care'' and the Meaningful Measures 2.0 goal to
``Leverage Quality Measures to Promote Equity and Close Gaps in Care.''
This proposed measure also supports the Meaningful Measures 2.0
objective to commit to a patient-centered approach in quality measure
and value-based incentives programs to ensure that quality and safety
measures address health equity.
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\50\ Centers for Medicare & Medicaid Services. Meaningful
Measures Framework. Available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/QualityInitiativesGenInfo/CMS-Quality-Strategy. Accessed on February
15, 2023.
\51\ CMS. (2022). Meaningful Measures 2.0: Moving from Measure
Reduction to Modernization. Available at https://www.cms.gov/medicare/meaningful-measures-framework/meaningful-measures-20-moving-measure-reduction-modernization. Accessed on February 20,
2023.
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b. Overview of Measure
The proposed Facility Commitment to Health Equity measure would
assess IPFs' commitment to health equity using a suite of equity-
focused organizational competencies aimed at achieving health equity
for populations that have been disadvantaged, marginalized, and
underserved by the healthcare system. As previously noted, these
populations include, but are not limited to, racial and ethnic minority
groups, people with disabilities, members of the LGBTQ+ community,
individuals with limited English proficiency, rural populations,
religious minorities, and people facing socioeconomic challenges. Table
17 sets forth the five attestation domains, and the elements within
each of those domains, to which an IPF would affirmatively attest for
the IPF to receive credit for that domain within the proposed Facility
Commitment to Health Equity measure.
[[Page 21277]]
Table 17--The Facility Commitment to Health Equity Measure Five
Attestations
------------------------------------------------------------------------
Elements: Select all that apply
(Note: Affirmative attestation
of all elements within a domain
Attestation would be required for the
facility to receive a point for
the domain in the numerator)
------------------------------------------------------------------------
Domain 1: Equity is a Strategic
Priority
Facility commitment to reducing (A) Our facility strategic plan
healthcare disparities is identifies priority
strengthened when equity is a key populations who currently
organizational priority. Please experience health disparities.
attest that your facility has a (B) Our facility strategic plan
strategic plan for advancing identifies health equity goals
health equity \*\ and that it and discrete action steps to
includes all the following achieving these goals.\*\
elements. (C) Our facility strategic plan
outlines specific resources
which have been dedicated to
achieving our equity goals.
(D) Our facility strategic plan
describes our approach for
engaging key stakeholders,
such as community-based
organizations.
Domain 2: Data Collection
Collecting valid and reliable (A) Our facility collects
demographic and SDOH data on demographic information (such
patients served in a facility is as self-reported race,
an important step in identifying national origin, primary
and eliminating health language, and ethnicity data)
disparities. Please attest that and/or social determinant of
your facility engages in the health information on the
following activities. majority of our patients.\**\
(B) Our facility has training
for staff in culturally
sensitive collection of
demographic and/or SDOH
information.
(C) Our facility inputs
demographic and/or SDOH
information collected from
patients into structured,
interoperable data elements
using a certified electronic
health record (EHR)
technology.
Domain 3: Data Analysis
Effective data analysis can provide (A) Our facility stratifies key
insights into which factors performance indicators by
contribute to health disparities demographic and/or SDOH
and how to respond. Please attest variables to identify equity
that your facility engages in the gaps and includes this
following activities. information on facility
performance dashboards.
Domain 4: Quality Improvement
Health disparities are evidence (A) Our facility participates
that high-quality care has not in local, regional, or
been delivered equitably \***\ to national quality improvement
all patients. Engagement in activities focused on reducing
quality improvement activities can health disparities.
improve quality of care for all
patients..
Domain 5: Leadership Engagement
Leaders and staff can improve their (A) Our facility senior
capacity to address disparities by leadership, including chief
demonstrating routine and thorough executives and the entire
attention to equity and setting an facility \****\ board of
organizational culture of equity. trustees, annually reviews our
Please attest that your facility strategic plan for achieving
engages in the following health equity.
activities.. (B) Our facility senior
leadership, including chief
executives and the entire
facility board of trustees,
annually reviews key
performance indicators
stratified by demographic and/
or social factors.
------------------------------------------------------------------------
* After publication of the 2022 MUC List, we clarified the language in
Domain 1 to refer to ``health equity'' instead of ``healthcare
equity.''
** After publication of the 2022 MUC List, we clarified the language in
Domain 2 to refer to example demographic information.
*** After publication of the 2022 MUC List, we clarified the language in
Domain 4: ``Health disparities are evidence that high quality care has
not been delivered equitably to all patients.''
**** After publication of the 2022 MUC List, we identified that Domain 5
incorrectly referred to the ``hospital board of trustees'' instead of
the ``facility board of trustees.''
[[Page 21278]]
(1) Measure Calculation
The proposed Facility Commitment to Health Equity measure consists
of five attestation-based questions, each representing a separate
domain of the IPF's commitment to addressing health equity. Some of
these domains have multiple elements to which an IPF would be required
to attest. For an IPF to affirmatively attest ``yes'' to a domain, and
receive credit for that domain, the IPF would evaluate and determine
whether it engages in each of the elements that comprise that domain.
Each of the domains would be represented in the denominator as a point,
for a total of five points (that is, one point per domain).
The numerator of the proposed Facility Commitment to Health Equity
measure would capture the total number of domain attestations that the
IPF is able to affirm. An IPF that affirmatively attests to each
element within the five domains would receive the maximum five points.
An IPF would only receive a point for a domain if it attests
``yes'' to all related elements within that domain. There is no
``partial credit'' for elements. For example, for Domain 1 (``Facility
commitment to reducing healthcare disparities is strengthened when
equity is a key organizational priority''), an IPF would evaluate and
determine whether its strategic plan meets each of the elements
described in (A) through (D) (see Table 17 in section V.D.2.b of this
proposed rule). If the IPF's strategic plan meets all four of these
elements, the IPF would affirmatively attest ``yes'' to Domain 1 and
would receive one (1) point for that attestation. An IPF would not be
able to receive partial credit for a domain. For example, if the IPF's
strategic plan meets elements (A) and (B), but not (C) and (D), of
Domain 1, then the IPF would not be able to affirmatively attest
``yes'' to Domain 1 and would not receive a point for that attestation,
and instead would receive zero points for Doman 1.
In response to our RFI on the potential for a structural measure
assessing an IPF's commitment to health equity, several commenters
expressed concern that such a measure would be difficult for IPFs to
report because of the requirement to use certified electronic health
record (EHR) technology for Domain 2 (87 FR 46972 through 46873). We
believe that use of certified EHR technology is an important element of
collecting valid and reliable demographic and social drivers of health
data on patients served in an IPF and that use of this technology
facilitates data analytics to ensure consistent, high-quality,
equitable care. However, we recognize that some IPFs may face
challenges to adopting certified EHR technology. We note that the IPFQR
Program is a pay-for-reporting program, not a pay-for-performance
program, and therefore IPFs that do not have certified EHR technology
can attest that they satisfy the other domains, as applicable, and
receive a score of 0-4 out of 5 without any penalties.
(2) Review by the Measure Applications Partnership (MAP)
We included the proposed Facility Commitment to Health Equity
measure on the publicly available ``List of Measures Under
Consideration for December 1, 2022'' (MUC List), a list of measures
under consideration for use in various Medicare programs.\52\ The
specifications for the proposed Facility Commitment to Health Equity
measure, which were available during the review of the MUC List, are
available on the CMS website at: https://mmshub.cms.gov/sites/default/files/map-hospital-measure-specifications-manual-2022.pdf.
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\52\ Centers for Medicare & Medicaid Services. List of Measures
Under Consideration for December 1, 2022. Available at: https://mmshub.cms.gov/measure-lifecycle/measure-implementation/pre-rulemaking/lists-and-reports.
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The Consensus-Based Entity (CBE) convened Measure Applications
Partnership (MAP) Health Equity Advisory Group reviewed the MUC List
and the proposed Facility Commitment to Health Equity measure (MUC
2022-027) in detail on December 6 through 7, 2022.\53\ The MAP Health
Equity Advisory Group raised concerns that this measure does not
evaluate outcomes and may not directly address health inequities at a
systemic level, but generally agreed that a structural measure such as
this one represents progress toward improving equitable care.\54\
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\53\ Centers for Medicare & Medicaid Services. 2022-2023 MAP
Final Recommendations. Available at: https://mmshub.cms.gov/measure-lifecycle/measure-implementation/pre-rulemaking/lists-and-reports.
\54\ Centers for Medicare & Medicaid Services. 2022-2023 MAP
Final Recommendations. Available at: https://mmshub.cms.gov/measure-lifecycle/measure-implementation/pre-rulemaking/lists-and-reports.
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In addition, on December 8 through 9, 2022, the MAP Rural Health
Advisory Group reviewed the 2022 MUC List and expressed support for
this measure as a step towards advancing access to and quality of care
with the caveat that resource challenges exist in rural
communities.\55\
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\55\ Centers for Medicare & Medicaid Services. 2022-2023 MAP
Final Recommendations. Available at: https://mmshub.cms.gov/measure-lifecycle/measure-implementation/pre-rulemaking/lists-and-reports.
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The MAP Hospital Workgroup reviewed the 2022 MUC List on December
13 through 14, 2022.\56\ The MAP Hospital Workgroup recognized that
reducing health care disparities would represent a substantial benefit
to overall quality of care but expressed reservations about the
measure's link to clinical outcomes. As stated in the MAP
recommendations document, the MAP Hospital Workgroup members voted to
conditionally support the Facility Commitment to Health Equity measure
for rulemaking pending: (1) endorsement by the CBE; (2) commitment to
consideration of equity related outcome measures in the future; (3)
provision of more clarity on the Facility Commitment to Health Equity
measure and supplementing interpretation with results; and (4)
verification of accurate attestation by IPFs.\57\ Thereafter, the MAP
Coordinating Committee deliberated on January 24 through 25, 2023 and
ultimately voted to uphold the MAP Hospital Workgroup's recommendation
to conditionally support the measure for rulemaking.\58\
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\56\ Centers for Medicare & Medicaid Services. 2022-2023 MAP
Final Recommendations. Available at: https://mmshub.cms.gov/measure-lifecycle/measure-implementation/pre-rulemaking/lists-and-reports.
\57\ Centers for Medicare & Medicaid Services. 2022-2023 MAP
Final Recommendations. Available at: https://mmshub.cms.gov/measure-lifecycle/measure-implementation/pre-rulemaking/lists-and-reports.
\58\ Centers for Medicare & Medicaid Services. 2022-2023 MAP
Final Recommendations. Available at: https://mmshub.cms.gov/measure-lifecycle/measure-implementation/pre-rulemaking/lists-and-reports.
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We believe that the proposed Facility Commitment to Health Equity
measure establishes an important foundation for prioritizing the
achievement of health equity among IPFs participating in the IPFQR
Program. Our approach to developing health equity measures has been
incremental to date, but we see inclusion of such measures in the IPFQR
Program as informing efforts to advance and achieve health equity not
only among IPFs, but also other acute care settings. We believe this
proposed measure to be a building block that lays the groundwork for a
future meaningful suite of measures that would assess IPF progress in
providing high-quality healthcare for all patients regardless of social
risk factors or demographic characteristics.
(3) CBE Endorsement
We have not submitted this measure for CBE endorsement at this
time.
[[Page 21279]]
Although section 1886(s)(4)(D)(i) of the Act generally requires that
measures specified by the Secretary shall be endorsed by the entity
with a contract under section 1890(a) of the Act, section
1886(s)(4)(D)(ii) of the Act states that, in the case of a specified
area or medical topic determined appropriate by the Secretary for which
a feasible and practical measure has not been endorsed by the entity
with a contract under section 1890(a) of the Act, the Secretary may
specify a measure that is not so endorsed as long as due consideration
is given to measures that have been endorsed or adopted by a consensus
organization identified by the Secretary. We reviewed CBE-endorsed
measures and were unable to identify any other CBE-endorsed measures on
this topic, and therefore, we believe the exception in section
1886(s)(4)(D)(ii) of the Act applies.
c. Data Collection, Submission, and Reporting
IPFs are required to submit information for structural measures
once annually using a CMS-approved web-based data collection tool
available within the Hospital Quality Reporting (HQR) System. For more
information about our previously finalized policies related to
reporting of structural measures, we refer readers to the FY 2014 IPPS/
LTCH PPS final rule (78 FR 50890 through 50901) and the FY 2015 IPF PPS
final rule (79 FR 45963 through 45964 and 45976). Given the role of
committed leadership in improving health outcomes for all patients, we
propose to adopt this measure beginning with attestation in CY 2025
reflecting the CY 2024 reporting period and affecting the FY 2026
payment determination.
We invite comments on our proposed adoption of the Facility
Commitment to Health Equity Measure beginning with the FY 2026 payment
determination.
3. Proposal To Adopt the Screening for Social Drivers of Health Measure
Beginning With Voluntary Reporting of CY 2024 Data Followed by Required
Reporting Beginning With CY 2025 Data/FY 2027 Payment Determination
a. Background
Health-related social needs (HRSNs), which we define as individual-
level, adverse social conditions that negatively impact an individual
person's health or healthcare, are significant risk factors associated
with worse health outcomes as well as increased healthcare
utilization.\59\ We believe that consistently pursuing identification
of HRSNs would have two significant benefits. First, HRSNs
disproportionately impact people who have historically been underserved
by the healthcare system \60\ and screening helps identify individuals
who may have HRSNs. Second, screening for HRSNs could support ongoing
IPF quality improvement initiatives by providing data with which to
stratify patient risk and organizational performance. Further, we
believe that IPFs collecting patient-level HRSN data through screening
is essential for the long-term in encouraging meaningful collaboration
between healthcare providers and community-based organizations and in
implementing and evaluating related innovations in health and social
care delivery.
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\59\ Centers for Medicare & Medicaid Services. (2021). A Guide
to Using the Accountable Health Communities Health-Related Social
Needs Screening Tool: Promising Practices and Key Insights. June
2021. Available at: https://innovation.cms.gov/media/document/ahcm-screeningtool-companion. Accessed on February 20, 2023.
\60\ American Hospital Association. (2020). Health Equity,
Diversity & Inclusion Measures for Hospitals and Health System
Dashboards. December 2020. Available at: https://ifdhe.aha.org/system/files/media/file/2020/12/ifdhe_inclusion_dashboard.pdf.
Accessed on February 20, 2023.
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Health disparities manifest primarily as worse health outcomes in
population groups where access to care is
inequitable.61 62 63 64 65 Such differences persist across
geography and healthcare settings irrespective of improvements in
quality of care over time.66 67 68 Assessment of HRSNs is an
essential mechanism for capturing the interaction between social,
community, and environmental factors associated with health status and
health outcomes.69 70 71
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\61\ Seligman, H.K., & Berkowitz, S.A. (2019). Aligning Programs
and Policies to Support Food Security and Public Health Goals in the
United States. Annual Review of Public Health, 40(1), 319-337.
Available at: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6784838/.
Accessed on February 20, 2023.
\62\ The Physicians Foundation. (2020). Survey of America's
Patients, Part Three. Available at: https://physiciansfoundation.org/wp-content/uploads/2020/10/2020-Physicians-Foundation-Survey-Part3.pdf. Accessed on February 20, 2023.
\63\ Office of the Assistant Secretary for Planning and
Evaluation (ASPE) (2020). Report to Congress: Social Risk Factors
and Performance Under Medicare's Value-Based Purchasing Program
(Second of Two Reports). Available at: https://aspe.hhs.gov/pdf-report/second-impact-report-to-congress. Accessed on February 20,
2023.
\64\ Trivedi AN, Nsa W, Hausmann LRM, et al. (2014). Quality and
Equity of Care in U.S. Hospitals. N Engl J Med, 371(24), 2298-2308.
Available at: https://www.nejm.org/doi/10.1056/NEJMsa1405003.
Accessed on February 13, 2023.
\65\ Billioux, A., Verlander, K., Anthony, S., & Alley, D.
(2017). Standardized Screening for Health Related Social Needs in
Clinical Settings: The Accountable Health Communities Screening
Tool. NAM Perspectives, 7(5). Available at: https://doi.org/10.31478/201705b. Accessed on February 20, 2023.
\66\ Office of the Assistant Secretary for Planning and
Evaluation (ASPE) (2020). Report to Congress: Social Risk Factors
and Performance Under Medicare's Value-Based Purchasing Program
(Second of Two Reports). Available at: https://aspe.hhs.gov/pdf-report/second-impact-report-to-congress. Accessed on February 20,
2023.
\67\ Hill-Briggs, F. (2021). Social Determinants of Health and
Diabetes: A Scientific Review. Diabetes Care. Available at: https://diabetesjournals.org/care/article/44/1/258/33180/Social-Determinants-of-Health-and-Diabetes-A. Accessed on February 20,
2023.
\68\ Khullar, D., MD. (2020). Association Between Patient Social
Risk and Physician Performance American academy of Family
Physicians. Addressing Social Determinants of Health in Primary Care
team-based approach for advancing health equity. Available at:
https://www.aafp.org/dam/AAFP/documents/patient_care/everyone_project/team-based-approach.pdf. Accessed on February 20,
2023.
\69\ Institute of Medicine. (2014). Capturing Social and
Behavioral Domains and Measures in Electronic Health Records: Phase
2. Washington, DC: The National Academies Press. Available at:
https://doi.org/10.17226/18951. Accessed on February 20, 2023.
\70\ Alley, D.E., C.N. Asomugha, P.H. Conway, and D.M. Sanghavi.
(2016). Accountable Health Communities--Addressing Social Needs
through Medicare and Medicaid. The New England Journal of Medicine
374(1):8-11. Available at: https://doi.org/10.1056/NEJMp1512532.
Accessed on February 20, 2023.
\71\ Centers for Disease Control and Prevention. CDC COVID-19
Response Health Equity Strategy: Accelerating Progress Towards
Reducing COVID-19 Disparities and Achieving Health Equity. July
2020. Available at: https://www.cdc.gov/coronavirus/2019-ncov/community/health-equity/cdc-strategy.html. Accessed on February 2,
2023.
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Growing evidence demonstrates that specific HRSNs are directly
associated with patient health outcomes as well as healthcare
utilization, costs, and performance in quality-based payment
programs.72 73 While widespread interest in addressing HRSNs
exists, action is inconsistent.\74\
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\72\ Zhang Y, Li J, Yu J, Braun RT, Casalino LP (2021). Social
Determinants of Health and Geographic Variation in Medicare per
Beneficiary Spending. JAMA Network Open. 2021;4(6):e2113212. https://jamanetwork.com/journals/jamanetworkopen/fullarticle/2780864.
Accessed on February 20, 2023.
\73\ Khullar, D., Schpero, W.L., Bond, A.M., Qian, Y., &
Casalino, L.P. (2020). Association Between Patient Social Risk and
Physician Performance Scores in the First Year of the Merit-based
Incentive Payment System. JAMA, 324(10), 975-983. https://doi.org/10.1001/jama.2020.13129. Accessed on February 20, 2023.
\74\ TK Fraze, AL Brewster, VA Lewis, LB Beidler, GF Murray, CH
Colla. Prevalence of screening for food insecurity, housing
instability, utility needs, transportation needs, and interpersonal
violence by US physician practices and hospitals. JAMA Network Open
2019; https://jamanetwork.com/journals/jamanetworkopen/fullarticle/10.1001/jamanetworkopen.2019.11514. Accessed on February 20, 2023.
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While social risk factors account for 50 to 70 percent of health
outcomes, the mechanisms by which this connection emerges are complex
and
[[Page 21280]]
multifaceted.75 76 77 78 The persistent interactions among
individuals' HRSNs, medical providers' practices and behaviors, and
community resources significantly impact healthcare access, quality,
and ultimately costs, as described in the CMS Equity Plan for Improving
Quality in Medicare.79 80 In their 2018 survey, to which
more than 8,500 physicians responded, the Physicians Foundation found
that almost 90 percent of these physician respondents reported their
patients had a serious health problem linked to poverty or other social
conditions.\81\ Additionally, associations among disproportionate
health risk, hospitalization, and adverse health outcomes have been
highlighted and magnified by the COVID-19 pandemic.82 83
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\75\ Kaiser Family Foundation. (2021). Racial and Ethnic Health
Inequities and Medicare. Available at: https://www.kff.org/medicare/report/racial-and-ethnic-health-inequities-and-medicare/. Accessed
February 20, 2023.
\76\ Khullar, D., MD. (2020). Association Between Patient Social
Risk and Physician Performance American academy of Family
Physicians. Addressing Social Determinants of Health in Primary Care
team-based approach for advancing health equity. Available at:
https://www.aafp.org/dam/AAFP/documents/patient_care/everyone_project/team-based-approach.pdf. Accessed on February 20,
2023.
\77\ Hammond, G., Johnston, K., Huang, K., Joynt Maddox, K.
(2020). Social Determinants of Health Improve Predictive Accuracy of
Clinical Risk Models for Cardiovascular Hospitalization, Annual
Cost, and Death. Circulation: Cardiovascular Quality and Outcomes,
13 (6) 290-299. Available at: https://doi.org/10.1161/CIRCOUTCOMES.120.006752. Accessed on February 20, 2023.
\78\ The Physicians Foundation. (2021). Viewpoints: Social
Determinants of Health. Available at: https://physiciansfoundation.org/wp-content/uploads/2019/08/The-Physicians-Foundation-SDOH-Viewpoints.pdf. Accessed on February 20, 2023.
\79\ Centers for Medicare & Medicaid Services. (2021). Paving
the Way to Equity: A Progress Report. Available at: https://www.cms.gov/files/document/paving-way-equity-cms-omh-progress-report.pdf. Accessed on February 20, 2023.
\80\ Centers for Medicare & Medicaid Services Office of Minority
Health. (2021). The CMS Equity Plan for Improving Quality in
Medicare. 2015-2021. Available at: https://www.cms.gov/About-CMS/
Agency-Information/OMH/OMH_Dwnld-
CMS_EquityPlanforMedicare_090615.pdf#:~:text=The%20Centers%20for%20Me
dicare%20%26%20Medicaid%20Services%20%28CMS%29,evidence%20base%2C%20i
dentifying%20opportunities%2C%20and%20gathering%20stakeholder%20input
. Accessed on February 20, 2023.
\81\ The Physicians Foundation. (2019). Viewpoints: Social
Determinants of Health. Available at: https://physiciansfoundation.org/wp-content/uploads/2019/08/The-Physicians-Foundation-SDOH-Viewpoints.pdf. Accessed on February 20, 2023.
\82\ Centers for Disease Control and Prevention. (2020). CDC
COVID-19 Response Health Equity Strategy: Accelerating Progress
Towards Reducing COVID-19 Disparities and Achieving Health Equity.
July 2020. Available at: https://www.cdc.gov/coronavirus/2019-ncov/community/health-equity/cdc-strategy.html. Accessed on February 20,
2023.
\83\ Kaiser Family Foundation. (2021). Racial and Ethnic Health
Inequities and Medicare. Available at: https://www.kff.org/medicare/report/racial-and-ethnic-health-inequities-and-medicare/. Accessed
on February 20, 2023.
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In 2017, CMS' Center for Medicare and Medicaid Innovation (CMMI)
launched the Accountable Health Communities (AHC) Model to test the
impact of systematically identifying and addressing the HRSNs of
Medicare and Medicaid beneficiaries (that is, through screening,
referral, and community navigation) on their health outcomes and
related healthcare utilization and costs.84 85 86 87 The AHC
Model is one of the first Federal pilots to systematically test whether
identifying and addressing core HRSNs improves healthcare costs,
utilization, and outcomes with over 600 clinical sites in 21
states.\88\ The AHC Model had a 5-year period of performance that began
in May 2017 and ended in April 2022, with beneficiary screening
beginning in the summer of 2018.89 90 Evaluation of the AHC
Model data is still underway.
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\84\ Centers for Medicare & Medicaid Services. (2021). A Guide
to Using the Accountable Health Communities Health-Related Social
Needs Screening Tool: Promising Practices and Key Insights. June
2021. Accessed: November 23, 2021. Available at: https://innovation.cms.gov/media/document/ahcm-screeningtool-companion.
Accessed on February 20, 2023.
\85\ Alley, D.E., Asomugha, C.N., et al. (2016). Accountable
Health Communities--Addressing Social Needs through Medicare and
Medicaid. The New England Journal of Medicine 374(1):8-11. Available
at: https://doi.org/10.1056/NEJMp1512532. Accessed on February 20,
2023.
\86\ Billioux, A., Verlander, K., Anthony, S., & Alley, D.
(2017). Standardized Screening for Health-Related Social Needs in
Clinical Settings: The Accountable Health Communities Screening
Tool. NAM Perspectives, 7(5). Available at: https://doi.org/10.31478/201705b. Accessed on February 20, 2023.
\87\ Centers for Medicare & Medicaid Services. (2021).
Accountable Health Communities Model. Accountable Health Communities
Model CMS Innovation Center Available at: https://innovation.cms.gov/innovation-models/ahcm. Accessed on February 20,
2023.
\88\ RTI International. (2020). Accountable Health Communities
(AHC) Model Evaluation. Available at: https://innovation.cms.gov/data-and-reports/2020/ahc-first-eval-rpt. Accessed on February 20,
2023.
\89\ RTI International. (2020). Accountable Health Communities
(AHC) Model Evaluation. Available at: https://innovation.cms.gov/data-and-reports/2020/ahc-first-eval-rpt. Accessed on February 20,
2023.
\90\ We note that the model officially concluded in April 2022,
but many awardees have continued with no-cost extensions to continue
utilizing unspent cooperative agreement funding and all awardees
will conclude by April 2023.
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Under the AHC Model, the following five core domains were selected
to screen for HRSNs among Medicare and Medicaid beneficiaries: (1) food
insecurity; (2) housing instability; (3) transportation needs; (4)
utility difficulties; and (5) interpersonal safety. These domains were
chosen based upon literature review and expert consensus utilizing the
following criteria: (1) availability of high-quality scientific
evidence linking a given HRSN to adverse health outcomes and increased
healthcare utilization, including hospitalizations and associated
costs; (2) ability for a given HRSN to be screened and identified in
the inpatient setting prior to discharge, addressed by community-based
services, and potentially improve healthcare outcomes, including
reduced readmissions; and (3) evidence that a given HRSN is not
systematically addressed by healthcare providers.\91\ In addition to
established evidence of their association with health status, risk, and
outcomes, these five domains were selected because they can be assessed
across the broadest spectrum of individuals in a variety of
settings.92 93 94
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\91\ Billioux, A., Verlander, K., Anthony, S., & Alley, D.
(2017). Standardized Screening for Health-Related Social Needs in
Clinical Settings: The Accountable Health Communities Screening
Tool. NAM Perspectives, 7(5). Available at: https://doi.org/10.31478/201705b. Accessed on February 20, 2023.
\92\ Billioux, A., Verlander, K., Anthony, S., & Alley, D.
(2017). Standardized Screening for Health-Related Social Needs in
Clinical Settings: The Accountable Health Communities Screening
Tool. NAM Perspectives, 7(5). Available at: https://doi.org/10.31478/201705b. Accessed on February 20, 2023.
\93\ Centers for Medicare & Medicaid Services. (2021).
Accountable Health Communities Model. Accountable Health Communities
Model CMS Innovation Center. Available at: https://innovation.cms.gov/innovation-models/ahcm. Accessed on February 20,
2023.
\94\ Kamyck, D., Senior Director of Marketing. (2019). CMS
releases standardized screening tool for health-related social
needs. Activate Care. Available at: https://blog.activatecare.com/standardized-screening-for-health-related-social-needs-in-clinical-settings-the-accountable-health-communities-screening-tool/.
Accessed on February 20, 2023.
---------------------------------------------------------------------------
These five evidence-based HRSN domains, which informed development
of the two Social Drivers of Health measures adopted in the Hospital
IQR Program and proposed here for the IPFQR Program, are described in
Table 18. We note that while the measures were initially developed by
The Health Initiative (THI), CMS has since assumed stewardship.
