Medicare Program; FY 2020 Inpatient Psychiatric Facilities Prospective Payment System and Quality Reporting Updates for Fiscal Year Beginning October 1, 2019 (FY 2020), 38424-38482 [2019-16370]
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Federal Register / Vol. 84, No. 151 / Tuesday, August 6, 2019 / Rules and Regulations
DEPARTMENT OF HEALTH AND
HUMAN SERVICES
Centers for Medicare & Medicaid
Services
42 CFR Part 412
[CMS–1712–F]
RIN 0938–AT69
Medicare Program; FY 2020 Inpatient
Psychiatric Facilities Prospective
Payment System and Quality
Reporting Updates for Fiscal Year
Beginning October 1, 2019 (FY 2020)
Centers for Medicare &
Medicaid Services (CMS), HHS.
ACTION: Final rule.
AGENCY:
This final rule updates the
prospective payment rates, the outlier
threshold, and the wage index for
Medicare inpatient hospital services
provided by Inpatient Psychiatric
Facilities (IPFs), which include
psychiatric hospitals and excluded
psychiatric units of an inpatient
prospective payment system hospital or
critical access hospital. Additionally,
this final rule revises and rebases the
IPF market basket to reflect a 2016 base
year and removes the IPF Prospective
Payment System (PPS) 1-year lag of the
wage index data. Finally, this final rule
implements updates to the Inpatient
Psychiatric Facilities Quality Reporting
Program. These changes will be effective
for IPF discharges beginning during the
fiscal year (FY) from October 1, 2019
through September 30, 2020 (FY 2020).
DATES: These regulations are effective
on October 1, 2019.
FOR FURTHER INFORMATION CONTACT: The
IPF Payment Policy mailbox at
IPFPaymentPolicy@cms.hhs.gov for
general information.
Mollie Knight, (410) 786–7948 or
Hudson Osgood, (410) 786–7897, for
information regarding the market basket
rebasing, update, or the labor related
share.
Theresa Bean, (410) 786–2287 or
James Hardesty, (410) 786–2629, for
information regarding the regulatory
impact analysis.
James Poyer, (410) 786–2261 or Jeffrey
Buck, (410) 786–0407, for information
regarding the inpatient psychiatric
facility quality reporting program.
SUPPLEMENTARY INFORMATION:
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SUMMARY:
Availability of Certain Tables
Exclusively Through the Internet on the
CMS Website
Addendum A to this final rule
summarizes the FY 2020 IPF PPS
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payment rates, outlier threshold, cost of
living adjustment factors for Alaska and
Hawaii, national and upper limit costto-charge ratios, and adjustment factors.
In addition, the B Addenda to this final
rule show the complete listing of ICD–
10 Clinical Modification (CM) and
Procedure Coding System codes
underlying the Code First table
(Addendum B–1), the FY 2020 IPF PPS
comorbidity adjustment (Addenda B–2
and B–3), and electroconvulsive therapy
(ECT) procedure codes (Addendum B–
4). The A and B addenda are available
online at: https://www.cms.gov/
Medicare/Medicare-Fee-for-ServicePayment/InpatientPsychFacilPPS/
tools.html.
Tables setting forth the FY 2020 Wage
Index for Urban Areas Based on CoreBased Statistical Area (CBSA) Labor
Market Areas and the FY 2020 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. In
addition, Addendum C to this final rule
is a provider-level file of the effects of
the change to the wage index
methodology, and is available at the
same CMS website address.
I. Executive Summary
A. Purpose
This final rule updates 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 the Fiscal Year (FY) beginning
October 1, 2019 through September 30,
2020. Additionally, this final rule
rebases and revises the IPF market
basket to reflect a 2016 base year and
uses the concurrent hospital wage data
as the basis of the IPF wage index rather
than using the prior year’s Inpatient
Prospective Payment System (IPPS)
hospital wage data. Finally, this final
rule updates the Inpatient Psychiatric
Facility Quality Reporting (IPFQR)
Program.
B. Summary of the Major Provisions
1. Inpatient Psychiatric Facilities
Prospective Payment System (IPF PPS)
In this final rule we:
• Rebase and revise the IPF market
basket to reflect a 2016 base year: Since
the IPF PPS inception, the market basket
used to update IPF PPS payments has
been periodically rebased and revised to
reflect more recent data on IPF cost
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structures. We last rebased and revised
the market basket applicable to IPFs in
the FY 2016 IPF PPS rule (80 FR 46656
through 46679), when we adopted a
2012-based IPF-specific market basket.
• Adjust the 2016-based IPF market
basket update (2.9 percent) by a
reduction for economy-wide
productivity (0.4 percentage point) as
required by section 1886(s)(2)(A)(i) of
the Social Security Act (the Act). We
further reduced the 2016-based IPF
market basket update by 0.75 percentage
point as required by section
1886(s)(2)(A)(ii) of the Act, resulting in
an IPF payment rate update of 1.75
percent for FY 2020.
• Made technical rate setting changes:
The IPF PPS payment rates are adjusted
annually for inflation, as well as
statutory and other policy factors. We
updated:
++ The IPF PPS federal per diem base
rate from $782.78 to $798.55.
++ The IPF PPS federal per diem base
rate for providers who failed to report
quality data to $782.85.
++ The Electroconvulsive therapy
(ECT) payment per treatment from
$337.00 to $343.79.
++ The ECT payment per treatment
for providers who failed to report
quality data to $337.03.
++ The labor-related share from 74.8
percent to 76.9 percent.
++ The core-based statistical area
(CBSA) rural and urban wage indices for
FY 2020, using the FY 2020 pre-floor,
pre-reclassified IPPS hospital wage
index data and OMB designations from
OMB Bulletin 17–01.
++ The wage index budget-neutrality
factor to 1.0026.
++ The fixed dollar loss threshold
amount from $12,865 to $14,960 to
maintain estimated outlier payments at
2 percent of total estimated aggregate
IPF PPS payments.
• Eliminate the 1-year lag in the wage
index data: We aligned the IPF wage
index data with the concurrent IPPS
wage index data by removing the 1-year
lag of the pre-floor, pre-reclassified IPPS
hospital wage index upon which the IPF
wage index is based.
2. Inpatient Psychiatric Facilities
Quality Reporting (IPFQR) Program
We updated the IPFQR Program by
adding a new measure for the program.
C. Summary of Impacts
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Provision description
Total transfers & cost reductions
FY 2020 IPF PPS payment update .........................................
The overall economic impact of this final rule is an estimated $65 million in increased payments to IPFs during FY 2020.
$0.
Updated quality reporting program (IPFQR) Program requirements.
II. Background
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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 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 in an
IPPS hospital that is excluded from the
IPPS, or a psychiatric unit in a Critical
Access Hospital (CAH) that is excluded
from the CAH payment system. These
excluded psychiatric units would 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 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. As noted in our FY 2019
IPF PPS final rule with comment period,
published in the Federal Register on
August 6, 2018 (83 FR 38576 through
38620), for the RY beginning in 2018,
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the productivity adjustment currently in
place is equal to 0.8 percentage point.
Section 1886(s)(2)(A)(ii) of the Act
requires the application of an ‘‘other
adjustment’’ that reduces 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
2019 IPF PPS final rule, for the RY
beginning in 2018, section 1886(s)(3)(E)
of the Act requires that the other
adjustment reduction currently in place
be equal to 0.75 percentage point.
Sections 1886(s)(4)(A)–(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 take into account
such reduction in computing the
payment amount for a subsequent RY.
(See section II.C of this final rule for an
explanation of the IPF PPS RY.) More
information about the specifics of the
current IPFQR Program is available in
the FY 2019 IFP PPS and Quality
Reporting Updates for Fiscal Year
Beginning October 1, 2018 final rule (83
FR 38589 through 38608).
To implement and periodically
update these provisions, we have
published various proposed and final
rules and notices in the Federal
Register. For more information
regarding these documents, see the
Center for Medicare & Medicaid (CMS)
website at https://www.cms.gov/
Medicare/Medicare-Fee-for-ServicePayment/InpatientPsychFacilPPS/
index.html?redirect=/Inpatient
PsychFacilPPS/.
B. Overview of the IPF PPS
The November 2004 IPF PPS final
rule (69 FR 66922) 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
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(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.
The patient-level adjustments include
age, Diagnosis-Related Group (DRG)
assignment, and comorbidities;
additionally, there are 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-ofliving adjustment for IPFs located in
Alaska and Hawaii, and an adjustment
for the presence of a qualifying
emergency department (ED).
The IPF PPS provides additional
payment policies for outlier cases,
interrupted stays, and a per treatment
payment for patients who undergo
electroconvulsive therapy (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.
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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).
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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.
Therefore, in the November 2004 IPF
PPS final rule, 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 RY 2012, we proposed and
finalized switching the IPF PPS
payment rate update from a RY that
begins on July 1 and ends on June 30,
to one that coincides with the federal
FY that begins October 1 and ends on
September 30. In order to transition
from one timeframe to another, the RY
2012 IPF PPS covered a 15-month
period from July 1, 2011 through
September 30, 2012. Therefore, the IPF
RY has been equivalent to the October
1 through September 30 federal FY
since RY 2013. For further discussion of
the 15-month market basket update for
RY 2012 and changing the payment rate
update period to coincide with a FY
period, we refer readers to the RY 2012
IPF PPS proposed rule (76 FR 4998) and
the RY 2012 IPF PPS final rule (76 FR
26432).
In November 2004, we implemented
the IPF PPS in a final rule that
published on November 15, 2004 in the
Federal Register (69 FR 66922). In
developing the IPF PPS, and to ensure
that the IPF PPS is able to 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 proposed rule
(68 FR 66923; 66928 through 66933) and
our November 15, 2004 IPF final rule
(69 FR 66933 through 66960). For
characteristics with statistically
significant cost differences, we used the
regression coefficients of those variables
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to determine the size of the
corresponding payment adjustments.
In that 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 1. 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 1. For
a detailed list of updates to the IPF PPS,
we refer readers to our regulations at
412.428.
The most recent IPF PPS annual
update was published in a final rule on
August 6, 2018 in the Federal Register
titled, ‘‘Medicare Program; FY 2019
Inpatient Psychiatric Facilities
Prospective Payment System and
Quality Reporting Updates’’ (83 FR
38576), which updated the IPF PPS
payment rates for FY 2019. That final
rule updated the IPF PPS federal per
diem base rates that were published in
the FY 2018 IPF PPS Rate Update final
rule (82 FR 36771) in accordance with
our established policies.
III. Provisions of the FY 2020 IPF PPS
Final Rule and Responses to Comments
On April 23, 2019 we published the
FY 2020 IPF PPS proposed rule (84 FR
16948). We received 24 comments on
the FY 2020 IPF PPS proposed rule,
with some commenters addressing
multiple issues. We received 4
comments on payment policy issues, 19
comments on quality issues, and 6
comments that were outside of the
scope of the proposed rule.
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A. 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 2016 IPF PPS final rule
(80 FR 46656 through 46679), where we
adopted a 2012-based IPF market basket.
The 2012-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 2020 IPF PPS proposed rule,
we proposed to rebase and revise the
IPF market basket to reflect a 2016 base
year.
2. Overview of the 2016-Based IPF
Market Basket
The proposed 2016-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 (for the proposed IPF market
basket, the base period is 2016) and total
base period expenditures are estimated
for a set of mutually exclusive and
exhaustive spending categories. Each
category is calculated as a proportion of
total costs. These proportions are called
cost or expenditure weights. Second,
each expenditure category is matched to
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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
expenditure weight for each cost
category is multiplied by the level of its
respective price proxy. The sum of these
products (that is, the expenditure
weights multiplied by their price 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 furnish IPF services. The
effects on total expenditures resulting
from changes in the mix of goods and
services purchased after the base period
are not measured. For example, an IPF
hiring more nurses after the base period
to accommodate the needs of patients
will 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 will 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. Creating an IPF-Specific Market
Basket
As discussed in the FY 2016 final rule
(80 FR 46656 through 46679), the 2012based IPF market basket reflects the
Medicare cost reports for both
freestanding and hospital-based
facilities. Previous market baskets, such
as the 2008-based rehabilitation,
psychiatric, and long-term care (RPL)
market basket, were calculated using
Medicare cost report data for
freestanding facilities only. We used
only freestanding facilities due to
concerns regarding our ability to
incorporate Medicare cost report data
for hospital-based providers. After
research on the available Medicare cost
report data, we concluded that Medicare
cost report data for both freestanding
IPFs and hospital-based IPFs can be
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used to calculate the major market
basket cost weights for a stand-alone IPF
market basket. In the FY 2016 IPF PPS
final rule (80 FR 46656 through 46679),
we finalized a detailed methodology to
derive market basket cost weights using
Medicare cost report data for both
freestanding IPFs and hospital-based
IPFs.
For the FY 2020 proposed rule, we
proposed to rebase and revise the 2012based IPF market basket to a 2016 base
year reflecting both freestanding IPFs
and hospital-based IPFs. In section
III.A.3.a., ‘‘Development of Cost
Categories and Weights,’’ we provide a
detailed description of our proposed
methodology used to develop the 2016based IPF market basket.
a. Development of Cost Categories and
Weights
i. Medicare Cost Reports
We proposed a 2016-based IPF market
basket that consists of seven major cost
categories and a residual derived from
the 2016 Medicare cost reports (CMS
Form 2552–10 effective for cost reports
beginning on or after May 1, 2010) for
freestanding and hospital-based IPFs.
CMS Form 2552–10 was also used to
derive the major cost categories in the
2012-based IPF market basket. The
seven cost categories are Wages and
Salaries, Employee Benefits, Contract
Labor, Pharmaceuticals, Professional
Liability Insurance (PLI), Home Office
Contract Labor, and Capital. The 2012based IPF market basket did not have a
Home Office Contract Labor cost
category. The residual ‘‘All Other’’
category reflects all remaining costs not
captured in the seven cost categories.
The 2016 cost reports include providers
whose cost reporting period beginning
date is on or between October 1, 2015
and September 30, 2016. We proposed
to select 2016 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 at the time of
rulemaking.
Similar to the Medicare cost report
data used to develop the 2012-based IPF
market basket, the Medicare cost report
data for 2016 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
of case mix and practice patterns
associated with providing services to
Medicare beneficiaries. Therefore, we
proposed to limit our selection of
Medicare cost reports used in the 2016based IPF market basket to those
facilities that had a Medicare LOS
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38427
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 2016-based IPF market basket,
for those IPFs with an average facility
LOS of greater than or equal to 15 days,
we proposed 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
proposed to include IPFs where the
Medicare LOS is within 95 percent
(higher or lower) of the facility LOS. We
proposed 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 2012-based IPF
market basket.
Applying these trims to the
approximate 1,600 total cost reports
(freestanding and hospital-based)
resulted in roughly 1,500 IPF Medicare
cost reports with an average Medicare
LOS of 12 days, average facility LOS of
9 days, and Medicare utilization (as
measured by Medicare inpatient IPF
days as a percentage of total facility
days) of 26 percent. Providers excluded
from the proposed 2016-based IPF
market basket (about 130 Medicare cost
reports) had an average Medicare LOS of
25 days, average facility LOS of 55 days,
and a Medicare utilization of 4 percent.
Of those excluded, about 70 percent of
these were freestanding providers; on
the other hand, freestanding providers
represent about 30 percent of all IPFs.
We note that seventy percent of those
excluded from the 2012-based IPF
market basket using this LOS edit were
also freestanding providers.
Using the post-LOS set of 2016
Medicare cost reports, we calculated
costs for the seven major cost categories
(Wages and Salaries, Employee Benefits,
Contract Labor, Professional Liability
Insurance, Pharmaceuticals, Home
Office Contract Labor, and Capital). For
comparison, the 2012-based IPF market
basket utilized the Bureau of Economic
Analysis Benchmark Input-Output data
to derive the Home Office Contract
Labor cost weight rather than the
Medicare cost report data. A more
detailed discussion of this
methodological change is provided.
Similar to the 2012-based IPF market
basket major cost weights, the proposed
2016-based IPF market basket cost
weights reflect Medicare allowable costs
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(routine, ancillary, and capital costs)
that are eligible for inclusion under the
IPF PPS payments. We proposed to
define Medicare allowable costs for
freestanding IPFs as 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 proposed that total Medicare
allowable costs be equal to total costs
for the IPF inpatient unit after the
allocation of overhead costs (Worksheet
B, part I, column 26, line 40) and a
portion of total ancillary costs
(Worksheet B, part I, column 26, lines
50 through 76 (excluding 52 and 75), 90
through 91, and 93). We proposed to
calculate the portion of ancillary costs
attributable to the hospital-based IPF for
a given ancillary cost center by
multiplying total facility ancillary costs
for the specific cost center (as reported
on Worksheet B, part I, column 26) by
the ratio of IPF Medicare ancillary costs
for the cost center (as reported on
Worksheet D–3, column 3 for IPF
subproviders) to total Medicare
ancillary costs for the cost center (equal
to the sum of Worksheet D–3, column 3
for all Inpatient Prospective Payment
System (IPPS), Skilled Nursing Facility
(SNF), IRF, and IPF). This is the same
methodology used for the 2012-based
IPF market basket.
We provide a description of the
proposed methodologies used to derive
costs for the seven major cost categories.
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Wages and Salaries Costs
For freestanding IPFs, we proposed
that Wages and Salaries costs be derived
as the sum of routine inpatient salaries,
ancillary salaries, and a proportion of
overhead (or general service cost centers
in the MCR) salaries as reported on
Worksheet A, column 1. Since overhead
salary costs are attributable to the entire
IPF, we only include the proportion
attributable to the Medicare allowable
cost centers. We proposed to estimate
the proportion of overhead salaries that
are attributed to Medicare allowable
costs centers by multiplying the ratio of
Medicare allowable salaries (Worksheet
A, column 1, lines 50 through 76
(excluding 52 and 75), 90 through 91,
and 93) to total salaries (Worksheet A,
column 1, line 200) times total overhead
salaries (Worksheet A, column 1, lines
4 through 18). This is the same
methodology used in the 2012-based IPF
market basket.
We proposed that Wages and Salaries
costs for hospital-based IPFs are derived
by summing inpatient routine salary
costs, ancillary salaries, overhead salary
costs attributable to the IPF inpatient
unit, and a portion of overhead salary
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costs attributable to the ancillary
departments.
We proposed to calculate hospitalbased inpatient routine salary costs
using Worksheet A, column 1, line 40.
We proposed to calculate hospitalbased 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) using salary
costs from Worksheet A, column 1
multiplied by the ratio of IPF Medicare
ancillary costs for the cost center (as
reported on Worksheet D–3, column 3
for IPF subproviders) to total Medicare
ancillary costs for the cost center (equal
to the sum of Worksheet D–3, column 3
for IPPS, SNF, IRF, and IPF).
We proposed to calculate the hospitalbased overhead salaries attributable to
the IPF inpatient unit by first
calculating total noncapital overhead
costs (Worksheet B, part I, columns 4–
18, line 40 less Worksheet B, part II,
columns
4–18) for each ancillary
department. We then multiplied total
noncapital overhead costs by 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 proposed to calculate the hospitalbased portion of overhead salaries
attributable to each ancillary
department by first calculating total
noncapital overhead costs attributable to
each specific ancillary department
(Worksheet B, part I, columns 4–18 less
Worksheet B, part II, columns 4–18). We
then identified the portion of these
noncapital overhead costs attributable to
Wages and Salaries by multiplying these
costs by the ratio of total facility
overhead salaries (as reported on
Worksheet A, column 1, lines 4–18) to
total overhead costs (as reported on
Worksheet A, column 1 & 2, lines 4–18).
Finally, we identified the portion of
these overhead salaries for each
ancillary department that is attributable
to the hospital-based IPF by multiplying
by the ratio of IPF Medicare ancillary
costs for the cost center (as reported on
Worksheet D–3, column 3 for hospitalbased IPFs) to total Medicare ancillary
costs for the cost center (equal to the
sum of Worksheet D–3, column 3 for all
IPPS, SNF, IRF, and IPF).
This is the same Wages and Salaries
Costs methodology used to derive the
2012-based IPF market basket.
Employee Benefits Costs
Effective with the implementation of
CMS Form 2552–10, we began
collecting Employee Benefits and
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Contract Labor data on Worksheet S–3,
part V.
For 2016 Medicare cost report data,
the majority of providers did not report
data on Worksheet S–3, part V. One (1)
percent of freestanding IPFs and roughly
40 percent of hospital-based IPFs
reported data on Worksheet S–3, part V.
Again, we continue to encourage all
providers to report these data on the
Medicare cost report.
For freestanding IPFs, we proposed
Employee Benefits costs were 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. For
those freestanding IPFs that reported
Worksheet S–3, part II data, but not
Worksheet S–3, part V, we proposed to
use the sum of Worksheet S–3, part II
lines 17, 18, 20, and 22 to derive
Employee Benefits costs. This proposed
method allowed us to obtain data from
more than 20 freestanding IPFs (roughly
5 percent of all freestanding IPFs) than
if we were to only use Worksheet S–3,
part V data as done for the 2012-based
IPF market basket.
For hospital-based IPFs, we proposed
to calculate total benefit costs as the
sum of inpatient unit benefit costs, a
portion of ancillary benefits, and a
portion of overhead benefits attributable
to the routine inpatient unit and a
portion of overhead benefits attributable
to the ancillary departments.
We proposed hospital-based inpatient
unit benefit costs be equal to Worksheet
S–3 part V, column 2, line 3.
We proposed the hospital-based
portion of ancillary benefit costs be
equal to hospital-based ancillary salaries
times the ratio of total facility benefits
to total facility salaries.
We proposed that the hospital-based
portion of overhead benefits attributable
to the routine inpatient unit and
ancillary departments be calculated by
multiplying ancillary salaries for the
hospital-based IPF and overhead
salaries attributable to the hospitalbased IPF (determined in the derivation
of hospital-based IPF Wages and
Salaries costs as described) by the ratio
of total facility benefits to total facility
salaries. 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.
Contract Labor Costs
Contract Labor costs are primarily
associated with direct patient care
services. Contract Labor costs are
exclusive of Home Office Contract Labor
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costs. 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.iii of this
final rule. To derive contract labor costs
using Worksheet S–3, part V data, for
freestanding IPFs, we proposed 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 reported
Worksheet S–3, part II data, but not
Worksheet S–3, part V, we proposed to
use the sum of Worksheet S–3, part II
lines 11 and 13 to derive Contract Labor
costs. For the 2012-based IPF market
basket, we only used data from
Worksheet S–3, part V, column 1, line
2 to derive the Contract Labor costs for
freestanding IPFs.
For hospital-based IPFs, we proposed
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.
Pharmaceuticals Costs
For freestanding IPFs, we proposed 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 proposed
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 proposed that hospital-based nonsalary pharmacy costs attributable to the
hospital-based IPF are 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 nonsalary pharmacy costs (Worksheet A,
column 2, line 15) to total pharmacy
costs (sum of Worksheet A, column 1
and 2 for line 15) for the total facility.
We proposed that hospital-based nonsalary drugs charged to patient costs
attributable to the hospital-based IPF are
calculated by multiplying total nonsalary 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
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reported on Worksheet D–3 for IPF
subproviders, column 3, line 73) to total
Medicare drugs charged to patients
ancillary costs for the total facility
(equal to the sum of Worksheet D–3,
column 3, line 73, for all IPPS, SNF,
IRF, and IPF).
This is the same Pharmaceuticals
Costs methodology used to derive the
2012-based IPF market basket.
Professional Liability Insurance (PLI)
Costs
For freestanding IPFs, we proposed
that PLI costs (often referred to as
malpractice costs) are equal to
premiums, paid losses and selfinsurance costs reported on Worksheet
S–2, part I, columns 1 through 3, line
118.
For hospital-based IPFs, we proposed
to assume that the PLI weight for the
total facility is similar to the hospitalbased IPF unit since the only data
reported on this worksheet is for the
entire facility. Therefore, hospital-based
IPF PLI costs were equal to total facility
PLI (as reported on Worksheet S–2, part
I, columns 1 through 3, line 118)
divided by total facility costs (as
reported on Worksheet A, columns 1
and 2, line 200) times hospital-based
IPF Medicare allowable total costs. Our
assumption is that the same proportion
of expenses are used among each unit of
the hospital.
This is the same methodology used to
derive the 2012-based IPF market
basket.
Home Office/Related Organization
Contract Labor Costs
For the 2016-based IPF market basket,
we proposed to determine the home
office/related organization contract
labor costs using Medicare cost report
data. This is a different methodology
compared to the 2012-based IPF market
basket. We believe this proposed
methodology is an improvement as it is
based on the data directly submitted by
providers on the Medicare cost report. It
is also consistent with the methodology
we adopted when we rebased and
revised the 2014-based IPPS market
basket (52 FR 38159).
For hospital-based IPFs, we proposed
to calculate the home office contract
labor cost weight using data reported on
Worksheet S–3, part II, column 4, lines
14, 1401, 1402, 2550, and 2551 and total
facility costs (Worksheet B, part 1,
column 26, line 202). We proposed to
use total facility costs as the
denominator for calculating the home
office contract labor cost weight as these
expenses reported on Worksheet S–3,
part II reflect the entire hospital facility.
Our assumption is that the same
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38429
proportion of expenses are used among
each unit of the hospital. Similar to the
other market basket costs weights, we
proposed to trim the Home Office
Contract Labor cost weight to remove
outliers. Since not all hospital-based
IPFs will have home office contract
labor costs, we proposed to trim the top
one percent of the Home Office Contract
Labor cost weight. This is the same
trimming methodology used to calculate
the Home Office Contract Labor cost
weight in the 2016-based IPPS market
basket. Using this proposed
methodology, we calculate a Home
Office Contract Labor cost weight for
hospital-based IPFs of 3.7 percent. We
discuss the trimming methodology for
the other major cost categories in the
‘‘Final Major Cost Category
Computation’’ in section ii. of this final
rule.
Freestanding IPFs are not required to
complete Worksheet S–3, part II.
Therefore, to estimate the Home Office
Contract Labor cost weight, we
proposed the following methodology:
(1) Using hospital-based IPFs with a
home office and also passing the one
percent trim as described, we calculate
the ratio of the Home Office Contract
Labor cost weight to the Medicare
allowable nonsalary, noncapital cost
weight (Medicare allowable nonsalary,
noncapital costs as a percent of total
Medicare allowable costs).
(2) We identify freestanding IPFs that
report a home office on Worksheet S–2,
part I, line 140—roughly 85 percent. We
proposed to calculate a Home Office
Contract Labor cost weight for these
freestanding IPFs by multiplying the
ratio calculated in Step (1) by the
Medicare allowable nonsalary,
noncapital cost weight for those
freestanding IPFs with a home office.
(3) We then calculated the
freestanding IPF cost weight by
multiplying the Home Office Contract
Labor cost weight in step (2) by the total
Medicare allowable costs for IPFs with
a home office as a percent of total
Medicare allowable costs for all
freestanding IPFs.
To calculate the Home Office Contract
Labor cost weight, we proposed to
weight together the freestanding Home
Office Contract Labor cost weight (3.0
percent) and the hospital-based Home
Office Contract Labor cost weight (3.7
percent) using total Medicare allowable
costs. The resulting overall cost weight
for Home Office was 3.5 percent (3.0
percent × 37 percent + 3.7 percent × 63
percent).
For the 2012-based IPF market basket,
we calculated the Home Office Contract
Labor cost weight using the Bureau of
Economic Analysis Input-Output
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expense data for North American
Industry Classification System (NAICS)
code 55, Management of Companies and
Enterprises using the methodology
described in section III.A.3.a.iii
(Derivation of the Detailed Operating
Cost Weights) of this final rule.
Capital Costs
For freestanding IPFs, we proposed
capital costs to 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. This
is the same methodology used for the
2012-based IPF market basket.
For hospital-based IPFs, we proposed
capital costs to 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 calculated the portion of ancillary
capital costs attributable to the hospitalbased 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 ratio of IPF
Medicare ancillary costs for the cost
center (as reported on Worksheet D–3,
column 3 for IPF subproviders) to total
Medicare ancillary costs for the cost
center (equal to the sum of Worksheet
D–3, column 3 for all IPPS, SNF, IRF,
and IPF). This is the same methodology
used for the 2012-based IPF market
basket.
ii. Final Major Cost Category
Computation
After we derived costs for the seven
major cost categories for each provider
using the Medicare cost report data as
described, we proposed to trim the data
for outliers. The proposed trimming
methodology for the Home Office
Contract Labor cost weight is slightly
different than the proposed trimming
methodology for the other six cost
categories. For the Wages and Salaries,
Employee Benefits, Contract Labor,
Pharmaceuticals, Professional Liability
Insurance, and Capital cost weights, we
first divided the costs for each of these
six categories by total Medicare
allowable costs calculated for the
provider to obtain cost weights for the
universe of IPF providers. Next, we
applied a mutually exclusive top and
bottom 5 percent trim for each cost
weight to remove outliers. After the
outliers have been removed, we
summed the costs for each category
across all remaining providers. We then
divided this by the sum of total
Medicare allowable costs across all
remaining providers to obtain a cost
weight for the proposed 2016-based IPF
market basket for the given category.
Finally, we calculated the residual
‘‘All Other’’ cost weight that reflects all
remaining costs that are not captured in
the seven cost categories listed. We did
not receive any comments on the
derivation of the major cost weights. In
this final rule, we are finalizing our
methodology for deriving the major cost
weights as we proposed.
Table 1 presents the major cost
categories and weights calculated from
the Medicare cost reports for the 2016based IPF market basket as well as for
the 2012-based IPF market basket.
TABLE 1—MAJOR COST CATEGORIES AS DERIVED FROM MEDICARE COST REPORTS
Final 2016based IPF
market basket
(percent)
Major cost categories
Wages and Salaries ................................................................................................................................................
Employee Benefits ...................................................................................................................................................
Contract Labor .........................................................................................................................................................
Professional Liability Insurance (Malpractice) .........................................................................................................
Pharmaceuticals ......................................................................................................................................................
Home Office/Related Organization Contract Labor .................................................................................................
Capital ......................................................................................................................................................................
‘‘All Other’’ Residual ................................................................................................................................................
2012-based
IPF market
basket
(percent)
51.2
13.5
1.3
0.9
4.7
3.5
7.1
17.9
51.0
13.1
1.3
1.1
4.8
n/a
7.0
21.6
Note: Total may not sum to 100 due to rounding.
As we did for the 2012-based IPF
market basket, we proposed 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 the proposed rule, this
rounded percentage was 79 percent;
therefore, we proposed 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. The 2012-based
IPF market basket percentage was 80
percent. We did not receive any
comments on the allocation of the
Contract Labor cost weight.
Table 2 shows the Wages and Salaries
and Employee Benefit cost weights after
Contract Labor cost weight allocation for
both the 2016-based IPF market basket
and 2012-based IPF market basket.
TABLE 2—WAGES AND SALARIES AND EMPLOYEE BENEFITS COST WEIGHTS AFTER CONTRACT LABOR ALLOCATION
Final 2016based IPF
market
basket
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Major cost categories
Wages and Salaries ................................................................................................................................................
Employee Benefits ...................................................................................................................................................
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2012-Based
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basket
52.1
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iii. Derivation of the Detailed Operating
Cost Weights
To further divide the ‘‘All Other’’
residual cost weight estimated from the
2016 Medicare Cost Report data into
more detailed cost categories, we
proposed to use the 2012 Benchmark
Input-Output (I–O) ‘‘Use Tables/Before
Redefinitions/Purchaser Value’’ for
NAICS 622000 Hospitals, published by
the Bureau of Economic Analysis (BEA).
These data, publicly available at https://
www.bea.gov/industry/io_annual.htm,
are the most recent data available at the
time of rulemaking. For the 2012-based
IPF market basket, we used the 2007
Benchmark I–O data.
The BEA Benchmark I–O data are
scheduled for publication every five
years. The 2012 Benchmark I–O data are
derived from the 2012 Economic Census
and are the building blocks for BEA’s
economic accounts. 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 proposed to inflate
the 2012 Benchmark I–O data forward to
2016 by applying the annual price
changes from the respective price
proxies to the appropriate market basket
cost categories obtained from the 2012
Benchmark I–O data. We then proposed
to calculate the cost shares that each
cost category represents of the inflated
2016 data. These resulting 2016 cost
shares were applied to the ‘‘All Other’’
residual cost weight to obtain the
proposed detailed cost weights for the
2016-based IPF market basket. For
example, the cost for Food: Direct
Purchases represents 5.0 percent of the
sum of the ‘‘All Other’’ 2016 Benchmark
I–O Hospital Expenditures inflated to
2016. Therefore, the Food: Direct
Purchases cost weight represents 5.0
percent of the 2016-based IPF market
basket’s ‘‘All Other’’ cost category (17.9
percent), yielding a ‘‘final’’ Food: Direct
Purchases cost weight of 0.9 percent in
the proposed 2016-based IPF market
basket (0.05 * 17.9 percent = 0.9
percent).
Using this methodology, we proposed
to derive seventeen detailed IPF market
basket cost category weights from the
proposed 2016-based IPF market basket
residual cost weight (17.9 percent).
1 https://www.bea.gov/papers/pdf/IOmanual_
092906.pdf.
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These categories were: (1) Electricity, (2)
Fuel, Oil, and Gasoline, (3) Food: Direct
Purchases, (4) Food: Contract Services,
(5) Chemicals, (6) Medical Instruments,
(7) Rubber & Plastics, (8) Paper and
Printing Products, (9) Miscellaneous
Products, (10) Professional Fees: Laborrelated, (11) Administrative and
Facilities Support Services, (12)
Installation, Maintenance, and Repair,
(13) All Other Labor-related Services,
(14) Professional Fees: Nonlabor-related,
(15) Financial Services, (16) Telephone
Services, and (17) All Other Nonlaborrelated Services. We note that for the
2012-based IPF market basket, we had a
Water and Sewerage cost weight. For the
proposed 2016-based IPF market basket,
we proposed to include Water and
Sewerage in the Electricity cost weight
due to the small amount of costs in this
category.
We did not receive any comments on
the derivation of the detailed operating
cost weights. In this final rule, we are
finalizing our methodology for deriving
the detailed operating cost weights as
we proposed.
iv. Derivation of the Detailed Capital
Cost Weights
As described in section III.A.3.a.i. of
this final rule, we proposed a CapitalRelated cost weight of 7.1 percent as
obtained from the 2016 Medicare cost
reports for freestanding and hospitalbased IPF providers. We proposed to
further separate this total CapitalRelated cost weight into more detailed
cost categories. Using 2016 Medicare
cost reports, we were able to group
Capital-Related costs into the following
categories: Depreciation, Interest, Lease,
and Other Capital-Related costs. For
each of these categories, we proposed to
determine separately for hospital-based
IPFs and freestanding IPFs what
proportion of total capital-related costs
the category represent.
For freestanding IPFs, we proposed to
derive the proportions for Depreciation,
Interest, Lease, and Other Capitalrelated costs using the data reported by
the IPF on Worksheet A–7, which is the
same methodology used for the 2012based IPF market basket.
For hospital-based IPFs, data for these
four categories were not reported
separately for the subprovider;
therefore, we proposed 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 subprovider IPF unit.
For example, if depreciation costs make
up 60 percent of total capital costs for
the entire facility, we believe it was
reasonable to assume that the hospital-
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38431
based IPF will also have a 60 percent
proportion because it is a subprovider
unit contained within the total facility.
This is the same methodology used for
the 2012-based IPF market basket.
In order to combine each detailed
capital cost weight for freestanding and
hospital-based IPFs into a single capital
cost weight for the 2016-based IPF
market basket, we proposed 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 2016.
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 2012-based IPF market
basket.
Next, we proposed to allocate lease
costs across each of the remaining
detailed capital-related cost categories
as done in the 2012-based IPF market
basket. This resulted in three primary
capital-related cost categories in the
2016-based IPF market basket:
Depreciation, Interest, and Other
Capital-Related costs. As done in the
2012-based IPF market basket, lease
costs are unique in that they are not
broken out as a separate cost category in
the 2016-based IPF market basket, but
rather we proposed to proportionally
distribute these costs among the cost
categories of Depreciation, Interest, and
Other Capital-Related, reflecting the
assumption that the underlying cost
structure of leases is similar to that of
capital-related costs in general. As done
under the 2012-based IPF market basket,
we proposed 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 Other
Capital-Related cost category
accordingly. We proposed 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 is the
same methodology used for the 2012based IPF market basket. The allocation
of these lease expenses are shown in
Table 3.
Finally, we proposed to further divide
the Depreciation and Interest cost
categories. We proposed to separate
Depreciation into the following two
categories: (1) Building and Fixed
Equipment; and (2) Movable Equipment;
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and proposed to separate Interest into
the following two categories: (1)
Government/Nonprofit; and (2) Forprofit.
To disaggregate the Depreciation cost
weight, we determined 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 2016based IPF market basket, we proposed to
use slightly different methods to obtain
the fixed percentages for hospital-based
IPFs compared to freestanding IPFs.
For freestanding IPFs, we proposed to
use depreciation data from Worksheet
A–7 of the 2016 Medicare cost reports.
However, for hospital-based IPFs, we
determined that the fixed percentage for
the entire facility may not be
representative of the IPF subprovider
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 proposed to
calculate a fixed percentage using: (1)
Building and fixture capital costs
allocated to the subprovider unit as
reported on Worksheet B, part I line 40;
and (2) building and fixture capital costs
for the top five ancillary cost centers
utilized by hospital-based IPFs. We
proposed to then weight these two fixed
percentages (inpatient and ancillary)
using the proportion that each capital
cost type represents of total capital costs
in the proposed 2016-based IPF market
basket. We then proposed to 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 2012-based IPF market basket.
To disaggregate the Interest cost
weight, we determined the percent of
total interest costs for IPFs that were
attributable to government and
nonprofit facilities, the ‘‘nonprofit
percentage.’’ For the 2016-based IPF
market basket, we proposed to use
interest costs data from Worksheet A–7
for both freestanding and hospital-based
IPFs. We then determined the percent of
total interest costs that are attributed to
government and nonprofit IPFs
separately for hospital-based and
freestanding IPFs and weight the
nonprofit percentages for hospital-based
and freestanding IPFs together using the
proportion of total capital costs each
provider type represents. This is the
same methodology used for the 2012based IPF market basket.
We did not receive public comments
on the derivation of the detailed capital
cost weights. In this final rule, we are
finalizing our methodology for deriving
the detailed capital cost weights as we
proposed. Table 3 provides the detailed
capital cost share composition of the
2016-based IPF market basket. These
detailed capital cost share composition
percentages are applied to the total
Capital-Related cost weight of 7.1
percent determined in section III.A.3.a.i.
of this final rule.
TABLE 3—CAPITAL COST SHARE COMPOSITION FOR THE FINAL 2016-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 ........................................................................................................................................................................
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Note: Detail may not add to total due to rounding.
v. 2016-Based IPF Market Basket Cost
Categories and Weights
market basket and the 2012-based IPF
market basket.
Table 4 shows the cost categories and
weights for the final 2016-based IPF
BILLING CODE 4120–01–P
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60
43
18
13
10
3
20
7
Capital
cost share
composition
after lease
expense
allocation
(percent)
74
52
22
16
12
4
n/a
10
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38433
Utilities
Insurance
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All Other Products and Services
All Other Products
Pharmaceuticals
Food: Direct Purchases
Food: Contract Services
Chemicals
Medical Instruments
Rubber & Plastics
and
Products
Miscellaneous Products
All Other Services
Labor-Related Services
Professional Fees: Labor-related
Administrative and Facilities
Services
and
All Other: Labor-related Services
Nonlabor-Related Services
Professional Fees: Nonlabor-related
Financial services
Services
All Other: Nonlabor-related Services
Costs
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100.0
66.0
100.0
65.5
52.2
13.8
52.1
13.4
1.1
1.7
0.8
0.3
0.8
0.9
0.1
n/a
0.9
1.1
0.9
1.1
24.9
10.7
24.6
11.5
4.7
0.9
1.0
0.3
2.3
0.3
0.5
0.7
4.8
1.4
0.9
0.6
1.9
0.5
0.9
0.6
14.2
7.7
13.1
6.6
4.4
0.6
1.3
1.4
2.9
0.7
1.6
1.5
6.5
6.5
4.5
0.8
0.3
1.0
2.6
2.3
0.6
1.1
7.0
7.1
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Table 4: Final2016-based IPF Market Basket Cost Weights Compared to 2012-based IPF
Market Basket Cost W
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b. Selection of Price Proxies
After developing the cost weights for
the proposed 2016-based IPF market
basket, we selected 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
based the price proxies on Bureau of
Labor Statistics (BLS) data and grouped
them into one of the following BLS
categories:
• Employment Cost Indexes.
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. Producer
Price Indexes (PPIs) measure price
changes for goods sold in other than
retail markets. PPIs are used when the
purchases of goods or services are made
at the wholesale level.
• Consumer Price Indexes. Consumer
Price Indexes (CPIs) measure change in
the prices of final goods and services
bought by consumers. 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:
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• Reliability. 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 from
the true population parameter that
occurs by chance because only a sample
was surveyed rather than the entire
population.)
• Timeliness. Timeliness implies that
the proxy is published regularly,
preferably at least once a quarter. The
market baskets are updated quarterly
and, therefore, it is important for the
underlying price proxies to be up-todate, reflecting the most recent data
available. We believe that using proxies
that are published regularly (at least
quarterly, whenever possible) helps to
ensure that we are using the most recent
data available to update the market
basket. We strive to use publications
that are disseminated frequently,
because we believe that this is an
optimal way to stay abreast of the most
current data available.
