Att E3_Inpatient Rehabilitation Facilities

3. Inpatient Rehabiliation Facilities - CAUTI, MRSA LabID, CDI LabID, Flu.pdf

The National Healthcare Safety Network (NHSN)

Att E3_Inpatient Rehabilitation Facilities

OMB: 0920-0666

⚠️ Notice: This form may be outdated. More recent filings and information on OMB 0920-0666 can be found here:

Document [pdf]

Download: pdf | pdf

Vol. 81

Monday,

No. 79

April 25, 2016

Part II

Department of Health and Human Services

asabaliauskas on DSK3SPTVN1PROD with PROPOSALS

Centers for Medicare & Medicaid Services
42 CFR Part 412
Medicare Program; Inpatient Rehabilitation Facility Prospective Payment
System for Federal Fiscal Year 2017; Proposed Rule

VerDate Sep<11>2014

19:36 Apr 22, 2016

Jkt 238001

PO 00000

Frm 00001

Fmt 4717

Sfmt 4717

E:\FR\FM\25APP2.SGM

25APP2

24178

Federal Register / Vol. 81, No. 79 / Monday, April 25, 2016 / Proposed Rules

DEPARTMENT OF HEALTH AND
HUMAN SERVICES
Centers for Medicare & Medicaid
Services
42 CFR Part 412
[CMS–1647–P]
RIN 0938–AS78

Medicare Program; Inpatient
Rehabilitation Facility Prospective
Payment System for Federal Fiscal
Year 2017
Centers for Medicare &
Medicaid Services (CMS), HHS.
ACTION: Proposed rule.
AGENCY:

This proposed rule would
update the prospective payment rates
for inpatient rehabilitation facilities
(IRFs) for federal fiscal year (FY) 2017
as required by the statute. As required
by section 1886(j)(5) of the Act, this rule
includes the classification and
weighting factors for the IRF prospective
payment system’s (IRF PPS’s) case-mix
groups and a description of the
methodologies and data used in
computing the prospective payment
rates for FY 2017. We are also proposing
to revise and update quality measures
and reporting requirements under the
IRF quality reporting program (QRP).
DATES: To be assured consideration,
comments must be received at one of
the addresses provided below, not later
than 5 p.m. on June 20, 2016.
ADDRESSES: In commenting, please refer
to file code CMS–1647–P. Because of
staff and resource limitations, we cannot
accept comments by facsimile (FAX)
transmission.
You may submit comments in one of
four ways (please choose only one of the
ways listed):
1. Electronically. You may submit
electronic comments on this regulation
to http://www.regulations.gov. Follow
the ‘‘Submit a comment’’ instructions.
2. By regular mail. You may mail
written comments to the following
address ONLY: Centers for Medicare &
Medicaid Services, Department of
Health and Human Services, Attention:
CMS–1647–P, P.O. Box 8016, Baltimore,
MD 21244–8016.
Please allow sufficient time for mailed
comments to be received before the
close of the comment period.
3. By express or overnight mail. You
may send written comments to the
following address ONLY: Centers for

asabaliauskas on DSK3SPTVN1PROD with PROPOSALS

SUMMARY:

VerDate Sep<11>2014

19:36 Apr 22, 2016

Jkt 238001

Medicare & Medicaid Services,
Department of Health and Human
Services, Attention: CMS–1647–P, Mail
Stop C4–26–05, 7500 Security
Boulevard, Baltimore, MD 21244–1850.
4. By hand or courier. Alternatively,
you may deliver (by hand or courier)
your written comments ONLY to the
following addresses prior to the close of
the comment period:
a. For delivery in Washington, DC—
Centers for Medicare & Medicaid
Services, Department of Health and
Human Services, Room 445–G, Hubert
H. Humphrey Building, 200
Independence Avenue SW.,
Washington, DC 20201
(Because access to the interior of the
Hubert H. Humphrey Building is not
readily available to persons without
Federal government identification,
commenters are encouraged to leave
their comments in the CMS drop slots
located in the main lobby of the
building. A stamp-in clock is available
for persons wishing to retain a proof of
filing by stamping in and retaining an
extra copy of the comments being filed.)
b. For delivery in Baltimore, MD—
Centers for Medicare & Medicaid
Services, Department of Health and
Human Services, 7500 Security
Boulevard, Baltimore, MD 21244–
1850
If you intend to deliver your
comments to the Baltimore address,
please call telephone number (410) 786–
7195 in advance to schedule your
arrival with one of our staff members.
Comments erroneously mailed to the
addresses indicated as appropriate for
hand or courier delivery may be delayed
and received after the comment period.
For information on viewing public
comments, see the beginning of the
SUPPLEMENTARY INFORMATION section.
FOR FURTHER INFORMATION CONTACT:
Gwendolyn Johnson, (410) 786–6954,
for general information.
Christine Grose, (410) 786–1362, for
information about the quality reporting
program.
Kadie Derby, (410) 786–0468, or
Susanne Seagrave, (410) 786–0044, for
information about the payment policies
and payment rates.
SUPPLEMENTARY INFORMATION: The IRF
PPS Addenda along with other
supporting documents and tables
referenced in this proposed rule are
available through the Internet on the
CMS Web site at http://
www.cms.hhs.gov/Medicare/Medicare-

PO 00000

Frm 00002

Fmt 4701

Sfmt 4702

Fee-for-Service-Payment/
InpatientRehabFacPPS/.
Inspection of Public Comments: All
comments received before the close of
the comment period are available for
viewing by the public, including any
personally identifiable or confidential
business information that is included in
a comment. We post all comments
received before the close of the
comment period on the following Web
site as soon as possible after they have
been received: http://
www.regulations.gov. Follow the search
instructions on that Web site to view
public comments.
Comments received timely will also
be available for public inspection as
they are received, generally beginning
approximately 3 weeks after publication
of a document, at the headquarters of
the Centers for Medicare & Medicaid
Services, 7500 Security Boulevard,
Baltimore, Maryland 21244, Monday
through Friday of each week from 8:30
a.m. to 4 p.m. To schedule an
appointment to view public comments,
phone 1–800–743–3951.
Executive Summary
A. Purpose
This proposed rule would update the
prospective payment rates for IRFs for
FY 2017 (that is, for discharges
occurring on or after October 1, 2016,
and on or before September 30, 2017) as
required under section 1886(j)(3)(C) of
the Social Security Act (the Act). As
required by section 1886(j)(5) of the Act,
this rule includes the classification and
weighting factors for the IRF PPS’s casemix groups and a description of the
methodologies and data used in
computing the prospective payment
rates for FY 2017. This proposed rule
also proposes revisions and updates to
the quality measures and reporting
requirements under the IRF QRP.
B. Summary of Major Provisions
In this proposed rule, we use the
methods described in the FY 2016 IRF
PPS final rule (80 FR 47036) to propose
updates to the federal prospective
payment rates for FY 2017 using
updated FY 2015 IRF claims and the
most recent available IRF cost report
data, which is FY 2014 IRF cost report
data. We are also proposing to revise
and update quality measures and
reporting requirements under the IRF
QRP.
C. Summary of Impacts

E:\FR\FM\25APP2.SGM

25APP2

Federal Register / Vol. 81, No. 79 / Monday, April 25, 2016 / Proposed Rules
Provision description

Transfers

FY 2017 IRF PPS payment rate update ..................................................

The overall economic impact of this proposed rule is an estimated
$125 million in increased payments from the Federal government to
IRFs during FY 2017.

Provision description

Costs

New quality reporting program requirements ...........................................

The total costs in FY 2017 for IRFs as a result of the proposed new
quality reporting requirements are estimated to be $5,231,398.17.

To assist readers in referencing
sections contained in this document, we
are providing the following Table of
Contents.
Table of Contents

asabaliauskas on DSK3SPTVN1PROD with PROPOSALS

24179

I. Background
A. Historical Overview of the IRF PPS
B. Provisions of the Affordable Care Act
Affecting the IRF PPS in FY 2012 and
Beyond
C. Operational Overview of the Current IRF
PPS
D. Advancing Health Information Exchange
II. Summary of Provisions of the Proposed
Rule
III. Proposed Update to the Case-Mix Group
(CMG) Relative Weights and Average
Length of Stay Values for FY 2017
IV. Facility-Level Adjustment Factors
V. Proposed FY 2017 IRF PPS Payment
Update
A. Background
B. Proposed FY 2017 Market Basket Update
and Productivity Adjustment
C. Proposed Labor-Related Share for FY
2017
D. Proposed Wage Adjustment
E. Description of the Proposed IRF
Standard Payment Conversion Factor
and Payment Rates for FY 2017
F. Example of the Methodology for
Adjusting the Proposed Federal
Prospective Payment Rates
VI. Proposed Update to Payments for HighCost Outliers under the IRF PPS
A. Proposed Update to the Outlier
Threshold Amount for FY 2017
B. Proposed Update to the IRF Cost-toCharge Ratio Ceiling and Urban/Rural
Averages
VII. Proposed Revisions and Updates to the
IRF Quality Reporting Program (QRP)
A. Background and Statutory Authority
B. General Considerations Used for
Selection of Quality, Resource Use, and
Other Measures for the IRF QRP
C. Policy for Retention of IRF QRP
Measures Adopted for Previous Payment
Determinations
D. Policy for Adopting Changes to IRF QRP
Measures
E. Quality Measures Previously Finalized
for and Currently Used in the IRF QRP
F. IRF QRP Quality, Resource Use and
Other Measures Proposed for the FY
2018 Payment Determination and
Subsequent Years
G. IRF QRP Quality Measure Proposed for
the FY 2020 Payment Determination and
Subsequent Years

VerDate Sep<11>2014

19:36 Apr 22, 2016

Jkt 238001

H. IRF QRP Quality Measures and Measure
Concepts under Consideration for Future
Years
I. Proposed Form, Manner, and Timing of
Quality Data Submission for the FY 2018
Payment Determination and Subsequent
Years
J. IRF QRP Data Completion Thresholds for
the FY 2016 Payment Determination and
Subsequent Years
K. IRF QRP Data Validation Process for the
FY 2016 Payment Determination and
Subsequent Years
L. Previously Adopted and Codified IRF
QRP Submission Exception and
Extension Policies
M. Previously Adopted and Finalized IRF
QRP Reconsideration and Appeals
Procedures
N. Public Display of Measure Data for the
IRF QRP & Procedures for the
Opportunity to Review and Correct Data
and Information
O. Mechanism for Providing Feedback
Reports to IRFs
P. Proposed Method for Applying the
Reduction to the FY 2017 IRF Increase
Factor for IRFs That Fail to Meet the
Quality Reporting Requirements
VIII. Collection of Information Requirements
A. Statutory Requirement for Solicitation
of Comments
B. Collection of Information Requirements
for Updates Related to the IRF QRP
IX. Response to Public Comments
X. Regulatory Impact Analysis
A. Statement of Need
B. Overall Impacts
C. Detailed Economic Analysis
D. Alternatives Considered
E. Accounting Statement
F. Conclusion

Acronyms, Abbreviations, and Short
Forms
Because of the many terms to which
we refer by acronym, abbreviation, or
short form in this final rule, we are
listing the acronyms, abbreviation, and
short forms used and their
corresponding terms in alphabetical
order.
The Act The Social Security Act
ADC Average Daily Census
ADE Adverse Drug Events
The Affordable Care Act Patient Protection
and Affordable Care Act (Pub. L. 111–148,
enacted on March 23, 2010)
AHRQ Agency for Healthcare Research and
Quality
APU Annual Payment Update

PO 00000

Frm 00003

Fmt 4701

Sfmt 4702

ASAP Assessment Submission and
Processing
ASCA The Administrative Simplification
Compliance Act of 2002 (Pub. L. 107–105,
enacted on December 27, 2002)
ASPE Office of the Assistant Secretary for
Planning and Evaluation
BLS U.S. Bureau of Labor Statistics
CAH Critical Access Hospitals
CASPER Certification and Survey Provider
Enhanced Reports
CAUTI Catheter-Associated Urinary Tract
Infection
CBSA Core-Based Statistical Area
CCR Cost-to-Charge Ratio
CDC The Centers for Disease Control and
Prevention
CDI Clostridium difficile Infection
CFR Code of Federal Regulations
CMG Case-Mix Group
CMS Centers for Medicare & Medicaid
Services
COA Care for Older Adults
CY Calendar year
DSH Disproportionate Share Hospital
DSH PP Disproportionate Share Patient
Percentage
eCQMs Electronically Specified Clinical
Quality Measures
ESRD End-Stage Renal Disease
FFS Fee-for-Service
FR Federal Register
FY Federal Fiscal Year
GPCI Geographic Practice Cost Index
HAI Healthcare Associated Infection
HCC Hierarchical Condition Category
HHA Home Health Agencies
HCP Home Care Personnel
HHS U.S. Department of Health & Human
Services
HIPAA Health Insurance Portability and
Accountability Act of 1996 (Pub. L. 104–
191, enacted on August 21, 1996)
Hospital VBP Hospital Value-Based
Purchasing Program (also HVBP)
IGI IHS Global Insight
IMPACT Act Improving Medicare PostAcute Care Transformation Act of 2014
(Pub. L. 113–185, enacted on October 6,
2014)
IME Indirect Medical Education
IPF Inpatient Psychiatric Facility
IPPS Inpatient prospective payment system
IQR Inpatient Quality Reporting Program
IRF Inpatient Rehabilitation Facility
IRF-PAI Inpatient Rehabilitation FacilityPatient Assessment Instrument
IRF PPS Inpatient Rehabilitation Facility
Prospective Payment System
IRF QRP Inpatient Rehabilitation Facility
Quality Reporting Program
IRVEN Inpatient Rehabilitation Validation
and Entry

E:\FR\FM\25APP2.SGM

25APP2

24180

Federal Register / Vol. 81, No. 79 / Monday, April 25, 2016 / Proposed Rules

LIP Low-Income Percentage
IVS Influenza Vaccination Season
LTCH Long-Term Care Hospital
MA (Medicare Part C) Medicare Advantage
MAC Medicare Administrative Contractor
MAP Measures Application Partnership
MedPAC Medicare Payment Advisory
Commission
MFP Multifactor Productivity
MMSEA Medicare, Medicaid, and SCHIP
Extension Act of 2007 (Pub. L. 110–173,
enacted on December 29, 2007)
MRSA Methicillin-Resistant
Staphylococcus aureus
MSPB Medicare Spending Per Beneficiary
MUC Measures Under Consideration
NHSN National Healthcare Safety Network
NQF National Quality Forum
OMB Office of Management and Budget
ONC Office of the National Coordinator for
Health Information Technology
OPPS/ASC Outpatient Prospective Payment
System/Ambulatory Surgical Center
PAC Post-Acute Care
PAC/LTC Post-Acute Care/Long-Term Care
PAI Patient Assessment Instrument
PPR Potentially Preventable Readmissions
PPS Prospective Payment System
PRA Paperwork Reduction Act of 1995
(Pub. L. 104–13, enacted on May 22, 1995)
QIES Quality Improvement Evaluation
System
QM Quality Measure
QRP Quality Reporting Program
RIA Regulatory Impact Analysis
RIC Rehabilitation Impairment Category
RFA Regulatory Flexibility Act (Pub. L. 96–
354, enacted on September 19, 1980)
RN Registered Nurse
RPL Rehabilitation, Psychiatric, and LongTerm Care market basket
RSRR Risk-standardized readmission rate
SIR Standardized Infection Ratio
SNF Skilled Nursing Facilities
SRR Standardized Risk Ratio
SSI Supplemental Security Income
TEP Technical Expert Panel

asabaliauskas on DSK3SPTVN1PROD with PROPOSALS

I. Background
A. Historical Overview of the IRF PPS
Section 1886(j) of the Act provides for
the implementation of a per-discharge
prospective payment system (PPS) for
inpatient rehabilitation hospitals and
inpatient rehabilitation units of a
hospital (collectively, hereinafter
referred to as IRFs). Payments under the
IRF PPS encompass inpatient operating
and capital costs of furnishing covered
rehabilitation services (that is, routine,
ancillary, and capital costs), but not
direct graduate medical education costs,
costs of approved nursing and allied
health education activities, bad debts,
and other services or items outside the
scope of the IRF PPS. Although a
complete discussion of the IRF PPS
provisions appears in the original FY
2002 IRF PPS final rule (66 FR 41316)
and the FY 2006 IRF PPS final rule (70
FR 47880), we are providing below a
general description of the IRF PPS for
FYs 2002 through 2016.

VerDate Sep<11>2014

19:36 Apr 22, 2016

Jkt 238001

Under the IRF PPS from FY 2002
through FY 2005 the federal prospective
payment rates were computed across
100 distinct case-mix groups (CMGs), as
described in the FY 2002 IRF PPS final
rule (66 FR 41316). We constructed 95
CMGs using rehabilitation impairment
categories (RICs), functional status (both
motor and cognitive), and age (in some
cases, cognitive status and age may not
be a factor in defining a CMG). In
addition, we constructed five special
CMGs to account for very short stays
and for patients who expire in the IRF.
For each of the CMGs, we developed
relative weighting factors to account for
a patient’s clinical characteristics and
expected resource needs. Thus, the
weighting factors accounted for the
relative difference in resource use across
all CMGs. Within each CMG, we created
tiers based on the estimated effects that
certain comorbidities would have on
resource use.
We established the federal PPS rates
using a standardized payment
conversion factor (formerly referred to
as the budget-neutral conversion factor).
For a detailed discussion of the budgetneutral conversion factor, please refer to
our FY 2004 IRF PPS final rule (68 FR
45684 through 45685). In the FY 2006
IRF PPS final rule (70 FR 47880), we
discussed in detail the methodology for
determining the standard payment
conversion factor.
We applied the relative weighting
factors to the standard payment
conversion factor to compute the
unadjusted federal prospective payment
rates under the IRF PPS from FYs 2002
through 2005. Within the structure of
the payment system, we then made
adjustments to account for interrupted
stays, transfers, short stays, and deaths.
Finally, we applied the applicable
adjustments to account for geographic
variations in wages (wage index), the
percentage of low-income patients,
location in a rural area (if applicable),
and outlier payments (if applicable) to
the IRFs’ unadjusted federal prospective
payment rates.
For cost reporting periods that began
on or after January 1, 2002, and before
October 1, 2002, we determined the
final prospective payment amounts
using the transition methodology
prescribed in section 1886(j)(1) of the
Act. Under this provision, IRFs
transitioning into the PPS were paid a
blend of the federal IRF PPS rate and the
payment that the IRFs would have
received had the IRF PPS not been
implemented. This provision also
allowed IRFs to elect to bypass this
blended payment and immediately be
paid 100 percent of the federal IRF PPS
rate. The transition methodology

PO 00000

Frm 00004

Fmt 4701

Sfmt 4702

expired as of cost reporting periods
beginning on or after October 1, 2002
(FY 2003), and payments for all IRFs
now consist of 100 percent of the federal
IRF PPS rate.
We established a CMS Web site as a
primary information resource for the
IRF PPS which is available at http://
www.cms.gov/Medicare/Medicare-Feefor-Service-Payment/InpatientRehab
FacPPS/index.html. The Web site may
be accessed to download or view
publications, software, data
specifications, educational materials,
and other information pertinent to the
IRF PPS.
Section 1886(j) of the Act confers
broad statutory authority upon the
Secretary to propose refinements to the
IRF PPS. In the FY 2006 IRF PPS final
rule (70 FR 47880) and in correcting
amendments to the FY 2006 IRF PPS
final rule (70 FR 57166) that we
published on September 30, 2005, we
finalized a number of refinements to the
IRF PPS case-mix classification system
(the CMGs and the corresponding
relative weights) and the case-level and
facility-level adjustments. These
refinements included the adoption of
the Office of Management and Budget’s
(OMB) Core-Based Statistical Area
(CBSA) market definitions,
modifications to the CMGs, tier
comorbidities, and CMG relative
weights, implementation of a new
teaching status adjustment for IRFs,
revision and rebasing of the market
basket index used to update IRF
payments, and updates to the rural, lowincome percentage (LIP), and high-cost
outlier adjustments. Beginning with the
FY 2006 IRF PPS final rule (70 FR 47908
through 47917), the market basket index
used to update IRF payments was a
market basket reflecting the operating
and capital cost structures for
freestanding IRFs, freestanding inpatient
psychiatric facilities (IPFs), and longterm care hospitals (LTCHs) (hereinafter
referred to as the rehabilitation,
psychiatric, and long-term care (RPL)
market basket). Any reference to the FY
2006 IRF PPS final rule in this final rule
also includes the provisions effective in
the correcting amendments. For a
detailed discussion of the final key
policy changes for FY 2006, please refer
to the FY 2006 IRF PPS final rule (70 FR
47880 and 70 FR 57166).
In the FY 2007 IRF PPS final rule (71
FR 48354), we further refined the IRF
PPS case-mix classification system (the
CMG relative weights) and the caselevel adjustments, to ensure that IRF
PPS payments would continue to reflect
as accurately as possible the costs of
care. For a detailed discussion of the FY
2007 policy revisions, please refer to the