[[Page 21281]]
Table 18--The Five Core HRSN Domains To Screen for Social Drivers of
Health
------------------------------------------------------------------------
Domain Description
------------------------------------------------------------------------
Food Insecurity............... Food insecurity is defined as limited or
uncertain access to adequate quality
and quantity of food at the household
level. It is associated with diminished
mental and physical health and
increased risk for chronic
conditions.\95\ \96\ Individuals
experiencing food insecurity often have
inadequate access to healthier food
options which can impede self-
management of chronic diseases like
diabetes and heart disease, and require
individuals to make personal trade-offs
between food purchases and medical
needs, including prescription
medication refills and preventive
health services.\97\ \98\ Food
insecurity is associated with high-cost
healthcare utilization including
emergency department (ED) visits and
hospitalizations.\99\ \100\ \101\
Evidence indicates that individuals
with serious mental illness have a
higher prevalence of food insecurity
than the U.S. population as a whole
(specifically 71% prevalence among
patients with severe mental illness
versus 14.9% in the population as a
whole).\102\
Housing Instability........... Housing instability encompasses multiple
conditions ranging from inability to
pay rent or mortgage, frequent changes
in residence including temporary stays
with friends and relatives, living in
crowded conditions, and actual lack of
sheltered housing in which an
individual does not have a personal
residence.\103\ \104\ Population
surveys consistently show that people
from some racial and ethnic minority
groups constitute the largest
proportion of the U.S. population
experiencing housing instability.\105\
Housing instability is associated with
higher rates of chronic illnesses,
injuries, and complications and more
frequent utilization of high-cost
healthcare services.\106\ \107\
Additionally, housing instability can
exacerbate psychiatric conditions and
individuals with psychiatric conditions
are more likely to have housing
instability.\108\
Transportation Needs.......... Unmet transportation needs include
limitations that impede transportation
to destinations required for all
aspects of daily living.\109\ Groups
disproportionately affected include
older adults (aged >65 years), people
with lower incomes, people with
impaired mobility, residents of rural
areas, and people from some racial and
ethnic minority groups. Transportation
needs contribute to postponement of
routine medical care and preventive
services which ultimately lead to
chronic illness exacerbation and more
frequent utilization of high-cost
healthcare services including emergency
medical services, EDs, and
hospitalizations.\110\ \111\ \112\
\113\ Patients with serious mental
illness often lack access to
transportation with many Medicaid
eligible patients relying on Medicaid's
non-emergency medical transportation
(NEMT) to access needed healthcare,
though this does not provide access to
transportation to other aspects of
daily living.\114\
Utility Difficulties.......... Inconsistent availability of
electricity, water, oil, and gas
services is directly associated with
housing instability and food
insecurity.\115\ Specifically,
interventions that increase or maintain
access to such services have been
associated with individual and
population-level health
improvements.\116\
Interpersonal Safety.......... Interpersonal safety affects individuals
across the lifespan, from birth to old
age, and is directly linked to mental
and physical health. Assessment for
this domain includes screening for
exposure to intimate partner violence,
child abuse, and elder abuse.\117\
Exposure to violence and social
isolation are reflective of individual-
level social relations and living
conditions that are directly associated
with injury, psychological distress,
and death in all age groups.\118\ \119\
Research indicates that adults with
mental illness are at an increased risk
of being victims of violence, noting
that 30.9 percent were victims of
violence within a six month period and
recommending increased public health
interventions to reduce violence in
this vulnerable population.\120\
------------------------------------------------------------------------
As a first step towards leveraging the opportunity to close equity
gaps by identifying patients' HRSNs, we finalized the adoption of two
evidence-based measures in the Hospital IQR Program--the Screening for
Social Drivers of Health measure and the Screen Positive Rate for
Social Drivers of Health measure (collectively, Social Drivers of
Health measures)--and refer readers to the FY 2023 IPPS/LTCH PPS final
rule (87 FR 49191 through 49220).
---------------------------------------------------------------------------
\95\ Berkowitz SA, Seligman HK, Meigs JB, Basu S. Food
insecurity, healthcare utilization, and high cost: a longitudinal
cohort study. Am J Managed Care. 2018 Sep;24(9):399-404. PMID:
30222918; PMCID: PMC6426124. Available at https://pubmed.ncbi.nlm.nih.gov/30222918/. Accessed on February 20, 2023.
\96\ Hill-Briggs, F. (2021). Social Determinants of Health and
Diabetes: A Scientific Review. Diabetes Care. Available at: https://diabetesjournals.org/care/article/44/1/258/33180/Social-Determinants-of-Health-and-Diabetes-A. Accessed on February 20,
2023.
\97\ Seligman, H.K., & Berkowitz, S.A. (2019). Aligning Programs
and Policies to Support Food Security and Public Health Goals in the
United States. Annual Review of Public Health, 40(1), 319-337.
Available at: https://pubmed.ncbi.nlm.nih.gov/30444684/. Accessed on
February 20, 2023.
\98\ National Academies of Sciences, Engineering, and Medicine
2006. Executive Summary: Cost-Benefit Analysis of Providing Non-
Emergency Medical Transportation. Washington, DC: The National
Academies Press. Available at: https://doi.org/10.17226/23285.
Accessed on February 20, 2023.
\99\ Hill-Briggs, F. (2021). Social Determinants of Health and
Diabetes: A Scientific Review. Diabetes Care. Available at: https://diabetesjournals.org/care/article/44/1/258/33180/Social-Determinants-of-Health-and-Diabetes-A. Accessed on February 20,
2023.
\100\ Berkowitz SA, Seligman HK, Meigs JB, Basu S. Food
insecurity, healthcare utilization, and high cost: a longitudinal
cohort study. Am J Managed Care. 2018 Sep;24(9):399-404. PMID:
30222918; PMCID: PMC6426124. Available at https://pubmed.ncbi.nlm.nih.gov/30222918/. Accessed on February 20, 2023.
\101\ Dean, E.B., French, M.T., & Mortensen, K. (2020a). Food
insecurity, health care utilization, and health care expenditures.
Health Services Research, 55(S2), 883-893. Available at: https://doi.org/10.1111/1475-6773.13283. Accessed on February 20, 2023.
\102\ https://ps.psychiatryonline.org/doi/10.1176/appi.ps.201300022?url_ver=Z39.88-2003&rfr_id=ori:rid:crossref.org&rfr_dat=cr_pub%20%200pubmed.
Accessed on February 20, 2023.
\103\ Larimer, M.E. (2009). Health Care and Public Service Use
and Costs Before and After Provision of Housing for Chronically
Homeless Persons with Severe Alcohol Problems. JAMA, 301(13), 1349.
Available at: https://doi.org/10.1001/jama.2009.414.
\104\ Hill-Briggs, F. (2021, January 1). Social Determinants of
Health and Diabetes: A Scientific Review. Diabetes Care. Available
at: https://pubmed.ncbi.nlm.nih.gov/33139407/.
\105\ Henry, M., de Sousa, T., Roddey, C., Gayen, S., Bednar,
T.; Abt Associates. The 2020 Annual Homeless Assessment Report
(AHAR) to Congress; Part 1: Point-in-Time Estimates of Homelessness,
January 2021. U.S. Department of Housing and Urban Development.
Accessed November 24, 2021. Available at: https://www.huduser.gov/portal/sites/default/files/pdf/2020-AHAR-Part-1.pdf.
\106\ Larimer, M.E. (2009). Health Care and Public Service Use
and Costs Before and After Provision of Housing for Chronically
Homeless Persons with Severe Alcohol Problems. JAMA, 301(13), 1349.
Available at: https://doi.org/10.1001/jama.2009.414.
\107\ Baxter, A., Tweed, E., Katikireddi, S., Thomson, H.
(2019). Effects of Housing First approaches on health and well-being
of adults who are homeless or at risk of homelessness: systematic
review and meta-analysis of randomized controlled trials. Journal of
Epidemiology and Community Health, 73; 379-387. Available at:
https://jech.bmj.com/content/jech/73/5/379.full.pdf.
\108\ Housing Instability and Mental Health. UNC Greensboro. May
7, 2021. Available at: https://chcs.uncg.edu/housing-instability-
mental-health/
#:~:text=Mental%20health%20is%20correlated%20with%20housing%20in%20se
veral,homeless%20population%20in%20America%20suffer%20a%20mental%20il
lness. Accessed on December 7, 2022.
\109\ National Academies of Sciences, Engineering, and Medicine
2006. Executive Summary: Cost-Benefit Analysis of Providing Non-
Emergency Medical Transportation. Washington, DC: The National
Academies Press. Available at: https://doi.org/10.17226/23285.
\110\ National Academies of Sciences, Engineering, and Medicine
2006. Executive Summary: Cost-Benefit Analysis of Providing Non-
Emergency Medical Transportation. Washington, DC: The National
Academies Press. Available at: https://doi.org/10.17226/23285.
\111\ Hill-Briggs, F. (2021, January 1). Social Determinants of
Health and Diabetes: A Scientific Review. Diabetes Care. Available
at: https://pubmed.ncbi.nlm.nih.gov/33139407/.
\112\ Billioux, A., Verlander, K., Anthony, S., & Alley, D.
(2017). Standardized Screening for Health-Related Social Needs in
Clinical Settings: The Accountable Health Communities Screening
Tool. NAM Perspectives, 7(5). Available at: https://doi.org/10.31478/201705b.
\113\ Shier, G., Ginsburg, M., Howell, J., Volland, P., &
Golden, R. (2013). Strong Social Support Services, Such as
Transportation And Help For Caregivers, Can Lead To Lower Health
Care Use And Costs. Health Affairs, 32(3), 544-551. Available at:
https://doi.org/10.1377/hlthaff.2012.0170.
\114\ https://www.nami.org/Advocacy/Policy-Priorities/Supporting-Community-Inclusion-and-Non-Discrimination/Medicaid-Non-Emergency-Medical-Transportation.
\115\ Baxter, A., Tweed, E., Katikireddi, S., Thomson, H.
(2019). Effects of Housing First approaches on health and well-being
of adults who are homeless or at risk of homelessness: systematic
review and meta-analysis of randomized controlled trials. Journal of
Epidemiology and Community Health, 73; 379-387. Available at:
https://jech.bmj.com/content/jech/73/5/379.full.pdf.
\116\ Wright, B.J., Vartanian, K.B., Li, H.F., Royal, N., &
Matson, J.K. (2016). Formerly Homeless People Had Lower Overall
Health Care Expenditures After Moving into Supportive Housing.
Health Affairs, 35(1), 20-27. Available at: https://doi.org/10.1377/hlthaff.2015.0393.
\117\ Billioux, A., Verlander, K., Anthony, S., & Alley, D.
(2017). Standardized Screening for Health-Related Social Needs in
Clinical Settings: The Accountable Health Communities Screening
Tool. NAM Perspectives, 7(5). Available at: https://doi.org/10.31478/201705b.
\118\ Henry M., de Sousa, T., Roddey, C., Gayen, S., Bednar, T.;
Abt Associates. The 2020 Annual Homeless Assessment Report (AHAR) to
Congress; Part 1: Point-in-Time Estimates of Homelessness, January
2021. U.S. Department of Housing and Urban Development. Accessed
November 24, 2021. Available at: https://www.huduser.gov/portal/sites/default/files/pdf/2020-AHAR-Part-1.pdf.
\119\ Larimer, M.E. (2009). Health Care and Public Service Use
and Costs Before and After Provision of Housing for Chronically
Homeless Persons with Severe Alcohol Problems. JAMA, 301(13), 1349.
Available at: https://doi.org/10.1001/jama.2009.414.
\120\ https://ajph.aphapublications.org/doi/abs/10.2105/AJPH.2013.301680.
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[[Page 21282]]
If also adopted in the IPFQR Program, these two Social Drivers of
Health measures (that is, the Screening for Social Drivers of Health
measure being proposed for adoption in this section and the Screen
Positive Rate for Social Drivers of Health measure being proposed for
adoption in section V.D.4 of this proposed rule) would support
identification of specific risk factors for inadequate healthcare
access and adverse health outcomes among patients. We note that these
measures would enable systematic collection of HRSNs data. This
activity aligns with our other efforts beyond the acute care setting,
including the CY 2023 Medicare Advantage and Part D final rule in which
we finalized the policy requiring that all Special Needs Plans (SNPs)
include one or more questions on housing stability, food security, and
access to transportation in their health risk assessment using
questions from a list of screening instruments specified in sub-
regulatory guidance (87 FR 27726 through 27740) as well as the CY 2023
Physician Fee Schedule (PFS) final rule in which we adopted the
Screening for Social Drivers of Health measure in the Merit-based
Incentive Payment System (MIPS) Program (87 FR 70054 through 70055).
The proposed Social Drivers of Health measures (as set forth in
this section V.D.3 and section V.D.4. of this proposed rule) would
encourage IPFs to identify patients with HRSNs, who are known to
experience the greatest risk of poor health outcomes, thereby improving
the accuracy of high-risk prediction calculations. Improvement in risk
prediction has the potential to reduce healthcare access barriers,
address the disproportionate expenditures attributed to people with
greatest risk, and improve the IPF's quality of
care.121 122 123 124 Further, these data could guide future
public and private resource allocation to promote targeted
collaboration among IPFs, health systems, community-based
organizations, and others in support of improving patient outcomes. We
believe that this screening is especially important for IPF patients
because patients with psychiatric conditions have an increased risk of
having HRSNs.\125\
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\121\ Baker, MC, Alberti, PM, et al. (2021). Social Determinants
Matter for Hospital Readmission Policy: Insights From New York City.
Health Affairs, 40(4), 645-654. Available at: https://doi.org/10.1377/hlthaff.2020.01742. Accessed on February 20, 2023.
\122\ Hammond, G., Johnston, K., et al. (2020). Social
Determinants of Health Improve Predictive Accuracy of Clinical Risk
Models for Cardiovascular Hospitalization, Annual Cost, and Death.
Circulation: Cardiovascular Quality and Outcomes, 13 (6) 290-299.
Available at: https://doi.org/10.1161/CIRCOUTCOMES.120.006752.
Accessed on February 20, 2023.
\123\ Hill-Briggs, F. (2021). Social Determinants of Health and
Diabetes: A Scientific Review. Diabetes Care. Available at: https://diabetesjournals.org/care/article/44/1/258/33180/Social-Determinants-of-Health-and-Diabetes-A. Accessed on February 20,
2023.
\124\ Jaffrey, J.B., Safran, G.B., Addressing Social Risk
Factors in Value-Based Payment: Adjusting Payment Not Performance to
Optimize Outcomes and Fairness. Health Affairs Blog, April 19, 2021.
Available at: https://www.healthaffairs.org/do/10.1377/forefront.20210414.379479/full/. Accessed on February 20, 2023.
\125\ Adepoju, OE, Liaw, W, et al. (2022) Assessment of Unmet
Health-Related Social Needs Among Patients with Mental Illness
Enrolled in Medicare Advantage. Available at: https://jamanetwork.com/journals/jamanetworkopen/fullarticle/2798096.
Accessed on December 7, 2022.
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In the FY 2023 IPF PPS final rule, we observed that the Hospital
IQR Program had proposed two Social Drivers of Health measures and
stated that we would consider these measures for the IPFQR Program in
the future (87 FR 46873). The first of these two measures is the
Screening for Social Drivers of Health measure, which assesses the
percent of patients admitted to the hospital who are 18 years or older
at time of admission and are screened for food insecurity, housing
instability, transportation needs, utility difficulties, and
interpersonal safety.
Utilization of screening tools to identify the burden of unmet
HRSNs can be a helpful first step for IPFs in identifying necessary
community partners and connecting individuals to resources in their
communities. We believe collecting data across the same five HRSN
domains that were screened under the AHC Model and adopted for acute
care hospitals in the Hospital IQR Program would illuminate their
impact on health outcomes and disparities and the healthcare cost
burden for IPFs, particularly for IPFs that serve patients with
disproportionately high levels of social risk, given that patients with
serious mental illness are especially vulnerable to and affected by
HRSNs. In addition, data collection in the IPF care setting could
inform meaningful and sustainable solutions for provider-types
participating in other quality reporting programs to close equity gaps
among the communities they serve.\126\ \127\ \128\ \129\ \130\
---------------------------------------------------------------------------
\126\ The Physicians Foundation: 2020 Survey of America's
Patients, Part Three. Available at: https://physiciansfoundation.org/wp-content/uploads/2020/10/2020-Physicians-Foundation-Survey-Part3.pdf.
\127\ Office of the Assistant Secretary for Planning and
Evaluation (ASPE) (2020). Report to Congress: Social Risk Factors
and Performance Under Medicare's Value-Based Purchasing Program
(Second of Two Reports). Available at: https://aspe.hhs.gov/pdf-report/second-impact-report-to-congress.
\128\ Billioux, A., Verlander, K., Anthony, S., & Alley, D.
(2017). Standardized Screening for Health-Related Social Needs in
Clinical Settings: The Accountable Health Communities Screening
Tool. NAM Perspectives, 7(5). Available at: https://doi.org/10.31478/201705b.
\129\ Baker, M.C., Alberti, P.M., Tsao, T.Y., Fluegge, K.,
Howland, R.E., & Haberman, M. (2021). Social Determinants Matter for
Hospital Readmission Policy: Insights From New York City. Health
Affairs, 40(4), 645-654. Available at: https://doi.org/10.1377/hlthaff.2020.01742.
\130\ De Marchis, E., Knox, M., Hessler, D., Willard-Grace, R.,
Oliyawola, JN, et al. (2019). Physician Burnout and Higher Clinic
Capacity to Address Patients' Social Needs. The Journal of the
American Board of Family Medicine, 32 (1), 69-78.
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For data collection of the proposed Screening for Social Drivers of
Health measure, IPFs could use a self-selected screening tool and
collect these data in multiple ways, which can vary to accommodate the
population they serve and their individual needs. One example of a
potential screening tool for IPFs to collect data on the proposed
Screening for Social Drivers Health Measure is the AHC Model's standard
10-item AHC Health-Related Social Needs Screening Tool (AHC HRSN
Screening Tool), which enables providers to identify HRSNs in the five
core domains (described in Table 18) among community-dwelling Medicare,
Medicaid, and dually eligible beneficiaries. The AHC Model, including
its screening tool, was tested across many care delivery sites in
diverse geographic locations across the United States. More than one
million Medicare and Medicaid beneficiaries have been screened using
the AHC HRSN Screening Tool, which was evaluated psychometrically and
demonstrated evidence of both reliability and validity, including
inter-rater reliability and concurrent and
[[Page 21283]]
predictive validity. Moreover, the AHC HRSN Screening Tool can be
implemented in a variety of places where patients seek healthcare,
including inpatient psychiatric facilities.
The intent of the proposed Screening for Social Drivers of Health
measure is to promote adoption of HRSN screening by IPFs. We encourage
IPFs to use the screening as a basis for developing their own
individual action plans (for example, navigation services and
subsequent referral), as well as an opportunity to initiate or improve
partnerships with community-based service providers. We believe that
this proposed measure would yield actionable information to close
equity gaps by encouraging IPFs to identify patients with HRSNs, with a
reciprocal goal of strengthening linkages between IPFs and local
community-based partners to promptly connect patients and families to
the support they need.
Both the proposed Screening for Social Drivers of Health measure
and the proposed Screen Positive Rate for Social Drivers of Health
measure, discussed in V.D.4. of this proposed rule, address our
Meaningful Measures Framework's \131\ quality priority of ``Work with
Communities to Promote Best Practices of Healthy Living'' through the
Meaningful Measures Area of ``Equity of Care.'' Additionally, pursuant
to our Meaningful Measures 2.0, these proposed Social Drivers of Health
measures address the equity priority area and align with our commitment
to introduce plans to close health equity gaps and promote equity
through quality measures, including to ``develop and implement measures
that reflect social and economic determinants.'' \132\ Development and
proposal of these measures also align with our strategic pillar to
advance health equity by addressing the health disparities that
underlie our health system.\133\ Further, proposal of these measures
aligns with these measures' adoption in the Hospital IQR Program in the
FY 2023 IPPS/LTCH final rule (87 FR 49202 through 49215).
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\131\ Centers for Medicare & Medicaid Services. Meaningful
Measures Framework. Available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/QualityInitiativesGenInfo/CMS-Quality-Strategy.
\132\ Centers for Medicare & Medicaid Services. Meaningful
Measures 2.0: Moving from Measure Reduction to Modernization.
Available at: https://www.cms.gov/meaningful-measures-20-moving-measure-reduction-modernization.
\133\ Brooks-LaSure, C. (2021). My First 100 Days and Where We
Go From Here: A Strategic Vision for CMS. Available at: https://www.cms.gov/blog/my-first-100-days-and-where-we-go-here-strategic-vision-cms.
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The proposed Screening for Social Drivers of Health measure
(alongside the proposed Screen Positive Rate for Social Drivers of
Health measure described in section V.D.4 of this proposed rule) would
be the first measurement of social drivers of health in the IPFQR
Program. We believe this proposed measure is appropriate for
measurement of the quality of care furnished by IPFs. Screening
patients for HRSNs during inpatient hospitalization in an IPF would
allow healthcare providers, including IPFs, to identify and potentially
help address HRSNs for this medically underserved patient population as
part of discharge planning and contribute to long-term improvements in
patient outcomes. Identifying and addressing HRSNs for patients
receiving care in IPFs could have a direct and positive impact on IPFs'
quality performance because of improvements in patient outcomes that
could occur when patients' HRSNs are reduced. Moreover, collecting
aggregate data on the HRSNs of IPF patient populations via this
proposed measure is crucial in informing design of future measures that
could enable us to set appropriate performance targets for IPFs with
respect to closing the gap on health equity.
b. Overview of Measure
The proposed Screening for Social Drivers of Health measure would
assess whether an IPF implements screening for all patients who are 18
years or older at time of admission for food insecurity, housing
instability, transportation needs, utility difficulties, and
interpersonal safety. To report on this proposed measure, IPFs would
provide: (1) the number of inpatients admitted to the facility who are
18 years or older at time of admission and who are screened for all of
the five HRSNs (food insecurity, housing instability, transportation
needs, utility difficulties, and interpersonal safety); and (2) the
total number of patients who are admitted to the facility who are 18
years or older on the date they are admitted.
Measure specifications for the proposed Screening for Social
Drivers of Health measure, which were available during the review of
the MUC List, are available at https://mmshub.cms.gov/sites/default/files/map-hospital-measure-specifications-manual-2022.pdf.
(1) Measure Calculation
(a) Cohort
The proposed Screening for Social Drivers of Health measure would
assess the total number of patients aged 18 years and older, screened
for social risk factors (specifically, food insecurity, housing
instability, transportation needs, utility difficulties, and
interpersonal safety) during an IPF stay.
(b) Numerator
The numerator of the proposed Screening for Social Drivers of
Health measure consists of the number of patients admitted to an IPF
stay who are 18 years or older on the date of admission and are
screened during their IPF stay for all of the following five HRSNs:
food insecurity, housing instability, transportation needs, utility
difficulties, and interpersonal safety.
(c) Denominator
The denominator of the proposed Screening for Social Drivers of
Health measure consists of the number of patients who are admitted to
an IPF stay and who are 18 years or older on the date of admission. The
following patients would be excluded from the denominator: (1) patients
who opt-out of screening; and (2) patients who are themselves unable to
complete the screening during their inpatient stay and have no legal
guardian or caregiver able to do so on the patient's behalf during
their inpatient stay.
(d) Calculation
The proposed Screening for Social Drivers of Health measure would
be calculated as the number of patients admitted to an IPF stay who are
18 years or older on the date of admission screened for all five HRSNs
(food insecurity, housing instability, transportation needs, utility
difficulties, and interpersonal safety) divided by the number of
patients 18 years or older on the date of admission admitted to the
IPF.
(2) Review by the Measure Applications Partnership
We included the proposed Screening for Social Drivers of Health
measure on the publicly available ``List of Measures Under
Consideration for December 1, 2022'' (MUC List), a list of measures
under consideration for use in various Medicare programs.\134\ The CBE-
[[Page 21284]]
convened MAP Health Equity Advisory Group reviewed the MUC List
including the proposed Screening for Social Drivers of Health measure
(MUC 2022-053) in detail on December 6 through 7, 2022.\135\ The MAP
Health Equity Advisory Group expressed support for the collection of
data related to social drivers of health, but raised concerns regarding
public reporting of these data and potential repetition of asking
patients the same questions across settings.\136\
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\134\ Centers for Medicare & Medicaid Services. List of Measures
Under Consideration for December 1, 2022. Available at: https://mmshub.cms.gov/measure-lifecycle/measure-implementation/pre-rulemaking/lists-and-reports.
\135\ Centers for Medicare & Medicaid Services. 2022-2023 MAP
Final Recommendations. Available at: https://mmshub.cms.gov/measure-lifecycle/measure-implementation/pre-rulemaking/lists-and-reports.
\136\ Centers for Medicare & Medicaid Services. 2022-2023 MAP
Final Recommendations. Available at: https://mmshub.cms.gov/measure-lifecycle/measure-implementation/pre-rulemaking/lists-and-reports.
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In addition, on December 8 through 9, 2022, the MAP Rural Health
Advisory Group reviewed the 2022 MUC List and the MAP Hospital
Workgroup did so on December 13 through 14, 2022.\137\ The MAP Rural
Health Advisory Group noted some potential reporting challenges
including the potential masking of health disparities that are
underrepresented in some areas and that sample size and populations
served may be an issue, but expressed that the proposed measure serves
as a starting point to determine where screening is occurring. The MAP
Hospital Workgroup expressed strong support for the measure but noted
that interoperability will be important and cautioned about survey
fatigue. The MAP Hospital Workgroup members conditionally supported the
measure pending: (1) testing of the measure's reliability and validity;
(2) endorsement by the CBE; (3) additional details on how potential
tools map to the individual HRSNs, as well as best practices; (4)
identification of resources that may be available to assist patients
with identified HRSNs; and (5) the measure's alignment with data
standards, particularly the GRAVITY project.\138\ The GRAVITY project's
mission statement is ``to serve as the open public collaborative
advancing health and social data standardization for health equity.''
\139\ Thereafter, the MAP Coordinating Committee deliberated on January
24 through 25, 2023, and ultimately voted to uphold the MAP Hospital
Workgroup's recommendation to conditionally support for rulemaking with
the same conditions.\140\
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\137\ Centers for Medicare & Medicaid Services. 2022-2023 MAP
Final Recommendations. Available at: https://mmshub.cms.gov/measure-lifecycle/measure-implementation/pre-rulemaking/lists-and-reports.
\138\ Centers for Medicare & Medicaid Services. 2022-2023 MAP
Final Recommendations. Available at: https://mmshub.cms.gov/measure-lifecycle/measure-implementation/pre-rulemaking/lists-and-reports.
\139\ https://thegravityproject.net/.
\140\ Centers for Medicare & Medicaid Services. 2022-2023 MAP
Final Recommendations. Available at: https://mmshub.cms.gov/measure-lifecycle/measure-implementation/pre-rulemaking/lists-and-reports.
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We believe this measure establishes an important foundation for
prioritizing the achievement of health equity among IPFs. Our approach
to developing health equity measures is incremental, and we believe
that health care equity outcomes in the IPFQR Program will inform
future efforts to advance and achieve health care equity by IPFs. We
additionally believe this measure to be a building block that lays the
groundwork for a future meaningful suite of measures that would assess
IPF progress in providing high-quality healthcare for all patients,
regardless of social risk factors or demographic characteristics.
(3) CBE Endorsement
We have not submitted this measure for CBE endorsement at this
time. Although section 1886(s)(4)(D)(i) of the Act generally requires
that measures specified by the Secretary shall be endorsed by the
entity with a contract under section 1890(a) of the Act, section
1886(s)(4)(D)(ii) of the Act, states that in the case of a specified
area or medical topic determined appropriate by the Secretary for which
a feasible and practical measure has not been endorsed by the entity
with a contract under section 1890(a) of the Act, the Secretary may
specify a measure that is not so endorsed as long as due consideration
is given to a measure that has been endorsed or adopted by a consensus
organization identified by the Secretary. We reviewed CBE-endorsed
measures and were unable to identify any other CBE-endorsed measures on
this topic, and therefore, we believe the exception in section
1886(s)(4)(D)(ii) of the Act applies.
c. Data Collection, Submission and Reporting
We believe incremental implementation of the proposed Screening for
Social Drivers of Health measure, by permitting one year of voluntary
reporting prior to required reporting, would allow IPFs who are not yet
screening patients for HRSNs to get experience with collecting data for
this proposed measure and equally allow IPFs who already undertake
screening efforts to report data already being collected. Therefore, we
propose voluntary reporting of this measure beginning with the data
collected in CY 2024, which would be reported to CMS in CY 2025,
followed by required reporting beginning with data collected in CY
2025, which would be reported to CMS in CY 2026 for the FY 2027 payment
determination.
Due to variability across IPFs and the populations they serve, and
in alignment with the Hospital IQR Program, we would allow IPFs
flexibility with selection of tools to screen patients for food
insecurity, housing instability, transportation needs, utility
difficulties, and interpersonal safety. Potential sources of these data
could include, for example, administrative claims data, electronic
clinical data, standardized patient assessments, or patient-reported
data and surveys.
Multiple screening tools for health-related social needs (HRSNs)
already exist. For additional information on resources, we refer
readers to evidence-based resources like the Social Interventions
Research and Evaluation Network (SIREN) website, for example, for
comprehensive information about the most widely used HRSN screening
tools.141 142 SIREN contains descriptions of the content and
characteristics of various tools, including information about intended
populations, completion time, and number of questions.
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\141\ Social Interventions Research & Evaluation Network.
(2019). Social Needs Screening Tool Comparison Table. Available at:
https://sirenetwork.ucsf.edu/tools-resources/resources/screening-tools-comparison. Accessed January 18, 2021.
\142\ The Social Interventions Research and Evaluation Network
(SIREN) at University of California San Francisco was launched in
the spring of 2016 to synthesize, disseminate, and catalyze research
on SDOH and healthcare delivery.
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We would encourage IPFs to consider digital standardized screening
tools and refer readers to the FY 2023 IPPS/LTCH PPS final rule (87 FR
49207 through 49208) where we discuss how the use of certified health
information technology (IT), including but not limited to certified EHR
technology, can support capture of HRSN information in an interoperable
fashion so that these data can be shared across the care continuum to
support coordinated care. We also encourage readers to learn about the
United States Core Data for Interoperability (USCDI) standard used in
certified health IT and how this standard can support interoperable
exchange of health and HRSN assessment data.\143\
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\143\ Office of the National Coordinator for Health IT (ONC).