• Availability. Availability means that
the proxy is publicly available. We
prefer that our proxies are publicly
available because this will help ensure
that our market basket updates are as
transparent to the public as possible. In
addition, this enables the public to be
able to obtain the price proxy data on
a regular basis.
• Relevance. Relevance means that
the proxy is applicable and
representative of the cost category
weight to which it is applied. The CPIs,
PPIs, and ECIs that we selected meet
these criteria. Therefore, we believe that
they continue to be the best measure of
price changes for the cost categories to
which they would be applied.
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Table 12 lists all price proxies that we
proposed to use for the 2016-based IPF
market basket. A detailed explanation of
the price proxies we proposed for each
cost category weight is provided.
i. Price Proxies for the Operating Portion
of the 2016-Based IPF Market Basket
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 2016-based IPF market
basket, we proposed to apply a proxy
blend based on six occupational
subcategories within the Wages and
Salaries category, which would reflect
the IPF occupational mix, as done for
the 2012-based IPF market basket.
We proposed to use the National
Industry-Specific Occupational
Employment and Wage estimates for
NAICS 622200, Psychiatric & Substance
Abuse Hospitals, published by the
Bureau of Labor Statistics Office of
Occupational Employment Statistics
(OES), as the data source for the wage
cost shares in the wage proxy blend. We
proposed to use May 2016 OES 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 2012-based IPF market
basket, we used May 2012 OES data.
Based on the OES 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 2016
occupational assignments for the six
wage subcategories; these are the same
occupational groups used in the 2012based IPF market basket.
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Table 5: 2016 Occupational Assignments for IPF Wage Blend
2016 Occupational Groupings
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13-0000
15-0000
19-0000
23-0000
25-0000
27-0000
Group 3
29-1021
29-1031
29-1051
29-1062
29-1063
29-1066
29-1069
29-1071
29-1122
29-1123
29-1125
29-1126
29-1127
29-1129
29-1141
29-1171
29-1199
Group 4
21-0000
29-2011
29-2012
29-2021
29-2034
29-2041
29-2051
29-2052
29-2053
29-2061
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Management
Management Occupations
NonHealth Professional & Technical
Business and Financial Operations Occupations
Computer and Mathematical Occupations
Life, Physical, and Social Science Occupations
Legal Occupations
Education, Training, and Library Occupations
Arts, Design, Entertainment, Sports, and Media Occupations
Health Professional & Technical
Dentists, General
Dietitians and Nutritionists
Pharmacists
Family and General Practitioners
Internists, General
Psychiatrists
Physicians and Surgeons, All Other
Physician Assistants
Occupational Therapists
Physical Therapists
Recreational Therapists
Respiratory Therapists
Speech-Language Pathologists
Therapists, All Other
Registered Nurses
Nurse Practitioners
Health Diagnosing and Treating Practitioners, All Other
Health Service
Community and Social Services Occupations
Medical and Clinical Laboratory Technologists
Medical and Clinical Laboratory Technicians
Dental Hygienists
Radiologic Technologists
Emergency Medical Technicians and Paramedics
Dietetic Technicians
Pharmacy Technicians
Psychiatric Technicians
Licensed Practical and Licensed Vocational Nurses
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Group 1
11-0000
Group 2
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Total expenditures by occupation
(that is, occupational assignment) were
calculated by taking the OES number of
employees multiplied by the OES
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
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expenditures of all six groups. These
proportions, listed in Table 6, represent
the weights used in the wage proxy
blend. We then proposed 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
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the price growth of the Wages and
Salaries cost category. These are the
same price proxies used in the 2012based IPF market basket. We did not
receive any public comments on the
2016-based IPF wage price proxy. In this
final rule, we are finalizing the 2016based IPF wage price proxy as proposed.
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BILLING CODE 4120–C
A comparison of the yearly changes
from FY 2017 to FY 2020 for the 2016-
based IPF wage blend and the 2012based IPF wage blend is shown in Table
7. The average annual growth rate is the
same for both price proxies over 2017–
2020.
TABLE 7—FISCAL YEAR GROWTH IN THE 2016-BASED IPF WAGE PROXY BLEND AND 2012-BASED IPF WAGE PROXY
BLEND
2017
2016-based IPF Final Wage Proxy Blend ...................................................................
2012-based IPF Wage Proxy Blend ............................................................................
2018
2.4
2.4
2019
2.6
2.6
3.0
3.0
2020
3.2
3.2
Average
2017–
2020
2.8
2.8
Benefits
To measure benefits price growth in
the 2016-based IPF market basket, we
proposed 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 publically available. Therefore, an
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‘‘ECIs for Total Benefits’’ is calculated
using publically 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 2012-based IPF market basket as
well as used in the IPPS, SNF, HHA,
RPL, LTCH, and ESRD market baskets.
We believe that the six price proxies
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listed in Table 8 are the most
technically appropriate indices to
measure the price growth of the Benefits
cost category in the proposed 2016based IPF market basket. We did not
receive any public comments on the
2016-based IPF benefit price proxy. In
this final rule, we are finalizing the
2016-based IPF benefit price proxy as
proposed.
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**SOURCE: IHS Global Inc., 2nd Quarter 2019 forecast with historical data through 1st Quarter 2019.
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TABLE 8—FINAL 2016-BASED IPF MARKET BASKET BENEFITS PROXY BLEND
2016-based
benefit
blend weight
(percent)
Wage subcategory
2012-based
benefit
blend weight
(percent)
Health Service .................................
36.3
36.2
Health Professional and Technical ..
NonHealth Service ...........................
34.9
8.9
33.5
9.2
NonHealth Professional and Technical.
Management ....................................
7.0
7.3
6.8
7.1
Clerical .............................................
6.1
6.7
Total ..........................................
100.0
100.0
A comparison of the yearly changes
from FY 2017 to FY 2020 for the 2016based IPF benefit proxy blend and the
Price proxy
ECI for Total Benefits for All Civilian workers in Healthcare and Social
Assistance.
ECI for Total Benefits for All Civilian workers in Hospitals.
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.
2012-based IPF benefit proxy is shown
in Table 9. The average annual growth
rate is the same for both price proxies
over 2017–2020.
TABLE 9—FISCAL YEAR GROWTH IN THE 2016-BASED IPF BENEFIT PROXY BLEND AND 2012-BASED IPF BENEFIT PROXY
BLEND
2017
2016-based IPF Final Benefit Proxy Blend .........................
2012-based IPF Benefit Proxy Blend ..................................
2018
1.9
1.9
2019
2.1
2.1
Average
2017–2020
2020
2.5
2.5
3.0
3.0
2.4
2.4
SOURCE: IHS Global Inc., 2nd Quarter 2019 forecast with historical data through 1st Quarter 2019.
Electricity
We proposed to continue to use the
PPI Commodity Index for Commercial
Electric Power (BLS series code
WPU0542) to measure the price growth
of this cost category. This is the same
price proxy used in the 2012-based IPF
market basket.
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Fuel, Oil, and Gasoline
Similar to the 2012-based IPF market
basket, for the 2016-based IPF market
basket, we proposed to use a blend of
the PPI for Petroleum Refineries and the
PPI Commodity for Natural Gas. Our
analysis of the BEA’s 2012 Benchmark
I–O data (use table before redefinitions,
purchaser’s value for NAICS 622000
[Hospitals]) shows that Petroleum
Refineries expenses accounts for
approximately 90 percent and Natural
Gas accounts for approximately 10
percent of Hospitals (NAICS 622000)
total Fuel, Oil, and Gasoline expenses.
Therefore, we proposed 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. The
2012-based IPF market basket used a 70/
30 blend of these price proxies,
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reflecting the 2007 I–O data. We believe
that these two price proxies continue to
be the most technically appropriate
indices available to measure the price
growth of the Fuel, Oil, and Gasoline
cost category in the proposed 2016based IPF market basket.
Professional Liability Insurance
We proposed to continue to use the
CMS Hospital Professional Liability
Index to measure changes in
professional liability insurance (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 2012based IPF market basket.
Pharmaceuticals
We proposed to continue 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 2012-based IPF
market basket.
Food: Direct Purchases
We proposed to continue to use the
PPI for Processed Foods and Feeds (BLS
series code WPU02) to measure the
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price growth of this cost category. This
is the same proxy used in the 2012based IPF market basket.
Food: Contract Purchases
We proposed to continue 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 2012based IPF market basket.
Chemicals
Similar to the 2012-based IPF market
basket, we proposed to use a four part
blended PPI as the proxy for the
chemical cost category in the proposed
2016-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).
We note that the four part blended PPI
used in the 2012-based IPF market
basket is composed of the PPI for
Industrial Gas Manufacturing (BLS
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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 Soap and Cleaning
Compound Manufacturing (BLS series
code PCU32561–32561–).
We proposed to derive the weights for
the PPIs using the 2012 Benchmark I–
O data. The 2012-based IPF market
basket used the 2007 Benchmark I–O
data to derive the weights for the four
PPIs.
38439
Table 10 shows the weights for each
of the four PPIs used to create proposed
blended Chemical proxy for the 2016based IPF market basket compared to
the 2012-based IPF market basket
blended Chemical proxy.
TABLE 10—BLENDED CHEMICAL PPI WEIGHTS
Final 2016based
IPF weights
(percent)
Name
PPI
PPI
PPI
PPI
PPI
for
for
for
for
for
Industrial Gas Manufacturing ..........................................................................................
Other Basic Inorganic Chemical Manufacturing .............................................................
Other Basic Organic Chemical Manufacturing ................................................................
Soap and Cleaning Compound Manufacturing ...............................................................
Other Miscellaneous Chemical Product Manufacturing ..................................................
Medical Instruments
We proposed to continue to use a
blend of two PPIs for the Medical
Instruments cost category. The 2012
Benchmark I–O data shows an
approximate 57/43 split between
Surgical and Medical Instruments and
Medical and Surgical Appliances and
Supplies for this cost category.
Therefore, we proposed a blend
composed of 57 percent of the
commodity-based PPI for Surgical and
Medical Instruments (BLS series code
WPU1562) and 43 percent of the
commodity-based PPI for Medical and
Surgical Appliances and Supplies (BLS
series code WPU1563). The 2012-based
IPF market basket used a 50/50 blend of
these PPIs based on the 2007
Benchmark I–O data.
Rubber and Plastics
We proposed to continue 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 2012based IPF market basket.
Paper and Printing Products
Administrative and Facilities Support
Services
We proposed to continue 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 2012based IPF market basket.
Installation, Maintenance, and Repair
We proposed to continue 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 2012based IPF market basket.
Miscellaneous Products
All Other: Labor-Related Services
We proposed to continue 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 2012based IPF market basket.
We proposed to continue 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 2012-based IPF market basket.
Professional Fees: Nonlabor-Related
We proposed to continue to use the
ECI for Total Compensation for Private
Industry workers in Professional and
Related (BLS series code
CIU2010000120000I) to measure the
We proposed to continue 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 2012-based IPF market basket.
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Professional Fees: Labor-Related
We proposed to continue 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 2012-based IPF
market basket.
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19
13
60
n/a
8
2012-based
IPF weights
(percent)
32
17
45
6
n/a
NAICS
325120
325180
325190
325610
325998
price growth of this category. This is the
same proxy used in the 2012-based IPF
market basket.
Financial Services
We proposed to continue 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 2012-based IPF market basket.
Telephone Services
We proposed to continue 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 2012based IPF market basket.
All Other: Nonlabor-Related Services
We proposed to continue 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 2012-based IPF market basket. We
did not receive any public comments on
the 2016-based IPF price proxies. In this
final rule, we are finalizing the 2016based IPF price proxies as proposed.
ii. Price Proxies for the Capital Portion
of the Proposed 2016-Based IPF Market
Basket
Capital Price Proxies Prior to Vintage
Weighting
We proposed to continue to use the
same price proxies for the capitalrelated cost categories as were applied
in the 2012-based IPF market basket,
which are provided and described in
Table 12. Specifically, we proposed to
proxy:
• Depreciation: Building and Fixed
Equipment cost category by BEA’s
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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 average yield on Moody’s Aaa bonds
(Federal Reserve).
• 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
proposed to continue to vintage weight
the capital price proxies for
Depreciation and Interest in order to
capture the long-term consumption of
capital. This vintage weighting method
is similar to the method used for the
2012-based IPF market basket and is
described in the section labeled Vintage
Weights for Price Proxies.
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 2016-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 proposed 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
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rate changes and, therefore, do not
reflect the actual annual price changes
for IPF capital-related costs. The capitalrelated component of the proposed
2016-based IPF market basket reflects
the underlying stability of the capitalrelated acquisition process.
The methodology used to calculate
the vintage weights for the 2016-based
IPF market basket is the same as that
used for the 2012-based IPF market
basket with the only difference being
the inclusion of more recent data. To
calculate the vintage weights for
depreciation and interest expenses, we
first needed a time series of capitalrelated 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
listed 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 capitalrelated purchases. However, the AHA
provided a consistent database of total
expenses back to 1963. Consequently,
we proposed 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
proposed 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
2016. We proposed to separate these
depreciation expenses into annual
amounts of building and fixed
equipment depreciation and movable
equipment depreciation as previously
determined. From these annual
depreciation amounts we derived
annual end-of-year book values for
building and fixed equipment and
movable equipment using the expected
life for each type of asset category.
While data are not available that are
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 needed the expected
lives for Building and Fixed Equipment,
Movable Equipment, and Interest for the
proposed 2016-based IPF market basket.
We proposed 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
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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 proposed to
determine the expected life of building
and fixed equipment separately for
hospital-based IPFs and freestanding
IPFs and weight these expected lives
using the percent of total capital costs
each provider type represents. We
proposed 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 22 years,
and the average expected life of movable
equipment to be equal to 11 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 2012-based
IPF market basket the expected life of
building and fixed equipment is 23
years and the expected life of movable
equipment is 11 years.
Multiplying these expected lives by
the annual depreciation amounts results
in annual year-end asset costs for
building and fixed equipment and
movable equipment. We then calculated
a time series, beginning in 1964, of
annual capital purchases by subtracting
the previous year’s asset costs from the
current year’s asset costs.
For the building and fixed equipment
and movable equipment vintage
weights, we proposed 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. For the interest
vintage weights, we proposed 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 proposed 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
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interest, 22 years, and in the case of
movable equipment, 11 years). For each
asset type, we used the time series of
annual capital-related purchase
amounts available from 2016 back to
1964. These data allow us to derive
thirty-two 22-year periods of capitalrelated purchases for building and fixed
equipment and interest, and forty-two
11-year periods of capital-related
purchases for movable equipment. For
each 22-year period for building and
fixed equipment and interest, or 11-year
period for movable equipment, we
calculated annual vintage weights by
dividing the capital-related purchase
amount in any given year by the total
amount of purchases over the entire 22year or 11-year period. This calculation
is done for each year in the 22-year or
11-year period and for each of the
periods for which we have data. We
then calculated the average vintage
weight for a given year of the expected
life by taking the average of these
vintage weights across the multiple
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 11 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
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periods of data. We did not receive any
public comments on the methodology
used to derive the vintage weights. In
this final rule, we are finalizing the
2016-based IPF market basket vintage
weights as proposed. Table 11 presents
the vintage weights for the capitalrelated portion of the 2016-based IPF
market basket and the 2012-based IPF
market basket.
BILLING CODE 4120–01–P
price indices. The example can be found
at the following link: https://
www.cms.gov/Research-Statistics-Dataand-Systems/Statistics-Trends-andReports/MedicareProgramRatesStats/
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MarketBasketResearch.html in the zip
file titled ‘‘Weight Calculations as
described in the IPPS FY 2010 Proposed
Rule.’’
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iii. Summary of Price Proxies of the
Final 2016-Based IPF Market Basket
Table 12 shows both the operating
and capital price proxies for the 2016based IPF market basket.
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Table 12: Price Proxies for the Final2016-based IPF Market Basket
100.0
66.0
52.2
13.8
1.1
Utilities
PPI for Commercial Electric Power
Blend of the PPI for Petroleum Refineries and PPI for
Natural Gas
0.8
0.3
0.9
Insurance
CMS Hospital Professional Liability Insurance Premium
Index
0.9
24.9
All Other Products and Services
Pharmaceuticals
PPI for Pharmaceuticals for human
10.7
4.7
Food: Direct Purchases
PPI for Processed Foods and Feeds
0.9
Food: Contract Services
CPI-U for Food
1.0
Chemicals
Blend of Chemical PPis
0.3
Medical Instruments
Blend of the PPI for Surgical and medical instruments and
PPI for Medical and
and
2.3
PPI for Rubber and Plastic Products
0.3
PPI for Converted
0.5
All Other Products
Products
From Home
0.7
Miscellaneous Products
14.2
All Other Services
7.7
Labor-Related Services
ECI for Total compensation for Private industry workers in
Professional and related
4.4
0.6
1.3
and
1.4
All Other: Labor-related Services
6.5
Nonlabor-Related Services
ECI for Total compensation for Private industry workers in
Professional and related
ECI for Total compensation for Private industry workers in
Financial activities
Professional Fees: Nonlabor-related
Financial services
4.5
0.8
0.3
CPI-Ufor
1.0
All Other: Nonlabor-related Services
7.1
Costs
5.3
BEA chained price index for nonresidential construction for
hospitals and special care facilities - vintage weighted (22
3.7
Fixed Assets
machinery and equipment- vintage weighted (11
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1.5
Movable
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BILLING CODE 4120–01–C
Comment: One commenter supported
the proposal to rebase and revise the IPF
market basket to reflect a 2016 base year
from a 2012 base year—as this ensures
the most recent cost data is utilized.
Response: We appreciate the
commenter’s support.
Final Decision: After careful
consideration of public comments, we
are finalizing the 2016-based IPF market
basket as proposed.
4. FY 2020 Market Basket Update
For FY 2020 (that is, beginning
October 1, 2019 and ending September
30, 2020), we proposed to use an
estimate of the 2016-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 that
contracts with CMS to forecast the
components of the market baskets and
multifactor productivity (MFP). In the
FY 2020 IPF proposed rule, we
proposed a FY 2020 IPF market basket
increase of 3.1 percent based on IGI’s
fourth quarter 2018 forecast with
historical data through third quarter
2018. In the FY 2020 proposed rule, we
also proposed that if more recent data
are subsequently available (for example,
a more recent estimate of the market
basket and MFP adjustment) we would
use such data, to determine the FY 2020
update in the final rule.
Table 13 compares the final 2016based IPF market basket and the 2012based IPF market basket percent
changes using the most recent estimate
based on IGI’s second quarter 2019
forecast with historical data through the
first quarter of 2019. The projected
2016-based IPF market basket increase
factor for FY 2020 is 2.9 percent. For
comparison, the current 2012-based IPF
market basket is also projected to
increase by 2.9 percent in FY 2020
based on IGI’s second quarter 2019
forecast.
TABLE 13—FINAL 2016-BASED IPF MARKET BASKET AND 2012-BASED IPF MARKET BASKET PERCENT CHANGES, FY
2015 THROUGH FY 2022
Final 2016based IPF
market basket
index percent
change
Fiscal year
(FY)
2012-based
IPF market
basket index
percent
change
Historical data:
FY 2015 ............................................................................................................................................................
FY 2016 ............................................................................................................................................................
FY 2017 ............................................................................................................................................................
FY 2018 ............................................................................................................................................................
1.9
1.9
2.4
2.6
1.8
1.9
2.5
2.6
Average 2015–2018 ..................................................................................................................................
2.2
2.2
............................................................................................................................................................
............................................................................................................................................................
............................................................................................................................................................
............................................................................................................................................................
2.6
2.9
3.1
3.1
2.7
2.9
3.2
3.1
Average 2019–2022 ..................................................................................................................................
2.9
3.0
Forecast:
FY 2019
FY 2020
FY 2021
FY 2022
5. 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 (MFP) (as
projected by the Secretary for the 10-
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year period ending with the applicable
FY, year, cost reporting period, or other
annual period) (the ‘‘MFP adjustment’’).
The BLS publishes the official measure
of private non-farm business MFP. We
refer readers to the BLS website at
https://www.bls.gov/mfp for the BLS
historical published MFP data.
MFP is derived by subtracting the
contribution of labor and capital inputs
growth from output growth. The
projections of the components of MFP
are currently produced by IGI, a
nationally recognized economic
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forecasting firm with which CMS
contracts to forecast the components of
the market baskets and MFP. For more
information on the productivity
adjustment, we refer reader to the
discussion in the FY 2016 IPF PPS final
rule (80 FR 46675).
For the FY 2020 final rule, using IGI’s
second quarter 2019 forecast, the MFP
adjustment for FY 2020 (the 10-year
moving average of MFP for the period
ending FY 2020) is projected to be 0.4
percent. Thus, in accordance with
section 1886(s)(2)(A)(i) of the Act, we
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Note: These market basket percent changes do not include any further adjustments as may be statutorily required. Source: IHS Global Inc.
2nd quarter 2019 forecast.
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base the FY 2020 market basket update,
which is used to determine the
applicable percentage increase for the
IPF payments, on the most recent
estimate of the 2016-based IPF market
basket (currently estimated to be 2.9
percent based on IGI’s second quarter
2019 forecast). We then reduce this
percentage increase of 2.9 percent by the
current estimate of the MFP adjustment
for FY 2020 of 0.4 percentage point (the
10-year moving average of MFP for the
period ending FY 2020 based on IGI’s
second quarter 2019 forecast) yielding a
productivity-adjusted IPF market basket
update of 2.5 percent. In addition, for
FY 2020 the 2016-based IPF PPS market
basket update is further reduced by 0.75
percentage point as required by sections
1886(s)(2)(A)(ii) and 1886(s)(3)(E) of the
Act. This results in a FY 2020 IPF PPS
payment rate update of 1.75 percent
(2.9¥0.4¥0.75 = 1.75 percent).
6. Labor-Related Share for FY 2020
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 proposed to continue
to classify a cost category as laborrelated if the costs are labor intensive
and vary with the local labor market.
We proposed 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, All Other:
Labor-related Services, and a portion of
the Capital-Related cost weight from the
proposed 2016-based IPF market basket.
These are the same categories as the
2012-based IPF market basket.
Similar to the 2012-based IPF market
basket, the 2016-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: Laborrelated and Professional Fees: Nonlaborrelated. For the 2016-based IPF market
basket, we proposed 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
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used to determine the labor-related
percentage of professional fees in the
2012-based IPF market basket.
As done in the 2012-based IPF market
basket, we proposed 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 proposed 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 2012-based IPF
market basket professional fees category
into Professional Fees: Labor-related
and Professional Fees: Nonlabor-related
cost categories.
In the 2016-based IPF market basket,
nonmedical professional fees that were
subject to allocation based on these
survey results represent 3.6 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 2.3 percentage points of the
3.6 percentage point figure into the
Professional Fees: Labor-related share
cost category and designate the
remaining 1.3 percentage point into the
Professional Fees: Nonlabor-related cost
category.
In addition to the professional
services listed, for the 2016-based IPF
market basket, we proposed to allocate
a proportion of the Home Office
Contract Labor cost weight, calculated
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using the Medicare cost reports, into the
Professional Fees: Labor-related and
Professional Fees: Nonlabor-related cost
categories. We proposed 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 laborrelated share that requires the services
to be purchased in the local labor
market.
Similar to the 2012-based IPF market
basket, we proposed for the 2016-based
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 proposed
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 determined the
proportion of the Home Office 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 proposed
to allocate 46 percent of the Home
Office Contract Labor cost weight (1.6
percentage points = 3.5 percent times 46
percent) to the Professional Fees: Laborrelated cost weight and 54 percent of the
Home Office Contract Labor cost weight
to the Professional Fees: Nonlaborrelated cost weight (1.9 percentage
points = 3.5 percent times 54 percent).
For the 2012-based IPF market basket,
we used a similar methodology but we
relied on provider counts rather than
total Medicare allowable costs to
determine the labor-related percentage.
In summary, based on the two
allocations mentioned earlier, we
apportioned percentage points of the
professional fees and home office/
related organization contract labor cost
weights into the Professional Fees:
Labor-Related cost category. This
amount was added to the portion of
professional fees that we already
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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 4.4 percent.
As stated, we proposed 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, All Other: Labor-related
Services, and a portion of the CapitalRelated cost weight from the proposed
2016-based IPF market basket. The
relative importance reflects the different
rates of price change for these cost
categories between the base year (2016)
and FY 2020. Based on IHS Global Inc.
4th quarter 2018 forecast of the
proposed 2016-based IPF market basket,
we proposed a total labor-related share
for FY 2020 of 76.8 percent (the sum of
73.7 percent for the operating cost and
3.1 percent for the labor-related share of
Capital).
Comment: One commenter opposed
the increase in the labor-related share
from 74.8 percent to 76.8 percent stating
it would negatively impact any facility
with a wage index below 1.0. The
growing disparity in wage indices
places facilities in low wage areas at a
significant disadvantage, and this
proposal will further increase that
disparity. They encouraged CMS to
maintain the FY 2019 labor-related
share in FY 2020.
Response: For FY 2020, we proposed
the FY 2020 labor-related share to be
equal to the sum of the relative
importance of shares of the following
proposed 2016-based IPF market basket
cost categories: Wages and Salaries,
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Employee Benefits, Professional Fees:
Labor-Related, Administrative and
Facilities Support Services, Installation,
Maintenance, and Repair, All Other:
Labor-related Services, and a portion of
the Capital-Related cost weight. The FY
2019 labor-related share reflected the
sum of the relative importance shares of
the same categories using the 2012based IPF market basket.
The increase in the labor-related share
from FY 2019 to FY 2020 is mostly a
result of the rebasing and revising of the
IPF market basket to reflect more recent
data. Of the 2.0-percentage point
difference between the FY 2020 laborrelated share using the proposed 2016based IPF market basket and the labor
share used in FY 2019, 1.9 percentage
point is from rebasing the market basket.
The detailed factors contributing to the
difference are: 0.6 percentage point is
due to an increase in the Compensation
and Capital cost weights as a result of
incorporating the 2016 MCR data, 0.3
percentage point is due to revising the
starting point of the calculation of the
relative importance from 2012 to 2016,
0.3 percentage point is due to the use of
MCR data to calculate the Home Office
Contract Labor cost weight (a portion of
which is included in the Professional
Fees: Labor-related services cost
weight), and the remaining 0.7
percentage point is due to the
incorporation of the 2012 Benchmark I–
O data, primarily stemming from an
increase in the Professional Fees: Laborrelated cost weight.
We appreciate the commenter’s
concern over the increase in the laborrelated share; however, we believe it is
technically appropriate to use the 2016based IPF market basket to determine
the labor-related share for FY 2020 as it
is based on more recent data regarding
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price pressures and cost structure of
IPFs. Our policy to use the most recent
market basket to determine the laborrelated share is a policy we have
regularly adopted for the IPF PPS as
well as for other PPSs including but not
limited to the IPPS, the Inpatient
Rehabilitation Facility PPS, and the
Long-term care hospital PPS.
Final Decision: After careful
consideration of comments, in this final
rule, we are finalizing the 2016-based
IPF market basket labor-related share
cost weights as proposed.
Based on IHS Global Inc. 2nd quarter
2019 forecast of the 2016-based IPF
market basket, the sum of the FY 2020
relative importance for Wages and
Salaries, Employee Benefits,
Professional Fees: Labor-related,
Administrative and Facilities Support
Services, Installation Maintenance &
Repair Services, and All Other: Laborrelated Services is 73.8 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 2012based IPF market basket. Since the
relative importance for Capital is 6.8
percent of the 2016-based IPF market
basket in FY 2020, we took 46 percent
of 6.8 percent to determine the proposed
labor-related share of Capital for FY
2020 of 3.1 percent. Therefore, we are
finalizing a total labor-related share for
FY 2020 of 76.9 percent (the sum of 73.8
percent for the operating cost and 3.1
percent for the labor-related share of
Capital).
Table 14 shows the FY 2020 laborrelated share using the final 2016-based
IPF market basket relative importance
and the FY 2019 labor-related share
using the 2012-based IPF market basket.
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B. Updates to the IPF PPS Rates for FY
Beginning October 1, 2019
The IPF PPS is based on a
standardized federal per diem base rate
calculated from the IPF average per
diem costs and adjusted for budgetneutrality 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 budgetneutrality 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)
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methodology had the IPF PPS not been
implemented. A step-by-step
description of the methodology used to
estimate payments under the 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 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.
Additional 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
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38447
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 electroconvulsive therapy
(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
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used on IPF claims as a result of the
proposed update to the ICD–10–PCS
code set for FY 2020. Addendum B–4 to
this final rule shows the ECT procedure
codes for FY 2020 and is available on
our website at https://www.cms.gov/
Medicare/Medicare-Fee-for-ServicePayment/InpatientPsychFacilPPS/
tools.html.
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2. Update of the Federal Per Diem Base
Rate and Electroconvulsive Therapy
Payment Per Treatment
The current (FY 2019) federal per
diem base rate is $782.78 and the ECT
payment per treatment is $337.00. For
the FY 2020 federal per diem base rate,
we applied the payment rate update of
1.75 percent (that is, the 2016-based IPF
market basket increase for FY 2020 of
2.9 percent less the productivity
adjustment of 0.4 percentage point, and
further reduced by the 0.75 percentage
point required under section
1886(s)(3)(E) of the Act), and the wage
index budget-neutrality factor of 1.0026
(as discussed in section III.D.1.f of this
final rule) to the FY 2019 federal per
diem base rate of $782.78, yielding a
federal per diem base rate of $798.55 for
FY 2020. Similarly, we applied the 1.75
percent payment rate update and the
1.0026 wage index budget-neutrality
factor to the FY 2019 ECT payment per
treatment of $337.00, yielding an ECT
payment per treatment of $343.79 for FY
2020.
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 rate year, the
Secretary will reduce any annual update
to a standard federal rate for discharges
during the RY by 2.0 percentage points.
Therefore, we are applying a 2.0
percentage point reduction to the
federal per diem base rate and the ECT
payment per treatment as follows:
• For IPFs that fail requirements
under the Inpatient Psychiatric
Facilities Quality Reporting (IPFQR)
Program, we applied a ¥0.25 percent
payment rate update (that is, the IPF
market basket increase for FY 2020 of
2.9 percent less the productivity
adjustment of 0.4 percentage point,
further reduced by the 0.75 percentage
point for an update of 1.75 percent, and
further reduced by 2 percentage points
in accordance with section
1886(s)(4)(A)(ii) of the Act, which
results in a negative update percentage)
and the wage index budget-neutrality
factor of 1.0026 to the FY 2019 federal
per diem base rate of $782.78, yielding
a federal per diem base rate of $782.85
for FY 2020.
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• For IPFs that fail to meet
requirements under the IPFQR Program,
we applied the ¥0.25 percent annual
payment rate update and the 1.0026
wage index budget-neutrality factor to
the FY 2019 ECT payment per treatment
of $337.00, yielding an ECT payment
per treatment of $337.03 for FY 2020.
C. 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 are finalizing our
proposal to continue to use the existing
regression-derived adjustment factors
established in 2005 for FY 2020.
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.
a. 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 Inpatient
Prospective Payment System (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
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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 2020,
we did not propose any changes to the
IPF MS–DRG adjustment factors but are
finalizing our proposal to maintain 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. 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-ConversionProject.html.
For FY 2020, we are finalizing our
proposal to continue to make 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/Inpatient
PsychFacilPPS/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, 2019,
using the final IPPS FY 2020 ICD–10–
CM/PCS code sets. The FY 2020 IPPS
final rule includes tables of the final
changes to the ICD–10–CM/PCS code
sets which underlie the FY 2020 IPF
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MS–DRGs. Both the FY 2020 IPPS final
rule and the tables of proposed changes
to the ICD–10–CM/PCS code sets which
underlie the FY 2020 MS–DRGs are
available on the IPPS website at https://
www.cms.gov/Medicare/Medicare-Feefor-Service-Payment/Acute
InpatientPPS/.
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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 would follow the
instructions in the ICD–10–CM text. The
submitted claim goes through the CMS
processing system, which will identify
the primary 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, see our November 2004 IPF PPS
final rule (69 FR 66945) and see sections
I.A.13 and I.B.7 of the FY 2019 ICD–10–
CM Coding Guidelines, available at
https://www.cdc.gov/nchs/icd/data/
10cmguidelines-FY2019-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
were present in ICD–9–CM (79 FR
46009). In FY 2018 and FY 2019, there
were no changes to the final ICD–10–
CM/PCS codes in the IPF Code First
table. For FY 2020, there continue to be
no changes to the ICD–10–CM/PCS
codes in the proposed IPF Code First
table. The final FY 2020 Code First table
is shown in Addendum B–1 on our
website at https://www.cms.gov/
Medicare/Medicare-Fee-for-ServicePayment/InpatientPsychFacilPPS/
tools.html.
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b. 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, length of stay (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
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38449
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 would 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 2020, we are finalizing our
proposal to continue to use the same
comorbidity adjustment factors in effect
in FY 2019, which are found in
Addendum A, available on our website
at https://www.cms.gov/Medicare/
Medicare-Fee-for-Service-Payment/
InpatientPsychFacilPPS/tools.html.
We have updated the ICD–10–CM/
PCS codes which are associated with
the existing IPF PPS comorbidity
categories, based upon the final FY 2020
update to the ICD–10–CM/PCS code set.
The final FY 2020 ICD–10–CM/PCS
updates include 4 ICD–10–CM diagnosis
codes added to the Poisoning
comorbidity category and 88 ICD–10–
PCS codes added to the Oncology
Procedures comorbidity category. In
addition, 3 ICD–10–PCS codes were
deleted from the Oncology Procedures
comorbidity category. These updates are
detailed in Addenda B–2 and B–3 of
this final rule, which are available on
our 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 2020 ICD–10–CM
codes to remove codes that were site
‘‘unspecified’’ in terms of laterality from
the FY 2020 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 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 proposed additions to the
FY 2020 ICD–10–CM/PCS codes were
site ‘‘unspecified’’ by laterality,
therefore we are not removing any of the
new codes.
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c. 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 more costly 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 2020, we
are finalizing our proposal to continue
to use the patient age adjustments
currently in effect in FY 2019, as shown
in Addendum A of this rule (see https://
www.cms.gov/Medicare/Medicare-Feefor-Service-Payment/Inpatient
PsychFacilPPS/tools.html).
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d. 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 length of stay
(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 to 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 rule.
For FY 2020, we are finalizing our
proposal to continue to use the variable
per diem adjustment factors currently in
effect, as shown in Addendum A of this
rule (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).
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D. 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), in order 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 § 412.64(b)(1)(ii)(A) and (C).
b. Change to the IPF Wage Index
Methodology
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 rate year (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 taking
into account 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 was put into regulation at
412.424(a)(2), and requires us to use the
best Medicare data available to estimate
costs per day, including an appropriate
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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 fiscal year 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 an 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 fiscal year (for example,
the RY 2006 IPF wage index was based
on the FY 2005 pre-floor, prereclassified 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 FY
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.
We proposed to change 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
proposed to use the pre-floor, prereclassified IPPS hospital wage index
from the fiscal year concurrent with the
IPF fiscal year as the basis for the IPF
wage index. For example, the FY 2020
IPF wage index would be 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.
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We explained in the proposed rule (84
FR 16973), that using the concurrent
pre-floor, pre-reclassified IPPS hospital
wage index would result in the most upto-date wage data being the basis for the
IPF wage index. It would also result in
more consistency and parity in the wage
index methodology used by other
Medicare payment systems. The
Medicare SNF PPS already uses 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 would 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 2020, we also proposed to
continue use the pre-floor, prereclassified IPPS hospital wage index as
the basis for the IPF wage index.
We received 1 comment on our
proposal to align the IPF wage index
data timeframe with that of the IPPS, by
using the concurrent pre-floor, prereclassified IPPS hospital wage index as
the basis for the IPF wage index for FY
2020 and subsequent years.
Comment: A commenter wrote that he
was not opposed to the proposal to
eliminate the 1-year lag in the wage
index data, but had issues with the data
itself. The commenter was opposed to
using the FY 2020 IPPS wage index data
file discussed in the FY 2020 IPPS
proposed rule because the data
excluded several hospitals which had
wage data based upon regional rather
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than local labor market rates. The
commenter felt this exclusion was
inappropriate and that it would
negatively affect certain IPFs.
Response: We appreciate the
comment, however, we are finalizing
our proposal to use the concurrent prefloor, pre-reclassified IPPS hospital
wage index as the basis for IPF wage
index for FY 2020 and subsequent years.
For FY 2020, we are also finalizing our
proposal to continue to use the prefloor, pre-reclassified IPPS hospital
wage index as the basis for the IPF wage
index. We believe it is the best available
data to use as a proxy for an IPF wage
index. This pre-floor, pre-reclassified
IPPS hospital wage index is also the
most appropriate wage index as IPFs
compete in the same labor market as
IPPS hospitals; this wage index best
reflects the variation in local labor costs
of IPFs in the various geographic areas
using the most recent IPPS hospital
wage data (data from hospital cost
reports for the cost reporting period
beginning during FY 2016) without any
geographic reclassifications, floors, or
other adjustments. We will apply the FY
2020 IPF wage index to payments
beginning October 1, 2019.
We identified a slight error in the
proposed rule wage index values after
the FY 2020 IPF PPS proposed rule was
published. A programming error caused
the data for all providers in a single
county to be included twice, which
affected the national average hourly
rate, and therefore affected nearly all
wage index values. We have changed
the programming logic so this error
cannot occur again. In addition, we
corrected the classification of one
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provider in North Carolina that was
erroneously identified as being in an
urban CBSA. We also standardized our
procedures for rounding, to ensure
consistency. The correction to the
NPRM wage index data was not
completed until after the comment
period closed on June 17, 2019. This
final rule reflects the corrected and
updated wage index data.
We are finalizing this change to the
IPF wage index methodology to
implement it in a budget-neutral
manner, so that total IPF payments will
not be affected. However, as shown in
Table 15, there will be distributional
effects. Table 15 compares the estimated
payments calculated using the FY 2020
IPF wage index based on the IPPS
hospital wage index data from the prior
fiscal year (the current methodology)
with the estimated payments calculated
using the FY 2020 IPF wage index based
on concurrent IPPS hospital wage index
data (the proposed change in
methodology which we are finalizing).
Due to budget neutrality, the effect on
total estimated FY 2020 IPF payments is
zero. Table 15 shows that urban IPFs are
estimated to experience a smaller
increase in payments by finalizing the
proposed methodology (0.03 percent
increase) compared to if we had
maintained the current methodology
(0.09 percent increase). Rural IPFs are
estimated to have a smaller decrease in
estimated payments by finalizing the
proposed methodology (0.20 percent
decrease) compared to if we had
maintained the current methodology
(0.54 percent decrease).
BILLING CODE 4120–01–P
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Total Urban
Urban unit
Urban hospital
1,260
783
477
0.09
0.05
0.13
0.03
-0.06
0.13
Total Rural
Rural unit
Rural hospital
321
255
66
-0.54
-0.62
-0.34
-0.20
-0.24
-0.10
121
100
256
-0.19
0.18
0.18
-0.19
0.08
0.21
32
15
19
-0.56
-0.31
-0.23
-0.30
-0.47
0.10
115
509
159
0.28
0.00
0.02
0.19
-0.09
-0.15
68
-0.53
-0.08
By Type of Ownership:
Freestanding IPFs
Urban Psychiatric Hospitals
Government
Non-Profit
For-Profit
Rural Psychiatric Hospitals
Government
Non-Profit
For-Profit
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IPF Units
Urban
Government
Non-Profit
For-Profit
Rural
Government
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Table 15. Distributional Effects of the Change to the IPF Wage Index Methodology
rPercent Change in Columns 3 and 41
Estimated
Impact of
Estimated
Impact of
Wage Index
Wage Index
Update
Under
Update
Number
Under
Proposed &
of
Current
Finalized
Facility by Type
Facilities Methodology Methodology
(4)
(1)
(2)
(3)
All Facilities
1,581
0.00
0.00
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To provide additional information to
IPFs about the effect of implementing
this change in the IPF wage index
methodology on estimated payments,
we have also posted a provider-level
table of effects (Addendum C) on the
CMS website, available at https://
www.cms.gov/Medicare/Medicare-Feefor-Service-Payment/Inpatient
PsychFacilPPS/WageIndex.html.
We are applying the IPF wage index
adjustment to the labor-related share of
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the national base rate or ECT payment
per treatment. The labor-related share of
the national rate and ECT payment per
treatment will change from 74.8 percent
in FY 2019 to 76.9 percent in FY 2020.
This percentage reflects the laborrelated share of the 2016-based IPF
market basket for FY 2020 (see section
III.A.6 of this rule).
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c. Office of Management and Budget
Bulletins
OMB publishes bulletins regarding
CBSA changes, including changes to
CBSA numbers and titles. 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 MSAs, and the
creation of Micropolitan Statistical
Areas and Combined Statistical Areas.
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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). The OMB bulletins may be
accessed online at https://
www.whitehouse.gov/omb/informationfor-agencies/bulletins/.
In accordance with our established
methodology, we have 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. For the FY 2015 IPF wage
index, we used the FY 2014 pre-floor,
pre-reclassified IPPS hospital wage
index to adjust the IPF PPS payments.