E:\FR\FM\25APP2.SGM

25APP2

asabaliauskas on DSK3SPTVN1PROD with PROPOSALS

Federal Register / Vol. 81, No. 79 / Monday, April 25, 2016 / Proposed Rules
FY 2007 IRF PPS final rule (71 FR
48354).
In the FY 2008 IRF PPS final rule (72
FR 44284), we updated the federal
prospective payment rates and the
outlier threshold, revised the IRF wage
index policy, and clarified how we
determine high-cost outlier payments
for transfer cases. For more information
on the policy changes implemented for
FY 2008, please refer to the FY 2008 IRF
PPS final rule (72 FR 44284), in which
we published the final FY 2008 IRF
federal prospective payment rates.
After publication of the FY 2008 IRF
PPS final rule (72 FR 44284), section
115 of the Medicare, Medicaid, and
SCHIP Extension Act of 2007 (Pub. L.
110–173, enacted on December 29,
2007) (MMSEA), amended section
1886(j)(3)(C) of the Act to apply a zero
percent increase factor for FYs 2008 and
2009, effective for IRF discharges
occurring on or after April 1, 2008.
Section 1886(j)(3)(C) of the Act required
the Secretary to develop an increase
factor to update the IRF federal
prospective payment rates for each FY.
Based on the legislative change to the
increase factor, we revised the FY 2008
federal prospective payment rates for
IRF discharges occurring on or after
April 1, 2008. Thus, the final FY 2008
IRF federal prospective payment rates
that were published in the FY 2008 IRF
PPS final rule (72 FR 44284) were
effective for discharges occurring on or
after October 1, 2007, and on or before
March 31, 2008; and the revised FY
2008 IRF federal prospective payment
rates were effective for discharges
occurring on or after April 1, 2008, and
on or before September 30, 2008. The
revised FY 2008 federal prospective
payment rates are available on the CMS
Web site at http://www.cms.gov/
Medicare/Medicare-Fee-for-ServicePayment/InpatientRehabFacPPS/DataFiles.html.
In the FY 2009 IRF PPS final rule (73
FR 46370), we updated the CMG relative
weights, the average length of stay
values, and the outlier threshold;
clarified IRF wage index policies
regarding the treatment of ‘‘New
England deemed’’ counties and multicampus hospitals; and revised the
regulation text in response to section
115 of the MMSEA to set the IRF
compliance percentage at 60 percent
(the ‘‘60 percent rule’’) and continue the
practice of including comorbidities in
the calculation of compliance
percentages. We also applied a zero
percent market basket increase factor for
FY 2009 in accordance with section 115
of the MMSEA. For more information on
the policy changes implemented for FY
2009, please refer to the FY 2009 IRF

VerDate Sep<11>2014

19:36 Apr 22, 2016

Jkt 238001

PPS final rule (73 FR 46370), in which
we published the final FY 2009 IRF
federal prospective payment rates.
In the FY 2010 IRF PPS final rule (74
FR 39762) and in correcting
amendments to the FY 2010 IRF PPS
final rule (74 FR 50712) that we
published on October 1, 2009, we
updated the federal prospective
payment rates, the CMG relative
weights, the average length of stay
values, the rural, LIP, teaching status
adjustment factors, and the outlier
threshold; implemented new IRF
coverage requirements for determining
whether an IRF claim is reasonable and
necessary; and revised the regulation
text to require IRFs to submit patient
assessments on Medicare Advantage
(MA) (formerly called Medicare Part C)
patients for use in the 60 percent rule
calculations. Any reference to the FY
2010 IRF PPS final rule in this final rule
also includes the provisions effective in
the correcting amendments. For more
information on the policy changes
implemented for FY 2010, please refer
to the FY 2010 IRF PPS final rule (74 FR
39762 and 74 FR 50712), in which we
published the final FY 2010 IRF federal
prospective payment rates.
After publication of the FY 2010 IRF
PPS final rule (74 FR 39762), section
3401(d) of the Patient Protection and
Affordable Care Act (Pub. L. 111–148,
enacted on March 23, 2010), as
amended by section 10319 of the same
Act and by section 1105 of the Health
Care and Education Reconciliation Act
of 2010 (Pub. L. 111–152, enacted on
March 30, 2010) (collectively,
hereinafter referred to as ‘‘The
Affordable Care Act’’), amended section
1886(j)(3)(C) of the Act and added
section 1886(j)(3)(D) of the Act. Section
1886(j)(3)(C) of the Act requires the
Secretary to estimate a multifactor
productivity adjustment to the market
basket increase factor, and to apply
other adjustments as defined by the Act.
The productivity adjustment applies to
FYs from 2012 forward. The other
adjustments apply to FYs 2010 to 2019.
Sections 1886(j)(3)(C)(ii)(II) and
1886(j)(3)(D)(i) of the Act defined the
adjustments that were to be applied to
the market basket increase factors in
FYs 2010 and 2011. Under these
provisions, the Secretary was required
to reduce the market basket increase
factor in FY 2010 by a 0.25 percentage
point adjustment. Notwithstanding this
provision, in accordance with section
3401(p) of the Affordable Care Act, the
adjusted FY 2010 rate was only to be
applied to discharges occurring on or
after April 1, 2010. Based on the selfimplementing legislative changes to
section 1886(j)(3) of the Act, we

PO 00000

Frm 00005

Fmt 4701

Sfmt 4702

24181

adjusted the FY 2010 federal
prospective payment rates as required,
and applied these rates to IRF
discharges occurring on or after April 1,
2010, and on or before September 30,
2010. Thus, the final FY 2010 IRF
federal prospective payment rates that
were published in the FY 2010 IRF PPS
final rule (74 FR 39762) were used for
discharges occurring on or after October
1, 2009, and on or before March 31,
2010, and the adjusted FY 2010 IRF
federal prospective payment rates
applied to discharges occurring on or
after April 1, 2010, and on or before
September 30, 2010. The adjusted FY
2010 federal prospective payment rates
are available on the CMS Web site at
http://www.cms.gov/Medicare/
Medicare-Fee-for-Service-Payment/
InpatientRehabFacPPS/Data-Files.html.
In addition, sections 1886(j)(3)(C) and
(D) of the Act also affected the FY 2010
IRF outlier threshold amount because
they required an adjustment to the FY
2010 RPL market basket increase factor,
which changed the standard payment
conversion factor for FY 2010.
Specifically, the original FY 2010 IRF
outlier threshold amount was
determined based on the original
estimated FY 2010 RPL market basket
increase factor of 2.5 percent and the
standard payment conversion factor of
$13,661. However, as adjusted, the IRF
prospective payments are based on the
adjusted RPL market basket increase
factor of 2.25 percent and the revised
standard payment conversion factor of
$13,627. To maintain estimated outlier
payments for FY 2010 equal to the
established standard of 3 percent of total
estimated IRF PPS payments for FY
2010, we revised the IRF outlier
threshold amount for FY 2010 for
discharges occurring on or after April 1,
2010, and on or before September 30,
2010. The revised IRF outlier threshold
amount for FY 2010 was $10,721.
Sections 1886(j)(3)(C)(ii)(II) and
1886(j)(3)(D)(i) of the Act also required
the Secretary to reduce the market
basket increase factor in FY 2011 by a
0.25 percentage point adjustment. The
FY 2011 IRF PPS notice (75 FR 42836)
and the correcting amendments to the
FY 2011 IRF PPS notice (75 FR 70013)
described the required adjustments to
the FY 2011 and FY 2010 IRF PPS
federal prospective payment rates and
outlier threshold amount for IRF
discharges occurring on or after April 1,
2010, and on or before September 30,
2011. It also updated the FY 2011
federal prospective payment rates, the
CMG relative weights, and the average
length of stay values. Any reference to
the FY 2011 IRF PPS notice in this final
rule also includes the provisions

E:\FR\FM\25APP2.SGM

25APP2

asabaliauskas on DSK3SPTVN1PROD with PROPOSALS

24182

Federal Register / Vol. 81, No. 79 / Monday, April 25, 2016 / Proposed Rules

effective in the correcting amendments.
For more information on the FY 2010
and FY 2011 adjustments or the updates
for FY 2011, please refer to the FY 2011
IRF PPS notice (75 FR 42836 and 75 FR
70013).
In the FY 2012 IRF PPS final rule (76
FR 47836), we updated the IRF federal
prospective payment rates, rebased and
revised the RPL market basket, and
established a new quality reporting
program for IRFs in accordance with
section 1886(j)(7) of the Act. We also
revised regulation text for the purpose
of updating and providing greater
clarity. For more information on the
policy changes implemented for FY
2012, please refer to the FY 2012 IRF
PPS final rule (76 FR 47836), in which
we published the final FY 2012 IRF
federal prospective payment rates.
The FY 2013 IRF PPS notice (77 FR
44618) described the required
adjustments to the FY 2013 federal
prospective payment rates and outlier
threshold amount for IRF discharges
occurring on or after October 1, 2012,
and on or before September 30, 2013. It
also updated the FY 2013 federal
prospective payment rates, the CMG
relative weights, and the average length
of stay values. For more information on
the updates for FY 2013, please refer to
the FY 2013 IRF PPS notice (77 FR
44618).
In the FY 2014 IRF PPS final rule (78
FR 47860), we updated the federal
prospective payment rates, the CMG
relative weights, and the outlier
threshold amount. We also updated the
facility-level adjustment factors using an
enhanced estimation methodology,
revised the list of diagnosis codes that
count toward an IRF’s 60 percent rule
compliance calculation to determine
‘‘presumptive compliance,’’ revised
sections of the Inpatient Rehabilitation
Facility-Patient Assessment Instrument
(IRF–PAI), revised requirements for
acute care hospitals that have IRF units,
clarified the IRF regulation text
regarding limitation of review, updated
references to previously changed
sections in the regulations text, and
revised and updated quality measures
and reporting requirements under the
IRF quality reporting program. For more
information on the policy changes
implemented for FY 2014, please refer
to the FY 2014 IRF PPS final rule (78 FR
47860), in which we published the final
FY 2014 IRF federal prospective
payment rates.
In the FY 2015 IRF PPS final rule (79
FR 45872), we updated the federal
prospective payment rates, the CMG
relative weights, and the outlier
threshold amount. We also further
revised the list of diagnosis codes that

VerDate Sep<11>2014

19:36 Apr 22, 2016

Jkt 238001

count toward an IRF’s 60 percent rule
compliance calculation to determine
‘‘presumptive compliance,’’ revised
sections of the IRF–PAI, and revised and
updated quality measures and reporting
requirements under the IRF quality
reporting program. For more
information on the policy changes
implemented for FY 2015, please refer
to the FY 2015 IRF PPS final rule (79 FR
45872) and the FY 2015 IRF PPS
correction notice (79 FR 59121).
In the FY 2016 IRF PPS final rule (80
FR 47036), we updated the federal
prospective payment rates, the CMG
relative weights, and the outlier
threshold amount. We also adopted an
IRF-specific market basket that reflects
the cost structures of only IRF
providers, a blended one-year transition
wage index based on the adoption of
new OMB area delineations, a 3-year
phase-out of the rural adjustment for
certain IRFs due to the new OMB area
delineations, and revisions and updates
to the IRF QRP. For more information
on the policy changes implemented for
FY 2016, please refer to the FY 2016 IRF
PPS final rule (80 FR 47036).
B. Provisions of the Affordable Care Act
Affecting the IRF PPS in FY 2012 and
Beyond
The Affordable Care Act included
several provisions that affect the IRF
PPS in FYs 2012 and beyond. In
addition to what was previously
discussed, section 3401(d) of the
Affordable Care Act also added section
1886(j)(3)(C)(ii)(I) (providing for a
‘‘productivity adjustment’’ for fiscal
year 2012 and each subsequent fiscal
year). The productivity adjustment for
FY 2017 is discussed in section V.B. of
this proposed rule. Section 3401(d) of
the Affordable Care Act requires an
additional 0.75 percentage point
adjustment to the IRF increase factor for
FY 2017, as discussed in section V.B. of
this proposed rule. Section
1886(j)(3)(C)(ii)(II) of the Act notes that
the application of these adjustments to
the market basket update may result in
an update that is less than 0.0 for a fiscal
year and in payment rates for a fiscal
year being less than such payment rates
for the preceding fiscal year.
Section 3004(b) of the Affordable Care
Act also addressed the IRF PPS
program. It reassigned the previously
designated section 1886(j)(7) of the Act
to section 1886(j)(8) and inserted a new
section 1886(j)(7), which contains
requirements for the Secretary to
establish a quality reporting program for
IRFs. Under that program, data must be
submitted in a form and manner and at
a time specified by the Secretary.
Beginning in FY 2014, section

PO 00000

Frm 00006

Fmt 4701

Sfmt 4702

1886(j)(7)(A)(i) of the Act requires the
application of a 2 percentage point
reduction of the applicable market
basket increase factor for IRFs that fail
to comply with the quality data
submission requirements. Application
of the 2 percentage point reduction may
result in an update that is less than 0.0
for a fiscal year and in payment rates for
a fiscal year being less than such
payment rates for the preceding fiscal
year. Reporting-based reductions to the
market basket increase factor will not be
cumulative; they will only apply for the
FY involved.
Under section 1886(j)(7)(D)(i) and (ii)
of the Act, the Secretary is generally
required to select quality measures for
the IRF quality reporting program from
those that have been endorsed by the
consensus-based entity which holds a
performance measurement contract
under section 1890(a) of the Act. This
contract is currently held by the
National Quality Forum (NQF). So long
as due consideration is given to
measures that have been endorsed or
adopted by a consensus-based
organization, section 1886(j)(7)(D)(ii) of
the Act authorizes the Secretary to
select non-endorsed measures for
specified areas or medical topics when
there are no feasible or practical
endorsed measure(s).
Section 1886(j)(7)(E) of the Act
requires the Secretary to establish
procedures for making the IRF PPS
quality reporting data available to the
public. In so doing, the Secretary must
ensure that IRFs have the opportunity to
review any such data prior to its release
to the public.
C. Operational Overview of the Current
IRF PPS
As described in the FY 2002 IRF PPS
final rule, upon the admission and
discharge of a Medicare Part A Fee-forService (FFS) patient, the IRF is
required to complete the appropriate
sections of a patient assessment
instrument (PAI), designated as the IRF–
PAI. In addition, beginning with IRF
discharges occurring on or after October
1, 2009, the IRF is also required to
complete the appropriate sections of the
IRF–PAI upon the admission and
discharge of each Medicare Advantage
(MA) (formerly called Medicare Part C)
patient, as described in the FY 2010 IRF
PPS final rule. All required data must be
electronically encoded into the IRF–PAI
software product. Generally, the
software product includes patient
classification programming called the
Grouper software. The Grouper software
uses specific IRF–PAI data elements to
classify (or group) patients into distinct

E:\FR\FM\25APP2.SGM

25APP2

asabaliauskas on DSK3SPTVN1PROD with PROPOSALS

Federal Register / Vol. 81, No. 79 / Monday, April 25, 2016 / Proposed Rules
CMGs and account for the existence of
any relevant comorbidities.
The Grouper software produces a 5character CMG number. The first
character is an alphabetic character that
indicates the comorbidity tier. The last
4 characters are numeric characters that
represent the distinct CMG number.
Free downloads of the Inpatient
Rehabilitation Validation and Entry
(IRVEN) software product, including the
Grouper software, are available on the
CMS Web site at http://www.cms.gov/
Medicare/Medicare-Fee-for-ServicePayment/InpatientRehabFacPPS/
Software.html.
Once a Medicare FFS Part A patient
is discharged, the IRF submits a
Medicare claim as a Health Insurance
Portability and Accountability Act of
1996 (Pub. L. 104–191, enacted on
August 21, 1996) (HIPAA) compliant
electronic claim or, if the
Administrative Simplification
Compliance Act of 2002 (Pub. L. 107–
105, enacted on December 27, 2002)
(ASCA) permits, a paper claim (a UB–
04 or a CMS–1450 as appropriate) using
the five-character CMG number and
sends it to the appropriate Medicare
Administrative Contractor (MAC). In
addition, once a Medicare Advantage
patient is discharged, in accordance
with the Medicare Claims Processing
Manual, chapter 3, section 20.3 (Pub.
100–04), hospitals (including IRFs) must
submit an informational-only bill (Type
of Bill (TOB) 111), which includes
Condition Code 04 to their MAC. This
will ensure that the Medicare Advantage
days are included in the hospital’s
Supplemental Security Income (SSI)
ratio (used in calculating the IRF lowincome percentage adjustment) for fiscal
year 2007 and beyond. Claims
submitted to Medicare must comply
with both ASCA and HIPAA.
Section 3 of the ASCA amends section
1862(a) of the Act by adding paragraph
(22), which requires the Medicare
program, subject to section 1862(h) of
the Act, to deny payment under Part A
or Part B for any expenses for items or
services ‘‘for which a claim is submitted
other than in an electronic form
specified by the Secretary.’’ Section
1862(h) of the Act, in turn, provides that
the Secretary shall waive such denial in
situations in which there is no method
available for the submission of claims in
an electronic form or the entity
submitting the claim is a small provider.
In addition, the Secretary also has the
authority to waive such denial ‘‘in such
unusual cases as the Secretary finds
appropriate.’’ For more information, see
the ‘‘Medicare Program; Electronic
Submission of Medicare Claims’’ final
rule (70 FR 71008). Our instructions for

VerDate Sep<11>2014

19:36 Apr 22, 2016

Jkt 238001

the limited number of Medicare claims
submitted on paper are available at
http://www.cms.gov/manuals/
downloads/clm104c25.pdf.
Section 3 of the ASCA operates in the
context of the administrative
simplification provisions of HIPAA,
which include, among others, the
requirements for transaction standards
and code sets codified in 45 CFR, parts
160 and 162, subparts A and I through
R (generally known as the Transactions
Rule). The Transactions Rule requires
covered entities, including covered
health care providers, to conduct
covered electronic transactions
according to the applicable transaction
standards. (See the CMS program claim
memoranda at http://www.cms.gov/
ElectronicBillingEDITrans/ and listed in
the addenda to the Medicare
Intermediary Manual, Part 3, section
3600).
The MAC processes the claim through
its software system. This software
system includes pricing programming
called the ‘‘Pricer’’ software. The Pricer
software uses the CMG number, along
with other specific claim data elements
and provider-specific data, to adjust the
IRF’s prospective payment for
interrupted stays, transfers, short stays,
and deaths, and then applies the
applicable adjustments to account for
the IRF’s wage index, percentage of lowincome patients, rural location, and
outlier payments. For discharges
occurring on or after October 1, 2005,
the IRF PPS payment also reflects the
teaching status adjustment that became
effective as of FY 2006, as discussed in
the FY 2006 IRF PPS final rule (70 FR
47880).
D. Advancing Health Information
Exchange
The Department of Health & Human
Services (HHS) has a number of
initiatives designed to encourage and
support the adoption of health
information technology and to promote
nationwide health information exchange
to improve health care. As discussed in
the August 2013 Statement ‘‘Principles
and Strategies for Accelerating Health
Information Exchange’’ (available at
http://www.healthit.gov/sites/default/
files/acceleratinghieprinciples_
strategy.pdf). HHS believes that all
individuals, their families, their
healthcare and social service providers,
and payers should have consistent and
timely access to health information in a
standardized format that can be securely
exchanged between the patient,
providers, and others involved in the
individual’s care. Health IT that
facilitates the secure, efficient, and
effective sharing and use of health-