United States Core Data for Interoperability. Accessed at: https://www.healthit.gov/isa/united-states-core-data-interoperability-uscdi.
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[[Page 21285]]
We propose that IPFs would report aggregate data on this measure,
that is IPFs would report aggregated data for the numerator and the
denominator to CMS (as described in section V.D.3.b.(1). of this
proposed rule) but would not be required to report patient-level data.
IPFs are required to submit information for chart-abstracted measures
once annually using a CMS-approved web-based data collection tool
available within the HQR System (previously referred to as the
QualityNet Secure Portal). We refer readers to section V.I. of the
preamble of this proposed rule (Form, Manner, and Timing of Quality
Data Submission) for more details on our previously finalized data
submission and deadline requirements across measure types.
We invite public comment on this proposal.
4. Proposal To Adopt the Screen Positive Rate for Social Drivers of
Health Measure Beginning With Voluntary Reporting of CY 2024 Data and
Followed by Required Reporting Beginning With CY 2025 Data/FY 2027
Payment Determination
a. Background
The impact of social risk factors on health outcomes has been well-
established in the literature.144 145 146 147 148 The
Physicians Foundation reported that 73 percent of the physician
respondents to the 2021 iteration of their annual survey agreed that
social risk factors like housing instability and food insecurity would
drive health services demand.\149\ Recognizing the need for a more
comprehensive approach to eliminating the health equity gap, we have
prioritized quality measures that would capture social risk factors and
facilitate assessment of their impact on health outcomes and
disparities and healthcare utilization and costs.150 151 152
Specifically, in the inpatient setting, we aim to encourage systematic
identification of patients' HRSNs (as defined in section V.D.3.a. of
this proposed rule) as part of discharge planning with the intention of
promoting linkages with relevant community-based services that address
those needs and support improvements in health outcomes following
discharge from the IPF.
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\144\ Institute of Medicine 2014. Capturing Social and
Behavioral Domains and Measures in Electronic Health Records: Phase
2. Washington, DC: The National Academies Press. Available at:
https://doi.org/10.17226/18951.
\145\ Centers for Medicare & Medicaid Services. (2021).
Accountable Health Communities Model. Accountable Health Communities
Model CMS Innovation Center. Available at: https://innovation.cms.gov/innovation-models/ahcm. Accessed November 23,
2021.
\146\ Kaiser Family Foundation. (2021). Racial and Ethnic Health
Inequities and Medicare. Available at: https://www.kff.org/medicare/report/racial-and-ethnic-health-inequities-and-medicare/. Accessed
November 23, 2021.
\147\ Milkie Vu et al. Predictors of Delayed Healthcare Seeking
Among American Muslim Women, Journal of Women's Health 26(6) (2016)
at 58; Nadimpalli SB, Cleland CM, Hutchinson MK, Islam N, Barnes LL,
Van Devanter N. (2016) The Association between Discrimination and
the Health of Sikh Asian Indians. Health Psychology, 35(4), 351-355.
https://doi.org/10.1037/hea0000268.
\148\ Office of the Assistant Secretary for Planning and
Evaluation (ASPE). (2020). Report to Congress: Social Risk Factors
and Performance Under Medicare's Value-Based Purchasing Program
(Second of Two Reports). Available at: https://aspe.hhs.gov/pdf-report/second-impact-report-to-congress.
\149\ The Physicians Foundation. (2020) 2020 Survey of America's
Patients, Part Three. Available at: https://physiciansfoundation.org/wp-content/uploads/2020/10/2020-Physicians-Foundation-Survey-Part3.pdf.
\150\ Alley, D.E., C.N. Asomugha, P.H. Conway, and D.M.
Sanghavi. 2016. Accountable Health Communities--Addressing Social
Needs through Medicare and Medicaid. The New England Journal of
Medicine 374(1):8-11. Available at: https://doi.org/10.1056/NEJMp1512532.
\151\ Centers for Medicare & Medicaid Services. (2021).
Accountable Health Communities Model. Accountable Health Communities
Model CMS Innovation Center. Available at: https://innovation.cms.gov/innovation-models/ahcm. Accessed November 23,
2021.
\152\ Billioux, A., Verlander, K., Anthony, S., & Alley, D.
(2017). Standardized Screening for Health-Related Social Needs in
Clinical Settings: The Accountable Health Communities Screening
Tool. NAM Perspectives, 7(5). Available at: https://doi.org/10.31478/201705b.
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While the Screening for Social Drivers of Health measure (discussed
previously in section V.D.3. of this proposed rule) enables
identification of individuals with HRSNs, use of the proposed Screen
Positive Rate for Social Drivers of Health measure would allow IPFs to
capture the magnitude of these needs and even estimate the impact of
individual-level HRSNs on healthcare utilization when evaluating
quality of care.153 154 155 The proposed Screen Positive
Rate for Social Drivers of Health measure would require IPFs to report
the rates of patients who screened positive for each of the five core
HRSNs. Reporting the screen positive rate for each of the five core
HRSNs would inform actionable planning by IPFs towards closing health
equity gaps unique to the populations they serve and enable the
development of individual patient action plans (including navigation
and referral services).
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\153\ Baker, M.C., Alberti, P.M., Tsao, T.Y., Fluegge, K.,
Howland, R.E., & Haberman, M. (2021). Social Determinants Matter for
Hospital Readmission Policy: Insights From New York City. Health
Affairs, 40(4), 645-654. Available at: https://doi.org/10.1377/hlthaff.2020.01742.
\154\ CMS. Accountable Health Communities Model. Accountable
Health Communities Model CMS Innovation Center. Available at:
https://innovation.cms.gov/innovation-models/ahcm. Accessed November
23, 2021.
\155\ Hammond, G., Johnston, K., Huang, K., Joynt Maddox, K.
(2020). Social Determinants of Health Improve Predictive Accuracy of
Clinical Risk Models for Cardiovascular Hospitalization, Annual
Cost, and Death. Circulation: Cardiovascular Quality and Outcomes,
13 (6) 290-299. Available at: https://doi.org/10.1161/CIRCOUTCOMES.120.006752.
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In the FY 2022 IPF PPS final rule (86 FR 42625 through 42632) and
the FY 2023 IPF PPS final rule (87 FR 46865 through 46873), we
discussed our ongoing consideration of potential approaches that could
be implemented to address health equity through the IPFQR Program. As a
result of the feedback we received, we identified the Screen Positive
Rate for Social Drivers of Health measure to help inform efforts to
address health equity.
This proposed measure would assess the percent of patients admitted
to the IPF who are 18 years or older at time of admission who were
screened for HRSNs and who screen positive for one or more of the core
HRSNs, including food insecurity, housing instability, transportation
needs, utility difficulties, or interpersonal safety (reported as five
separate rates).\156\
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\156\ Billioux, A., Verlander, K., Anthony, S., & Alley, D.
(2017). Standardized Screening for Health Related Social Needs in
Clinical Settings: The Accountable Health Communities Screening
Tool. NAM Perspectives, 7(5). Available at: https://doi.org/10.31478/201705b.
---------------------------------------------------------------------------
We refer readers to section V.D.3 of this proposed rule where we
previously discussed the screening and identification process resulting
in the selection of these five domains associated with the proposed
Screen for Social Drivers of Health measure. The proposed Screening for
Social Drivers of Health measure forms the basis of this proposed
Screen Positive Rate for Social Drivers of Health measure. That is, the
number of patients screened for all five HRSNs in the Screening for
Social Drivers of Health measure is the denominator of the Screen
Positive for Social Drivers of Health measure described here.
The COVID-19 pandemic underscored the overwhelming impact that
these five core domains of HRSNs have on disparities, health risk,
healthcare access, and health outcomes, including premature
mortality.157 158
[[Page 21286]]
Adoption of the Screen Positive Rate for Social Drivers of Health
measure would encourage IPFs to track prevalence of specific HRSNs
among patients over time and use the data to stratify risk as part of
quality performance improvement efforts. This proposed measure may also
prove useful for patients by providing data transparency and signifying
IPFs' familiarity, expertise, and commitment regarding these health
equity issues. This proposed measure also has the potential to reduce
healthcare provider burden and burnout, including among IPFs and their
staff, by both acknowledging patients' non-clinical needs that
nevertheless greatly contribute to adverse clinical outcomes and
linking providers with community-based organizations to enhance
patient-centered treatment and discharge
planning.159 160 161 Finally, we believe the proposed Screen
Positive Rate for Social Drivers of Health measure has the potential to
facilitate data-informed collaboration with community-based services
and focused community investments, including the development of
pathways and infrastructure to connect patients to local community
resources.
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\157\ Kaiser Family Foundation. (2021). Racial and Ethnic Health
Inequities and Medicare. Available at: https://www.kff.org/medicare/report/racial-and-ethnic-health-inequities-and-medicare/. Accessed
November 23, 2021.
\158\ Centers for Disease Control and Prevention. (2019). CDC
COVID-19 Response Health Equity Strategy: Accelerating Progress
Towards Reducing COVID-19 Disparities and Achieving Health Equity.
July 2020. Available at: https://www.cdc.gov/coronavirus/2019-ncov/community/health-equity/cdc-strategy.html. Accessed November 17,
2021.
\159\ The Physicians Foundation. (2020). Survey of America's
Patients, Part Three. Available at: https://physiciansfoundation.org/wp-content/uploads/2020/10/2020-Physicians-Foundation-Survey-Part3.pdf.
\160\ De Marchis, E., Knox, M., Hessler, D., WillardGrace, R.,
Oliyawola, JN, et al. (2019). Physician Burnout and Higher Clinic
Capacity to Address Patients' Social Needs. The Journal of the
American Board of Family Medicine, 32 (1), 69-78.
\161\ Kung, A., Cheung, T., Knox, M., Willard-Grace, R.,
Halpern, J., et.al, (2019). Capacity to Address Social Needs Affect
Primary Care Clinician Burnout. Annals of Family Medicine. 17 (6),
487-494. Available at: https://doi.org/10.1370/afm.2470.
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Ultimately, we are focused on supporting effective and sustainable
collaboration between healthcare delivery and local community-based
services organizations to meet the unmet needs of people they serve.
Reporting data from both the Screening for Social Drivers of Health and
the Screen Positive Rate for Social Drivers of Health measures would
enable both identification and quantification of the levels of HRSNs
among communities served by IPFs. These two Social Drivers of Health
measures harmonize, as it is important to know both whether screening
occurred and the results from the screening in order to develop
sustainable solutions. We believe that there are multiple benefits to
increasing IPFs' understanding of their patients' HRSNs. First, we
believe that this could lead to increased clinical-community
collaborations and an associated increase in system capacity and
community investments. Second, we believe this in turn could yield a
net reduction in costly healthcare utilization by promoting more
appropriate healthcare service consumption.\162\
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\162\ Centers for Medicare & Medicaid Services. (2021).
Accountable Health Communities Model. Accountable Health Communities
Model [bond] CMS Innovation Center. Available at: https://innovation.cms.gov/innovation-models/ahcm. Accessed November 23,
2021.
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Pursuant to our Meaningful Measures 2.0 Framework and in alignment
with the measures previously adopted for hospitals participating in the
Hospital IQR Program, the proposed Screen Positive Rate for Social
Drivers of Health measure would address the equity priority area and
align with our commitment to introduce plans to close health equity
gaps and promote equity through quality measures, including to
``develop and implement measures that reflect social and economic
determinants.'' \163\ Under our Meaningful Measures Framework, the
Screen Positive Rate for Social Drivers of Health measure would address
the quality priority of ``Work with Communities to Promote Best
Practices of Healthy Living'' through the Meaningful Measures Area of
``Equity of Care.'' \164\ Adoption of this proposed measure would also
align with our strategic pillar to advance health equity by addressing
the health disparities that underlie our health system.\165\
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\163\ Centers for Medicare & Medicaid Services. Meaningful
Measures 2.0: Moving from Measure Reduction to Modernization.
Available at: https://www.cms.gov/meaningful-measures-20-moving-measure-reduction-modernization.
\164\ Centers for Medicare & Medicaid Services. (2021). CMS
Measures Management System Blueprint (Blueprint v 17.0). Available
at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/MMS/MMS-Blueprint.
\165\ Brooks-LaSure, C. (2021). My First 100 Days and Where We
Go From Here: A Strategic Vision for CMS. Available at: https://www.cms.gov/blog/my-first-100-days-and-where-we-go-here-strategic-vision-cms.
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b. Overview of Measure
The proposed Screen Positive Rate for Social Drivers of Health
measure is intended to enhance standardized data collection that can
identify individuals who are at higher risk for poor health outcomes
related to HRSNs who would benefit from connection via the IPF to
targeted community-based services.\166\ The proposed measure would
identify the proportion of patients who screened positive for one or
more of the following five HRSNs on the date of admission to the IPF:
food insecurity, housing instability, transportation needs, utility
difficulties, and interpersonal safety.
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\166\ Centers for Medicare & Medicaid Services. (2021). A Guide
to Using the Accountable Health Communities Health-Related Social
Needs Screening Tool: Promising Practices and Key Insights (June
2021). Available at: https://innovation.cms.gov/media/document/ahcm-screeningtool-companion. Accessed November 23, 2021.
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Consistent with the Hospital IQR Program, which adopted this
measure in the FY 2023 IPPS/LTCH PPS final rule (87 FR 49215 through
49220), we would require IPFs to report this measure as five separate
rates. Specifically, IPFs would report the number of patients who
screened positive for food insecurity, the number of patients who
screened positive for housing instability, the number of patients who
screened positive for transportation needs, the number of patients who
screened positive for utility difficulties, and the number of patients
who screened positive for interpersonal safety. We note that this
measure is intended to provide information to IPFs on the level of
unmet HRSNs among patients served, and not for comparison between IPFs.
The specifications for the proposed Screen Positive Rate for Social
Drivers of Health measure, which were available during the review of
the MUC List, are available at: https://mmshub.cms.gov/sites/default/files/map-hospital-measure-specifications-manual-2022.pdf.
(1) Measure Calculation
(a) Cohort
The proposed Screen Positive Rate for Social Drivers of Health is a
process measure that would provide information on the percent of
patients, 18 years or older on the date of admission for an IPF stay,
who were screened for an HRSN, and who screen positive for one or more
of the following five HRSNs: food insecurity; housing instability;
transportation needs; utility difficulties; or interpersonal safety.
(b) Numerator
The numerator would consist of the number of patients admitted for
an IPF stay who are 18 years or older on the date of admission, who
were screened for an HRSN, and who screen positive for having an unmet
need in one or more of the following five HRSNs (calculated
separately): The number of patients who screened positive for food
insecurity, the number of patients who screened positive for housing
instability, the number of patients who screened positive for
transportation needs, the number of patients who screened positive for
utility difficulties, and the number of patients who
[[Page 21287]]
screened positive for interpersonal safety. IPFs would report the
number of patients who screened positive for having unmet needs in each
of the five HRSNs as a separate numerator. A patient who screened
positive for more than one unmet HRSN would be included in the
numerator for each of those HRSNs. For example, a patient who screened
positive for food insecurity, housing instability, and transportation
needs would be included in each of these numerators.
(c) Denominator
The denominator would consist of the number of patients admitted
for an IPF stay who are 18 years or older on the date of admission and
are screened for an HRSN (food insecurity, housing instability,
transportation needs, utility difficulties and interpersonal safety)
during their IPF stay. The following patients would be excluded from
the denominator: (1) patients who opt-out of screening; and (2)
patients who are themselves unable to complete the screening during
their inpatient stay and have no caregiver able to do so on the
patient's behalf during their inpatient stay.
(d) Calculation
The result of this measure would be calculated as five separate
rates. Each rate is derived from the number of patients admitted for an
IPF stay and who are 18 years or older on the date of admission,
screened for an HRSN, and who screen positive for each of the five
HRSNs (that is, the number of patients who screened positive for food
insecurity, the number of patients who screened positive for housing
instability, the number of patients who screened positive for
transportation needs, the number of patients who screened positive for
utility difficulties, and the number of patients who screened positive
for interpersonal safety) divided by the number of patients 18 years or
older on the date of admission screened for all five HRSNs. The measure
is reported as five separate rates--one for each HRSN, each calculated
with the same denominator.
(2) Review by the Measure Applications Partnership
We included the proposed Screen Positive Rate for Social Drivers of
Health measure on the publicly available MUC List, a list of measures
under consideration for use in various Medicare programs.\167\ The CBE-
convened MAP Health Equity Advisory Group reviewed the MUC List and the
Screen Positive Rate for Social Drivers of Health measure (MUC 2022-
050) in detail on December 6 through 7, 2022.\168\ The MAP Health
Equity Advisory Group expressed support for the collection of data
related to social drivers of health, but raised concerns regarding
public reporting of these data and potential repetition of asking
patients the same questions across settings.\169\
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\167\ Centers for Medicare & Medicaid Services. List of Measures
Under Consideration for December 1, 2022. Available at: https://mmshub.cms.gov/measure-lifecycle/measure-implementation/pre-rulemaking/lists-and-reports.
\168\ Centers for Medicare & Medicaid Services. 2022-2023 MAP
Final Recommendations. Available at: https://mmshub.cms.gov/measure-lifecycle/measure-implementation/pre-rulemaking/lists-and-reports.
\169\ Centers for Medicare & Medicaid Services. 2022-2023 MAP
Final Recommendations. Available at: https://mmshub.cms.gov/measure-lifecycle/measure-implementation/pre-rulemaking/lists-and-reports.
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In addition, on December 8 through 9, 2022, the MAP Rural Health
Advisory Group reviewed the 2022 MUC List, which was also reviewed by
the MAP Hospital Workgroup on December 13 through 14, 2022.\170\ The
MAP Rural Health Advisory Group noted potential reporting challenges
including the potential masking of health disparities that are
underrepresented in some areas and that sample size and populations
served may be an issue, but also expressed support that the measure
seeks to advance the drivers of health and serves as a starting point
to determine where screening is occurring. The MAP Hospital Workgroup
recommended conditional support of the measure for rulemaking pending:
(1) endorsement by the CBE to address reliability and validity
concerns; (2) attentiveness to how results are shared and
contextualized for public reporting; and (3) examination of any
differences in reported rates by reporting process (that is, to assess
whether reported rates are the same or different across IPFs and other
facilities that may use different processes to report their data).\171\
Thereafter, the MAP Coordinating Committee deliberated on January 24
through 25, 2023, and ultimately voted to conditionally support the
Screen Positive Rate for Social Drivers of Health measure for
rulemaking with the same conditions.\172\
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\170\ Centers for Medicare & Medicaid Services. 2022-2023 MAP
Final Recommendations. Available at: https://mmshub.cms.gov/measure-lifecycle/measure-implementation/pre-rulemaking/lists-and-reports.
\171\ Centers for Medicare & Medicaid Services. 2022-2023 MAP
Final Recommendations. Available at: https://mmshub.cms.gov/measure-lifecycle/measure-implementation/pre-rulemaking/lists-and-reports.
\172\ Centers for Medicare & Medicaid Services. 2022-2023 MAP
Final Recommendations. Available at: https://mmshub.cms.gov/measure-lifecycle/measure-implementation/pre-rulemaking/lists-and-reports.
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We agree with the MAP Coordinating Committee's support for the
proposed Screen Positive Rate for Social Drivers of Health measure. We
believe this measure, alongside the Screening for Social Drivers of
Health measure, establishes an important foundation to prioritizing the
achievement of health equity among IPFs participating in the IPFQR
Program. Our approach to developing health equity measures is
incremental, and we believe that health equity outcomes in the IPFQR
Program will inform future efforts to advance and achieve health equity
by IPFs. We believe this measure to be a building block that lays the
groundwork for a future meaningful suite of measures that would assess
IPF progress in providing high-quality healthcare for all patients,
regardless of social risk factors or demographic characteristics.
(3) CBE Endorsement
We have not submitted this measure for CBE endorsement at this
time. Although section 1886(s)(4)(D)(i) of the Act generally requires
that measures specified by the Secretary shall be endorsed by the
entity with a contract under section 1890(a) of the Act, section
1886(s)(4)(D)(ii) of the Act states that in the case of a specified
area or medical topic determined appropriate by the Secretary for which
a feasible and practical measure has not been endorsed by the entity
with a contract under section 1890(a) of the Act, the Secretary may
specify a measure that is not so endorsed as long as due consideration
is given to a measure that has been endorsed or adopted by a consensus
organization identified by the Secretary. We reviewed CBE-endorsed
measures and were unable to identify any other CBE-endorsed measures on
this topic; therefore, we believe the exception in section
1886(s)(4)(D)(ii) of the Act applies.
c. Data Collection, Submission, and Reporting
We believe incremental implementation of the proposed Screen
Positive Rate for Social Drivers of Health measure, by permitting one
year of voluntary reporting prior to required reporting, would allow
IPFs who are not yet screening patients for HRSNs to get experience
with the measure and equally allow IPFs who already undertake screening
efforts to report
[[Page 21288]]
data already being collected. Therefore, we propose voluntary reporting
of this measure, along with the Screening for Social Drivers of Health
measure described in section V.D.3 of this proposed rule, beginning
with the data collected in CY 2024, which would be reported to CMS in
2025 followed by required reporting beginning with data collected in CY
2025, which would be reported to CMS in 2026 and affect FY 2027 payment
determination.
While this measure would require IPFs to collect patient-level data
on their patients' social drivers of health screening results, we
propose to adopt this measure as an aggregate measure (that is, IPFs
would be required to submit only numerator results for each of the five
screening areas and the number of patients screened for all five of the
HRSNs). IPFs are required to submit information for aggregate chart-
abstracted measures once annually using a CMS-approved web-based data
collection tool available within the HQR System (previously referred to
as the QualityNet Secure Portal). We refer readers to section V.I of
this proposed rule (Form, Manner, and Timing of Quality Data
Submission) for more details on our previously finalized data
submission and deadline requirements across measure types.
We invite public comment on this proposal.
5. Proposal To Adopt the Psychiatric Inpatient Experience (PIX) Survey
Beginning With Voluntary Reporting of CY 2025 Data and Required
Reporting Beginning With CY 2026 Data/FY 2028 Payment Determination
a. Background
We believe that a comprehensive approach to quality must include
directly reported feedback regarding facility, provider, and payer
performance. Therefore, we have consistently stated our commitment to
identifying an appropriate patient experience of care measure for the
IPF setting and adopting this measure in the IPFQR Program at the first
opportunity (77 FR 53646, 78 FR 50897, 79 FR 45964 through 45965, 80 FR
46714 through 46715, 82 FR 38470 through 38471, 83 FR 38596, 84 FR
38467, 85 FR 47043, 86 FR 42654 through 42656, and 87 FR 46846).
In the FY 2014 IPPS/LTCH PPS final rule, we adopted a voluntary
information collection regarding whether IPFs participating in the
IPFQR Program assess patient experience of inpatient behavioral health
services using a standardized instrument and for IPFs that answer
``Yes'' to indicate the name of the survey that they administer (78 FR
50896 through 50897). In the FY 2015 IPF PPS final rule, we adopted
this information collection as the Assessment of Patient Experience of
Care measure beginning with the FY 2016 payment determination (79 FR
45964 through 45965). Data for CY 2016 showed that while the majority
of IPFs (approximately 76 percent) were collecting patient experience
of care data through a standardized instrument, there was a wide
variation in the instrument being used. The data for CY 2016 indicated
that the most widely used survey instrument was not in the public
domain and was used by less than 30 percent of the IPFs that used a
patient experience survey. In the FY 2015 IPF PPS final rule, we
indicated our intention to adopt a standardized measure of patient
experience of care for the IPFQR Program.
In the FY 2019 IPF PPS final rule, we removed the Assessment of
Patient Experience of Care measure from the IPFQR Program because we
believed that we had collected sufficient information to inform
development of a patient experience of care measure (83 FR 38596
through 38597). In the FY 2020 IPF PPS final rule, we summarized our
request for comments on our analysis of the results of the Assessment
of Patient Experience of Care measure and feedback on potential
adoption of the Hospital Consumer Assessment of Healthcare Providers
and Systems (HCAHPS) survey for the IPFQR Program (84 FR 38467). In
response to our request, many commenters expressed concern that HCAHPS
was not specified for the IPF setting and recommended that CMS identify
a survey that has been developed for and tested in the IPF setting.
Furthermore, in the FY 2021 IPF PPS proposed rule, we did not propose
any updates to the IPFQR Program; however, we received many comments
requesting that we adopt a patient experience of care measure in the
IPFQR Program, which we summarized in the FY 2021 IPF PPS final rule
(85 FR 47043). We received similar input strongly advocating for a
patient experience of care measure for the IPFQR Program in response to
a solicitation of comments on potential measures for the IPFQR Program
in the FY 2022 IPF PPS proposed rule, which we summarized in the FY
2022 IPF PPS final rule (86 FR 42654 through 42656). Many of these
comments were from patients and their families and described how
meaningful such a measure would be for individuals who receive services
from IPFs. Though we did not solicit input on a patient experience of
care measure in the FY 2023 IPF PPS proposed rule, we received many
comments strongly recommending that we adopt such a measure, which we
summarized in the FY 2023 IPF PPS final rule (87 FR 46846). Since
publication of the FY 2023 IPF PPS final rule, section 4125(c) of the
Consolidated Appropriations Act, 2023 (Pub. L. 117-328) was enacted,
which amends section 1886(s)(4) of the Act to require that the quality
measures specified for the IPFQR Program shall include a quality
measure of patients' perspective on care not later than the FY 2031
payment determination.
We have continued to review publicly available patient experience
of care instruments to identify such an instrument specified for, and
tested in, the IPF setting. In our review, we identified the
Psychiatric Inpatient Experience (PIX) survey as a publicly available
survey instrument developed for and tested in the IPF setting. Pursuant
to the Meaningful Measures 2.0 Framework, this measure addresses the
``Person-Centered'' priority area, as well as the ``Individual and
Caregiver Voice'' foundation and aligns with our commitment to
prioritize outcome and patient-reported measures.\173\ This measure
also aligns with the CMS National Quality Strategy Goal 4 ``Foster
Engagement.'' It also supports the Behavioral Health Strategy goal of
``Strengthen Equity and Quality in Behavioral Health Care.'' \174\
Furthermore, this measure supports the new Universal Foundation domain
of ``Person-Centered Care.'' \175\
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\173\ Centers for Medicare & Medicaid Services. Meaningful
Measures 2.0: Moving from Measure Reduction to Modernization.
Available at: https://www.cms.gov/meaningful-measures-20-moving-measure-reduction-modernization.
\174\ CMS. (2022). CMS Behavioral Health Strategy. Available at
https://www.cms.gov/cms-behavioral-health-strategy. Accessed on
February 20, 2023.
\175\ https://www.nejm.org/doi/full/10.1056/NEJMp2215539.
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b. Overview of Measure
The PIX survey was developed by a team at the Yale University, Yale
New Haven Psychiatric Hospital to address the gap in available
experience of care surveys, specifically the lack of publicly
available, minimally burdensome, psychometrically validated surveys
specified for the IPF setting.\176\ The interdisciplinary team that
developed this survey, including researchers and clinicians, conducted
the following steps in developing the survey: (1)
[[Page 21289]]
literature review; (2) patient focus groups; (3) solicitation of input
from a patient and family advisory council; (4) review of content
validity with an expert panel; (5) development of survey; and (6)
survey testing within the Yale New Haven Psychiatric Hospital
system.\177\
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\176\ Klemanski DH, Barnes T, Bautista C, Tancreti C, Klink B,
Dix E. Development and Validation of the Psychiatric Inpatient
Experience (PIX) Survey: A Novel Measure of Patient Experience
Quality Improvement. Journal of Patient Experience. 2022;9.
doi:10.1177/23743735221105671.
\177\ Klemanski DH, Barnes T, Bautista C, Tancreti C, Klink B,
Dix E. Development and Validation of the Psychiatric Inpatient
Experience (PIX) Survey: A Novel Measure of Patient Experience
Quality Improvement. Journal of Patient Experience. 2022;9.
doi:10.1177/23743735221105671.
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The resulting survey contains 23 items in four domains. Patients
can respond to each of the 23 items using a five-point Likert scale
(that is, strongly disagree, somewhat disagree, neutral, somewhat
agree, strongly agree) or choose that the item does not apply. The four
domains are:
Relationship with Treatment Team;
Nursing Presence;
Treatment Effectiveness; and
Healing Environment.\178\
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\178\ Klemanski DH, Barnes T, Bautista C, Tancreti C, Klink B,
Dix E. Development and Validation of the Psychiatric Inpatient
Experience (PIX) Survey: A Novel Measure of Patient Experience
Quality Improvement. Journal of Patient Experience. 2022;9.
doi:10.1177/23743735221105671.
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The PIX survey is distributed to patients by administrative staff
at a time beginning 24 hours prior to planned discharge. The survey,
which is available in both English and Spanish, can be completed prior
to discharge using either a paper copy of the survey or an electronic
version of the survey via tablet computer.\179\ For a complete list of
survey questions, including which questions are elements of each
domain, we refer readers to the description of the survey in the
Journal of Patient Experience: https://journals.sagepub.com/doi/full/10.1177/23743735221105671.