On February 28, 2013, OMB issued
OMB Bulletin No. 13–01, which
established revised delineations for
MSAs, Micropolitan Statistical Areas,
and Combined Statistical Areas in the
United States and Puerto Rico based on
the 2000 Census, and provided guidance
on the use of the delineations of these
statistical areas. A copy of this bulletin
may be obtained at https://
www.whitehouse.gov/omb/informationfor-agencies/bulletins/.
Because the FY 2014 pre-floor, prereclassified IPPS hospital wage index
did not reflect the statistical area
revisions set forth in OMB Bulletin 13–
01, the FY 2015 IPF PPS wage index,
which was based on the FY 2014 prefloor, pre-reclassified IPPS hospital
wage index, did not reflect OMB’s new
area delineations based on the 2010
Census. According to OMB, ‘‘[t]his
bulletin provides the delineations of all
Metropolitan Statistical Areas,
Metropolitan Divisions, Micropolitan
Statistical Areas, Combined Statistical
Areas, and New England City and Town
Areas in the United States and Puerto
Rico based on the standards published
on June 28, 2010, in the Federal
Register (75 FR 37246 through 37252)
and Census Bureau data.’’ These OMB
Bulletin changes are reflected in the FY
2015 pre-floor, pre-reclassified IPPS
hospital wage index, upon which the FY
2016 IPF wage index was based. We
adopted these new OMB CBSA
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delineations in the FY 2016 IPF wage
index and subsequent IPF wage indexes.
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. On
July 15, 2015, OMB issued OMB
Bulletin No. 15–01, which provided
minor updates to, and superseded, OMB
Bulletin No. 13–01 that was issued on
February 28, 2013. The attachment to
OMB Bulletin No. 15–01 provides
detailed information on the update to
statistical areas since February 28, 2013.
The updates provided in the attachment
to OMB Bulletin No. 15–01 are based on
the application of the 2010 Standards
for Delineating Metropolitan and
Micropolitan Statistical Areas to Census
Bureau population estimates for July 1,
2012 and July 1, 2013. The complete list
of statistical areas incorporating these
changes is provided in OMB Bulletin
No. 15–01. A copy of this bulletin may
be obtained at https://
www.whitehouse.gov/omb/informationfor-agencies/bulletins/. OMB Bulletin
No. 15–01 establishes revised
delineations for the Nation’s
Metropolitan Statistical Areas,
Micropolitan Statistical Areas, and
Combined Statistical Areas. The bulletin
also provides delineations of
Metropolitan Divisions as well as
delineations of New England City and
Town Areas.
In accordance with our longstanding
policy, the IPF PPS continues to use the
latest labor market area delineations
available as soon as is reasonably
possible to maintain a more accurate
and up-to-date payment system that
reflects the reality of population shifts
and labor market conditions. As
discussed in the FY 2017 IPPS/LTCH
PPS final rule (81 FR 56913), the
updated labor market area definitions
from OMB Bulletin 15–01 were
implemented under the IPPS beginning
on October 1, 2016 (FY 2017).
Therefore, we implemented these
revisions for the IPF PPS beginning
October 1, 2017 (FY 2018), consistent
with our historical practice of modeling
IPF PPS adoption of the labor market
area delineations after IPPS adoption of
these delineations (historically the IPF
wage index has been based upon the
pre-floor, pre-reclassified IPPS hospital
wage index from the prior year).
On August 15, 2017, OMB announced
in OMB Bulletin No. 17–01 that one
Micropolitan Statistical Area now
qualifies as a Metropolitan Statistical
Area. The new urban CBSA is as
follows:
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• Twin Falls, Idaho (CBSA 46300).
This CBSA is comprised of the
principal city of Twin Falls, Idaho in
Jerome County, Idaho and Twin Falls
County, Idaho. Prior to this
redesignation, Jerome County and Twin
Falls County, Idaho were classified as
rural. The OMB bulletin is available on
the OMB website at https://
www.whitehouse.gov/sites/
whitehouse.gov/files/omb/bulletins/
2017/b-17-01.pdf.
With the change made by OMB
Bulletin No. 17–01, these two counties
are now designated as urban, and any
IPFs in those areas will change their
status from being rural to being urban.
We adopted these new OMB
designations in FY 2020 as they are
included in the FY 2020 pre-floor, prereclassified IPPS hospital wage index
upon which the FY 2020 IPF wage
index is proposed to be based. That is,
the FY 2020 pre-floor, pre-reclassified
IPPS hospital wage index, which is the
basis of the final FY 2020 IPF wage
index, will include this new OMB
designation.
Therefore, the 17 percent IPF rural
adjustment will cease for IPF providers
in these two counties. Currently, there
is a single IPF in new CBSA 46300,
which will lose its 17 percent rural
adjustment as a result of being redesignated as urban. However, the FY
2020 IPF wage index value for CBSA
46300 is 0.8291, which is 3.5 percent
higher than the rural wage index value
for Idaho (0.8009). As such, the loss of
the 17 percent IPF wage index
adjustment will be mitigated in part by
the increase in the wage index value
when changing from the rural Idaho
wage index value to the urban CBSA
46300 wage index value. Given that the
loss of the rural adjustment will be
mitigated in part by the increase in wage
index value, and that only a single IPF
is affected by this change, we do not
believe it is necessary to transition this
provider from its rural to newly urban
status.
Thus, we are finalizing our proposal
to adopt this new OMB designation in
the proposed IPF wage index for FY
2020 and for subsequent fiscal years.
The FY 2020 IPF wage index already
includes the OMB delineations that
were adopted in prior fiscal years. The
FY 2020 IPF wage index (including the
CBSA update from OMB Bulletin No.
17–01) is located on the CMS website at
https://www.cms.gov/Medicare/
Medicare-Fee-for-Service-Payment/
InpatientPsychFacilPPS/
WageIndex.html.
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d. Solicitation of Public Comments on
the IPF Wage Index
Historically, we have calculated the
IPF PPS wage index values using
unadjusted wage index values from
another provider setting. Stakeholders
have occasionally commented on
certain aspects of the IPF PPS wage
index values and their impact on
payments. We solicited comments on
concerns stakeholders may have
regarding the wage index used to adjust
IPF PPS payments and suggestions for
possible updates and improvements to
the geographic adjustment of IPF PPS
payments. We did not receive any
comments.
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e. Adjustment for Rural Location
In the November 2004 IPF PPS final
rule, 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 2020, we are finalizing our
proposal to continue to apply a 17
percent payment adjustment for IPFs
located in a rural area as defined at
§ 412.64(b)(1)(ii)(C). A complete
discussion of the adjustment for rural
locations appears in the November 2004
IPF PPS final rule (69 FR 66954).
f. 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 2020, we are finalizing
our proposal to continue 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 2020 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 update
to the wage indexes (based on the FY
2016 hospital cost report data) and the
labor-related share in a budget-neutral
manner:
Step 1. Simulate estimated IPF PPS
payments, using the FY 2019 IPF wage
index values (available on the CMS
website) and labor-related share (as
published in the FY 2019 IPF PPS final
rule (83 FR 38579)).
Step 2. Simulate estimated IPF PPS
payments using the FY 2020 IPF wage
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index values (available on the CMS
website) and FY 2020 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 FY
2020 budget-neutral wage adjustment
factor of 1.0026.
Step 4. Apply the FY 2020 budgetneutral wage adjustment factor from
step 3 to the FY 2019 IPF PPS federal
per diem base rate after the application
of the market basket update described in
section III.A.4 of this rule, to determine
the FY 2020 IPF PPS federal per diem
base rate.
2. Teaching Adjustment
In the November 2004 IPF PPS final
rule, we implemented regulations at
§ 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 full-time
equivalent (FTE) interns and residents
training in the IPF and the IPF’s average
daily census (ADC).
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/the
IPF’s ADC)). The teaching variable is
then raised to 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
later in this section of this 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
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38455
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
(publication date of the IPF PPS final
rule). A complete discussion of the
temporary adjustment to the FTE cap to
reflect residents added due to hospital
closure and by residency program
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
is 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 rerun the teaching
adjustment factors in the regression
analysis until we more fully analyze IPF
PPS data as part of the IPF PPS
refinement we discuss in section IV of
this rule. Therefore, in this FY 2020
final rule, we are finalizing our proposal
to continue to retain the coefficient
value of 0.5150 for the teaching
adjustment to the federal per diem base
rate.
3. Cost of Living Adjustment 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
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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
would 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-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 Nonforeign Area
Retirement Equity Assurance Act, as
contained in subtitle B of title XIX of the
National Defense Authorization Act
(NDAA) for FY 2010 (Pub. L. 111–84,
October 28, 2009), 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 think 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
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 2018,
the COLA factors were updated in FY
2018 IPPS/LTCH rulemaking (82 FR
38529). As such, we also updated the
IPF PPS COLA factors for FY 2018 (82
FR 36780 through 36782) to reflect the
updated COLA factors finalized in the
FY 2018 IPPS/LTCH rulemaking. We are
finalizing our proposal to continue to
apply the same COLA factors in FY
2020 that were used in FY 2018 and FY
2019.
TABLE 16—COMPARISON OF IPF PPS COST-OF-LIVING ADJUSTMENT FACTORS: IPFS LOCATED IN ALASKA AND HAWAII
FY 2015
through
FY 2017
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 IPF PPS COLA factors for FY
2020 are also shown in Addendum A to
this final rule, available at https://
www.cms.gov/Medicare/Medicare-Feefor-Service-Payment/Inpatient
PsychFacilPPS/tools.html.
4. 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-
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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
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FY 2018
through
FY 2020
1.23
1.23
1.23
1.25
1.25
1.25
1.25
1.25
1.25
1.19
1.25
1.25
1.25
1.21
1.25
1.25
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
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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 the 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
2020, we are finalizing our proposal to
continue 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 factor in our 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 Payment Adjustments and
Policies
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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 percase 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 more
costly 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.
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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
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. Update to the Outlier Fixed Dollar
Loss Threshold Amount
In accordance with the update
methodology described in § 412.428(d),
we updated 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.
Based on an analysis of the latest
available data (the March 2019 update
of FY 2018 IPF claims) and rate
increases, we believe it is necessary to
update the fixed dollar loss threshold
amount to maintain an outlier
percentage that equals 2 percent of total
estimated IPF PPS payments. We are
updating the IPF outlier threshold
amount for FY 2020 using FY 2018
claims data and 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
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threshold amounts for years 2008
through 2019. Based on an analysis of
these updated data, we estimate that IPF
outlier payments as a percentage of total
estimated payments are approximately
2.23 percent in FY 2019. Therefore, we
are finalizing our proposal to update the
outlier threshold amount to $14,960 to
maintain estimated outlier payments at
2 percent of total estimated aggregate
IPF payments for FY 2020. This final
rule update is an increase from the FY
2019 threshold of $12,865.
We received one comment on our
proposed update to the outlier
threshold.
Comment: A commenter was
concerned that the 13.4 percent
proposed increase in the outlier
threshold was too steep to implement in
a single year, and suggested that when
an increase in the outlier threshold is
necessary, it should be limited to no
more than 5 percent in any given year.
Response: The outlier fixed dollar
threshold amount is calculated by
simulating aggregate payments and
using an iterative process to determine
a threshold that results in outlier
payments being equal to 2 percent of
total payments under the simulation. To
determine the IPF outlier threshold
amount for FY 2020 we estimated the
FY 2020 IPF PPS aggregate and outlier
payments using the most recent claims
available (March 2019 update of the FY
2018 MedPAR claims) and the FY 2020
final payment rates. The outlier
threshold was varied in this simulation
until estimated outlier payments
equaled 2 percent of estimated aggregate
payments. Based on the regression
analysis and payment simulations used
to develop the IPF PPS, we established
a 2 percent outlier policy in our
November 2004 IPF PPS final rule (69
FR 66960 through 66962), 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. This outlier fixed dollar
loss threshold update methodology is
based on longstanding IPF payment
policy and is described in detail in the
RY 2007 IPF PPS final rule (71 FR 27072
and 27073). To continue to maintain
this established 2 percent outlier policy,
for this final rule we must raise the IPF
PPS outlier fixed dollar threshold
amount from $12,865 to $14,960. If the
fixed dollar threshold amount increase
was limited to 5 percent for FY 2020 as
suggested by the commenter we would
not meet the established 2 percent
outlier policy. Our IPF PPS outlier
policy limiting outlier payments to a
defined percentage of total payments is
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consistent with the outlier policies in
other Medicare payment systems.
3. 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-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 we 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 available.
For FY 2020, we are finalizing our
proposal 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
2020 is 2.0239 for rural IPFs, and 1.7263
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
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actual CCR can be computed using the
first tentatively or final settled cost
report.
• 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 are finalizing our proposal to
continue to update the FY 2020 national
median and ceiling CCRs for urban and
rural IPFs based on the CCRs entered in
the latest available IPF PPS Provider
Specific File. Specifically, for FY 2020,
to be used in each of the three situations
listed previously, using the most recent
CCRs entered in the CY 2019 Provider
Specific File, we provide an estimated
national median CCR of 0.5720 for rural
IPFs and a national median CCR of
0.4370 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).
IV. Update on IPF PPS Refinements
For RY 2012, we identified several
areas of concern for future refinement,
and we invited comments on these
issues in the RY 2012 IPF PPS proposed
and final rules. For further discussion of
these issues and to review the public
comments, we refer readers to the RY
2012 IPF PPS proposed rule (76 FR
4998) and final rule (76 FR 26432).
We have delayed making refinements
to the IPF PPS until we have completed
a thorough analysis of IPF PPS data on
which to base those refinements.
Specifically, we will delay updating the
adjustment factors derived from the
regression analysis until we have IPF
PPS data that include as much
information as possible regarding the
patient-level characteristics of the
population that each IPF serves. We
have begun and will continue the
necessary analysis to better understand
IPF industry practices so that we may
refine the IPF PPS in the future, as
appropriate. Our preliminary analysis
has also revealed variation in cost and
claim data, particularly related to labor
costs, drugs costs, and laboratory
services. Some providers have very low
labor costs, or very low or missing drug
or laboratory costs or charges, relative to
other providers. As we noted in the FY
2016 IPF PPS final rule (80 FR 46693
through 46694), our preliminary
analysis of 2012 to 2013 IPF data found
that over 20 percent of IPF stays
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reported no ancillary costs, such as
laboratory and drug costs, in their cost
reports, or laboratory or drug charges on
their claims. Because we expect that
most patients requiring hospitalization
for active psychiatric treatment will
need drugs and laboratory services, we
again remind providers that the IPF PPS
federal per diem base rate includes the
cost of all ancillary services, including
drugs and laboratory services.
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 the requirement 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. For details, we
refer readers to see these Transmittals,
which are available on the CMS website
at https://www.cms.gov/Regulationsand-Guidance/Guidance/Transmittals/
index.html. CMS suspended the
requirement that cost reports from
psychiatric hospitals include certain
ancillary costs effective April 27, 2018,
in order to consider excluding allinclusive rate providers from this
requirement. 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.
We only pay 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.
We will continue to analyze data from
claims and cost reports that do not
include ancillary charges or costs, and
will be sharing our findings with CMS
Office of the Center for Program
Integrity and CMS Office of Financial
Management for further investigation, as
the results warrant. Our refinement
analysis is dependent on recent precise
data for costs, including ancillary costs.
We will continue to collect these data
and analyze them for both timeliness
and accuracy with the expectation that
these data will be used in a future
refinement. It is currently our intent to
explore refinements to the adjustments
in future rulemaking. Since we did not
propose refinements, for FY 2020 we
will continue to use the existing
adjustment factors.
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V. Inpatient Psychiatric Facilities
Quality Reporting (IPFQR) Program
A. Background and Statutory Authority
We refer readers to the FY 2019 IPF
PPS final rule (83 FR 38589) for a
discussion of the background and
statutory authority 2 of the IPFQR
Program.
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
under Medicare’s IPF PPS
(§ 412.404(b)). Generally, psychiatric
hospitals and psychiatric units within
acute care and critical access hospitals
that treat Medicare patients are paid
under the IPF PPS. Consistent with
previous regulations, we continue to use
the term 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 and
Administrative Procedures
The current IPFQR Program includes
13 measures. For more information on
these measures, we refer readers to the
following final rules:
• The FY 2013 IPPS/LTCH PPS final
rule (77 FR 53646 through 53652);
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2 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 RY update period would be 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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• The FY 2014 IPPS/LTCH PPS final
rule (78 FR 50889 through 50897);
• The FY 2015 IPF PPS final rule (79
FR 45963 through 45975);
• The FY 2016 IPF PPS final rule (80
FR 46695 through 46714);
• The FY 2017 IPPS/LTCH PPS final
rule (81 FR 57238 through 57247); and
• The FY 2019 IPF PPS final rule (83
FR 38590 through 38606).
For more information on previously
adopted procedural requirements, we
refer readers to the following rules:
• The FY 2013 IPPS/LTCH PPS final
rule (77 FR 53653 through 53660);
• The FY 2014 IPPS/LTCH PPS final
rule (78 FR 50897 through 50903;
• The FY 2015 IPF PPS final rule (79
FR 45975 through 45978);
• The FY 2016 IPF PPS final rule (80
FR 46715 through 46719);
• The FY 2017 IPPS/LTCH PPS final
rule (81 FR 57248 through 57249);
• The FY 2018 IPPS/LTCH PPS final
rule (82 FR 38471 through 38474); and
• The FY 2019 IPF PPS final rule (83
FR 38606 through 38608).
finalized our proposals to adopt
considerations for removing or retaining
measures within the IPFQR Program
and criteria for determining when a
measure is ‘‘topped out.’’ In the FY 2019
IPF PPS final rule (83 FR 38591 through
38593), we added one additional
measure removal factor. We are not
proposing any changes to these removal
factors, topped-out criteria, or retention
factors 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 will
continue to retain measures from each
previous year’s IPFQR Program measure
set for subsequent years’ measure sets,
except when we specifically propose to
remove or replace a measure. We will
continue to use the notice-and-comment
rulemaking process to propose measures
for removal or replacement, as we
described upon adopting these factors in
the 2018 IPPS/LTCH PPS final rule (82
FR 38464 through 38465).
D. IPFQR Program Measures
b. Application of Considerations for
Removal and Retention to Current
Measure Set
1. Measure Selection Process
Before being proposed for inclusion in
the IPFQR Program, measures are placed
on a list of measures under
consideration (MUC), which is
published annually by December 1 on
behalf of CMS by the National Quality
Forum (NQF). Following publication on
the MUC list, the Measure Applications
Partnership (MAP), a multi-stakeholder
group convened by the NQF, reviews
the measures under consideration for
the IPFQR Program, among other
Federal programs, and provides input
on those measures to the Secretary. We
considered the input and
recommendations provided by the MAP
in selecting all measures for the IPFQR
Program. Further details concerning the
input and recommendations from the
MAP for the measure proposed in the
FY 2020 IPF PPS Proposed rule
(Medication Continuation Following
Inpatient Psychiatric Discharge, NQF
#3205) are provided in Section V.D.3.
2. Removal or Retention of IPFQR
Program Measures
a. Background
In the FY 2018 IPPS/LTCH PPS final
rule (82 FR 38463 through 38465), we
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In the FY 2018 IPPS/LTCH PPS final
rule, we noted that several commenters
requested that we evaluate the current
measures in the IPFQR Program using
the removal and retention factors that
we finalized in that rule (82 FR 38464).
Following this evaluation, we proposed
to remove eight measures from the
IPFQR Program in the FY 2019 IPF PPS
proposed rule (83 FR 21118 through
21123) for the FY 2020 program year
and subsequent years. In the FY 2019
IPF PPS final rule (83 FR 38593 through
38604) we finalized removal of five of
these measures. In our evaluation of the
IPFQR Program measure set subsequent
to publication of the FY 2019 IPF PPS
final rule, we have not identified
additional measures to which our
measure removal factors apply.
Therefore, we are not proposing to
remove any additional measures at this
time.
The previously finalized number of
measures for the FY 2021 payment
determination and subsequent years
totals 13.
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3. Proposed New Quality Measure for
the FY 2021 Payment Determination
and Subsequent Years—Medication
Continuation Following Inpatient
Psychiatric Discharge (NQF #3205)
a. Background
Medication continuation is important
for patients discharged from the
inpatient psychiatric setting with major
depressive disorder (MDD),
schizophrenia, or bipolar disorder
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because of significant negative outcomes
associated with non-adherence to
medication regimens. For example,
patients with MDD who do not remain
on prescribed medications are more
likely to have negative health outcomes
such as relapse and readmission,
decreased quality of life, and increased
healthcare costs.3 4 Patients with
3 Geddes
JR, Carney SM, Davies C, et al. Relapse
prevention with antidepressant drug treatment in
depressive disorders: A systematic review. Lancet.
2003;361(9358):653–661.
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schizophrenia who do not adhere to
their medication regimen are more
likely to be hospitalized, use emergency
psychiatric services, be arrested, be
victims of crimes, and consume alcohol
or drugs compared to those who adhere
4 Glue P, Donovan MR, Kolluri S, Emir B.
Metaanalysis of relapse prevention antidepressant
trials in depressive disorders. The Australian and
New Zealand journal of psychiatry. 2010;44(8):697–
705.
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to their medication regimen.5 Patients
with bipolar disorder who do not adhere
to their medications have increased
suicide risk.6 For these reasons,
guidelines from the American
Psychiatric Association (APA) and the
Department of Veterans Affairs/
Department of Defense (VA/DoD),
which are based on extensive literature,
recommend pharmacotherapy as the
primary form of treatment for patients
with these conditions.7 8 9 10 11
Furthermore, we believe that there are
factors external to the IPF that influence
filling prescriptions post-discharge in
the psychiatric population. While it may
not be possible to achieve complete
post-discharge compliance with
pharmacotherapy, there is evidence that
improvements to the quality of care
provided by IPFs, including discharge
processes, can help to increase
medication continuation rates.12 13 14 15 16
5 Gilmer TP, Dolder CR, Lacro JP, et al. Adherence
to treatment with antipsychotic medication and
health care costs among Medicaid beneficiaries
with schizophrenia. The American journal of
psychiatry. 2004;161(4):692–699.
6 Gonzalez-Pinto A, Mosquera F, Alonso M, et al.
Suicidal risk in bipolar I disorder patients and
adherence to long-term lithium treatment. Bipolar
disorders. 2006;8(5 Pt 2):618–624.
7 American Psychiatric Association. (2002).
Practice guideline for the treatment of patients with
bipolar disorder, second edition. Retrieved from:
https://psychiatryonline.org/pb/assets/raw/sitewide/
practice_guidelines/guidelines/bipolar.pdf.
8 American Psychiatric Association. (2010).
Practice guideline for the treatment of patients with
major depressive disorder, 3rd ed. Retrieved from:
https://psychiatryonline.org/pb/assets/raw/sitewide/
practice_guidelines/guidelines/mdd.pdf.
9 American Psychiatric Association. (2010).
Practice guideline for the treatment of patients with
schizophrenia: 2nd ed. Retrieved from: https://
psychiatryonline.org/pb/assets/raw/sitewide/
practice_guidelines/guidelines/schizophrenia.pdf.
10 U.S. Department of Veterans Affairs, & U.S.
Department of Defense. (2016). Management of
major depressive disorder (MDD). Retrieved from:
https://www.healthquality.va.gov/guidelines/MH/
mdd/VADoDMDDCPGFINAL82916.pdf.
11 U.S. Department of Veterans Affairs & U.S.
Department of Defense. (2010) VA/DOD clinical
practice guideline for management of bipolar
disorder in adults. Retrieved from: https://
www.healthquality.va.gov/guidelines/MH/bd/bd_
305_full.pdf.
12 Haddad PM, Brain C, Scott J. Nonadherence
with antipsychotic medication in schizophrenia:
challenges and management strategies. Patient
related outcome measures. 2014;5:43–62.
13 Hung CI. Factors predicting adherence to
antidepressant treatment. Current opinion in
psychiatry. 2014;27(5):344–349.
14 Lanouette NM, Folsom DP, Sciolla A, Jeste DV.
Psychotropic medication nonadherence among
United States Latinos: a comprehensive literature
review. Psychiatric services (Washington, DC).
2009;60(2):157–174.
15 Mitchell AJ. Understanding Medication
Discontinuation in Depression. BMedSci
Psychiatric Times. 2007;24(4).
16 Sylvia LG, Hay A, Ostacher MJ, et al.
Association between therapeutic alliance, care
satisfaction, and pharmacological adherence in
bipolar disorder. Journal of clinical
psychopharmacology. 2013;33(3):343–350.
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These interventions include patient
education, enhanced therapeutic
relationships, shared decision-making,
and text-message reminders, with
multidimensional approaches resulting
in the best outcomes.
We proposed to adopt the Medication
Continuation Following Inpatient
Psychiatric Discharge measure (NQF
#3205) for the FY 2020 payment
determination and subsequent years in
the FY 2018 IPPS/LTCH PPS proposed
rule (82 FR 20122 through 20126) to
address this important clinical topic. In
the FY 2018 IPPS/LTCH PPS final rule
(82 FR 38465 through 38470), we did
not finalize adoption of the Medication
Continuation Following Inpatient
Psychiatric Discharge measure (NQF
#3205), because we recognized that this
measure may place undue burden on
facilities that were updating processes
to account for previously adopted
measures despite being calculated from
claims data, which should not require
additional information collection
burden. We did not want to place undue
burden on facilities, especially small,
rural facilities, and we wished to
accommodate the need for facilities to
develop and implement innovative
efforts, such as updating their processes
and clinical workflows, for this
measure.
At that time, we stated that we would
consider proposing this measure again
in future rulemaking. We note that since
the FY 2018 IPPS/LTCH PPS final rule,
we have removed five measures from
the IPFQR Program (83 FR 38593
through 38602), reducing burden on
IPFs by approximately 546,000 hours
and $20 million (83 FR38610 through
38611), and IPFs have had an additional
2 years to familiarize themselves with
the remaining IPFQR Program measure
set and to update processes and clinical
workflows accordingly. Therefore, we
believe that it is now appropriate to
propose this measure for the IPFQR
Program again.
Since the FY 2018 IPPS/LTCH PPS
final rule, we have not made any
changes to the Medication Continuation
Following Inpatient Psychiatric
Discharge (NQF #3205) measure’s
specifications. However, we have taken
steps to improve upon the suitability of
this measure for the IPFQR Program.
First, we considered recommendations
and comments received on the
Medication Continuation Following
Inpatient Psychiatric Discharge (NQF
#3205) measure from the FY 2018 IPPS/
LTCH PPS final rule (82 FR 38468
through 38470). We provide more detail
about these comments.
Second, since the FY 2018 IPPS/
LTCH PPS final rule, we have provided
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38461
additional information about this
measure to the MAP and to the NQF,
including reliability and validity testing.
The measure was subsequently
endorsed by NQF. We continue to
believe that this measure evaluates a
process with a demonstrated quality
gap, because in testing this measure, we
found that the range of performance
between the 10th percentile and the
80th percentile facility performance was
between 67 percent and 88 percent. We
found that if all facilities had at least the
median rate then 16,000 additional
Medicare beneficiaries would fill
prescriptions for an evidence-based
medication to manage their condition
following discharge.17 Furthermore, we
believe this measure has the potential to
benefit patients by encouraging facilities
to adopt interventions to improve post
discharge medication continuation rates
with no additional reporting burden to
IPFs.
In response to our proposal in the FY
2018 IPPS/LTCH PPS proposed rule,
many comments focused on the
potential undue burden of the measure
given the fact that many facilities were
still updating processes to account for
previously adopted measures (82 FR
38469). Between the FY 2018 IPPS/
LTCH PPS final rule and this proposed
rule, we have not adopted any new
measures into the program. We believe
that IPFs no longer need to update
processes to account for previously
adopted measures because they have
had 2 years to complete all such
updates. Therefore, we believe that
there is less burden associated with the
IPFQR program than when we proposed
to adopt this measure in the FY 2018
IPPS/LTCH PPS proposed rule.
Some commenters also expressed
concern that patients may experience
barriers to filling prescriptions that are
beyond the control of IPFs (82 FR 38469
through 38470). While we believe that
there are factors external to an IPF that
influence filling prescriptions after a
patient is discharged, as the
methodology report for the measure
indicates,18 IPFs can also undertake
interventions to improve the likelihood
of a patient’s medication continuation
post-discharge.
In response to comments that the
affected population may be too small to
17 https://www.cms.gov/Medicare/QualityInitiatives-Patient-Assessment-Instruments/
HospitalQualityInits/Downloads/Version_1-0_
Inpatient_Psychiatric_Facility_Medication_
Continuation_Public.zip.
18 https://www.cms.gov/Medicare/QualityInitiatives-Patient-Assessment-Instruments/
HospitalQualityInits/Downloads/Version_1-0_
Inpatient_Psychiatric_Facility_Medication_
Continuation_Public.zip
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report meaningful data because it is
limited to Medicare patients enrolled in
Parts A, B, and D (82 FR 38469 through
38470), we note that the NQF found this
measure to be valid and reliable,19
indicating that the size of the
population is sufficient to report
meaningful data. These commenters
additionally expressed that because the
measure is limited to Medicare patients
enrolled in Parts A, B, and D, there may
not be a performance gap because these
patients do not experience the same
access barriers as other inpatient
psychiatric populations. However, we
note that in their endorsement review of
the measure, the NQF found that there
was evidence of a performance gap in
the quality area that was addressed by
the measure even though the measure is
limited to patients enrolled in Medicare
A, B, and D.20
Finally, in response to comments that
the measure had not completed full
endorsement review by NQF (82 FR
38469), the measure is now fully
endorsed by the NQF as discussed in
more detail in Section B of this rule.
Further, in its review of the measure for
endorsement, the NQF standing
committee agreed that there is evidence
that lack of adherence to medication
leads to relapse and negative outcomes
and that claims data related to
medication adherence are directly
correlated to outcomes.21
b. Overview of Measure
The Medication Continuation
Following Inpatient Psychiatric
Discharge measure (NQF #3205)
assesses whether patients admitted to
IPFs with diagnoses of MDD,
schizophrenia, or bipolar disorder filled
at least one evidence-based medication
prior to discharge or during the postdischarge period. As detailed in the
following discussion, the NQF endorsed
this measure on June 28, 2017. For more
information about this measure, we refer
readers to the measure specifications in
the measure technical report https://
www.cms.gov/Medicare/QualityInitiatives-Patient-AssessmentInstruments/HospitalQualityInits/
Downloads/Version_1-0_Inpatient_
Psychiatric_Facility_Medication_
Continuation_Public.zip) or the
measure’s NQF page (https://
www.qualityforum.org/QPS/3205).
In compliance with section
1890A(a)(2) of the Act, this measure was
included in a publicly available
19 https://www.qualityforum.org/WorkArea/
linkit.aspx?LinkIdentifier=id&ItemID=85831.
20 https://www.qualityforum.org/WorkArea/
linkit.aspx?LinkIdentifier=id&ItemID=85831.
21 https://www.qualityforum.org/WorkArea/
linkit.aspx?LinkIdentifier=id&ItemID=85831
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document: ‘‘List of Measures under
Consideration for December 1, 2016’’
(https://www.cms.gov/Medicare/
Quality-Initiatives-Patient-AssessmentInstruments/QualityMeasures/
Downloads/Measures-underConsideration-List-for-2016.pdf). The
MAP Hospital Workgroup concluded in
its December 2016 meeting that the
measure addressed a critical quality
objective, was evidence-based, and
would contribute to efficient use of
resources.22 One Workgroup member
commented that it was appropriate to
hold IPFs accountable for patients
filling a prescription for an evidencebased medication post-discharge.
The MAP Hospital Workgroup
classified the measure as ‘‘Refine and
Resubmit Prior to Rulemaking.’’ 23 The
measure received this classification
because the MAP recommended that
measure testing be completed to
demonstrate reliability and validity at
the facility level in the hospital setting
and that the measure be submitted to
NQF for review and endorsement.24 The
MAP also requested additional details
on the measure, such as: (1) The
definition of medication dispensation;
(2) how the facility would know
whether the medication was dispensed;
and (3) how the measure would be
impacted if Medicare Part D coverage is
optional.25 The methodology report for
the measure (https://www.cms.gov/
Medicare/Quality-Initiatives-PatientAssessment-Instruments/
QualityMeasures/Downloads/Measuresunder-Consideration-List-for-2016.pdf)
that we finalized, includes the results of
reliability and validity testing, and
additional measure updates that
occurred after the MAP review. This
newest methodology report also
provides the additional details
requested by the MAP at the December
2016 meeting. This includes the specific
medication list, which is based on APA
and VA/DoD practice guidelines for
each medication 26 27 28 29 30 and
22 MAP Hospital Workgroup, Preliminary
Analysis Worksheet. December 2016. https://
www.qualityforum.org/WorkArea/linkit.aspx?
LinkIdentifier=id&ItemID=84199.
23 https://www.qualityforum.org/WorkArea/
linkit.aspx?LinkIdentifier=id&ItemID=84452.
24 https://www.qualityforum.org/WorkArea/
linkit.aspx?LinkIdentifier=id&ItemID=84452.
25 https://www.qualityforum.org/WorkArea/
linkit.aspx?LinkIdentifier=id&ItemID=84452.
26 American Psychiatric Association. (2010).
Practice guideline for the treatment of patients with
major depressive disorder, 3rd ed. Retrieved from:
https://psychiatryonline.org/pb/assets/raw/sitewide/
practice_guidelines/guidelines/mdd.pdf.
27 American Psychiatric Association. (2002).
Practice guideline for the treatment of patients with
bipolar disorder, second edition. Retrieved from:
https://psychiatryonline.org/pb/assets/raw/sitewide/
practice_guidelines/guidelines/bipolar.pdf.
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information about how facilities can
help patients fill prescriptions for
medications to ensure that the facility
knows that the prescription has been
filled. Additionally, the methodology
report provides details about measure
performance among patients with Part D
and the performance gap for this patient
population.
This measure was submitted to NQF
for endorsement on December 16, 2016.
Consistent with the recommendation
from the December 2016 MAP meeting
that testing for reliability and validity
should be completed, in Spring 2017 we
refined our NQF submission by
providing the complete results of all
testing for NQF’s review of the measure
for endorsement. The measure received
NQF endorsement on June 28, 2017.31
This measure supports the CMS
Meaningful Measure Area ‘‘promote
effective prevention and treatment of
chronic disease,’’ which includes the
meaningful measure area of
‘‘prevention, treatment, and
management of mental health.’’ The
measure would also complement the
portfolio of facility-level measures in
the IPFQR Program that assess the
transition from the inpatient to
outpatient setting: Follow-Up After
Hospitalization for Mental Illness;
Thirty-day All Cause Unplanned
Readmission Following Psychiatric
Hospitalization in an Inpatient
Psychiatric Facility; Transition Record
with Specified Elements Received by
Discharged Patients; and Timely
Transmission of Transition Record.
c. Data Sources
The proposed Medication
Continuation Following Inpatient
Psychiatric Discharge measure (NQF
#3205) uses Medicare fee-for-service
(FFS) claims to identify whether
patients admitted to IPFs with diagnoses
of MDD, schizophrenia, or bipolar
disorder filled at least one evidencebased medication such that they would
have medication for use post-discharge.
The performance period for this
measure is 24 months. For example, for
28 American Psychiatric Association. (2010).
Practice guideline for the treatment of patients with
schizophrenia: 2nd ed. Retrieved from: https://
psychiatryonline.org/pb/assets/raw/sitewide/
practice_guidelines/guidelines/schizophrenia.pdf.
29 U.S. Department of Veterans Affairs & U.S.
Department of Defense. (2016). Management of
major depressive disorder (MDD). Retrieved from:
https://www.healthquality.va.gov/guidelines/MH/
mdd/VADoDMDDCPGFINAL82916.pdf.
30 U.S. Department of Veterans Affairs & U.S.
Department of Defense. (2010) VA/DOD clinical
practice guideline for management of bipolar
disorder in adults. Retrieved from: https://
www.healthquality.va.gov/guidelines/MH/bd/bd_
305_full.pdf.
31 https://www.qualityforum.org/QPS/3205.
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the FY 2021 payment determination, the
performance period will include
discharges between July 1, 2017 and
June 30, 2019.32
d. Measure Calculation
The numerator for the measure
includes discharges for patients with a
principal diagnosis of MDD,
schizophrenia, or bipolar disorder in the
denominator who were dispensed at
least one evidence-based outpatient
medication within 2 days prior to
discharge through 30 days postdischarge. The denominator for the
measure includes Medicare fee-forservice (FFS) beneficiaries with Part D
coverage aged 18 years and older
discharged to home or home health care
from an IPF with a principal diagnosis
of MDD, schizophrenia, or bipolar
disorder. The denominator excludes
discharges for patients who:
• Received Electroconvulsive
Therapy (ECT) during the inpatient stay
or 30 day post-discharge period;
• Received Transcranial Magnetic
Stimulation (TMS) during the inpatient
stay or follow-up;
• Were pregnant during the inpatient
stay;
• Had a secondary diagnosis of
delirium; or
• Had a principal diagnosis of
schizophrenia with a secondary
diagnosis of dementia.
For more information about the
development of the measure, including
rationale for the 2 day prior to 30 day
post-discharge period and the
denominator exclusions, we refer
readers to the measure technical report
(https://www.cms.gov/Medicare/
Quality-Initiatives-Patient-AssessmentInstruments/HospitalQualityInits/
Downloads/Version1-0_Inpatient_
Psychiatric_Facility_Medication_
Continuation_Public.zip).
We invited public comment on our
proposal to adopt the Medication
Continuation Following Inpatient
Psychiatric Discharge (NQF #3205)
measure for the FY 2021 payment
determination and subsequent years as
discussed.
Comment: Several commenters
expressed support for the Medication
Continuation Following Inpatient
Psychiatric Discharge (NQF #3205)
measure specifically noting that it is an
NQF-endorsed measure that addresses
an important clinical topic with a
demonstrated quality gap. Several of
32 If data availability or operational issues prevent
use of this performance period, we would announce
the updated performance period through subregulatory communications including
announcement on a CMS website and/or on our
applicable listservs.
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these commenters noted that the
measure will help facilities identify
interventions for post-discharge
medication compliance, thereby
improving care transitions. Some
commenters further expressed that the
measure aligns with the goal of not
increasing provider burden.
Response: We thank these
commenters for their support.
Comment: Some commenters
recommended that CMS not adopt the
Medication Continuation Following
Inpatient Psychiatric Discharge (NQF
#3205) measure because this measure
imposes burden on facilities.
Response: We do not believe that this
measure imposes any data reporting
burden on facilities because it is
calculated by CMS using data submitted
on Medicare Parts A, B, and D claims.
We acknowledge that to improve
performance on this measure there may
be costs or burden associated with
updating clinical workflows to improve
discharge planning and counseling on
the importance of medication
continuation. However, because of the
severity of the negative health outcomes
associated with medication
discontinuation for this patient
population, we believe that these
updates are part of providing high
quality inpatient psychiatric care.
Comment: Some commenters
recommended that CMS not adopt
Medication Continuation Following
Inpatient Psychiatric Discharge (NQF
#3205) because they believe that
restricting the denominator to patients
who have Medicare Parts A, B, and D
coverage makes the population size too
small to be meaningful.
Response: During measure testing, the
denominator was restricted to patients
who have Medicare Parts A, B, and D
coverage during measure testing and
results showed that the majority of
providers met the 75 case minimum
threshold required to obtain an overall
reliability score of at least 0.7, which is
the minimum acceptable reliability
rating. Furthermore, the NQF standing
committee evaluated this when
considering the measure for
endorsement and determined that the
measure meets their scientific
acceptability criteria.33
Comment: Some commenters
recommended that CMS not adopt this
measure because they believe that the
measure assesses patient behavior (that
is, filling prescriptions) as opposed to
provider quality and therefore does not
33 https://www.qualityforum.org/Projects/a-b/
Behavioral_Health_2016-2017/Draft_Report_for_
Comment.aspx.
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38463
produce data that will help consumers
select facilities.
Response: We recognize that there are
factors external to the IPF that influence
filling prescriptions post-discharge in
the psychiatric population. While it may
not be possible to achieve complete
post-discharge compliance with
pharmacotherapy, there is evidence that
improvements to the quality of care for
patients in the IPF setting, including the
discharge processes, can help to
increase medication continuation
rates.34 35 36 37 38 These interventions
include patient education, enhanced
therapeutic relationships, shared
decision-making, and text-message
reminders, with multidimensional
approaches resulting in the best
outcomes. We note that in testing the
measure, the measure developer found a
median score of 79.6% and an
approximate 21-percentage point
difference between the 10th and 90th
percentiles. This means that in the 10th
percentile facilities, depending on their
condition, 60.0 to 63.9 percent of
patients (with Medicare Parts A, B, and
D) fill prescriptions for evidence-based
medications, whereas in the 90th
percentile facilities 89.7 to 95.5 percent
of such patients fill prescriptions for
evidence-based medications.39 We
believe that this performance gap,
coupled with the ability of facilities to
provide interventions to improve
medication continuation, indicate that
the measure does provide meaningful
information about the quality of care
provided to patients.
Comment: Several commenters
recommended that CMS not adopt the
Medication Continuation Following
Inpatient Discharge (NQF #3205)
measure because these commenters
believe prescription fills do not actually
reflect medication adherence.
34 Haddad PM, Brain C, Scott J. Nonadherence
with antipsychotic medication in schizophrenia:
challenges and management strategies. Patient
related outcome measures. 2014;5:43–62.
35 Hung CI. Factors predicting adherence to
antidepressant treatment. Current opinion in
psychiatry. 2014;27(5):344–349.