PO 00000

Frm 00007

Fmt 4701

Sfmt 4702

24183

related information when and where it
is needed is an important tool for
settings across the continuum of care,
including inpatient rehabilitation
facilities. The effective adoption and use
of health information exchange and
health IT tools will be essential as IRFs
seek to improve quality and lower costs
through value-based care.
The Office of the National
Coordinator for Health Information
Technology (ONC) has released a
document entitled ‘‘Connecting Health
and Care for the Nation: A Shared
Nationwide Interoperability Roadmap’’
(available at https://www.healthit.gov/
sites/default/files/hie-interoperability/
nationwide-interoperability-roadmapfinal-version-1.0.pdf). In the near term,
the Roadmap focuses on actions that
will enable individuals and providers
across the care continuum to send,
receive, find, and use a common set of
electronic clinical information at the
nationwide level by the end of 2017.
The Roadmap’s goals also align with the
Improving Medicare Post-Acute Care
Transformation Act of 2014 (Pub. L.
113–185) (IMPACT Act), which requires
assessment data to be standardized and
interoperable to allow for exchange of
the data.
The Roadmap identifies four critical
pathways that health IT stakeholders
should focus on now in order to create
a foundation for long-term success: (1)
Improve technical standards and
implementation guidance for priority
data domains and associated elements;
(2) rapidly shift and align federal, state,
and commercial payment policies from
FFS to value-based models to stimulate
the demand for interoperability; (3)
clarify and align federal and state
privacy and security requirements that
enable interoperability; and (4) align
and promote the use of consistent
policies and business practices that
support interoperability, in coordination
with stakeholders. In addition, ONC has
released the final version of the 2016
Interoperability Standards Advisory
(available at https://www.healthit.gov/
standards-advisory/2016), which
provides a list of the best available
standards and implementation
specifications to enable priority health
information exchange functions.
Providers, payers, and vendors are
encouraged to take these ‘‘best available
standards’’ into account as they
implement interoperable health
information exchange across the
continuum of care, including care
settings such as inpatient rehabilitation
facilities.
We encourage stakeholders to utilize
health information exchange and
certified health IT to effectively and

E:\FR\FM\25APP2.SGM

25APP2

24184

Federal Register / Vol. 81, No. 79 / Monday, April 25, 2016 / Proposed Rules

efficiently help providers improve
internal care delivery practices, engage
patients in their care, support
management of care across the
continuum, enable the reporting of
electronically specified clinical quality
measures (eCQMs), and improve
efficiencies and reduce unnecessary
costs. As adoption of certified health IT
increases and interoperability standards
continue to mature, HHS will seek to
reinforce standards through relevant
policies and programs.

asabaliauskas on DSK3SPTVN1PROD with PROPOSALS

II. Summary of Provisions of the
Proposed Rule
In this proposed rule, we propose to
update the IRF federal prospective
payment rates for FY 2017 and to revise
and update quality measures and
reporting requirements under the IRF
QRP.
The proposed updates to the IRF
federal prospective payment rates for FY
2017 are as follows:
• Update the FY 2017 IRF PPS
relative weights and average length of
stay values using the most current and
complete Medicare claims and cost
report data in a budget-neutral manner,
as discussed in section III of this
proposed rule.
• Describe the continued use of FY
2014 facility-level adjustment factors as
discussed in section IV of this proposed
rule.
• Update the FY 2017 IRF PPS
payment rates by the proposed market
basket increase factor, based upon the
most current data available, with a 0.75
percentage point reduction as required
by sections 1886(j)(3)(C)(ii)(II) and
1886(j)(3)(D)(v) of the Act and a
proposed productivity adjustment
required by section 1886(j)(3)(C)(ii)(I) of
the Act, as described in section V of this
proposed rule.
• Update the FY 2017 IRF PPS
payment rates by the FY 2017 wage
index and the labor-related share in a
budget-neutral manner, as discussed in
section V of this proposed rule.
• Describe the calculation of the IRF
standard payment conversion factor for
FY 2017, as discussed in section V of
this proposed rule.
• Update the outlier threshold
amount for FY 2017, as discussed in
section VI of this proposed rule.
• Update the cost-to-charge ratio
(CCR) ceiling and urban/rural average
CCRs for FY 2017, as discussed in
section VI of this proposed rule.
• Describe proposed revisions and
updates to quality measures and
reporting requirements under the
quality reporting program for IRFs in

VerDate Sep<11>2014

19:36 Apr 22, 2016

Jkt 238001

accordance with section 1886(j)(7) of the
Act, as discussed in section VII of this
proposed rule.
III. Proposed Update to the Case-Mix
Group (CMG) Relative Weights and
Average Length of Stay Values for FY
2017
As specified in § 412.620(b)(1), we
calculate a relative weight for each CMG
that is proportional to the resources
needed by an average inpatient
rehabilitation case in that CMG. For
example, cases in a CMG with a relative
weight of 2, on average, will cost twice
as much as cases in a CMG with a
relative weight of 1. Relative weights
account for the variance in cost per
discharge due to the variance in
resource utilization among the payment
groups, and their use helps to ensure
that IRF PPS payments support
beneficiary access to care, as well as
provider efficiency.
In this proposed rule, we propose to
update the CMG relative weights and
average length of stay values for FY
2017. As required by statute, we always
use the most recent available data to
update the CMG relative weights and
average lengths of stay. For FY 2017, we
propose to use the FY 2015 IRF claims
and FY 2014 IRF cost report data. These
data are the most current and complete
data available at this time. Currently,
only a small portion of the FY 2015 IRF
cost report data are available for
analysis, but the majority of the FY 2015
IRF claims data are available for
analysis.
In this proposed rule, we propose to
apply these data using the same
methodologies that we have used to
update the CMG relative weights and
average length of stay values each fiscal
year since we implemented an update to
the methodology to use the more
detailed CCR data from the cost reports
of IRF subprovider units of primary
acute care hospitals, instead of CCR data
from the associated primary care
hospitals, to calculate IRFs’ average
costs per case, as discussed in the FY
2009 IRF PPS final rule (73 FR 46372).
In calculating the CMG relative weights,
we use a hospital-specific relative value
method to estimate operating (routine
and ancillary services) and capital costs
of IRFs. The process used to calculate
the CMG relative weights for this
proposed rule is as follows:
Step 1. We estimate the effects that
comorbidities have on costs.
Step 2. We adjust the cost of each
Medicare discharge (case) to reflect the
effects found in the first step.

PO 00000

Frm 00008

Fmt 4701

Sfmt 4702

Step 3. We use the adjusted costs from
the second step to calculate CMG
relative weights, using the hospitalspecific relative value method.
Step 4. We normalize the FY 2017
CMG relative weights to the same
average CMG relative weight from the
CMG relative weights implemented in
the FY 2016 IRF PPS final rule (80 FR
47036).
Consistent with the methodology that
we have used to update the IRF
classification system in each instance in
the past, we propose to update the CMG
relative weights for FY 2017 in such a
way that total estimated aggregate
payments to IRFs for FY 2017 are the
same with or without the changes (that
is, in a budget-neutral manner) by
applying a budget neutrality factor to
the standard payment amount. To
calculate the appropriate budget
neutrality factor for use in updating the
FY 2017 CMG relative weights, we use
the following steps:
Step 1. Calculate the estimated total
amount of IRF PPS payments for FY
2017 (with no changes to the CMG
relative weights).
Step 2. Calculate the estimated total
amount of IRF PPS payments for FY
2017 by applying the proposed changes
to the CMG relative weights (as
discussed in this proposed rule).
Step 3. Divide the amount calculated
in step 1 by the amount calculated in
step 2 to determine the budget
neutrality factor (0.9990) that would
maintain the same total estimated
aggregate payments in FY 2017 with and
without the proposed changes to the
CMG relative weights.
Step 4. Apply the budget neutrality
factor (0.9990) to the FY 2016 IRF PPS
standard payment amount after the
application of the budget-neutral wage
adjustment factor.
In section V.E. of this proposed rule,
we discuss the proposed use of the
existing methodology to calculate the
proposed standard payment conversion
factor for FY 2017.
In Table 1, ‘‘Proposed Relative
Weights and Average Length of Stay
Values for Case-Mix Groups,’’ we
present the CMGs, the comorbidity tiers,
the corresponding relative weights, and
the average length of stay values for
each CMG and tier for FY 2017. The
average length of stay for each CMG is
used to determine when an IRF
discharge meets the definition of a
short-stay transfer, which results in a
per diem case level adjustment.

E:\FR\FM\25APP2.SGM

25APP2

24185

Federal Register / Vol. 81, No. 79 / Monday, April 25, 2016 / Proposed Rules
TABLE 1—PROPOSED RELATIVE WEIGHTS AND AVERAGE LENGTH OF STAY VALUES FOR CASE-MIX GROUPS
CMG Description
(M=motor, C=cognitive, A=age)

CMG
0101 .........
0102 .........
0103 .........
0104
0105
0106
0107
0108
0109

.........
.........
.........
.........
.........
.........

0110 .........
0201 .........
0202 .........
0203 .........
0204 .........
0205 .........
0206 .........
0207 .........
0301 .........
0302 .........
0303 .........
0304 .........
0401 .........
0402 .........
0403 .........
0404 .........
0405 .........
0501 .........
0502 .........
0503 .........
0504 .........
0505 .........
0506 .........
0601 .........
0602 .........
0603 .........
0604 .........
0701 .........
0702 .........

asabaliauskas on DSK3SPTVN1PROD with PROPOSALS

0703 .........
0704 .........
0801 .........
0802 .........
0803 .........
0804 .........

Stroke M>51.05 ..........................
Stroke M>44.45 and M<51.05
and C>18.5.
Stroke M>44.45 and M<51.05
and C<18.5.
Stroke M>38.85 and M<44.45 ...
Stroke M>34.25 and M<38.85 ...
Stroke M>30.05 and M<34.25 ...
Stroke M>26.15 and M<30.05 ...
Stroke M<26.15 and A>84.5 ......
Stroke M>22.35 and M<26.15
and A<84.5.
Stroke M<22.35 and A<84.5 ......
Traumatic brain injury M>53.35
and C>23.5.
Traumatic brain injury M>44.25
and M<53.35 and C>23.5.
Traumatic brain injury M>44.25
and C<23.5.
Traumatic brain injury M>40.65
and M<44.25.
Traumatic brain injury M>28.75
and M<40.65.
Traumatic brain injury M>22.05
and M<28.75.
Traumatic brain injury M<22.05
Non-traumatic
brain
injury
M>41.05.
Non-traumatic
brain
injury
M>35.05 and M<41.05.
Non-traumatic
brain
injury
M>26.15 and M<35.05.
Non-traumatic
brain
injury
M<26.15.
Traumatic spinal cord injury
M>48.45.
Traumatic spinal cord injury
M>30.35 and M<48.45.
Traumatic spinal cord injury
M>16.05 and M<30.35.
Traumatic spinal cord injury
M<16.05 and A>63.5.
Traumatic spinal cord injury
M<16.05 and A<63.5.
Non-traumatic spinal cord injury
M>51.35.
Non-traumatic spinal cord injury
M>40.15 and M<51.35.
Non-traumatic spinal cord injury
M>31.25 and M<40.15.
Non-traumatic spinal cord injury
M>29.25 and M<31.25.
Non-traumatic spinal cord injury
M>23.75 and M<29.25.
Non-traumatic spinal cord injury
M<23.75.
Neurological M>47.75 ................
Neurological
M>37.35
and
M<47.75.
Neurological
M>25.85
and
M<37.35.
Neurological M<25.85 ................
Fracture of lower extremity
M>42.15.
Fracture of lower extremity
M>34.15 and M<42.15.
Fracture of lower extremity
M>28.15 and M<34.15.
Fracture of lower extremity
M<28.15.
Replacement of lower extremity
joint M>49.55.
Replacement of lower extremity
joint M>37.05 and M<49.55.
Replacement of lower extremity
joint M>28.65 and M<37.05
and A>83.5.
Replacement of lower extremity
joint M>28.65 and M<37.05
and A<83.5.

VerDate Sep<11>2014

19:36 Apr 22, 2016

Jkt 238001

Relative weight
Tier 1

Tier 2

Tier 3

Average length of stay
None

Tier 1

Tier 2

Tier 3

None

0.8007
1.0117

0.7158
0.9044

0.6527
0.8247

0.6228
0.7869

8
11

9
12

9
10

8
10

1.1804

1.0552

0.9622

0.9181

1.2603
1.4562
1.6306
1.8168
2.2856
2.0579

1.1266
1.3018
1.4576
1.6241
2.0432
1.8396

1.0274
1.1871
1.3293
1.4811
1.8632
1.6776

0.9803
1.1327
1.2683
1.4132
1.7779
1.6007

12
14
16
17
21
19

12
15
16
19
22
20

12
14
15
17
21
18

12
14
15
17
20
19

2.7293
0.7826

2.4398
0.6402

2.2249
0.5775

2.1230
0.5385

29
8

27
8

24
8

24
7

1.0939

0.8948

0.8072

0.7527

1.2187

0.9969

0.8993

0.8385

1.3419

1.0977

0.9902

0.9233

1.6233

1.3279

1.1979

1.1170

1.9247

1.5744

1.4202

1.3243

2.5314
1.1417

2.0708
0.9423

1.8680
0.8561

1.7418
0.8003

31
10

23
11

20
10

19
10

1.4064

1.1608

1.0546

0.9858

1.6478

1.3600

1.2356

1.1550

2.1328

1.7604

1.5993

1.4949

0.9816

0.8589

0.7927

0.7201

1.4090

1.2330

1.1379

1.0337

2.2221

1.9445

1.7946

1.6303

3.8903

3.4042

3.1418

2.8541

3.4259

2.9979

2.7668

2.5134

0.8605

0.6793

0.6459

0.5815

1.1607

0.9162

0.8712

0.7843

1.4538

1.1476

1.0912

0.9824

1.7071

1.3475

1.2813

1.1535

1.9596

1.5468

1.4708

1.3242

2.7126

2.1412

2.0360

1.8330

1.0371
1.3356

0.8203
1.0563

0.7581
0.9762

0.6940
0.8936

10
12

9
12

9
11

1.6450

1.3010

1.2023

1.1007

2.1787
1.0013

1.7232
0.8151

1.5924
0.7777

1.4578
0.7065

20
10

18
9

16
9

1.2773

1.0398

0.9921

0.9013

1.5395

1.2533

1.1958

1.0863

1.9955

1.6245

1.5500

1.4081

0.7944

0.6410

0.5920

0.5443

1.0351

0.8353

0.7714

0.7093

1.3845

1.1173

1.0318

0.9488

1.2461

1.0055

0.9286

0.8539

PO 00000

Frm 00009

Fmt 4701

Sfmt 4702

E:\FR\FM\25APP2.SGM

25APP2

24186

Federal Register / Vol. 81, No. 79 / Monday, April 25, 2016 / Proposed Rules

TABLE 1—PROPOSED RELATIVE WEIGHTS AND AVERAGE LENGTH OF STAY VALUES FOR CASE-MIX GROUPS—Continued
CMG Description
(M=motor, C=cognitive, A=age)

CMG
0805 .........
0806 .........
0901 .........
0902 .........
0903 .........
0904 .........
1001 .........
1002 .........
1003 .........
1101 .........
1102 .........
1201 .........
1202 .........
1203 .........
1301 .........
1302 .........
1303 .........
1401
1402
1403
1404
1501
1502

.........
.........
.........
.........
.........
.........

1503 .........
1504 .........
1601 .........
1602 .........
1603 .........
1701 .........
1702 .........
1703 .........
1704 .........
1801 .........
1802 .........
1803 .........

asabaliauskas on DSK3SPTVN1PROD with PROPOSALS

1901 .........
1902 .........
1903 .........
2001 .........
2002 .........
2003 .........
2004 .........
2101 .........
5001 .........
5101 .........
5102 .........

Replacement of lower extremity
joint M>22.05 and M<28.65.
Replacement of lower extremity
joint M<22.05.
Other orthopedic M>44.75 .........
Other orthopedic M>34.35 and
M<44.75.
Other orthopedic M>24.15 and
M<34.35.
Other orthopedic M<24.15 .........
Amputation,
lower
extremity
M>47.65.
Amputation,
lower
extremity
M>36.25 and M<47.65.
Amputation,
lower
extremity
M<36.25.
Amputation, non-lower extremity
M>36.35.
Amputation, non-lower extremity
M<36.35.
Osteoarthritis M>37.65 ...............
Osteoarthritis
M>30.75
and
M<37.65.
Osteoarthritis M<30.75 ...............
Rheumatoid,
other
arthritis
M>36.35.
Rheumatoid,
other
arthritis
M>26.15 and M<36.35.
Rheumatoid,
other
arthritis
M<26.15.
Cardiac M>48.85 ........................
Cardiac M>38.55 and M<48.85
Cardiac M>31.15 and M<38.55
Cardiac M<31.15 ........................
Pulmonary M>49.25 ...................
Pulmonary
M>39.05
and
M<49.25.
Pulmonary
M>29.15
and
M<39.05.
Pulmonary M<29.15 ...................
Pain syndrome M>37.15 ............
Pain syndrome M>26.75 and
M<37.15.
Pain syndrome M<26.75 ............
Major multiple trauma without
brain or spinal cord injury
M>39.25.
Major multiple trauma without
brain or spinal cord injury
M>31.05 and M<39.25.
Major multiple trauma without
brain or spinal cord injury
M>25.55 and M<31.05.
Major multiple trauma without
brain or spinal cord injury
M<25.55.
Major multiple trauma with brain
or spinal cord injury M>40.85.
Major multiple trauma with brain
or spinal cord injury M>23.05
and M<40.85.
Major multiple trauma with brain
or spinal cord injury M<23.05.
Guillian Barre M>35.95 ..............
Guillian Barre M>18.05 and
M<35.95.
Guillian Barre M<18.05 ..............
Miscellaneous M>49.15 .............
Miscellaneous M>38.75 and
M<49.15.
Miscellaneous M>27.85 and
M<38.75.
Miscellaneous M<27.85 .............
Burns M>0 ..................................
Short-stay cases, length of stay
is 3 days or fewer.
Expired, orthopedic, length of
stay is 13 days or fewer.
Expired, orthopedic, length of
stay is 14 days or more.

VerDate Sep<11>2014

19:36 Apr 22, 2016

Jkt 238001

Relative weight
Tier 1

Tier 2

Tier 3

Average length of stay
None

Tier 1

Tier 2

Tier 3

None

1.4829

1.1966

1.1051

1.0162

1.7995

1.4521

1.3410

1.2331

0.9866
1.2620

0.7948
1.0166

0.7350
0.9402

0.6689
0.8556

11
12

10
12

9
11

8
10

1.5866

1.2780

1.1819

1.0757

2.0099
1.0742

1.6190
0.9500

1.4973
0.8207

1.3627
0.7414

18
11

16
10

16
9

1.3925

1.2314

1.0639

0.9611

1.9643

1.7371

1.5008

1.3558

1.3216

1.1917

0.9756

0.8848

1.8958

1.7094

1.3994

1.2692

1.0418
1.2108

1.0235
1.1895

0.9300
1.0808

0.8239
0.9576

10
12

11
13

11
12

10
11

1.5410
1.1826

1.5140
0.9291

1.3756
0.8691

1.2187
0.8014

14
13

17
10

15
10

14
10

1.6264

1.2778

1.1954

1.1021

2.0043

1.5746

1.4731

1.3582

0.8643
1.1810
1.4079
1.7799
1.0124
1.2770

0.7307
0.9985
1.1903
1.5048
0.8580
1.0823

0.6621
0.9047
1.0785
1.3635
0.7912
0.9980

0.6007
0.8208
0.9785
1.2371
0.7466
0.9418

9
11
13
17
10
11

8
11
13
16
9
11

8
10
12
15
9
11

8
10
11
14
8
10

1.5560

1.3187

1.2160

1.1475

1.9351
0.9845
1.2824

1.6400
0.8935
1.1639

1.5123
0.8304
1.0817

1.4271
0.7671
0.9993

19
9
12

17
9
13

15
10
12

14
9
12

1.6089
1.1329

1.4602
0.9223

1.3571
0.8471

1.2537
0.7644

13
16

17
10

15
10

14
10

1.4266

1.1614

1.0667

0.9626

1.7041

1.3873

1.2743

1.1498

2.1883

1.7815

1.6363

1.4766

1.3252

1.0733

0.9440

0.8290

1.8549

1.5023

1.3214

1.1604

2.8949

2.3447

2.0623

1.8110

1.1743
2.1344

1.0503
1.9090

0.9267
1.6843

0.9127
1.6589

13
19

13
22

11
19

3.4585
0.9216
1.2117

3.0934
0.7549
0.9926

2.7292
0.6924
0.9103

2.6881
0.6268
0.8241

50
9
12

31
9
11

32
8
11

28
8
10

1.5152

1.2412

1.1383

1.0305

1.9423
1.6749
....................

1.5911
1.6749
....................

1.4591
1.4953
....................

1.3210
1.3672
0.1586

19
24
....................

17
18
....................

16
16
....................

15
17
2

....................

0.6791

....................

1.4216

....................