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\179\ Klemanski DH, Barnes T, Bautista C, Tancreti C, Klink B,
Dix E. Development and Validation of the Psychiatric Inpatient
Experience (PIX) Survey: A Novel Measure of Patient Experience
Quality Improvement. Journal of Patient Experience. 2022;9.
doi:10.1177/23743735221105671.
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(1) Measure Calculation
(a) Cohort
The cohort for this measure is all patients discharged from an IPF
during the reporting period who do not meet one of the following
exclusions: (1) patients who are under 13 years of age at time of
discharge, and (2) patients who are unable to complete the survey due
to cognitive or intellectual limitations. Our proposed sampling
procedures that IPFs could apply to the PIX survey measure are
described in section V.I.6 of the preamble of this proposed rule.
(b) Calculation
The measure would be reported as five separate rates, one for each
of the four domains of the PIX survey and one overall rate. Each of
these rates would be calculated from patient responses on the PIX
survey and then publicly reported on the Care Compare website (or
successor CMS website). We would report the mean rates for each domain
as well the overall mean rate on the Care Compare website (or successor
CMS website). To calculate the mean scores, we would assign a numerical
value ranging from 1 (Strongly Disagree) to 5 (Strongly Agree). We
would then calculate the average response by adding the values of all
responses and dividing that value by the number of responses, excluding
questions that were omitted or to which the patient selected ``Does Not
Apply.''
(2) Review by the Measure Applications Partnership (MAP)
We included the PIX survey measure on the publicly available ``List
of Measures Under Consideration for December 1, 2022'' (MUC List), a
list of measures under consideration for use in various Medicare
programs.\180\ The CBE-convened Measure Applications Partnership (MAP)
reviewed the MUC List and discussed the potential use of the PIX survey
for the IPFQR Program.
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\180\ Centers for Medicare & Medicaid Services. List of Measures
Under Consideration for December 1, 2022. Available at: https://mmshub.cms.gov/measure-lifecycle/measure-implementation/pre-rulemaking/lists-and-reports.
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The MAP Health Equity Advisory Group agreed that well-constructed
patient experience of care measures are an important indicator of
quality care. Overall, the MAP Health Equity Advisory Group expressed
that this measure is a ``step in the right direction for behavioral
health.'' \181\
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\181\ Centers for Medicare & Medicaid Services. 2022-2023 MAP
Final Recommendations. Available at: https://mmshub.cms.gov/measure-lifecycle/measure-implementation/pre-rulemaking/lists-and-reports.
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In addition, on December 8 through 9, 2022, the MAP Rural Health
Workgroup reviewed the 2022 MUC List and expressed support for this
measure, with patient support being especially strong. Some members of
the MAP Rural Health Advisory Group were concerned about operational
challenges, specifically costs related to implementation and
maintenance and potential bias if the surveying occurs prior to
discharge.\182\
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\182\ Centers for Medicare & Medicaid Services. 2022-2023 MAP
Final Recommendations. Available at: https://mmshub.cms.gov/measure-lifecycle/measure-implementation/pre-rulemaking/lists-and-reports.
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The MAP Hospital workgroup reviewed the 2022 MUC List on December
13 through 14, 2022. The MAP Hospital workgroup conditionally supported
the measure for rulemaking, while emphasizing the importance of
including patient reported experience of care data in the IPFQR
Program. The MAP Hospital workgroup's conditions for support included
endorsement by the CBE and additional testing data for this measure,
specifically: (1) data from testing of the measure in a variety of
settings (including urban, rural, safety net providers, and others),
(2) data regarding survey results depending on the timing of survey
administration (pre- versus post-discharge), (3) data regarding patient
factors (for example, voluntary versus involuntary admissions), and (4)
data regarding of mode of administration (for example, email versus
mail) that may affect performance.\183\ Thereafter, the MAP
Coordinating Committee deliberated on January 24 through 25, 2023 and
ultimately voted to uphold the Hospital Workgroup's recommendation to
conditionally support the PIX survey measure for rulemaking pending the
same conditions as the MAP Hospital workgroup.\184\
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\183\ Centers for Medicare & Medicaid Services. 2022-2023 MAP
Final Recommendations. Available at: https://mmshub.cms.gov/measure-lifecycle/measure-implementation/pre-rulemaking/lists-and-reports.
\184\ Centers for Medicare & Medicaid Services. 2022-2023 MAP
Final Recommendations. Available at: https://mmshub.cms.gov/measure-lifecycle/measure-implementation/pre-rulemaking/lists-and-reports.
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We believe that the testing that has been conducted on the PIX
survey demonstrates that it is a valid and reliable tool for measuring
patient experience of care in IPFs, and that the results from this
initial testing are generalizable across IPFs. However, we agree with
the MAP Hospital workgroup that additional testing of this measure
could help better understand measure results, including any differences
in measure results that were not analyzed during the PIX survey's
initial testing. Therefore, we intend to conduct additional testing of
the PIX survey prior to public reporting of the measure data, and we
are proposing two years of voluntary reporting before beginning
mandatory reporting of the PIX survey.
(3) CBE Endorsement
The measure developer has not submitted this measure for CBE
endorsement at this time. The developer does intend to submit this
measure for endorsement in the future, following additional testing as
recommended by the MAP Hospital workgroup. Although
[[Page 21290]]
section 1886(s)(4)(D)(i) of the Act generally requires that measures
specified by the Secretary shall be endorsed by the entity with a
contract under section 1890(a) of the Act, section 1886(s)(4)(D)(ii) of
the Act states that in the case of a specified area or medical topic
determined appropriate by the Secretary for which a feasible and
practical measure has not been endorsed by the entity with a contract
under section 1890(a) of the Act, the Secretary may specify a measure
that is not so endorsed as long as due consideration is given to a
measure that has been endorsed or adopted by a consensus organization
identified by the Secretary.
We reviewed CBE-endorsed measures and were unable to identify any
other CBE-endorsed measures on this topic. We did identify the
Experience of Care and Health Outcomes (ECHO) Survey measure (CBE
#008); however, this measure has had its endorsement removed as of the
spring 2020 cycle. Additionally, this survey was developed and tested
for outpatient behavioral health, not the inpatient setting.
Additionally, we identified the Patient Experience of Psychiatric Care
as Measured by the Inpatient Consumer Survey (ICS) measure (CBE #0726).
This measure has also had its endorsement removed as of the spring 2018
cycle. As neither of these two measures are endorsed at this time, we
believe the exception in section 1886(s)(4)(D)(ii) of the Act applies.
(c) Data Collection, Submission and Reporting
IPFs would be responsible for administering the survey and
collecting data on survey responses because the PIX survey is
administered beginning 24 hours prior to a patient's planned discharge.
Therefore, IPFs would collect the data in a manner similar to the
collection of data for chart-abstracted measures or other patient
screening measures. That is, the IPFs would collect data in the
facility and then report these data to CMS using the methods described
in section V.I.4 of this proposed rule, that is ``Data Submission
Requirements'' under ``Procedural Requirements.''
Because we anticipate that many IPFs, which already administer
different patient experience of care survey instruments to their
patients, would need to transition to the PIX survey, we are proposing
a voluntary reporting period beginning with data from CY 2025, which
would be reported to CMS in CY 2026. We would then require IPFs to
report data for the PIX survey measure beginning with data collected
during CY 2026, to be reported to CMS during CY 2027 and affect the FY
2028 payment determination.
We invite comments on our proposal.
E. Proposed Modification of the COVID-19 Vaccination Coverage Among
Healthcare Personnel (HCP) Measure Beginning With the Quarter 4 CY 2023
Reporting Period/FY 2025 Payment Determination
1. Background
On January 31, 2020, the Secretary of the Department of Health and
Human Services declared a public health emergency (PHE) for the United
States in response to the global outbreak of SARS-COV-2, a novel (new)
coronavirus that causes a disease named ``coronavirus disease 2019''
(COVID-19).\185\ Subsequently, multiple quality reporting programs
including the Hospital IQR Program (86 FR 45374) and the IPFQR Program
(86 FR 42633 through 42640) adopted the COVID-19 Vaccination Coverage
among Healthcare Personnel (HCP) measure. The COVID-19 Vaccination
Coverage Among Healthcare Personnel (HCP) measure adopted in the IPFQR
Program in the FY 2022 IPF PPS final rule (86 FR 42633 through 42650)
requires each IPF to calculate the percentage of HCP eligible to work
in the IPF for at least one day during the reporting period, excluding
persons with contraindications to the COVID-19 vaccine, who have
received a complete vaccination course against SARS-CoV-2 (86 FR 42633
through 42640).
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\185\ U.S. Dept of Health and Human Services, Office of the
Assistant Secretary for Preparedness and Response. (2020).
Determination that a Public Health Emergency Exists. Available at:
https://www.phe.gov/emergency/news/healthactions/phe/Pages/2019-nCoV.aspx.
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COVID-19 has continued to spread domestically and around the world
with more than 102.7 million cases and 1.1 million deaths in the United
States as of February 13, 2023.\186\ In recognition of the ongoing
significance and complexity of COVID-19, the Secretary has renewed the
PHE on April 21, 2020, July 23, 2020, October 2, 2020, January 7, 2021,
April 15, 2021, July 19, 2021, October 15, 2021, January 14, 2022,
April 12, 2022, July 15, 2022, October 13, 2022, January 11, and
February 9, 2023.\187\ The President has announced that the PHE will
end on May 11, 2023,\188\ and HHS has stated that the public health
response to COVID-19 remains a public health priority with a whole of
government approach to combatting the virus, including through
vaccination efforts.\189\
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\186\ Centers for Disease Control and Prevention. COVID Data
Tracker. Accessed February 13, 2023. Available at: https://covid.cdc.gov/covid-data-tracker/#datatracker-home.
\187\ U.S. Dept. of Health and Human Services. Office of the
Assistant Secretary for Preparedness and Response. (2023). Renewal
of Determination that a Public Health Emergency Exists. Available
at: https://aspr.hhs.gov/legal/PHE/Pages/covid19-11Jan23.aspx.
\188\ https://www.whitehouse.gov/wp-content/uploads/2023/01/SAP-H.R.-382-H.J.-Res.-7.pdf.
\189\ U.S. Dept. of Health and Human Services. Fact Sheet:
COVID-19 Public Health Emergency Transition Roadmap. February 9,
2023. Available at: https://www.hhs.gov/about/news/2023/02/09/fact-sheet-covid-19-public-health-emergency-transition-roadmap.html.
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In the FY 2022 IPF PPS final rule (86 FR 42633 through 42635) and
in our Revised Guidance for Staff Vaccination Requirements,\190\ we
stated that vaccination is a critical part of the nation's strategy to
effectively counter the spread of COVID-19. We continue to believe it
is important to incentivize and track HCP vaccination through quality
measurement across care settings, including IPFs, in order to protect
HCP, patients, and caregivers, and to help sustain the ability of HCP
to continue serving their communities throughout the PHE and beyond.
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\190\ Centers for Medicare & Medicaid Services. Revised Guidance
for Staff Vaccination Requirements QSO-23-02-ALL. October 26, 2022.
Available at: https://www.cms.gov/files/document/qs0-23-02-all.pdf.
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At the time we issued the FY 2022 IPF PPS final rule, the Food and
Drug Administration (FDA) had issued emergency use authorizations
(EUAs) for initial and primary adult vaccines manufactured by Pfizer-
BioNTech,\191\ Moderna,\192\ and Janssen.\193\ On August 23, 2021, the
FDA issued an approval for the Pfizer-BioNTech vaccine, now marketed as
Comirnaty.\194\ The FDA issued approval for the Moderna vaccine,
marketed as Spikevax, on
[[Page 21291]]
January 31, 2022 \195\ and an EUA for the Novavax adjuvanted vaccine on
July 13, 2022.\196\ The FDA also issued EUAs for COVID-19 single
vaccine booster doses in September 2021 \197\ and October 2021 \198\
for certain populations and in November 2021 \199\ for all individuals
18 years of age and older. EUAs were subsequently issued for a second
vaccine booster dose in March 2022 \200\ and for bivalent or
``updated'' booster doses in August 2022.\201\
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\191\ Food and Drug Administration. (December 2020). FDA Takes
Key Action in Fight Against COVID-19 By Issuing Emergency Use
Authorization for First COVID-19 Vaccine. Available at: https://www.fda.gov/news-events/press-announcements/fda-takes-key-action-fight-against-covid-19-issuing-emergency-use-authorization-first-covid-19.
\192\ Food and Drug Administration. (December 2020). FDA Takes
Additional Action in Fight Against COVID-19 By Issuing Emergency Use
Authorization for Second COVID-19 Vaccine. Available at: https://www.fda.gov/news-events/press-announcements/fda-takes-additional-action-fight-against-covid-19-issuing-emergency-use-authorization-second-covid.
\193\ Food and Drug Administration. (February 2021). FDA Issues
Emergency Use Authorization for Third COVID-19 Vaccine. Available
at: https://www.fda.gov/news-events/press-announcements/fda-issues-emergency-use-authorization-third-covid-19-vaccine.
\194\ Food and Drug Administration. (August 2021). FDA Approves
First COVID-19 Vaccine. Available at: https://www.fda.gov/news-events/press-announcements/fda-approves-first-covid-19-vaccine.
\195\ Food and Drug Administration. (January 2022). Coronavirus
(COVID-19) Update: FDA Takes Key Action by Approving Second COVID-19
Vaccine. Available at: https://www.fda.gov/news-events/press-announcements/coronavirus-covid-19-update-fda-takes-key-action-approving-second-covid-19-vaccine.
\196\ Food and Drug Administration. (July 2022). Coronavirus
(COVID-19) Update: FDA Authorizes Emergency Use of Novavax COVID-19
Vaccine, Adjuvanted. Available at: https://www.fda.gov/news-events/press-announcements/coronavirus-covid-19-update-fda-authorizes-emergency-use-novavax-covid-19-vaccine-adjuvanted.
\197\ Food and Drug Administration. (September 2021). FDA
Authorizes Booster Dose of Pfizer-BioNTech COVID-19 Vaccine for
Certain Populations. Available at: https://www.fda.gov/news-events/press-announcements/fda-authorizes-booster-dose-pfizer-biontech-covid-19-vaccine-certain-populations.
\198\ Food and Drug Administration. (October 2021). Coronavirus
(COVID-19) Update: FDA Takes Additional Actions on the Use of a
Booster Dose for COVID-19 Vaccines. Available at: https://www.fda.gov/news-events/press-announcements/coronavirus-covid-19-update-fda-takes-additional-actions-use-booster-dose-covid-19-vaccines.
\199\ Food and Drug Administration. (November 2021). Coronavirus
(COVID-19) Update: FDA Expands Eligibility for COVID-19 Vaccine
Boosters. Available at: https://www.fda.gov/news-events/press-announcements/coronavirus-covid-19-update-fda-expands-eligibility-covid-19-vaccine-boosters.
\200\ Food and Drug Administration. (March 2022). Coronavirus
(COVID-19) Update: FDA Authorizes Second Booster Dose of Two COVID-
19 Vaccines for Older and Immunocompromised Individuals. Available
at: https://www.fda.gov/news-events/press-announcements/coronavirus-covid-19-update-fda-authorizes-second-booster-dose-two-covid-19-vaccines-older-and.
\201\ Food and Drug Administration. (August 2022). Coronavirus
(COVID-19) Update: FDA Authorizes Moderna, Pfizer-BioNTech Bivalent
COVID-19 Vaccines for Use as a Booster Dose. Available at: https://www.fda.gov/news-events/press-announcements/coronavirus-covid-19-update-fda-authorizes-moderna-pfizer-biontech-bivalent-covid-19-vaccines-use.
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In the FY 2022 IPF PPS final rule, we stated that data
demonstrating the effectiveness of COVID-19 vaccines to prevent
asymptomatic infection or transmission of SARS-COV-2, the novel (new)
coronavirus that causes COVID-19, were limited (86 FR 42634). While the
impact of COVID-19 vaccines on asymptomatic infection and transmission
was not yet fully known at the time of the FY 2022 IPF PPS final rule,
there were robust data available on COVID-19 vaccine effectiveness
across multiple populations against symptomatic infection,
hospitalization, and death. Two-dose COVID-19 vaccines from Pfizer-
BioNTech and Moderna had been found to be 88 percent and 93 percent
effective against hospitalization for COVID-19, respectively, over 6
months for adults over age 18 without immunocompromising conditions.
\202\ During a SARS-COV-2 surge in the spring and summer of 2021, 92
percent of COVID-19 hospitalizations and 91 percent of COVID-19-
associated deaths were reported among persons not fully
vaccinated.\203\ Real-world studies of population-level vaccine
effectiveness indicated similarly high rates of effectiveness in
preventing SARS-COV-2 infection among frontline workers in multiple
industries, with a 90 percent effectiveness in preventing symptomatic
and asymptomatic infection from December 2020 through August 2021.\204\
Vaccines have also been highly effective in real-world conditions (that
is, vaccines have continued to be highly effective in conditions other
than clinical trials) at preventing COVID-19 in HCP with up to 96
percent effectiveness for fully vaccinated HCP, including those at risk
for severe infection and those in racial and ethnic groups
disproportionately affected by COVID-19.\205\ In the presence of high
community prevalence of COVID-19, residents of nursing homes with low
staff vaccination coverage had cases of COVID-19-related deaths 195
percent higher than those among residents of nursing homes with high
staff vaccination coverage.\206\ Currently available data demonstrate
that COVID-19 vaccines are effective and prevent severe disease,
including hospitalization, and death.
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\202\ Centers for Disease Control and Prevention. (September 24,
2021). Morbidity and Mortality Weekly Report (MMWR). Comparative
Effectiveness of Moderna, Pfizer-BioNTech, and Janssen (Johnson &
Johnson) Vaccines in Preventing COVID-19 Hospitalizations Among
Adults Without Immunocompromising Conditions--United States, March-
August 2021. Available at: https://cdc.gov/mmwr/volumes/70/wr/mm7038e1.htm?s_cid=mm7038e1_w.
\203\ Centers for Disease Control and Prevention. (September 10,
2021). Morbidity and Mortality Weekly Report (MMWR). Monitoring
Incidence of COVID-19 Cases, Hospitalizations, and Deaths, by
Vaccination Status--13 U.S. Jurisdictions, April 4-July 17, 2021.
Available at: https://cdc.gov.mmwr/volumes/70/wr/mm7037e1.htm?s_cid=mm7037e1_w.
\204\ Centers for Disease Control and Prevention. (August 27,
2021). Morbidity and Mortality Weekly Report (MMWR). Effectiveness
of COVID-19 Vaccines in Preventing SARS-COV-2 Infection Among
Frontline Workers Before and During B.1.617.2 (Delta) Variant
Predominance--Eight U.S. Locations, December 2020-August 2021.
Available at: https://cdc.gov/mmwr/volume/70/wr/mm7034e4.htm?s_cid=mm7034e4_w.
\205\ Pilishivi, T. et al. (December 2022). Effectiveness of
mRNA Covid-19 Vaccine among U.S. Health Care Personnel. New England
Journal of Medicine. 2021 Dec 16;385(25):e90. Available online at:
https://pubmed.ncbi.nlm.nih.gov/34551224/.
\206\ McGarry BE et al. (January 2022). Nursing Home Staff
Vaccination and Covid-19 Outcomes. New England Journal of Medicine.
2022 Jan 27;386(4):397-398. Available online at: https://pubmed.ncbi.nlm.nih.gov/34879189/.
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As SARS-COV-2 persists and evolves, our COVID-19 vaccination
strategy must remain responsive. When we adopted the COVID-19
Vaccination Coverage Among HCP measure in the FY 2022 IPF PPS final
rule, we stated that the need for booster doses of the COVID-19 vaccine
had not been established and no additional doses had been recommended
(86 FR 42639). We also stated that we believed the numerator was
sufficiently broad to include potential future boosters as part of a
``complete vaccination course'' and that the measure was sufficiently
specified to address boosters (86 FR 42639). Since we adopted the
COVID-19 Vaccination Coverage Among HCP measure in the FY 2022 IPF PPS
final rule, new variants of SARS-COV-2 have emerged around the world
and within the United States. Specifically, the Omicron variant (and
its related subvariants) is listed as a variant of concern by the
Centers for Disease Control and Prevention (CDC) because it spreads
more easily than earlier variants.\207\ Vaccine manufacturers have
responded to the Omicron variant by developing bivalent COVID-19
vaccines, which include a component of the original virus strain to
provide broad protection against COVID-19 and a component of the
Omicron variant to provide better protection against COVID-19 caused by
the Omicron variant.\208\ These booster doses of the bivalent COVID-19
vaccine have been shown to increase immune response to SARS-COV-2
variants, including Omicron, particularly in individuals who are more
than 6 months removed from receipt of their primary series.\209\ The
FDA issued EUAs for two bivalent COVID-19 vaccine booster doses, one
from Pfizer-BioNTech \210\ and one from
[[Page 21292]]
Moderna,\211\ and strongly encourages anyone who is eligible to
consider receiving a booster dose with a bivalent COVID-19 vaccine to
provide better protection against currently circulating variants.\212\
COVID-19 booster doses are associated with a greater reduction in
infections among HCP and their patients relative to those who only
received primary series vaccination. One study showed a rate of
breakthrough infections among HCP who received only the two-dose
regimen of the COVID-19 vaccine of 21.4 percent compared to a rate of
0.7 percent among HCP who received a third dose of the COVID-19
vaccine.\213\
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\207\ Centers for Disease Control and Prevention. (August 2021).
Variants of the Virus. Available at: https://www.cdc.gov/coronavirus/2019-ncov/variants/.
\208\ Food and Drug Administration. (November 2022). COVID-19
Bivalent Vaccine Boosters.
\209\ Chalkias, S et al. (October 2022). A Bivalent Omicron-
Containing Booster Vaccine against Covid-19. N Engl J Med 2022;
387:1279-1291. Available online at: https://www.nejm.org/doi/full/10.1056/NEJMoa2208343.
\210\ Food and Drug Administration. (November 2022). Pfizer-
BioNTech COVID-19 Vaccines. Available at: https://www.fda.gov/emergency-preparedness-and-response/coronavirus-disease-2019-Covid-19/pfizer-biontech-covid-19-vaccines.
\211\ Food and Drug Administration. (November 2022). Moderna
COVID-19 Vaccines. Available at: https://www.fda.gov/emergency-preparedness-and-response/coronavirus-disease-2019-covid-19/moderna-covid-19-vaccines.
\212\ Food and Drug Administration. (August 2022). Coronavirus
(COVID-19) Update: FDA Authorizes Moderna, Pfizer-BioNTech Bivalent
COVID-19 Vaccines for Use as a Booster Dose. Available at: https://www.fda.gov/news-events/press-announcements/coronavirus-covid-19-update-fda-authorizes-moderna-pfizer-biontech-bivalent-covid-19-vaccines-use.
\213\ Oster Y et al. (May 2022). The effect of a third BNT162b2
vaccine on breakthrough infections in health care workers: a cohort
analysis. Clin Microbiol Infect. 2022 May;28(5):735.e1-735.e3.
Available online at: https://pubmed.ncbi.nlm.nih.gov/35143997/.
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Despite the efficacy of COVID-19 vaccination generally, data
submitted to the CDC via the National Health Safety Network (NHSN)
demonstrate clinically significant variation in booster dose
vaccination rates across facilities, including IPFs. During the first
quarter of 2022, IPFs reported a median coverage rate of booster or
additional dose(s) of 19.1 percent, with an interquartile range of 8.7
percent to 37.9 percent. These data, which show a performance gap in
booster coverage, indicate that there is opportunity to improve booster
vaccination coverage among HCP in IPFs.\214\
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\214\ Measure Applications Partnership (MAP) Hospital Workgroup
Preliminary Analyses. Available at: https://mmshub.cms.gov/sites/default/files/map-hospital-measure-specifications-manual-2022.pdf.
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We believe that vaccination remains the most effective means to
prevent the worst consequences of COVID-19, including severe illness,
hospitalization, and death. Given the availability of vaccine efficacy
data, EUAs issued by the FDA for bivalent boosters, the continued
presence of SARS-COV-2 in the United States, and variance among rates
of booster dose vaccination, it is important to modify the COVID-19
Vaccination Coverage Among HCP measure to reflect recent guidance that
explicitly specifies for HCP to receive primary series and booster
vaccine doses in a timely manner. Given the persistent spread of COVID-
19, we continue to believe that monitoring and surveillance is
important and provides patients, beneficiaries, and their caregivers
with information to support informed decision-making.
Beginning with the fourth quarter of the CY 2023 reporting period/
FY 2025 payment determination, we propose to modify the COVID-19
Vaccination Coverage Among HCP measure to replace the term ``complete
vaccination course'' with the term ``up-to-date'' in the HCP
vaccination definition. We also propose to update the numerator to
specify the time frames within which an HCP is considered ``up-to-
date'' with recommended COVID-19 vaccines, including booster doses.
In the FY 2022 IPF PPS final rule (86 FR 42638), we stated, and
reiterate now, that the COVID-19 Vaccination Coverage Among HCP measure
is a process measure that assesses HCP vaccination coverage rates.
Unlike outcome measures, process measures do not assess a particular
outcome.
2. Overview of Measure
The proposed COVID-19 Vaccination Coverage Among HCP measure is a
process measure developed by the CDC to track COVID-19 vaccination
coverage among HCP in settings such as acute care facilities, including
IPFs, and post-acute care facilities.
We refer readers to the FY 2022 IPF PPS final rule (86 FR 42635
through 42636) for more information on the initial review of the
current COVID-19 Vaccination Coverage Among HCP measure by the Measure
Applications Partnership (MAP). We included an updated version of the
proposed modification of the COVID-19 Vaccination Coverage Among HCP
measure on the list of measures under consideration (MUC List), which
is published annually on behalf of CMS by the CBE with which the
Secretary must contract as required by section 1890(a) of the Act, for
the 2022 to 2023 pre-rulemaking cycle for consideration by the MAP.
In December 2022, the MAP Hospital Workgroup discussed the proposed
modification of the COVID-19 Vaccination Coverage Among HCP measure.
The MAP Hospital Workgroup stated that the proposed modification of the
current measure captures ``up-to-date'' vaccination information in
accordance with the CDC's recommendations, which have been updated
since their initial development. Additionally, the MAP Hospital
Workgroup appreciated that the proposed modified measure's denominator
is broader and simplified from seven categories of healthcare personnel
to four.\215\
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\215\ Centers for Medicare & Medicaid Services. 2022-2023 MAP
Final Recommendations. Available at: https://mmshub.cms.gov/measure-lifecycle/measure-implementation/pre-rulemaking/lists-and-reports.
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During review on December 6 and 7, 2022, the MAP Health Equity
Advisory Group highlighted the importance of COVID-19 measures and
asked whether the proposed modified measure excludes individuals with
contraindications to Food and Drug Administration (FDA) authorized or
approved COVID-19 vaccines, and whether the measure will be stratified
by demographic factors.\216\ The CDC, the measure developer for this
measure, responded to the question regarding individuals with
contraindications by confirming that HCP with contraindications to the
vaccines are excluded from the measure denominator. The CDC further
explained that the proposed modified measure will not be stratified
since the data are submitted at an aggregate rather than an individual
level.
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\216\ Centers for Medicare & Medicaid Services. 2022-2023 MAP
Final Recommendations. Available at: https://mmshub.cms.gov/measure-lifecycle/measure-implementation/pre-rulemaking/lists-and-reports.
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During review on December 8 through 9, 2022, the MAP Rural Health
Advisory Group expressed concerns about data collection burden, citing
that collection is performed manually and that small rural hospitals
may not have employee health software.\217\ The measure developer (that
is, the CDC) acknowledged the challenge of getting adequate
documentation and emphasized the goal to ensure the measure does not
present a burden on providers. The measure developer also noted that
the model used for this measure is based on the Influenza Vaccination
Coverage Among HCP measure (CBE #0431), and it intends to utilize a
similar approach to the modified COVID-19 Vaccination Coverage Among
HCP measure if vaccination strategy becomes seasonal. The proposed
modified COVID-19 Vaccination Coverage Among HCP measure received
conditional support for rulemaking pending testing indicating the
measure is reliable and valid, and endorsement by the CBE. The MAP
noted that the previous version of
[[Page 21293]]
the measure received endorsement from the CBE (CBE #3636) \218\ and
that the CDC intends to submit the proposed updated measure for
endorsement.
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\217\ Centers for Medicare & Medicaid Services. 2022-2023 MAP
Final Recommendations. Available at: https://mmshub.cms.gov/measure-lifecycle/measure-implementation/pre-rulemaking/lists-and-reports.
\218\ Centers for Medicare & Medicaid Services. 2022-2023 MAP
Final Recommendations. Available at: https://mmshub.cms.gov/measure-lifecycle/measure-implementation/pre-rulemaking/lists-and-reports.
and CMS Measures Inventory Tool. Available at: https://cmit.cms.gov/cmit/#/MeasureView?variantId=5273§ionNumber=1.
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a. Measure Specifications
The proposed modification of the COVID-19 Vaccination Coverage
Among HCP measure would require that IPFs collect data at least one
week each month for each of the three months in a quarter.