36 Lanouette NM, Folsom DP, Sciolla A, Jeste DV.
Psychotropic medication nonadherence among
United States Latinos: a comprehensive literature
review. Psychiatric services (Washington, DC).
2009;60(2):157–174.
37 Mitchell AJ. Understanding Medication
Discontinuation in Depression. BMedSci
Psychiatric Times. 2007;24(4).
38 Sylvia LG, Hay A, Ostacher MJ, et al.
Association between therapeutic alliance, care
satisfaction, and pharmacological adherence in
bipolar disorder. Journal of clinical
psychopharmacology. 2013;33(3):343–350.
39 https://www.cms.gov/Medicare/QualityInitiatives-Patient-Assessment-Instruments/
HospitalQualityInits/Downloads/Version_1-0_
Inpatient_Psychiatric_Facility_Medication_
Continuation_Public.zip.
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Response: While we agree with
commenters that it is possible that
patients may fill prescriptions and then
not take the medication, or take it
incorrectly, we believe that the measure
is a good indicator of patient adherence
to medication regimens. The NQF
Standing Committee for Behavioral
Health evaluated the potential for
patients to fill their prescriptions but
not be adherent to the medication
regimen during their review of the
measure and found that most studies
related to adverse events for medication
non-compliance used the filling of a
prescription as a proxy for medication
adherence,40 which aligns with this
measure’s methodology.
Comment: One commenter
recommended that CMS not adopt this
measure because facilities cannot
internally track performance on this
measure and therefore cannot identify
performance gaps that require
interventions.
Response: We believe that this
measure will help facilities identify
performance gaps that require
interventions by making this data
available to facilities. We also note that
the American Psychiatric Association’s
(APA’s) and Department of Veterans
Affairs and Department of Defense (VA/
DoD) practice guidelines for depressive
disorder, bipolar disorder, and
schizophrenia provide strategies for
facilities to implement to help patients
fill prescriptions prior to discharge so
that the facility can track whether the
prescription has been filled.41 42 43 44 45
Comment: Several commenters
expressed the belief that this measure is
not appropriate for the inpatient
psychiatric setting and suggested that
40 https://www.qualityforum.org/Projects/a-b/
Behavioral_Health_2016-2017/Draft_Report_for_
Comment.asp.
41 American Psychiatric Association. (2010).
Practice guideline for the treatment of patients with
major depressive disorder, 3rd ed. Retrieved from:
https://psychiatryonline.org/pb/assets/raw/sitewide/
practice_guidelines/guidelines/mdd.pdf.
42 American Psychiatric Association. (2002).
Practice guideline for the treatment of patients with
bipolar disorder, second edition. Retrieved from:
https://psychiatryonline.org/pb/assets/raw/sitewide/
practice_guidelines/guidelines/bipolar.pdf.
43 American Psychiatric Association. (2010).
Practice guideline for the treatment of patients with
schizophrenia: 2nd ed. Retrieved from: https://
psychiatryonline.org/pb/assets/raw/sitewide/
practice_guidelines/guidelines/schizophrenia.pdf.
44 U.S. Department of Veterans Affairs & U.S.
Department of Defense. (2016). Management of
major depressive disorder (MDD). Retrieved from:
https://www.healthquality.va.gov/guidelines/MH/
mdd/VADoDMDDCPGFINAL82916.pdf.
45 U.S. Department of Veterans Affairs & U.S.
Department of Defense. (2010) VA/DOD clinical
practice guideline for management of bipolar
disorder in adults. Retrieved from: https://
www.healthquality.va.gov/guidelines/MH/bd/bd_
305_full.pdf.
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this or a similar measure be considered
for the outpatient setting instead
because these commenters believe that
outpatient providers have more
influence on patients’ post-discharge
care.
Response: We agree with the
commenters that outpatient providers
do have more influence on a patient’s
post-discharge care in the long term;
however this measure is specified to
address the short term period
immediately following discharge from
the IPF prior to the patient’s follow-up
with an outpatient provider (which,
according to data collected through the
Follow-Up After Hospitalization for
Mental Illness (NQF #0576) measure,
will be more than 30 days postdischarge nearly half of all patients).46
Therefore, we do not agree that this
measure would be more appropriate for
the outpatient setting. This measure
addresses care provided during the
discharge planning phase of care, which
occurs within the IPF to facilitate a safe
care transition until the patient can be
seen by an outpatient provider. We note
that the period immediately following
discharge from a psychiatric hospital is
a high-risk period for patients, and has
been linked to an increased risk of
adverse outcomes, including
suicide.47 48 We believe it is vital that
patients have continuity of
pharmacotherapy consistent with the
prescriptions provided by their
inpatient providers until they can
develop a long-term care plan with their
outpatient providers
Comment: One commenter expressed
concern that because this measure’s
patient population has Medicare Parts
A, B, and D coverage, these patients do
not experience the same barriers to
access experienced by patients without
similar health insurance coverage and
therefore the measure may not provide
meaningful data.
Response: We agree that the patients
included in the measure may not
experience the same barriers to access to
medications that some other patients
encounter because they have insurance
and low-income Medicare patients
qualify for additional support to help
pay for medications. However, as
previously noted, in the measure
technical report,49 the claims data used
46 https://www.medicare.gov/hospitalcompare/
psych-measures.html.
47 https://www.ncbi.nlm.nih.gov/pubmed/
27654151.
48 https://psychnews.psychiatryonline.org/doi/
full/10.1176/appi.pn.2017.7a17.
49 https://www.cms.gov/Medicare/QualityInitiatives-Patient-Assessment-Instruments/
HospitalQualityInits/Downloads/Version_1-0_
Inpatient_Psychiatric_Facility_Medication_
Continuation_Public.zip.
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for analysis and testing of this measure
demonstrated ample opportunity for
improvement in medication
continuation rates for patients with
Medicare Parts A, B, and D, with
median medication continuation rates of
79% and a variation of 21 percentage
points between the 10th and 90th
percentile facilities. Further,
considering that the Medicare
population may have lower barriers to
access, we would expect to see higher
medication continuation rates and less
variation in performance across
facilities.
In addition, we note that while the
measure denominator includes only
patients with Medicare Parts A, B, and
D, all patients can benefit from the
evidence-based interventions that
facilities may implement to improve
medication adherence.
Comment: One commenter requested
clarification of how CMS will assess
prescription refills for patients who do
not have Part D.
Response: We note that the
denominator of this measure is
restricted to patients who have
Medicare Parts A, B, and D coverage.
Therefore, we will not assess
prescription refills for patients who do
not have Part D coverage because they
are not in the measure’s patient
population.
Comment: One commenter expressed
concern that the measure will not
capture medication continuity for
patients who filled 90-day supplies
prior to admission.
Response: During measure testing, we
found that the number of patients who
filled a 90-day prescription in the 90
days prior to admission was small.
Specifically, 5.5 percent of those with
major depressive disorder had a 90-day
prescription at some point in the 90
days prior to admission, 2.8 percent of
those with bipolar disorder had such a
prescription, and 1.2 percent of those
with schizophrenia had such a
prescription. Furthermore, we believe
that medications are often adjusted
during the inpatient stay, and patients
may need to fill a new prescription
following discharge even if they have
medications at home. Therefore, we
believe that the patient population with
appropriate pharmacotherapy due to 90day prescriptions prior to admission is
very small and does not necessitate any
changes to the measure specifications.
Comment: One commenter expressed
concern that 2 days prior to discharge is
too brief a period and recommended
expanding the period to 5 days prior to
discharge.
Response: When we developed and
tested this measure, we found that most
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outpatient medications filled during the
inpatient stay are filled one day prior to
discharge.50 In consulting with clinical
experts, we found that discharge
planning, including filling
prescriptions, could start as early as two
days prior to discharge. These experts
unanimously agreed to extend the
follow-up period to include two days
prior to discharge.51 Because most
medications filled during the stay are
filled one day prior to discharge and
discharge planning typically starts two
days prior to discharge we believe that
this measure period is appropriate.
Comment: Several commenters
requested clarification of whether the
data would be publicly reported
annually or every two years because the
measure has a two year performance
period. These commenters further
expressed concern that if data is
reported annually the data may
misrepresent facilities with recent
improvement.
Response: The IPFQR Program
publicly displays all measure data
annually (78 FR 50897 through 50898
and 81 FR 57248 through 57249). For
this measure we will post the data
annually using a two-year performance
period, similar to our reporting of the
Thirty-Day All-Cause Unplanned
Readmission Following Psychiatric
Hospitalization in an Inpatient
Psychiatric Facility (NQF #2860)
measure. As an example, for both
measures the intended performance
period for FY 2021 reporting is July 1,
2017 through June 30, 2019. For FY
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50 https://www.cms.gov/Medicare/QualityInitiatives-Patient-Assessment-Instruments/
HospitalQualityInits/Downloads/Version_1-0_
Inpatient_Psychiatric_Facility_Medication_
Continuation_Public.zip.
51 Ibid.
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2022 reporting the performance period
is July 1, 2018 through June 30, 2020.
We note that these periods do overlap;
however we believe that facilities with
recent improvement will be
distinguishable because their scores will
show year-over-year improvement.
Comment: One commenter expressed
concern that facilities without
outpatient pharmacies may be at a
performance disadvantage because they
cannot ensure that patients fill
prescriptions prior to discharge.
Response: We believe that many of
the interventions to improve
performance on this measure (for
example, patient education at discharge,
therapeutic alliance, text message
reminders, etc.) are applicable to all
facilities, regardless of whether they
have an outpatient pharmacy on
premises. Furthermore, we note that the
practice guidelines for these conditions
provide strategies for facilities to
implement to help patients fill
prescriptions prior to discharge so that
the facility can track whether the
prescription has been filled.52 53 54 55 56
52 American Psychiatric Association. (2010).
Practice guideline for the treatment of patients with
major depressive disorder, 3rd ed. Retrieved from:
https://psychiatryonline.org/pb/assets/raw/sitewide/
practice_guidelines/guidelines/mdd.pdf.
53 American Psychiatric Association. (2002).
Practice guideline for the treatment of patients with
bipolar disorder, second edition. Retrieved from:
https://psychiatryonline.org/pb/assets/raw/sitewide/
practice_guidelines/guidelines/bipolar.pdf.
54 American Psychiatric Association. (2010).
Practice guideline for the treatment of patients with
schizophrenia: 2nd ed. Retrieved from: https://
psychiatryonline.org/pb/assets/raw/sitewide/
practice_guidelines/guidelines/schizophrenia.pdf.
55 U.S. Department of Veterans Affairs & U.S.
Department of Defense. (2016). Management of
major depressive disorder (MDD). Retrieved from:
https://www.healthquality.va.gov/guidelines/MH/
mdd/VADoDMDDCPGFINAL82916.pdf.
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Comment: One commenter requested
that CMS provide guidance on what
medications are considered evidencebased medications for these conditions.
Response: The measure technical
report available at https://www.cms.gov/
Medicare/Quality-Initiatives-PatientAssessment-Instruments/
HospitalQualityInits/Downloads/
Version_1-0_Inpatient_Psychiatric_
Facility_Medication_Continuation_
Public.zip has a detailed list of
medications for each condition. As part
of routine measure maintenance, we
will evaluate and update this list on a
recurrent basis.
Final Rule Action: After consideration
of the public comments, we are
finalizing as proposed the adoption of
the Medication Continuation Following
Inpatient Psychiatric Discharge (NQF
#3205) measure for the FY 2021
payment determination and subsequent
years.
4. Summary of Previously Finalized and
Newly Proposed Measures for the FY
2021 Payment Determination and
Subsequent Years
The previously finalized number of
measures for the FY 2021 payment
determination and subsequent years
totals 13. In this final rule, we are
adopting one additional measure for the
FY 2021 payment determination and
subsequent years which, brings the total
to 14, as shown in table 18.
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56 U.S. Department of Veterans Affairs & U.S.
Department of Defense. (2010) VA/DOD clinical
practice guideline for management of bipolar
disorder in adults. Retrieved from: https://
www.healthquality.va.gov/guidelines/MH/bd/bd_
305_full.pdf.
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Table 18. Previously Finalized and Newly Proposed Measures for the FY 2021
Payment Determination and Subsequent Years
NQF#
0640
0641
Measure ID
HBIPS-2
HBIPS-3
0560
HBIPS-5
0576
FUH
N/A*
SUB-2 and
SUB-2a
N/A*
SUB-3 and
SUB-3a
N/A*
TOB-2 and
TOB-2a
N/A*
TOB-3 and
TOB-3a
1659
IMM-2
N/A*
N/A
N/A*
N/A
N/A
N/A
2860
N/A
3205
N/A
Measure
Hours of Physical Restraint Use
Hours of Seclusion Use
Patients Discharged on Multiple Antipsychotic
Medications with Appropriate Justification
Follow-up After Hospitalization for Mental Illness
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 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)
Timely Transmission of Transition Record
(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 Discharge from
aniPF
* Measure IS no longer endorsed by the NQF but was endorsed at tnne of adoptiOn. SectiOn
1886(s)(4)(D)(ii) of the Act authorizes the Secretary to specify a measure that is not endorsed by the NQF
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 fmd 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.
5. Possible IPFQR Program Measures
and Topics for Future Consideration
As we have previously indicated in
the FY 2015 IPF PPS final rule (79 FR
45974 through 45975), we seek to
develop a comprehensive set of quality
measures to be available for widespread
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use for informed decision-making and
quality improvement in the IPF setting.
In the FY 2020 IPF PPS proposed rule,
we sought public comments on possible
new measures or new measure topics.
We welcomed all comments but
expressed particular interest in
comments on future adoption of one or
more measures of patient experience of
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care based on a consumer survey,
especially such as the Hospital
Consumer Assessment of Healthcare
Providers and Systems (HCAHPS)
Survey, and potential future measures
and topics as part of CMS’ Meaningful
Measures Framework.
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a. Future Adoption a Patient Experience
of Care Survey
In past assessments of the IPFQR
Program Measure Set, we identified
Patient Experience of Care as a measure
gap area for this program (78 FR 50897,
79 FR 45964 through 45965, and 83 FR
38596 through 38597), which is
consistent with input from past public
comment (77 FR 53653). When we
adopted the ‘‘Assessment of Patient
Experience of Care Measure’’ for the FY
2016 payment determination and
subsequent years, we noted that in
addition to serving as an indicator of
quality within IPFs, information
gathered through the collection of this
measure would be helpful in developing
a standardized survey as a successor to
the measure (79 FR 45964). When we
removed the Assessment of Patient
Experience of Care measure from the
IPFQR Program, we stated we believe
that we have now collected sufficient
information to inform development of a
patient experience of care measure (83
FR 38596).
At that time, several commenters
expressed support for ensuring that
patients have an opportunity to express
their perspectives on their experience of
receiving care at an IPF (83 FR 38597).
Our analysis of the FY 2018 payment
determination data (that is, data that
represents facility assessment of patient
experience of care as of December 31,
2016) collected under the Assessment of
Patient Experience of Care measure
shows that approximately one third of
facilities use the Hospital Consumer
Assessment of Healthcare Providers and
Systems (HCAHPS) survey 57 to assess
patient experience of care. This is more
than the portion of facilities using any
other survey.
We sought public comment on how
such providers have implemented the
survey in their facilities, on whether
they use the entire HCAHPS survey, or
a subset of the survey questions; and if
a subset, which specific questions they
use. Additionally, we sought public
comment on other potential surveys that
commenters believe would be
appropriate to adopt for the IPFQR
Program. We intend to use this
information to inform future
development and testing of a surveybased patient experience of care
measure (or measures) for the inpatient
psychiatric patient population.
Comment: Many commenters
supported future adoption of a patient
experience of care survey. Several of
57 For more information about the HCAHPS
survey, please see https://www.ahrq.gov/cahps/
surveys-guidance/hospital/about/adult_hp_
survey.html.
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these commenters expressed concern
about the potential adoption of the
HCAHPS survey for this patient
population, specifically noting that this
survey does not include some of the
unique aspects of inpatient psychiatric
care including group therapy, nonphysician providers, and involuntary
admissions. Some commenters observed
that while most IPFs use a patient
experience of care survey, there is not
one survey used predominantly across
settings and recommended that CMS
partner with providers to either develop
a minimally burdensome survey or to
establish a core set of questions that
should be included, therefore allowing
provider flexibility to ask additional
questions. These commenters believe
that a custom developed survey would
better address the needs of the patient
population and would be preferable for
providers than having to switch from a
setting specific survey to a survey not
designed for this setting. One
commenter recommended that adoption
of a patient experience of care measure
should be done incrementally through a
voluntary data collection period to
ensure feasibility of collection prior to
mandatory data submission. Several
commenters also noted that the
HCAHPS survey modalities (phone or
mail post-discharge) may limit
participation and recommended
additional survey modalities for this
potentially more transient patient
population. One commenter expressed
concern that a patient experience of care
measure could be misinterpreted as the
current state of care when the data has
been collected in the past.
Response: We thank these
commenters for their input and will
consider these suggestions and concerns
as we seek to develop or select an
appropriate patient experience of care
survey for the IPF setting.
b. Other Future Measures
In the FY 2020 IPF PPS proposed rule,
we also sought feedback and suggestions
for future measures and topics for the
IPFQR Program that align with CMS’s
Meaningful Measures Framework (FY
2019 IPF PPS final rule, 83 FR 38590
through 38591).
Comment: One commenter
recommended that CMS collaborate
with providers to identify measure
concepts and develop measures
appropriate to the setting. Several
commenters provided recommendations
for future measure considerations;
specifically measures that assess:
• Facility use of a standardized
assessment of patient outcomes between
admission and discharge;
• Family and caregiver engagement;
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38467
• Clinical improvement outcomes;
• Patient empowerment;
• Safety planning for patients with
suicidal ideation;
• Discharge and transitions of care;
• Access to care; and
• Inpatient assaults and violence.
Response: We thank these
commenters for their suggestions and
will consider these concepts as we
continue to develop a measure set that
meets the specific needs of IPFs and
inpatient psychiatric patients and their
families.
E. Public Display and Review
Requirements
We refer readers to the FY 2013 IPPS/
LTCH PPS final rule (77 FR 53653
through 53654), 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) for discussion of our previously
finalized public display and review
requirements. We did not propose any
changes to these requirements.
F. Form, Manner, and Timing of Quality
Data Submission for the FY 2021
Payment Determination and Subsequent
Years
1. Procedural Requirements for the FY
2021 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), and the FY 2018 IPPS/LTCH
PPS final rule (82 FR 38471 through
38472) for our previously finalized
procedural requirements. In the FY 2020
IPF PPS proposed rule, we did not
propose any changes to these policies.
2. Data Submission Requirements for
the FY 2021 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), and the FY 2018 IPPS/LTCH
PPS final rule (82 FR 38472 through
38473) for our previously finalized data
submission requirements.
Because the Medication Continuation
following Discharge from an IPF (NQF
#3205) measure is calculated by CMS
using Medicare Fee-for-Service claims,
there will be no additional data
submission requirements for the FY
2021 payment determination and
subsequent years. Therefore, in the FY
2020 IPF PPS proposed rule, we did not
propose any changes to our previously
finalized data submission policies.
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3. Reporting Requirements for the FY
2021 Payment Determination and
Subsequent Years
We refer readers to the FY 2013 IPPS/
LTCH PPS final rule (77 FR 53656
through 53657), the FY 2014 IPPS/LTCH
PPS final rule (78 FR 50900 through
50901), and the FY 2015 IPF PPS final
rule (79 FR 45976 through 45977) for
our previously finalized reporting
requirements. In the FY 2020 IPF PPS
proposed rule, we did not propose any
changes to these policies.
4. 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) discussions for our
previously finalized sampling policies.
In the FY 2020 IPF PPS proposed rule,
we did not propose any changes to these
policies.
5. 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. In
the FY 2020 IPF PPS proposed rule, we
did not propose any changes to these
policies.
VI. Collection of Information
Requirements
The FY 2020 IPF PPS proposed rule
did not propose any new or revised
‘‘collection of information’’
requirements as defined under 5 CFR
1320.3 the Paperwork Reduction Act’s
(PRA) implementing regulations. Nor
did it contain any proposals that would
have imposed any new or revised
burden within the context of the PRA of
1995 (44 U.S.C. 3501 et seq.). However,
we did make a number of burden
adjustments based on updated Bureau of
Labor Statistics (BLS) wage figures and
more recent facility counts and
estimated case data. These adjustments
reduce our overall time estimate by
50,067 hours and increase our cost
estimate by $1,820,149.
A. Collection of Information
Requirements for the IPFQR Program
H. Extraordinary Circumstances
Exceptions (ECE) Policy
We refer readers to the FY 2013 IPPS/
LTCH PPS final rule (77 FR 53659
With regard to the IPFQR Program, we
are finalizing one new measure
(Medication Continuation Following
Inpatient Psychiatric Discharge (NQF
#3205)) that impacts the FY 2021
payment determination and subsequent
years. The finalized measure is
calculated by CMS using IPF submitted
claims data. The claims’ requirements
and burden are approved by OMB under
control number 0938–0050 (CMS–2552–
10) for our Medicare cost report. The
final measure does not impact any of the
cost report’s data fields or burden
estimates as all worksheets and lines
remain unchanged. Similarly, this final
rule does not impose any new or revised
collection of information requirements
or burden under OMB control number
0938–1171 (CMS–10432) which
contains information about our nonclaims based IPFQR Program quality
measure and non-quality measure
information collection/reporting
requirements and burden.
We refer readers to 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
58 We note that for operational reasons we
sometimes publish IPFQR program requirements in
the IPPS/LTCH PPS proposed and final rule as
opposed to the IPF PPS proposed and final rule.
6. Data 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. In the FY 2020 IPF PPS
proposed rule, we did not propose any
changes to these policies.
G. Reconsideration and Appeals
Procedures
We refer readers to the FY 2013 IPPS/
LTCH PPS final rule (77 FR 53658
through 53659) and the FY 2014 IPPS/
LTCH PPS final rule (78 FR 50903) for
our previously finalized reconsideration
and appeals procedures. In the FY 2020
IPF PPS proposed rule, we did not
propose any changes to these policies.
jbell on DSK3GLQ082PROD with RULES2
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 ECE policies. In
the FY 2020 IPF PPS proposed rule, we
did not propose any changes to these
policies.
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through 46721), the FY 2017 IPPS/LTCH
PPS 58 final rule (81 FR 57265 through
57266), the FY 2018 IPPS/LTCH PPS
final rule (82 FR 38507 through 38508),
and the FY 2019 IPF PPS final rule (83
FR 38609 through 38612) for a detailed
discussion of the burden for the
program requirements that we have
previously adopted. Information
pertaining to the requirements and
burden that are currently approved by
OMB can be found at reginfo.gov under
control numbers 0938–0050 and 0938–
1171.
B. Adjustments to IPFQR Program
Burden Estimates
In the FY 2019 IPF PPS final rule (83
FR 38609), 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 $18.29 per hour
(as of May 2016). Since then, BLS (the
Bureau of Labor Statistics) has revised
their wage data with May 2017 serving
as their most recent update.59 In
response, we proposed to update our
cost estimates using the May 2017 figure
of $18.83 per hour, an increase of $0.54
per hour or $1.08 per hour when
adjusted by 100 percent to account for
fringe benefits and overhead. This is
necessarily a rough adjustment, both
because fringe benefits and overhead
costs vary significantly from employerto-employer and because methods of
estimating these costs vary widely from
study-to-study. Nonetheless, we believe
that doubling the hourly wage rate
($18.83 × 2 = $37.66) to estimate total
cost is a reasonably accurate estimation
method.
We also proposed to update our
facility count and case estimates to the
most recent data available. Specifically,
we estimate that there are now
approximately 1,679 (down from the
previous estimate of 1,734) facilities and
that for measures which require
reporting on the entire patient
population, these facilities will report
on an average of 1,283 cases per facility
(up from the previous estimate of 1,213).
Accordingly, we proposed to adjust our
currently approved cost estimate from
$125,511,558 (see tables 19, 20, and 21)
to $127,331,707 (see tables 22, 23, and
24).
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59 https://www.bls.gov/ooh/healthcare/medicalrecords-and-health-information-technicians.htm.
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38469
0640
0641
0560
1663
1664
jbell on DSK3GLQ082PROD with RULES2
0576
VerDate Sep<11>2014
Hours of
Physical
1,213
Restraint Use
Hours of
HBIPS-3
1,213
Seclusion Use
Patients
Discharged on
Multiple
Antipsychotic
HBIPS-5
609
Medications
with
Appropriate
Justification
Alcohol Use
SUB-2
Brief
and SUB- Intervention
609
2a
Provided or
Offered
Alcohol and
Other Drug
Use Disorder
Treatment
Provided or
SUB-3
Offered at
and SUB609
Discharge and
3a
Alcohol and
Other Drug
Use Disorder
Treatment at
HBIPS-2
FUH
20:00 Aug 05, 2019
Follow-up
After
Hospitalization for
Mental
Illness*
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0
Frm 00047
0.25
303.25
1,734
525,835.5
19,235,063
0.25
303.25
1,734
525,835.5
19,235,063
0.25
152.25
1,734
264,001.5
9,657,175
0.25
152.25
1,734
264,001.5
9,657,175
0.25
152.25
1,734
264,001.5
9,657,175
0
0
0
0
0
Fmt 4701
Sfmt 4725
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Table 19: Currently Approved Burden: Measure Data Collection and Reporting
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1654
TOB-2
TOB-2a
1656
TOB-3
and
TOB-3a
1659
IMM-2
647
n/a
VerDate Sep<11>2014
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Tobacco Use
Treatment
Provided or
Offered and
Tobacco Use
Treatment
Tobacco Use
Treatment
Provided or
Offered at
Discharge and
Tobacco Use
Treatment at
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
Jkt 247001
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609
0.25
152.25
1,734
264,001.5
9,657.175
609
0.25
152.25
1,734
264,001.5
9,657,175
609
0.25
152.25
1,734
264,001.5
9,657,175
609
0.25
152.25
1,734
264,001.5
9,657,175
Frm 00048
Fmt 4701
Sfmt 4725
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648
n/a
n/a
n/a
2860
n/a
Timely
Transmission
of Transition
Record
(Discharges
from an
Inpatient
Facility to
Home/Self
Care or Any
Other Site of
Screening for
Metabolic
Disorders
Thirty-day
all-cause
unplanned
readmission
following
Psychiatric
hospitalizatio
n in an
Inpatient
Psychiatric
38471
609
0.25
152.25
1,734
264,001.5
9,657,175
609
0.25
152.25
1,734
264,001.5
9,657,175
0
0
0
0
0
0
*
* CMS will collect this data using Medicare Part A and Part B claims; therefore these measures will not
require facilities to submit data on any cases.
**This number was erroneously written as 7.907 in the proposed rule, it has been corrected to 7,907 here.
Table 20: Currently Approved Burden: Non-Measure Data Collection and
Reporting
2.0
3,468
36.58
73.16
126,859
ER06AU19.019</GPH>
1,734
VerDate Sep<11>2014
20:00 Aug 05, 2019
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Non-measure
Data Collection
and Submission
38472
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Table 21: Currently Approved Burden: Total
Respondents
Responses
Time
Cost($)
Measure Data
Collection and
Reporting
1,734
13,710,738
(7,907
responses per
facility*
1,734
3,427,685
125,384,699
Non-Measure Data
Collection and
1,734
3,468
126,859
Notice of
Participation, Data
Accuracy
Acknowledgement,
and Vendor
Authorization
Form*
n/a
n/a
n/a
Requirement
n/a
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*The 15 minutes per measure estimate for chart abstraction under Measure Data
Collection and Reporting also includes the time for completing and submitting any forms.
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38473
0640
0641
0560
1663
1664
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0576
VerDate Sep<11>2014
Hours of
Physical
1,283
Restraint Use
Hours of
HBIPS-3
1,283
Seclusion Use
Patients
Discharged on
Multiple
Antipsychotic
HBIPS-5
609
Medications
with
Appropriate
Justification
Alcohol Use
SUB-2
Brief
and SUB- Intervention
609
2a
Provided or
Offered
Alcohol and
Other Drug
Use Disorder
Treatment
Provided or
SUB-3
Offered at
and SUB609
Discharge and
3a
Alcohol and
Other Drug
Use Disorder
Treatment at
HBIPS-2
FUH
Follow-up
After
Hospitalizatio
n for Mental
Illness*
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0
Frm 00051
0.25
320.75
1,679
538,539.25
20,281,388
0.25
320.75
1,679
538,539.25
20,281,388
0.25
152.25
1,679
255,627.75
9,626,941
0.25
152.25
1,679
255,627.75
9,626,941
0.25
152.25
1,679
255,627.75
9,626,941
0
0
0
0
0
Fmt 4701
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Table 22: Burden Adjustments: Measure Data Collection and Reporting
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1654
TOB-2
TOB-2a
1656
TOB-3
and
TOB-3a
1659
IMM-2
647
n/a
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Tobacco Use
Treatment
Provided or
Offered and
Tobacco Use
Treatment
Tobacco Use
Treatment
Provided or
Offered at
Discharge and
Tobacco Use
Treatment at
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
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609
0.25
152.25
1,679
255,627.75
9,626,941
609
0.25
152.25
1,679
255,627.75
9,626,941
609
0.25
152.25
1,679**
255,627.75
9,626,941
609
0.25
152.25
1,679
255,627.75
9,626,941
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648
n/a
n/a
n/a
2860
n/a
Timely
Transmission
of Transition
Record
(Discharges
from an
Inpatient
Facility to
Home/Self
Care or Any
Other Site of
Screening for
Metabolic
Disorders
Thirty-day
all-cause
unplanned
readmission
following
Psychiatric
hospitalizatio
ninan
Inpatient
Psychiatric
38475
609
0.25
152.25
1,679
255,627.75
9,626,941
609
0.25
152.25
1,679
255,627.75
9,626,941
0
0
0
0
0
0
*
* CMS will collect this data using Medicare Part A and Part B claims; therefore these measures will not
require facilities to submit data on any cases.
**The number of facilities submitting data for IMM-2 was erroneously written as 1,734 in the proposed
rule and has been corrected to 1,679 here; the total number of responses was erroneously written as 7,907
in the proposed rule and has been corrected to 8,047 here ..
Table 23: Burden Adjustments: Non-Measure Data Collection and Reporting
2.0
3,358
37.66
75.32
126,462
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1,679
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Non-measure
Data Collection
and Submission
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BILLING CODE 4120–01–C
As mentioned at the beginning of this
section, the adjustments are in response
to updates to BLS wage figures and
more recent facility counts and
estimated case data. They are not a
result of any of the provisions proposed
in the FY 2020 IPF PPS proposed rule.
The adjusted burden figures will be
submitted to OMB for approval under
control number 0938–1171 (CMS–
10432) as a non-substantive change.
We did not receive any public
comments on our proposed burden
estimates.
C. Submission of PRA-Related
Comments
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We invited public comments on our
proposed burden adjustments as well as
on any of the information collection
requirements/burden set out under
OMB control number 0938–1171.
We did not receive any public
comments on our proposed burden
estimates.
VII. Regulatory Impact Statement
A. Statement of Need
This rule finalizes updates to the
prospective payment rates for Medicare
inpatient hospital services provided by
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IPFs for discharges occurring during FY
2020 (October 1, 2019 through
September 30, 2020). We are finalizing
our proposal to apply the 2016-based
IPF market basket increase of 2.9
percent, less the productivity
adjustment of 0.4 percentage point as
required by 1886(s)(2)(A)(i) of the Act,
and further reduced by 0.75 percentage
point as required by sections
1886(s)(2)(A)(ii) and 1886(s)(3)(E) of the
Act, for a final total FY 2020 payment
rate update of 1.75 percent. In this final
rule, we revised and rebased the IPF
market basket to reflect a 2016 base
year. We also aligned the IPF wage
index data with the concurrent IPPS
wage index data by removing the 1-year
lag of the pre-floor, pre-reclassified IPPS
hospital wage index upon which the IPF
wage index is based. We also updated
the IPF labor-related share and the IPF
wage index including adoption of a new
OMB designation. Finally, we updated
the IPFQR Program for the FY 2021
payment determination and subsequent
years.
B. Overall Impact
We have examined the impacts of this
final rule as required by Executive
Order 12866 on Regulatory Planning
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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), the Congressional
Review Act (5 U.S.C. 804(2)) and
Executive Order 13771 on Reducing
Regulation and Controlling Regulatory
Costs (January 30, 2017).
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,
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jobs, the environment, public health or
safety, or state, local or tribal
governments or communities (also
referred to as ‘‘economically
significant’’); (2) creating a serious
inconsistency or otherwise interfering
with an action taken or planned by
another agency; (3) materially altering
the budgetary impacts of entitlement
grants, user fees, or loan programs or the
rights and obligations of recipients
thereof; or (4) raising novel legal or
policy issues arising out of legal
mandates, the President’s priorities, or
the principles set forth in the Executive
Order.
A regulatory impact analysis (RIA)
must be prepared for major rules with
economically significant effects ($100
million or more in any 1 year). This
final rule is not economically significant
under Executive Order 12866, within
the meaning of section 3(f)(1) of the
Executive Order. However, OMB has
determined that the actions are
significant within the meaning of
section 3(f)(4) of the Executive Order.
Therefore, OMB has reviewed this final
rule, and the Departments have
provided the following assessment of
their impact.
We estimate that the total impact of
these changes for FY 2020 payments
compared to FY 2019 payments will be
a net increase of approximately $65
million. This reflects an $75 million
increase from the update to the payment
rates (+$125 million from the second
quarter 2019 IGI forecast of the 2016based IPF market basket of 2.9 percent,
¥$15 million for the productivity
adjustment of 0.4 percentage point, and
¥$35 million for the ‘‘other
adjustment’’ of 0.75 percentage point),
as well as a $10 million decrease as a
result of the update to the outlier
threshold amount. Outlier payments are
estimated to change from 2.23 percent
in FY 2019 to 2.00 percent of total
estimated IPF payments in FY 2020.
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C. Anticipated Effects
In this section, we discuss the
historical background of the IPF PPS
and the impact of this final 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. The budget
neutrality factor includes the following
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components: Outlier adjustment, stoploss 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
final rule, we are updating 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 final rule will be due to
the market basket update for FY 2020 of
2.9 percent (see section III.A.4 of this
final rule) less the productivity
adjustment of 0.4 percentage point
required by section 1886(s)(2)(A)(i) of
the Act; further reduced by the ‘‘other
adjustment’’ of 0.75 percentage point
under sections 1886(s)(2)(A)(ii) and
1886(s)(3)(E) of the Act; and the update
to the outlier fixed dollar loss threshold
amount.
We estimate that the FY 2020 impact
will be a net increase of $65 million in
payments to IPF providers. This reflects
an estimated $75 million increase from
the update to the payment rates and a
$10 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 2020. This estimate does not include
the implementation of the required 2.0
percentage point reduction of the
market basket increase factor for any IPF
that fails to meet the IPF quality
reporting requirements (as discussed in
section V.A. of this final rule).
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 $7.5
million to $38.5 million or less in any
1 year, depending on industry
classification (for details, refer to the
SBA Small Business Size Standards
found at https://www.sba.gov/sites/
default/files/files/Size_Standards_
Table.pdf). 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.
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38477
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 25, we estimate that the overall
revenue impact of this final rule on all
IPFs is to increase estimated Medicare
payments by approximately 1.5 percent.
As a result, since the estimated impact
of this final rule is a net increase in
revenue across almost all categories of
IPFs, the Secretary has determined that
this final 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 604 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 VII.C.1 of this final rule, the
rates and policies set forth in this final
rule will not have an adverse impact on
the rural hospitals based on the data of
the 255 rural excluded psychiatric units
and 66 rural psychiatric hospitals in our
database of 1,581 IPFs for which data
were available. Therefore, the Secretary
has determined that this final rule will
not have a significant impact on the
operations of a substantial number of
small rural hospitals.
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 2019, that
threshold is approximately $154
million. This final rule does not impose
spending costs on state, local, or tribal
governments in the aggregate, or by the
private sector of $154 million or more.
Executive Order 13132 establishes
certain requirements that an agency
must meet when it promulgates a final
rule that imposes substantial direct
requirement costs on state and local
governments, preempts state law, or
otherwise has Federalism implications.
This final rule will not have a
substantial effect on state and local
governments.
2. Impact on Providers
To show the impact on providers of
the changes to the IPF PPS discussed in
this final rule, we compare estimated
payments under the IPF PPS rates and
factors for FY 2020 versus those under
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FY 2019. We determined the percent
change in the estimated FY 2020 IPF
PPS payments compared to the
estimated FY 2019 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 update
to the outlier fixed dollar loss threshold
amount; the updated wage index data
including the updated labor-related
share; and the market basket update for
FY 2020, as adjusted by the productivity
adjustment according to section
1886(s)(2)(A)(i) of the Act, and the
‘‘other adjustment’’ according to
sections 1886(s)(2)(A)(ii) and
1886(s)(3)(E) of the Act.
To illustrate the impacts of the FY
2020 changes in this final rule, our
analysis begins with a FY 2019 baseline
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simulation model based on FY 2018 IPF
payments inflated to the midpoint of FY
2019 using IHS Global Inc.’s second
quarter 2019 forecast of the market
basket update (see section III.A.4 of this
final rule); the estimated outlier
payments in FY 2019; the FY 2019 IPF
wage index; the FY 2019 labor-related
share; and the FY 2019 percentage
amount of the rural adjustment. During
the simulation, total outlier payments
are maintained at 2 percent of total
estimated IPF PPS payments.
Each of the following changes is
added incrementally to this baseline
model in order for us to isolate the
effects of each change:
• The update to the outlier fixed
dollar loss threshold amount.
• The FY 2020 IPF wage index and
the FY 2020 labor-related share.
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• The market basket update for FY
2020 of 2.9 percent less the productivity
adjustment of 0.4 percentage point in
accordance with section 1886(s)(2)(A)(i)
of the Act and further reduced by the
‘‘other adjustment’’ of 0.75 percentage
point in accordance with sections
1886(s)(2)(A)(ii) and 1886(s)(3)(E) of the
Act, for a payment rate update of 1.75
percent.
Our final column comparison in Table
25 illustrates the percent change in
payments from FY 2019 (that is, October
1, 2018, to September 30, 2019) to FY
2020 (that is, October 1, 2019, to
September 30, 2020) including all the
payment policy changes in this final
rule.
BILLING CODE 4120–01–P
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38479
Number
of
Facilities
(2)
1,581
Outlier
(3)
-0.23
CBSA
Wage
Index
&
Labor
Share
(4)
0.00
Total Urban
Urban unit
Urban hospital
1,260
783
477
-0.24
-0.37
-0.08
0.03
-0.06
0.13
1.54
1.32
1.81
Total Rural
Rural unit
Rural hospital
321
255
66
-0.19
-0.25
-0.06
-0.20
-0.24
-0.10
1.34
1.23
1.61
121
100
256
-0.40
-0.09
-0.02
-0.19
0.08
0.21
1.21
1.75
1.94
32
15
19
-0.13
-0.10
0.00
-0.30
-0.47
0.10
1.36
1.20
1.84
115
509
159
-0.67
-0.36
-0.16
0.19
-0.09
-0.15
1.26
1.29
1.43
68
136
-0.22
-0.32
-0.08
-0.13
1.42
1.26
Facility by Type
(1)
All Facilities
By Type of Ownership:
Freestanding IPFs
Urban Psychiatric Hospitals
Government
Non-Profit
For-Profit
Rural Psychiatric Hospitals
Government
Non-Profit
For-Profit
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IPF Units
Urban
Government
Non-Profit
For-Profit
Rural
Government
Non-Profit
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Total
Percent
Change 1
(5)
1.51
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Table 25. FY 2020 IPF PPS Final Payment Impacts
[Percent Change in Columns 3 through 5]
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BILLING CODE 4120–01–C
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3. Impact Results
Table 25 displays the results of our
analysis. The table groups IPFs into the
categories listed here based on
characteristics provided in the Provider
of Services (POS) file, the IPF provider
specific file, and cost report data from
the Healthcare Cost Report Information
System:
• Facility Type.
• Location.
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• Teaching Status Adjustment.
• Census Region.
• Size.
The top row of the table shows the
overall impact on the 1,581 IPFs
included in this analysis. 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 2.23 percent in FY 2019.
Thus, we are adjusting the outlier
threshold amount in this final rule to set
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total estimated outlier payments equal
to 2.0 percent of total payments in FY
2020. The estimated change in total IPF
payments for FY 2020, therefore,
includes an approximate 0.23 percent
decrease in payments because the
outlier portion of total payments is
expected to decrease from
approximately 2.23 percent to 2.0
percent.
The overall impact of this outlier
adjustment update (as shown in column
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3 of Table 25), across all hospital
groups, is to decrease total estimated
payments to IPFs by 0.23 percent. The
largest decrease in payments is
estimated to be ¥0.78 percent for
teaching IPFs with more than 30 percent
interns and residents to beds.
In column 4, we present the effects of
the budget-neutral update to the IPF
wage index and the Labor-Related Share
(LRS). This represents the effect of using
the concurrent hospital wage data and
taking into account the updated OMB
delineations. That is, the impact
represented in this column reflects the
update from the FY 2019 IPF wage
index to the final FY 2020 IPF wage
index, which includes basing the FY
2020 IPF wage index on the FY 2020
pre-floor, pre-reclassified IPPS hospital
wage index data, updating the OMB
designations for two counties in Idaho,
and updating the LRS from 74.8 percent
in FY 2019 to 76.9 percent in FY 2020.