PO 00000

Frm 00010

Fmt 4701

Sfmt 4702

E:\FR\FM\25APP2.SGM

25APP2

24187

Federal Register / Vol. 81, No. 79 / Monday, April 25, 2016 / Proposed Rules

TABLE 1—PROPOSED RELATIVE WEIGHTS AND AVERAGE LENGTH OF STAY VALUES FOR CASE-MIX GROUPS—Continued

5103 .........
5104 .........

Relative weight

CMG Description
(M=motor, C=cognitive, A=age)

CMG

Expired,
of stay
Expired,
of stay

not orthopedic, length
is 15 days or fewer.
not orthopedic, length
is 16 days or more.

Tier 1

Tier 2

Tier 3

....................

Generally, updates to the CMG
relative weights result in some increases
and some decreases to the CMG relative
weight values. Table 2 shows how we
estimate that the application of the
proposed revisions for FY 2017 would
affect particular CMG relative weight
values, which would affect the overall
distribution of payments within CMGs
and tiers. Note that, because we propose
to implement the CMG relative weight
revisions in a budget-neutral manner (as
previously described), total estimated
aggregate payments to IRFs for FY 2017
would not be affected as a result of the
proposed CMG relative weight
revisions. However, the proposed
revisions would affect the distribution
of payments within CMGs and tiers.

TABLE 2—DISTRIBUTIONAL EFFECTS
OF THE PROPOSED CHANGES TO
THE CMG RELATIVE WEIGHTS
[FY 2016 Values compared with FY 2017
values]

Tier 1

Tier 2

Tier 3

0.8033

....................

2.1360

....................

discharges) were classified into this
CMG and tier.
The largest decrease in a CMG relative
weight value affecting the largest
number of IRF cases would be a 1.4
percent decrease in the CMG relative
weight for CMG 0110—Stroke, with a
motor score less than 22.35 and age less
than 84.5 -in the ‘‘no comorbidity’’ tier.
In the FY 2015 IRF claims data, this
change would have affected 13,587
cases (3.5 percent of all IRF cases).
The proposed changes in the average
length of stay values for FY 2017,
compared with the FY 2016 average
length of stay values, are small and do
not show any particular trends in IRF
length of stay patterns.
We invite public comment on our
proposed updates to the CMG relative
weights and average length of stay
values for FY 2017.
IV. Facility-Level Adjustment Factors

Section 1886(j)(3)(A)(v) of the Act
confers broad authority upon the
Secretary to adjust the per unit payment
rate by such factors as the Secretary
determines are necessary to properly
Increased by 15%
or more ..............
0
0.0 reflect variations in necessary costs of
Increased by betreatment among rehabilitation
tween 5% and
facilities. Under this authority, we
15% ...................
797
0.2 currently adjust the federal prospective
Changed by less
payment amount associated with a CMG
than 5% .............
391,183
99.5
to account for facility-level
Decreased by becharacteristics such as an IRF’s LIP,
tween 5% and
15% ...................
1,237
0.3 teaching status, and location in a rural
area, if applicable, as described in
Decreased by 15%
or more ..............
14
0.0 § 412.624(e).
Based on the substantive changes to
As Table 2 shows, 99.5 percent of all
the facility-level adjustment factors that
IRF cases are in CMGs and tiers that
were adopted in the FY 2014 final rule
would experience less than a 5 percent
(78 FR 47860, 47868 through 47872), in
change (either increase or decrease) in
the FY 2015 final rule (79 FR 45872,
the CMG relative weight value as a
45882 through 45883), we froze the
result of the proposed revisions for FY
facility-level adjustment factors at the
2017. The largest estimated increase in
FY 2014 levels for FY 2015 and all
the proposed CMG relative weight
subsequent years (unless and until we
values that affects the largest number of propose to update them again through
IRF discharges would be a 0.1 percent
future notice-and-comment rulemaking).
increase in the CMG relative weight
For FY 2017, we will continue to hold
value for CMG 0704—Fracture of lower
the adjustment factors at the FY 2014
extremity, with a motor score less than
levels as we continue to monitor the
28.15-in the ‘‘no comorbidity’’ tier. In
most current IRF claims data available
the FY 2015 claims data, 18,696 IRF
and continue to evaluate and monitor
discharges (4.8 percent of all IRF
the effects of the FY 2014 changes.
Percentage change

asabaliauskas on DSK3SPTVN1PROD with PROPOSALS

Average length of stay
None

VerDate Sep<11>2014

Number
of cases
affected

19:36 Apr 22, 2016

Percentage
of cases
affected

Jkt 238001

PO 00000

Frm 00011

Fmt 4701

Sfmt 4702

None

V. Proposed FY 2017 IRF PPS Payment
Update
A. Background
Section 1886(j)(3)(C) of the Act
requires the Secretary to establish an
increase factor that reflects changes over
time in the prices of an appropriate mix
of goods and services included in the
covered IRF services, which is referred
to as a market basket index. According
to section 1886(j)(3)(A)(i) of the Act, the
increase factor shall be used to update
the IRF federal prospective payment
rates for each FY. Section
1886(j)(3)(C)(ii)(I) of the Act requires the
application of a productivity
adjustment, as described below. In
addition, sections 1886(j)(3)(C)(ii)(II)
and 1886(j)(3)(D)(v) of the Act require
the application of a 0.75 percentage
point reduction to the market basket
increase factor for FY 2017. Thus, in
this proposed rule, we propose to
update the IRF PPS payments for FY
2017 by a market basket increase factor
as required by section 1886(j)(3)(C) of
the Act, with a productivity adjustment
as required by section 1886(j)(3)(C)(ii)(I)
of the Act, and a 0.75 percentage point
reduction as required by sections
1886(j)(3)(C)(ii)(II) and 1886(j)(3)(D)(v)
of the Act.
For FY 2015, IRF PPS payments were
updated using the 2008-based RPL
market basket. Beginning with the FY
2016 IRF PPS, we created and adopted
a stand-alone IRF market basket, which
was referred to as the 2012-based IRF
market basket, reflecting the operating
and capital cost structures for
freestanding IRFs and hospital-based
IRFs. The general structure of the 2012based IRF market basket is similar to the
2008-based RPL market basket;
however, we made several notable
changes. In developing the 2012-based
IRF market basket, we derived cost
weights from Medicare cost report data
for both freestanding and hospital-based
IRFs (the 2008-based RPL market basket
was based on freestanding data only),
incorporated the 2007 Input-Output
data from the Bureau of Economic
Analysis (the 2008-based RPL market
basket was based on the 2002 InputOutput data); used new price proxy
blends for two cost categories (Fuel, Oil,

E:\FR\FM\25APP2.SGM

25APP2

24188

Federal Register / Vol. 81, No. 79 / Monday, April 25, 2016 / Proposed Rules

asabaliauskas on DSK3SPTVN1PROD with PROPOSALS

and Gasoline and Medical Instruments);
added one additional cost category
(Installation, Maintenance, and Repair),
which was previously included in the
residual All Other Services: LaborRelated cost category of the 2008-based
RPL market basket; and eliminated three
cost categories (Apparel, Machinery &
Equipment, and Postage). The FY 2016
IRF PPS final rule (80 FR 47046 through
47068) contains a complete discussion
of the development of the 2012-based
IRF market basket.
B. Proposed FY 2017 Market Basket
Update and Productivity Adjustment
For FY 2017, we are proposing to use
the same methodology described in the
FY 2016 IRF PPS final rule (80 FR
47066) to compute the FY 2017 market
basket increase factor to update the IRF
PPS base payment rate. Consistent with
historical practice, we are proposing to
estimate the market basket update for
the IRF PPS based on IHS Global
Insight’s forecast using the most recent
available data. IHS Global Insight (IGI),
Inc. is a nationally recognized economic
and financial forecasting firm with
which CMS contracts to forecast the
components of the market baskets and
multifactor productivity (MFP).
Based on IGI’s first quarter 2016
forecast with historical data through the
fourth quarter of 2015, the projected
2012-based IRF market basket increase
factor for FY 2017 would be 2.7 percent.
Therefore, consistent with our historical
practice of estimating market basket
increases based on the best available
data, we are proposing a market basket
increase factor of 2.7 percent for FY
2017. We are also proposing that if more
recent data are subsequently available
(for example, a more recent estimate of
the market basket update), we would
use such data to determine the FY 2017
update in the final rule.
According to section 1886(j)(3)(C)(i) of
the Act, the Secretary shall establish an
increase factor based on an appropriate
percentage increase in a market basket
of goods and services. Section
1886(j)(3)(C)(ii) of the Act then requires
that, after establishing the increase
factor for a FY, the Secretary shall
reduce such increase factor for FY 2012
and each subsequent FY, by the
productivity adjustment described in
section 1886(b)(3)(B)(xi)(II) of the Act.
Section 1886(b)(3)(B)(xi)(II) of the Act
sets forth the definition of this
productivity adjustment. The statute
defines the productivity adjustment to
be equal to the 10-year moving average
of changes in annual economy-wide
private nonfarm business MFP (as
projected by the Secretary for the 10year period ending with the applicable

VerDate Sep<11>2014

19:36 Apr 22, 2016

Jkt 238001

FY, year, cost reporting period, or other
annual period) (the ‘‘MFP adjustment’’).
The BLS publishes the official measure
of private nonfarm business MFP. Please
see http://www.bls.gov/mfp for the BLS
historical published MFP data. A
complete description of the MFP
projection methodology is available on
the CMS Web site at http://
www.cms.gov/Research-Statistics-Dataand-Systems/Statistics-Trends-andReports/MedicareProgramRatesStats/
MarketBasketResearch.html.
Using IGI’s first quarter 2016 forecast,
the MFP adjustment for FY 2017 (the
10-year moving average of MFP for the
period ending FY 2017) is currently
projected to be 0.5 percent. Thus, in
accordance with section 1886(j)(3)(C) of
the Act, we are proposing to base the FY
2017 market basket update, which is
used to determine the applicable
percentage increase for the IRF
payments, on the most recent estimate
of the 2012-based IRF market basket. We
are proposing to then reduce this
percentage increase by the most up-todate estimate of the MFP adjustment for
FY 2017 of 0.5 percentage point (the 10year moving average of MFP for the
period ending FY 2017 based on IGI’s
first quarter 2016 forecast). Following
application of the MFP, we are
proposing to further reduce the
applicable percentage increase by 0.75
percentage point, as required by
sections 1886(j)(3)(C)(ii)(II) and
1886(j)(3)(D)(v) of the Act. Therefore,
the estimate of the FY 2017 IRF update
for the proposed rule is 1.45 percent (2.7
percent market basket update, less 0.5
percentage point MFP adjustment, less
0.75 percentage point legislative
adjustment). Furthermore, we propose
that if more recent data are subsequently
available (for example, a more recent
estimate of the market basket update
and MFP adjustment), we would use
such data to determine the FY 2017
market basket update and MFP
adjustment in the final rule.
For FY 2017, the Medicare Payment
Advisory Commission (MedPAC)
recommends that a 0-percent update be
applied to IRF PPS payment rates. As
discussed, and in accordance with
sections 1886(j)(3)(C) and 1886(j)(3)(D)
of the Act, the Secretary is proposing to
update the IRF PPS payment rates for
FY 2017 by an adjusted market basket
increase factor of 1.45 percent, as
section 1886(j)(3)(C) of the Act does not
provide the Secretary with the authority
to apply a different update factor to IRF
PPS payment rates for FY 2017.

PO 00000

Frm 00012

Fmt 4701

Sfmt 4702

C. Proposed Labor-Related Share for FY
2017
Section 1886(j)(6) of the Act specifies
that the Secretary is to adjust the
proportion (as estimated by the
Secretary from time to time) of
rehabilitation facilities’ costs which are
attributable to wages and wage-related
costs of the prospective payment rates
computed under section 1886(j)(3) for
area differences in wage levels by a
factor (established by the Secretary)
reflecting the relative hospital wage
level in the geographic area of the
rehabilitation facility compared to the
national average wage level for such
facilities. 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 continue to
classify a cost category as labor-related
if the costs are labor-intensive and vary
with the local labor market.
Based on our definition of the laborrelated share and the cost categories in
the 2012-based IRF market basket, we
propose to include in the labor-related
share for FY 2017 the sum of the FY
2017 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 2012-based
IRF market basket. For more details
regarding the methodology for
determining specific cost categories for
inclusion in the 2012-based IRF laborrelated share, see the FY 2016 IRF final
rule (80 FR 47066 through 47068).
Using this proposed method and the
IHS Global Insight, Inc. first quarter
2016 forecast for the 2012-based IRF
market basket, the proposed IRF laborrelated share for FY 2017 is the sum of
the FY 2017 relative importance of each
labor-related cost category. The relative
importance reflects the different rates of
price change for these cost categories
between the base year (FY 2012) and FY
2017.
The sum of the relative importance for
FY 2017 operating costs (Wages and
Salaries, Employee Benefits,
Professional Fees: Labor-related,
Administrative and Facilities Support
Services, Installation Maintenance &
Repair Services, and All Other: Laborrelated Services) using the 2012-based
IRF market basket is 67.1 percent, as
shown in Table 3.
We propose that the portion of Capital
that is influenced by the local labor
market is estimated to be 46 percent.
Since the relative importance for

E:\FR\FM\25APP2.SGM

25APP2

Federal Register / Vol. 81, No. 79 / Monday, April 25, 2016 / Proposed Rules
Capital-Related Costs is 8.4 percent of
the 2012-based IRF market basket in FY
2017, we propose to take 46 percent of
8.4 percent to determine the laborrelated share of Capital for FY 2017. The
result would be 3.9 percent, which we
propose to add to 67.1 percent for the

operating cost amount to determine the
total proposed labor-related share for FY
2017. Thus, the labor-related share that
we are proposing to use for IRF PPS in
FY 2017 would be 71.0 percent. By
comparison, the FY 2016 labor-related
share under the 2012-based IRF market

24189

basket was also 71.0 percent.
Furthermore, we propose that if more
recent data are subsequently available
(for example, a more recent estimate of
the labor-related share), we would use
such data to determine the FY 2017 IRF
labor-related share in the final rule.

TABLE 3—IRF LABOR-RELATED SHARE
FY 2017 proposed
labor-related
share 1

FY 2016 final
labor related
share 2

Wages and Salaries ................................................................................................................................
Employee Benefits ...................................................................................................................................
Professional Fees: Labor-related ............................................................................................................
Administrative and Facilities Support Services .......................................................................................
Installation, Maintenance, and Repair .....................................................................................................
All Other: Labor-related Services ............................................................................................................

47.7
11.4
3.5
0.8
1.9
1.8

47.6
11.4
3.5
0.8
2.0
1.8

Subtotal .............................................................................................................................................
Labor-related portion of capital (46%) .....................................................................................................

67.1
3.9

Total Labor-Related Share ........................................................................................................

71.0

1 Based

on the 2012-based IRF Market Basket, IHS Global Insight, Inc. 1st quarter 2016 forecast.
Register 80 FR 47068.

2 Federal

D. Proposed Wage Adjustment

asabaliauskas on DSK3SPTVN1PROD with PROPOSALS

1. Background
Section 1886(j)(6) of the Act requires
the Secretary to adjust the proportion of
rehabilitation facilities’ costs
attributable to wages and wage-related
costs (as estimated by the Secretary from
time to time) by a factor (established by
the Secretary) reflecting the relative
hospital wage level in the geographic
area of the rehabilitation facility
compared to the national average wage
level for those facilities. The Secretary
is required to update the IRF PPS wage
index on the basis of information
available to the Secretary on the wages
and wage-related costs to furnish
rehabilitation services. Any adjustment
or updates made under section
1886(j)(6) of the Act for a FY are made
in a budget-neutral manner.
For FY 2017, we propose to maintain
the policies and methodologies
described in the FY 2016 IRF PPS final
rule (80 FR 47036, 47068 through
47075) related to the labor market area
definitions and the wage index
methodology for areas with wage data.
Thus, we propose to use the CBSA labor
market area definitions and the FY 2016
pre-reclassification and pre-floor
hospital wage index data. The current
statistical areas which were
implemented in FY 2016 are based on
OMB standards published on February
28, 2013, in OMB Bulletin No. 13–01.
For FY 2017, we are continuing to use
the new OMB delineations that we
adopted beginning with FY 2016. In
accordance with section 1886(d)(3)(E) of

VerDate Sep<11>2014

19:36 Apr 22, 2016

Jkt 238001

the Act, the FY 2016 pre-reclassification
and pre-floor hospital wage index is
based on data submitted for hospital
cost reporting periods beginning on or
after October 1, 2011, and before
October 1, 2012 (that is, FY 2012 cost
report data).
The labor market designations made
by the OMB include some geographic
areas where there are no hospitals and,
thus, no hospital wage index data on
which to base the calculation of the IRF
PPS wage index. We propose to
continue to use the same methodology
discussed in the FY 2008 IRF PPS final
rule (72 FR 44299) to address those
geographic areas where there are no
hospitals and, thus, no hospital wage
index data on which to base the
calculation for the FY 2017 IRF PPS
wage index.

OMB delineations issued on February
28, 2013, in OMB Bulletin No. 13–01.
OMB Bulletin No. 13–01 established
revised delineations for Metropolitan
Statistical Areas, Micropolitan
Statistical Areas, and Combined
Statistical Areas in the United States
and Puerto Rico, and provided guidance
on the use of the delineations of these
statistical areas based on new standards
published on June 28, 2010, in the
Federal Register (75 FR 37246 through
37252). A copy of this bulletin may be
obtained at http://www.whitehouse.gov/
sites/default/files/omb/bulletins/2013/b13-01.pdf. For FY 2017, we are
continuing to use the new OMB
delineations that we adopted beginning
with FY 2016 to calculate the area wage
indexes and the transition periods,
which we discuss below.