The denominator would be the number of HCP eligible to work in the
facility for at least one day during the reporting period, excluding
persons with contraindications to COVID-19 vaccination that are
described by the CDC.\219\ There are not any proposed changes to the
denominator exclusions for the current COVID-19 Vaccination Coverage
Among HCP measure, and the proposed modified COVID-19 Vaccination
Coverage Among HCP measure would continue to exclude otherwise
denominator-eligible HCPs with contraindications as defined by the
CDC.\220\ IPFs report the following four categories of HCP to NHSN;
\221\ the first three categories are included in the measure
denominator:
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\219\ Centers for Disease Control and Prevention. (2022).
Contraindications and precautions. Available at: https://www.cdc.gov/vaccines/covid-19/clinical-considerations/interim-considerations-us.html#contraindications.
\220\ Centers for Disease Control and Prevention. (2022).
Contraindications and precautions. Available at: https://www.cdc.gov/vaccines/covid-19/clinical-considerations/interim-considerations-us.html#contraindications.
\221\ https://www.cdc.gov/nhsn/pdfs/nqf/covid-vax-hcpcoverage-rev-2023-508.pdf.
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1. Employees: This category includes all persons who receive a
direct paycheck from the IPF (that is, on the IPF's payroll),
regardless of clinical responsibility or patient contact.
2. Licensed independent practitioners (LIPs): This category
includes physicians (MD, DO), advanced practice nurses, and physician
assistants who are affiliated with the IPF but are not directly
employed by it (that is, they do not receive a paycheck from the IPF),
regardless of clinical responsibility or patient contact. Post-
residency fellows are also included in this category if they are not on
the IPF's payroll.
3. Adult students/trainees and volunteers: This category includes
medical, nursing, or other health professional students, interns,
medical residents, or volunteers aged 18 or older who are affiliated
with the healthcare facility, but are not directly employed by it (that
is, they do not receive a paycheck from the facility), regardless of
clinical responsibility or patient contact.
4. Other contract personnel: Contract personnel are defined as
persons providing care, treatment, or services at the IPF through a
contract who do not fall into any of the previously discussed
denominator categories. Please note that this also includes vendors
providing care, treatment, or services at the facility who may or may
not be paid through a contract. Facilities are required to enter data
on other contract personnel for submission in the NHSN application, but
reporting for this category is not included in the COVID-19 Vaccination
Coverage Among HCP measure.
The numerator would be the cumulative number of HCP in the
denominator population who are ``up-to-date'' with CDC recommended
COVID-19 vaccines. IPFs should refer to the CDC's guidance, to
determine the then-applicable definition of ``up-to-date,'' as of the
first day of the applicable reporting quarter. The CDC's guidance can
be found at: https://www.cdc.gov/nhsn/pdfs/hps/covidvax/UpToDateGuidance-508.pdf. For purposes of NHSN surveillance, the CDC
used the following definition of ``up-to-date'' during the fourth
quarter of CY 2022 surveillance period (September 26, 2022 through
December 25, 2022):
1. Individuals who received an updated bivalent \222\ booster dose,
or
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\222\ The updated (bivalent) Moderna and Pfizer-BioNTech
boosters target the most recent Omicron subvariants. The updated
(bivalent) boosters were recommended by the CDC on 9/2/2022. As of
this date, the original, monovalent mRNA vaccines are no longer
authorized as a booster dose for people ages 12 years and older.
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2a. Individuals who received their last booster dose less than 2
months ago, or
2b. Individuals who completed their primary series \223\ less than
2 months ago.
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\223\ Completing a primary series means receiving a two-dose
series of a COVID-19 vaccine or a single dose of Janssen/J&J COVID-
19 vaccine.
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We refer readers to https://www.cdc.gov/nhsn/nqf/ for
more details on the proposed modified measure specifications.
We propose that public reporting of the modified version of the
COVID-19 Vaccination Coverage Among HCP measure would begin with the
October 2024 Care Compare refresh, or as soon as technically feasible
after that refresh.
b. CBE Endorsement
The current version of the COVID-19 Vaccination Coverage Among HCP
measure received CBE endorsement (CBE #3636, ``Quarterly Reporting of
COVID-19 Vaccination Coverage among Healthcare Personnel'') on July 26,
2022.\224\
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\224\ CMS Measures Inventor Tool. COVDI-19 Vaccination Coverage
among Healthcare Personnel. Available at: https://cmit.cms.gov/cmit/#/MeasureView?variantId=5273§ionNumber=1.
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Although section 1886(s)(4)(D)(i) of the Act generally requires
that measures specified by the Secretary shall be endorsed by the
entity with a contract under section 1890(a) of the Act, section
1886(s)(4)(D)(ii) of the Act states that in the case of a specified
area or medical topic determined appropriate by the Secretary for which
a feasible and practical measure has not been endorsed by the entity
with a contract under section 1890(a) of the Act, the Secretary may
specify a measure that is not so endorsed as long as due consideration
is given to a measure that has been endorsed or adopted by a consensus
organization identified by the Secretary.
We reviewed CBE-endorsed measures and were unable to identify any
other CBE-endorsed measures on this topic; therefore, we believe the
exception in section 1886(s)(4)(D)(ii) of the Act applies. The CDC, as
the measure developer, is currently pursuing endorsement for the
modified version of the measure as the current version of the measure
has already received endorsement.
3. Data Collection, Submission, and Reporting
We refer readers to the FY 2022 IPF PPS final rule (86 FR 42636
through 42640) for information on data submission and reporting of the
current COVID-19 Vaccination Coverage Among HCP measure. While we do
not propose any changes to the data submission or reporting process, we
propose that reporting of the updated measure would begin with the
fourth quarter of CY 2023 reporting period for FY 2025 payment
determination. Beginning with the FY 2026 payment determination, we
propose that IPFs would be required to submit data for the entire
calendar year.
Under the data submission and reporting process, IPFs would collect
the numerator and denominator for the COVID-19 Vaccination Coverage
Among HCP measure for at least one self-selected week during each month
of the reporting quarter and submit the data to the CDC's National
Health Safety Network (NHSN) Healthcare Personal Safety (HPS) Component
before the quarterly deadline. If an IPF submits more than one week of
data in a month, the CDC would use most recent week's
[[Page 21294]]
data to calculate the measure results which would be publicly reported.
Each quarter, the CDC would calculate a single quarterly COVID-19 HCP
vaccination coverage rate for each IPF, which would be calculated by
taking the average of the data from the three weekly rates submitted by
the IPF for that quarter. CMS would publicly report each quarterly
COVID-19 HCP vaccination coverage rate as calculated by the CDC based
on the data IPFs submit to the NHSN (86 FR 42636 through 42640).
We invite public comment on this proposal.
F. Removal or Retention of IPFQR Program Measures
1. Background
In the FY 2018 IPPS/LTCH PPS final rule (82 FR 38463 through 38465)
and FY 2019 IPF PPS final rule (83 FR 38591 through 38593), we adopted
several considerations for removing or retaining measures within the
IPFQR Program.
Specifically, we have adopted eight factors that we consider when
evaluating whether to propose a measure for removal from the IPFQR
Program. These factors are: (1) measure performance among IPFs is so
high and unvarying that meaningful distinctions and improvements in
performance can no longer be made (``topped out'' measures); (2)
measure does not align with current clinical guidelines or practice;
(3) measure can be replaced by a more broadly applicable measure
(across setting or populations) or a measure that is more proximal in
time to desired patient outcomes for the particular topic; (4) measure
performance or improvement does not result in better patient outcomes;
(5) measure can be replaced by a measure more strongly associated with
desired patient outcomes for the particular topic; (6) measure
collection or public reporting leads to negative intended consequences
other than patient harm; (7) measure is not feasible to implement as
specified; and (8) the costs associated with a measure outweigh the
benefit of its continued use in the program. For measure removal factor
one, we specified that a measure is ``topped out'' if it meets the
following criteria: (1) statistically indistinguishable performance at
the 75th and 90th percentiles; and (2) the truncated coefficient of
variation is less than or equal to 0.10.
We also adopted three factors for consideration in determining
whether to retain a measure in the IPFQR Program, even if the measure
meets one or more factors for removal. These retention factors are: (1)
measure aligns with other CMS and HHS policy goals, such as those
delineated in the National Quality Strategy and CMS Quality Strategy;
(2) measure aligns with other CMS programs, including other quality
reporting programs; and (3) measure supports efforts to move IPFs
towards reporting electronic measures. In the FY 2018 IPPS/LTCH PPS
final rule (82 FR 38464), we stated that these removal and retention
factors are considerations that we take into account in balancing the
benefits and drawbacks of removing or retaining measures on a case-by-
case basis.
Since adoption, we have not proposed any changes to these policies
for removal or retention and refer readers to the FY 2018 IPPS/LTCH PPS
final rule (82 FR 38463 through 38465) and the FY 2019 IPF PPS final
rule (83 FR 38591 through 38593) for more information. We do not
propose any updates to these measure retention and removal policies. We
propose to codify these previously adopted policies at Sec.
412.433(e).
We welcome comments on this proposal.
2. Proposed Measures for Removal
We continue to evaluate our measure set against these removal and
retention factors on an ongoing basis. In this continual evaluation of
the IPFQR Program measure set under our Meaningful Measures Framework
and according to our measure removal and retention factors, we
identified two measures that we believe are appropriate to propose
removing from the IPFQR Program beginning with the FY 2025 payment
determination. Our discussion of these measures follows.
a. Proposed Removal of the Patients Discharged on Multiple
Antipsychotic Medications With Appropriate Justification (HBIPS-5)
(Previously Endorsed Under CBE #0560) Measure Beginning With FY 2025
Payment Determination
As we assessed our existing measure set to ensure that it remains
appropriate for the IPFQR Program, we determined that measure removal
factor two (that is, measure does not align with current clinical
guidelines or practice) applies to the Patients Discharged on Multiple
Antipsychotic Medications with Appropriate Justification (HBIPS-5) (CBE
#560) measure due to the American Psychiatric Association's (APA's)
updated guidelines for patients with schizophrenia.
We adopted the HBIPS-5 measure in the FY 2013 IPPS/LTCH PPS final
rule as part of a set with the Patients Discharged on Multiple
Antipsychotic Medications (HBIPS-4) (previously endorsed under CBE
#0552) measure because of the belief that these two measures would help
reduce unnecessary use of multiple antipsychotics, which would lead to
better clinical outcomes and reduced side effects for patients (77 FR
53649 through 53650). We subsequently removed the HBIPS-4 measure in
the FY 2016 IPF PPS final rule (80 FR 46695 through 46696). As we
described in that final rule, following our adoption of these measures,
some experts, including the CBE, provided input that the HBIPS-4
measure did not provide meaningful information about the quality of
care received by IPF patients. This led to the removal of the HBIPS-4
measure's CBE endorsement in January 2014. During the CBE's review of
the HBIPS-4 measure in 2014, the CBE observed that the HBIPS-4 and
HBIPS-5 measures could be collected and reported separately and
expressed that the HBIPS-5 measure should be retained in the IPFQR
Program as it continued to provide meaningful quality of care
information (80 FR 046695 through 46696).
Evidence supporting development and adoption of the HBIPS-5 measure
included the APA Workgroup on Schizophrenia's 2004 Practice Guideline
for the Treatment of Patients with Schizophrenia. These guidelines
stated that the ``combinations of antipsychotics . . . should be
justified by strong documentation that the patient is not equally
benefited by monotherapy.'' \225\ In December 2019, the APA Board of
Trustees approved updated guidelines for treatment of patients with
schizophrenia.\226\ The updated guidelines are based on evolving
clinical knowledge and have increased focus and specificity of
recommendations for the use of pharmacotherapy; they also underscore
the importance of patient preference and shared-decision making.\227\
These guidelines no longer contain the recommendation that combinations
of antipsychotics should be justified by strong documentation that
patients are not equally benefited by monotherapy. Therefore, the
guidelines that originally supported the HBIPS-5 measure have changed
substantially, and the HBIPS-
[[Page 21295]]
5 measure is no longer aligned with current clinical guidelines and
practice.
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\225\ https://www.researchgate.net/publication/298561608_Practice_guideline_for_the_treatment_of_patients_with_schizophrenia_second_edition.
\226\ https://ajp.psychiatryonline.org/doi/10.1176/appi.ajp.2020.177901.
\227\ The American Psychiatric Association. Practice Guideline
for the Treatment of Patients with Schizophrenia, Third Edition.
Available at: https://psychiatryonline.org/doi/book/10.1176/appi.books.9780890424841. Accessed on February 15, 2023.
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Furthermore, the HBIPS-5 measure is no longer supported by the
measure steward (that is, The Joint Commission), who withdrew it from
the CBE endorsement process in 2019. As a result, the HBIPS-5 measure
lost its CBE endorsement in October 2019.\228\ Subsequent to this, the
CBE-convened MAP's discussion of measure set removal for 2021-2022
included a discussion of this measure. Because the HBIPS-5 measure no
longer aligns with clinical guidelines and is no longer CBE endorsed
due to lack of support from the measure developer, the MAP recommended
that the measure should be removed from the IPFQR Program.\229\
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\228\ CMS Measures Inventory Tool. Patients Discharged on
multiple antipsychotic medications with appropriate justification.
Available at: https://cmit.cms.gov/cmit/#/MeasureView?variantId=1141§ionNumber=1.
\229\ MAP 2021-2022 Considerations for Implementing Measures in
Federal Programs. Available at: https://mmshub.cms.gov/sites/default/files/map_2021-2022_considerations_for_implementing_measures_in_federal_programs_final_report.pdf.
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We agree with the MAP's assessment that the measure no longer
aligns with clinical guidelines and therefore propose to remove the
measure from the IPFQR Program beginning with FY 2025 payment
determination. We note that data for the FY 2024 payment determination
represents care provided in CY 2022 and will be reported to CMS prior
to the publication of the FY 2024 IPF PPS final rule; therefore, the FY
2025 payment determination is the first period for which we can remove
this measure.
We invite comments on our proposal.
b. Proposed Removal of the Tobacco Use Brief Intervention Provided or
Offered and Tobacco Use Brief Intervention (TOB-2/2a) for FY 2025 and
Subsequent Years
We adopted the Tobacco Use Brief Intervention Provided or Offered
and Tobacco Use Brief Intervention (TOB-2/2a) measure in the FY 2015
IPF PPS final rule (79 FR 45971 through 45972) because of our belief
that it is important to address the common comorbidity of tobacco use
among IPF patients. The TOB-2/2a measure requires IPFs to chart-
abstract measure data on a sample of IPF patient records, in accordance
with established sampling policies (80 FR 46717 through 46719). When we
introduced the TOB-2/2a measure to the IPFQR Program, the benefits of
this measure were high because IPF performance was not consistent with
respect to, and there were no other measures addressing, provision of
tobacco use cessation counseling or treatment. At the time, the TOB-2/
2a measure provided a means of distinguishing IPF performance
regarding, and incentivized facilities to improve rates of, treatment
for this common comorbidity. To further address tobacco use, we
subsequently adopted the Tobacco Use Treatment Provided or Offered at
Discharge and Tobacco Use Treatment at Discharge (TOB-3/3a) measure in
the FY 2016 IPF PPS final rule (80 FR 46696 through 46699).
In the FY 2022 IPF PPS proposed rule, we proposed to remove the
Tobacco Use Brief Intervention Provided or Offered and Tobacco Use
Brief Intervention (TOB-2/2a) measure from the IPFQR Program beginning
with the FY 2024 payment determination under our measure removal factor
8, the costs associated with a measure outweigh the benefit of its
continued use in the program (86 FR 19508 through 19509). We expressed
our belief that the quality improvement benefits from the TOB-2/2a
measure had greatly diminished because performance had leveled off,
that is overall performance on the measure was no longer improving. We
took this to mean that most IPFs routinely offer tobacco use brief
interventions.
In the FY 2022 IPF PPS proposed rule, we also expressed our belief
that the costs of maintaining this measure are high because costs are
multi-faceted and include not only the IPFs' burden associated with
reporting, but also our costs associated with implementing and
maintaining the measure (86 FR 19508 through 19509). Additionally, we
must expend resources in maintaining information collection systems,
analyzing reported data, and providing public reporting of the
collected information. We expressed that, for this measure, IPF
information collection burden and related costs associated with
reporting this measure to CMS were high because the measure is a chart-
abstracted measure. Furthermore, we observed CMS incurs costs
associated with the program oversight of the measure for public
display.
However, in the FY 2022 IPF PPS final rule, we did not finalize our
proposal to remove the Tobacco Use Brief Intervention Provided or
Offered and Tobacco Use Brief Intervention (TOB-2/2a) measure (86 FR
42648 through 42651). We stated that, following review of the public
comments we received, we believed the benefits of continuing to
encourage facilities to offer tobacco use brief interventions were
greater than we had estimated. We noted that these benefits included
the potential for IPFs to continue improving performance on the TOB-2/
2a measure, the importance of tobacco use interventions due to
increased tobacco use during the COVID-19 pandemic, and this measure's
potential influence on other quality improvement activities related to
tobacco use.
In our continual evaluation of the IPFQR Program measure set under
our Meaningful Measures Framework and according to our measure removal
and retention factors, we observed that having two measures addressing
tobacco use, which are both associated with relatively high information
collection burden, may not appropriately balance costs and benefits
within the program. While we believe that both the TOB-2/2a measure and
the TOB-3/3a measure address clinically important interventions to
address smoking in this population, we believe that the overall cost
associated with retaining both of these measures outweighs the benefit
of having two measures to address treatment for the same comorbidity
among the same patient population.
Both measures capture information about tobacco cessation
counseling and FDA-approved tobacco cessation medications. The
difference between the measures is that the TOB-2/2a measure captures
whether the tobacco cessation counseling and FDA-approved tobacco
cessation medications were offered or refused during the inpatient
stay, while the TOB-3/3a measure captures whether a referral to
outpatient tobacco cessation counseling and FDA-approved tobacco
cessation medications were offered or refused at the time of the
patient's discharge.
As we considered each of these measures, we determined that it
would be more appropriate to retain the TOB-3/3a measure in the IPFQR
Program, that is, to propose to remove the TOB-2/2a measure instead of
the TOB-3/3a measure, because there is more opportunity for improvement
on the TOB-3/3a measure. Specifically, the performance on the TOB-3/3a
measure is lower than performance on the TOB-2/2a measure. National
performance on TOB-2 and 2a measure and TOB-3 and 3a measure for the
last five payment determination years in the IPFQR Program is presented
in Table 19. Given the relatively high performance on the TOB-2/2a
measure compared to the TOB-3/3a measure, we believe that retaining the
TOB-3/3a measure, and
[[Page 21296]]
removing the TOB-2/2a measure, would provide more opportunity to drive
improvement among IPFs; therefore, would potentially impact more
patients.
Table 19--National Performance on TOB-2 and TOB-2A and TOB-3 and TOB-3A From CY 2017 Through CY 2022
----------------------------------------------------------------------------------------------------------------
TOB-2 TOB-2a TOB-3 TOB-3a
Payment determination year performance performance performance performance
(%) (%) (%) (%)
----------------------------------------------------------------------------------------------------------------
FY 2019......................................... 79.7 44.9 54.1 15.0
FY 2020......................................... 81.0 46.2 57.5 17.8
FY 2021......................................... 82.0 46.8 59.9 21.6
FY 2022......................................... 80.4 44.9 60.7 21.7
FY 2023......................................... 72.2 39.0 57.4 18.3
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As described earlier in this section V.F.2.b of this proposed rule,
because the TOB-2/2a measure has a high cost (especially due to its
high information collection burden), we believe that these high costs
are no longer greater than the benefits of retaining this measure.
Therefore, we believe measure removal factor 8 (that is, the costs
associated with a measure outweigh the benefit of its continued use in
the IPFQR Program), applies to the TOB-2/2a measure.
Furthermore, the TOB-2/2a measure is no longer supported by the
measure steward (that is, the Joint Commission), who withdrew it from
the CBE endorsement process in 2018. Therefore, the TOB-2/2a measure
has not been CBE endorsed since October 2018.\230\ Subsequent to this,
the CBE-convened MAP's discussion of measure set removal for 2021and
2022 included a discussion of this measure. Because the TOB-2/2a
measure is a high-cost measure and is no longer CBE endorsed, the MAP
recommended that we remove the measure from the IPFQR Program.\231\
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\230\ CMS Measures Inventory Tool. Tobacco Use Treatment
Provided or Offered. Available at: https://cmit.cms.gov/cmit/#/MeasureView?variantId=1818§ionNumber=1.
\231\ MAP 2021-2022 Considerations for Implementing Measures in
Federal Programs. Available at: https://mmshub.cms.gov/sites/default/files/map_2021-2022_considerations_for_implementing_measures_in_federal_programs_final_report.pdf.
---------------------------------------------------------------------------
We agree with the MAP that this is a high-cost measure.
Furthermore, we recognize that it is similar to the other tobacco use
measure in the IPFQR Program measure set (that is, the TOB-3/3a
measure) which we do not propose to remove. Therefore, we propose to
remove Tobacco Use Brief Intervention Provided or Offered and Tobacco
Use Brief Intervention (TOB-2/2a) measure under our measure removal
factor 8, ``the costs associated with a measure outweigh the benefit of
its continued use in the program,'' beginning with FY 2025 payment
determination. We note that data for the FY 2024 payment determination
represents care provided in CY 2022 and will be reported to CMS prior
to the publication of the FY 2024 IPF PPS final rule; therefore, the FY
2025 payment determination is the first period for which we can remove
this measure.
We welcome public comment on this proposal.
G. Summary of IPFQR Program Measures
1. IPFQR Program Measures for the FY 2024 Payment Determination
We do not propose any changes to our measure set for the FY 2024
payment determination. The 14 measures which will be in the program for
FY 2024 payment determination are shown in Table 20.
Table 20--IPFQR Program Measure Set for the FY 2024 Payment Determination
----------------------------------------------------------------------------------------------------------------
CBE No. Measure ID Measure
----------------------------------------------------------------------------------------------------------------
0640......................... HBIPS-2....................................... Hours of Physical Restraint Use.
0641......................... HBIPS-3....................................... Hours of Seclusion Use.
0560 *....................... HBIPS-5....................................... Patients Discharged on Multiple
Antipsychotic Medications with
Appropriate Justification.
N/A.......................... FAPH.......................................... Follow-Up After Psychiatric
Hospitalization.
N/A *........................ SUB-2 and SUB-2a.............................. Alcohol Use Brief Intervention
Provided or Offered and SUB-2a
Alcohol Use Brief Intervention.
N/A *........................ SUB-3 and SUB-3a.............................. Alcohol and Other Drug Use
Disorder Treatment Provided or
Offered at Discharge and SUB-3a
Alcohol and Other Drug Use
Disorder Treatment at Discharge.
N/A *........................ TOB-2 and TOB-2a.............................. Tobacco Use Treatment Provided or
Offered and TOB-2a Tobacco Use
Treatment.
N/A *........................ TOB-3 and TOB-3a.............................. Tobacco Use Treatment Provided or
Offered at Discharge and TOB-3a
Tobacco Use Treatment at
Discharge.
1659......................... IMM-2......................................... Influenza Immunization.
N/A *........................ N/A........................................... Transition Record with Specified
Elements Received by Discharged
Patients (Discharges from an
Inpatient Facility to Home/Self
Care or Any Other Site of Care).
N/A.......................... N/A........................................... Screening for Metabolic
Disorders.
2860......................... N/A........................................... Thirty-Day All-Cause Unplanned
Readmission Following
Psychiatric Hospitalization in
an Inpatient Psychiatric
Facility.
3205......................... Med Cont...................................... Medication Continuation Following
Inpatient Psychiatric Discharge.
[[Page 21297]]
3636......................... N/A........................................... COVID-19 Healthcare Personnel
(HCP) Vaccination Measure.
----------------------------------------------------------------------------------------------------------------
* Measure is no longer endorsed by the CBE but was endorsed at the time of adoption. We note that although
section 1886(s)(4)(D)(i) of the Act generally requires measures specified by the Secretary be endorsed by the
entity with a contract under section be endorsed by the entity with a contract under section 1890(a) of the
Act, section 1886(s)(4)(D)(ii) states that in the case of a specified area or medical topic determined
appropriate by the Secretary for which a feasible and practical measure has not been endorsed by the entity
with a contract under section 1890(a) of the Act, the Secretary may specify a measure that is not so endorsed
as long as due consideration is given to measures that have been endorsed or adopted by a consensus
organization identified by the Secretary. We attempted to find available measures for each of these clinical
topics that have been endorsed or adopted by a consensus organization and found no other feasible and
practical measures on the topics for the IPF setting.
2. IPFQR Program Measures for the FY 2025 Payment Determination
In this proposed rule, we propose to remove two measures for the FY
2025 payment determination and subsequent years. We also propose to
modify one measure for the FY 2025 payment determination and subsequent
years. The 12 measures, which would be in the program for FY 2025
payment determination if we finalize these proposals, are shown Table
21.
Table 21--IPFQR Program Measure Set for the FY 2025 Payment Determination if Proposals To Modify and Remove
Measures Are Finalized
----------------------------------------------------------------------------------------------------------------
CBE No. Measure ID Measure
----------------------------------------------------------------------------------------------------------------
0640......................... HBIPS-2....................................... Hours of Physical Restraint Use.
0641......................... HBIPS-3....................................... Hours of Seclusion Use.
N/A.......................... FAPH.......................................... Follow-Up After Psychiatric
Hospitalization.
1659......................... IMM-2......................................... Influenza Immunization.
N/A *........................ SUB-2 and SUB-2a.............................. Alcohol Use Brief Intervention
Provided or Offered and SUB-2a
Alcohol Use Brief Intervention.
N/A *........................ SUB-3 and SUB-3a.............................. Alcohol and Other Drug Use
Disorder Treatment Provided or
Offered at Discharge and SUB-3a
Alcohol and Other Drug Use
Disorder Treatment at Discharge.
N/A *........................ TOB-3 and TOB-3a.............................. Tobacco Use Treatment Provided or
Offered at Discharge and TOB-3a
Tobacco Use Treatment at
Discharge.
N/A *........................ N/A........................................... Transition Record with Specified
Elements Received by Discharged
Patients (Discharges from an
Inpatient Facility to Home/Self
Care or Any Other Site of Care).
N/A.......................... N/A........................................... Screening for Metabolic
Disorders.
2860......................... N/A........................................... Thirty-Day All-Cause Unplanned
Readmission Following
Psychiatric Hospitalization in
an Inpatient Psychiatric
Facility.
3205......................... Med Cont...................................... Medication Continuation Following
Inpatient Psychiatric Discharge.
N/A.......................... N/A........................................... Modified COVID-19 Vaccination
Coverage Among Healthcare
Personnel (HCP)\1\.
----------------------------------------------------------------------------------------------------------------
* Measure is no longer endorsed by the CBE but was endorsed at the time of adoption. We note that although
section 1886(s)(4)(D)(i) of the Act generally requires measures specified by the Secretary be endorsed by the
entity with a contract under section 1890(a) of the Act, section 1886(s)(4)(D)(ii) states that in the case of
a specified area or medical topic determined appropriate by the Secretary for which a feasible and practical
measure has not been endorsed by the entity with a contract under section 1890(a) of the Act, the Secretary
may specify a measure that is not so endorsed as long as due consideration is given to measures that have been
endorsed or adopted by a consensus organization identified by the Secretary. We attempted to find available
measures for each of these clinical topics that have been endorsed or adopted by a consensus organization and
found no other feasible and practical measures on the topics for the IPF setting.
\1\ We have proposed updates to the COVID-19 HCP measure in section V.E. of this proposed rule.
3. IPFQR Program Measures for the FY 2026 Payment Determination
If we finalize our proposals for the FY 2026 payment determination
and subsequent years, the measure set would include 13 required and two
voluntary measures. This includes the 12 required measures discussed in
section V.G.2 of this proposed rule for the FY 2025 payment
determination and subsequent years, as well as the one required measure
and two voluntary measures we proposed for the FY 2026 payment
determination and subsequent years. The measures which would be in the
program for FY 2026 payment determination if we finalize these four
proposals are shown Table 22.
Table 22--IPFQR Program Measure Set for the FY 2026 Payment Determination if Proposals To Adopt New Required and
Voluntary Measures Are Finalized
----------------------------------------------------------------------------------------------------------------
CBE No. Measure ID Measure
----------------------------------------------------------------------------------------------------------------
Required Measures
----------------------------------------------------------------------------------------------------------------
0640......................... HBIPS-2....................................... Hours of Physical Restraint Use.
0641......................... HBIPS-3....................................... Hours of Seclusion Use.
N/A.......................... FAPH.......................................... Follow-Up After Psychiatric
Hospitalization.
1659......................... IMM-2......................................... Influenza Immunization.
N/A *........................ SUB-2 and SUB-2a.............................. Alcohol Use Brief Intervention
Provided or Offered and SUB-2a
Alcohol Use Brief Intervention.
N/A *........................ SUB-3 and SUB-3a.............................. Alcohol and Other Drug Use
Disorder Treatment Provided or
Offered at Discharge and SUB-3a
Alcohol and Other Drug Use
Disorder Treatment at Discharge.
[[Page 21298]]
N/A *........................ TOB-3 and TOB-3a.............................. Tobacco Use Treatment Provided or
Offered at Discharge and TOB-3a
Tobacco Use Treatment at
Discharge.
N/A *........................ N/A........................................... Transition Record with Specified
Elements Received by Discharged
Patients (Discharges from an
Inpatient Facility to Home/Self
Care or Any Other Site of Care).