We note that there is no projected
change in aggregate payments to IPFs, as
indicated in the first row of column 4,
however, there will be distributional
effects among different categories of
IPFs. For example, we estimate the
largest increase in payments to be 2.08
percent for Pacific IPFs, and the largest
decrease in payments to be 0.83 percent
for New England IPFs.
Finally, column 5 compares our
estimates of the total final changes
reflected in this final rule for FY 2020
to the estimates for FY 2019 (without
these changes). The average estimated
increase for all IPFs is approximately
1.5 percent. This estimated net increase
includes the effects of the 2016-based
market basket update of 2.9 percent
reduced by the productivity adjustment
of 0.4 percentage point, as required by
section 1886(s)(2)(A)(i) of the Act and
further reduced by the ‘‘other
adjustment’’ of 0.75 percentage point, as
required by sections 1886(s)(2)(A)(ii)
and 1886(s)(3)(E) of the Act. It also
includes the overall estimated 0.23
percent decrease in estimated IPF
outlier payments as a percent of total
payments from the final update to the
outlier fixed dollar loss threshold
amount. Column 5 also includes the
distributional effects of the updates to
the IPF wage index and the labor-related
share.
IPF payments are estimated to
increase by 1.54 percent in urban areas
and 1.34 percent in rural areas. Overall,
IPFs are estimated to experience a net
increase in payments as a result of the
updates in this final rule. The largest
payment increase is estimated at 3.49
percent for IPFs in the Pacific region.
Comment: One commenter wrote that
the proposed 1.7 percent estimated total
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IPF update was not sufficient to cover
the costs of medical inflation and the
growing demand for IPF services. This
commenter was concerned that the
update could negatively impact the
financial viability of IPFs and jeopardize
access.
Response: Total IPF payments were
estimated to increase by 1.7 percent in
the FY 2020 IPF PPS proposed rule.
This 1.7 percent increase is a
combination of the effects of the
proposed market basket update for FY
2020 and the proposed update to the
outlier threshold.
The final FY 2020 estimated increase
in payments is based on a more recent
estimate of the final 2016-based IPF
market basket percentage increase of 2.9
percent, a more recent estimate of the
MFP adjustment of 0.4 percentage point,
less the 0.75 percentage point reduction
(in accordance with sections
1886(s)(2)(A)(ii) and 1886(s)(3)(E) of the
Act) and impact of the outlier threshold,
for a total payment update of 1.75
percent.
The 2.9 percentage increase of the IPF
market basket represents the FY 2020
projected increase in prices of the
relative inputs used to furnish IPF
services to Medicare beneficiaries. The
forecasted prices of the individual
inputs are based on IGI’s most recent
2nd quarter 2019 forecast of the price
proxies in the market basket. IGI is a
nationally recognized economic and
financial forecasting firm that has
received multiple awards for their
macroeconomic forecast accuracy of
major economic indicators. CMS uses
IGI’s price forecasts in all of the FFS
market baskets used for payment
updates and has used the forecasts
produced by this company for many
years. In this FY 2020 final rule, we are
also updating the cost weights for the
IPF market basket, from 2012 to 2016,
which captures changes in relative costs
due to quantity and intensity. We
therefore believe that the IPF market
basket represents an appropriate
measure of input price inflation that is
expected to be realized by IPFs in FY
2020.
As stated, the Act mandates that the
market basket update (which accounts
for input price inflation) be adjusted for
multifactor productivity and a 0.75
percentage point legislatively required
adjustment. CMS does not have the
authority to alter these payment
adjustments, but we note that under the
current law at 1886(s)(3)(E), FY 2020 is
the last year that the 0.75 percentage
point ‘‘other’’ adjustment will be made.
Estimated IPF payments are also
reduced by 0.23 percent as a result of
the update to the outlier threshold.
PO 00000
Frm 00059
Fmt 4701
Sfmt 4700
38481
Based on an updated analysis of the
most recent IPF claims data for this final
rule we now estimate that IPF outlier
payments as a percentage of total
estimated payments will be
approximately 2.23 percent in FY 2019.
Since this percentage exceeds our
established 2 percent IPF outlier policy
we are adjusting the outlier threshold
amount to set total estimated outlier
payments equal to 2 percent of total
estimated payments in FY 2020. The
estimated change in total IPF payments
for FY 2020 includes an approximate
0.23 percent decrease in payments
because the estimated outlier portion of
total payments is estimated to decrease
from 2.23 percent to 2 percent.
4. Effect on Beneficiaries
Under the IPF PPS, IPFs will receive
payment based on the average resources
consumed by patients for each day. We
do not expect changes in the quality of
care or access to services for Medicare
beneficiaries under the FY 2020 IPF
PPS, but we continue to expect that
paying prospectively for IPF services
will enhance the efficiency of the
Medicare program.
5. Effects of Updates to the Inpatient
Psychiatric Facilities Quality Reporting
(IPFQR) Program
As discussed in section V. of this final
rule and in accordance with section
1886(s)(4)(A)(i) of the Act, we will
implement a 2 percentage point
reduction in the market basket update
when calculating the FY 2021 national
per diem rate for discharges from IPFs
that have failed to comply with the
IPFQR Program requirements for the FY
2021 payment determination. In section
III.B. of this final rule, we discuss how
the 2 percentage point reduction will be
applied. For the FY 2019 payment
determination (that is, data submitted in
CY 2018), of the 1,679 IPFs eligible for
the IPFQR Program, 50 did not receive
the full market basket update due to
reasons specific to the IPFQR Program;
24 of these IPFs chose not to participate
and 26 did not meet the requirements of
the Program. Thus, we estimate similar
numbers for the FY 2021 payment
determination and that the IPFQR
Program will have a negligible impact
on overall IPF payments in FY 2021.
We are finalizing provisions that
impact the FY 2021 payment
determination and subsequent years. We
refer readers to section VI. of this final
rule for details discussing information
collection requirements for the IPFQR
Program. We will closely monitor the
effects of this quality reporting program
on IPFs and help facilitate successful
reporting outcomes through ongoing
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Federal Register / Vol. 84, No. 151 / Tuesday, August 6, 2019 / Rules and Regulations
jbell on DSK3GLQ082PROD with RULES2
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
final rule, we should estimate the cost
associated with regulatory review. Due
to the uncertainty involved with
accurately quantifying the number of
entities that will review this final rule,
we assume that the total number of
unique commenters on the most recent
IPF proposed rule from FY 2020 (84 FR
16948) will be the number of reviewers
of this final rule. We acknowledge that
this assumption may understate or
overstate the costs of reviewing this
final rule. It is possible that not all
commenters reviewed the FY 2020 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 of
this final rule. We solicited comments
on this assumption.
We also recognize that different types
of entities are in many cases affected by
mutually exclusive sections of this final
rule; therefore, for the purposes of our
estimate, we assume that each reviewer
reads approximately 50 percent of this
final rule.
Using the May, 2018 mean (average)
wage information from the BLS for
medical and health service managers
(Code 11–9111), we estimate that the
cost of reviewing this final rule is
$109.36 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 1.4 hours for the
staff to review half of this final rule. For
each IPF that reviews the final rule, the
estimated cost is (1.4 hours × $109.36)
or $153.10. Therefore, we estimate that
the total cost of reviewing this final rule
is $3,674.40 ($153.10 × 24 reviewers).
We received one comment on our
assumption about the number of
reviewers of the IPF PPS proposed rule.
Comment: One commenter wrote that
CMS should consider the number of
downloads of the IPF proposed rule in
calculating regulatory review costs,
since many reviewers may read the rule
but not submit a comment. The
commenter also noted that some
organizations may download the rule
VerDate Sep<11>2014
20:00 Aug 05, 2019
Jkt 247001
once and distribute copies to others to
read. This commenter suggested that
CMS consider the greater of the number
of downloads or of the number of
unique commenters as a fair estimate of
the number of reviewers. This
commenter believes that this method
would be a fairer assumption of the
number of reviewers.
Response: We appreciate the
commenter’s input on our methodology.
We have acknowledged that our method
provides an estimate that could
overstate or understate the costs of
reviewing the rule. We do not believe
this suggested methodology would
improve the accuracy of the estimate.
We do not currently have the ability to
track the number of times the IPF rule
is downloaded, and if we did, to know
how many of those downloads are by
those who are providers or similar
stakeholders. We also prefer to use a
methodology for estimating the number
of reviewers that is consistent with the
methodology that other Medicare
payment systems use. As such, we will
continue to use the number of
commenters on the most recent
proposed rule as the basis for our review
cost estimate.
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.
Therefore, we are updating the IPF PPS
using the methodology published in the
November 2004 IPF PPS final rule;
applying the 2016-based IPF PPS market
basket update for FY 2020 of 2.9
percent, reduced by the statutorily
required multifactor productivity
adjustment of 0.4 percentage point and
the ‘‘other adjustment’’ of 0.75
percentage point, along with the wage
index budget neutrality adjustment to
update the payment rates; finalizing a
FY 2020 IPF wage index which is fully
based upon the OMB CBSA
designations from Bulletin 17–01 and
which uses the FY 2020 pre-floor, prereclassified IPPS hospital wage index as
its basis; and finalizing changes to the
IPFQR Program.
E. Accounting Statement
As required by OMB Circular A–4
(available at www.whitehouse.gov/sites/
whitehouse.gov/files/omb/circulars/A4/
a-4.pdf), in Table 26, we have prepared
an accounting statement showing the
classification of the expenditures
PO 00000
Frm 00060
Fmt 4701
Sfmt 9990
associated with the updates to the IPF
wage index and payment rates in this
final rule. Table 26 provides our best
estimate of the increase in Medicare
payments under the IPF PPS as a result
of the changes presented in this final
rule and based on the data for 1,581
IPFs in our database.
TABLE 26—ACCOUNTING STATEMENT:
CLASSIFICATION OF ESTIMATED EXPENDITURES
[Change in estimated impacts from FY 2019
IPF PPS to FY 2020 IPF PPS]
Category
Annualized Monetized
Transfers.
From Whom to Whom? ..
Transfers
$65 million.
Federal Government to
IPF Medicare Providers.
F. Congressional Review Act
Pursuant to the Congressional Review
Act (5 U.S.C. 801 et seq.) the Office of
Information and Regulatory Affairs
designated this rule as not a major rule,
as defined by 5 U.S.C. 804(2).
G. Regulatory Reform Analysis Under
Executive Order 13771
Executive Order 13771, titled
Reducing Regulation and Controlling
Regulatory Costs, was issued on January
30, 2017 and requires that the costs
associated with significant new
regulations ‘‘shall, to the extent
permitted by law, be offset by the
elimination of existing costs associated
with at least two prior regulations.’’
This final rule is not expected to be
subject to the requirements of Executive
Order 13771 because it is estimated to
result in no more than de minimis costs
as described previously and thus is not
a regulatory action for the purposes of
E.O. 13771.
H. Conclusion
In accordance with the provisions of
Executive Order 12866, this regulation
was reviewed by the Office of
Management and Budget.
Dated: July 26, 2019 .
Seema Verma,
Administrator, Centers for Medicare &
Medicaid Services.
Dated: July 26, 2019.
Alex M. Azar II,
Secretary, Department of Health and Human
Services.
[FR Doc. 2019–16370 Filed 7–30–19; 4:15 pm]
BILLING CODE 4120–01–P
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]]>Agencies
[Federal Register Volume 84, Number 151 (Tuesday, August 6, 2019)]
[Rules and Regulations]
[Pages 38424-38482]
From the Federal Register Online via the Government Publishing Office [www.gpo.gov]
[FR Doc No: 2019-16370]
[[Page 38423]]
Vol. 84
Tuesday,
No. 151
August 6, 2019
Part III
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 2020 Inpatient Psychiatric Facilities Prospective
Payment System and Quality Reporting Updates for Fiscal Year Beginning
October 1, 2019 (FY 2020); Rules
Federal Register / Vol. 84 , No. 151 / Tuesday, August 6, 2019 /
Rules and Regulations
[[Page 38424]]
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DEPARTMENT OF HEALTH AND HUMAN SERVICES
Centers for Medicare & Medicaid Services
42 CFR Part 412
[CMS-1712-F]
RIN 0938-AT69
Medicare Program; FY 2020 Inpatient Psychiatric Facilities
Prospective Payment System and Quality Reporting Updates for Fiscal
Year Beginning October 1, 2019 (FY 2020)
AGENCY: Centers for Medicare & Medicaid Services (CMS), HHS.
ACTION: Final rule.
-----------------------------------------------------------------------
SUMMARY: This final rule updates the prospective payment rates, the
outlier threshold, and the wage index for Medicare inpatient hospital
services provided by Inpatient Psychiatric Facilities (IPFs), which
include psychiatric hospitals and excluded psychiatric units of an
inpatient prospective payment system hospital or critical access
hospital. Additionally, this final rule revises and rebases the IPF
market basket to reflect a 2016 base year and removes the IPF
Prospective Payment System (PPS) 1-year lag of the wage index data.
Finally, this final rule implements updates to the Inpatient
Psychiatric Facilities Quality Reporting Program. These changes will be
effective for IPF discharges beginning during the fiscal year (FY) from
October 1, 2019 through September 30, 2020 (FY 2020).
DATES: These regulations are effective on October 1, 2019.
FOR FURTHER INFORMATION CONTACT: The IPF Payment Policy mailbox at
[email protected] for general information.
Mollie Knight, (410) 786-7948 or Hudson Osgood, (410) 786-7897, for
information regarding the market basket rebasing, update, or the labor
related share.
Theresa Bean, (410) 786-2287 or James Hardesty, (410) 786-2629, for
information regarding the regulatory impact analysis.
James Poyer, (410) 786-2261 or Jeffrey Buck, (410) 786-0407, for
information regarding the inpatient psychiatric facility quality
reporting program.
SUPPLEMENTARY INFORMATION:
Availability of Certain Tables Exclusively Through the Internet on the
CMS Website
Addendum A to this final rule summarizes the FY 2020 IPF PPS
payment rates, outlier threshold, cost of living adjustment factors for
Alaska and Hawaii, national and upper limit cost-to-charge ratios, and
adjustment factors. In addition, the B Addenda to this final rule show
the complete listing of ICD-10 Clinical Modification (CM) and Procedure
Coding System codes underlying the Code First table (Addendum B-1), the
FY 2020 IPF PPS comorbidity adjustment (Addenda B-2 and B-3), and
electroconvulsive therapy (ECT) procedure codes (Addendum B-4). 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 2020 Wage Index for Urban Areas Based
on Core-Based Statistical Area (CBSA) Labor Market Areas and the FY
2020 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. In addition, Addendum C to this final rule is a
provider-level file of the effects of the change to the wage index
methodology, and is available at the same CMS website address.
I. Executive Summary
A. Purpose
This final rule updates 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 the Fiscal Year (FY) beginning October 1, 2019 through
September 30, 2020. Additionally, this final rule rebases and revises
the IPF market basket to reflect a 2016 base year and uses the
concurrent hospital wage data as the basis of the IPF wage index rather
than using the prior year's Inpatient Prospective Payment System (IPPS)
hospital wage data. Finally, this final rule updates the Inpatient
Psychiatric Facility Quality Reporting (IPFQR) Program.
B. Summary of the Major Provisions
1. Inpatient Psychiatric Facilities Prospective Payment System (IPF
PPS)
In this final rule we:
Rebase and revise the IPF market basket to reflect a 2016
base year: Since the IPF PPS inception, the market basket used to
update IPF PPS payments has been periodically rebased and revised to
reflect more recent data on IPF cost structures. We last rebased and
revised the market basket applicable to IPFs in the FY 2016 IPF PPS
rule (80 FR 46656 through 46679), when we adopted a 2012-based IPF-
specific market basket.
Adjust the 2016-based IPF market basket update (2.9
percent) by a reduction for economy-wide productivity (0.4 percentage
point) as required by section 1886(s)(2)(A)(i) of the Social Security
Act (the Act). We further reduced the 2016-based IPF market basket
update by 0.75 percentage point as required by section
1886(s)(2)(A)(ii) of the Act, resulting in an IPF payment rate update
of 1.75 percent for FY 2020.
Made technical rate setting changes: The IPF PPS payment
rates are adjusted annually for inflation, as well as statutory and
other policy factors. We updated:
++ The IPF PPS federal per diem base rate from $782.78 to $798.55.
++ The IPF PPS federal per diem base rate for providers who failed
to report quality data to $782.85.
++ The Electroconvulsive therapy (ECT) payment per treatment from
$337.00 to $343.79.
++ The ECT payment per treatment for providers who failed to report
quality data to $337.03.
++ The labor-related share from 74.8 percent to 76.9 percent.
++ The core-based statistical area (CBSA) rural and urban wage
indices for FY 2020, using the FY 2020 pre-floor, pre-reclassified IPPS
hospital wage index data and OMB designations from OMB Bulletin 17-01.
++ The wage index budget-neutrality factor to 1.0026.
++ The fixed dollar loss threshold amount from $12,865 to $14,960
to maintain estimated outlier payments at 2 percent of total estimated
aggregate IPF PPS payments.
Eliminate the 1-year lag in the wage index data: We
aligned the IPF wage index data with the concurrent IPPS wage index
data by removing the 1-year lag of the pre-floor, pre-reclassified IPPS
hospital wage index upon which the IPF wage index is based.
2. Inpatient Psychiatric Facilities Quality Reporting (IPFQR) Program
We updated the IPFQR Program by adding a new measure for the
program.
C. Summary of Impacts
[[Page 38425]]
------------------------------------------------------------------------
Total transfers & cost
Provision description reductions
------------------------------------------------------------------------
FY 2020 IPF PPS payment update......... The overall economic impact of
this final rule is an
estimated $65 million in
increased payments to IPFs
during FY 2020.
Updated quality reporting program $0.
(IPFQR) Program requirements.
------------------------------------------------------------------------
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 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 in an
IPPS hospital that is excluded from the IPPS, or a psychiatric unit in
a Critical Access Hospital (CAH) that is excluded from the CAH payment
system. These excluded psychiatric units would 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 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. As noted in
our FY 2019 IPF PPS final rule with comment period, published in the
Federal Register on August 6, 2018 (83 FR 38576 through 38620), for the
RY beginning in 2018, the productivity adjustment currently in place is
equal to 0.8 percentage point.
Section 1886(s)(2)(A)(ii) of the Act requires the application of an
``other adjustment'' that reduces 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 2019 IPF PPS final rule, for the RY beginning in 2018,
section 1886(s)(3)(E) of the Act requires that the other adjustment
reduction currently in place be equal to 0.75 percentage point.
Sections 1886(s)(4)(A)-(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 take into account such reduction in computing the payment amount
for a subsequent RY. (See section II.C of this final rule for an
explanation of the IPF PPS RY.) More information about the specifics of
the current IPFQR Program is available in the FY 2019 IFP PPS and
Quality Reporting Updates for Fiscal Year Beginning October 1, 2018
final rule (83 FR 38589 through 38608).
To implement and periodically update these provisions, we have
published various proposed and final rules and notices in the Federal
Register. For more information regarding these documents, see the
Center for Medicare & Medicaid (CMS) website at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/InpatientPsychFacilPPS/?redirect=/InpatientPsychFacilPPS/.
B. Overview of the IPF PPS
The November 2004 IPF PPS final rule (69 FR 66922) 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.
The patient-level adjustments include age, Diagnosis-Related Group
(DRG) assignment, and comorbidities; additionally, there are
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 provides additional payment policies for outlier cases,
interrupted stays, and a per treatment payment for patients who undergo
electroconvulsive therapy (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.
[[Page 38426]]
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).
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. Therefore, in the
November 2004 IPF PPS final rule, 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 RY 2012, we proposed and finalized switching the IPF PPS payment
rate update from a RY that begins on July 1 and ends on June 30, to one
that coincides with the federal FY that begins October 1 and ends on
September 30. In order to transition from one timeframe to another, the
RY 2012 IPF PPS covered a 15-month period from July 1, 2011 through
September 30, 2012. Therefore, the IPF RY has been equivalent to the
October 1 through September 30 federal FY since RY 2013. For further
discussion of the 15-month market basket update for RY 2012 and
changing the payment rate update period to coincide with a FY period,
we refer readers to the RY 2012 IPF PPS proposed rule (76 FR 4998) and
the RY 2012 IPF PPS final rule (76 FR 26432).
In November 2004, we implemented the IPF PPS in a final rule that
published on November 15, 2004 in the Federal Register (69 FR 66922).
In developing the IPF PPS, and to ensure that the IPF PPS is able to
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 proposed rule (68 FR 66923;
66928 through 66933) and our November 15, 2004 IPF 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 that 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 1. 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 1. For a detailed list of updates to the IPF PPS, we refer
readers to our regulations at 412.428.
The most recent IPF PPS annual update was published in a final rule
on August 6, 2018 in the Federal Register titled, ``Medicare Program;
FY 2019 Inpatient Psychiatric Facilities Prospective Payment System and
Quality Reporting Updates'' (83 FR 38576), which updated the IPF PPS
payment rates for FY 2019. That final rule updated the IPF PPS federal
per diem base rates that were published in the FY 2018 IPF PPS Rate
Update final rule (82 FR 36771) in accordance with our established
policies.
III. Provisions of the FY 2020 IPF PPS Final Rule and Responses to
Comments
On April 23, 2019 we published the FY 2020 IPF PPS proposed rule
(84 FR 16948). We received 24 comments on the FY 2020 IPF PPS proposed
rule, with some commenters addressing multiple issues. We received 4
comments on payment policy issues, 19 comments on quality issues, and 6
comments that were outside of the scope of the proposed rule.
A. 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 2016 IPF PPS final rule (80 FR
46656 through 46679), where we adopted a 2012-based IPF market basket.
The 2012-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 2020 IPF PPS proposed rule, we
proposed to rebase and revise the IPF market basket to reflect a 2016
base year.
2. Overview of the 2016-Based IPF Market Basket
The proposed 2016-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 (for the proposed IPF market basket, the base period
is 2016) and total base period expenditures are estimated for a set of
mutually exclusive and exhaustive spending categories. Each category is
calculated as a proportion of total costs. These proportions are called
cost or expenditure weights. Second, each expenditure category is
matched to
[[Page 38427]]
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
expenditure weight for each cost category is multiplied by the level of
its respective price proxy. The sum of these products (that is, the
expenditure weights multiplied by their price 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 furnish IPF
services. The effects on total expenditures resulting from changes in
the mix of goods and services purchased after the base period are not
measured. For example, an IPF hiring more nurses after the base period
to accommodate the needs of patients will 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 will 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. Creating an IPF-Specific Market Basket
As discussed in the FY 2016 final rule (80 FR 46656 through 46679),
the 2012-based IPF market basket reflects the Medicare cost reports for
both freestanding and hospital-based facilities. Previous market
baskets, such as the 2008-based rehabilitation, psychiatric, and long-
term care (RPL) market basket, were calculated using Medicare cost
report data for freestanding facilities only. We used only freestanding
facilities due to concerns regarding our ability to incorporate
Medicare cost report data for hospital-based providers. After research
on the available Medicare cost report data, we concluded that Medicare
cost report data for both freestanding IPFs and hospital-based IPFs can
be used to calculate the major market basket cost weights for a stand-
alone IPF market basket. In the FY 2016 IPF PPS final rule (80 FR 46656
through 46679), we finalized a detailed methodology to derive market
basket cost weights using Medicare cost report data for both
freestanding IPFs and hospital-based IPFs.
For the FY 2020 proposed rule, we proposed to rebase and revise the
2012-based IPF market basket to a 2016 base year reflecting both
freestanding IPFs and hospital-based IPFs. In section III.A.3.a.,
``Development of Cost Categories and Weights,'' we provide a detailed
description of our proposed methodology used to develop the 2016-based
IPF market basket.
a. Development of Cost Categories and Weights
i. Medicare Cost Reports
We proposed a 2016-based IPF market basket that consists of seven
major cost categories and a residual derived from the 2016 Medicare
cost reports (CMS Form 2552-10 effective for cost reports beginning on
or after May 1, 2010) for freestanding and hospital-based IPFs. CMS
Form 2552-10 was also used to derive the major cost categories in the
2012-based IPF market basket. The seven cost categories are Wages and
Salaries, Employee Benefits, Contract Labor, Pharmaceuticals,
Professional Liability Insurance (PLI), Home Office Contract Labor, and
Capital. The 2012-based IPF market basket did not have a Home Office
Contract Labor cost category. The residual ``All Other'' category
reflects all remaining costs not captured in the seven cost categories.
The 2016 cost reports include providers whose cost reporting period
beginning date is on or between October 1, 2015 and September 30, 2016.
We proposed to select 2016 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 at the time of rulemaking.
Similar to the Medicare cost report data used to develop the 2012-
based IPF market basket, the Medicare cost report data for 2016 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 of case mix and practice patterns
associated with providing services to Medicare beneficiaries.
Therefore, we proposed to limit our selection of Medicare cost reports
used in the 2016-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 2016-based IPF market
basket, for those IPFs with an average facility LOS of greater than or
equal to 15 days, we proposed 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 proposed
to include IPFs where the Medicare LOS is within 95 percent (higher or
lower) of the facility LOS. We proposed 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
2012-based IPF market basket.
Applying these trims to the approximate 1,600 total cost reports
(freestanding and hospital-based) resulted in roughly 1,500 IPF
Medicare cost reports with an average Medicare LOS of 12 days, average
facility LOS of 9 days, and Medicare utilization (as measured by
Medicare inpatient IPF days as a percentage of total facility days) of
26 percent. Providers excluded from the proposed 2016-based IPF market
basket (about 130 Medicare cost reports) had an average Medicare LOS of
25 days, average facility LOS of 55 days, and a Medicare utilization of
4 percent. Of those excluded, about 70 percent of these were
freestanding providers; on the other hand, freestanding providers
represent about 30 percent of all IPFs. We note that seventy percent of
those excluded from the 2012-based IPF market basket using this LOS
edit were also freestanding providers.
Using the post-LOS set of 2016 Medicare cost reports, we calculated
costs for the seven major cost categories (Wages and Salaries, Employee
Benefits, Contract Labor, Professional Liability Insurance,
Pharmaceuticals, Home Office Contract Labor, and Capital). For
comparison, the 2012-based IPF market basket utilized the Bureau of
Economic Analysis Benchmark Input-Output data to derive the Home Office
Contract Labor cost weight rather than the Medicare cost report data. A
more detailed discussion of this methodological change is provided.
Similar to the 2012-based IPF market basket major cost weights, the
proposed 2016-based IPF market basket cost weights reflect Medicare
allowable costs
[[Page 38428]]
(routine, ancillary, and capital costs) that are eligible for inclusion
under the IPF PPS payments. We proposed to define Medicare allowable
costs for freestanding IPFs as 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 proposed that total Medicare allowable
costs be equal to total costs for the IPF inpatient unit after the
allocation of overhead costs (Worksheet B, part I, column 26, line 40)
and a portion of total ancillary costs (Worksheet B, part I, column 26,
lines 50 through 76 (excluding 52 and 75), 90 through 91, and 93). We
proposed to calculate the portion of ancillary costs attributable to
the hospital-based IPF for a given ancillary cost center by multiplying
total facility ancillary costs for the specific cost center (as
reported on Worksheet B, part I, column 26) by the ratio of IPF
Medicare ancillary costs for the cost center (as reported on Worksheet
D-3, column 3 for IPF subproviders) to total Medicare ancillary costs
for the cost center (equal to the sum of Worksheet D-3, column 3 for
all Inpatient Prospective Payment System (IPPS), Skilled Nursing
Facility (SNF), IRF, and IPF). This is the same methodology used for
the 2012-based IPF market basket.
We provide a description of the proposed methodologies used to
derive costs for the seven major cost categories.
Wages and Salaries Costs
For freestanding IPFs, we proposed that Wages and Salaries costs be
derived as the sum of routine inpatient salaries, ancillary salaries,
and a proportion of overhead (or general service cost centers in the
MCR) salaries as reported on Worksheet A, column 1. Since overhead
salary costs are attributable to the entire IPF, we only include the
proportion attributable to the Medicare allowable cost centers. We
proposed to estimate the proportion of overhead salaries that are
attributed to Medicare allowable costs centers by multiplying the ratio
of Medicare allowable salaries (Worksheet A, column 1, lines 50 through
76 (excluding 52 and 75), 90 through 91, and 93) to total salaries
(Worksheet A, column 1, line 200) times total overhead salaries
(Worksheet A, column 1, lines 4 through 18). This is the same
methodology used in the 2012-based IPF market basket.
We proposed that Wages and Salaries costs for hospital-based IPFs
are derived by summing inpatient routine salary costs, ancillary
salaries, overhead salary costs attributable to the IPF inpatient unit,
and a portion of overhead salary costs attributable to the ancillary
departments.
We proposed to calculate hospital-based inpatient routine salary
costs using Worksheet A, column 1, line 40.
We proposed to calculate hospital-based 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) using salary costs from
Worksheet A, column 1 multiplied by the ratio of IPF Medicare ancillary
costs for the cost center (as reported on Worksheet D-3, column 3 for
IPF subproviders) to total Medicare ancillary costs for the cost center
(equal to the sum of Worksheet D-3, column 3 for IPPS, SNF, IRF, and
IPF).
We proposed to calculate the hospital-based overhead salaries
attributable to the IPF inpatient unit by first calculating total
noncapital overhead costs (Worksheet B, part I, columns 4-18, line 40
less Worksheet B, part II, columns 4-18) for each ancillary department.
We then multiplied total noncapital overhead costs by 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 proposed to calculate the hospital-based portion of overhead
salaries attributable to each ancillary department by first calculating
total noncapital overhead costs attributable to each specific ancillary
department (Worksheet B, part I, columns 4-18 less Worksheet B, part
II, columns 4-18). We then identified the portion of these noncapital
overhead costs attributable to Wages and Salaries by multiplying these
costs by the ratio of total facility overhead salaries (as reported on
Worksheet A, column 1, lines 4-18) to total overhead costs (as reported
on Worksheet A, column 1 & 2, lines 4-18). Finally, we identified the
portion of these overhead salaries for each ancillary department that
is attributable to the hospital-based IPF by multiplying by 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 IPPS, SNF, IRF, and IPF).
This is the same Wages and Salaries Costs methodology used to
derive the 2012-based IPF market basket.
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 2016 Medicare cost report data, the majority of providers did
not report data on Worksheet S-3, part V. One (1) percent of
freestanding IPFs and roughly 40 percent of hospital-based IPFs
reported data on Worksheet S-3, part V. Again, we continue to encourage
all providers to report these data on the Medicare cost report.
For freestanding IPFs, we proposed Employee Benefits costs were
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. For those freestanding IPFs that
reported Worksheet S-3, part II data, but not Worksheet S-3, part V, we
proposed to use the sum of Worksheet S-3, part II lines 17, 18, 20, and
22 to derive Employee Benefits costs. This proposed method allowed us
to obtain data from more than 20 freestanding IPFs (roughly 5 percent
of all freestanding IPFs) than if we were to only use Worksheet S-3,
part V data as done for the 2012-based IPF market basket.
For hospital-based IPFs, we proposed to calculate total benefit
costs as the sum of inpatient unit benefit costs, a portion of
ancillary benefits, and a portion of overhead benefits attributable to
the routine inpatient unit and a portion of overhead benefits
attributable to the ancillary departments.
We proposed hospital-based inpatient unit benefit costs be equal to
Worksheet S-3 part V, column 2, line 3.
We proposed the hospital-based portion of ancillary benefit costs
be equal to hospital-based ancillary salaries times the ratio of total
facility benefits to total facility salaries.
We proposed that the hospital-based portion of overhead benefits
attributable to the routine inpatient unit and ancillary departments be
calculated by multiplying ancillary salaries for the hospital-based IPF
and overhead salaries attributable to the hospital-based IPF
(determined in the derivation of hospital-based IPF Wages and Salaries
costs as described) by the ratio of total facility benefits to total
facility salaries. 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.
Contract Labor Costs
Contract Labor costs are primarily associated with direct patient
care services. Contract Labor costs are exclusive of Home Office
Contract Labor
[[Page 38429]]
costs. 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.iii of this final rule.
To derive contract labor costs using Worksheet S-3, part V data, for
freestanding IPFs, we proposed 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 reported Worksheet S-3, part II data, but
not Worksheet S-3, part V, we proposed to use the sum of Worksheet S-3,
part II lines 11 and 13 to derive Contract Labor costs. For the 2012-
based IPF market basket, we only used data from Worksheet S-3, part V,
column 1, line 2 to derive the Contract Labor costs for freestanding
IPFs.
For hospital-based IPFs, we proposed 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.
Pharmaceuticals Costs
For freestanding IPFs, we proposed 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 proposed 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 proposed that hospital-based non-salary pharmacy costs
attributable to the hospital-based IPF are 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, column 1 and 2 for line 15)
for the total facility.
We proposed that hospital-based non-salary drugs charged to patient
costs attributable to the hospital-based IPF are 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 IPF subproviders, column 3, line
73) to total Medicare drugs charged to patients ancillary costs for the
total facility (equal to the sum of Worksheet D-3, column 3, line 73,
for all IPPS, SNF, IRF, and IPF).
This is the same Pharmaceuticals Costs methodology used to derive
the 2012-based IPF market basket.
Professional Liability Insurance (PLI) Costs
For freestanding IPFs, we proposed that PLI costs (often referred
to as malpractice costs) are equal to premiums, paid losses and self-
insurance costs reported on Worksheet S-2, part I, columns 1 through 3,
line 118.
For hospital-based IPFs, we proposed 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.
Therefore, hospital-based IPF PLI costs were equal to total facility
PLI (as reported on Worksheet S-2, part I, columns 1 through 3, line
118) divided by total facility costs (as reported on Worksheet A,
columns 1 and 2, line 200) times hospital-based IPF Medicare allowable
total costs. Our assumption is that the same proportion of expenses are
used among each unit of the hospital.
This is the same methodology used to derive the 2012-based IPF
market basket.
Home Office/Related Organization Contract Labor Costs
For the 2016-based IPF market basket, we proposed to determine the
home office/related organization contract labor costs using Medicare
cost report data. This is a different methodology compared to the 2012-
based IPF market basket. We believe this proposed methodology is an
improvement as it is based on the data directly submitted by providers
on the Medicare cost report. It is also consistent with the methodology
we adopted when we rebased and revised the 2014-based IPPS market
basket (52 FR 38159).
For hospital-based IPFs, we proposed to calculate the home office
contract labor cost weight using data reported on Worksheet S-3, part
II, column 4, lines 14, 1401, 1402, 2550, and 2551 and total facility
costs (Worksheet B, part 1, column 26, line 202). We proposed to use
total facility costs as the denominator for calculating the home office
contract labor cost weight as these expenses reported on Worksheet S-3,
part II reflect the entire hospital facility. Our assumption is that
the same proportion of expenses are used among each unit of the
hospital. Similar to the other market basket costs weights, we proposed
to trim the Home Office Contract Labor cost weight to remove outliers.
Since not all hospital-based IPFs will have home office contract labor
costs, we proposed to trim the top one percent of the Home Office
Contract Labor cost weight. This is the same trimming methodology used
to calculate the Home Office Contract Labor cost weight in the 2016-
based IPPS market basket. Using this proposed methodology, we calculate
a Home Office Contract Labor cost weight for hospital-based IPFs of 3.7
percent. We discuss the trimming methodology for the other major cost
categories in the ``Final Major Cost Category Computation'' in section
ii. of this final rule.
Freestanding IPFs are not required to complete Worksheet S-3, part
II. Therefore, to estimate the Home Office Contract Labor cost weight,
we proposed the following methodology:
(1) Using hospital-based IPFs with a home office and also passing
the one percent trim as described, we calculate the ratio of the Home
Office Contract Labor cost weight to the Medicare allowable nonsalary,
noncapital cost weight (Medicare allowable nonsalary, noncapital costs
as a percent of total Medicare allowable costs).
(2) We identify freestanding IPFs that report a home office on
Worksheet S-2, part I, line 140--roughly 85 percent. We proposed to
calculate a Home Office Contract Labor cost weight for these
freestanding IPFs by multiplying the ratio calculated in Step (1) by
the Medicare allowable nonsalary, noncapital cost weight for those
freestanding IPFs with a home office.
(3) We then calculated the freestanding IPF cost weight by
multiplying the Home Office Contract Labor cost weight in step (2) by
the total Medicare allowable costs for IPFs with a home office as a
percent of total Medicare allowable costs for all freestanding IPFs.
To calculate the Home Office Contract Labor cost weight, we
proposed to weight together the freestanding Home Office Contract Labor
cost weight (3.0 percent) and the hospital-based Home Office Contract
Labor cost weight (3.7 percent) using total Medicare allowable costs.
The resulting overall cost weight for Home Office was 3.5 percent (3.0
percent x 37 percent + 3.7 percent x 63 percent).
For the 2012-based IPF market basket, we calculated the Home Office
Contract Labor cost weight using the Bureau of Economic Analysis Input-
Output
[[Page 38430]]
expense data for North American Industry Classification System (NAICS)
code 55, Management of Companies and Enterprises using the methodology
described in section III.A.3.a.iii (Derivation of the Detailed
Operating Cost Weights) of this final rule.
Capital Costs
For freestanding IPFs, we proposed capital costs to 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. This is the same methodology used for the 2012-
based IPF market basket.
For hospital-based IPFs, we proposed capital costs to 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
calculated 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 ratio of IPF
Medicare ancillary costs for the cost center (as reported on Worksheet
D-3, column 3 for IPF subproviders) to total Medicare ancillary costs
for the cost center (equal to the sum of Worksheet D-3, column 3 for
all IPPS, SNF, IRF, and IPF). This is the same methodology used for the
2012-based IPF market basket.
ii. Final Major Cost Category Computation
After we derived costs for the seven major cost categories for each
provider using the Medicare cost report data as described, we proposed
to trim the data for outliers. The proposed trimming methodology for
the Home Office Contract Labor cost weight is slightly different than
the proposed trimming methodology for the other six cost categories.
For the Wages and Salaries, Employee Benefits, Contract Labor,
Pharmaceuticals, Professional Liability Insurance, and Capital cost
weights, we first divided the costs for each of these six categories by
total Medicare allowable costs calculated for the provider to obtain
cost weights for the universe of IPF providers. Next, we applied a
mutually exclusive top and bottom 5 percent trim for each cost weight
to remove outliers. After the outliers have been removed, we summed the
costs for each category across all remaining providers. We then divided
this by the sum of total Medicare allowable costs across all remaining
providers to obtain a cost weight for the proposed 2016-based IPF
market basket for the given category.
Finally, we calculated the residual ``All Other'' cost weight that
reflects all remaining costs that are not captured in the seven cost
categories listed. We did not receive any comments on the derivation of
the major cost weights. In this final rule, we are finalizing our
methodology for deriving the major cost weights as we proposed.
Table 1 presents the major cost categories and weights calculated
from the Medicare cost reports for the 2016-based IPF market basket as
well as for the 2012-based IPF market basket.
Table 1--Major Cost Categories as Derived From Medicare Cost Reports
------------------------------------------------------------------------
Final 2016- 2012-based
based IPF IPF market
Major cost categories market basket basket
(percent) (percent)
------------------------------------------------------------------------
Wages and Salaries...................... 51.2 51.0
Employee Benefits....................... 13.5 13.1
Contract Labor.......................... 1.3 1.3
Professional Liability Insurance 0.9 1.1
(Malpractice)..........................
Pharmaceuticals......................... 4.7 4.8
Home Office/Related Organization 3.5 n/a
Contract Labor.........................
Capital................................. 7.1 7.0
``All Other'' Residual.................. 17.9 21.6
------------------------------------------------------------------------
Note: Total may not sum to 100 due to rounding.
As we did for the 2012-based IPF market basket, we proposed 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 the proposed rule,
this rounded percentage was 79 percent; therefore, we proposed 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. The 2012-based IPF market basket percentage was 80 percent. We
did not receive any comments on the allocation of the Contract Labor
cost weight.
Table 2 shows the Wages and Salaries and Employee Benefit cost
weights after Contract Labor cost weight allocation for both the 2016-
based IPF market basket and 2012-based IPF market basket.
Table 2--Wages and Salaries and Employee Benefits Cost Weights After
Contract Labor Allocation
------------------------------------------------------------------------
Final 2016- 2012-Based
Major cost categories based IPF IPF market
market basket basket
------------------------------------------------------------------------
Wages and Salaries...................... 52.2 52.1
Employee Benefits....................... 13.8 13.4
------------------------------------------------------------------------
[[Page 38431]]
iii. Derivation of the Detailed Operating Cost Weights
To further divide the ``All Other'' residual cost weight estimated
from the 2016 Medicare Cost Report data into more detailed cost
categories, we proposed to use the 2012 Benchmark Input-Output (I-O)
``Use Tables/Before Redefinitions/Purchaser Value'' for NAICS 622000
Hospitals, published by the Bureau of Economic Analysis (BEA). These
data, publicly available at https://www.bea.gov/industry/io_annual.htm,
are the most recent data available at the time of rulemaking. For the
2012-based IPF market basket, we used the 2007 Benchmark I-O data.