2. Update

3. Transition Period

The wage index used for the IRF PPS
is calculated using the prereclassification and pre-floor acute care
hospital wage index data and is
assigned to the IRF on the basis of the
labor market area in which the IRF is
geographically located. IRF labor market
areas are delineated based on the CBSAs
established by the OMB. In the FY 2016
IRF PPS final rule (80 FR 47036, 47068),
we established an IRF wage index based
on FY 2011 acute care hospital wage
data to adjust the FY 2016 IRF payment
rates. We also adopted the revised
CBSAs set forth by OMB. The current
CBSA delineations (which were
implemented for the IRF PPS beginning
with FY 2016) are based on revised

In FY 2016, we applied a 1-year
blended wage index for all IRF
providers to mitigate the impact of the
wage index change due to the
implementation of the revised CBSA
delineations. In FY 2016, all IRF
providers received a blended wage
index using 50 percent of their FY 2016
wage index based on the revised OMB
CBSA delineations and 50 percent of
their FY 2016 wage index based on the
OMB delineations used in FY 2015. We
propose to maintain the policy
established in FY 2016 IRF PPS final
rule related to the blended one-year
transition wage index (80 FR 47036,
47073 through 47074). This 1-year
blended wage index became effective on

PO 00000

Frm 00013

Fmt 4701

Sfmt 4702

E:\FR\FM\25APP2.SGM

25APP2

24190

Federal Register / Vol. 81, No. 79 / Monday, April 25, 2016 / Proposed Rules

October 1, 2015, and expires on
September 30, 2016.
For FY 2016, in addition to the
blended wage index, we also adopted a
3-year budget neutral phase out of the
rural adjustment for FY 2015 rural IRFs
that became urban in FY 2016 under the
revised CBSA delineations. In FY 2016,
IRFs that were designated as rural in FY
2015 and became designated as urban in
FY 2016 received two-thirds of the 2015
rural adjustment of 14.9 percent. FY
2017 represents the second year of the
3-year phase out of the rural adjustment,
in which these same IRFs will receive
one-third of the 2015 rural adjustment
of 14.9 percent, as finalized in the FY
2016 IRF PPS final rule (80 FR 47036,
47073 through 47074).
For FY 2017, the proposed wage
index will be based solely on the
previously adopted revised CBSA
delineations and their respective wage
index (rather than on a blended wage
index). We are not proposing any
additional wage index transition
adjustments for IRF providers due to the
adoption of the new OMB delineations
in FY 2016, but will continue the 3-year
phase out of the rural adjustments for
IRF providers that changed from rural to
urban status that was finalized in the FY
2016 IFR PPS final rule (80 FR 47036,
47073 through 47074).
For a full discussion of our
implementation of the new OMB labor
market area delineations for the FY 2016
wage index, please refer to the FY 2016
IRF PPS final rule (80 FR 47036, 47068
through 47076). We are not proposing
any changes to this policy in this
proposed rule. For FY 2017, 19 IRFs that
were designated as rural in FY 2015 and
became designated as urban in FY 2016
will receive the proposed FY 2017 wage
index (based solely on the revised CBSA
delineations) and one-third of the FY
2015 rural adjustment of 14.9 percent
(80 FR 47036, 47073 through 47076).
The proposed wage index applicable to
FY 2017 is available on the CMS Web
site at http://www.cms.gov/Medicare/

Medicare-Fee-for-Service-Payment/
InpatientRehabFacPPS/Data-Files.html.
Table A is for urban areas, and Table B
is for rural areas.
To calculate the wage-adjusted facility
payment for the payment rates set forth
in this proposed rule, we multiply the
unadjusted federal payment rate for
IRFs by the FY 2017 labor-related share
based on the 2012-based IRF market
basket (71.0 percent) to determine the
labor-related portion of the standard
payment amount. A full discussion of
the calculation of the labor-related share
is located in section V.C of this
proposed rule. We then multiply the
labor-related portion by the applicable
IRF wage index from the tables in the
addendum to this proposed rule. These
tables are available through the Internet
on the CMS Web site at http://
www.cms.gov/Medicare/Medicare-Feefor-Service-Payment/InpatientRehab
FacPPS/Data-Files.html.
Adjustments or updates to the IRF
wage index made under section
1886(j)(6) of the Act must be made in a
budget-neutral manner. We propose to
calculate a budget-neutral wage
adjustment factor as established in the
FY 2004 IRF PPS final rule (68 FR
45689), codified at § 412.624(e)(1), as
described in the steps below. We
propose to use the listed steps to ensure
that the FY 2017 IRF standard payment
conversion factor reflects the proposed
update to the wage indexes (based on
the FY 2012 hospital cost report data)
and the labor-related share in a budgetneutral manner:
Step 1. Determine the total amount of
the estimated FY 2016 IRF PPS
payments, using the FY 2016 standard
payment conversion factor and the
labor-related share and the wage
indexes from FY 2016 (as published in
the FY 2016 IRF PPS final rule (80 FR
47036)).
Step 2. Calculate the total amount of
estimated IRF PPS payments using the
proposed FY 2017 standard payment
conversion factor and the proposed FY

2017 labor-related share and CBSA
urban and rural wage indexes.
Step 3. Divide the amount calculated
in step 1 by the amount calculated in
step 2. The resulting quotient is the
proposed FY 2017 budget-neutral wage
adjustment factor of 0.9992.
Step 4. Apply the proposed FY 2017
budget-neutral wage adjustment factor
from step 3 to the FY 2016 IRF PPS
standard payment conversion factor
after the application of the adjusted
market basket update to determine the
proposed FY 2017 standard payment
conversion factor.
We discuss the calculation of the
proposed standard payment conversion
factor for FY 2017 in section V.E of this
proposed rule.
We invite public comment on the
proposed IRF wage adjustment for FY
2017.
E. Description of the Proposed IRF
Standard Payment Conversion Factor
and Payment Rates for FY 2017
To calculate the proposed standard
payment conversion factor for FY 2017,
as illustrated in Table 4, we begin by
applying the proposed adjusted market
basket increase factor for FY 2017 that
was adjusted in accordance with
sections 1886(j)(3)(C) and (D) of the Act,
to the standard payment conversion
factor for FY 2016 ($15,478). Applying
the proposed 1.45 percent adjusted
market basket increase for FY 2017 to
the standard payment conversion factor
for FY 2016 of $15,478 yields a standard
payment amount of $15,702. Then, we
apply the proposed budget neutrality
factor for the FY 2017 wage index and
labor-related share of 0.9992, which
results in a proposed standard payment
amount of $15,690. We next apply the
proposed budget neutrality factors for
the revised CMG relative weights of
0.9990, which results in the proposed
standard payment conversion factor of
$15,674 for FY 2017.

TABLE 4—CALCULATIONS TO DETERMINE THE PROPOSED FY 2017 STANDARD PAYMENT CONVERSION FACTOR

asabaliauskas on DSK3SPTVN1PROD with PROPOSALS

Explanation for adjustment

Calculations

Standard Payment Conversion Factor for FY 2016 ......................................................................................................................
Market Basket Increase Factor for FY 2017 (2.7 percent), reduced by 0.5 percentage point for the productivity adjustment
as required by section 1886(j)(3)(C)(ii)(I) of the Act, and reduced by 0.75 percentage point in accordance with paragraphs
1886(j)(3)(C) and (D) of the Act .................................................................................................................................................
Budget Neutrality Factor for the Wage Index and Labor-Related Share ......................................................................................
Budget Neutrality Factor for the Revisions to the CMG Relative Weights ...................................................................................
Proposed FY 2017 Standard Payment Conversion Factor ...........................................................................................................

We invite public comment on the
proposed FY 2017 standard payment
conversion factor.

VerDate Sep<11>2014

19:36 Apr 22, 2016

Jkt 238001

After the application of the proposed
CMG relative weights described in
section III of this proposed rule to the

PO 00000

Frm 00014

Fmt 4701

Sfmt 4702

$15,478
× 1.0145
× 0.9992
× 0.9990
= $15,674

proposed FY 2017 standard payment
conversion factor ($15,674), the
resulting proposed unadjusted IRF

E:\FR\FM\25APP2.SGM

25APP2

Federal Register / Vol. 81, No. 79 / Monday, April 25, 2016 / Proposed Rules

24191

prospective payment rates for FY 2017
are shown in Table 5.

TABLE 5—PROPOSED FY 2017 PAYMENT RATES
Payment rate
tier 1

asabaliauskas on DSK3SPTVN1PROD with PROPOSALS

CMG
0101
0102
0103
0104
0105
0106
0107
0108
0109
0110
0201
0202
0203
0204
0205
0206
0207
0301
0302
0303
0304
0401
0402
0403
0404
0405
0501
0502
0503
0504
0505
0506
0601
0602
0603
0604
0701
0702
0703
0704
0801
0802
0803
0804
0805
0806
0901
0902
0903
0904
1001
1002
1003
1101
1102
1201
1202
1203
1301
1302
1303
1401
1402
1403
1404
1501
1502
1503

.........................................................................................
.........................................................................................
.........................................................................................
.........................................................................................
.........................................................................................
.........................................................................................
.........................................................................................
.........................................................................................
.........................................................................................
.........................................................................................
.........................................................................................
.........................................................................................
.........................................................................................
.........................................................................................
.........................................................................................
.........................................................................................
.........................................................................................
.........................................................................................
.........................................................................................
.........................................................................................
.........................................................................................
.........................................................................................
.........................................................................................
.........................................................................................
.........................................................................................
.........................................................................................
.........................................................................................
.........................................................................................
.........................................................................................
.........................................................................................
.........................................................................................
.........................................................................................
.........................................................................................
.........................................................................................
.........................................................................................
.........................................................................................
.........................................................................................
.........................................................................................
.........................................................................................
.........................................................................................
.........................................................................................
.........................................................................................
.........................................................................................
.........................................................................................
.........................................................................................
.........................................................................................
.........................................................................................
.........................................................................................
.........................................................................................
.........................................................................................
.........................................................................................
.........................................................................................
.........................................................................................
.........................................................................................
.........................................................................................
.........................................................................................
.........................................................................................
.........................................................................................
.........................................................................................
.........................................................................................
.........................................................................................
.........................................................................................
.........................................................................................
.........................................................................................
.........................................................................................
.........................................................................................
.........................................................................................
.........................................................................................

VerDate Sep<11>2014

19:36 Apr 22, 2016

Jkt 238001

PO 00000

Frm 00015

$12,550.17
15,857.39
18,501.59
19,753.94
22,824.48
25,558.02
28,476.52
35,824.49
32,255.52
42,779.05
12,266.47
17,145.79
19,101.90
21,032.94
25,443.60
30,167.75
39,677.16
17,895.01
22,043.91
25,827.62
33,429.51
15,385.60
22,084.67
34,829.20
60,976.56
53,697.56
13,487.48
18,192.81
22,786.86
26,757.09
30,714.77
42,517.29
16,255.51
20,934.19
25,783.73
34,148.94
15,694.38
20,020.40
24,130.12
31,277.47
12,451.43
16,224.16
21,700.65
19,531.37
23,242.97
28,205.36
15,463.97
19,780.59
24,868.37
31,503.17
16,837.01
21,826.05
30,788.44
20,714.76
29,714.77
16,329.17
18,978.08
24,153.63
18,536.07
25,492.19
31,415.40
13,547.04
18,510.99
22,067.42
27,898.15
15,868.36
20,015.70
24,388.74

Fmt 4701

Sfmt 4702

Payment rate
tier 2

Payment rate
tier 3

$11,219.45
14,175.57
16,539.20
17,658.33
20,404.41
22,846.42
25,456.14
32,025.12
28,833.89
38,241.43
10,034.49
14,025.10
15,625.41
17,205.35
20,813.50
24,677.15
32,457.72
14,769.61
18,194.38
21,316.64
27,592.51
13,462.40
19,326.04
30,478.09
53,357.43
46,989.08
10,647.35
14,360.52
17,987.48
21,120.72
24,244.54
33,561.17
12,857.38
16,556.45
20,391.87
27,009.44
12,775.88
16,297.83
19,644.22
25,462.41
10,047.03
13,092.49
17,512.56
15,760.21
18,755.51
22,760.22
12,457.70
15,934.19
20,031.37
25,376.21
14,890.30
19,300.96
27,227.31
18,678.71
26,793.14
16,042.34
18,644.22
23,730.44
14,562.71
20,028.24
24,680.28
11,452.99
15,650.49
18,656.76
23,586.24
13,448.29
16,963.97
20,669.30

E:\FR\FM\25APP2.SGM

$10,230.42
12,926.35
15,081.52
16,103.47
18,606.61
20,835.45
23,214.76
29,203.80
26,294.70
34,873.08
9,051.74
12,652.05
14,095.63
15,520.39
18,775.88
22,260.21
29,279.03
13,418.51
16,529.80
19,366.79
25,067.43
12,424.78
17,835.44
28,128.56
49,244.57
43,366.82
10,123.84
13,655.19
17,103.47
20,083.10
23,053.32
31,912.26
11,882.46
15,300.96
18,844.85
24,959.28
12,189.67
15,550.18
18,742.97
24,294.70
9,279.01
12,090.92
16,172.43
14,554.88
17,321.34
21,018.83
11,520.39
14,736.69
18,525.10
23,468.68
12,863.65
16,675.57
23,523.54
15,291.55
21,934.20
14,576.82
16,940.46
21,561.15
13,622.27
18,736.70
23,089.37
10,377.76
14,180.27
16,904.41
21,371.50
12,401.27
15,642.65
19,059.58

25APP2

Payment rate
no comorbidity
$9,761.77
12,333.87
14,390.30
15,365.22
17,753.94
19,879.33
22,150.50
27,866.80
25,089.37
33,275.90
8,440.45
11,797.82
13,142.65
14,471.80
17,507.86
20,757.08
27,300.97
12,543.90
15,451.43
18,103.47
23,431.06
11,286.85
16,202.21
25,553.32
44,735.16
39,395.03
9,114.43
12,293.12
15,398.14
18,079.96
20,755.51
28,730.44
10,877.76
14,006.29
17,252.37
22,849.56
11,073.68
14,126.98
17,026.67
22,070.56
8,531.36
11,117.57
14,871.49
13,384.03
15,927.92
19,327.61
10,484.34
13,410.67
16,860.52
21,358.96
11,620.70
15,064.28
21,250.81
13,868.36
19,893.44
12,913.81
15,009.42
19,101.90
12,561.14
17,274.32
21,288.43
9,415.37
12,865.22
15,337.01
19,390.31
11,702.21
14,761.77
17,985.92

24192

Federal Register / Vol. 81, No. 79 / Monday, April 25, 2016 / Proposed Rules
TABLE 5—PROPOSED FY 2017 PAYMENT RATES—Continued
CMG

1504
1601
1602
1603
1701
1702
1703
1704
1801
1802
1803
1901
1902
1903
2001
2002
2003
2004
2101
5001
5101
5102
5103
5104

F. Example of the Methodology for
Adjusting the Proposed Federal
Prospective Payment Rates
Table 6 illustrates the methodology
for adjusting the proposed federal
prospective payments (as described in
sections V.A. through V.F. of this
proposed rule). The following examples
are based on two hypothetical Medicare
beneficiaries, both classified into CMG
0110 (without comorbidities). The
proposed unadjusted federal
prospective payment rate for CMG 0110
(without comorbidities) appears in
Table 5.
Example: One beneficiary is in
Facility A, an IRF located in rural
Spencer County, Indiana, and another
beneficiary is in Facility B, an IRF
located in urban Harrison County,
Indiana. Facility A, a rural non-teaching
hospital has a Disproportionate Share
Hospital (DSH) percentage of 5 percent
(which would result in a LIP adjustment
of 1.0156), a wage index of 0.8297, and
a rural adjustment of 14.9 percent.
Facility B, an urban teaching hospital,
has a DSH percentage of 15 percent

Payment rate
tier 1

Payment rate
tier 2

Payment rate
tier 3

30,330.76
15,431.05
20,100.34
25,217.90
17,757.07
22,360.53
26,710.06
34,299.41
20,771.18
29,073.70
45,374.66
18,405.98
33,454.59
54,208.53
14,445.16
18,992.19
23,749.24
30,443.61
26,252.38
..............................
..............................
..............................
..............................
..............................

25,705.36
14,004.72
18,242.97
22,887.17
14,456.13
18,203.78
21,744.54
27,923.23
16,822.90
23,547.05
36,750.83
16,462.40
29,921.67
48,485.95
11,832.30
15,558.01
19,454.57
24,938.90
26,252.38
..............................
..............................
..............................
..............................
..............................

23,703.79
13,015.69
16,954.57
21,271.19
13,277.45
16,719.46
19,973.38
25,647.37
14,796.26
20,711.62
32,324.49
14,525.10
26,399.72
42,777.48
10,852.68
14,268.04
17,841.71
22,869.93
23,437.33
..............................
..............................
..............................
..............................
..............................

(which would result in a LIP adjustment
of 1.0454 percent), a wage index of
0.8756, and a teaching status adjustment
of 0.0784.
To calculate each IRF’s labor and nonlabor portion of the federal prospective
payment, we begin by taking the
unadjusted federal prospective payment
rate for CMG 0110 (without
comorbidities) from Table 5. Then, we
multiply the labor-related share for FY
2017 (71.0 percent) described in section
V.E. of this proposed rule by the
proposed unadjusted federal
prospective payment rate. To determine
the non-labor portion of the proposed
federal prospective payment rate, we
subtract the labor portion of the
proposed federal payment from the
proposed unadjusted federal
prospective payment.
To compute the proposed wageadjusted federal prospective payment,
we multiply the labor portion of the
proposed federal payment by the
appropriate proposed wage index
located in tables A and B. These tables
are available on CMS Web site at http://

Payment rate
no comorbidity
22,368.37
12,023.53
15,663.03
19,650.49
11,981.21
15,087.79
18,021.97
23,144.23
12,993.75
18,188.11
28,385.61
14,305.66
26,001.60
42,133.28
9,824.46
12,916.94
16,152.06
20,705.35
21,429.49
2,485.90
10,644.21
22,282.16
12,590.92
33,479.66

www.cms.hhs.gov/Medicare/MedicareFee-for-Service-Payment/
InpatientRehabFacPPS/. The resulting
figure is the wage-adjusted labor
amount. Next, we compute the proposed
wage-adjusted federal payment by
adding the wage-adjusted labor amount
to the non-labor portion.
Adjusting the proposed wage-adjusted
federal payment by the facility-level
adjustments involves several steps.
First, we take the wage-adjusted federal
prospective payment and multiply it by
the appropriate rural and LIP
adjustments (if applicable). Second, to
determine the appropriate amount of
additional payment for the teaching
status adjustment (if applicable), we
multiply the teaching status adjustment
(0.0784, in this example) by the wageadjusted and rural-adjusted amount (if
applicable). Finally, we add the
additional teaching status payments (if
applicable) to the wage, rural, and LIPadjusted federal prospective payment
rates. Table 6 illustrates the components
of the adjusted payment calculation.

asabaliauskas on DSK3SPTVN1PROD with PROPOSALS

TABLE 6—EXAMPLE OF COMPUTING THE IRF FY 2017 FEDERAL PROSPECTIVE PAYMENT
Rural Facility A
(Spencer Co., IN)

Steps
1.
2.
3.
4.
5.
6.
7.

Unadjusted Federal Prospective Payment ..........................................................................
Labor Share .........................................................................................................................
Labor Portion of Federal Payment ......................................................................................
CBSA-Based Wage Index (shown in the Addendum, Tables A and B) .............................
Wage-Adjusted Amount .......................................................................................................
Non-Labor Amount ..............................................................................................................
Wage-Adjusted Federal Payment .......................................................................................

VerDate Sep<11>2014

19:36 Apr 22, 2016

Jkt 238001

PO 00000

Frm 00016

Fmt 4701

Sfmt 4702

E:\FR\FM\25APP2.SGM

$33,275.90
× 0.710
= $23,625.89
× 0.8297
= $19,602.40
+ $9,650.01
= $29,252.41

25APP2

Urban Facility B
(Harrison Co., IN)
$33,275.90
× 0.710
= $23,625.89
× 0.8756
= $20,686.83
+ $9,650.01
= $30,336.84

24193

Federal Register / Vol. 81, No. 79 / Monday, April 25, 2016 / Proposed Rules
TABLE 6—EXAMPLE OF COMPUTING THE IRF FY 2017 FEDERAL PROSPECTIVE PAYMENT—Continued
Rural Facility A
(Spencer Co., IN)

Steps

× 1.149
= $33,611.02
× 1.0156
= $34,135.35
$33,611.02
×0
= $0.00
+ $34,135.35
= $34,135.35

8. Rural Adjustment .................................................................................................................
9. Wage- and Rural-Adjusted Federal Payment .....................................................................
10. LIP Adjustment ..................................................................................................................
11. FY 2017 Wage-, Rural- and LIP-Adjusted Federal Prospective Payment Rate ...............
12. FY 2017 Wage- and Rural-Adjusted Federal Prospective Payment ................................
13. Teaching Status Adjustment .............................................................................................
14. Teaching Status Adjustment Amount ................................................................................
15. FY 2017 Wage-, Rural-, and LIP-Adjusted Federal Prospective Payment Rate ..............
16. Total FY 2017 Adjusted Federal Prospective Payment ....................................................