N/A.......................... N/A........................................... Screening for Metabolic
Disorders.
2860......................... N/A........................................... Thirty-Day All-Cause Unplanned
Readmission Following
Psychiatric Hospitalization in
an Inpatient Psychiatric
Facility.
3205......................... Med Cont...................................... Medication Continuation Following
Inpatient Psychiatric Discharge.
N/A.......................... N/A........................................... Modified COVID-19 Vaccination
Coverage Among Healthcare
Personnel (HCP).\1\
N/A.......................... Facility Commitment........................... Facility Commitment to Health
Equity.\2\
----------------------------------------------------------------------------------------------------------------
Voluntary Measures
----------------------------------------------------------------------------------------------------------------
N/A.......................... Screening for SDOH............................ Screening for Social Drivers of
Health.\3\
N/A.......................... Screen Positive............................... Screen Positive Rate for Social
Drivers of Health.\4\
----------------------------------------------------------------------------------------------------------------
* Measure is no longer endorsed by the CBE but was endorsed at time of adoption. We note that although section
1886(s)(4)(D)(i) of the Act generally requires measures specified by the Secretary be endorsed by the entity
with a contract under section 1890(a) of the Act, section 1886(s)(4)(D)(ii) states that in the case of a
specified area or medical topic determined appropriate by the Secretary for which a feasible and practical
measure has not been endorsed by the entity with a contract under section 1890(a) of the Act, the Secretary
may specify a measure that is not so endorsed as long as due consideration is given to measures that have been
endorsed or adopted by a consensus organization identified by the Secretary. We attempted to find available
measures for each of these clinical topics that have been endorsed or adopted by a consensus organization and
found no other feasible and practical measures on the topics for the IPF setting.
\1\ We have proposed updates to the COVID-HCP measure in section V.E. of this proposed rule.
\2\ We have proposed adoption of the Facility Commitment measure in section V.D.2. of this proposed rule.
\3\ We have proposed voluntary reporting of the Screening for SDOH measure in section V.D.3. of this proposed
rule.
\4\ We have proposed voluntary reporting of the Screen Positive Rate for SDOH measure in section V.D.4 of this
proposed rule.
4. IPFQR Program Measures for the FY 2027 IPFQR Program's Payment
Determination
If we finalize our proposals for the FY 2027 payment determination
and subsequent years, the measure set would include 15 required
measures and one voluntary measure. This includes the 13 required
measures discussed in section V.G.3 of this proposed rule for the FY
2026 payment determination and subsequent years, as well as the two
measures which we proposed to require for the FY 2027 payment
determination and subsequent years. It also includes the one new
voluntary measure proposed in section V.D.5. of this proposed rule. The
measures which would be in the program for the FY 2027 payment
determination and subsequent years if we finalize these proposals are
shown Table 23.
Table 23--IPFQR Program Measure Set for the FY 2027 Payment Determination if Proposals To Adopt New Required and
Voluntary Measures Are Finalized
----------------------------------------------------------------------------------------------------------------
CBE No. Measure ID Measure
----------------------------------------------------------------------------------------------------------------
Required Measures
----------------------------------------------------------------------------------------------------------------
0640......................... HBIPS-2....................................... Hours of Physical Restraint Use.
0641......................... HBIPS-3....................................... Hours of Seclusion Use.
N/A.......................... FAPH.......................................... Follow-Up After Psychiatric
Hospitalization.
1659......................... IMM-2......................................... Influenza Immunization.
N/A *........................ SUB-2 and SUB-2a.............................. Alcohol Use Brief Intervention
Provided or Offered and SUB-2a
Alcohol Use Brief Intervention.
N/A *........................ SUB-3 and SUB-3a.............................. Alcohol and Other Drug Use
Disorder Treatment Provided or
Offered at Discharge and SUB-3a
Alcohol and Other Drug Use
Disorder Treatment at Discharge.
N/A *........................ TOB-3 and TOB-3a.............................. Tobacco Use Treatment Provided or
Offered at Discharge and TOB-3a
Tobacco Use Treatment at
Discharge.
N/A *........................ N/A........................................... Transition Record with Specified
Elements Received by Discharged
Patients (Discharges from an
Inpatient Facility to Home/Self
Care or Any Other Site of Care).
N/A.......................... N/A........................................... Screening for Metabolic
Disorders.
2860......................... N/A........................................... Thirty-Day All-Cause Unplanned
Readmission Following
Psychiatric Hospitalization in
an Inpatient Psychiatric
Facility.
3205......................... Med Cont...................................... Medication Continuation Following
Inpatient Psychiatric Discharge.
N/A.......................... N/A........................................... Modified COVID-19 Vaccination
Coverage Among Healthcare
Personnel (HCP).\1\
N/A.......................... Facility Commitment........................... Facility Commitment to Health
Equity.\2\
N/A.......................... Screening for SDOH............................ Screening for Social Drivers of
Health.\3\
N/A.......................... Screen Positive............................... Screen Positive Rate for Social
Drivers of Health.\4\
----------------------------------------------------------------------------------------------------------------
[[Page 21299]]
Voluntary Measure
----------------------------------------------------------------------------------------------------------------
N/A.......................... PIX........................................... Psychiatric Inpatient Experience
Survey.\5\
----------------------------------------------------------------------------------------------------------------
* Measure is no longer endorsed by the CBE but was endorsed at time of adoption. Although section
1886(s)(4)(D)(i) of the Act generally requires that any measures specified by the Secretary shall be endorsed
by the entity with a contract under section 1890(a) of the Act, section 1886(s)(4)(D)(ii) states that in the
case of a specified area or medical topic determined appropriate by the Secretary for which a feasible and
practical measure has not been endorsed by the entity with a contract under section 1890(a) of the Act, the
Secretary may specify a measure that is not so endorsed as long as due consideration is given to measures that
have been endorsed or adopted by a consensus organization identified by the Secretary. We attempted to find
available measures for each of these clinical topics that have been endorsed or adopted by a consensus
organization and found no other feasible and practical measures on the topics for the IPF setting.
\1\ We have proposed updates to the COVID-HCP measure in Section V.E. of this proposed rule.
\2\ We have proposed adoption of the Facility Commitment measure in section V.D.2. of this proposed rule.
\3\ We have proposed adoption of the Screening for SDOH measure in section V.D.3. of this proposed rule.
\4\ We have proposed adoption of the Screen Positive measure in section V.D.4. of this proposed rule.
\5\ We have proposed voluntary reporting of the Psychiatric Inpatient Experience measure in section V.D.5. of
this proposed rule.
5. IPFQR Program Measures for the FY 2028 Payment Determination
If we finalize our proposals for the FY 2028 payment determination
and subsequent years, the measure set would include 16 required
measures. This includes the 15 required measures discussed in section
V.G.4 and V.G.5 of this proposed rule for the FY 2027 payment
determination as well as the measure which we proposed to require
beginning with the FY 2028 payment determination. The measures which
would be in the program beginning with the FY 2028 payment
determination if we finalize these proposals are shown Table 24.
Table 24--IPFQR Program Measure Set for the FY 2029 Payment Determination if Proposals To Adopt New Required and
Voluntary Measures Are Finalized
----------------------------------------------------------------------------------------------------------------
CBE No. Measure ID Measure
----------------------------------------------------------------------------------------------------------------
0640......................... HBIPS-2....................................... Hours of Physical Restraint Use.
0641......................... HBIPS-3....................................... Hours of Seclusion Use.
N/A.......................... FAPH.......................................... Follow-Up After Psychiatric
Hospitalization.
1659......................... IMM-2......................................... Influenza Immunization.
N/A*......................... SUB-2 and SUB-2a.............................. Alcohol Use Brief Intervention
Provided or Offered and SUB-2a
Alcohol Use Brief Intervention.
N/A*......................... SUB-3 and SUB-3a.............................. Alcohol and Other Drug Use
Disorder Treatment Provided or
Offered at Discharge and SUB-3a
Alcohol and Other Drug Use
Disorder Treatment at Discharge.
N/A*......................... TOB-3 and TOB-3a.............................. Tobacco Use Treatment Provided or
Offered at Discharge and TOB-3a
Tobacco Use Treatment at
Discharge.
N/A*......................... N/A........................................... Transition Record with Specified
Elements Received by Discharged
Patients (Discharges from an
Inpatient Facility to Home/Self
Care or Any Other Site of Care).
N/A.......................... N/A........................................... Screening for Metabolic
Disorders.
2860......................... N/A........................................... Thirty-Day All-Cause Unplanned
Readmission Following
Psychiatric Hospitalization in
an Inpatient Psychiatric
Facility.
3205......................... Med Cont...................................... Medication Continuation Following
Inpatient Psychiatric Discharge.
N/A.......................... N/A........................................... Modified COVID-19 Vaccination
Coverage Among Healthcare
Personnel (HCP).\1\
N/A.......................... Facility Commitment........................... Facility Commitment to Health
Equity.\2\
N/A.......................... Screening for SDOH............................ Screening for Social Drivers of
Health.\3\
N/A.......................... Screen Positive............................... Screen Positive Rate for Social
Drivers of Health.\4\
N/A.......................... PIX........................................... Psychiatric Inpatient Experience
Survey.\5\
----------------------------------------------------------------------------------------------------------------
* Measure is no longer endorsed by the CBE but was endorsed at time of adoption. Although section
1886(s)(4)(D)(i) of the Act generally requires that any measures specified by the Secretary shall be endorsed
by the entity with a contract under section 1890(a) of the Act, section 1886(s)(4)(D)(ii) states that in the
case of a specified area or medical topic determined appropriate by the Secretary for which a feasible and
practical measure has not been endorsed by the entity with a contract under section 1890(a) of the Act, the
Secretary may specify a measure that is not so endorsed as long as due consideration is given to measures that
have been endorsed or adopted by a consensus organization identified by the Secretary. We attempted to find
available measures for each of these clinical topics that have been endorsed or adopted by a consensus
organization and found no other feasible and practical measures on the topics for the IPF setting.
\1\ We have proposed updates to the COVID-HCP measure in Section V.E. of this proposed rule.
\2\ We have proposed adoption of the Facility Commitment measure in section V.D.2. of this proposed rule.
\3\ We have proposed adoption of the Screening for SDOH measure in section V.D.3. of this proposed rule.
\4\ We have proposed adoption of the Screen Positive measure in section V.D.4. of this proposed rule.
\5\ We have proposed required reporting of the Psychiatric Inpatient Experience measure in section V.D.5. of
this proposed rule.
H. Public Display and Review Requirements
In the FY 2013 IPPS/LTCH PPS final rule (77 FR 53653 through
53654), we adopted procedures for making data submitted under the IPFQR
Program available to the public, after an IPF has the opportunity to
review such data prior to public display, as required by section
1886(s)(4)(E) of the Act. We adopted modifications to these procedural
requirements in the FY 2014 IPPS/LTCH PPS final rule (78 FR 50897
through 50898), and the FY 2017 IPPS/LTCH PPS final rule (81 FR 57248
through 57249).
Specifically, the IPFQR Program adopted a policy to provide IPFs a
30-day period to review their data, and submit corrections to errors
resulting
[[Page 21300]]
from CMS calculations, prior to public display on a CMS website. The
IPFQR Program notifies IPFs of the exact timeframes for this preview
period and public display through subregulatory guidance. We do not
propose any changes to these requirements.
We propose to codify the procedural requirements for public
reporting of IPFQR Program data at Sec. 412.433(g). If finalized,
paragraph (g) would provide that IPFs will have a period of 30 days to
review data on quality measures that CMS received under the IPFQR
Program, and submit corrections to errors resulting from CMS
calculations, prior to CMS publishing this data on a CMS website.
We welcome comments on our proposals to codify these policies.
I. Form, Manner, and Timing of Quality Data Submission for the FY 2024
Payment Determination and Subsequent Years
Procedural Requirements for the FY 2024 Payment Determination and
Subsequent Years
We refer readers to the FY 2013 IPPS/LTCH PPS final rule (77 FR
53654 through 53655), the FY 2014 IPPS/LTCH PPS final rule (78 FR 50898
through 50899), the FY 2018 IPPS/LTCH PPS final rule (82 FR 38471
through 38472), and the FY 2022 IPF PPS final rule (86 FR 42656 through
42657) for our previously finalized procedural requirements for
participation in, and withdrawal from, the IPFQR Program, as well as
data submission requirements. We do not propose any changes to our
previously finalized procedural requirements.
We propose to codify these procedural requirements for
participation in the IPFQR Program at Sec. 412.433(b) through (d). If
finalized, paragraphs (b) through (d) would set forth the procedural
requirements for an IPF to register for, or withdraw from,
participation in the IPFQR Program and to submit the required data on
measures in a form and manner and time specified by CMS.
We welcome comments on our proposal to codify these policies.
2. Data Submission Requirements for the FY 2025 Payment Determination
and Subsequent Years
We refer readers to the FY 2013 IPPS/LTCH PPS final rule (77 FR
53655 through 53657), the FY 2014 IPPS/LTCH PPS final rule (78 FR 50899
through 50900), the FY 2018 IPPS/LTCH PPS final rule (82 FR 38472
through 38473), and the FY 2022 IPF PPS final rule (86 FR 42657 through
42661) for our previously finalized data submission requirements.
The measure we propose to modify beginning with the FY 2025 payment
determination--the COVID-19 Vaccination Coverage Among HCP measure--
requires facilities to report data on the number of HCP who have
received a complete vaccination course of a COVID-19 vaccine through
the Centers for Disease Control and Prevention's (CDC's) National
Healthcare Safety Network (NHSN). We propose to update this measure to
no longer refer to ``complete vaccination course'' but instead to refer
to ``up-to-date'' vaccination, as described in section V.E. of this
proposed rule.
We do not propose any updates to the form, manner, and timing of
data submission for the COVID-19 Vaccination Coverage Among HCP measure
and refer readers to the FY 2022 IPF PPS final rule (86 FR 42657) for
these policies.
3. Data Submission Requirements for the FY 2026 Payment Determination
and Subsequent Years
In sections V.D 3 and V.D.4 of this proposed rule, we propose to
adopt measures for voluntary reporting for the FY 2026 IPFQR Program
and required reporting for the FY 2027 IPFQR Program's payment
determination and subsequent years. These measures are the Screening
for Social Drivers of Health measure and Screen Positive Rate for
Social Drivers of Health measure. We propose that our previously
finalized data submission requirements, specifically, our previously
finalized data submission requirements for aggregate data reporting
described in the FY 2018 IPPS/LTCH PPS final rule (82 FR 38472 through
38473) would apply to these measures.
We invite public comment on this proposal.
4. Data Submission Requirements for the FY 2027 Payment Determination
and Subsequent Years
In section V.D.5. of this proposed rule, we are proposing to adopt
one patient-reported measure, Psychiatric Inpatient Experience (PIX)
measure for voluntary reporting beginning in the FY 2027 program year
and required reporting beginning with the FY 2028 payment
determination. Because, unlike other patient experience of care
measures, this measure is collected by facilities prior to discharge,
we are proposing that facilities would report these data using the
patient-level data reporting described in the FY 2022 IPF PPS final
rule (86 FR 42658 through 42661).
5. Proposed Data Validation Pilot Beginning With Data Submitted in 2025
As discussed in the FY 2019 IPF PPS final rule (83 FR 28607) and in
the FY 2022 IPF PPS final rule (86 FR 42661), we are concerned that the
ability to detect error is lower for aggregate measure data reporting
than for patient-level data reporting (that is, data regarding each
patient included in a measure and, for example, whether the patient was
included in the numerator and denominator of the measure). In the FY
2022 IPF PPS final rule, we noted that adoption of patient-level data
requirements would enable us to adopt a data validation policy for the
IPFQR Program in the future (86 FR 42661). We believe that it would be
appropriate to develop such a policy incrementally through adoption of
a data validation pilot prior to national implementation of data
validation within the IPFQR Program. We sought public input on a
potential data validation pilot, and many commenters supported the
concept of data validation following implementation of patient-level
reporting (86 FR 42661). In the FY 2022 IPF PPS final rule, we adopted
required patient-level reporting beginning with data submitted in CY
2023 affecting the FY 2024 payment determination and reflecting care
provided during CY 2022 (86 FR 42658 through 42661).
We now propose a data validation pilot beginning with data
submitted in CY 2024 (reflecting care provided during CY 2023). When we
sought public comment on a data validation pilot in the FY 2022 IPF PPS
proposed rule (86 FR 19515), we requested input on potential elements
of such a pilot, including the number of measures and the number of
participating IPFs. As summarized in the FY 2022 IPF PPS final rule (86
FR 42661), one commenter recommended selecting two measures and 200
IPFs for this pilot. We considered that recommendation; however, to
align with validation policies in our other quality reporting programs,
we decided to request a specific number of charts. Specifically, we are
proposing to request eight charts per quarter from each IPF as opposed
to requesting all of the charts that each facility used to calculate
one or more specific measures. We also decided to initiate our pilot
with fewer IPFs than the commenter recommended to limit the burden
associated with this pilot.
We also reviewed the validation policies of other quality reporting
programs. We specifically reviewed the Hospital IQR Program's chart-
abstracted
[[Page 21301]]
measure validation policies described in the FY 2017 IPPS/LTCH PPS
final rule (81 FR 57179 through 57180), the Hospital IQR Program's
pilot for eCQM validation described in the FY 2015 IPPS/LTCH PPS final
rule (79 FR 50262 through 50273), the Hospital Outpatient Quality
Reporting (OQR) Program's planned pilot of data validation as described
in the CY 2009 OPPS/ASC final rule (73 FR 68502), and the Hospital OQR
Program's finalized validation policies as described in the CY 2012
OPPS/ASC final rule (76 FR 74485) and the CY 2018 OPPS/ASC final rule
(82 FR 59441 through 5944) because these programs are also pay-for-
reporting programs, like the IPFQR Program.
Following our review of the validation policies within these
programs, we propose a validation pilot in which we would randomly
select on an annual basis up to 100 IPFs and request each selected IPF
to provide to CMS eight charts per quarter, a total of 32 charts per
year, used to calculate all chart-based measures beginning with data
submitted in CY 2025. We believe that randomly selecting up to 100 IPFs
would provide a sufficiently large set of IPFs to meaningfully test our
validation procedures while minimizing burden for IPFs. We would
specify the timeline and mechanism for submitting data in our data
requests to individual IPFs that have been selected to participate in
the validation pilot. We note that consistent with the Hospital IQR
Program, we would reimburse IPFs for the cost of submitting charts for
validation at a rate of $3.00 per chart (85 FR 58949).
Because this is a voluntary pilot, we recognize that some selected
IPFs would not participate; however, we believe that this pilot would
be beneficial for IPFs that do participate as an opportunity to receive
education and feedback on the data they submit prior to future proposal
and adoption of a validation requirement in the IPFQR Program.
We invite comment on our proposal.
6. Quality Measure Sampling Requirements
We refer readers to the FY 2013 IPPS/LTCH PPS final rule (77 FR
53657 through 53658), the FY 2014 IPPS/LTCH PPS final rule (78 FR 50901
through 50902), the FY 2016 IPF PPS final rule (80 FR 46717 through
46719), and the FY 2019 IPF PPS final rule (83 FR 38607 through 38608)
for discussions of our previously finalized sampling policies.
Because the Facility Commitment to Health Equity measure proposed
in section V.D.2 of this proposed rule is a structural attestation
measure, these policies would not apply to that measure. Additionally,
because the Screening for Social Drivers of Health measure (described
in section V.D.3 of this proposed rule) would apply to all patients and
the Screen Positive Rate for Social Drivers of Health measure
(described in section V.D.4 of this proposed rule) would apply to all
patients who had been screened for health-related social needs (HRSNs),
our previously finalized sampling policies would not apply to these two
measures. As described in the FY 2022 IPF PPS final rule, our sampling
policies do not apply to the COVID-19 Vaccination Coverage Among
Healthcare Personnel measure because the denominator is all healthcare
personnel (86 FR 42661).
Generally, we have applied our sampling procedures to chart-
abstracted measures, where appropriate (that is, where the measure does
not require application to the entire patient population). However,
because the PIX survey measure is a patient reported measure, we have
considered whether our sampling procedures for chart-abstracted
measures are appropriate for this measure. After consideration of our
current sampling procedures and sampling for patient reported measures
in other quality reporting programs (specifically, the requirements for
reporting the HCAHPS measure), we are proposing that the PIX survey
measure (described in section V.D.5 of this proposed rule) would be
eligible for sampling but would not be included in the global sample.
Instead, we are proposing that sampling for this measure would align
with sampling for the HCAHPS survey measure in acute care hospitals and
the Hospital IQR Program as described in the HCAHPS Quality Assurance
Guidelines.\232\ Specifically, we are proposing to require IPFs to
develop sampling plans that ensure that IPFs are able to submit data
for 300 completed PIX surveys per year. IPFs would be required to
sample from every month throughout the entire reporting period and not
stop sampling or curtail ongoing interview activities once a certain
number of completed surveys has been attained. IPFs that are unable to
reach 300 completed surveys through sampling would be required to
submit data on survey results for all eligible patient discharges.
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\232\ HCHAPS Quality Assurance Guidelines, Version 17.0. March
2022. Available at: https://hcahpsonline.org/globalassets/hcahps/quality-assurance/2022_qag_v17.0.pdf.
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We invite public comment on our proposal.
7. Non-Measure Data Collection
We refer readers to the FY 2015 IPF PPS final rule (79 FR 45973),
the FY 2016 IPF PPS final rule (80 FR 46717), and the FY 2019 IPF PPS
final rule (83 FR 38608) for our previously finalized non-measure data
collection policies. We do not propose any changes to these policies.
8. Accuracy and Completeness Acknowledgement (DACA) Requirements
We refer readers to the FY 2013 IPPS/LTCH PPS final rule (77 FR
53658) for our previously finalized DACA requirements. We do not
propose any changes to these policies.
J. Reconsideration and Appeals Procedures
We refer readers to 42 CFR 412.434 for the IPFQR Program's
reconsideration and appeals procedures. We do not propose any changes
to these policies.
K. Extraordinary Circumstances Exceptions (ECE) Policy
We refer readers to the FY 2013 IPPS/LTCH PPS final rule (77 FR
53659 through 53660), the FY 2014 IPPS/LTCH PPS final rule (78 FR
50903), the FY 2015 IPF PPS final rule (79 FR 45978), and the FY 2018
IPPS/LTCH PPS final rule (82 FR 38473 through 38474) for our previously
finalized Extraordinary Circumstances Exceptions policies. We do not
propose any changes to these policies.
We propose to codify the ECE policies at Sec. 412.433(f). If
finalized, paragraph (f) would provide that we may grant an exception
to one or more data submission deadlines and requirements in the event
of extraordinary circumstances beyond the control of the IPF either in
response to a request by the IPF or at our discretion if we determine
an extraordinary circumstance occurred.
We welcome comments on our proposal to codify these policies.
VI. Collection of Information Requirements
Under the Paperwork Reduction Act of 1995 (PRA) (44 U.S.C. 3501 et
seq.), we are required to provide 60-day notice in the Federal Register
and solicit public comment before a ``collection of information''
requirement is submitted to the Office of Management and Budget (OMB)
for review and approval. For the purposes of the PRA and this section
of the preamble, collection of information is defined under 5 CFR
1320.3(c) of the PRA's implementing regulations.
To fairly evaluate whether an information collection should be
[[Page 21302]]
approved by OMB, section 3506(c)(2)(A) of the Paperwork Reduction Act
of 1995 requires that we solicit comment on the following issues:
The need for the information collection and its usefulness
in carrying out the proper functions of our agency.
The accuracy of our estimate of the information collection
burden.
The quality, utility, and clarity of the information to be
collected.
Recommendations to minimize the information collection
burden on the affected public, including automated collection
techniques.
We are soliciting public comment (see section VI.C of this proposed
rule) on each of these issues for the following sections of this
document that contain information collection requirements. Comments, if
received, will be responded to within the subsequent final rule.
A. Wage Estimates
To derive average costs, we used data from the U.S. Bureau of Labor
Statistics' (BLS') May 202/1 National Occupational Employment and Wage
Estimates for all salary estimates (https://www.bls.gov/oes/current/oes_nat.htm). In this regard, Table 25 presents BLS' mean hourly wage
for Medical Records and Health Information Technicians (the occupation
title that we have estimated is appropriate for completing data
collection and reporting under the IPFQR Program), our estimated cost
of fringe benefits and other indirect costs (calculated at 100 percent
of salary), and our adjusted hourly wage.
Table 25--Wage Assumptions for the IPFQR Program
----------------------------------------------------------------------------------------------------------------
Adjusted
Occupation Median hourly Fringe benefits hourly
Occupation title code wage ($/hr.) and other indirect wage ($/
costs ($/hr.) hr.)
----------------------------------------------------------------------------------------------------------------
Medical Records and Health Information Technician. 29-2071 22.43 22.43 44.86
----------------------------------------------------------------------------------------------------------------
As indicated, we are adjusting our hourly wage estimates by a
factor of 100 percent. This is necessarily a rough adjustment, both
because fringe benefits and other indirect costs vary significantly
from employer to employer, and because methods of estimating these
costs vary widely from study to study. Nonetheless, we believe that
doubling the hourly wage to estimate the total cost is a reasonably
accurate estimation method.
In the FY 2022 IPF PPS final rule (86 FR 42662), which was the most
recent rule in which we adopted updates to the IPFQR Program, we
estimated that reporting measures for the IPFQR Program could be
accomplished by a Medical Records and Health Information Technician
(BLS Occupation Code: 29-2071) with a median hourly wage of $20.50/hour
(BLS, May 2019). While we are not changing the respondent's occupation
title or occupation code, we are proposing to adjust our cost estimates
using BLS' May 2021 median wage rate figure of $22.43/hour, an increase
of $1.93/hour ($22.43/hour-$20.50/hour). When factoring in our overhead
and other indirect cost adjustments, the wage is increased by $3.86/
hour ($44.86/hour-$41.00/hour).
We have also estimated the average hourly cost for beneficiaries
undertaking administrative and other tasks on their own time. Based on
recommendations from the Valuing Time in U.S. Department of Health and
Human Services Regulatory Impact Analyses \233\ guidance we have
estimated a post-tax wage of $20.71/hr. The Valuing Time in U.S.
Department of Health and Human Services Regulatory Impact Analyses:
Conceptual Framework and Best Practices identifies the approach for
valuing time when individuals undertake activities on their own time.
To derive the costs for beneficiaries, a measurement of the usual
weekly earnings of wage and salary workers of $998, divided by 40 hours
to calculate an hourly pre-tax wage rate of $24.95/hours. This rate is
adjusted downwards by an estimate of the effective tax rate for median
income households of about 17 percent, resulting in the post-tax hourly
wage rate of $20.71/hour. Unlike our State and private sector wage
adjustments, we are not adjusting beneficiary wages for fringe benefits
and other indirect costs since the individuals' activities, if any,
would occur outside the scope of their employment.
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\233\ https://aspe.hhs.gov/sites/default/files/private/pdf/257746/VOT.pdf.
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B. Proposed Information Collection Requirements (ICRs) Regarding the
IPFQR Program
The following proposed requirement and burden changes will be
submitted to OMB for review under control number 0938-1171 (CMS-10432).
We are not proposing changes that will affect any of data collection
instruments that are currently approved under that control number. In
section VI.B.1 of this proposed rule, we restate our currently approved
burden estimates. In section VI.B.2 of this proposed rule, we estimate
the changes in burden associated with the policies proposed in this
rule and updated estimates for wage rates, facility counts, and case
counts. Then in section VI.B.3 of this proposed rule, we provide an
overview of the total estimated burden.
1. Currently Approved Burden
For a detailed discussion of the burden for the IPFQR Program
requirements that we have previously adopted, we refer readers to the
following rules:
The FY 2013 IPPS/LTCH PPS final rule (77 FR 53673);
The FY 2014 IPPS/LTCH PPS final rule (78 FR 50964);
The FY 2015 IPF PPS final rule (79 FR 45978 through
45980);
The FY 2016 IPF PPS final rule (80 FR 46720 through
46721);
The FY 2017 IPPS/LTCH PPS final rule (81 FR 57265 through
57266);
The FY 2018 IPPS/LTCH PPS final rule (82 FR 38507 through
38508);
The FY 2019 IPF PPS final rule (83 FR 38609 through
38612);
The FY 2020 IPF PPS final rule (84 FR 38468 through
38476); and
The FY 2022 IPF PPS final rule (86 FR 42661 through
42672).
Table 26 provides an overview of our currently approved burden
estimates.
[[Page 21303]]
TABLE 26--Currently Approved Burden OMB Control Number 0938-1171
[CMS-10432]
--------------------------------------------------------------------------------------------------------------------------------------------------------
Number Estimated Total Time per Annual time Total
Measure/response description respondents responses annual response per facility annual time Total annual
(facilities) per facility responses (hours) (hours) (hours) cost ($)
--------------------------------------------------------------------------------------------------------------------------------------------------------
Hours of Physical Restraint Use.................... 1,634 1,346 2,199,364 0.25 336.50 549,841 22,543,481
Hours of Seclusion Use............................. 1,634 1,346 2,199,364 0.25 336.50 549,841 22,543,481
Patients Discharged on Multiple Antipsychotic 1,634 * 609 995,106 0.25 152.25 248,776.5 10,199,836.50
Medications with Appropriate Justification........