The BEA Benchmark I-O data are scheduled for publication every five
years. The 2012 Benchmark I-O data are derived from the 2012 Economic
Census and are the building blocks for BEA's economic accounts. 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 proposed to inflate the 2012
Benchmark I-O data forward to 2016 by applying the annual price changes
from the respective price proxies to the appropriate market basket cost
categories obtained from the 2012 Benchmark I-O data. We then proposed
to calculate the cost shares that each cost category represents of the
inflated 2016 data. These resulting 2016 cost shares were applied to
the ``All Other'' residual cost weight to obtain the proposed detailed
cost weights for the 2016-based IPF market basket. For example, the
cost for Food: Direct Purchases represents 5.0 percent of the sum of
the ``All Other'' 2016 Benchmark I-O Hospital Expenditures inflated to
2016. Therefore, the Food: Direct Purchases cost weight represents 5.0
percent of the 2016-based IPF market basket's ``All Other'' cost
category (17.9 percent), yielding a ``final'' Food: Direct Purchases
cost weight of 0.9 percent in the proposed 2016-based IPF market basket
(0.05 * 17.9 percent = 0.9 percent).
---------------------------------------------------------------------------
\1\ https://www.bea.gov/papers/pdf/IOmanual_092906.pdf.
---------------------------------------------------------------------------
Using this methodology, we proposed to derive seventeen detailed
IPF market basket cost category weights from the proposed 2016-based
IPF market basket residual cost weight (17.9 percent). These categories
were: (1) Electricity, (2) Fuel, Oil, and Gasoline, (3) Food: Direct
Purchases, (4) Food: Contract Services, (5) Chemicals, (6) Medical
Instruments, (7) Rubber & 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, (13) All Other Labor-related Services, (14)
Professional Fees: Nonlabor-related, (15) Financial Services, (16)
Telephone Services, and (17) All Other Nonlabor-related Services. We
note that for the 2012-based IPF market basket, we had a Water and
Sewerage cost weight. For the proposed 2016-based IPF market basket, we
proposed to include Water and Sewerage in the Electricity cost weight
due to the small amount of costs in this category.
We did not receive any comments on the derivation of the detailed
operating cost weights. In this final rule, we are finalizing our
methodology for deriving the detailed operating cost weights as we
proposed.
iv. Derivation of the Detailed Capital Cost Weights
As described in section III.A.3.a.i. of this final rule, we
proposed a Capital-Related cost weight of 7.1 percent as obtained from
the 2016 Medicare cost reports for freestanding and hospital-based IPF
providers. We proposed to further separate this total Capital-Related
cost weight into more detailed cost categories. Using 2016 Medicare
cost reports, we were able to group Capital-Related costs into the
following categories: Depreciation, Interest, Lease, and Other Capital-
Related costs. For each of these categories, we proposed to determine
separately for hospital-based IPFs and freestanding IPFs what
proportion of total capital-related costs the category represent.
For freestanding IPFs, we proposed to derive the proportions for
Depreciation, Interest, Lease, and Other Capital-related costs using
the data reported by the IPF on Worksheet A-7, which is the same
methodology used for the 2012-based IPF market basket.
For hospital-based IPFs, data for these four categories were not
reported separately for the subprovider; therefore, we proposed 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 subprovider IPF
unit. For example, if depreciation costs make up 60 percent of total
capital costs for the entire facility, we believe it was reasonable to
assume that the hospital-based IPF will also have a 60 percent
proportion because it is a subprovider unit contained within the total
facility. This is the same methodology used for the 2012-based IPF
market basket.
In order to combine each detailed capital cost weight for
freestanding and hospital-based IPFs into a single capital cost weight
for the 2016-based IPF market basket, we proposed 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 2016. 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 2012-based IPF
market basket.
Next, we proposed to allocate lease costs across each of the
remaining detailed capital-related cost categories as done in the 2012-
based IPF market basket. This resulted in three primary capital-related
cost categories in the 2016-based IPF market basket: Depreciation,
Interest, and Other Capital-Related costs. As done in the 2012-based
IPF market basket, lease costs are unique in that they are not broken
out as a separate cost category in the 2016-based IPF market basket,
but rather we proposed to proportionally distribute these costs among
the cost categories of Depreciation, Interest, and Other Capital-
Related, reflecting the assumption that the underlying cost structure
of leases is similar to that of capital-related costs in general. As
done under the 2012-based IPF market basket, we proposed 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 Other Capital-
Related cost category accordingly. We proposed 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 is the same methodology used for the
2012-based IPF market basket. The allocation of these lease expenses
are shown in Table 3.
Finally, we proposed to further divide the Depreciation and
Interest cost categories. We proposed to separate Depreciation into the
following two categories: (1) Building and Fixed Equipment; and (2)
Movable Equipment;
[[Page 38432]]
and proposed to separate Interest into the following two categories:
(1) Government/Nonprofit; and (2) For-profit.
To disaggregate the Depreciation cost weight, we determined 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 2016-based IPF market basket, we proposed
to use slightly different methods to obtain the fixed percentages for
hospital-based IPFs compared to freestanding IPFs.
For freestanding IPFs, we proposed to use depreciation data from
Worksheet A-7 of the 2016 Medicare cost reports. However, for hospital-
based IPFs, we determined that the fixed percentage for the entire
facility may not be representative of the IPF subprovider 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 proposed to calculate a fixed percentage using:
(1) Building and fixture capital costs allocated to the subprovider
unit as reported on Worksheet B, part I line 40; and (2) building and
fixture capital costs for the top five ancillary cost centers utilized
by hospital-based IPFs. We proposed to then weight these two fixed
percentages (inpatient and ancillary) using the proportion that each
capital cost type represents of total capital costs in the proposed
2016-based IPF market basket. We then proposed to 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 2012-based IPF market basket.
To disaggregate the Interest cost weight, we determined the percent
of total interest costs for IPFs that were attributable to government
and nonprofit facilities, the ``nonprofit percentage.'' For the 2016-
based IPF market basket, we proposed to use interest costs data from
Worksheet A-7 for both freestanding and hospital-based IPFs. We then
determined the percent of total interest costs that are attributed to
government and nonprofit IPFs separately for hospital-based and
freestanding IPFs and weight the nonprofit percentages for hospital-
based and freestanding IPFs together using the proportion of total
capital costs each provider type represents. This is the same
methodology used for the 2012-based IPF market basket.
We did not receive public comments on the derivation of the
detailed capital cost weights. In this final rule, we are finalizing
our methodology for deriving the detailed capital cost weights as we
proposed. Table 3 provides the detailed capital cost share composition
of the 2016-based IPF market basket. These detailed capital cost share
composition percentages are applied to the total Capital-Related cost
weight of 7.1 percent determined in section III.A.3.a.i. of this final
rule.
Table 3--Capital Cost Share Composition for the Final 2016-Based IPF
Market Basket
------------------------------------------------------------------------
Capital cost Capital cost
share share
composition composition
before lease after lease
expense expense
allocation allocation
(percent) (percent)
------------------------------------------------------------------------
Depreciation............................ 60 74
Building and Fixed Equipment........ 43 52
Movable Equipment................... 18 22
Interest................................ 13 16
Government/Nonprofit................ 10 12
For Profit.............................. 3 4
Lease................................... 20 n/a
Other................................... 7 10
------------------------------------------------------------------------
Note: Detail may not add to total due to rounding.
v. 2016-Based IPF Market Basket Cost Categories and Weights
Table 4 shows the cost categories and weights for the final 2016-
based IPF market basket and the 2012-based IPF market basket.
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b. Selection of Price Proxies
After developing the cost weights for the proposed 2016-based IPF
market basket, we selected 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 based
the price proxies on Bureau of Labor Statistics (BLS) data and grouped
them into one of the following BLS categories:
Employment Cost Indexes. 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. Producer Price Indexes (PPIs)
measure price changes for goods sold in other than retail markets. PPIs
are used when the purchases of goods or services are made at the
wholesale level.
Consumer Price Indexes. Consumer Price Indexes (CPIs)
measure change in the prices of final goods and services bought by
consumers. 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. 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 from the
true population parameter that occurs by chance because only a sample
was surveyed rather than the entire population.)
Timeliness. Timeliness implies that the proxy is published
regularly, preferably at least once a quarter. The market baskets are
updated quarterly and, therefore, it is important for the underlying
price proxies to be up-to-date, reflecting the most recent data
available. We believe that using proxies that are published regularly
(at least quarterly, whenever possible) helps to ensure that we are
using the most recent data available to update the market basket. We
strive to use publications that are disseminated frequently, because we
believe that this is an optimal way to stay abreast of the most current
data available.
Availability. Availability means that the proxy is
publicly available. We prefer that our proxies are publicly available
because this will help ensure that our market basket updates are as
transparent to the public as possible. In addition, this enables the
public to be able to obtain the price proxy data on a regular basis.
Relevance. Relevance means that the proxy is applicable
and representative of the cost category weight to which it is applied.
The CPIs, PPIs, and ECIs that we selected meet these criteria.
Therefore, we believe that they continue to be the best measure of
price changes for the cost categories to which they would be applied.
Table 12 lists all price proxies that we proposed to use for the
2016-based IPF market basket. A detailed explanation of the price
proxies we proposed for each cost category weight is provided.
i. Price Proxies for the Operating Portion of the 2016-Based IPF Market
Basket
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 2016-based IPF market basket, we proposed to
apply a proxy blend based on six occupational subcategories within the
Wages and Salaries category, which would reflect the IPF occupational
mix, as done for the 2012-based IPF market basket.
We proposed to use the National Industry-Specific Occupational
Employment and Wage estimates for NAICS 622200, Psychiatric & Substance
Abuse Hospitals, published by the Bureau of Labor Statistics Office of
Occupational Employment Statistics (OES), as the data source for the
wage cost shares in the wage proxy blend. We proposed to use May 2016
OES 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 2012-
based IPF market basket, we used May 2012 OES data.
Based on the OES 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 2016 occupational assignments for the six wage subcategories;
these are the same occupational groups used in the 2012-based IPF
market basket.
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[[Page 38436]]
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Total expenditures by occupation (that is, occupational assignment)
were calculated by taking the OES number of employees multiplied by the
OES 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 proposed 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 2012-based IPF market basket. We did not receive
any public comments on the 2016-based IPF wage price proxy. In this
final rule, we are finalizing the 2016-based IPF wage price proxy as
proposed.
[[Page 38437]]
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BILLING CODE 4120-C
A comparison of the yearly changes from FY 2017 to FY 2020 for the
2016-based IPF wage blend and the 2012-based IPF wage blend is shown in
Table 7. The average annual growth rate is the same for both price
proxies over 2017-2020.
Table 7--Fiscal Year Growth in the 2016-Based IPF Wage Proxy Blend and 2012-Based IPF Wage Proxy Blend
----------------------------------------------------------------------------------------------------------------
Average
2017 2018 2019 2020 2017-2020
----------------------------------------------------------------------------------------------------------------
2016-based IPF Final Wage Proxy Blend.................... 2.4 2.6 3.0 3.2 2.8
2012-based IPF Wage Proxy Blend.......................... 2.4 2.6 3.0 3.2 2.8
----------------------------------------------------------------------------------------------------------------
**Source: IHS Global Inc., 2nd Quarter 2019 forecast with historical data through 1st Quarter 2019.
Benefits
To measure benefits price growth in the 2016-based IPF market
basket, we proposed 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 publically available.
Therefore, an ``ECIs for Total Benefits'' is calculated using
publically 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 2012-based IPF market basket as
well as used in the IPPS, SNF, HHA, RPL, LTCH, and 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
Benefits cost category in the proposed 2016-based IPF market basket. We
did not receive any public comments on the 2016-based IPF benefit price
proxy. In this final rule, we are finalizing the 2016-based IPF benefit
price proxy as proposed.
[[Page 38438]]
Table 8--Final 2016-Based IPF Market Basket Benefits Proxy Blend
----------------------------------------------------------------------------------------------------------------
2016-based 2012-based
benefit blend benefit blend
Wage subcategory weight weight Price proxy
(percent) (percent)
----------------------------------------------------------------------------------------------------------------
Health Service............................. 36.3 36.2 ECI for Total Benefits for All
Civilian workers in Healthcare and
Social Assistance.
Health Professional and Technical.......... 34.9 33.5 ECI for Total Benefits for All
Civilian workers in Hospitals.
NonHealth Service.......................... 8.9 9.2 ECI for Total Benefits for Private
Industry workers in Service
Occupations.
NonHealth Professional and Technical....... 7.0 7.3 ECI for Total Benefits for Private
Industry workers in Professional,
Scientific, and Technical
Services.
Management................................. 6.8 7.1 ECI for Total Benefits for Private
Industry workers in Management,
Business, and Financial.
Clerical................................... 6.1 6.7 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 2017 to FY 2020 for the
2016-based IPF benefit proxy blend and the 2012-based IPF benefit proxy
is shown in Table 9. The average annual growth rate is the same for
both price proxies over 2017-2020.
Table 9--Fiscal Year Growth in the 2016-Based IPF Benefit Proxy Blend and 2012-Based IPF Benefit Proxy Blend
----------------------------------------------------------------------------------------------------------------
Average 2017-
2017 2018 2019 2020 2020
----------------------------------------------------------------------------------------------------------------
2016-based IPF Final Benefit 1.9 2.1 2.5 3.0 2.4
Proxy Blend....................
2012-based IPF Benefit Proxy 1.9 2.1 2.5 3.0 2.4
Blend..........................
----------------------------------------------------------------------------------------------------------------
Source: IHS Global Inc., 2nd Quarter 2019 forecast with historical data through 1st Quarter 2019.
Electricity
We proposed to continue to use the PPI Commodity Index for
Commercial Electric Power (BLS series code WPU0542) to measure the
price growth of this cost category. This is the same price proxy used
in the 2012-based IPF market basket.
Fuel, Oil, and Gasoline
Similar to the 2012-based IPF market basket, for the 2016-based IPF
market basket, we proposed to use a blend of the PPI for Petroleum
Refineries and the PPI Commodity for Natural Gas. Our analysis of the
BEA's 2012 Benchmark I-O data (use table before redefinitions,
purchaser's value for NAICS 622000 [Hospitals]) shows that Petroleum
Refineries expenses accounts for approximately 90 percent and Natural
Gas accounts for approximately 10 percent of Hospitals (NAICS 622000)
total Fuel, Oil, and Gasoline expenses. Therefore, we proposed 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. The 2012-based IPF market basket used a 70/30 blend of these
price proxies, reflecting the 2007 I-O data. We believe that these two
price proxies continue to be the most technically appropriate indices
available to measure the price growth of the Fuel, Oil, and Gasoline
cost category in the proposed 2016-based IPF market basket.
Professional Liability Insurance
We proposed to continue to use the CMS Hospital Professional
Liability Index to measure changes in professional liability insurance
(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 2012-based IPF market basket.
Pharmaceuticals
We proposed to continue 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
2012-based IPF market basket.
Food: Direct Purchases
We proposed to continue 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 2012-based IPF market
basket.
Food: Contract Purchases
We proposed to continue 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 2012-based IPF market
basket.
Chemicals
Similar to the 2012-based IPF market basket, we proposed to use a
four part blended PPI as the proxy for the chemical cost category in
the proposed 2016-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).
We note that the four part blended PPI used in the 2012-based IPF
market basket is composed of the PPI for Industrial Gas Manufacturing
(BLS
[[Page 38439]]
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 Soap and Cleaning Compound Manufacturing (BLS
series code PCU32561-32561-).
We proposed to derive the weights for the PPIs using the 2012
Benchmark I-O data. The 2012-based IPF market basket used the 2007
Benchmark I-O data to derive the weights for the four PPIs.
Table 10 shows the weights for each of the four PPIs used to create
proposed blended Chemical proxy for the 2016-based IPF market basket
compared to the 2012-based IPF market basket blended Chemical proxy.
Table 10--Blended Chemical PPI Weights
----------------------------------------------------------------------------------------------------------------
Final 2016-
based IPF 2012-based IPF
Name weights weights NAICS
(percent) (percent)
----------------------------------------------------------------------------------------------------------------
PPI for Industrial Gas Manufacturing............................ 19 32 325120
PPI for Other Basic Inorganic Chemical Manufacturing............ 13 17 325180
PPI for Other Basic Organic Chemical Manufacturing.............. 60 45 325190
PPI for Soap and Cleaning Compound Manufacturing................ n/a 6 325610
PPI for Other Miscellaneous Chemical Product Manufacturing...... 8 n/a 325998
----------------------------------------------------------------------------------------------------------------
Medical Instruments
We proposed to continue to use a blend of two PPIs for the Medical
Instruments cost category. The 2012 Benchmark I-O data shows an
approximate 57/43 split between Surgical and Medical Instruments and
Medical and Surgical Appliances and Supplies for this cost category.
Therefore, we proposed a blend composed of 57 percent of the commodity-
based PPI for Surgical and Medical Instruments (BLS series code
WPU1562) and 43 percent of the commodity-based PPI for Medical and
Surgical Appliances and Supplies (BLS series code WPU1563). The 2012-
based IPF market basket used a 50/50 blend of these PPIs based on the
2007 Benchmark I-O data.
Rubber and Plastics
We proposed to continue 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 2012-based IPF market
basket.
Paper and Printing Products
We proposed to continue 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 2012-
based IPF market basket.
Miscellaneous Products
We proposed to continue 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 2012-based IPF
market basket.
Professional Fees: Labor-Related
We proposed to continue 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 2012-based IPF market basket.
Administrative and Facilities Support Services
We proposed to continue 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 2012-based IPF market
basket.
Installation, Maintenance, and Repair
We proposed to continue 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 2012-based IPF market
basket.
All Other: Labor-Related Services
We proposed to continue 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 2012-based IPF market basket.
Professional Fees: Nonlabor-Related
We proposed to continue 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 2012-based IPF market basket.
Financial Services
We proposed to continue 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 2012-based IPF market basket.
Telephone Services
We proposed to continue 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 2012-based IPF market
basket.
All Other: Nonlabor-Related Services
We proposed to continue 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 2012-based IPF
market basket. We did not receive any public comments on the 2016-based
IPF price proxies. In this final rule, we are finalizing the 2016-based
IPF price proxies as proposed.
ii. Price Proxies for the Capital Portion of the Proposed 2016-Based
IPF Market Basket
Capital Price Proxies Prior to Vintage Weighting
We proposed to continue to use the same price proxies for the
capital-related cost categories as were applied in the 2012-based IPF
market basket, which are provided and described in Table 12.
Specifically, we proposed to proxy:
Depreciation: Building and Fixed Equipment cost category
by BEA's
[[Page 38440]]
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 average yield on
Moody's Aaa bonds (Federal Reserve).
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 proposed to continue
to vintage weight the capital price proxies for Depreciation and
Interest in order to capture the long-term consumption of capital. This
vintage weighting method is similar to the method used for the 2012-
based IPF market basket and is described in the section labeled Vintage
Weights for Price Proxies.
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 2016-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
proposed 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 2016-based IPF market
basket reflects the underlying stability of the capital-related
acquisition process.
The methodology used to calculate the vintage weights for the 2016-
based IPF market basket is the same as that used for the 2012-based IPF
market basket with the only difference being the inclusion of more
recent data. To calculate the vintage weights for depreciation and
interest expenses, we first needed 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 listed 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-related purchases. However, the AHA provided a consistent
database of total expenses back to 1963. Consequently, we proposed 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 proposed 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 2016. We proposed to separate these depreciation expenses into
annual amounts of building and fixed equipment depreciation and movable
equipment depreciation as previously determined. From these annual
depreciation amounts we derived annual end-of-year book values for
building and fixed equipment and movable equipment using the expected
life for each type of asset category. While data are not available that
are 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 needed the expected lives for Building and
Fixed Equipment, Movable Equipment, and Interest for the proposed 2016-
based IPF market basket. We proposed 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
proposed to determine the expected life of building and fixed equipment
separately for hospital-based IPFs and freestanding IPFs and weight
these expected lives using the percent of total capital costs each
provider type represents. We proposed 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 22
years, and the average expected life of movable equipment to be equal
to 11 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 2012-based IPF
market basket the expected life of building and fixed equipment is 23
years and the expected life of movable equipment is 11 years.
Multiplying these expected lives by the annual depreciation amounts
results in annual year-end asset costs for building and fixed equipment
and movable equipment. We then calculated a time series, beginning in
1964, of annual capital purchases by subtracting the previous year's
asset costs from the current year's asset costs.
For the building and fixed equipment and movable equipment vintage
weights, we proposed 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. For the interest vintage weights, we proposed 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 proposed 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
[[Page 38441]]
interest, 22 years, and in the case of movable equipment, 11 years).
For each asset type, we used the time series of annual capital-related
purchase amounts available from 2016 back to 1964. These data allow us
to derive thirty-two 22-year periods of capital-related purchases for
building and fixed equipment and interest, and forty-two 11-year
periods of capital-related purchases for movable equipment. For each
22-year period for building and fixed equipment and interest, or 11-
year period for movable equipment, we calculated annual vintage weights
by dividing the capital-related purchase amount in any given year by
the total amount of purchases over the entire 22-year or 11-year
period. This calculation is done for each year in the 22-year or 11-
year period and for each of the periods for which we have data. We then
calculated the average vintage weight for a given year of the expected
life by taking the average of these vintage weights across the multiple
periods of data. We did not receive any public comments on the
methodology used to derive the vintage weights. In this final rule, we
are finalizing the 2016-based IPF market basket vintage weights as
proposed. Table 11 presents the vintage weights for the capital-related
portion of the 2016-based IPF market basket and the 2012-based IPF
market basket.
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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 11 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 the
following link: https://www.cms.gov/Research-Statistics-Data-and-
Systems/Statistics-Trends-and-Reports/MedicareProgramRatesStats/
[[Page 38442]]
MarketBasketResearch.html in the zip file titled ``Weight Calculations
as described in the IPPS FY 2010 Proposed Rule.''
iii. Summary of Price Proxies of the Final 2016-Based IPF Market Basket
Table 12 shows both the operating and capital price proxies for the
2016-based IPF market basket.
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BILLING CODE 4120-01-C
Comment: One commenter supported the proposal to rebase and revise
the IPF market basket to reflect a 2016 base year from a 2012 base
year--as this ensures the most recent cost data is utilized.
Response: We appreciate the commenter's support.
Final Decision: After careful consideration of public comments, we
are finalizing the 2016-based IPF market basket as proposed.
4. FY 2020 Market Basket Update
For FY 2020 (that is, beginning October 1, 2019 and ending
September 30, 2020), we proposed to use an estimate of the 2016-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 that contracts with CMS to forecast the components of
the market baskets and multifactor productivity (MFP). In the FY 2020
IPF proposed rule, we proposed a FY 2020 IPF market basket increase of
3.1 percent based on IGI's fourth quarter 2018 forecast with historical
data through third quarter 2018. In the FY 2020 proposed rule, we also
proposed that if more recent data are subsequently available (for
example, a more recent estimate of the market basket and MFP
adjustment) we would use such data, to determine the FY 2020 update in
the final rule.
Table 13 compares the final 2016-based IPF market basket and the
2012-based IPF market basket percent changes using the most recent
estimate based on IGI's second quarter 2019 forecast with historical
data through the first quarter of 2019. The projected 2016-based IPF
market basket increase factor for FY 2020 is 2.9 percent. For
comparison, the current 2012-based IPF market basket is also projected
to increase by 2.9 percent in FY 2020 based on IGI's second quarter
2019 forecast.
Table 13--Final 2016-Based IPF Market Basket and 2012-Based IPF Market
Basket Percent Changes, FY 2015 Through FY 2022
------------------------------------------------------------------------
Final 2016-
based IPF 2012-based IPF
Fiscal year (FY) market basket market basket
index percent index percent
change change
------------------------------------------------------------------------
Historical data:
FY 2015............................. 1.9 1.8
FY 2016............................. 1.9 1.9
FY 2017............................. 2.4 2.5
FY 2018............................. 2.6 2.6
-------------------------------
Average 2015-2018............... 2.2 2.2
-------------------------------
Forecast:
FY 2019............................. 2.6 2.7
FY 2020............................. 2.9 2.9
FY 2021............................. 3.1 3.2
FY 2022............................. 3.1 3.1
-------------------------------
Average 2019-2022............... 2.9 3.0
------------------------------------------------------------------------
Note: These market basket percent changes do not include any further
adjustments as may be statutorily required. Source: IHS Global Inc.
2nd quarter 2019 forecast.
5. 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 (MFP) (as projected by the Secretary for the 10-year
period ending with the applicable FY, year, cost reporting period, or
other annual period) (the ``MFP adjustment''). The BLS publishes the
official measure of private non-farm business MFP. We refer readers to
the BLS website at https://www.bls.gov/mfp for the BLS historical
published MFP data.
MFP is derived by subtracting the contribution of labor and capital
inputs growth from output growth. The projections of the components of
MFP are currently produced by IGI, a nationally recognized economic
forecasting firm with which CMS contracts to forecast the components of
the market baskets and MFP. For more information on the productivity
adjustment, we refer reader to the discussion in the FY 2016 IPF PPS
final rule (80 FR 46675).
For the FY 2020 final rule, using IGI's second quarter 2019
forecast, the MFP adjustment for FY 2020 (the 10-year moving average of
MFP for the period ending FY 2020) is projected to be 0.4 percent.
Thus, in accordance with section 1886(s)(2)(A)(i) of the Act, we
[[Page 38445]]
base the FY 2020 market basket update, which is used to determine the
applicable percentage increase for the IPF payments, on the most recent
estimate of the 2016-based IPF market basket (currently estimated to be
2.9 percent based on IGI's second quarter 2019 forecast). We then
reduce this percentage increase of 2.9 percent by the current estimate
of the MFP adjustment for FY 2020 of 0.4 percentage point (the 10-year
moving average of MFP for the period ending FY 2020 based on IGI's
second quarter 2019 forecast) yielding a productivity-adjusted IPF
market basket update of 2.5 percent. In addition, for FY 2020 the 2016-
based IPF PPS market basket update is further reduced by 0.75
percentage point as required by sections 1886(s)(2)(A)(ii) and
1886(s)(3)(E) of the Act. This results in a FY 2020 IPF PPS payment
rate update of 1.75 percent (2.9-0.4-0.75 = 1.75 percent).
6. Labor-Related Share for FY 2020
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 proposed to continue to classify a cost category as labor-
related if the costs are labor intensive and vary with the local labor
market.
We proposed 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, All Other: Labor-related Services, and a
portion of the Capital-Related cost weight from the proposed 2016-based
IPF market basket. These are the same categories as the 2012-based IPF
market basket.
Similar to the 2012-based IPF market basket, the 2016-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 2016-based IPF market
basket, we proposed 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 2012-based IPF market basket.
As done in the 2012-based IPF market basket, we proposed 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 proposed 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 2012-based IPF market basket
professional fees category into Professional Fees: Labor-related and
Professional Fees: Nonlabor-related cost categories.
In the 2016-based IPF market basket, nonmedical professional fees
that were subject to allocation based on these survey results represent
3.6 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 2.3
percentage points of the 3.6 percentage point figure into the
Professional Fees: Labor-related share cost category and designate the
remaining 1.3 percentage point into the Professional Fees: Nonlabor-
related cost category.
In addition to the professional services listed, for the 2016-based
IPF market basket, we proposed to allocate a proportion of the Home
Office Contract Labor cost weight, calculated using the Medicare cost
reports, into the Professional Fees: Labor-related and Professional
Fees: Nonlabor-related cost categories. We proposed 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 2012-based IPF market basket, we proposed for the
2016-based 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 proposed 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
determined the proportion of the Home Office 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 proposed to
allocate 46 percent of the Home Office Contract Labor cost weight (1.6
percentage points = 3.5 percent times 46 percent) to the Professional
Fees: Labor-related cost weight and 54 percent of the Home Office
Contract Labor cost weight to the Professional Fees: Nonlabor-related
cost weight (1.9 percentage points = 3.5 percent times 54 percent). For
the 2012-based IPF market basket, we used a similar methodology but we
relied on provider counts rather than total Medicare allowable costs to
determine the labor-related percentage.
In summary, based on the two allocations mentioned earlier, we
apportioned percentage points of the professional fees and home office/
related organization contract labor cost weights into the Professional
Fees: Labor-Related cost category. This amount was added to the portion
of professional fees that we already
[[Page 38446]]
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 4.4 percent.
As stated, we proposed 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, All
Other: Labor-related Services, and a portion of the Capital-Related
cost weight from the proposed 2016-based IPF market basket. The
relative importance reflects the different rates of price change for
these cost categories between the base year (2016) and FY 2020. Based
on IHS Global Inc. 4th quarter 2018 forecast of the proposed 2016-based
IPF market basket, we proposed a total labor-related share for FY 2020
of 76.8 percent (the sum of 73.7 percent for the operating cost and 3.1
percent for the labor-related share of Capital).
Comment: One commenter opposed the increase in the labor-related
share from 74.8 percent to 76.8 percent stating it would negatively
impact any facility with a wage index below 1.0. The growing disparity
in wage indices places facilities in low wage areas at a significant
disadvantage, and this proposal will further increase that disparity.
They encouraged CMS to maintain the FY 2019 labor-related share in FY
2020.
Response: For FY 2020, we proposed the FY 2020 labor-related share
to be equal to the sum of the relative importance of shares of the
following proposed 2016-based IPF market basket cost categories: Wages
and Salaries, Employee Benefits, Professional Fees: Labor-Related,
Administrative and Facilities Support Services, Installation,
Maintenance, and Repair, All Other: Labor-related Services, and a
portion of the Capital-Related cost weight. The FY 2019 labor-related
share reflected the sum of the relative importance shares of the same
categories using the 2012-based IPF market basket.
The increase in the labor-related share from FY 2019 to FY 2020 is
mostly a result of the rebasing and revising of the IPF market basket
to reflect more recent data. Of the 2.0-percentage point difference
between the FY 2020 labor-related share using the proposed 2016-based
IPF market basket and the labor share used in FY 2019, 1.9 percentage
point is from rebasing the market basket. The detailed factors
contributing to the difference are: 0.6 percentage point is due to an
increase in the Compensation and Capital cost weights as a result of
incorporating the 2016 MCR data, 0.3 percentage point is due to
revising the starting point of the calculation of the relative
importance from 2012 to 2016, 0.3 percentage point is due to the use of
MCR data to calculate the Home Office Contract Labor cost weight (a
portion of which is included in the Professional Fees: Labor-related
services cost weight), and the remaining 0.7 percentage point is due to
the incorporation of the 2012 Benchmark I-O data, primarily stemming
from an increase in the Professional Fees: Labor-related cost weight.
We appreciate the commenter's concern over the increase in the
labor-related share; however, we believe it is technically appropriate
to use the 2016-based IPF market basket to determine the labor-related
share for FY 2020 as it is based on more recent data regarding price
pressures and cost structure of IPFs. Our policy to use the most recent
market basket to determine the labor-related share is a policy we have
regularly adopted for the IPF PPS as well as for other PPSs including
but not limited to the IPPS, the Inpatient Rehabilitation Facility PPS,
and the Long-term care hospital PPS.
Final Decision: After careful consideration of comments, in this
final rule, we are finalizing the 2016-based IPF market basket labor-
related share cost weights as proposed.
Based on IHS Global Inc. 2nd quarter 2019 forecast of the 2016-
based IPF market basket, the sum of the FY 2020 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
73.8 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 2012-based IPF market basket. Since the
relative importance for Capital is 6.8 percent of the 2016-based IPF
market basket in FY 2020, we took 46 percent of 6.8 percent to
determine the proposed labor-related share of Capital for FY 2020 of
3.1 percent. Therefore, we are finalizing a total labor-related share
for FY 2020 of 76.9 percent (the sum of 73.8 percent for the operating
cost and 3.1 percent for the labor-related share of Capital).
Table 14 shows the FY 2020 labor-related share using the final
2016-based IPF market basket relative importance and the FY 2019 labor-
related share using the 2012-based IPF market basket.
[[Page 38447]]
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B. Updates to the IPF PPS Rates for FY Beginning October 1, 2019
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 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. Additional
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
electroconvulsive therapy (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
[[Page 38448]]
used on IPF claims as a result of the proposed update to the ICD-10-PCS
code set for FY 2020. Addendum B-4 to this final rule shows the ECT
procedure codes for FY 2020 and is available on our website at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/InpatientPsychFacilPPS/tools.html.
2. Update of the Federal Per Diem Base Rate and Electroconvulsive
Therapy Payment Per Treatment
The current (FY 2019) federal per diem base rate is $782.78 and the
ECT payment per treatment is $337.00. For the FY 2020 federal per diem
base rate, we applied the payment rate update of 1.75 percent (that is,
the 2016-based IPF market basket increase for FY 2020 of 2.9 percent
less the productivity adjustment of 0.4 percentage point, and further
reduced by the 0.75 percentage point required under section
1886(s)(3)(E) of the Act), and the wage index budget-neutrality factor
of 1.0026 (as discussed in section III.D.1.f of this final rule) to the
FY 2019 federal per diem base rate of $782.78, yielding a federal per
diem base rate of $798.55 for FY 2020. Similarly, we applied the 1.75
percent payment rate update and the 1.0026 wage index budget-neutrality
factor to the FY 2019 ECT payment per treatment of $337.00, yielding an
ECT payment per treatment of $343.79 for FY 2020.
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 rate year, the Secretary will reduce
any annual update to a standard federal rate for discharges during the
RY by 2.0 percentage points. Therefore, we are applying a 2.0
percentage point reduction to the federal per diem base rate and the
ECT payment per treatment as follows:
For IPFs that fail requirements under the Inpatient
Psychiatric Facilities Quality Reporting (IPFQR) Program, we applied a
-0.25 percent payment rate update (that is, the IPF market basket
increase for FY 2020 of 2.9 percent less the productivity adjustment of
0.4 percentage point, further reduced by the 0.75 percentage point for
an update of 1.75 percent, and further reduced by 2 percentage points
in accordance with section 1886(s)(4)(A)(ii) of the Act, which results
in a negative update percentage) and the wage index budget-neutrality
factor of 1.0026 to the FY 2019 federal per diem base rate of $782.78,
yielding a federal per diem base rate of $782.85 for FY 2020.
For IPFs that fail to meet requirements under the IPFQR
Program, we applied the -0.25 percent annual payment rate update and
the 1.0026 wage index budget-neutrality factor to the FY 2019 ECT
payment per treatment of $337.00, yielding an ECT payment per treatment
of $337.03 for FY 2020.
C. 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 are finalizing our proposal to continue to use the existing
regression-derived adjustment factors established in 2005 for FY 2020.
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. 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
Inpatient Prospective Payment System (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 2020, we did not propose any changes to the IPF MS-DRG
adjustment factors but are finalizing our proposal to maintain 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. 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 2020, we are finalizing our proposal to continue to make 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,
2019, using the final IPPS FY 2020 ICD-10-CM/PCS code sets. The FY 2020
IPPS final rule includes tables of the final changes to the ICD-10-CM/
PCS code sets which underlie the FY 2020 IPF
[[Page 38449]]
MS-DRGs. Both the FY 2020 IPPS final rule and the tables of proposed
changes to the ICD-10-CM/PCS code sets which underlie the FY 2020 MS-
DRGs are available on the 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 would follow the instructions
in the ICD-10-CM text. The submitted claim goes through the CMS
processing system, which will identify the primary 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, see our November
2004 IPF PPS final rule (69 FR 66945) and see sections I.A.13 and I.B.7
of the FY 2019 ICD-10-CM Coding Guidelines, available at https://www.cdc.gov/nchs/icd/data/10cmguidelines-FY2019-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 were present in ICD-9-CM (79
FR 46009). In FY 2018 and FY 2019, there were no changes to the final
ICD-10-CM/PCS codes in the IPF Code First table. For FY 2020, there
continue to be no changes to the ICD-10-CM/PCS codes in the proposed
IPF Code First table. The final FY 2020 Code First table is shown in
Addendum B-1 on our website at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/InpatientPsychFacilPPS/tools.html.
b. 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,
length of stay (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 would 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 2020, we are
finalizing our proposal to continue to use the same comorbidity
adjustment factors in effect in FY 2019, which are found in Addendum A,
available on our website at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/InpatientPsychFacilPPS/tools.html.
We have updated the ICD-10-CM/PCS codes which are associated with
the existing IPF PPS comorbidity categories, based upon the final FY
2020 update to the ICD-10-CM/PCS code set. The final FY 2020 ICD-10-CM/
PCS updates include 4 ICD-10-CM diagnosis codes added to the Poisoning
comorbidity category and 88 ICD-10-PCS codes added to the Oncology
Procedures comorbidity category. In addition, 3 ICD-10-PCS codes were
deleted from the Oncology Procedures comorbidity category. These
updates are detailed in Addenda B-2 and B-3 of this final rule, which
are available on our 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 2020
ICD-10-CM codes to remove codes that were site ``unspecified'' in terms
of laterality from the FY 2020 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 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 proposed additions to the FY 2020
ICD-10-CM/PCS codes were site ``unspecified'' by laterality, therefore
we are not removing any of the new codes.
[[Page 38450]]
c. 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 more
costly 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 2020, we are finalizing our proposal
to continue to use the patient age adjustments currently in effect in
FY 2019, as shown in Addendum A of this rule (see https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/InpatientPsychFacilPPS/tools.html).
d. 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 length of stay (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 to 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 rule.
For FY 2020, we are finalizing our proposal to continue to use the
variable per diem adjustment factors currently in effect, as shown in
Addendum A of this rule (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. 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), in order 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 Sec. 412.64(b)(1)(ii)(A) and (C).
b. Change to the IPF Wage Index Methodology
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 rate year (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 taking into account 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 was put into regulation at
412.424(a)(2), and requires us to 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
fiscal year 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 an 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 fiscal year (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 FY 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.
We proposed to change 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 proposed to use the
pre-floor, pre-reclassified IPPS hospital wage index from the fiscal
year concurrent with the IPF fiscal year as the basis for the IPF wage
index. For example, the FY 2020 IPF wage index would be 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.
[[Page 38451]]
We explained in the proposed rule (84 FR 16973), that using the
concurrent pre-floor, pre-reclassified IPPS hospital wage index would
result in the most up-to-date wage data being the basis for the IPF
wage index. It would also result in more consistency and parity in the
wage index methodology used by other Medicare payment systems. The
Medicare SNF PPS already uses 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 would 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 2020, we also proposed to continue use the pre-floor, pre-
reclassified IPPS hospital wage index as the basis for the IPF wage
index.
We received 1 comment on our proposal to align the IPF wage index
data timeframe with that of the IPPS, by using the concurrent pre-
floor, pre-reclassified IPPS hospital wage index as the basis for the
IPF wage index for FY 2020 and subsequent years.
Comment: A commenter wrote that he was not opposed to the proposal
to eliminate the 1-year lag in the wage index data, but had issues with
the data itself. The commenter was opposed to using the FY 2020 IPPS
wage index data file discussed in the FY 2020 IPPS proposed rule
because the data excluded several hospitals which had wage data based
upon regional rather than local labor market rates. The commenter felt
this exclusion was inappropriate and that it would negatively affect
certain IPFs.
Response: We appreciate the comment, however, we are finalizing our
proposal to use the concurrent pre-floor, pre-reclassified IPPS
hospital wage index as the basis for IPF wage index for FY 2020 and
subsequent years. For FY 2020, we are also finalizing our proposal to
continue to use the pre-floor, pre-reclassified IPPS hospital wage
index as the basis for the IPF wage index. We believe it is the best
available data to use as a proxy for an IPF wage index. This pre-floor,
pre-reclassified IPPS hospital wage index is also the most appropriate
wage index as IPFs compete in the same labor market as IPPS hospitals;
this wage index best reflects the variation in local labor costs of
IPFs in the various geographic areas using the most recent IPPS
hospital wage data (data from hospital cost reports for the cost
reporting period beginning during FY 2016) without any geographic
reclassifications, floors, or other adjustments. We will apply the FY
2020 IPF wage index to payments beginning October 1, 2019.
We identified a slight error in the proposed rule wage index values
after the FY 2020 IPF PPS proposed rule was published. A programming
error caused the data for all providers in a single county to be
included twice, which affected the national average hourly rate, and
therefore affected nearly all wage index values. We have changed the
programming logic so this error cannot occur again. In addition, we
corrected the classification of one provider in North Carolina that was
erroneously identified as being in an urban CBSA. We also standardized
our procedures for rounding, to ensure consistency. The correction to
the NPRM wage index data was not completed until after the comment
period closed on June 17, 2019. This final rule reflects the corrected
and updated wage index data.
We are finalizing this change to the IPF wage index methodology to
implement it in a budget-neutral manner, so that total IPF payments
will not be affected. However, as shown in Table 15, there will be
distributional effects. Table 15 compares the estimated payments
calculated using the FY 2020 IPF wage index based on the IPPS hospital
wage index data from the prior fiscal year (the current methodology)
with the estimated payments calculated using the FY 2020 IPF wage index
based on concurrent IPPS hospital wage index data (the proposed change
in methodology which we are finalizing). Due to budget neutrality, the
effect on total estimated FY 2020 IPF payments is zero. Table 15 shows
that urban IPFs are estimated to experience a smaller increase in
payments by finalizing the proposed methodology (0.03 percent increase)
compared to if we had maintained the current methodology (0.09 percent
increase). Rural IPFs are estimated to have a smaller decrease in
estimated payments by finalizing the proposed methodology (0.20 percent
decrease) compared to if we had maintained the current methodology
(0.54 percent decrease).
BILLING CODE 4120-01-P
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BILLING CODE 4120-01-C
To provide additional information to IPFs about the effect of
implementing this change in the IPF wage index methodology on estimated
payments, we have also posted a provider-level table of effects
(Addendum C) on the CMS website, available at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/InpatientPsychFacilPPS/WageIndex.html.