Thus, the proposed adjusted payment
for Facility A would be $34,135.35, and
the proposed adjusted payment for
Facility B would be $34,092.54.

asabaliauskas on DSK3SPTVN1PROD with PROPOSALS

VI. Proposed Update to Payments for
High-Cost Outliers Under the IRF PPS
A. Proposed Update to the Outlier
Threshold Amount for FY 2017
Section 1886(j)(4) of the Act provides
the Secretary with the authority to make
payments in addition to the basic IRF
prospective payments for cases
incurring extraordinarily high costs. A
case qualifies for an outlier payment if
the estimated cost of the case exceeds
the adjusted outlier threshold. We
calculate the adjusted outlier threshold
by adding the IRF PPS payment for the
case (that is, the CMG payment adjusted
by all of the relevant facility-level
adjustments) and the adjusted threshold
amount (also adjusted by all of the
relevant facility-level adjustments).
Then, we calculate the estimated cost of
a case by multiplying the IRF’s overall
CCR by the Medicare allowable covered
charge. If the estimated cost of the case
is higher than the adjusted outlier
threshold, we make an outlier payment
for the case equal to 80 percent of the
difference between the estimated cost of
the case and the outlier threshold.
In the FY 2002 IRF PPS final rule (66
FR 41362 through 41363), we discussed
our rationale for setting the outlier
threshold amount for the IRF PPS so
that estimated outlier payments would
equal 3 percent of total estimated
payments. For the 2002 IRF PPS final
rule, we analyzed various outlier
policies using 3, 4, and 5 percent of the
total estimated payments, and we
concluded that an outlier policy set at
3 percent of total estimated payments
would optimize the extent to which we
could reduce the financial risk to IRFs
of caring for high-cost patients, while
still providing for adequate payments
for all other (non-high cost outlier)
cases.
Subsequently, we updated the IRF
outlier threshold amount in the FYs

VerDate Sep<11>2014

19:36 Apr 22, 2016

Jkt 238001

2006 through 2016 IRF PPS final rules
and the FY 2011 and FY 2013 notices
(70 FR 47880, 71 FR 48354, 72 FR
44284, 73 FR 46370, 74 FR 39762, 75 FR
42836, 76 FR 47836, 76 FR 59256, and
77 FR 44618, 78 FR 47860, 79 FR 45872,
80 FR 47036, respectively) to maintain
estimated outlier payments at 3 percent
of total estimated payments. We also
stated in the FY 2009 final rule (73 FR
46370 at 46385) that we would continue
to analyze the estimated outlier
payments for subsequent years and
adjust the outlier threshold amount as
appropriate to maintain the 3 percent
target.
To update the IRF outlier threshold
amount for FY 2017, we propose to use
FY 2015 claims data and the same
methodology that we used to set the
initial outlier threshold amount in the
FY 2002 IRF PPS final rule (66 FR 41316
and 41362 through 41363), which is also
the same methodology that we used to
update the outlier threshold amounts for
FYs 2006 through 2016. Based on an
analysis of the preliminary data used for
the proposed rule, we estimated that IRF
outlier payments as a percentage of total
estimated payments would be
approximately 2.8 percent in FY 2016.
Therefore, we propose to update the
outlier threshold amount from $8,658
for FY 2016 to $8,301 for FY 2017 to
maintain estimated outlier payments at
approximately 3 percent of total
estimated aggregate IRF payments for
FY 2017.
We invite public comment on the
proposed update to the FY 2017 outlier
threshold amount to maintain estimated
outlier payments at approximately 3
percent of total estimated IRF payments.
B. Proposed Update to the IRF Cost-ToCharge Ratio Ceiling and Urban/Rural
Averages
In accordance with the methodology
stated in the FY 2004 IRF PPS final rule
(68 FR 45674, 45692 through 45694), we
propose to apply a ceiling to IRFs’ CCRs.
Using the methodology described in that
final rule, we propose to update the
national urban and rural CCRs for IRFs,

PO 00000

Frm 00017

Fmt 4701

Sfmt 4702

Urban Facility B
(Harrison Co., IN)
× 1.000
= $30,336.84
× 1.0454
= $31,714.13
$30,336.84
× 0.0784
= $2,378.41
+ $31,714.13
= $34,092.54

as well as the national CCR ceiling for
FY 2017, based on analysis of the most
recent data that is available. We apply
the national urban and rural CCRs in the
following situations:
• New IRFs that have not yet
submitted their first Medicare cost
report.
• IRFs whose overall CCR is in excess
of the national CCR ceiling for FY 2017,
as discussed below.
• Other IRFs for which accurate data
to calculate an overall CCR are not
available.
Specifically, for FY 2017, we propose
to estimate a national average CCR of
0.562 for rural IRFs, which we
calculated by taking an average of the
CCRs for all rural IRFs using their most
recently submitted cost report data.
Similarly, we propose to estimate a
national average CCR of 0.435 for urban
IRFs, which we calculated by taking an
average of the CCRs for all urban IRFs
using their most recently submitted cost
report data. We apply weights to both of
these averages using the IRFs’ estimated
costs, meaning that the CCRs of IRFs
with higher costs factor more heavily
into the averages than the CCRs of IRFs
with lower costs. For this proposed rule,
we have used the most recent available
cost report data (FY 2014). This
includes all IRFs whose cost reporting
periods begin on or after October 1,
2013, and before October 1, 2014. If, for
any IRF, the FY 2014 cost report was
missing or had an ‘‘as submitted’’ status,
we used data from a previous fiscal
year’s (that is, FY 2004 through FY
2013) settled cost report for that IRF. We
do not use cost report data from before
FY 2004 for any IRF because changes in
IRF utilization since FY 2004 resulting
from the 60 percent rule and IRF
medical review activities suggest that
these older data do not adequately
reflect the current cost of care.
In accordance with past practice, we
propose to set the national CCR ceiling
at 3 standard deviations above the mean
CCR. Using this method, the proposed
national CCR ceiling would be 1.36 for
FY 2017. This means that, if an

E:\FR\FM\25APP2.SGM

25APP2

24194

Federal Register / Vol. 81, No. 79 / Monday, April 25, 2016 / Proposed Rules

individual IRF’s CCR exceeds this
proposed ceiling of 1.36 for FY 2017, we
would replace the IRF’s CCR with the
appropriate proposed national average
CCR (either rural or urban, depending
on the geographic location of the IRF).
We calculated the proposed national
CCR ceiling by:
Step 1. Taking the national average
CCR (weighted by each IRF’s total costs,
as previously discussed) of all IRFs for
which we have sufficient cost report
data (both rural and urban IRFs
combined).
Step 2. Estimating the standard
deviation of the national average CCR
computed in step 1.
Step 3. Multiplying the standard
deviation of the national average CCR
computed in step 2 by a factor of 3 to
compute a statistically significant
reliable ceiling.
Step 4. Adding the result from step 3
to the national average CCR of all IRFs
for which we have sufficient cost report
data, from step 1.
The proposed national average rural
and urban CCRs and the proposed
national CCR ceiling in this section will
be updated in the final rule if more
recent data becomes available to use in
these analyses.
We invite public comment on the
proposed update to the IRF CCR ceiling
and the urban/rural averages for FY
2017.
VII. Proposed Revisions and Updates to
the IRF Quality Reporting Program
(QRP)

asabaliauskas on DSK3SPTVN1PROD with PROPOSALS

A. Background and Statutory Authority
We seek to promote higher quality
and more efficient health care for
Medicare beneficiaries, and our efforts
are furthered by QRPs coupled with
public reporting of that information.
Section 3004(b) of the Affordable Care
Act amended section 1886(j)(7) of the
Act, requiring the Secretary to establish
the IRF QRP. This program applies to
freestanding IRFs, as well as IRF units
affiliated with either acute care facilities
or critical access hospitals (CAHs).
Beginning with the FY 2014 payment
determination and subsequent years, the
Secretary is required to reduce any
annual update to the standard federal
rate for discharges occurring during
such fiscal year by 2 percentage points
for any IRF that does not comply with
the requirements established by the
Secretary. Section 1886(j)(7) of the Act
requires that for the FY 2014 payment
determination and subsequent years,
each IRF submit data on quality
measures specified by the Secretary in
a form and manner, and at a time,
specified by the Secretary. For more

VerDate Sep<11>2014

19:36 Apr 22, 2016

Jkt 238001

information on the statutory history of
the IRF QRP, please refer to the FY 2015
IRF PPS final rule (79 FR 45908).
The Improving Medicare Post-Acute
Care Transformation Act of 2014
(IMPACT Act) imposed new data
reporting requirements for certain PAC
providers, including IRFs. For
information on the statutory background
of the IMPACT Act, please refer to the
FY 2016 IRF PPS final rule (80 FR 47080
through 47083).
In the FY 2016 IRF PPS final rule, we
reviewed general activities and finalized
the general timeline and sequencing of
such activities that would occur under
the IRF QRP. For further information,
please refer to the FY 2016 IRF PPS final
rule (80 FR 40708 through 47128). In
addition, we established our approach
for identifying cross-cutting measures
and process for the adoption of
measures, including the application and
purpose of the Measures Application
Partnership (MAP) and the notice-andcomment rulemaking process (80 FR
47080 through 47084). For information
on these topics, please refer to the FY
2016 IRF PPS final rule (80 FR 47080).
B. General Considerations Used for
Selection of Quality, Resource Use, and
Other Measures for the IRF QRP
For a detailed discussion of the
considerations we use for the selection
of IRF QRP quality measures, such as
alignment with the CMS Quality
Strategy,1 which incorporates the 3
broad aims of the National Quality
Strategy,2 please refer to the FY 2015
IRF PPS final rule (79 FR 45911) and the
FY 2016 IRF PPS final rule (80 FR 47083
through 47084). Overall, we strive to
promote high quality and efficiency in
the delivery of health care to the
beneficiaries we serve. Performance
improvement leading to the highestquality health care requires continuous
evaluation to identify and address
performance gaps and reduce the
unintended consequences that may arise
in treating a large, vulnerable, and aging
population. QRPs, coupled with public
reporting of quality information, are
critical to the advancement of health
care quality improvement efforts. Valid,
reliable, relevant quality measures are
fundamental to the effectiveness of our
QRPs. Therefore, selection of quality
measures is a priority for us in all of our
QRPs.
In this proposed rule, we propose to
adopt for the IRF QRP one measure that
1 http://www.cms.gov/Medicare/QualityInitiatives-Patient-Assessment-Instruments/
QualityInitiativesGenInfo/CMS-QualityStrategy.html.
2 http://www.ahrq.gov/workingforquality/nqs/
nqs2011annlrpt.htm.

PO 00000

Frm 00018

Fmt 4701

Sfmt 4702

we are specifying under section
1899B(c)(1) of the Act to meet the
Medication Reconciliation domain, that
is, Drug Regimen Review Conducted
with Follow-Up for Identified IssuesPost Acute Care Inpatient Rehabilitation
Facility Quality Reporting Program.
Further, we are proposing to adopt for
the IRF QRP, three measures to meet the
resource use and other measure
domains identified in section
1899B(d)(1) of the Act. These include:
(1) Total Estimated Medicare Spending
per Beneficiary: Medicare Spending Per
Beneficiary-Post Acute Care Inpatient
Rehabilitation Facility Quality
Reporting Program; (2) Discharge to
Community: Discharge to CommunityPost Acute Care Inpatient Rehabilitation
Facility Quality Reporting Program, and
(3) Measures to reflect all-condition
risk-adjusted potentially preventable
hospital readmission rates: Potentially
Preventable 30-Day Post-Discharge
Readmission Measure for Inpatient
Rehabilitation Facility Quality
Reporting Program. Also, we are
proposing an additional measure: (4)
Potentially Preventable Within Stay
Readmission Measure for Inpatient
Rehabilitation Facilities.
In our selection and specification of
measures, we employ a transparent
process in which we seek input from
stakeholders and national experts and
engage in a process that allows for prerulemaking input on each measure, as
required by section 1890A of the Act. To
meet this requirement, we provided the
following opportunities for stakeholder
input: Our measure development
contractor convened technical expert
panel (TEPs) that included stakeholder
experts and patient representatives on
July 29, 2015, for the Drug Regimen
Review Conducted with Follow-Up for
Identified Issues measures; on August
25, 2015, September 25, 2015, and
October 5, 2015, for the Discharge to
Community measures; on August 12 and
13, 2015, and October 14, 2015, for the
Potentially Preventable 30-Day PostDischarge Readmission Measures and
Potentially Preventable Within Stay
Readmission Measure for IRFs; and on
October 29 and 30, 2015, for the
Medicare Spending per Beneficiary
(MSPB) measures. In addition, we
released draft quality measure
specifications for public comment for
the Drug Regimen Review Conducted
with Follow-Up for Identified Issues
measures from September 18, 2015, to
October 6, 2015; for the Discharge to
Community measures from November 9,
2015, to December 8, 2015; for the
Potentially Preventable 30-Day PostDischarge Readmission Measure for

E:\FR\FM\25APP2.SGM

25APP2

Federal Register / Vol. 81, No. 79 / Monday, April 25, 2016 / Proposed Rules
IRFs and Potentially Preventable Within
Stay Readmission Measure for IRFs from
November 2, 2015 to December 1, 2015;
and for the MSPB measures from
January 13, 2016 to February 5, 2016.
We implemented a public mailbox,
[email protected], for
the submission of public comments.
This PAC mailbox is accessible on our
post-acute care quality initiatives Web
site at https://www.cms.gov/Medicare/
Quality-Initiatives-Patient-AssessmentInstruments/Post-Acute-Care-QualityInitiatives/IMPACT-Act-of-2014-andCross-Setting-Measures.html.
Additionally, we sought public input
from the MAP Post-Acute Care, LongTerm Care Workgroup during the
annual in-person meeting held
December 14 and 15, 2015. The MAP is
composed of multi-stakeholder groups
convened by the NQF, our current
contractor under section 1890(a) of the
Act, tasked to provide input on the
selection of quality and efficiency
measures described in section
1890(b)(7)(B) of the Act.
The MAP reviewed each IMPACT
Act-related measure, as well as other
quality measures proposed in this rule
for use in the IRF QRP. For more
information on the MAP’s
recommendations, please refer to the
MAP 2016 Final Recommendations to
HHS and CMS public report at http://
www.qualityforum.org/Publications/
2016/02/MAP_2016_Considerations_
for_Implementing_Measures_in_
Federal_Programs_-_PAC-LTC.aspx.
For measures that do not have NQF
endorsement, or which are not fully
supported by the MAP for use in the IRF

QRP, we are proposing for the IRF QRP
for the purposes of satisfying the
measure domains required under the
IMPACT Act, measures that closely
align with the national priorities
identified in the National Quality
Strategy (http://www.ahrq.gov/
workingforquality/) and for which the
MAP supports the measure concept.
Further discussion as to the importance
and high-priority status of these
proposed measures in the IRF setting is
included under each quality measure
proposal in this proposed rule.
C. Policy for Retention of IRF QRP
Measures Adopted for Previous Payment
Determinations
In the CY 2013 Hospital Outpatient
Prospective Payment System/
Ambulatory Surgical Center (OPPS/
ASC) Payment Systems and Quality
Reporting Programs final rule (77 FR
68500 through 68507), we adopted a
policy that would allow any quality
measure adopted for use in the IRF QRP
to remain in effect until the measure
was actively removed, suspended, or
replaced, when we initially adopt a
measure for the IRF QRP for a payment
determination. For the purpose of
streamlining the rulemaking process,
when we initially adopt a measure for
the IRF QRP for a payment
determination, this measure will also be
adopted for all subsequent years or until
we propose to remove, suspend, or
replace the measure. For further
information on how measures are
considered for removal, suspension, or
replacement, please refer to the CY 2013
OPPS/ASC final rule (77 FR 68500).

24195

We are not proposing any changes to
the policy for retaining IRF QRP
measures adopted for previous payment
determinations.
D. Policy for Adopting Changes to IRF
QRP Measures
In the CY 2013 OPPS/ASC final rule
(77 FR 68500 through 68507), we
adopted a subregulatory process to
incorporate NQF updates to IRF quality
measure specifications that do not
substantively change the nature of the
measure. Substantive changes will be
proposed and finalized through
rulemaking. For further information on
what constitutes a substantive versus a
nonsubstantive change and the
subregulatory process for
nonsubstantive changes, please refer to
the CY 2013 OPPS/ASC final rule (77
FR 68500). We are not proposing any
changes to the policy for adopting
changes to IRF QRP measures.
E. Quality Measures Previously
Finalized for and Currently Used in the
IRF QRP
A history of the IRF QRP quality
measures adopted for the FY 2014
payment determinations and subsequent
years is presented in Table 7. The year
in which each quality measure was first
adopted and implemented, and then
subsequently re-proposed or revised, if
applicable, is displayed. The initial and
subsequent annual payment
determination years are also shown in
Table 7. For more information on a
particular measure, please refer to the
IRF PPS final rule and associated page
numbers referenced in the Table 7.

asabaliauskas on DSK3SPTVN1PROD with PROPOSALS

TABLE 7—QUALITY MEASURES PREVIOUSLY FINALIZED FOR AND CURRENTLY USED IN THE IRF QUALITY REPORTING
PROGRAM
Measure title

Final rule

Data
collection start date

National Healthcare Safety Network
(NHSN) Catheter-Associated Urinary
Tract Infection (CAUTI) Outcome
Measure (NQF #0138).

Adopted an application of the measure
in FY 2012 IRF PPS Final Rule (76
FR 47874 through 47886).

October 1, 2012 .....

FY 2014 and subsequent years.

Adopted the NQF-endorsed version and
expanded measure (with standardized
infection ratio) in CY 2013 OPPS/ASC
Final Rule (77 FR 68504 through
68505).
Adopted application of measure in FY
2012 IRF PPS final rule (76 FR 47876
through 47878).
Adopted a non-risk-adjusted application
of the NQF-endorsed version in CY
2013 OPPS/ASC Final Rule (77 FR
68500 through 68507).
Adopted the risk adjusted, NQF-endorsed version in FY 2014 IRF PPS
Final Rule (78 FR 47911 through
47912).

January 1, 2013 .....

FY 2015 and subsequent years.

October 1, 2012 .....

FY 2014 and subsequent years.

January 1, 2013 .....

FY 2015 and subsequent years.

October 1, 2014 .....

FY 2017 and subsequent years.

Percent of Residents or Patients with
Pressure Ulcers That Are New or
Worsened (Short Stay) (NQF #0678).

VerDate Sep<11>2014

19:36 Apr 22, 2016

Jkt 238001

PO 00000

Frm 00019

Fmt 4701

Sfmt 4702

E:\FR\FM\25APP2.SGM

Annual payment determination:
initial and subsequent APU years

25APP2

24196

Federal Register / Vol. 81, No. 79 / Monday, April 25, 2016 / Proposed Rules

TABLE 7—QUALITY MEASURES PREVIOUSLY FINALIZED FOR AND CURRENTLY USED IN THE IRF QUALITY REPORTING
PROGRAM—Continued
Final rule

Data
collection start date

Adopted in the FY 2016 IRF PPS final
rule (80 FR 47089 through 47096) to
fulfill IMPACT Act requirements.
Adopted in FY 2014 IRF PPS final rule
(78 FR 47906 through 47911).

October 1, 2015 .....

FY 2018 and subsequent years.

October 1, 2014 .....

FY 2017 and subsequent years.

Adopted in FY 2014 IRF PPS final rule
(78 FR 47905 through 47906).
Adopted in FY 2014 IRF PPS final rule
(78 FR 47906 through 47910).

October 1, 2014 .....

FY 2016 and subsequent years.

N/A ..........................

FY 2017 and subsequent years.

Adopted the NQF-endorsed version in
FY 2016 IRF PPS final rule (80 FR
47087 through 47089).
Adopted in the FY 2015 IRF PPS final
rule (79 FR 45911 through 45913).

N/A ..........................

FY 2018 and subsequent years.

January 1, 2015 .....

FY 2017 and subsequent years.

Adopted in the FY 2015 IRF PPS final
rule (79 FR 45913 through 45914).

January 1, 2015 .....

FY 2017 and subsequent years.

Adopted an application of the measure
in FY 2016 IRF PPS Final Rule (80
FR 47096 through 47100).
Adopted an application of the measure
in the FY 2016 IRF PPS final rule (80
FR 47100 through 47111).

October 1, 2016 .....

FY 2018 and subsequent years.

October 1, 2016 .....

FY 2018 and subsequent years.

Adopted in the FY 2016 IRF PPS final
rule (80 FR 47111 through 47117).

October 1, 2016 .....

FY 2018 and subsequent years.

Adopted in the FY 2016 IRF PPS final
rule (80 FR 47117 through 47118).

October 1, 2016 .....

FY 2018 and subsequent years.

Adopted in the FY 2016 IRF PPS final
rule (80 FR 47118 through 47119).

October 1, 2016 .....

FY 2018 and subsequent years.

Adopted in the FY 2016 IRF PPS final
rule (80 FR 47119 through 47120).

October 1, 2016 .....

FY 2018 and subsequent years.

Measure title

Percent of Residents or Patients Who
Were Assessed and Appropriately
Given the Seasonal Influenza Vaccine
(Short Stay) (NQF #0680).
Influenza Vaccination Coverage among
Healthcare Personnel (NQF #0431).
All-Cause Unplanned Readmission Measure for 30 Days Post Discharge from
Inpatient Rehabilitation Facilities (NQF
#2502).

National Healthcare Safety Network
(NHSN) Facility-Wide Inpatient Hospital-Onset Methicillin-Resistant Staphylococcus aureus (MRSA) Bacteremia
Outcome Measure (NQF #1716).
National Healthcare Safety Network
(NHSN) Facility-Wide Inpatient Hospital-Onset Clostridium difficile Infection
(CDI) Outcome Measure (NQF #1717).
Application of Percent of Residents Experiencing One or More Falls with Major
Injury (Long Stay) (NQF #0674).
Application of Percent of Long-Term Care
Hospital Patients with an Admission
and Discharge Functional Assessment
and a Care Plan That Addresses Function (NQF #2631).
IRF Functional Outcome Measure:
Change in Self-Care for Medical Rehabilitation Patients (NQF #2633)*.
IRF Functional outcome Measure:
Change in Mobility Score for Medical
Rehabilitation (NQF #2634)*.
IRF Functional Outcome Measure: Discharge Self-Care Score for Medical
Rehabilitation Patients (NQF #2635).
IRF Functional Outcome Measure: Discharge Mobility Score for Medical Rehabilitation Patients (NQF #2636).