Alcohol Use Brief Intervention Provided or Offered 1,634 * 609 995,106 0.25 152.25 248,776.5 10,199,836.50
(SUB-2 and SUB-2a)................................
Alcohol and Other Drug Use Disorder Treatment 1,634 * 609 995,106 0.25 152.25 248,776.5 10,199,836.50
Provided or Offered at Discharge and Alcohol and
Other Drug Use Disorder Treatment at Discharge
(SUB-3 and SUB-3a)................................
Tobacco Use Treatment Provided or Offered and 1,634 * 609 995,106 0.25 152.25 248,776.5 10,199,836.50
Tobacco Use Treatment (TOB-2 and TOB-2a)..........
Tobacco Use Treatment Provided or Offered at 1,634 * 609 995,106 0.25 152.25 248,776.5 10,199,836.50
Discharge and Tobacco Use Treatment at Discharge
(TOB-3 and TOB-3a)................................
Influenza Immunization............................. 1,634 * 609 995,106 0.25 152.25 248,776.5 10,199,836.50
Transition Record with Specified Elements Received 1,634 * 609 995,106 0.25 152.25 248,776.5 10,199,836.50
by Discharged Patients (Discharges from an
Inpatient Facility to Home/Self Care or Any Other
Site of Care).....................................
Screening for Metabolic Disorders.................. 1,634 * 609 995,106 0.25 152.25 248,776.5 10,199,836.50
Thirty-day all-cause unplanned readmission 0 ** 0 0 0 0 0 0
following psychiatric hospitalization in an IPF...
Medication Continuation Following Inpatient 0 ** 0 0 0 0 0 0
Psychiatric Discharge.............................
COVID-19 Vaccination Rate Among Healthcare 0 *** 0 0 0 0 0 0
Personnel.........................................
Follow-Up After Psychiatric Hospitalization........ 0 ** 0 0 0 0 0 0
----------------------------------------------------------------------------------------------------
Subtotal....................................... 1,634 7,564 12,359,576 N/A 1,891 3,089,894 126,685,654
--------------------------------------------------------------------------------------------------------------------------------------------------------
Non-Measure Data Collection and Reporting.......... 1,634 4 6,536 0.5 2.0 3,268 133,988
----------------------------------------------------------------------------------------------------
Total.......................................... 1,634 7,568 12,366,112 Varies 1,893 3,093,162 126,819,642
--------------------------------------------------------------------------------------------------------------------------------------------------------
* Under our previously finalized ``global sample'' (80 FR 46717 through 46718) we allow facilities to apply the same sampling methodology to all
measures eligible for sampling. In the FY 2016 IPF PPS final rule (80 FR 46718), we finalized that facilities with between 609 and 3,056 cases that
choose to participate in the global sample would be required to report data for 609 cases. Because facilities are only required to submit data on a
number specified by the global sampling methodology, rather than abstracting data for all patients or applying measure specific sampling
methodologies, we believe that the number of cases under the global sample is a good approximation of facility burden associated with these measures.
Therefore, for the average IPF discharge rate of 1,346 discharges the global sample requires abstraction of 609 records.
** CMS will collect these data using Medicare Part A and Part B claims; therefore, these measures will not require facilities to submit data on any
cases.
*** The COVID-19 HCP measure will be calculated using data submitted to the CDC under a separate OMB control number (0920-1317).
2. Adjustments Due to Changes in This Proposed Rule
In this proposed rule, we propose provisions that impact policies
beginning with the FY 2025 through FY 2028 payment determinations. For
the purposes of calculating burden, we attribute the costs to the year
in which the costs begin. For example, data submission for the measures
that affect the FY 2025 payment determination occurs during CY 2024 and
generally reflects are provided during CY 2023. The following
discussion describes the burden changes for proposals attributed to the
year in which the costs begin. For the proposals in this proposed rule,
those years are CY 2023 through CY 2027.
Additionally, in the FY 2022 IPF PPS final rule (86 FR 42661
through 42672), which is the most recent rule that updated the IPFQR
Program policies, we estimated that there were 1,634 participating IPFs
and that (for measures that require reporting on the entire patient
population) these IPFs will report on an average of 1,346 cases per
IPF. In this FY 2024 IPF PPS proposed rule, we are proposing to adjust
our IPF count and case estimates by using the most recent data
available. Specifically, we estimate that there are now approximately
1,596 facilities (a decrease of 38 facilities) and an average of 1,261
cases per facility (a decrease of 85 cases per facility). We will
update our estimates, as applicable, using these revised estimates in
the following subsections.
a. Proposals Affecting Data Reporting Beginning in CY 2023
In section V.E of this proposed rule, we propose to modify the
COVID-19 Vaccination Coverage Among Healthcare Personnel measure
beginning with data reflecting the fourth quarter of CY 2023 affecting
the FY 2025 payment determination. We do not believe that the proposed
modification (that is, a change in terminology to refer to ``up-to-
date'' instead of ``complete vaccination course'') would impact our
currently approved IPF information collection requirements or reporting
burden. Furthermore, the modified COVID-19 Vaccination Coverage Among
HCP measure would be calculated using data submitted to the CDC for
healthcare safety surveillance under the CDC's OMB control number 0920-
1317. In this regard, the CDC owns the requirements and burden that
fall under that control number.
b. Proposals Affecting Burden Beginning With CY 2024
(1) Proposed Updates Affecting Facility Reporting Burden
In section V.F.2 of this proposed rule, we propose to remove two
measures beginning with the FY 2025 payment determination. Data for
these measures would be submitted in CY 2024, so we are estimating the
reduced burden to occur in CY 2024. These two measures are:
Patients Discharged on Multiple Antipsychotic Medications
with
[[Page 21304]]
Appropriate Justification (HBIPS-5); and
Tobacco Use Treatment Provided or Offered and Tobacco Use
Treatment (TOB-2 and TOB-2a).
Using our currently approved burden estimates, the change in total
burden associated with these proposed measure removals would be minus
1,990,212 responses, minus 497,553 hours, and minus $20,339,673 as
depicted in Table 27.
Table 27--Updates to Burden Associated With Proposed Measure Removals
--------------------------------------------------------------------------------------------------------------------------------------------------------
Number Estimated Time per Annual time
Measure/response description respondents responses per Total annual response per facility Total annual Total annual cost
(facilities) facility responses (hours) (hours) time (hours) ($)
(a) (b) (c) = (a) x (d) (e) = (b) x (f) = (a) x (g) = (f) x $41.00/
(b) (d) (e) hr
--------------------------------------------------------------------------------------------------------------------------------------------------------
Patients Discharged on Multiple 1,634 (* 609) (995,106) 0.25 (152.25) (248,776.5) (10,199,836.50)
Antipsychotic Medications with
Appropriate Justification..........
Tobacco Use Treatment Provided or 1,634 (* 609) (995,106) 0.25 (152.25) (248,776.5) (10,199,836.50)
Offered and Tobacco Use Treatment
(TOB-2 and TOB-2a).................
-------------------------------------------------------------------------------------------------------------------
Total............................. 1,634 (1,218) (1,990,212) 0.25 (304.5) (497,553) (20,339,673)
--------------------------------------------------------------------------------------------------------------------------------------------------------
* Under our previously finalized ``global sample'' (80 FR 46717 through 46718) we allow facilities to apply the same sampling methodology to all
measures eligible for sampling. In the FY 2016 IPF PPS final rule (80 FR 46718), we finalized that facilities with between 609 and 3,056 cases that
choose to participate in the global sample would be required to report data for 609 cases. Because facilities are only required to submit data on a
number specified by the global sampling methodology, rather than abstracting data for all patients or applying measure specific sampling
methodologies, we believe that the number of cases under the global sample is a good approximation of facility burden associated with these measures.
Therefore, for the average IPF discharge rate of 1,346 discharges the global sample requires abstraction of 609 records.
Additionally, we are applying our updated wage rate, case count,
and facility counts to the remaining measure set and program
requirements for data submission in CY 2024. See Table 28 and 29 for
information on the effects of these updates. Specifically, we estimate
that there are now approximately 1,596 facilities (a decrease of 38
facilities) and an average of 1,261 cases per facility (a decrease of
85 cases per facility). We also estimate a wage increase of $3.86/hour
as described in section VI.A of this proposed rule. Our previous
estimate shows that the two measures which do not allow sampling had
1,346 cases per measure and the six remaining measures which do allow
sampling require 609 cases per measure per facility. We have estimated
that these measures would take 0.25 hours per case. The effects of the
updated wage rate are depicted in Table 28.
Table 28--Effects of Updated Wage Rate
--------------------------------------------------------------------------------------------------------------------------------------------------------
Number of Change in cost
estimated Total number Total effort per facility
Data collection type Number of cases per of cases per Effort per per facility ($(effort *
measures measure per facility case (hours) (hours) 3.86/hour wage
facility change)
--------------------------------------------------------------------------------------------------------------------------------------------------------
No-sampling measures.................................... 2 1,346 2,692 0.25 673 2,597.78
Sampling measures....................................... 6 609 3,654 0.25 913.5 3,526.11
Non-Measure Data........................................ 1 4 4 0.5 2 7.72
-----------------------------------------------------------------------------------------------
Total Change per Facility........................... .............. .............. .............. .............. .............. 6,131.61
--------------------------------------------------------------------------------------------------------------------------------------------------------
The remaining calculations will use the updated wage rate to
calculate the effects of other updates.
We have previously estimated 1,346 cases for measures which do not
allow sampling. Based on more recent data, we are updating our estimate
for measures that do not allow sampling to 1,261 cases per IPF (a
change of +85 cases for each of these 2 measures). This is equivalent
to 138,890 cases across the 1,634 IPFs (85 cases * 1,634 IPFs) in our
previous estimate for each measure. We are not changing our estimated
case counts for measures that allow sampling. We continue to assume an
average of 0.25 hours of effort per case. Therefore, this change in
cases reflects a total annual effort of 42.5 hours per facility (2
measures * 85 cases per measure * 0.25 hours per case) at a cost of
$1,906.55 (42.5 hours * $44.86/hour).
As indicated above we estimate a reduction of 38 facilities based
on updated numbers. Table 29 shows the effects of this reduction in
facilities on the reporting burden associated with each measure type.
Table 29--Effects of Updated Facility Counts
--------------------------------------------------------------------------------------------------------------------------------------------------------
Change in Change in annual
Number of annual effort effort for
Measure type Number of estimated cases Cases per Effort per case Effort per for removing removing 38
measures (per measure per facility facility 38 facilities facilities
facility) (hours) (dollars)
--------------------------------------------------------------------------------------------------------------------------------------------------------
No Sampling................. 2 1,261............. 2,522 0.25.............. 630.5 (23,959) (1,074,800.74)
Sampling.................... 6 609............... 3,654 0.25.............. 913.5 (34,713) (1,557,225.18)
[[Page 21305]]
Non-Measure Data Collection. 1 4................. 4 0.5............... 2 (76) (3,409.36)
---------------------------------------------------------------------------------------------------------------------------
Total................... 9 Varies............ 6,180 Varies............ 1,546 (58,748) (2,635,435.28)
--------------------------------------------------------------------------------------------------------------------------------------------------------
We note that at 6,180 cases per facility, removing 38 facilities
from our estimate removes a total of 234,840 cases (6,180 cases per
facility * 38 facilities).
The total effects of changes for the CY 2024 calendar year on our
burden estimates are summarized in Table 30.
Table 30--Total CY 2024 Facility Information Collection Burden Changes
----------------------------------------------------------------------------------------------------------------
Total Total annual Total annual cost
responses time (hours) ($)
----------------------------------------------------------------------------------------------------------------
Remove Two Measures......................................... (1,990,212) (497,553) (20,339,673)
Update Wage Estimate........................................ N/A N/A 8,253,147.06
Update Case Estimate........................................ (277,280) (69,445) (3,115,302.70)
Update Facility Estimate.................................... (234,840) (58,748) (2,635,435.28)
---------------------------------------------------
Total................................................... (2,502,332) (625,746) (17,837,263.92)
----------------------------------------------------------------------------------------------------------------
(b) Proposed Updates Affecting Patient Survey Burden
In section V.D.3 of this proposed rule, we propose to adopt the
Screening for Social Drivers of Health measure beginning with a
voluntary data submission in CY 2025 (reflecting care provided in CY
2024). In this regard, IPFs would be able to collect data and report
the measure via multiple methods. For additional information on these
methods, we refer readers to section V.D.3.c of this proposed rule. We
believe that most IPFs would likely collect data during the patient
intake process. Because this measure reflects care provided in CY 2024,
the burden for administering the screening to patients would occur
during CY 2024.
The Hospital IQR Program, which adopted the Screening for Social
Drivers of Health measure, estimated the information collection burden
associated with patients responding to the selected screening
instrument would require two minutes per patient to complete the
screening in the FY 2022 IPPS/LTCH PPS final rule (87 FR 49385 through
49386) under OMB Control Number 0938-1022 (CMS-10210). The Hospital IQR
Program also estimated that during the voluntary reporting period
roughly 50 percent of hospitals would survey 50 percent of patients (87
FR 49385 through 49386).
We agree with these estimates and believe that a similar proportion
of IPFs will participate in the voluntary reporting period. As
described in section VI.A of this proposed rule, we estimate the cost
of patients' time for completing surveys to be $20.71/hour. Using these
estimates, we believe that during the voluntary reporting period the
annual burden of surveying IPF patients would be 16,603.59 hours
[(1,596 facilities x 50 percent of facilities) x (1,261 patients per
facility x 50 percent of patients) x 0.033 hours/response] at a cost of
$343,860.29 (16,603.59 hours x 20.71/hour). These estimates are
summarized in Table 31.
Table 31--Total CY 2024 Patient Survey Burden Changes
----------------------------------------------------------------------------------------------------------------
Total annual Total annual
Total responses time (hours) cost ($)
----------------------------------------------------------------------------------------------------------------
Screening for SDOH........................................... 503,139 16,603.59 343,860.29
----------------------------------------------------------------------------------------------------------------
(c) Proposals Affecting Burden Beginning with CY 2025
(1) Proposed Updates Affecting Facility Reporting Burden
In section V.D.2. of this proposed rule, we propose to adopt the
Facility Commitment to Health Equity measure beginning with the FY 2026
payment determination. Data for this attestation measure would be
submitted during CY 2025. Consistent with our burden estimate from the
Hospital IQR Program, when we adopted the similar Hospital Commitment
to Health Equity measure in the FY 2023 IPPS/LTCH PPS final rule, we
estimate an average of 10 minutes per facility for a medical records
and health information technician to collect and report this
information (87 FR 49385). We recognize that some IPFs may take more
than 10 minutes to collect this information, especially in the first
year of reporting; however, we believe that many IPFs would require
less than 10 minutes. In addition, we believe that many IPFs will be
able to submit similar responses in future years. Using the estimate of
10 minutes per IPF per year at $44.86/hour for a medical records and
health information technician, we estimate that this policy would
result in a total annual burden increase of 267 hours across all
participating IPFs (0.167 hours x 1,596 IPFs) at a cost of $11,956.63
(267 hours x $44.86/hour).
[[Page 21306]]
In sections V.D.3 and V.D.4 of this proposed rule, we propose to
adopt the Screening for Social Drivers of Health measure and the
associated Screen Positive Rate for Social Drivers of Health measure
beginning with a voluntary data submission in CY 2025 (reflecting care
provided in CY 2024). We described our anticipated burden for
administering the screening in the previous section because this burden
would accrue during CY 2024. The burden associated with reporting each
of these measures to CMS would occur during CY 2025. We anticipate that
the burden for reporting the two measures would be consistent with the
burden for other web-based submissions, such as the Facility Commitment
to Health Equity measure described previously in this section and for
similar measures adopted in the Ambulatory Surgical Center Quality
Reporting (ASCQR) Program (OMB control number 0938-1270; CMS-10530),
which we have estimated to have a reporting burden of 0.167 hours per
IPF. We note that for the voluntary reporting year we have estimated
only 50 percent of IPFs would report these data. Therefore, we estimate
the burden associated with reporting of each of these measures to be
133 hours (0.167 hr. x 798 IPFs) at a cost of $5,966 (133 hr. x $44.86/
hr. for a medical records and health information technician) for the
voluntary reporting period. These estimates are summarized in Table 32.
A summary of our estimated changes in information collection burden
for CY 2025 is shown in Table 32.
Table 32--Total CY 2025 Facility Information Collection Burden Changes
--------------------------------------------------------------------------------------------------------------------------------------------------------
Number Estimated Time per Annual time
Measure/response description respondents responses per Total annual response per facility Total annual Total annual
(facilities) facility responses (hours) (hours) time (hours) cost ($)
--------------------------------------------------------------------------------------------------------------------------------------------------------
Facility Commitment to Health Equity.... 1,596 1 1,596 0.167 0.167 267 11,956.63
Screening for Social Drivers of......... 798 1 798 0.167 0.167 133 5,966.38
--------------------------------------------------------------------------------------------------------------------------------------------------------
Health
--------------------------------------------------------------------------------------------------------------------------------------------------------
Screen Positive Rate for Social Drivers 798 1 798 0.167 0.167 133 5,966.38
of Health..............................
---------------------------------------------------------------------------------------------------------------
Totals.............................. 1,596 3 3,192 0.167 0.167 533 23,889.39
--------------------------------------------------------------------------------------------------------------------------------------------------------
(2) Proposed Updates Affecting Patient Survey Burden
Beginning with CY 2025, IPFs would need to screen 100 percent of
their patients to prepare for required reporting of the Screening for
SDOH measure in CY 2026 (for the FY 2027 payment determination).
Therefore, we estimate that 100 percent of IPFs would screen 100
percent of their patients. We recognize that this may be an
overestimate as some IPFs may choose not to participate and some
patients may opt out of screening or be unable to provide responses;
however, we believe that the numbers of IPFs and patients opting out
will be relatively small and therefore 100 percent will be a reasonable
approximation.
Using the facility counts, patient counts, and average hourly
earnings described previously, we estimate the burden of surveying IPF
patients for health-related social needs (HRSNs) under the Screening
for Social Drivers of Health and Screen Positive Rate for Social
Drivers of Health measures will be 66,414 hours (1,596 facilities x
1,261 patients per facility x 0.033 hours) at a cost of $1,375,433.94
(66,414 hours x $20.71/hour). We note that 16,603.59 hours and
$343,960.29 of this burden was previously accounted for in our analysis
of the burden of the voluntary reporting period. Therefore, the
incremental burden of switching to required reporting is 49,810.41
hours and $1,031,473.65.
Additionally, in section V.D.5 of this proposed rule, we are
proposing to adopt the Psychiatric Inpatient Experience (PIX) survey
measure beginning with voluntary data submission in CY 2026. To prepare
for data submission in 2026, IPFs would begin administering this survey
in CY 2025. We believe 50 percent of IPFs would begin collecting these
data for the voluntary data submission period. We note that we have
proposed to allow IPFs with more than 300 eligible discharges to
sample, which would require these facilities to survey 300 patients.
Because the questions on the PIX survey are similar in content and
response options to the questions on the Hospital Consumer Assessment
of Healthcare Providers and Systems (HCAHPS) survey, we believe that it
would take patients a similar amount of time to respond to these
questions. In the Information Collection Request associated with OMB
control number 0938-0981 (CMS-10102), we have estimated this time to be
7.25 minutes.
Therefore, we believe that the burden associated with conducting
the PIX survey in CY 2025 would be 28,967.4 hours (50 percent of 1,596
facilities x 300 patients/facility x 0.121 hours) at a cost of
$599,914.85 (28,967.4hours x $20.71/hour).
Our estimates for the CY 2025 total patient survey burden changes
are summarized in Table 33.
Table 33--Total CY 2025 Patient Survey Burden Changes
----------------------------------------------------------------------------------------------------------------
Total Total annual Total annual
responses time (hours) cost ($)
----------------------------------------------------------------------------------------------------------------
Screening for SDOH.............................................. 1,509,417 49,810.41 1,031,473.65
PIX............................................................. 239,400 28,967.4 599,914.85
-----------------------------------------------
Totals...................................................... 1,748,817 78,777.81 1,631,388.5
----------------------------------------------------------------------------------------------------------------
[[Page 21307]]
(d) Proposals Affecting Burden Beginning With CY 2026
(1) Proposed Updates Affecting Facility Reporting Burden
Beginning with CY 2026 data submission (affecting the FY 2027
payment determination), we estimate that 100 percent of IPFs would
submit data on the Screening for Social Drivers of Health measure and
Screen Positive Rate for Social Drivers of Health measure. Because we
have already accounted for 50 percent of facilities submitting
voluntary data on these measures, the incremental burden is the burden
associated with the remaining 50 percent of facilities submitting data;
that is, we estimate this burden to be 266 hours at a cost of
$11,932.76. We also believe that 50 percent of facilities will submit
data on the PIX measure for the voluntary reporting period in CY 2025.
Because the data for this measure would require calculating an average
of scores across a sample of patient surveys, we anticipate that the
information collection and reporting burden for this measure would be
approximately 15 minutes (0.25 hours) per patient for whom they are
reporting data. The burden associated with reporting the Screening for
Social Drivers of Health measure, the Screen Positive Rate for Social
Drivers of Health measure, and the PIX survey measure to CMS is
described in Table 34.
Table 34--Total CY 2026 Facility Information Collection Burden Changes
--------------------------------------------------------------------------------------------------------------------------------------------------------
Number Estimated Time per Annual time
Measure/response description respondents responses per Total annual response per facility Total annual Total annual
(facilities) facility responses (hours) (hours) time (hours) cost ($)
--------------------------------------------------------------------------------------------------------------------------------------------------------
Screening for Social Drivers of Health.. 798 1 798 0.167 0.167 133 5,966.38
Screen Positive Rate for Social `Drivers 798 1 798 0.167 0.167 133 5,966.38
of Health..............................
PIX Survey.............................. 798 300 239,400 0.25 75 59,850 2,684,871.00
---------------------------------------------------------------------------------------------------------------
Totals.............................. 798 302 240,996 Varies 75.33 60,116 2,696,803.76
--------------------------------------------------------------------------------------------------------------------------------------------------------
(2) Proposed Updates Affecting Patient Survey Burden
Because reporting the PIX measure would be required for FY 2028
payment determination, the remaining 50 percent of facilities (those
which did not participate in the voluntary reporting period) would
begin surveying patients in CY 2026. To prepare for data submission of
the PIX survey measure in CY 2027, IPFs that had not previously begun
administering the PIX survey would begin administering this survey in
CY 2026. The incremental burden of these 50 percent of facilities
administering the survey would be equivalent to the burden associated
with the 50 percent of facilities that participated in the voluntary
reporting in CY 2025. These estimates are summarized in Table 35.
Table 35--Total CY 2026 Patient Survey Burden Changes
----------------------------------------------------------------------------------------------------------------
Total Total annual Total annual
responses time (hours) cost ($)
----------------------------------------------------------------------------------------------------------------
PIX.......................................................... 239,400 28,967.4 599,914.85
----------------------------------------------------------------------------------------------------------------
(e.) Proposals Affecting Facility Reporting Burden Beginning With CY
2027
For data submission occurring in CY 2027, submission on the PIX
survey measure would be required, therefore, we believe that an
additional 50 percent of facilities would report the measure (that is,
the 50 percent of facilities not previously accounted for under the
voluntary reporting period). Therefore, we estimate that the
incremental increase in burden for IPFs associated with this
requirement would be reporting by the 50 percent of facilities that had
not previously reported the PIX survey measure. This burden is depicted
in Table 36.
Table 36--Total CY 2027 Facility Information Collection Burden Changes
--------------------------------------------------------------------------------------------------------------------------------------------------------
Number Estimated Time per Annual time per
Measure/response description respondents responses per Total annual response facility Total annual Total annual
(facilities) facility responses (hours) (hours) time (hours) cost ($)
--------------------------------------------------------------------------------------------------------------------------------------------------------
PIX Survey....................... 798 300 239,400 0.25 75 59,850 2,684,871.00
--------------------------------------------------------------------------------------------------------------------------------------------------------
3. Overall Burden Summary
Table 37 summarizes the incremental changes in burden for IPFs
associated with proposed policies for data collection and submission in
CYs 2024 through 2027 as well as updates to our estimated wage rate,
facility counts, and case counts.
Table 37--Proposed Incremental Changes in Facility Burden
----------------------------------------------------------------------------------------------------------------
Total Total annual Total annual
responses time (hours) cost ($)
----------------------------------------------------------------------------------------------------------------
Changes Associated with CY 2024 Updates......................... (2,502,332) (625,746) (17,837,264)
[[Page 21308]]
Changes Associated with CY 2025 Updates......................... 3,192 533 23,889
Changes Associated with CY 2026 Updates......................... 240,996 60,116 2,696,804
Changes Associated with CY 2027 Updates......................... 239,400 59,850 2,684,871
-----------------------------------------------
Total....................................................... (2,018,744) (505,247) (12,431,700)
----------------------------------------------------------------------------------------------------------------
Table 38 summarizes the incremental changes in burden for patients
due to data collection associated with proposed policies for data
collection and submission in CYs 2024 through CY 2026.
Table 38--Proposed Incremental Changes in Survey Burden for Patients
----------------------------------------------------------------------------------------------------------------
----------------------------------------------------------------------------------------------------------------
Changes Associated with CY 2024 Updates......................... 503,139 16,604 343,860
Changes Associated with CY 2025 Updates......................... 1,748,817 78,778 1,631,339
Changes Associated with CY 2026 Updates......................... 239,400 28,967 599,915
-----------------------------------------------
Totals...................................................... 2,491,356 124,349 2,575,114
----------------------------------------------------------------------------------------------------------------
C. Submission of PRA-Related Comments
We have submitted a copy of this proposed rule's information
collection requirements to OMB for their review. The requirements are
not effective until they have been approved by OMB.
To obtain copies of the supporting statement and any related forms
for the proposed collections discussed above, please visit the CMS
website at https://www.cms.gov/regulations-and-guidance/legislation/paperworkreductionactof1995/pra-listing, or call the Reports Clearance
Office at 410-786-1326.
We invite public comments on these potential information collection
requirements. If you wish to comment, please submit your comments
electronically as specified in the DATES and ADDRESSES sections of this
proposed rule and identify the rule (CMS-1783-P), the ICR's CFR
citation, and OMB control number.
VII. Response to Comments
Because of the large number of public comments, we normally receive
on Federal Register documents, we are not able to acknowledge or
respond to them individually. We will consider all comments we receive
by the date and time specified in the DATES section of this preamble,
and, when we proceed with a subsequent document, we will respond to the
comments in the preamble to that document.
VIII. Regulatory Impact Analysis
A. Statement of Need
This rule proposes updates to the prospective payment rates for
Medicare inpatient hospital services provided by IPFs for discharges
occurring during FY 2024 (October 1, 2023 through September 30, 2024).
We propose to apply the proposed 2021-based IPF market basket increase
of 3.2 percent, less the productivity adjustment of 0.2 percentage
point as required by 1886(s)(2)(A)(i) of the Act for a proposed total
FY 2024 payment rate update of 3.0 percent. In this proposed rule, we
propose to update the outlier fixed dollar loss threshold amount,
update the IPF labor-related share, and update the IPF wage index to
reflect the FY 2024 hospital inpatient wage index.
B. Overall Impact
We have examined the impacts of this rule as required by Executive
Order 12866 on Regulatory Planning and Review (September 30, 1993),
Executive Order 13563 on Improving Regulation and Regulatory Review
(January 18, 2011), the Regulatory Flexibility Act (RFA) (September 19,
1980, Pub. L. 96-354), section 1102(b) of the Social Security Act,
section 202 of the Unfunded Mandates Reform Act of 1995 (March 22,
1995; Pub. L. 104-4), Executive Order 13132 on Federalism (August 4,
1999), and the Congressional Review Act (5 U.S.C. 804(2)).
Executive Orders 12866 and 13563 direct agencies to assess all
costs and benefits of available regulatory alternatives and, if
regulation is necessary, to select regulatory approaches that maximize
net benefits (including potential economic, environmental, public
health and safety effects, distributive impacts, and equity). Section
3(f) of Executive Order 12866 defines a ``significant regulatory
action'' as an action that is likely to result in a rule: (1) having an
annual effect on the economy of $100 million or more in any 1 year, or
adversely and materially affecting a sector of the economy,
productivity, competition, jobs, the environment, public health or
safety, or State, local or Tribal governments or communities; (2)
creating a serious inconsistency or otherwise interfering with an
action taken or planned by another agency; (3) materially altering the
budgetary impacts of entitlement grants, user fees, or loan programs or
the rights and obligations of recipients thereof; or (4) raising novel
legal or policy issues arising out of legal mandates, the President's
priorities, or the principles set forth in the Executive Order.
A regulatory impact analysis (RIA) must be prepared for major rules
with significant regulatory action/s and/or with significant effects as
per section 3(f)(1) ($100 million or more in any 1 year). We estimate
that the total impact of these changes for FY 2024 payments compared to
FY 2023 payments will be a net increase of approximately $55 million.