We are applying the IPF wage index adjustment to the labor-related
share of the national base rate or ECT payment per treatment. The
labor-related share of the national rate and ECT payment per treatment
will change from 74.8 percent in FY 2019 to 76.9 percent in FY 2020.
This percentage reflects the labor-related share of the 2016-based IPF
market basket for FY 2020 (see section III.A.6 of this rule).
c. Office of Management and Budget Bulletins
OMB publishes bulletins regarding CBSA changes, including changes
to CBSA numbers and titles. 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 MSAs, and the creation of Micropolitan Statistical Areas and
Combined Statistical Areas.
[[Page 38454]]
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). The OMB bulletins may be accessed
online at https://www.whitehouse.gov/omb/information-for-agencies/bulletins/.
In accordance with our established methodology, we have
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. For the FY 2015 IPF wage index, we used
the FY 2014 pre-floor, pre-reclassified IPPS hospital wage index to
adjust the IPF PPS payments. On February 28, 2013, OMB issued OMB
Bulletin No. 13-01, which established revised delineations for MSAs,
Micropolitan Statistical Areas, and Combined Statistical Areas in the
United States and Puerto Rico based on the 2000 Census, and provided
guidance on the use of the delineations of these statistical areas. A
copy of this bulletin may be obtained at https://www.whitehouse.gov/omb/information-for-agencies/bulletins/.
Because the FY 2014 pre-floor, pre-reclassified IPPS hospital wage
index did not reflect the statistical area revisions set forth in OMB
Bulletin 13-01, the FY 2015 IPF PPS wage index, which was based on the
FY 2014 pre-floor, pre-reclassified IPPS hospital wage index, did not
reflect OMB's new area delineations based on the 2010 Census. According
to OMB, ``[t]his bulletin provides the delineations of all Metropolitan
Statistical Areas, Metropolitan Divisions, Micropolitan Statistical
Areas, Combined Statistical Areas, and New England City and Town Areas
in the United States and Puerto Rico based on the standards published
on June 28, 2010, in the Federal Register (75 FR 37246 through 37252)
and Census Bureau data.'' These OMB Bulletin changes are reflected in
the FY 2015 pre-floor, pre-reclassified IPPS hospital wage index, upon
which the FY 2016 IPF wage index was based. We adopted these new OMB
CBSA delineations in the FY 2016 IPF wage index and subsequent IPF wage
indexes.
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. On July 15, 2015, OMB issued
OMB Bulletin No. 15-01, which provided minor updates to, and
superseded, OMB Bulletin No. 13-01 that was issued on February 28,
2013. The attachment to OMB Bulletin No. 15-01 provides detailed
information on the update to statistical areas since February 28, 2013.
The updates provided in the attachment to OMB Bulletin No. 15-01 are
based on the application of the 2010 Standards for Delineating
Metropolitan and Micropolitan Statistical Areas to Census Bureau
population estimates for July 1, 2012 and July 1, 2013. The complete
list of statistical areas incorporating these changes is provided in
OMB Bulletin No. 15-01. A copy of this bulletin may be obtained at
https://www.whitehouse.gov/omb/information-for-agencies/bulletins/. OMB
Bulletin No. 15-01 establishes revised delineations for the Nation's
Metropolitan Statistical Areas, Micropolitan Statistical Areas, and
Combined Statistical Areas. The bulletin also provides delineations of
Metropolitan Divisions as well as delineations of New England City and
Town Areas.
In accordance with our longstanding policy, the IPF PPS continues
to use the latest labor market area delineations available as soon as
is reasonably possible to maintain a more accurate and up-to-date
payment system that reflects the reality of population shifts and labor
market conditions. As discussed in the FY 2017 IPPS/LTCH PPS final rule
(81 FR 56913), the updated labor market area definitions from OMB
Bulletin 15-01 were implemented under the IPPS beginning on October 1,
2016 (FY 2017). Therefore, we implemented these revisions for the IPF
PPS beginning October 1, 2017 (FY 2018), consistent with our historical
practice of modeling IPF PPS adoption of the labor market area
delineations after IPPS adoption of these delineations (historically
the IPF wage index has been based upon the pre-floor, pre-reclassified
IPPS hospital wage index from the prior year).
On August 15, 2017, OMB announced in OMB Bulletin No. 17-01 that
one Micropolitan Statistical Area now qualifies as a Metropolitan
Statistical Area. The new urban CBSA is as follows:
Twin Falls, Idaho (CBSA 46300).
This CBSA is comprised of the principal city of Twin Falls, Idaho
in Jerome County, Idaho and Twin Falls County, Idaho. Prior to this
redesignation, Jerome County and Twin Falls County, Idaho were
classified as rural. The OMB bulletin is available on the OMB website
at https://www.whitehouse.gov/sites/whitehouse.gov/files/omb/bulletins/2017/b-17-01.pdf.
With the change made by OMB Bulletin No. 17-01, these two counties
are now designated as urban, and any IPFs in those areas will change
their status from being rural to being urban. We adopted these new OMB
designations in FY 2020 as they are included in the FY 2020 pre-floor,
pre-reclassified IPPS hospital wage index upon which the FY 2020 IPF
wage index is proposed to be based. That is, the FY 2020 pre-floor,
pre-reclassified IPPS hospital wage index, which is the basis of the
final FY 2020 IPF wage index, will include this new OMB designation.
Therefore, the 17 percent IPF rural adjustment will cease for IPF
providers in these two counties. Currently, there is a single IPF in
new CBSA 46300, which will lose its 17 percent rural adjustment as a
result of being re-designated as urban. However, the FY 2020 IPF wage
index value for CBSA 46300 is 0.8291, which is 3.5 percent higher than
the rural wage index value for Idaho (0.8009). As such, the loss of the
17 percent IPF wage index adjustment will be mitigated in part by the
increase in the wage index value when changing from the rural Idaho
wage index value to the urban CBSA 46300 wage index value. Given that
the loss of the rural adjustment will be mitigated in part by the
increase in wage index value, and that only a single IPF is affected by
this change, we do not believe it is necessary to transition this
provider from its rural to newly urban status.
Thus, we are finalizing our proposal to adopt this new OMB
designation in the proposed IPF wage index for FY 2020 and for
subsequent fiscal years. The FY 2020 IPF wage index already includes
the OMB delineations that were adopted in prior fiscal years. The FY
2020 IPF wage index (including the CBSA update from OMB Bulletin No.
17-01) is located on the CMS website at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/InpatientPsychFacilPPS/WageIndex.html.
[[Page 38455]]
d. Solicitation of Public Comments on the IPF Wage Index
Historically, we have calculated the IPF PPS wage index values
using unadjusted wage index values from another provider setting.
Stakeholders have occasionally commented on certain aspects of the IPF
PPS wage index values and their impact on payments. We solicited
comments on concerns stakeholders may have regarding the wage index
used to adjust IPF PPS payments and suggestions for possible updates
and improvements to the geographic adjustment of IPF PPS payments. We
did not receive any comments.
e. Adjustment for Rural Location
In the November 2004 IPF PPS final rule, 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 2020,
we are finalizing our proposal to continue to apply a 17 percent
payment adjustment for IPFs located in a rural area as defined at Sec.
412.64(b)(1)(ii)(C). A complete discussion of the adjustment for rural
locations appears in the November 2004 IPF PPS final rule (69 FR
66954).
f. 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 2020, we
are finalizing our proposal to continue 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 2020 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 update to the wage indexes
(based on the FY 2016 hospital cost report data) and the labor-related
share in a budget-neutral manner:
Step 1. Simulate estimated IPF PPS payments, using the FY 2019 IPF
wage index values (available on the CMS website) and labor-related
share (as published in the FY 2019 IPF PPS final rule (83 FR 38579)).
Step 2. Simulate estimated IPF PPS payments using the FY 2020 IPF
wage index values (available on the CMS website) and FY 2020 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 FY 2020 budget-
neutral wage adjustment factor of 1.0026.
Step 4. Apply the FY 2020 budget-neutral wage adjustment factor
from step 3 to the FY 2019 IPF PPS federal per diem base rate after the
application of the market basket update described in section III.A.4 of
this rule, to determine the FY 2020 IPF PPS federal per diem base rate.
2. Teaching Adjustment
In the November 2004 IPF PPS final rule, we implemented regulations
at 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 full-time equivalent (FTE) interns and residents training in
the IPF and the IPF's average daily census (ADC).
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/the IPF's ADC)). The teaching
variable is then raised to 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 later in this section of this 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 (publication date of the IPF PPS final rule). A
complete discussion of the temporary adjustment to the FTE cap to
reflect residents added due to hospital closure and by residency
program 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 is
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 rerun the teaching adjustment factors in
the regression analysis until we more fully analyze IPF PPS data as
part of the IPF PPS refinement we discuss in section IV of this rule.
Therefore, in this FY 2020 final rule, we are finalizing our proposal
to continue to retain the coefficient value of 0.5150 for the teaching
adjustment to the federal per diem base rate.
3. Cost of Living Adjustment 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
[[Page 38456]]
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 would 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 Nonforeign Area Retirement Equity
Assurance Act, as contained in subtitle B of title XIX of the National
Defense Authorization Act (NDAA) for FY 2010 (Pub. L. 111-84, October
28, 2009), 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 think 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 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 2018, the COLA factors were
updated in FY 2018 IPPS/LTCH rulemaking (82 FR 38529). As such, we also
updated the IPF PPS COLA factors for FY 2018 (82 FR 36780 through
36782) to reflect the updated COLA factors finalized in the FY 2018
IPPS/LTCH rulemaking. We are finalizing our proposal to continue to
apply the same COLA factors in FY 2020 that were used in FY 2018 and FY
2019.
Table 16--Comparison of IPF PPS Cost-of-Living Adjustment Factors: IPFs
Located in Alaska and Hawaii
------------------------------------------------------------------------
FY 2015 FY 2018
Area through FY through FY
2017 2020
------------------------------------------------------------------------
Alaska:
City of Anchorage and 80-kilometer 1.23 1.25
(50-mile) radius by road...........
City of Fairbanks and 80-kilometer 1.23 1.25
(50-mile) radius by road...........
City of Juneau and 80-kilometer (50- 1.23 1.25
mile) radius by road...............
Rest of Alaska...................... 1.25 1.25
Hawaii:
City and County of Honolulu......... 1.25 1.25
County of Hawaii.................... 1.19 1.21
County of Kauai..................... 1.25 1.25
County of Maui and County of Kalawao 1.25 1.25
------------------------------------------------------------------------
The IPF PPS COLA factors for FY 2020 are also shown in Addendum A
to this final rule, available at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/InpatientPsychFacilPPS/tools.html.
4. 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
[[Page 38457]]
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 the 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 2020, we are finalizing our proposal to continue 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 factor in
our 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 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 more costly 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 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. Update to the Outlier Fixed Dollar Loss Threshold Amount
In accordance with the update methodology described in Sec.
412.428(d), we updated 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.
Based on an analysis of the latest available data (the March 2019
update of FY 2018 IPF claims) and rate increases, we believe it is
necessary to update the fixed dollar loss threshold amount to maintain
an outlier percentage that equals 2 percent of total estimated IPF PPS
payments. We are updating the IPF outlier threshold amount for FY 2020
using FY 2018 claims data and 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
2019. Based on an analysis of these updated data, we estimate that IPF
outlier payments as a percentage of total estimated payments are
approximately 2.23 percent in FY 2019. Therefore, we are finalizing our
proposal to update the outlier threshold amount to $14,960 to maintain
estimated outlier payments at 2 percent of total estimated aggregate
IPF payments for FY 2020. This final rule update is an increase from
the FY 2019 threshold of $12,865.
We received one comment on our proposed update to the outlier
threshold.
Comment: A commenter was concerned that the 13.4 percent proposed
increase in the outlier threshold was too steep to implement in a
single year, and suggested that when an increase in the outlier
threshold is necessary, it should be limited to no more than 5 percent
in any given year.
Response: The outlier fixed dollar threshold amount is calculated
by simulating aggregate payments and using an iterative process to
determine a threshold that results in outlier payments being equal to 2
percent of total payments under the simulation. To determine the IPF
outlier threshold amount for FY 2020 we estimated the FY 2020 IPF PPS
aggregate and outlier payments using the most recent claims available
(March 2019 update of the FY 2018 MedPAR claims) and the FY 2020 final
payment rates. The outlier threshold was varied in this simulation
until estimated outlier payments equaled 2 percent of estimated
aggregate payments. Based on the regression analysis and payment
simulations used to develop the IPF PPS, we established a 2 percent
outlier policy in our November 2004 IPF PPS final rule (69 FR 66960
through 66962), 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. This outlier fixed dollar loss threshold update methodology is
based on longstanding IPF payment policy and is described in detail in
the RY 2007 IPF PPS final rule (71 FR 27072 and 27073). To continue to
maintain this established 2 percent outlier policy, for this final rule
we must raise the IPF PPS outlier fixed dollar threshold amount from
$12,865 to $14,960. If the fixed dollar threshold amount increase was
limited to 5 percent for FY 2020 as suggested by the commenter we would
not meet the established 2 percent outlier policy. Our IPF PPS outlier
policy limiting outlier payments to a defined percentage of total
payments is
[[Page 38458]]
consistent with the outlier policies in other Medicare payment systems.
3. 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 we 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 available.
For FY 2020, we are finalizing our proposal 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 2020 is 2.0239 for rural IPFs, and 1.7263 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.
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 are finalizing our proposal to continue to update the FY 2020
national median and ceiling CCRs for urban and rural IPFs based on the
CCRs entered in the latest available IPF PPS Provider Specific File.
Specifically, for FY 2020, to be used in each of the three situations
listed previously, using the most recent CCRs entered in the CY 2019
Provider Specific File, we provide an estimated national median CCR of
0.5720 for rural IPFs and a national median CCR of 0.4370 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).
IV. Update on IPF PPS Refinements
For RY 2012, we identified several areas of concern for future
refinement, and we invited comments on these issues in the RY 2012 IPF
PPS proposed and final rules. For further discussion of these issues
and to review the public comments, we refer readers to the RY 2012 IPF
PPS proposed rule (76 FR 4998) and final rule (76 FR 26432).
We have delayed making refinements to the IPF PPS until we have
completed a thorough analysis of IPF PPS data on which to base those
refinements. Specifically, we will delay updating the adjustment
factors derived from the regression analysis until we have IPF PPS data
that include as much information as possible regarding the patient-
level characteristics of the population that each IPF serves. We have
begun and will continue the necessary analysis to better understand IPF
industry practices so that we may refine the IPF PPS in the future, as
appropriate. Our preliminary analysis has also revealed variation in
cost and claim data, particularly related to labor costs, drugs costs,
and laboratory services. Some providers have very low labor costs, or
very low or missing drug or laboratory costs or charges, relative to
other providers. As we noted in the FY 2016 IPF PPS final rule (80 FR
46693 through 46694), our preliminary analysis of 2012 to 2013 IPF data
found that over 20 percent of IPF stays reported no ancillary costs,
such as laboratory and drug costs, in their cost reports, or laboratory
or drug charges on their claims. Because we expect that most patients
requiring hospitalization for active psychiatric treatment will need
drugs and laboratory services, we again remind providers that the IPF
PPS federal per diem base rate includes the cost of all ancillary
services, including drugs and laboratory services.
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 the requirement 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. 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/. CMS suspended the requirement that cost reports from
psychiatric hospitals include certain ancillary costs effective April
27, 2018, in order to consider excluding all-inclusive rate providers
from this requirement. 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.
We only pay 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.
We will continue to analyze data from claims and cost reports that
do not include ancillary charges or costs, and will be sharing our
findings with CMS Office of the Center for Program Integrity and CMS
Office of Financial Management for further investigation, as the
results warrant. Our refinement analysis is dependent on recent precise
data for costs, including ancillary costs. We will continue to collect
these data and analyze them for both timeliness and accuracy with the
expectation that these data will be used in a future refinement. It is
currently our intent to explore refinements to the adjustments in
future rulemaking. Since we did not propose refinements, for FY 2020 we
will continue to use the existing adjustment factors.
[[Page 38459]]
V. Inpatient Psychiatric Facilities Quality Reporting (IPFQR) Program
A. Background and Statutory Authority
We refer readers to the FY 2019 IPF PPS final rule (83 FR 38589)
for a discussion of the background and statutory authority \2\ of the
IPFQR Program.
---------------------------------------------------------------------------
\2\ 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 RY update period would be 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).
---------------------------------------------------------------------------
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 under
Medicare's IPF PPS (Sec. 412.404(b)). Generally, psychiatric hospitals
and psychiatric units within acute care and critical access hospitals
that treat Medicare patients are paid under the IPF PPS. Consistent
with previous regulations, we continue to use the term 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 and Administrative Procedures
The current IPFQR Program includes 13 measures. For more
information on these measures, we refer readers to the following final
rules:
The FY 2013 IPPS/LTCH PPS final rule (77 FR 53646 through
53652);
The FY 2014 IPPS/LTCH PPS final rule (78 FR 50889 through
50897);
The FY 2015 IPF PPS final rule (79 FR 45963 through
45975);
The FY 2016 IPF PPS final rule (80 FR 46695 through
46714);
The FY 2017 IPPS/LTCH PPS final rule (81 FR 57238 through
57247); and
The FY 2019 IPF PPS final rule (83 FR 38590 through
38606).
For more information on previously adopted procedural requirements,
we refer readers to the following rules:
The FY 2013 IPPS/LTCH PPS final rule (77 FR 53653 through
53660);
The FY 2014 IPPS/LTCH PPS final rule (78 FR 50897 through
50903;
The FY 2015 IPF PPS final rule (79 FR 45975 through
45978);
The FY 2016 IPF PPS final rule (80 FR 46715 through
46719);
The FY 2017 IPPS/LTCH PPS final rule (81 FR 57248 through
57249);
The FY 2018 IPPS/LTCH PPS final rule (82 FR 38471 through
38474); and
The FY 2019 IPF PPS final rule (83 FR 38606 through
38608).
D. IPFQR Program Measures
1. Measure Selection Process
Before being proposed for inclusion in the IPFQR Program, measures
are placed on a list of measures under consideration (MUC), which is
published annually by December 1 on behalf of CMS by the National
Quality Forum (NQF). Following publication on the MUC list, the Measure
Applications Partnership (MAP), a multi-stakeholder group convened by
the NQF, reviews the measures under consideration for the IPFQR
Program, among other Federal programs, and provides input on those
measures to the Secretary. We considered the input and recommendations
provided by the MAP in selecting all measures for the IPFQR Program.
Further details concerning the input and recommendations from the MAP
for the measure proposed in the FY 2020 IPF PPS Proposed rule
(Medication Continuation Following Inpatient Psychiatric Discharge, NQF
#3205) are provided in Section V.D.3.
2. Removal or Retention of IPFQR Program Measures
a. Background
In the FY 2018 IPPS/LTCH PPS final rule (82 FR 38463 through
38465), we finalized our proposals to adopt considerations for removing
or retaining measures within the IPFQR Program and criteria for
determining when a measure is ``topped out.'' In the FY 2019 IPF PPS
final rule (83 FR 38591 through 38593), we added one additional measure
removal factor. We are not proposing any changes to these removal
factors, topped-out criteria, or retention factors 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 will continue to retain measures from each previous
year's IPFQR Program measure set for subsequent years' measure sets,
except when we specifically propose to remove or replace a measure. We
will continue to use the notice-and-comment rulemaking process to
propose measures for removal or replacement, as we described upon
adopting these factors in the 2018 IPPS/LTCH PPS final rule (82 FR
38464 through 38465).
b. Application of Considerations for Removal and Retention to Current
Measure Set
In the FY 2018 IPPS/LTCH PPS final rule, we noted that several
commenters requested that we evaluate the current measures in the IPFQR
Program using the removal and retention factors that we finalized in
that rule (82 FR 38464). Following this evaluation, we proposed to
remove eight measures from the IPFQR Program in the FY 2019 IPF PPS
proposed rule (83 FR 21118 through 21123) for the FY 2020 program year
and subsequent years. In the FY 2019 IPF PPS final rule (83 FR 38593
through 38604) we finalized removal of five of these measures. In our
evaluation of the IPFQR Program measure set subsequent to publication
of the FY 2019 IPF PPS final rule, we have not identified additional
measures to which our measure removal factors apply. Therefore, we are
not proposing to remove any additional measures at this time.
The previously finalized number of measures for the FY 2021 payment
determination and subsequent years totals 13.
BILLING CODE 4120-01-P
[[Page 38460]]
[GRAPHIC] [TIFF OMITTED] TR06AU19.014
BILLING CODE 4120-01-C
3. Proposed New Quality Measure for the FY 2021 Payment Determination
and Subsequent Years--Medication Continuation Following Inpatient
Psychiatric Discharge (NQF #3205)
a. Background
Medication continuation is important for patients discharged from
the inpatient psychiatric setting with major depressive disorder (MDD),
schizophrenia, or bipolar disorder because of significant negative
outcomes associated with non-adherence to medication regimens. For
example, patients with MDD who do not remain on prescribed medications
are more likely to have negative health outcomes such as relapse and
readmission, decreased quality of life, and increased healthcare
costs.3 4 Patients with schizophrenia who do not adhere to
their medication regimen are more likely to be hospitalized, use
emergency psychiatric services, be arrested, be victims of crimes, and
consume alcohol or drugs compared to those who adhere
[[Page 38461]]
to their medication regimen.\5\ Patients with bipolar disorder who do
not adhere to their medications have increased suicide risk.\6\ For
these reasons, guidelines from the American Psychiatric Association
(APA) and the Department of Veterans Affairs/Department of Defense (VA/
DoD), which are based on extensive literature, recommend
pharmacotherapy as the primary form of treatment for patients with
these conditions.7 8 9 10 11
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\3\ Geddes JR, Carney SM, Davies C, et al. Relapse prevention
with antidepressant drug treatment in depressive disorders: A
systematic review. Lancet. 2003;361(9358):653-661.
\4\ Glue P, Donovan MR, Kolluri S, Emir B. Metaanalysis of
relapse prevention antidepressant trials in depressive disorders.
The Australian and New Zealand journal of psychiatry.
2010;44(8):697-705.
\5\ Gilmer TP, Dolder CR, Lacro JP, et al. Adherence to
treatment with antipsychotic medication and health care costs among
Medicaid beneficiaries with schizophrenia. The American journal of
psychiatry. 2004;161(4):692-699.
\6\ Gonzalez-Pinto A, Mosquera F, Alonso M, et al. Suicidal risk
in bipolar I disorder patients and adherence to long-term lithium
treatment. Bipolar disorders. 2006;8(5 Pt 2):618-624.
\7\ American Psychiatric Association. (2002). Practice guideline
for the treatment of patients with bipolar disorder, second edition.
Retrieved from: https://psychiatryonline.org/pb/assets/raw/sitewide/practice_guidelines/guidelines/bipolar.pdf.
\8\ American Psychiatric Association. (2010). Practice guideline
for the treatment of patients with major depressive disorder, 3rd
ed. Retrieved from: https://psychiatryonline.org/pb/assets/raw/sitewide/practice_guidelines/guidelines/mdd.pdf.
\9\ American Psychiatric Association. (2010). Practice guideline
for the treatment of patients with schizophrenia: 2nd ed. Retrieved
from: https://psychiatryonline.org/pb/assets/raw/sitewide/practice_guidelines/guidelines/schizophrenia.pdf.
\10\ U.S. Department of Veterans Affairs, & U.S. Department of
Defense. (2016). Management of major depressive disorder (MDD).
Retrieved from: https://www.healthquality.va.gov/guidelines/MH/mdd/VADoDMDDCPGFINAL82916.pdf.
\11\ U.S. Department of Veterans Affairs & U.S. Department of
Defense. (2010) VA/DOD clinical practice guideline for management of
bipolar disorder in adults. Retrieved from: https://www.healthquality.va.gov/guidelines/MH/bd/bd_305_full.pdf.
---------------------------------------------------------------------------
Furthermore, we believe that there are factors external to the IPF
that influence filling prescriptions post-discharge in the psychiatric
population. While it may not be possible to achieve complete post-
discharge compliance with pharmacotherapy, there is evidence that
improvements to the quality of care provided by IPFs, including
discharge processes, can help to increase medication continuation
rates.12 13 14 15 16 These interventions include patient
education, enhanced therapeutic relationships, shared decision-making,
and text-message reminders, with multidimensional approaches resulting
in the best outcomes.
---------------------------------------------------------------------------
\12\ Haddad PM, Brain C, Scott J. Nonadherence with
antipsychotic medication in schizophrenia: challenges and management
strategies. Patient related outcome measures. 2014;5:43-62.
\13\ Hung CI. Factors predicting adherence to antidepressant
treatment. Current opinion in psychiatry. 2014;27(5):344-349.
\14\ Lanouette NM, Folsom DP, Sciolla A, Jeste DV. Psychotropic
medication nonadherence among United States Latinos: a comprehensive
literature review. Psychiatric services (Washington, DC).
2009;60(2):157-174.
\15\ Mitchell AJ. Understanding Medication Discontinuation in
Depression. BMedSci Psychiatric Times. 2007;24(4).
\16\ Sylvia LG, Hay A, Ostacher MJ, et al. Association between
therapeutic alliance, care satisfaction, and pharmacological
adherence in bipolar disorder. Journal of clinical
psychopharmacology. 2013;33(3):343-350.
---------------------------------------------------------------------------
We proposed to adopt the Medication Continuation Following
Inpatient Psychiatric Discharge measure (NQF #3205) for the FY 2020
payment determination and subsequent years in the FY 2018 IPPS/LTCH PPS
proposed rule (82 FR 20122 through 20126) to address this important
clinical topic. In the FY 2018 IPPS/LTCH PPS final rule (82 FR 38465
through 38470), we did not finalize adoption of the Medication
Continuation Following Inpatient Psychiatric Discharge measure (NQF
#3205), because we recognized that this measure may place undue burden
on facilities that were updating processes to account for previously
adopted measures despite being calculated from claims data, which
should not require additional information collection burden. We did not
want to place undue burden on facilities, especially small, rural
facilities, and we wished to accommodate the need for facilities to
develop and implement innovative efforts, such as updating their
processes and clinical workflows, for this measure.
At that time, we stated that we would consider proposing this
measure again in future rulemaking. We note that since the FY 2018
IPPS/LTCH PPS final rule, we have removed five measures from the IPFQR
Program (83 FR 38593 through 38602), reducing burden on IPFs by
approximately 546,000 hours and $20 million (83 FR38610 through 38611),
and IPFs have had an additional 2 years to familiarize themselves with
the remaining IPFQR Program measure set and to update processes and
clinical workflows accordingly. Therefore, we believe that it is now
appropriate to propose this measure for the IPFQR Program again.
Since the FY 2018 IPPS/LTCH PPS final rule, we have not made any
changes to the Medication Continuation Following Inpatient Psychiatric
Discharge (NQF #3205) measure's specifications. However, we have taken
steps to improve upon the suitability of this measure for the IPFQR
Program. First, we considered recommendations and comments received on
the Medication Continuation Following Inpatient Psychiatric Discharge
(NQF #3205) measure from the FY 2018 IPPS/LTCH PPS final rule (82 FR
38468 through 38470). We provide more detail about these comments.
Second, since the FY 2018 IPPS/LTCH PPS final rule, we have
provided additional information about this measure to the MAP and to
the NQF, including reliability and validity testing. The measure was
subsequently endorsed by NQF. We continue to believe that this measure
evaluates a process with a demonstrated quality gap, because in testing
this measure, we found that the range of performance between the 10th
percentile and the 80th percentile facility performance was between 67
percent and 88 percent. We found that if all facilities had at least
the median rate then 16,000 additional Medicare beneficiaries would
fill prescriptions for an evidence-based medication to manage their
condition following discharge.\17\ Furthermore, we believe this measure
has the potential to benefit patients by encouraging facilities to
adopt interventions to improve post discharge medication continuation
rates with no additional reporting burden to IPFs.
---------------------------------------------------------------------------
\17\ https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HospitalQualityInits/Downloads/Version_1-0_Inpatient_Psychiatric_Facility_Medication_Continuation_Public.zip.
---------------------------------------------------------------------------
In response to our proposal in the FY 2018 IPPS/LTCH PPS proposed
rule, many comments focused on the potential undue burden of the
measure given the fact that many facilities were still updating
processes to account for previously adopted measures (82 FR 38469).
Between the FY 2018 IPPS/LTCH PPS final rule and this proposed rule, we
have not adopted any new measures into the program. We believe that
IPFs no longer need to update processes to account for previously
adopted measures because they have had 2 years to complete all such
updates. Therefore, we believe that there is less burden associated
with the IPFQR program than when we proposed to adopt this measure in
the FY 2018 IPPS/LTCH PPS proposed rule.
Some commenters also expressed concern that patients may experience
barriers to filling prescriptions that are beyond the control of IPFs
(82 FR 38469 through 38470). While we believe that there are factors
external to an IPF that influence filling prescriptions after a patient
is discharged, as the methodology report for the measure indicates,\18\
IPFs can also undertake interventions to improve the likelihood of a
patient's medication continuation post-discharge.
---------------------------------------------------------------------------
\18\ https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HospitalQualityInits/Downloads/Version_1-0_Inpatient_Psychiatric_Facility_Medication_Continuation_Public.zip
---------------------------------------------------------------------------
In response to comments that the affected population may be too
small to
[[Page 38462]]
report meaningful data because it is limited to Medicare patients
enrolled in Parts A, B, and D (82 FR 38469 through 38470), we note that
the NQF found this measure to be valid and reliable,\19\ indicating
that the size of the population is sufficient to report meaningful
data. These commenters additionally expressed that because the measure
is limited to Medicare patients enrolled in Parts A, B, and D, there
may not be a performance gap because these patients do not experience
the same access barriers as other inpatient psychiatric populations.
However, we note that in their endorsement review of the measure, the
NQF found that there was evidence of a performance gap in the quality
area that was addressed by the measure even though the measure is
limited to patients enrolled in Medicare A, B, and D.\20\
---------------------------------------------------------------------------
\19\ https://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=85831.
\20\ https://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=85831.
---------------------------------------------------------------------------
Finally, in response to comments that the measure had not completed
full endorsement review by NQF (82 FR 38469), the measure is now fully
endorsed by the NQF as discussed in more detail in Section B of this
rule. Further, in its review of the measure for endorsement, the NQF
standing committee agreed that there is evidence that lack of adherence
to medication leads to relapse and negative outcomes and that claims
data related to medication adherence are directly correlated to
outcomes.\21\
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\21\ https://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=85831
---------------------------------------------------------------------------
b. Overview of Measure
The Medication Continuation Following Inpatient Psychiatric
Discharge measure (NQF #3205) assesses whether patients admitted to
IPFs with diagnoses of MDD, schizophrenia, or bipolar disorder filled
at least one evidence-based medication prior to discharge or during the
post-discharge period. As detailed in the following discussion, the NQF
endorsed this measure on June 28, 2017. For more information about this
measure, we refer readers to the measure specifications in the measure
technical report https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HospitalQualityInits/Downloads/Version_1-0_Inpatient_Psychiatric_Facility_Medication_Continuation_Public.zip) or the measure's NQF page (https://www.qualityforum.org/QPS/3205).
In compliance with section 1890A(a)(2) of the Act, this measure was
included in a publicly available document: ``List of Measures under
Consideration for December 1, 2016'' (https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/QualityMeasures/Downloads/Measures-under-Consideration-List-for-2016.pdf). The MAP
Hospital Workgroup concluded in its December 2016 meeting that the
measure addressed a critical quality objective, was evidence-based, and
would contribute to efficient use of resources.\22\ One Workgroup
member commented that it was appropriate to hold IPFs accountable for
patients filling a prescription for an evidence-based medication post-
discharge.
---------------------------------------------------------------------------
\22\ MAP Hospital Workgroup, Preliminary Analysis Worksheet.
December 2016. https://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=84199.
---------------------------------------------------------------------------
The MAP Hospital Workgroup classified the measure as ``Refine and
Resubmit Prior to Rulemaking.'' \23\ The measure received this
classification because the MAP recommended that measure testing be
completed to demonstrate reliability and validity at the facility level
in the hospital setting and that the measure be submitted to NQF for
review and endorsement.\24\ The MAP also requested additional details
on the measure, such as: (1) The definition of medication dispensation;
(2) how the facility would know whether the medication was dispensed;
and (3) how the measure would be impacted if Medicare Part D coverage
is optional.\25\ The methodology report for the measure (https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/QualityMeasures/Downloads/Measures-under-Consideration-List-for-2016.pdf) that we finalized, includes the results of
reliability and validity testing, and additional measure updates that
occurred after the MAP review. This newest methodology report also
provides the additional details requested by the MAP at the December
2016 meeting. This includes the specific medication list, which is
based on APA and VA/DoD practice guidelines for each medication
26 27 28 29 30 and information about how facilities can help
patients fill prescriptions for medications to ensure that the facility
knows that the prescription has been filled. Additionally, the
methodology report provides details about measure performance among
patients with Part D and the performance gap for this patient
population.
---------------------------------------------------------------------------
\23\ https://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=84452.
\24\ https://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=84452.
\25\ https://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=84452.
\26\ American Psychiatric Association. (2010). Practice
guideline for the treatment of patients with major depressive
disorder, 3rd ed. Retrieved from: https://psychiatryonline.org/pb/assets/raw/sitewide/practice_guidelines/guidelines/mdd.pdf.
\27\ American Psychiatric Association. (2002). Practice
guideline for the treatment of patients with bipolar disorder,
second edition. Retrieved from: https://psychiatryonline.org/pb/assets/raw/sitewide/practice_guidelines/guidelines/bipolar.pdf.
\28\ American Psychiatric Association. (2010). Practice
guideline for the treatment of patients with schizophrenia: 2nd ed.
Retrieved from: https://psychiatryonline.org/pb/assets/raw/sitewide/practice_guidelines/guidelines/schizophrenia.pdf.
\29\ U.S. Department of Veterans Affairs & U.S. Department of
Defense. (2016). Management of major depressive disorder (MDD).
Retrieved from: https://www.healthquality.va.gov/guidelines/MH/mdd/VADoDMDDCPGFINAL82916.pdf.
\30\ U.S. Department of Veterans Affairs & U.S. Department of
Defense. (2010) VA/DOD clinical practice guideline for management of
bipolar disorder in adults. Retrieved from: https://www.healthquality.va.gov/guidelines/MH/bd/bd_305_full.pdf.
---------------------------------------------------------------------------
This measure was submitted to NQF for endorsement on December 16,
2016. Consistent with the recommendation from the December 2016 MAP
meeting that testing for reliability and validity should be completed,
in Spring 2017 we refined our NQF submission by providing the complete
results of all testing for NQF's review of the measure for endorsement.
The measure received NQF endorsement on June 28, 2017.\31\
---------------------------------------------------------------------------
\31\ https://www.qualityforum.org/QPS/3205.
---------------------------------------------------------------------------
This measure supports the CMS Meaningful Measure Area ``promote
effective prevention and treatment of chronic disease,'' which includes
the meaningful measure area of ``prevention, treatment, and management
of mental health.'' The measure would also complement the portfolio of
facility-level measures in the IPFQR Program that assess the transition
from the inpatient to outpatient setting: Follow-Up After
Hospitalization for Mental Illness; Thirty-day All Cause Unplanned
Readmission Following Psychiatric Hospitalization in an Inpatient
Psychiatric Facility; Transition Record with Specified Elements
Received by Discharged Patients; and Timely Transmission of Transition
Record.
c. Data Sources
The proposed Medication Continuation Following Inpatient
Psychiatric Discharge measure (NQF #3205) uses Medicare fee-for-service
(FFS) claims to identify whether patients admitted to IPFs with
diagnoses of MDD, schizophrenia, or bipolar disorder filled at least
one evidence-based medication such that they would have medication for
use post-discharge. The performance period for this measure is 24
months. For example, for
[[Page 38463]]
the FY 2021 payment determination, the performance period will include
discharges between July 1, 2017 and June 30, 2019.\32\
---------------------------------------------------------------------------
\32\ If data availability or operational issues prevent use of
this performance period, we would announce the updated performance
period through sub-regulatory communications including announcement
on a CMS website and/or on our applicable listservs.
---------------------------------------------------------------------------
d. Measure Calculation
The numerator for the measure includes discharges for patients with
a principal diagnosis of MDD, schizophrenia, or bipolar disorder in the
denominator who were dispensed at least one evidence-based outpatient
medication within 2 days prior to discharge through 30 days post-
discharge. The denominator for the measure includes Medicare fee-for-
service (FFS) beneficiaries with Part D coverage aged 18 years and
older discharged to home or home health care from an IPF with a
principal diagnosis of MDD, schizophrenia, or bipolar disorder. The
denominator excludes discharges for patients who:
Received Electroconvulsive Therapy (ECT) during the
inpatient stay or 30 day post-discharge period;
Received Transcranial Magnetic Stimulation (TMS) during
the inpatient stay or follow-up;
Were pregnant during the inpatient stay;
Had a secondary diagnosis of delirium; or
Had a principal diagnosis of schizophrenia with a
secondary diagnosis of dementia.
For more information about the development of the measure,
including rationale for the 2 day prior to 30 day post-discharge period
and the denominator exclusions, we refer readers to the measure
technical report (https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HospitalQualityInits/Downloads/Version1-0_Inpatient_Psychiatric_Facility_Medication_Continuation_Public.zip).
We invited public comment on our proposal to adopt the Medication
Continuation Following Inpatient Psychiatric Discharge (NQF #3205)
measure for the FY 2021 payment determination and subsequent years as
discussed.
Comment: Several commenters expressed support for the Medication
Continuation Following Inpatient Psychiatric Discharge (NQF #3205)
measure specifically noting that it is an NQF-endorsed measure that
addresses an important clinical topic with a demonstrated quality gap.
Several of these commenters noted that the measure will help facilities
identify interventions for post-discharge medication compliance,
thereby improving care transitions. Some commenters further expressed
that the measure aligns with the goal of not increasing provider
burden.
Response: We thank these commenters for their support.
Comment: Some commenters recommended that CMS not adopt the
Medication Continuation Following Inpatient Psychiatric Discharge (NQF
#3205) measure because this measure imposes burden on facilities.
Response: We do not believe that this measure imposes any data
reporting burden on facilities because it is calculated by CMS using
data submitted on Medicare Parts A, B, and D claims. We acknowledge
that to improve performance on this measure there may be costs or
burden associated with updating clinical workflows to improve discharge
planning and counseling on the importance of medication continuation.
However, because of the severity of the negative health outcomes
associated with medication discontinuation for this patient population,
we believe that these updates are part of providing high quality
inpatient psychiatric care.
Comment: Some commenters recommended that CMS not adopt Medication
Continuation Following Inpatient Psychiatric Discharge (NQF #3205)
because they believe that restricting the denominator to patients who
have Medicare Parts A, B, and D coverage makes the population size too
small to be meaningful.
Response: During measure testing, the denominator was restricted to
patients who have Medicare Parts A, B, and D coverage during measure
testing and results showed that the majority of providers met the 75
case minimum threshold required to obtain an overall reliability score
of at least 0.7, which is the minimum acceptable reliability rating.
Furthermore, the NQF standing committee evaluated this when considering
the measure for endorsement and determined that the measure meets their
scientific acceptability criteria.\33\
---------------------------------------------------------------------------
\33\ https://www.qualityforum.org/Projects/a-b/Behavioral_Health_2016-2017/Draft_Report_for_Comment.aspx.
---------------------------------------------------------------------------
Comment: Some commenters recommended that CMS not adopt this
measure because they believe that the measure assesses patient behavior
(that is, filling prescriptions) as opposed to provider quality and
therefore does not produce data that will help consumers select
facilities.
Response: We recognize that there are factors external to the IPF
that influence filling prescriptions post-discharge in the psychiatric
population. While it may not be possible to achieve complete post-
discharge compliance with pharmacotherapy, there is evidence that
improvements to the quality of care for patients in the IPF setting,
including the discharge processes, can help to increase medication
continuation rates.34 35 36 37 38 These interventions
include patient education, enhanced therapeutic relationships, shared
decision-making, and text-message reminders, with multidimensional
approaches resulting in the best outcomes. We note that in testing the
measure, the measure developer found a median score of 79.6% and an
approximate 21-percentage point difference between the 10th and 90th
percentiles. This means that in the 10th percentile facilities,
depending on their condition, 60.0 to 63.9 percent of patients (with
Medicare Parts A, B, and D) fill prescriptions for evidence-based
medications, whereas in the 90th percentile facilities 89.7 to 95.5
percent of such patients fill prescriptions for evidence-based
medications.\39\ We believe that this performance gap, coupled with the
ability of facilities to provide interventions to improve medication
continuation, indicate that the measure does provide meaningful
information about the quality of care provided to patients.
---------------------------------------------------------------------------
\34\ Haddad PM, Brain C, Scott J. Nonadherence with
antipsychotic medication in schizophrenia: challenges and management
strategies. Patient related outcome measures. 2014;5:43-62.
\35\ Hung CI. Factors predicting adherence to antidepressant
treatment. Current opinion in psychiatry. 2014;27(5):344-349.
\36\ Lanouette NM, Folsom DP, Sciolla A, Jeste DV. Psychotropic
medication nonadherence among United States Latinos: a comprehensive
literature review. Psychiatric services (Washington, DC).
2009;60(2):157-174.
\37\ Mitchell AJ. Understanding Medication Discontinuation in
Depression. BMedSci Psychiatric Times. 2007;24(4).