Annual payment determination:
initial and subsequent APU years

* These measures were under review at NQF when they were finalized for use in the IRF QRP. These measures are now NQF-endorsed.

asabaliauskas on DSK3SPTVN1PROD with PROPOSALS

F. IRF QRP Quality, Resource Use and
Other Measures Proposed for the FY
2018 Payment Determination and
Subsequent Years
For the FY 2018 payment
determinations and subsequent years, in
addition to the quality measures we are
retaining under our policy described in
section VII.C. of this proposed rule, we
are proposing four new measures. Three
of these measures proposed were
developed to meet the requirements of
IMPACT Act. They are:
(1) MSPB–PAC IRF QRP,
(2) Discharge to Community–PAC IRF
QRP, and

VerDate Sep<11>2014

19:36 Apr 22, 2016

Jkt 238001

(3) Potentially Preventable 30-Day
Post-Discharge Readmission Measure for
IRF QRP.
The fourth measure to be proposed is:
(4) Potentially Preventable Within Stay
Readmission Measure for IRFs. The
measures are described in more detail
below.
For the risk-adjustment of the
resource use and other measures, we
understand the important role that
sociodemographic status plays in the
care of patients. However, we continue
to have concerns about holding
providers to different standards for the
outcomes of their patients of diverse
sociodemographic status because we do
not want to mask potential disparities or
minimize incentives to improve the

PO 00000

Frm 00020

Fmt 4701

Sfmt 4702

outcomes of disadvantaged populations.
We routinely monitor the impact of
sociodemographic status on providers’
results on our measures.
The NQF is currently undertaking a
two-year trial period in which new
measures and measures undergoing
maintenance review will be assessed to
determine if risk-adjusting for
sociodemographic factors is appropriate.
For two years, NQF will conduct a trial
of temporarily allowing inclusion of
sociodemographic factors in the riskadjustment approach for some
performance measures. At the
conclusion of the trial, NQF will issue
recommendations on future permanent
inclusion of sociodemographic factors.
During the trial, measure developers are

E:\FR\FM\25APP2.SGM

25APP2

Federal Register / Vol. 81, No. 79 / Monday, April 25, 2016 / Proposed Rules

asabaliauskas on DSK3SPTVN1PROD with PROPOSALS

expected to submit information such as
analyses and interpretations as well as
performance scores with and without
sociodemographic factors in the risk
adjustment model.
Furthermore, the Office of the
Assistant Secretary for Planning and
Evaluation (ASPE) is conducting
research to examine the impact of
sociodemographic status on quality
measures, resource use, and other
measures under the Medicare program
as directed by the IMPACT Act. We will
closely examine the findings of the
ASPE reports and related Secretarial
recommendations and consider how
they apply to our quality programs at
such time as they are available.
We are inviting public comment on
how socioeconomic and demographic
factors should be used in risk
adjustment for the resource use
measures.
1. Proposal To Address the IMPACT Act
Domain of Resource Use and Other
Measures: Total Estimated MSPB–PAC
IRF QRP
We are proposing an MSPB–PAC IRF
QRP measure for inclusion in the IRF
QRP for the FY 2018 payment
determination and subsequent years.
Section 1899B(d)(1)(A) of the Act
requires the Secretary to specify
resource use measures, including total
estimated MSPB, on which PAC
providers consisting of Skilled Nursing
Facilities (SNFs), IRFs, Long-Term Care
Hospitals (LTCHs), and Home Health
Agencies (HHAs) are required to submit
necessary data specified by the
Secretary.
Rising Medicare expenditures for
post-acute care as well as wide variation
in spending for these services
underlines the importance of measuring
resource use for providers rendering
these services. Between 2001 and 2013,
Medicare PAC spending grew at an
annual rate of 6.1 percent and doubled
to $59.4 billion, while payments to
inpatient hospitals grew at an annual
rate of 1.7 percent over this same
period.3 A study commissioned by the
Institute of Medicine discovered that
variation in PAC spending explains 73
percent of variation in total Medicare
spending across the United States.4
We reviewed the NQF’s consensusendorsed measures and were unable to
identify any NQF-endorsed resource use
measures for PAC settings. As such, we
are proposing this MSPB–PAC IRF
3 MedPAC, ‘‘A Data Book: Health Care Spending
and the Medicare Program,’’ (2015). 114
4 Institute of Medicine, ‘‘Variation in Health Care
Spending: Target Decision Making, Not
Geography,’’ (Washington, DC: National Academies
2013). 2.

VerDate Sep<11>2014

19:36 Apr 22, 2016

Jkt 238001

measure under the Secretary’s authority
to specify non-NQF-endorsed measures
under section 1899B(e)(2)(B). Given the
current lack of resource use measures
for PAC settings, our proposed MSPB–
PAC IRF QRP measure has the potential
to provide valuable information to IRF
providers on their relative Medicare
spending in delivering services to
approximately 338,000 Medicare
beneficiaries.5
The proposed MSPB–PAC IRF
episode-based measure will provide
actionable and transparent information
to support IRF providers’ efforts to
promote care coordination and deliver
high quality care at a lower cost to
Medicare. The MSPB–PAC IRF QRP
measure holds IRF providers
accountable for the Medicare payments
within an ‘‘episode of care’’ (episode),
which includes the period during which
a patient is directly under the IRF’s care,
as well as a defined period after the end
of the IRF treatment, which may be
reflective of and influenced by the
services furnished by the IRF. MSPB–
PAC IRF QRP episodes, constructed
according to the methodology described
below, have high levels of Medicare
spending with substantial variation. In
FY 2013 and FY 2014, Medicare FFS
beneficiaries experienced 613,089
MSPB–PAC IRF QPR episodes triggered
by admission to an IRF. The mean
payment-standardized, risk-adjusted
episode spending for these episodes is
$30,370. There is substantial variation
in the Medicare payments for these
MSPB–PAC IRF QRP episodes—ranging
from approximately $15,059 at the 5th
percentile to approximately $55,912 at
the 95th percentile. This variation is
partially driven by variation in
payments occurring following IRF
treatment.
Evaluating Medicare payments during
an episode creates a continuum of
accountability between providers and
has the potential to improve posttreatment care planning and
coordination. While some stakeholders
throughout the measure development
process supported the measures and
believe that measuring Medicare
spending was critical for improving
efficiency, others believed that resource
use measures did not reflect quality of
care in that they do not take into
account patient outcomes or experience
beyond those observable in claims data.
However, IRFs involved in the provision
of high quality PAC care as well as
appropriate discharge planning and
post-discharge care coordination would
be expected to perform well on this
5 Figures for 2013. MedPAC, ‘‘Medicare Payment
Policy,’’ Report to the Congress (2015). xvii–xviii.

PO 00000

Frm 00021

Fmt 4701

Sfmt 4702

24197

measure since beneficiaries would
likely experience fewer costly adverse
events (for example, avoidable
hospitalizations, infections, and
emergency room usage). Further, it is
important that the cost of care be
explicitly measured so that, in
conjunction with other quality
measures, we can recognize providers
that are involved in the provision of
high quality care at lower cost.
We have undertaken development of
MSPB–PAC measures for each of the
four PAC settings. We are proposing an
LTCH-specific MSPB–PAC measure in
the FY 2017 IPPS/LTCH proposed rule
published elsewhere in this issue of the
Federal Register and a SNF-specific
MSBP–PAC measure in the FY 2017
SNF PPS proposed rule published
elsewhere in this issue of the Federal
Register. We intend to propose a HHAspecific MSBP–PAC measure through
future notice-and-comment rulemaking.
The four setting-specific MSPB–PAC
measures are closely aligned in terms of
episode construction and measure
calculation. Each of the MSPB–PAC
measures assess Medicare Part A and
Part B spending during an episode, and
the numerator and denominator are
defined similarly for each of the MSPB–
PAC measures. However, developing
setting-specific measures allows us to
account for differences between settings
in payment policy, the types of data
available, and the underlying health
characteristics of beneficiaries. For
example, we are proposing to use the
IRF setting-specific rehabilitation
impairment categories (RICs) in the
MSPB–PAC IRF QRP risk adjustment
model, as detailed below.
The MSPB–PAC measures mirror the
general construction of the inpatient
prospective payment system (IPPS)
hospital MSPB measure that was
finalized in the FY 2012 IPPS/LTCH
PPS Final Rule (76 FR 51618 through
51627). It was endorsed by the NQF on
December 6, 2013, and has been used in
the Hospital Value-Based Purchasing
(VBP) Program (NQF #2158) since FY
2015.6 The hospital MSPB measure was
originally established under the
authority of section 1886(o)(2)(B)(ii) of
the Act. The hospital MSPB measure
evaluates hospitals’ Medicare spending
relative to the Medicare spending for the
national median hospital during a
hospital MSPB episode. It assesses
Medicare Part A and Part B payments
for services performed by hospitals and
other healthcare providers during a
6 QualityNet, ‘‘Measure Methodology Reports:
Medicare Spending Per Beneficiary (MSPB)
Measure,’’ (2015). http://www.qualitynet.org/dcs/
ContentServer?pagename=QnetPublic%2FPage%2
FQnetTier3&cid=1228772053996.

E:\FR\FM\25APP2.SGM

25APP2

asabaliauskas on DSK3SPTVN1PROD with PROPOSALS

24198

Federal Register / Vol. 81, No. 79 / Monday, April 25, 2016 / Proposed Rules

hospital MSPB episode, which is
comprised of the periods immediately
prior to, during, and following a
patient’s hospital stay.7 8 Similarly, the
MSPB–PAC measures assess all
Medicare Part A and Part B payments
for FFS claims with a start date during
the episode window (which, as
discussed below, is the time period
which Medicare FFS Part A and Part B
services are counted towards the MSPB–
PAC IRF QRP episode). However, there
are differences between the MSPB–PAC
measures, as proposed, and the hospital
MSPB measure to reflect differences in
payment policies and the nature of care
provided in each PAC setting. For
example, the MSPB–PAC measures
exclude a limited set of services (for
example, clinically unrelated services)
provided to a beneficiary during the
episode window while the hospital
MSPB measure does not exclude any
services.9
MSPB–PAC episodes may begin
within 30 days of discharge from an
inpatient hospital as part of a patient’s
trajectory from an acute to a PAC
setting. An IRF stay beginning within 30
days of discharge from an inpatient
hospital will be included once in the
hospital’s MSPB measure, and once in
the IRF provider’s MSPB–PAC measure.
Aligning the hospital MSPB and MSPB–
PAC measures in this way creates
continuous accountability and aligns
incentives to improve care planning and
coordination across inpatient and PAC
settings.
We have sought and considered the
input of stakeholders throughout the
measure development process for the
MSPB–PAC measures. We convened a
TEP consisting of 12 panelists with
combined expertise in all of the PAC
settings on October 29 and 30, 2015 in
Baltimore, Maryland. A follow-up email
survey was sent to TEP members on
November 18, 2015 to which 7
responses were received by December 8,
2015. The MSPB–PAC TEP Summary
Report is available at https://
www.cms.gov/Medicare/QualityInitiatives-Patient-AssessmentInstruments/Post-Acute-Care-QualityInitiatives/IMPACT-Act-of-2014/
IMPACT-Act-Downloads-andVideos.html. The measures were also
presented to the NQF-convened MAP
7 QualityNet, ‘‘Measure Methodology Reports:
Medicare Spending Per Beneficiary (MSPB)
Measure,’’ (2015). http://www.qualitynet.org/dcs/
ContentServer?pagename=Qnet
Public%2FPage%2FQnetTier3&cid=122877
2053996.
8 FY 2012 IPPS/LTCH PPS final rule (76 FR
51619).
9 FY 2012 IPPS/LTCH PPS Final Rule (76 FR
51620).

VerDate Sep<11>2014

19:36 Apr 22, 2016

Jkt 238001

Post-Acute Care/Long-Term Care (PAC/
LTC) Workgroup on December 15, 2015.
As the MSPB–PAC measures were
under development, there were three
voting options for members: (1)
Encourage continued development, (2)
do not encourage further consideration,
and (3) insufficient information.10 The
MAP PAC/LTC workgroup voted to
‘‘encourage continued development’’ for
each of the MSPB–PAC measures.11 The
MAP PAC/LTC workgroup’s vote of
‘‘encourage continued development’’
was affirmed by the MAP Coordinating
Committee on January 26, 2016.12 The
MAP’s concerns about the MSPB–PAC
measures, as outlined in their final
report ‘‘MAP 2016 Considerations for
Implementing Measures in Federal
Programs: Post-Acute Care and LongTerm Care’’ and Spreadsheet of Final
Recommendations, were taken into
consideration during the measure
development process and are discussed
as part of our responses to public
comments, described below.13 14
Since the MAP’s review and
recommendation of continued
development, we have continued to
refine risk adjustment models and
conduct measure testing for the
IMPACT Act measures in compliance
with the MAP’s recommendations. The
proposed IMPACT Act measures are
both consistent with the information
submitted to the MAP and support the
scientific acceptability of these
measures for use in quality reporting
programs.
In addition, a public comment period,
accompanied by draft measures
specifications, was originally open from
January 13 to 27, 2016 and twice
extended to January 29 and February 5.
10 National Quality Forum, Measure Applications
Partnership, ‘‘Process and Approach for MAP PreRulemaking Deliberations, 2015–2016’’ (February
2016) http://www.qualityforum.org/WorkArea/
linkit.aspx?LinkIdentifier=id&ItemID=81693.
11 National Quality Forum, Measure Applications
Partnership Post-Acute Care/Long-Term Care
Workgroup, ‘‘Meeting Transcript—Day 2 of 2’’
(December 15, 2015) 104–106 http://
www.qualityforum.org/WorkArea/linkit.aspx?Link
Identifier=id&ItemID=81470.
12 National Quality Forum, Measure Applications
Partnership, ‘‘Meeting Transcript—Day 1 of 2’’
(January 26, 2016) 231–232 http://
www.qualityforum.org/WorkArea/linkit.aspx?Link
Identifier=id&ItemID=81637.
13 National Quality Forum, Measure Applications
Partnership, ‘‘MAP 2016 Considerations for
Implementing Measures in Federal Programs: PostAcute Care and Long-Term Care’’ Final Report,
(February 2016) http://www.qualityforum.org/
Publications/2016/02/MAP_2016_Considerations_
for_Implementing_Measures_in_Federal_Programs_
-_PAC-LTC.aspx.
14 National Quality Forum, Measure Applications
Partnership, ‘‘Spreadsheet of MAP 2016 Final
Recommendations’’ (February 1, 2016) http://
www.qualityforum.org/WorkArea/linkit.aspx?Link
Identifier=id&ItemID=81593.

PO 00000

Frm 00022

Fmt 4701

Sfmt 4702

A total of 45 comments on the MSPB–
PAC measures were received during this
3.5 week period. Also, the comments
received covered each of the MAP’s
concerns as outlined in their Final
Recommendations.15 The MSPB–PAC
Public Comment Summary Report is
available at https://www.cms.gov/
Medicare/Quality-Initiatives-PatientAssessment-Instruments/Post-AcuteCare-Quality-Initiatives/IMPACT-Act-of2014/IMPACT-Act-Downloads-andVideos.html and contains the public
comments (summarized and verbatim),
along with our responses including
statistical analyses. If finalized, the
MSPB–PAC IRF QRP measure, along
with the other MSPB–PAC measures, as
applicable, will be submitted for NQF
endorsement.
To calculate the MSPB–PAC IRF QRP
measure for each IRF provider, we first
define the construction of the MSPB–
PAC IRF QRP episode, including the
length of the episode window as well as
the services included in the episode.
Next, we apply the methodology for the
measure calculation. The specifications
are discussed further below. More
detailed specifications for the proposed
MSPB–PAC measures, including the
MSPB–PAC IRF QRP measure in this
proposed rule, are available at https://
www.cms.gov/Medicare/QualityInitiatives-Patient-AssessmentInstruments/Post-Acute-Care-QualityInitiatives/IMPACT-Act-of-2014/
IMPACT-Act-Downloads-andVideos.html.
a. Episode Construction
An MSPB–PAC IRF QRP episode
begins at the episode trigger, which is
defined as the patient’s admission to an
IRF. This admitting facility is the
attributed provider, for whom the
MSPB–PAC IRF QRP measure is
calculated. The episode window is the
time period during which Medicare FFS
Part A and Part B services are counted
towards the MSPB–PAC IRF QRP
episode. Because Medicare FFS claims
are already reported to the Medicare
program for payment purposes, IRF
providers will not be required to report
any additional data to CMS for
calculation of this measure. Thus, there
will be no additional data collection
burden from the implementation of this
measure.
The episode window is comprised of
a treatment period and an associated
services period. The treatment period
begins at the trigger (that is, on the day
15 National Quality Forum, Measure Applications
Partnership, ‘‘Spreadsheet of MAP 2016 Final
Recommendations’’ (February 1, 2016) http://
www.qualityforum.org/WorkArea/linkit.aspx?Link
Identifier=id&ItemID=81593.

E:\FR\FM\25APP2.SGM

25APP2

asabaliauskas on DSK3SPTVN1PROD with PROPOSALS

Federal Register / Vol. 81, No. 79 / Monday, April 25, 2016 / Proposed Rules
of admission to the IRF) and ends on the
day of discharge from that IRF.
Readmissions to the same facility
occurring within 7 or fewer days do not
trigger a new episode, and instead are
included in the treatment period of the
original episode. When two sequential
stays at the same IRF occur within 7 or
fewer days of one another, the treatment
period ends on the day of discharge for
the latest IRF stay. The treatment period
includes those services that are
provided directly or reasonably
managed by the IRF provider that are
directly related to the beneficiary’s care
plan. The associated services period is
the time during which Medicare Part A
and Part B services (with certain
exclusions) are counted towards the
episode. The associated services period
begins at the episode trigger and ends 30
days after the end of the treatment
period. The distinction between the
treatment period and the associated
services period is important because
clinical exclusions of services may
differ for each period. Certain services
are excluded from the MSPB–PAC IRF
QRP episodes because they are
clinically unrelated to IRF care, and/or
because IRF providers may have limited
influence over certain Medicare services
delivered by other providers during the
episode window. These limited servicelevel exclusions are not counted
towards a given IRF provider’s Medicare
spending to ensure that beneficiaries
with certain conditions and complex
care needs receive the necessary care.
Certain services that have been
determined by clinicians to be outside
of the control of an IRF provider include
planned hospital admissions,
management of certain preexisting
chronic conditions (for example,
dialysis for end-stage renal disease
(ESRD), and enzyme treatments for
genetic conditions), treatment for
preexisting cancers, organ transplants,
and preventive screenings (for example,
colonoscopy and mammograms).
Exclusion of such services from the
MSPB–PAC IRF QRP episode ensures
that facilities do not have disincentives
to treat patients with certain conditions
or complex care needs.
An MSPB–PAC episode may begin
during the associated services period of
an MSPB–PAC IRF QRP episode in the
30 days post-treatment. One possible
scenario occurs where an IRF provider
discharges a beneficiary who is then
admitted to a HHA within 30 days. The
HHA claim would be included once as
an associated service for the attributed
provider of the first MSPB–PAC IRF
QRP episode and once as a treatment
service for the attributed provider of the

VerDate Sep<11>2014

19:36 Apr 22, 2016

Jkt 238001

second MSPB–PAC HHA episode. As in
the case of overlap between hospital and
PAC episodes discussed earlier, this
overlap is necessary to ensure
continuous accountability between
providers throughout a beneficiary’s
trajectory of care, as both providers
share incentives to deliver high quality
care at a lower cost to Medicare. Even
within the IRF setting, one MSPB–PAC
IRF QRP episode may begin in the
associated services period of another
MSPB–PAC IRF QRP episode in the 30
days post-treatment. The second IRF
claim would be included once as an
associated service for the attributed IRF
provider of the first MSPB–PAC IRF
QRP episode and once as a treatment
service for the attributed IRF provider of
the second MSPB–PAC IRF QRP
episode. Again, this ensures that IRF
providers have the same incentives
throughout both MSPB–PAC IRF QRP
episodes to deliver quality care and
engage in patient-focused care planning
and coordination. If the second MSPB–
PAC IRF QRP episode were excluded
from the second IRF provider’s MSPB–
PAC IRF QRP measure, that provider
would not share the same incentives as
the first IRF provider of the first MSPB–
PAC IRF QRP episode. The MSPB–PAC
IRF QRP measure is designed to
benchmark the resource use of each
attributed provider against what their
spending is expected to be as predicted
through risk adjustment. As discussed
further below, the measure takes the
ratio of observed spending to expected
spending for each episode and then
takes the average of those ratios across
all of the attributed provider’s episodes.
The measure is not a simple sum of all
costs across a provider’s episodes, thus
mitigating concerns about double
counting.
b. Measure Calculation
Medicare payments for Part A and
Part B claims for services included in
MSPB–PAC IRF QRP episodes, defined
according to the methodology
previously discussed, are used to
calculate the MSPB–PAC IRF QRP
measure. Measure calculation involves
determination of the episode exclusions,
the approach for standardizing
payments for geographic payment
differences, the methodology for risk
adjustment of episode spending to
account for differences in patient case
mix, and the specifications for the
measure numerator and denominator.
(1) Exclusion Criteria
In addition to service-level exclusions
that remove some payments from
individual episodes, we exclude certain
episodes in their entirety from the