This reflects a $85 million increase from the update to the payment
rates (+$90 million from the 4th quarter 2022 IGI forecast of the
proposed 2021-based IPF market basket of 3.2 percent, and -$5 million
for the productivity adjustment of 0.2 percentage point), as well as a
$30 million decrease as a result of the update to the outlier threshold
amount. Outlier payments are estimated to change from 3.0 percent in FY
2023 to 2.0 percent of total estimated IPF payments in FY 2024.
Based on our estimates, OMB's Office of Information and Regulatory
Affairs has determined that this rulemaking is ``significant.'' '' per
section 3(f)(1) as measured by the $100 million threshold
[[Page 21309]]
or more in any 1 year. Accordingly, we have prepared a Regulatory
Impact Analysis that to the best of our ability presents the costs and
benefits of the rulemaking. Therefore, OMB has reviewed these proposed
regulations, and we have provided the following assessment of their
impact.
C. Detailed Economic Analysis
In this section, we discuss the historical background of the IPF
PPS and the impact of this proposed rule on the Federal Medicare budget
and on IPFs.
1. Budgetary Impact
As discussed in the November 2004 and RY 2007 IPF PPS final rules,
we applied a budget neutrality factor to the Federal per diem base rate
and ECT payment per treatment to ensure that total estimated payments
under the IPF PPS in the implementation period would equal the amount
that would have been paid if the IPF PPS had not been implemented. This
Budget neutrality factor included the following components: Outlier
adjustment, stop loss adjustment, and the behavioral offset. As
discussed in the RY 2009 IPF PPS notice (73 FR 25711), the stop-loss
adjustment is no longer applicable under the IPF PPS.
As discussed in section III.D.1 of this proposed rule, we propose
to update the wage index and labor-related share in a budget neutral
manner by applying a wage index budget neutrality factor to the Federal
per diem base rate and ECT payment per treatment. Therefore, the
budgetary impact to the Medicare program of this proposed rule would be
due to the market basket update for FY 2024 of 3.2 percent (see section
III.A.2 of this proposed rule) less the productivity adjustment of 0.2
percentage point required by section 1886(s)(2)(A)(i) of the Act and
the update to the outlier fixed dollar loss threshold amount.
We estimate that the FY 2024 impact will be a net increase of $55
million in payments to IPF providers. This reflects an estimated $85
million increase from the update to the payment rates and a $30 million
decrease due to the update to the outlier threshold amount to set total
estimated outlier payments at 2.0 percent of total estimated payments
in FY 2024. This estimate does not include the implementation of the
required 2.0 percentage point reduction of the productivity-adjusted
market basket update factor for any IPF that fails to meet the IPF
quality reporting requirements (as discussed in section III.B.2. of
this proposed rule).
2. Impact on Providers
To show the impact on providers of the changes to the IPF PPS
discussed in this proposed rule, we compare estimated payments under
the proposed IPF PPS rates and factors for FY 2024 versus those under
FY 2023. We determined the percent change in the estimated FY 2024 IPF
PPS payments compared to the estimated FY 2023 IPF PPS payments for
each category of IPFs. In addition, for each category of IPFs, we have
included the estimated percent change in payments resulting from the
proposed update to the outlier fixed dollar loss threshold amount; the
updated wage index data including the proposed labor-related share; and
the proposed market basket update for FY 2024, as reduced by the
proposed productivity adjustment according to section 1886(s)(2)(A)(i)
of the Act.
To illustrate the impacts of the proposed FY 2024 changes in this
proposed rule, our analysis begins with FY 2022 IPF PPS claims (based
on the 2022 MedPAR claims, December 2022 update). We estimate FY 2024
IPF PPS payments using these 2022 claims, the finalized FY 2023 IPF PPS
Federal per diem base rates, and the finalized FY 2023 IPF PPS patient
and facility level adjustment factors (as published in the FY 2023 IPF
PPS final rule (87 FR 46846). We then estimate the FY 2024 outlier
payments based on these simulated FY 2023 IPF PPS payments using the
same methodology as the same methodology that we used to set the
initial outlier threshold amount in the RY 2007 IPF PPS final rule (71
FR 27072 and 27073), which is also the same methodology that we used to
update the outlier threshold amounts for years 2008 through 2022, where
total outlier payments are maintained at 2 percent of total estimated
FY 2023 IPF PPS payments. We note that in the FY 2023 final rule (87 FR
46862 through 46864) we excluded providers from our simulation of IPF
PPS payments for FY 2022 and FY 2023 if their change in estimated
average cost per day was outside 3 standard deviations from the mean.
As discussed in section III.E.2 of this FY 2024 IPF PPS proposed rule,
we are not proposing to apply this methodology for FY 2024.
Each of the following changes is added incrementally to this
baseline model in order for us to isolate the effects of each change:
The proposed update to the outlier fixed dollar loss
threshold amount.
The proposed FY 2024 IPF wage index, and the proposed FY
2024 labor-related share.
The proposed market basket update for FY 2024 of 3.2
percent less the proposed productivity adjustment of 0.2 percentage
point in accordance with section 1886(s)(2)(A)(i) of the Act for a
payment rate update of 3.0 percent.
Our proposed column comparison in Table 39 illustrates the percent
change in payments from FY 2023 (that is, October 1, 2022, to September
30, 2023) to FY 2024 (that is, October 1, 2023, to September 30, 2024)
including all the proposed payment policy changes.
Table 39--FY 2024 IPF PPS Proposed Payment Impacts
----------------------------------------------------------------------------------------------------------------
Wage index
Facility by type Number of Outlier FY24, LRS, and Total percent
facilities 5% Cap change\1\
(1) (2) (3) (4) (5)
----------------------------------------------------------------------------------------------------------------
All Facilities.................................. 1,481 -1.0 0.0 1.9
Total Urban..................................... 1,209 -1.1 0.1 2.0
Urban unit.................................. 695 -1.6 0.2 1.6
Urban hospital.............................. 514 -0.5 0.0 2.5
Total Rural..................................... 272 -0.6 -0.8 1.5
Rural unit.................................. 211 -0.6 -0.8 1.6
Rural hospital.............................. 61 -0.7 -0.9 1.3
----------------------------------------------------------------------------------------------------------------
[[Page 21310]]
By Type of Ownership:
----------------------------------------------------------------------------------------------------------------
Freestanding IPFs
----------------------------------------------------------------------------------------------------------------
Urban Psychiatric Hospitals
Government.................................. 117 -1.8 0.1 1.2
Non-Profit.................................. 98 -0.5 0.5 3.0
For-Profit.................................. 299 -0.3 -0.2 2.5
Rural Psychiatric Hospitals
Government.................................. 31 -1.3 -0.6 1.1
Non-Profit.................................. 13 -2.4 -0.2 0.3
For-Profit.................................. 17 0.0 -1.3 1.6
----------------------------------------------------------------------------------------------------------------
IPF Units
----------------------------------------------------------------------------------------------------------------
Urban
Government.................................. 100 -2.9 0.6 0.6
Non-Profit.................................. 455 -1.5 0.4 1.9
For-Profit.................................. 140 -0.7 -0.6 1.6
Rural
Government.................................. 51 -0.4 -0.7 1.9
Non-Profit.................................. 118 -0.7 -0.7 1.6
For-Profit.................................. 42 -0.4 -1.1 1.4
----------------------------------------------------------------------------------------------------------------
By Teaching Status:
----------------------------------------------------------------------------------------------------------------
Non-teaching.................................... 1,283 -0.8 -0.2 2.0
Less than 10% interns and residents to beds..... 101 -1.8 0.9 2.1
10% to 30% interns and residents to beds........ 67 -2.4 0.4 1.0
More than 30% interns and residents to beds..... 30 -2.1 0.5 1.4
----------------------------------------------------------------------------------------------------------------
By Region:
----------------------------------------------------------------------------------------------------------------
New England..................................... 105 -1.4 -0.7 0.9
Mid-Atlantic.................................... 204 -1.7 1.1 2.4
South Atlantic.................................. 228 -0.6 0.1 2.5
East North Central.............................. 243 -0.6 -0.3 2.1
East South Central.............................. 149 -0.7 -0.8 1.4
West North Central.............................. 105 -1.9 -0.3 0.7
West South Central.............................. 215 -0.6 -0.1 2.3
Mountain........................................ 106 -0.6 -0.9 1.4
Pacific......................................... 126 -1.3 0.4 2.1
----------------------------------------------------------------------------------------------------------------
By Bed Size:
----------------------------------------------------------------------------------------------------------------
Psychiatric Hospitals
Beds: 0-24.................................. 92 -0.8 -0.4 1.7
Beds: 25-49................................. 84 -0.2 -0.8 2.1
Beds: 50-75................................. 86 -0.1 -0.2 2.7
Beds: 76+................................... 313 -0.6 0.1 2.5
Psychiatric Units
Beds: 0-24.................................. 487 -1.1 -0.3 1.6
Beds: 25-49................................. 241 -1.2 0.3 2.1
Beds: 50-75................................. 106 -1.8 0.0 1.1
Beds: 76+................................... 72 -2.2 0.7 1.5
----------------------------------------------------------------------------------------------------------------
\1\ This column includes the impact of the updates in columns (3) through (4) above, and of the proposed IPF
market basket update factor for FY 2024 (3.2 percent), reduced by 0.2 percentage point for the productivity
adjustment as required by section 1886(s)(2)(A)(i) of the Act.
3. Impact Results
Table 39 displays the results of our analysis. The table groups
IPFs into the categories listed here based on characteristics provided
in the Provider of Services file, the IPF PSF, and cost report data
from the Healthcare Cost Report Information System:
Facility Type.
Location.
Teaching Status Adjustment.
Census Region.
Size.
The top row of the table shows the overall impact on the 1,481 IPFs
included in the analysis. In column 2, we present the number of
facilities of each type that had information available in the PSF, had
claims in the MedPAR dataset for FY 2022.
[[Page 21311]]
In column 3, we present the effects of the update to the outlier
fixed dollar loss threshold amount. We estimate that IPF outlier
payments as a percentage of total IPF payments are 3.0 percent in FY
2023. Therefore, we propose to adjust the outlier threshold amount to
set total estimated outlier payments equal to 2.0 percent of total
payments in FY 2024. The estimated change in total IPF payments for FY
2024, therefore, includes an approximate 1.0 percent decrease in
payments because we would expect the outlier portion of total payments
to decrease from approximately 3.0 percent to 2.0 percent.
The overall impact of the estimated decrease to payments due to
updating the outlier fixed dollar loss threshold (as shown in column 3
of Table 3), across all hospital groups, is a 1.0 percent decrease. The
largest decrease in payments due to this change is estimated to be 2.9
percent for urban government unit IPFs.
In column 4, we present the effects of the proposed budget-neutral
update to the IPF wage index, the proposed Labor-Related Share (LRS),
and the 5-percent cap on any decrease to a provider's wage index from
its wage index in the prior year. This represents the effect of using
the concurrent hospital wage data as discussed in section III.D.1.a of
this proposed rule. That is, the impact represented in this column
reflects the proposed update from the FY 2023 IPF wage index to the
proposed FY 2024 IPF wage index, which includes basing the FY 2024 IPF
wage index on the FY 2024 pre-floor, pre-reclassified IPPS hospital
wage index data, applying a 5-percent cap on any decrease to a
provider's wage index from its wage index in the prior year, and
updating the LRS from 77.4 percent in FY 2023 to 78.5 percent in FY
2024. We note that there is no projected change in aggregate payments
to IPFs, as indicated in the first row of column 4; however, there
would be distributional effects among different categories of IPFs. For
example, we estimate the largest increase in payments to be 1.1 percent
for Mid-Atlantic IPFs, and the largest decrease in payments to be 1.3
percent for freestanding rural for-profit IPFs.
Column 5 incorporates the proposed market basket update of 3.2
percent reduced by 0.2 percentage point for the productivity adjustment
as required by section 1886(s)(2)(A)(i) of the Act. This includes the
proposal to rebase the IPF PPS market basket to reflect a 2021 base
year.
Overall, IPFs are estimated to experience a net increase in
payments as a result of the updates in this proposed rule. IPF payments
are estimated to increase by 2.0 percent in urban areas and 1.5 percent
in rural areas. The largest payment increases are estimated at 3.0
percent for freestanding urban non-profit IPFs.
4. Effect on Beneficiaries
Under the FY 2024 IPF PPS, IPFs will continue to receive payment
based on the average resources consumed by patients for each day. Our
longstanding payment methodology reflects the differences in patient
resource use and costs among IPFs, as required under section 124 of the
BBRA. We expect that updating IPF PPS rates in this proposed rule will
improve or maintain beneficiary access to high quality care by ensuring
that payment rates reflect the best available data on the resources
involved in inpatient psychiatric care and the costs of these
resources. We continue to expect that paying prospectively for IPF
services under the FY 2024 IPF PPS will enhance the efficiency of the
Medicare program.
As discussed in sections V.D.3 and V.D.4 of this proposed rule, we
expect that additional proposed IPFQR Program measures will support
improving care for patients with health-related social needs. We also
believe that our proposed data validation pilot is an important step
towards ensuring that the data beneficiaries and their caregivers
access on Care Compare (or a successor CMS website) are accurate and
reliable. Based on the input from patients and their caregivers
regarding the importance of having a patient experience care measure
for the IPF setting in which they note many benefits (including, but
not limited to helping patients select facilities in which to receive
care, providing patients an opportunity to be heard, and increasing
alignment between general acute and acute psychiatric settings). We
believe that our proposed PIX survey measure will have positive effects
on patients and their caregivers. Therefore, we expect that the
proposed updates to the IPFQR Program will improve quality for
beneficiaries.
5. Effects of the Updates to the IPFQR Program
In section V.D.3 of this proposed rule, we propose to adopt the
Screening for Social Drivers of Health measure for the IPFQR Program
beginning with voluntary reporting of CY 2024 data, and with required
reporting of CY 2025 data for the FY 2027 payment determination. For
IPFs that are not currently administering some screening mechanism and
elect to begin doing so as a result of this policy, there will be some
non-recurring costs associated with changes in workflow and information
systems to collect the data. The extent of these costs is difficult to
quantify as different facilities may utilize different modes of data
collection (for example, paper-based, electronically patient-directed
and clinician-facilitated). In addition, depending on the method of
data collection utilized, the time required to complete the survey may
add a negligible amount of time to patient visits.
In section V.D.5 of this proposed rule, we are proposing to adopt
the Psychiatric Inpatient Experience (PIX) survey measure. There may be
some non-recurring costs associated with changes in workflow and
information systems to administer this survey and collect the data. The
extent of these costs is difficult to quantify as different facilities
currently have different practices for surveying patients to gather
information on their experiences of care.
In addition, for the IPFQR Program, we propose to adopt the
Facility Commitment to Health Equity measure and the Screen Positive
for Social Drivers of Health measure, as well as to update the COVID-19
Vaccination Coverage Among HCP measure. These updates would not impact
providers workflows or information systems to collect or report the
data, and because they represent processes of care or structural data
that the IPFs would already have in place, we do not believe they would
incur costs for providers beyond the recurring information collection
costs (described in section VI.A of this proposed rule).
Finally, we propose to remove two chart-abstracted measures from
the IPFQR Program. We believe that the impact of removing the Tobacco
Use Brief Intervention Provided or Offered and Tobacco Use Brief
Intervention Provided (TOB-2/2a) measure would be minimal as we do not
believe that IPFs would update their workflow to no longer provide
brief tobacco cessation interventions to patients who use tobacco.
However, we believe that there may be some simplification of workflows
and clinical documentation associated with the removal of the Patients
Discharged on Multiple Antipsychotic Medications with Appropriate
Justification (HBIPS-5) measure because IPFs would no longer have to
ensure the presence of appropriate documentation for the use of
multiple antipsychotics. For more information on the updated clinical
guidelines regarding polypharmacy for patients with schizophrenia, we
refer
[[Page 21312]]
readers to section V.F.2.a of this proposed rule.
As discussed in section III.B.2 of this proposed rule and in
accordance with section 1886(s)(4)(A)(i) of the Act, we will apply a 2-
percentage point reduction to the FY 2024 market basket update for IPFs
that have failed to comply with the IPFQR Program requirements for FY
2024, including reporting on the required measures. In section III.B.2
of this proposed rule, we discuss how the 2-percentage point reduction
will be applied. For the FY 2023 payment determination, of the 1,596
IPFs eligible for the IPFQR Program, 6 IPFs did not receive the full
market basket update because of the IPFQR Program; 2 of these IPFs
chose not to participate and 4 did not meet the requirements of the
program. Thus, we estimate that the IPFQR Program will have a
negligible impact on overall IPF payments for FY 2024.
Based on the IPFQR Program proposals in this proposed rule, we
estimate a total decrease in burden of 505,247 hours across all IPFs,
resulting in a total decrease in information collection cost of
$12,431,700 across all IPFs. Further information on these estimates can
be found in section VI.A of this proposed rule.
We intend to closely monitor the effects of the IPFQR Program on
IPFs and help facilitate successful reporting outcomes through ongoing
stakeholder education, national trainings, and a technical help desk.
6. Regulatory Review Costs
If regulations impose administrative costs on private entities,
such as the time needed to read and interpret this proposed rule, we
should estimate the cost associated with regulatory review. Due to the
uncertainty involved with accurately quantifying the number of entities
that will be directly impacted and will review this proposed rule, we
assume that the total number of unique commenters on the most recent
IPF proposed rule will be the number of reviewers of this proposed
rule. For this FY 2024 IPF PPS proposed rule, the most recent IPF
proposed rule was the FY 2023 IPF PPS proposed rule, and we received
396 unique comments on this proposed rule. We acknowledge that this
assumption may understate or overstate the costs of reviewing this
proposed rule. It is possible that not all commenters reviewed the FY
2023 IPF proposed rule in detail, and it is also possible that some
reviewers chose not to comment on that proposed rule. For these
reasons, we thought that the number of commenters would be a fair
estimate of the number of reviewers who are directly impacted by this
proposed rule. We are soliciting comments on this assumption.
We also recognize that different types of entities are in many
cases affected by mutually exclusive sections of this proposed rule;
therefore, for the purposes of our estimate, we assume that each
reviewer reads approximately 50 percent of this proposed rule. Using
the May, 2021 mean (average) wage information from the BLS for medical
and health service managers (Code 11-9111), we estimate that the cost
of reviewing this proposed rule is $115.22 per hour, including overhead
and fringe benefits https://www.bls.gov/oes/current/oes119111.htm.
Assuming an average reading speed of 250 words per minute, we estimate
that it would take approximately 138 minutes (2.30 hours) for the staff
to review half of this proposed rule (34,500), which contains a total
of approximately 69,000 words. For each IPF that reviews the proposed
rule, the estimated cost is (2.30 x $115.22) or $265.01. Therefore, we
estimate that the total cost of reviewing this proposed rule is
$104,943.96 ($265.01 x 396 reviewers).
D. Alternatives Considered
The statute does not specify an update strategy for the IPF PPS and
is broadly written to give the Secretary discretion in establishing an
update methodology. We continue to believe it is appropriate to
routinely update the IPF PPS so that it reflects the best available
data about differences in patient resource use and costs among IPFs as
required by the statute. Therefore, we propose to: Update the IPF PPS
using the methodology published in the November 2004 IPF PPS final
rule; apply the proposed 2021-based IPF PPS market basket update for FY
2024 of 3.2 percent, reduced by the statutorily required proposed
productivity adjustment of 0.2 percentage point along with the proposed
wage index budget neutrality adjustment to update the payment rates;
and use a FY 2024 IPF wage index which uses the FY 2024 pre-floor, pre-
reclassified IPPS hospital wage index as its basis.
Lastly, we considered and are soliciting comments on alternative
methodologies that could be appropriate for establishing the FY 2024
outlier fixed dollar loss threshold.
E. Accounting Statement
As required by OMB Circular A-4 (www.whitehous.gov/sites/whitehouse.gov/files/omb/circulars/A4/A-4/pdf), in Table 40, we have
prepared an accounting statement showing the classification of the
expenditures associated with the updates to the IPF wage index and
payment rates in this proposed rule. Table 40 provides our best
estimate of the increase in Medicare payments under the IPF PPS as a
result of the changes presented in this proposed rule and is based on
1,481 IPFs with data available in the PSF and with claims in our FY
2022 MedPAR claims dataset. Lastly, Table 40 also includes our best
estimate of the costs of reviewing and understanding this proposed
rule.
Table 40--Accounting Statement: Classification of Estimated Costs and Transfers
----------------------------------------------------------------------------------------------------------------
Primary Units
estimate -------------------------------------------------------
Category ($million/
year) Year dollars Period covered
----------------------------------------------------------------------------------------------------------------
Regulatory Review Costs................. .11 FY 2021................... FY 2024.
Annualized Monetized Transfers from 55 FY 2024................... FY 2024.
Federal Government to IPF Medicare
Providers.
----------------------------------------------------------------------------------------------------------------
F. Regulatory Flexibility Act
The RFA requires agencies to analyze options for regulatory relief
of small entities if a rule has a significant impact on a substantial
number of small entities. For purposes of the RFA, small entities
include small businesses, nonprofit organizations, and small
governmental jurisdictions. Most IPFs and most other providers and
suppliers are small entities, either by nonprofit status or having
revenues of $8 million to $41.5 million or less in any 1 year.
[[Page 21313]]
Individuals and states are not included in the definition of a small
entity.
Because we lack data on individual hospital receipts, we cannot
determine the number of small proprietary IPFs or the proportion of
IPFs' revenue derived from Medicare payments. Therefore, we assume that
all IPFs are considered small entities.
The Department of Health and Human Services generally uses a
revenue impact of 3 to 5 percent as a significance threshold under the
RFA. As shown in Table 39, we estimate that the overall revenue impact
of this proposed rule on all IPFs is to increase estimated Medicare
payments by approximately 1.9 percent. As a result, since the estimated
impact of this proposed rule is a net increase in revenue across almost
all categories of IPFs, the Secretary has determined that this proposed
rule will have a positive revenue impact on a substantial number of
small entities.
In addition, section 1102(b) of the Act requires us to prepare a
regulatory impact analysis if a rule may have a significant impact on
the operations of a substantial number of small rural hospitals. This
analysis must conform to the provisions of section 603 of the RFA. For
purposes of section 1102(b) of the Act, we define a small rural
hospital as a hospital that is located outside of a metropolitan
statistical area and has fewer than 100 beds. As discussed in section
VIII.C.2 of this proposed rule, the rates and policies set forth in
this proposed rule will not have an adverse impact on the rural
hospitals based on the data of the 211 rural excluded psychiatric units
and 61 rural psychiatric hospitals in our database of 1,481 IPFs for
which data were available. Therefore, the Secretary has determined that
this proposed rule will not have a significant impact on the operations
of a substantial number of small rural hospitals.
G. Unfunded Mandate Reform Act (UMRA)
Section 202 of the Unfunded Mandates Reform Act of 1995 (UMRA) also
requires that agencies assess anticipated costs and benefits before
issuing any rule whose mandates require spending in any 1 year of $100
million in 1995 dollars, updated annually for inflation. In 2023, that
threshold is approximately $177 million. This proposed rule does not
mandate any requirements for State, local, or Tribal governments, or
for the private sector. This proposed rule would not impose a mandate
that will result in the expenditure by State, local, and Tribal
governments, in the aggregate, or by the private sector, of more than
$177 million in any 1 year.
H. Federalism
Executive Order 13132 establishes certain requirements that an
agency must meet when it promulgates a proposed rule that imposes
substantial direct requirement costs on State and local governments,
preempts State law, or otherwise has Federalism implications. This
proposed rule does not impose substantial direct costs on State or
local governments or preempt State law.
Chiquita Brooks-LaSure, Administrator of the Centers for Medicare &
Medicaid Services, approved this document on March 30, 2023.
List of Subjects in 42 CFR Part 412
Administrative practice and procedure, Health facilities, Medicare,
Puerto Rico, Reporting and recordkeeping requirements.
For the reasons set forth in the preamble, the Centers for Medicare
& Medicaid Services proposes to amend 42 CFR part 412 as set forth
below:
PART 412--PROSPECTIVE PAYMENT SYSTEMS PROSPECTIVE PAYMENT SYSTEMS
FOR INPATIENT HOSPITAL SERVICES
0
1. The authority citation for part 412 continues to read as follows:
Authority: 42 U.S.C. 1302 and 1395hh.
0
2. Section 412.25 is amended by revising paragraph (c)(2) to read as
follows:
Sec. 412.25 Excluded hospital units: Common requirements.
* * * * *
(c) * * *
(2) The status of an IPF unit may be changed from not excluded to
excluded or excluded to not excluded at any time during a cost
reporting period, but only if the hospital notifies the fiscal
intermediary and the CMS Regional Office in writing of the change at
least 30 days before the date of the change, and maintains the
information needed to accurately determine costs that are or are not
attributable to the IPF unit. A change in the status of an IPF unit
from not excluded to excluded or excluded to not excluded that is made
during a cost reporting period must remain in effect for the rest of
that cost reporting period.
* * * * *
0
3. Section 412.433 is added to read as follows:
Sec. 412.433 Procedural requirements under the IPFQR Program.
(a) Statutory authority. Section 1886(s)(4) of the Act requires the
Secretary to implement a quality reporting program for inpatient
psychiatric hospitals and psychiatric units. Under section 1886(s)(4)
of the act, for an IPF paid under the IPF PPS that fails to submit data
required for the quality measures selected by the Secretary in a form
and manner and at a time specified by the Secretary, we reduce the
otherwise applicable annual update to the standard Federal rate by 2.0
percentage points with respect to the applicable fiscal year.
(b) Participation in the IPFQR Program. To participate in the IPFQR
Program, an IPF (as defined under Sec. 412.402) that is paid under the
IPF PPS must:
(1) Register on the QualityNet website before beginning to report
data;
(2) Identify and register a QualityNet security official as part of
the registration process under paragraph (b)(1) of this section; and
(3) Submit a notice of participation (NOP).
(c) Withdrawal from the IPFQR Program. An IPF may withdraw from the
IPFQR Program by changing the NOP status in the secure portion of the
QualityNet website. The IPF may withdraw at any time up to and
including August 15 before the beginning of each respective payment
determination year. A withdrawn IPF is subject to a reduced annual
payment update as specified under paragraph (a) of this section and is
required to renew participation as specified in paragraph (b) of this
section in order to participate in any future year of the IPFQR
Program.
(d) Submission of IPFQR Program data. General rule. Except as
provided in paragraph (f) of this section, IPFs that participate in the
IPFQR Program must submit to CMS data on measures selected under
section 1886(s)(4)(D) of the Act and specified non-measure data in a
form and manner, and at a time specified by CMS.
(e) Quality measure updates, retention, and removal. (1) CMS uses
rulemaking to make substantive updates to the specifications of
measures used in the IPFQR Program
(2) General rule for the retention of Quality Measures. Quality
measures adopted for the IPFQR Program measure set for a previous
payment determination year are retained for use in subsequent payment
determination years, except when they are removed, suspended, or
modified as set forth in paragraph (3) of this section.
[[Page 21314]]
(3) Measure removal, suspension, or modification through the
rulemaking process. CMS will use the regular rulemaking process to
remove, suspend, or modify quality measures in the IPFQR Program to
allow for public comment.
(i) Factors for consideration in removal or replacement of quality
measures. CMS will weigh whether to remove or modify measures based on
the following factors:
(A) Factor 1: Measure performance among IPFs is so high and
unvarying that meaningful distinctions and improvements in performance
can no longer be made;
(B) Factor 2: Measure does not align with current clinical
guidelines or practice;
(C) Factor 3: Measure can be replaced by a more broadly applicable
measure (across settings or populations) or a measure that is more
proximal in time to desired patient outcomes for the particular topic;
(D) Factor 4: Measure performance or improvement does not result in
better patient outcomes;
(E) Factor 5: Measure can be replaced by a measure that is more
strongly associated with desired patient outcomes for the particular
topic;
(F) Factor 6: Measure collection or public reporting leads to
negative unintended consequences other than patient harm;
(G) Factor 7: Measure is not feasible to implement as specified;
and
(H) Factor 8: The costs associated with a measure outweigh the
benefit of its continued use in the program.
(ii) Retention. CMS may retain a quality measure that meets one or
more of the measure removal factors described in paragraph (i) of this
subsection if the continued collection of data on the quality measure
would align with other CMS and HHS policy goals, align with other CMS
programs, or support efforts to move IPFs toward reporting electronic
measures.
(f) Extraordinary circumstances exception. CMS may grant an
exception to one or more data submissions deadlines and requirements in
the event of extraordinary circumstances beyond the control of the IPF,
such as when an act of nature affects an entire region or locale or a
systemic problem with one of CMS's data collection systems directly or
indirectly affects data submission. CMS may grant an exception as
follows:
(1) Upon request by the IPF.
(2) At the discretion of CMS. CMS may grant exceptions to IPFs that
have not requested them when CMS determines that an extraordinary
circumstance has occurred.
(g) Public reporting of IPFQR Program data. Data that an IPF
submits to CMS for the IPFQR Program will be made publicly available on
a CMS website after providing the IPF an opportunity to review the data
to be made public. IPFs will have a period of 30 days to review and
submit corrections to errors resulting from CMS calculations prior to
the data being made public.
Dated: March 31, 2023.
Xavier Becerra,
Secretary, Department of Health and Human Services.
[FR Doc. 2023-07122 Filed 4-4-23; 4:15 pm]
BILLING CODE 4120-01-P