\38\ Sylvia LG, Hay A, Ostacher MJ, et al. Association between
therapeutic alliance, care satisfaction, and pharmacological
adherence in bipolar disorder. Journal of clinical
psychopharmacology. 2013;33(3):343-350.
\39\ https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HospitalQualityInits/Downloads/Version_1-0_Inpatient_Psychiatric_Facility_Medication_Continuation_Public.zip.
---------------------------------------------------------------------------
Comment: Several commenters recommended that CMS not adopt the
Medication Continuation Following Inpatient Discharge (NQF #3205)
measure because these commenters believe prescription fills do not
actually reflect medication adherence.
[[Page 38464]]
Response: While we agree with commenters that it is possible that
patients may fill prescriptions and then not take the medication, or
take it incorrectly, we believe that the measure is a good indicator of
patient adherence to medication regimens. The NQF Standing Committee
for Behavioral Health evaluated the potential for patients to fill
their prescriptions but not be adherent to the medication regimen
during their review of the measure and found that most studies related
to adverse events for medication non-compliance used the filling of a
prescription as a proxy for medication adherence,\40\ which aligns with
this measure's methodology.
---------------------------------------------------------------------------
\40\ https://www.qualityforum.org/Projects/a-b/Behavioral_Health_2016-2017/Draft_Report_for_Comment.asp.
---------------------------------------------------------------------------
Comment: One commenter recommended that CMS not adopt this measure
because facilities cannot internally track performance on this measure
and therefore cannot identify performance gaps that require
interventions.
Response: We believe that this measure will help facilities
identify performance gaps that require interventions by making this
data available to facilities. We also note that the American
Psychiatric Association's (APA's) and Department of Veterans Affairs
and Department of Defense (VA/DoD) practice guidelines for depressive
disorder, bipolar disorder, and schizophrenia provide strategies for
facilities to implement to help patients fill prescriptions prior to
discharge so that the facility can track whether the prescription has
been filled.41 42 43 44 45
---------------------------------------------------------------------------
\41\ American Psychiatric Association. (2010). Practice
guideline for the treatment of patients with major depressive
disorder, 3rd ed. Retrieved from: https://psychiatryonline.org/pb/assets/raw/sitewide/practice_guidelines/guidelines/mdd.pdf.
\42\ American Psychiatric Association. (2002). Practice
guideline for the treatment of patients with bipolar disorder,
second edition. Retrieved from: https://psychiatryonline.org/pb/assets/raw/sitewide/practice_guidelines/guidelines/bipolar.pdf.
\43\ American Psychiatric Association. (2010). Practice
guideline for the treatment of patients with schizophrenia: 2nd ed.
Retrieved from: https://psychiatryonline.org/pb/assets/raw/sitewide/practice_guidelines/guidelines/schizophrenia.pdf.
\44\ U.S. Department of Veterans Affairs & U.S. Department of
Defense. (2016). Management of major depressive disorder (MDD).
Retrieved from: https://www.healthquality.va.gov/guidelines/MH/mdd/VADoDMDDCPGFINAL82916.pdf.
\45\ U.S. Department of Veterans Affairs & U.S. Department of
Defense. (2010) VA/DOD clinical practice guideline for management of
bipolar disorder in adults. Retrieved from: https://www.healthquality.va.gov/guidelines/MH/bd/bd_305_full.pdf.
---------------------------------------------------------------------------
Comment: Several commenters expressed the belief that this measure
is not appropriate for the inpatient psychiatric setting and suggested
that this or a similar measure be considered for the outpatient setting
instead because these commenters believe that outpatient providers have
more influence on patients' post-discharge care.
Response: We agree with the commenters that outpatient providers do
have more influence on a patient's post-discharge care in the long
term; however this measure is specified to address the short term
period immediately following discharge from the IPF prior to the
patient's follow-up with an outpatient provider (which, according to
data collected through the Follow-Up After Hospitalization for Mental
Illness (NQF #0576) measure, will be more than 30 days post-discharge
nearly half of all patients).\46\ Therefore, we do not agree that this
measure would be more appropriate for the outpatient setting. This
measure addresses care provided during the discharge planning phase of
care, which occurs within the IPF to facilitate a safe care transition
until the patient can be seen by an outpatient provider. We note that
the period immediately following discharge from a psychiatric hospital
is a high-risk period for patients, and has been linked to an increased
risk of adverse outcomes, including suicide.47 48 We believe
it is vital that patients have continuity of pharmacotherapy consistent
with the prescriptions provided by their inpatient providers until they
can develop a long-term care plan with their outpatient providers
---------------------------------------------------------------------------
\46\ https://www.medicare.gov/hospitalcompare/psych-measures.html.
\47\ https://www.ncbi.nlm.nih.gov/pubmed/27654151.
\48\ https://psychnews.psychiatryonline.org/doi/full/10.1176/appi.pn.2017.7a17.
---------------------------------------------------------------------------
Comment: One commenter expressed concern that because this
measure's patient population has Medicare Parts A, B, and D coverage,
these patients do not experience the same barriers to access
experienced by patients without similar health insurance coverage and
therefore the measure may not provide meaningful data.
Response: We agree that the patients included in the measure may
not experience the same barriers to access to medications that some
other patients encounter because they have insurance and low-income
Medicare patients qualify for additional support to help pay for
medications. However, as previously noted, in the measure technical
report,\49\ the claims data used for analysis and testing of this
measure demonstrated ample opportunity for improvement in medication
continuation rates for patients with Medicare Parts A, B, and D, with
median medication continuation rates of 79% and a variation of 21
percentage points between the 10th and 90th percentile facilities.
Further, considering that the Medicare population may have lower
barriers to access, we would expect to see higher medication
continuation rates and less variation in performance across facilities.
---------------------------------------------------------------------------
\49\ https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HospitalQualityInits/Downloads/Version_1-0_Inpatient_Psychiatric_Facility_Medication_Continuation_Public.zip.
---------------------------------------------------------------------------
In addition, we note that while the measure denominator includes
only patients with Medicare Parts A, B, and D, all patients can benefit
from the evidence-based interventions that facilities may implement to
improve medication adherence.
Comment: One commenter requested clarification of how CMS will
assess prescription refills for patients who do not have Part D.
Response: We note that the denominator of this measure is
restricted to patients who have Medicare Parts A, B, and D coverage.
Therefore, we will not assess prescription refills for patients who do
not have Part D coverage because they are not in the measure's patient
population.
Comment: One commenter expressed concern that the measure will not
capture medication continuity for patients who filled 90-day supplies
prior to admission.
Response: During measure testing, we found that the number of
patients who filled a 90-day prescription in the 90 days prior to
admission was small. Specifically, 5.5 percent of those with major
depressive disorder had a 90-day prescription at some point in the 90
days prior to admission, 2.8 percent of those with bipolar disorder had
such a prescription, and 1.2 percent of those with schizophrenia had
such a prescription. Furthermore, we believe that medications are often
adjusted during the inpatient stay, and patients may need to fill a new
prescription following discharge even if they have medications at home.
Therefore, we believe that the patient population with appropriate
pharmacotherapy due to 90-day prescriptions prior to admission is very
small and does not necessitate any changes to the measure
specifications.
Comment: One commenter expressed concern that 2 days prior to
discharge is too brief a period and recommended expanding the period to
5 days prior to discharge.
Response: When we developed and tested this measure, we found that
most
[[Page 38465]]
outpatient medications filled during the inpatient stay are filled one
day prior to discharge.\50\ In consulting with clinical experts, we
found that discharge planning, including filling prescriptions, could
start as early as two days prior to discharge. These experts
unanimously agreed to extend the follow-up period to include two days
prior to discharge.\51\ Because most medications filled during the stay
are filled one day prior to discharge and discharge planning typically
starts two days prior to discharge we believe that this measure period
is appropriate.
---------------------------------------------------------------------------
\50\ https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HospitalQualityInits/Downloads/Version_1-0_Inpatient_Psychiatric_Facility_Medication_Continuation_Public.zip.
\51\ Ibid.
---------------------------------------------------------------------------
Comment: Several commenters requested clarification of whether the
data would be publicly reported annually or every two years because the
measure has a two year performance period. These commenters further
expressed concern that if data is reported annually the data may
misrepresent facilities with recent improvement.
Response: The IPFQR Program publicly displays all measure data
annually (78 FR 50897 through 50898 and 81 FR 57248 through 57249). For
this measure we will post the data annually using a two-year
performance period, similar to our reporting of the Thirty-Day All-
Cause Unplanned Readmission Following Psychiatric Hospitalization in an
Inpatient Psychiatric Facility (NQF #2860) measure. As an example, for
both measures the intended performance period for FY 2021 reporting is
July 1, 2017 through June 30, 2019. For FY 2022 reporting the
performance period is July 1, 2018 through June 30, 2020. We note that
these periods do overlap; however we believe that facilities with
recent improvement will be distinguishable because their scores will
show year-over-year improvement.
Comment: One commenter expressed concern that facilities without
outpatient pharmacies may be at a performance disadvantage because they
cannot ensure that patients fill prescriptions prior to discharge.
Response: We believe that many of the interventions to improve
performance on this measure (for example, patient education at
discharge, therapeutic alliance, text message reminders, etc.) are
applicable to all facilities, regardless of whether they have an
outpatient pharmacy on premises. Furthermore, we note that the practice
guidelines for these conditions provide strategies for facilities to
implement to help patients fill prescriptions prior to discharge so
that the facility can track whether the prescription has been
filled.52 53 54 55 56
---------------------------------------------------------------------------
\52\ American Psychiatric Association. (2010). Practice
guideline for the treatment of patients with major depressive
disorder, 3rd ed. Retrieved from: https://psychiatryonline.org/pb/assets/raw/sitewide/practice_guidelines/guidelines/mdd.pdf.
\53\ American Psychiatric Association. (2002). Practice
guideline for the treatment of patients with bipolar disorder,
second edition. Retrieved from: https://psychiatryonline.org/pb/assets/raw/sitewide/practice_guidelines/guidelines/bipolar.pdf.
\54\ American Psychiatric Association. (2010). Practice
guideline for the treatment of patients with schizophrenia: 2nd ed.
Retrieved from: https://psychiatryonline.org/pb/assets/raw/sitewide/practice_guidelines/guidelines/schizophrenia.pdf.
\55\ U.S. Department of Veterans Affairs & U.S. Department of
Defense. (2016). Management of major depressive disorder (MDD).
Retrieved from: https://www.healthquality.va.gov/guidelines/MH/mdd/VADoDMDDCPGFINAL82916.pdf.
\56\ U.S. Department of Veterans Affairs & U.S. Department of
Defense. (2010) VA/DOD clinical practice guideline for management of
bipolar disorder in adults. Retrieved from: https://www.healthquality.va.gov/guidelines/MH/bd/bd_305_full.pdf.
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Comment: One commenter requested that CMS provide guidance on what
medications are considered evidence-based medications for these
conditions.
Response: The measure technical report available at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HospitalQualityInits/Downloads/Version_1-0_Inpatient_Psychiatric_Facility_Medication_Continuation_Public.zip has
a detailed list of medications for each condition. As part of routine
measure maintenance, we will evaluate and update this list on a
recurrent basis.
Final Rule Action: After consideration of the public comments, we
are finalizing as proposed the adoption of the Medication Continuation
Following Inpatient Psychiatric Discharge (NQF #3205) measure for the
FY 2021 payment determination and subsequent years.
4. Summary of Previously Finalized and Newly Proposed Measures for the
FY 2021 Payment Determination and Subsequent Years
The previously finalized number of measures for the FY 2021 payment
determination and subsequent years totals 13. In this final rule, we
are adopting one additional measure for the FY 2021 payment
determination and subsequent years which, brings the total to 14, as
shown in table 18.
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5. Possible IPFQR Program Measures and Topics for Future Consideration
As we have previously indicated in the FY 2015 IPF PPS final rule
(79 FR 45974 through 45975), we seek to develop a comprehensive set of
quality measures to be available for widespread use for informed
decision-making and quality improvement in the IPF setting. In the FY
2020 IPF PPS proposed rule, we sought public comments on possible new
measures or new measure topics. We welcomed all comments but expressed
particular interest in comments on future adoption of one or more
measures of patient experience of care based on a consumer survey,
especially such as the Hospital Consumer Assessment of Healthcare
Providers and Systems (HCAHPS) Survey, and potential future measures
and topics as part of CMS' Meaningful Measures Framework.
[[Page 38467]]
a. Future Adoption a Patient Experience of Care Survey
In past assessments of the IPFQR Program Measure Set, we identified
Patient Experience of Care as a measure gap area for this program (78
FR 50897, 79 FR 45964 through 45965, and 83 FR 38596 through 38597),
which is consistent with input from past public comment (77 FR 53653).
When we adopted the ``Assessment of Patient Experience of Care
Measure'' for the FY 2016 payment determination and subsequent years,
we noted that in addition to serving as an indicator of quality within
IPFs, information gathered through the collection of this measure would
be helpful in developing a standardized survey as a successor to the
measure (79 FR 45964). When we removed the Assessment of Patient
Experience of Care measure from the IPFQR Program, we stated we believe
that we have now collected sufficient information to inform development
of a patient experience of care measure (83 FR 38596).
At that time, several commenters expressed support for ensuring
that patients have an opportunity to express their perspectives on
their experience of receiving care at an IPF (83 FR 38597). Our
analysis of the FY 2018 payment determination data (that is, data that
represents facility assessment of patient experience of care as of
December 31, 2016) collected under the Assessment of Patient Experience
of Care measure shows that approximately one third of facilities use
the Hospital Consumer Assessment of Healthcare Providers and Systems
(HCAHPS) survey \57\ to assess patient experience of care. This is more
than the portion of facilities using any other survey.
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\57\ For more information about the HCAHPS survey, please see
https://www.ahrq.gov/cahps/surveys-guidance/hospital/about/adult_hp_survey.html.
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We sought public comment on how such providers have implemented the
survey in their facilities, on whether they use the entire HCAHPS
survey, or a subset of the survey questions; and if a subset, which
specific questions they use. Additionally, we sought public comment on
other potential surveys that commenters believe would be appropriate to
adopt for the IPFQR Program. We intend to use this information to
inform future development and testing of a survey-based patient
experience of care measure (or measures) for the inpatient psychiatric
patient population.
Comment: Many commenters supported future adoption of a patient
experience of care survey. Several of these commenters expressed
concern about the potential adoption of the HCAHPS survey for this
patient population, specifically noting that this survey does not
include some of the unique aspects of inpatient psychiatric care
including group therapy, non-physician providers, and involuntary
admissions. Some commenters observed that while most IPFs use a patient
experience of care survey, there is not one survey used predominantly
across settings and recommended that CMS partner with providers to
either develop a minimally burdensome survey or to establish a core set
of questions that should be included, therefore allowing provider
flexibility to ask additional questions. These commenters believe that
a custom developed survey would better address the needs of the patient
population and would be preferable for providers than having to switch
from a setting specific survey to a survey not designed for this
setting. One commenter recommended that adoption of a patient
experience of care measure should be done incrementally through a
voluntary data collection period to ensure feasibility of collection
prior to mandatory data submission. Several commenters also noted that
the HCAHPS survey modalities (phone or mail post-discharge) may limit
participation and recommended additional survey modalities for this
potentially more transient patient population. One commenter expressed
concern that a patient experience of care measure could be
misinterpreted as the current state of care when the data has been
collected in the past.
Response: We thank these commenters for their input and will
consider these suggestions and concerns as we seek to develop or select
an appropriate patient experience of care survey for the IPF setting.
b. Other Future Measures
In the FY 2020 IPF PPS proposed rule, we also sought feedback and
suggestions for future measures and topics for the IPFQR Program that
align with CMS's Meaningful Measures Framework (FY 2019 IPF PPS final
rule, 83 FR 38590 through 38591).
Comment: One commenter recommended that CMS collaborate with
providers to identify measure concepts and develop measures appropriate
to the setting. Several commenters provided recommendations for future
measure considerations; specifically measures that assess:
Facility use of a standardized assessment of patient
outcomes between admission and discharge;
Family and caregiver engagement;
Clinical improvement outcomes;
Patient empowerment;
Safety planning for patients with suicidal ideation;
Discharge and transitions of care;
Access to care; and
Inpatient assaults and violence.
Response: We thank these commenters for their suggestions and will
consider these concepts as we continue to develop a measure set that
meets the specific needs of IPFs and inpatient psychiatric patients and
their families.
E. Public Display and Review Requirements
We refer readers to the FY 2013 IPPS/LTCH PPS final rule (77 FR
53653 through 53654), 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) for discussion of our previously finalized public
display and review requirements. We did not propose any changes to
these requirements.
F. Form, Manner, and Timing of Quality Data Submission for the FY 2021
Payment Determination and Subsequent Years
1. Procedural Requirements for the FY 2021 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), and the FY 2018 IPPS/LTCH PPS final rule (82 FR 38471
through 38472) for our previously finalized procedural requirements. In
the FY 2020 IPF PPS proposed rule, we did not propose any changes to
these policies.
2. Data Submission Requirements for the FY 2021 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), and the FY 2018 IPPS/LTCH PPS final rule (82 FR 38472
through 38473) for our previously finalized data submission
requirements.
Because the Medication Continuation following Discharge from an IPF
(NQF #3205) measure is calculated by CMS using Medicare Fee-for-Service
claims, there will be no additional data submission requirements for
the FY 2021 payment determination and subsequent years. Therefore, in
the FY 2020 IPF PPS proposed rule, we did not propose any changes to
our previously finalized data submission policies.
[[Page 38468]]
3. Reporting Requirements for the FY 2021 Payment Determination and
Subsequent Years
We refer readers to the FY 2013 IPPS/LTCH PPS final rule (77 FR
53656 through 53657), the FY 2014 IPPS/LTCH PPS final rule (78 FR 50900
through 50901), and the FY 2015 IPF PPS final rule (79 FR 45976 through
45977) for our previously finalized reporting requirements. In the FY
2020 IPF PPS proposed rule, we did not propose any changes to these
policies.
4. 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)
discussions for our previously finalized sampling policies. In the FY
2020 IPF PPS proposed rule, we did not propose any changes to these
policies.
5. 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. In the FY 2020 IPF PPS proposed rule, we did not
propose any changes to these policies.
6. Data 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. In the FY 2020
IPF PPS proposed rule, we did not propose any changes to these
policies.
G. Reconsideration and Appeals Procedures
We refer readers to the FY 2013 IPPS/LTCH PPS final rule (77 FR
53658 through 53659) and the FY 2014 IPPS/LTCH PPS final rule (78 FR
50903) for our previously finalized reconsideration and appeals
procedures. In the FY 2020 IPF PPS proposed rule, we did not propose
any changes to these policies.
H. 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 ECE policies. In the FY 2020 IPF PPS proposed rule, we did
not propose any changes to these policies.
VI. Collection of Information Requirements
The FY 2020 IPF PPS proposed rule did not propose any new or
revised ``collection of information'' requirements as defined under 5
CFR 1320.3 the Paperwork Reduction Act's (PRA) implementing
regulations. Nor did it contain any proposals that would have imposed
any new or revised burden within the context of the PRA of 1995 (44
U.S.C. 3501 et seq.). However, we did make a number of burden
adjustments based on updated Bureau of Labor Statistics (BLS) wage
figures and more recent facility counts and estimated case data. These
adjustments reduce our overall time estimate by 50,067 hours and
increase our cost estimate by $1,820,149.
A. Collection of Information Requirements for the IPFQR Program
With regard to the IPFQR Program, we are finalizing one new measure
(Medication Continuation Following Inpatient Psychiatric Discharge (NQF
#3205)) that impacts the FY 2021 payment determination and subsequent
years. The finalized measure is calculated by CMS using IPF submitted
claims data. The claims' requirements and burden are approved by OMB
under control number 0938-0050 (CMS-2552-10) for our Medicare cost
report. The final measure does not impact any of the cost report's data
fields or burden estimates as all worksheets and lines remain
unchanged. Similarly, this final rule does not impose any new or
revised collection of information requirements or burden under OMB
control number 0938-1171 (CMS-10432) which contains information about
our non-claims based IPFQR Program quality measure and non-quality
measure information collection/reporting requirements and burden.
We refer readers to 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 \58\
final rule (81 FR 57265 through 57266), the FY 2018 IPPS/LTCH PPS final
rule (82 FR 38507 through 38508), and the FY 2019 IPF PPS final rule
(83 FR 38609 through 38612) for a detailed discussion of the burden for
the program requirements that we have previously adopted. Information
pertaining to the requirements and burden that are currently approved
by OMB can be found at reginfo.gov under control numbers 0938-0050 and
0938-1171.
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\58\ We note that for operational reasons we sometimes publish
IPFQR program requirements in the IPPS/LTCH PPS proposed and final
rule as opposed to the IPF PPS proposed and final rule.
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B. Adjustments to IPFQR Program Burden Estimates
In the FY 2019 IPF PPS final rule (83 FR 38609), 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 $18.29 per hour (as of May 2016).
Since then, BLS (the Bureau of Labor Statistics) has revised their wage
data with May 2017 serving as their most recent update.\59\ In
response, we proposed to update our cost estimates using the May 2017
figure of $18.83 per hour, an increase of $0.54 per hour or $1.08 per
hour when adjusted by 100 percent to account for fringe benefits and
overhead. This is necessarily a rough adjustment, both because fringe
benefits and overhead 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
rate ($18.83 x 2 = $37.66) to estimate total cost is a reasonably
accurate estimation method.
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\59\ https://www.bls.gov/ooh/healthcare/medical-records-and-health-information-technicians.htm.
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We also proposed to update our facility count and case estimates to
the most recent data available. Specifically, we estimate that there
are now approximately 1,679 (down from the previous estimate of 1,734)
facilities and that for measures which require reporting on the entire
patient population, these facilities will report on an average of 1,283
cases per facility (up from the previous estimate of 1,213).
Accordingly, we proposed to adjust our currently approved cost estimate
from $125,511,558 (see tables 19, 20, and 21) to $127,331,707 (see
tables 22, 23, and 24).
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BILLING CODE 4120-01-C
As mentioned at the beginning of this section, the adjustments are
in response to updates to BLS wage figures and more recent facility
counts and estimated case data. They are not a result of any of the
provisions proposed in the FY 2020 IPF PPS proposed rule. The adjusted
burden figures will be submitted to OMB for approval under control
number 0938-1171 (CMS-10432) as a non-substantive change.
We did not receive any public comments on our proposed burden
estimates.
C. Submission of PRA-Related Comments
We invited public comments on our proposed burden adjustments as
well as on any of the information collection requirements/burden set
out under OMB control number 0938-1171.
We did not receive any public comments on our proposed burden
estimates.
VII. Regulatory Impact Statement
A. Statement of Need
This rule finalizes updates to the prospective payment rates for
Medicare inpatient hospital services provided by IPFs for discharges
occurring during FY 2020 (October 1, 2019 through September 30, 2020).
We are finalizing our proposal to apply the 2016-based IPF market
basket increase of 2.9 percent, less the productivity adjustment of 0.4
percentage point as required by 1886(s)(2)(A)(i) of the Act, and
further reduced by 0.75 percentage point as required by sections
1886(s)(2)(A)(ii) and 1886(s)(3)(E) of the Act, for a final total FY
2020 payment rate update of 1.75 percent. In this final rule, we
revised and rebased the IPF market basket to reflect a 2016 base year.
We also aligned the IPF wage index data with the concurrent IPPS wage
index data by removing the 1-year lag of the pre-floor, pre-
reclassified IPPS hospital wage index upon which the IPF wage index is
based. We also updated the IPF labor-related share and the IPF wage
index including adoption of a new OMB designation. Finally, we updated
the IPFQR Program for the FY 2021 payment determination and subsequent
years.
B. Overall Impact
We have examined the impacts of this final 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), the Congressional Review Act (5 U.S.C. 804(2)) and
Executive Order 13771 on Reducing Regulation and Controlling Regulatory
Costs (January 30, 2017).
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,
[[Page 38477]]
jobs, the environment, public health or safety, or state, local or
tribal governments or communities (also referred to as ``economically
significant''); (2) creating a serious inconsistency or otherwise
interfering with an action taken or planned by another agency; (3)
materially altering the budgetary impacts of entitlement grants, user
fees, or loan programs or the rights and obligations of recipients
thereof; or (4) raising novel legal or policy issues arising out of
legal mandates, the President's priorities, or the principles set forth
in the Executive Order.
A regulatory impact analysis (RIA) must be prepared for major rules
with economically significant effects ($100 million or more in any 1
year). This final rule is not economically significant under Executive
Order 12866, within the meaning of section 3(f)(1) of the Executive
Order. However, OMB has determined that the actions are significant
within the meaning of section 3(f)(4) of the Executive Order.
Therefore, OMB has reviewed this final rule, and the Departments have
provided the following assessment of their impact.
We estimate that the total impact of these changes for FY 2020
payments compared to FY 2019 payments will be a net increase of
approximately $65 million. This reflects an $75 million increase from
the update to the payment rates (+$125 million from the second quarter
2019 IGI forecast of the 2016-based IPF market basket of 2.9 percent, -
$15 million for the productivity adjustment of 0.4 percentage point,
and -$35 million for the ``other adjustment'' of 0.75 percentage
point), as well as a $10 million decrease as a result of the update to
the outlier threshold amount. Outlier payments are estimated to change
from 2.23 percent in FY 2019 to 2.00 percent of total estimated IPF
payments in FY 2020.
C. Anticipated Effects
In this section, we discuss the historical background of the IPF
PPS and the impact of this final 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. The
budget neutrality factor includes 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 final rule, we are updating
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 final rule will be due to the
market basket update for FY 2020 of 2.9 percent (see section III.A.4 of
this final rule) less the productivity adjustment of 0.4 percentage
point required by section 1886(s)(2)(A)(i) of the Act; further reduced
by the ``other adjustment'' of 0.75 percentage point under sections
1886(s)(2)(A)(ii) and 1886(s)(3)(E) of the Act; and the update to the
outlier fixed dollar loss threshold amount.
We estimate that the FY 2020 impact will be a net increase of $65
million in payments to IPF providers. This reflects an estimated $75
million increase from the update to the payment rates and a $10 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 2020. This estimate does not include the implementation of the
required 2.0 percentage point reduction of the market basket increase
factor for any IPF that fails to meet the IPF quality reporting
requirements (as discussed in section V.A. of this final rule).
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 $7.5 million to $38.5 million or less in any 1 year,
depending on industry classification (for details, refer to the SBA
Small Business Size Standards found at https://www.sba.gov/sites/default/files/files/Size_Standards_Table.pdf). 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 25, we estimate that the overall revenue impact
of this final rule on all IPFs is to increase estimated Medicare
payments by approximately 1.5 percent. As a result, since the estimated
impact of this final rule is a net increase in revenue across almost
all categories of IPFs, the Secretary has determined that this final
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 604 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
VII.C.1 of this final rule, the rates and policies set forth in this
final rule will not have an adverse impact on the rural hospitals based
on the data of the 255 rural excluded psychiatric units and 66 rural
psychiatric hospitals in our database of 1,581 IPFs for which data were
available. Therefore, the Secretary has determined that this final rule
will not have a significant impact on the operations of a substantial
number of small rural hospitals.
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 2019, that
threshold is approximately $154 million. This final rule does not
impose spending costs on state, local, or tribal governments in the
aggregate, or by the private sector of $154 million or more.
Executive Order 13132 establishes certain requirements that an
agency must meet when it promulgates a final rule that imposes
substantial direct requirement costs on state and local governments,
preempts state law, or otherwise has Federalism implications. This
final rule will not have a substantial effect on state and local
governments.
2. Impact on Providers
To show the impact on providers of the changes to the IPF PPS
discussed in this final rule, we compare estimated payments under the
IPF PPS rates and factors for FY 2020 versus those under
[[Page 38478]]
FY 2019. We determined the percent change in the estimated FY 2020 IPF
PPS payments compared to the estimated FY 2019 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
update to the outlier fixed dollar loss threshold amount; the updated
wage index data including the updated labor-related share; and the
market basket update for FY 2020, as adjusted by the productivity
adjustment according to section 1886(s)(2)(A)(i) of the Act, and the
``other adjustment'' according to sections 1886(s)(2)(A)(ii) and
1886(s)(3)(E) of the Act.
To illustrate the impacts of the FY 2020 changes in this final
rule, our analysis begins with a FY 2019 baseline simulation model
based on FY 2018 IPF payments inflated to the midpoint of FY 2019 using
IHS Global Inc.'s second quarter 2019 forecast of the market basket
update (see section III.A.4 of this final rule); the estimated outlier
payments in FY 2019; the FY 2019 IPF wage index; the FY 2019 labor-
related share; and the FY 2019 percentage amount of the rural
adjustment. During the simulation, total outlier payments are
maintained at 2 percent of total estimated IPF PPS payments.
Each of the following changes is added incrementally to this
baseline model in order for us to isolate the effects of each change:
The update to the outlier fixed dollar loss threshold
amount.
The FY 2020 IPF wage index and the FY 2020 labor-related
share.
The market basket update for FY 2020 of 2.9 percent less
the productivity adjustment of 0.4 percentage point in accordance with
section 1886(s)(2)(A)(i) of the Act and further reduced by the ``other
adjustment'' of 0.75 percentage point in accordance with sections
1886(s)(2)(A)(ii) and 1886(s)(3)(E) of the Act, for a payment rate
update of 1.75 percent.
Our final column comparison in Table 25 illustrates the percent
change in payments from FY 2019 (that is, October 1, 2018, to September
30, 2019) to FY 2020 (that is, October 1, 2019, to September 30, 2020)
including all the payment policy changes in this final rule.
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BILLING CODE 4120-01-C
3. Impact Results
Table 25 displays the results of our analysis. The table groups
IPFs into the categories listed here based on characteristics provided
in the Provider of Services (POS) file, the IPF provider specific file,
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 1,581 IPFs
included in this analysis. 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
2.23 percent in FY 2019. Thus, we are adjusting the outlier threshold
amount in this final rule to set total estimated outlier payments equal
to 2.0 percent of total payments in FY 2020. The estimated change in
total IPF payments for FY 2020, therefore, includes an approximate 0.23
percent decrease in payments because the outlier portion of total
payments is expected to decrease from approximately 2.23 percent to 2.0
percent.
The overall impact of this outlier adjustment update (as shown in
column
[[Page 38481]]
3 of Table 25), across all hospital groups, is to decrease total
estimated payments to IPFs by 0.23 percent. The largest decrease in
payments is estimated to be -0.78 percent for teaching IPFs with more
than 30 percent interns and residents to beds.
In column 4, we present the effects of the budget-neutral update to
the IPF wage index and the Labor-Related Share (LRS). This represents
the effect of using the concurrent hospital wage data and taking into
account the updated OMB delineations. That is, the impact represented
in this column reflects the update from the FY 2019 IPF wage index to
the final FY 2020 IPF wage index, which includes basing the FY 2020 IPF
wage index on the FY 2020 pre-floor, pre-reclassified IPPS hospital
wage index data, updating the OMB designations for two counties in
Idaho, and updating the LRS from 74.8 percent in FY 2019 to 76.9
percent in FY 2020. We note that there is no projected change in
aggregate payments to IPFs, as indicated in the first row of column 4,
however, there will be distributional effects among different
categories of IPFs. For example, we estimate the largest increase in
payments to be 2.08 percent for Pacific IPFs, and the largest decrease
in payments to be 0.83 percent for New England IPFs.
Finally, column 5 compares our estimates of the total final changes
reflected in this final rule for FY 2020 to the estimates for FY 2019
(without these changes). The average estimated increase for all IPFs is
approximately 1.5 percent. This estimated net increase includes the
effects of the 2016-based market basket update of 2.9 percent reduced
by the productivity adjustment of 0.4 percentage point, as required by
section 1886(s)(2)(A)(i) of the Act and further reduced by the ``other
adjustment'' of 0.75 percentage point, as required by sections
1886(s)(2)(A)(ii) and 1886(s)(3)(E) of the Act. It also includes the
overall estimated 0.23 percent decrease in estimated IPF outlier
payments as a percent of total payments from the final update to the
outlier fixed dollar loss threshold amount. Column 5 also includes the
distributional effects of the updates to the IPF wage index and the
labor-related share.
IPF payments are estimated to increase by 1.54 percent in urban
areas and 1.34 percent in rural areas. Overall, IPFs are estimated to
experience a net increase in payments as a result of the updates in
this final rule. The largest payment increase is estimated at 3.49
percent for IPFs in the Pacific region.
Comment: One commenter wrote that the proposed 1.7 percent
estimated total IPF update was not sufficient to cover the costs of
medical inflation and the growing demand for IPF services. This
commenter was concerned that the update could negatively impact the
financial viability of IPFs and jeopardize access.
Response: Total IPF payments were estimated to increase by 1.7
percent in the FY 2020 IPF PPS proposed rule. This 1.7 percent increase
is a combination of the effects of the proposed market basket update
for FY 2020 and the proposed update to the outlier threshold.
The final FY 2020 estimated increase in payments is based on a more
recent estimate of the final 2016-based IPF market basket percentage
increase of 2.9 percent, a more recent estimate of the MFP adjustment
of 0.4 percentage point, less the 0.75 percentage point reduction (in
accordance with sections 1886(s)(2)(A)(ii) and 1886(s)(3)(E) of the
Act) and impact of the outlier threshold, for a total payment update of
1.75 percent.
The 2.9 percentage increase of the IPF market basket represents the
FY 2020 projected increase in prices of the relative inputs used to
furnish IPF services to Medicare beneficiaries. The forecasted prices
of the individual inputs are based on IGI's most recent 2nd quarter
2019 forecast of the price proxies in the market basket. IGI is a
nationally recognized economic and financial forecasting firm that has
received multiple awards for their macroeconomic forecast accuracy of
major economic indicators. CMS uses IGI's price forecasts in all of the
FFS market baskets used for payment updates and has used the forecasts
produced by this company for many years. In this FY 2020 final rule, we
are also updating the cost weights for the IPF market basket, from 2012
to 2016, which captures changes in relative costs due to quantity and
intensity. We therefore believe that the IPF market basket represents
an appropriate measure of input price inflation that is expected to be
realized by IPFs in FY 2020.
As stated, the Act mandates that the market basket update (which
accounts for input price inflation) be adjusted for multifactor
productivity and a 0.75 percentage point legislatively required
adjustment. CMS does not have the authority to alter these payment
adjustments, but we note that under the current law at 1886(s)(3)(E),
FY 2020 is the last year that the 0.75 percentage point ``other''
adjustment will be made.
Estimated IPF payments are also reduced by 0.23 percent as a result
of the update to the outlier threshold. Based on an updated analysis of
the most recent IPF claims data for this final rule we now estimate
that IPF outlier payments as a percentage of total estimated payments
will be approximately 2.23 percent in FY 2019. Since this percentage
exceeds our established 2 percent IPF outlier policy we are adjusting
the outlier threshold amount to set total estimated outlier payments
equal to 2 percent of total estimated payments in FY 2020. The
estimated change in total IPF payments for FY 2020 includes an
approximate 0.23 percent decrease in payments because the estimated
outlier portion of total payments is estimated to decrease from 2.23
percent to 2 percent.
4. Effect on Beneficiaries
Under the IPF PPS, IPFs will receive payment based on the average
resources consumed by patients for each day. We do not expect changes
in the quality of care or access to services for Medicare beneficiaries
under the FY 2020 IPF PPS, but we continue to expect that paying
prospectively for IPF services will enhance the efficiency of the
Medicare program.
5. Effects of Updates to the Inpatient Psychiatric Facilities Quality
Reporting (IPFQR) Program
As discussed in section V. of this final rule and in accordance
with section 1886(s)(4)(A)(i) of the Act, we will implement a 2
percentage point reduction in the market basket update when calculating
the FY 2021 national per diem rate for discharges from IPFs that have
failed to comply with the IPFQR Program requirements for the FY 2021
payment determination. In section III.B. of this final rule, we discuss
how the 2 percentage point reduction will be applied. For the FY 2019
payment determination (that is, data submitted in CY 2018), of the
1,679 IPFs eligible for the IPFQR Program, 50 did not receive the full
market basket update due to reasons specific to the IPFQR Program; 24
of these IPFs chose not to participate and 26 did not meet the
requirements of the Program. Thus, we estimate similar numbers for the
FY 2021 payment determination and that the IPFQR Program will have a
negligible impact on overall IPF payments in FY 2021.
We are finalizing provisions that impact the FY 2021 payment
determination and subsequent years. We refer readers to section VI. of
this final rule for details discussing information collection
requirements for the IPFQR Program. We will closely monitor the effects
of this quality reporting program on IPFs and help facilitate
successful reporting outcomes through ongoing
[[Page 38482]]
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 final rule, we
should estimate the cost associated with regulatory review. Due to the
uncertainty involved with accurately quantifying the number of entities
that will review this final rule, we assume that the total number of
unique commenters on the most recent IPF proposed rule from FY 2020 (84
FR 16948) will be the number of reviewers of this final rule. We
acknowledge that this assumption may understate or overstate the costs
of reviewing this final rule. It is possible that not all commenters
reviewed the FY 2020 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 of this final rule. We
solicited comments on this assumption.
We also recognize that different types of entities are in many
cases affected by mutually exclusive sections of this final rule;
therefore, for the purposes of our estimate, we assume that each
reviewer reads approximately 50 percent of this final rule.
Using the May, 2018 mean (average) wage information from the BLS
for medical and health service managers (Code 11-9111), we estimate
that the cost of reviewing this final rule is $109.36 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 1.4 hours for
the staff to review half of this final rule. For each IPF that reviews
the final rule, the estimated cost is (1.4 hours x $109.36) or $153.10.
Therefore, we estimate that the total cost of reviewing this final rule
is $3,674.40 ($153.10 x 24 reviewers).
We received one comment on our assumption about the number of
reviewers of the IPF PPS proposed rule.
Comment: One commenter wrote that CMS should consider the number of
downloads of the IPF proposed rule in calculating regulatory review
costs, since many reviewers may read the rule but not submit a comment.
The commenter also noted that some organizations may download the rule
once and distribute copies to others to read. This commenter suggested
that CMS consider the greater of the number of downloads or of the
number of unique commenters as a fair estimate of the number of
reviewers. This commenter believes that this method would be a fairer
assumption of the number of reviewers.
Response: We appreciate the commenter's input on our methodology.
We have acknowledged that our method provides an estimate that could
overstate or understate the costs of reviewing the rule. We do not
believe this suggested methodology would improve the accuracy of the
estimate. We do not currently have the ability to track the number of
times the IPF rule is downloaded, and if we did, to know how many of
those downloads are by those who are providers or similar stakeholders.
We also prefer to use a methodology for estimating the number of
reviewers that is consistent with the methodology that other Medicare
payment systems use. As such, we will continue to use the number of
commenters on the most recent proposed rule as the basis for our review
cost estimate.
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. Therefore, we are updating the IPF PPS using the
methodology published in the November 2004 IPF PPS final rule; applying
the 2016-based IPF PPS market basket update for FY 2020 of 2.9 percent,
reduced by the statutorily required multifactor productivity adjustment
of 0.4 percentage point and the ``other adjustment'' of 0.75 percentage
point, along with the wage index budget neutrality adjustment to update
the payment rates; finalizing a FY 2020 IPF wage index which is fully
based upon the OMB CBSA designations from Bulletin 17-01 and which uses
the FY 2020 pre-floor, pre-reclassified IPPS hospital wage index as its
basis; and finalizing changes to the IPFQR Program.
E. Accounting Statement
As required by OMB Circular A-4 (available at www.whitehouse.gov/sites/whitehouse.gov/files/omb/circulars/A4/a-4.pdf), in Table 26, 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 final rule. Table 26 provides our best estimate
of the increase in Medicare payments under the IPF PPS as a result of
the changes presented in this final rule and based on the data for
1,581 IPFs in our database.
Table 26--Accounting Statement: Classification of Estimated Expenditures
[Change in estimated impacts from FY 2019 IPF PPS to FY 2020 IPF PPS]
------------------------------------------------------------------------
Category Transfers
------------------------------------------------------------------------
Annualized Monetized Transfers............ $65 million.
From Whom to Whom?........................ Federal Government to IPF
Medicare Providers.
------------------------------------------------------------------------
F. Congressional Review Act
Pursuant to the Congressional Review Act (5 U.S.C. 801 et seq.) the
Office of Information and Regulatory Affairs designated this rule as
not a major rule, as defined by 5 U.S.C. 804(2).
G. Regulatory Reform Analysis Under Executive Order 13771
Executive Order 13771, titled Reducing Regulation and Controlling
Regulatory Costs, was issued on January 30, 2017 and requires that the
costs associated with significant new regulations ``shall, to the
extent permitted by law, be offset by the elimination of existing costs
associated with at least two prior regulations.'' This final rule is
not expected to be subject to the requirements of Executive Order 13771
because it is estimated to result in no more than de minimis costs as
described previously and thus is not a regulatory action for the
purposes of E.O. 13771.
H. Conclusion
In accordance with the provisions of Executive Order 12866, this
regulation was reviewed by the Office of Management and Budget.
Dated: July 26, 2019 .
Seema Verma,
Administrator, Centers for Medicare & Medicaid Services.
Dated: July 26, 2019.
Alex M. Azar II,
Secretary, Department of Health and Human Services.
[FR Doc. 2019-16370 Filed 7-30-19; 4:15 pm]
BILLING CODE 4120-01-P