PO 00000

Frm 00023

Fmt 4701

Sfmt 4702

24199

MSPB–PAC IRF QRP measure to ensure
that the MSPB–PAC IRF QRP measure
accurately reflects resource use and
facilitates fair and meaningful
comparisons between IRF providers.
The proposed episode-level exclusions
are as follows:
• Any episode that is triggered by an
IRF claim outside the 50 states, DC,
Puerto Rico, and U.S. territories.
• Any episode where the claim(s)
constituting the attributed IRF
provider’s treatment have a standard
allowed amount of zero or where the
standard allowed amount cannot be
calculated.
• Any episode in which a beneficiary
is not enrolled in Medicare FFS for the
entirety of a 90-day lookback period
(that is, a 90-day period prior to the
episode trigger) plus episode window
(including where a beneficiary dies), or
is enrolled in Part C for any part of the
lookback period plus episode window.
• Any episode in which a beneficiary
has a primary payer other than Medicare
for any part of the 90-day lookback
period plus episode window.
• Any episode where the claim(s)
constituting the attributed IRF
provider’s treatment include at least one
related condition code indicating that it
is not a prospective payment system
bill.
(2) Standardization and Risk
Adjustment
Section 1899B(d)(2)(C) of the Act
requires that the MSPB–PAC measures
are adjusted for the factors described
under section 1886(o)(2)(B)(ii) of the
Act, which include adjustment for
factors such as age, sex, race, severity of
illness, and other factors that the
Secretary determines appropriate.
Medicare payments included in the
MSPB–PAC IRF QRP measure are
payment-standardized and riskadjusted. Payment standardization
removes sources of payment variation
not directly related to clinical decisions
and facilitates comparisons of resource
use across geographic areas. We propose
to use the same payment
standardization methodology as that
used in the NQF-endorsed hospital
MSPB measure. This methodology
removes geographic payment
differences, such as wage index and
geographic practice cost index (GPCI),
incentive payment adjustments, and
other add-on payments that support
broader Medicare program goals
including indirect graduate medical
education (IME) and hospitals serving a

E:\FR\FM\25APP2.SGM

25APP2

24200

Federal Register / Vol. 81, No. 79 / Monday, April 25, 2016 / Proposed Rules

asabaliauskas on DSK3SPTVN1PROD with PROPOSALS

disproportionate share of uninsured
patients.16
Risk adjustment uses patient claims
history to account for case-mix variation
and other factors that affect resource use
but are beyond the influence of the
attributed IRF provider. To assist with
risk adjustment for MSPB–PAC IRF QRP
episodes, we create mutually exclusive
and exhaustive clinical case mix
categories using the most recent
institutional claim in the 60 days prior
to the start of the MSPB–PAC IRF QRP
episode. The beneficiaries in these
clinical case mix categories have a
greater degree of clinical similarity than
the overall IRF patient population, and
allow us to more accurately estimate
Medicare spending. Our proposed
MSPB–PAC IRF QRP model, adapted for
the IRF setting from the NQF-endorsed
hospital MSPB measure uses a
regression framework with a 90-day
hierarchical condition category (HCC)
lookback period and covariates
including the clinical case mix
categories, HCC indicators, age brackets,
indicators for originally disabled, ESRD
enrollment, and long-term care status,
and selected interactions of these
covariates where sample size and
predictive ability make them
appropriate. We sought and considered
public comment regarding the treatment
of hospice services occurring within the
MSPB–PAC IRF QRP episode window.
Given the comments received, we
propose to include the Medicare
spending for hospice services but risk
adjust for them, such that MSPB–PAC
IRF QRP episodes with hospice are
compared to a benchmark reflecting
other MSPB–PAC IRF QRP episodes
with hospice. We believe that this
provides a balance between the
measure’s intent of evaluating Medicare
spending and ensuring that providers do
not have incentives against the
appropriate use of hospice services in a
patient-centered continuum of care.
We are proposing to use RICs in
response to commenters’ concerns about
the risk adjustment approach for the
MSPB–PAC IRF QRP measure.
Commenters suggested the use of case
mix groups (CMGs); however, we
16 QualityNet, ‘‘CMS Price (Payment)
Standardization—Detailed Methods’’ (Revised May
2015) https://qualitynet.org/dcs/ContentServer?c=
Page&pagename=QnetPublic%2FPage%2
FQnetTier4&cid=1228772057350.

VerDate Sep<11>2014

19:36 Apr 22, 2016

Jkt 238001

believe that the use of RICs may be more
appropriate given that the other
covariates incorporated in the model
partially account for factors in CMGs
(for example, age and certain HCC
indicators). RICs do not account for
functional status as CMGs do, as the
functional status information in CMGs
is based on the IRF–PAI. Given the
move toward standardized data that was
mandated by the IMPACT Act, we have
chosen to defer risk adjustment for
functional status until standardized data
become available. We are seeking
comment on whether the use of CMGs
would still be appropriate to include in
the MSPB–PAC IRF QRP risk
adjustment model.
We understand the important role that
sociodemographic factors, beyond age,
play in the care of patients. However,
we continue to have concerns about
holding providers to different standards
for the outcomes of their patients of
diverse sociodemographic status
because we do not want to mask
potential disparities or minimize
incentives to improve the outcomes of
disadvantaged populations. We
routinely monitor the impact of
sociodemographic status on providers’
results on our measures.
The NQF is currently undertaking a
two-year trial period in which new
measures and measures undergoing
maintenance review will be assessed to
determine if risk-adjusting for
sociodemographic factors is appropriate.
For two years, NQF will conduct a trial
of temporarily allowing inclusion of
sociodemographic factors in the riskadjustment approach for some
performance measures. At the
conclusion of the trial, NQF will issue
recommendations on future permanent
inclusion of sociodemographic factors.
During the trial, measure developers are
expected to submit information such as
analyses and interpretations as well as
performance scores with and without
sociodemographic factors in the risk
adjustment model.
Furthermore, ASPE is conducting
research to examine the impact of
sociodemographic status on quality
measures, resource use, and other
measures under the Medicare program
as required under the IMPACT Act. We
will closely examine the findings of the
ASPE reports and related Secretarial
recommendations and consider how

PO 00000

Frm 00024

Fmt 4701

Sfmt 4702

they apply to our quality programs at
such time as they are available.
While we conducted analyses on the
impact of age by sex on the performance
of the MSPB–PAC IRF QRP riskadjustment model, we are not proposing
to adjust the MSPB–PAC IRF QRP
measure for socioeconomic and
demographic factors at this time. As this
MSPB–PAC IRF QRP measure will be
submitted for NQF endorsement, we
prefer to await the results of this trial
and study before deciding whether to
risk adjust for socioeconomic and
demographic factors. We will monitor
the results of the trial, studies, and
recommendations. We are inviting
public comment on how socioeconomic
and demographic factors should be used
in risk adjustment for the MSPB–PAC
IRF QRP measure.
(3) Measure Numerator and
Denominator
The MPSB–PAC IRF QRP measure is
a payment-standardized, risk-adjusted
ratio that compares a given IRF
provider’s Medicare spending against
the Medicare spending of other IRF
providers within a performance period.
Similar to the hospital MSPB measure,
the ratio allows for ease of comparison
over time as it obviates the need to
adjust for inflation or policy changes.
The MSPB–PAC IRF QRP measure is
calculated as the ratio of the MSPB–PAC
Amount for each IRF provider divided
by the episode-weighted median MSPB–
PAC Amount across all IRF providers.
To calculate the MSPB–PAC Amount for
each IRF provider, one calculates the
average of the ratio of the standardized
episode spending over the expected
episode spending (as predicted in risk
adjustment), and then multiplies this
quantity by the average episode
spending level across all IRF providers
nationally. The denominator for an IRF
provider’s MSPB–PAC IRF QRP
measure is the episode-weighted
national median of the MSPB–PAC
Amounts across all IRF providers. An
MSPB–PAC IRF QRP measure of less
than 1 indicates that a given IRF
provider’s Medicare spending is less
than that of the national median IRF
provider during a performance period.
Mathematically, this is represented in
equation (A) below:

E:\FR\FM\25APP2.SGM

25APP2

Federal Register / Vol. 81, No. 79 / Monday, April 25, 2016 / Proposed Rules

c. Data Sources
The MSPB–PAC IRF QRP resource
use measure is an administrative claimsbased measure. It uses Medicare Part A
and Part B claims from FFS
beneficiaries and Medicare eligibility
files.
d. Cohort
The measure cohort includes
Medicare FFS beneficiaries with an IRF
treatment period ending during the data
collection period.

asabaliauskas on DSK3SPTVN1PROD with PROPOSALS

e. Reporting
If this proposed measure is finalized,
we intend to provide initial confidential
feedback to providers, prior to public
reporting of this measure, based on
Medicare FFS claims data from
discharges in CY 2015 and 2016. We
intend to publicly report this measure
using claims data from discharges in CY
2016 and 2017.
We propose a minimum of 20
episodes for reporting and inclusion in
the IRF QRP. For the reliability
calculation, as described in the measure
specifications identified and for which
a link has been provided above, we used
two years of data (FY 2013 and FY 2014)
to increase the statistical reliability of
this measure. The reliability results
support the 20 episode case minimum,
and 99.74 percent of IRF providers had
moderate or high reliability (above 0.4).
We invite public comment on our
proposal to adopt the MSPB–PAC IRF
QRP measure for the IRF QRP.
2. Proposal To Address the IMPACT Act
Domain of Resource Use and Other
Measures: Discharge to Community-Post
Acute Care (PAC) Inpatient
Rehabilitation Facility Quality
Reporting Program
Sections 1899B(d)(1)(B) and
1899B(a)(2)(E)(ii) of the Act require the
Secretary to specify a measure to

VerDate Sep<11>2014

19:36 Apr 22, 2016

Jkt 238001

address the domain of discharge to
community by SNFs, LTCHs, and IRFs
by October 1, 2016, and HHAs by
January 1, 2017. We are proposing to
adopt the measure, Discharge to
Community-PAC IRF QRP, for the IRF
QRP for the FY 2018 payment
determination and subsequent years as
a Medicare FFS claims-based measure to
meet this requirement.
This proposed measure assesses
successful discharge to the community
from an IRF setting, with successful
discharge to the community including
no unplanned rehospitalizations and no
death in the 31 days following discharge
from the IRF. Specifically, this proposed
measure reports an IRF’s riskstandardized rate of Medicare FFS
patients who are discharged to the
community following an IRF stay, and
do not have an unplanned readmission
to an acute care hospital or LTCH in the
31 days following discharge to
community, and who remain alive
during the 31 days following discharge
to community. The term ‘‘community’’,
for this measure, is defined as home/
self-care, with or without home health
services, based on Patient Discharge
Status Codes 01, 06, 81, and 86 on the
Medicare FFS claim.17 18 This measure
is conceptualized uniformly across the
PAC settings, in terms of the definition
of the discharge to community outcome,
the approach to risk adjustment, and the
measure calculation.
Discharge to a community setting is
an important health care outcome for
many patients for whom the overall
goals of post-acute care include
optimizing functional improvement,
returning to a previous level of
independence, and avoiding
institutionalization. Returning to the
community is also an important
outcome for many patients who are not
expected to make functional
17 Further description of patient discharge status
codes can be found, for example, at the following
Web page: https://med.noridianmedicare.com/web/
jea/topics/claim-submission/patient-status-codes.
18 This definition is not intended to suggest that
board and care homes, assisted living facilities, or
other settings included in the definition of
‘‘community’’ for the purpose of this measure are
the most integrated setting for any particular
individual or group of individuals under the
Americans with Disabilities Act (ADA) and Section
504.

PO 00000

Frm 00025

Fmt 4701

Sfmt 4702

improvement during their IRF stay, and
for patients who may be expected to
decline functionally due to their
medical condition. The discharge to
community outcome offers a multidimensional view of preparation for
community life, including the cognitive,
physical, and psychosocial elements
involved in a discharge to the
community.19 20
In addition to being an important
outcome from a patient and family
perspective, patients discharged to
community settings, on average, incur
lower costs over the recovery episode,
compared with those discharged to
institutional settings.21 22 Given the high
costs of care in institutional settings,
encouraging IRFs to prepare patients for
discharge to community, when
clinically appropriate, may have costsaving implications for the Medicare
program.23 Also, providers have
discovered that successful discharge to
community was a major driver of their
ability to achieve savings, where
capitated payments for post-acute care
were in place.24 For patients who
require long-term care due to persistent
disability, discharge to community
could result in lower long-term care

19 El-Solh AA, Saltzman SK, Ramadan FH,
Naughton BJ. Validity of an artificial neural
network in predicting discharge destination from a
postacute geriatric rehabilitation unit. Archives of
physical medicine and rehabilitation.
2000;81(10):1388–1393.
20 Tanwir S, Montgomery K, Chari V, Nesathurai
S. Stroke rehabilitation: Availability of a family
member as caregiver and discharge destination.
European journal of physical and rehabilitation
medicine. 2014;50(3):355–362.
21 Dobrez D, Heinemann AW, Deutsch A,
Manheim L, Mallinson T. Impact of Medicare’s
prospective payment system for inpatient
rehabilitation facilities on stroke patient outcomes.
American journal of physical medicine &
rehabilitation/Association of Academic Physiatrists.
2010;89(3):198–204.
22 Gage B, Morley M, Spain P, Ingber M.
Examining Post Acute Care Relationships in an
Integrated Hospital System. Final Report. RTI
International;2009.
23 Ibid.
24 Doran JP, Zabinski SJ. Bundled payment
initiatives for Medicare and non-Medicare total
joint arthroplasty patients at a community hospital:
Bundles in the real world. The journal of
arthroplasty. 2015;30(3):353–355.

E:\FR\FM\25APP2.SGM

25APP2

EP25AP16.000

Where:
• Yij = attributed standardized spending for
episode i and provider j
• Yij = expected standardized spending for
episode i and provider j, as predicted
from risk adjustment
• nj = number of episodes for provider j
• n = total number of episodes nationally
• i ∈ {Ij} = all episodes i in the set of
episodes attributed to provider j.

24201

24202

Federal Register / Vol. 81, No. 79 / Monday, April 25, 2016 / Proposed Rules

asabaliauskas on DSK3SPTVN1PROD with PROPOSALS

costs for Medicaid and for patients’ outof-pocket expenditures.25
Analyses conducted for ASPE on PAC
episodes, using a 5 percent sample of
2006 Medicare claims, revealed that
relatively high average, unadjusted
Medicare payments are associated with
discharge to institutional settings from
IRFs, SNFs, LTCHs or HHAs, as
compared with payments associated
with discharge to community settings.26
Average, unadjusted Medicare payments
associated with discharge to community
settings ranged from $0 to $4,017 for IRF
discharges, $0 to $3,544 for SNF
discharges, $0 to $4,706 for LTCH
discharges, and $0 to $992 for HHA
discharges. In contrast, payments
associated with discharge to noncommunity settings were considerably
higher, ranging from $11,847 to $25,364
for IRF discharges, $9,305 to $29,118 for
SNF discharges, $12,465 to $18,205 for
LTCH discharges, and $7,981 to $35,192
for HHA discharges.27
Measuring and comparing facilitylevel discharge to community rates is
expected to help differentiate among
facilities with varying performance in
this important domain, and to help
avoid disparities in care across patient
groups. Variation in discharge to
community rates has been reported
within and across post-acute settings;
across a variety of facility-level
characteristics, such as geographic
location (for example, regional location,
urban or rural location), ownership (for
example, for-profit or nonprofit), and
freestanding or hospital-based units;
and across patient-level characteristics,
such as race and gender.28 29 30 31 32 33
25 Newcomer RJ, Ko M, Kang T, Harrington C,
Hulett D, Bindman AB. Health Care Expenditures
After Initiating Long-term Services and Supports in
the Community Versus in a Nursing Facility.
Medical Care. 2016;54(3):221–228.
26 Gage B, Morley M, Spain P, Ingber M.
Examining Post Acute Care Relationships in an
Integrated Hospital System. Final Report. RTI
International;2009.
27 Ibid.
28 Reistetter TA, Karmarkar AM, Graham JE, et al.
Regional variation in stroke rehabilitation
outcomes. Archives of physical medicine and
rehabilitation. 2014;95(1):29–38.
29 El-Solh AA, Saltzman SK, Ramadan FH,
Naughton BJ. Validity of an artificial neural
network in predicting discharge destination from a
postacute geriatric rehabilitation unit. Archives of
physical medicine and rehabilitation.
2000;81(10):1388–1393.
30 March 2015 Report to the Congress: Medicare
Payment Policy. Medicare Payment Advisory
Commission;2015.
31 Bhandari VK, Kushel M, Price L, Schillinger D.
Racial disparities in outcomes of inpatient stroke
rehabilitation. Archives of physical medicine and
rehabilitation. 2005;86(11):2081–2086.
32 Chang PF, Ostir GV, Kuo YF, Granger CV,
Ottenbacher KJ. Ethnic differences in discharge
destination among older patients with traumatic
brain injury. Archives of physical medicine and
rehabilitation. 2008;89(2):231–236.

VerDate Sep<11>2014

19:36 Apr 22, 2016

Jkt 238001

Discharge to community rates in the IRF
setting have been reported to range from
about 60 to 80 percent.34 35 36 37 38 39
Longer-term studies show that rates of
discharge to community from IRFs have
decreased over time as IRF length of
stay has decreased.40 41 In the IRF
Medicare FFS population, using CY
2013 national claims data, we
discovered that approximately 69
percent of patients were discharged to
the community. Greater variation in
discharge to community rates is seen in
the SNF setting, with rates ranging from
31 to 65 percent.42 43 44 45 A multi-center
33 Berges IM, Kuo YF, Ostir GV, Granger CV,
Graham JE, Ottenbacher KJ. Gender and ethnic
differences in rehabilitation outcomes after hipreplacement surgery. American journal of physical
medicine & rehabilitation/Association of Academic
Physiatrists. 2008;87(7):567–572.
34 Galloway RV, Granger CV, Karmarkar AM, et al.
The Uniform Data System for Medical
Rehabilitation: Report of patients with debility
discharged from inpatient rehabilitation programs
in 2000–2010. American journal of physical
medicine & rehabilitation/Association of Academic
Physiatrists. 2013;92(1):14–27.
35 Morley MA, Coots LA, Forgues AL, Gage BJ.
Inpatient rehabilitation utilization for Medicare
beneficiaries with multiple sclerosis. Archives of
physical medicine and rehabilitation.
2012;93(8):1377–1383.
36 Reistetter TA, Graham JE, Deutsch A, Granger
CV, Markello S, Ottenbacher KJ. Utility of
functional status for classifying community versus
institutional discharges after inpatient
rehabilitation for stroke. Archives of physical
medicine and rehabilitation. 2010;91(3):345–350.
37 Gagnon D, Nadeau S, Tam V. Clinical and
administrative outcomes during publicly-funded
inpatient stroke rehabilitation based on a case-mix
group classification model. Journal of rehabilitation
medicine. 2005;37(1):45–52.
38 DaVanzo J, El-Gamil A, Li J, Shimer M,
Manolov N, Dobson A. Assessment of patient
outcomes of rehabilitative care provided in
inpatient rehabilitation facilities (IRFs) and after
discharge. Vienna, VA: Dobson DaVanzo &
Associates, LLC;2014.
39 Kushner DS, Peters KM, Johnson-Greene D.
Evaluating Siebens Domain Management Model for
Inpatient Rehabilitation to Increase Functional
Independence and Discharge Rate to Home in
Geriatric Patients. Archives of physical medicine
and rehabilitation. 2015;96(7):1310–1318.
40 Galloway RV, Granger CV, Karmarkar AM, et al.
The Uniform Data System for Medical
Rehabilitation: Report of patients with debility
discharged from inpatient rehabilitation programs
in 2000–2010. American journal of physical
medicine & rehabilitation/Association of Academic
Physiatrists. 2013;92(1):14–27.
41 Mallinson T, Deutsch A, Bateman J, et al.
Comparison of discharge functional status after
rehabilitation in skilled nursing, home health, and
medical rehabilitation settings for patients after hip
fracture repair. Archives of physical medicine and
rehabilitation. 2014;95(2):209–217.
42 El-Solh AA, Saltzman SK, Ramadan FH,
Naughton BJ. Validity of an artificial neural
network in predicting discharge destination from a
postacute geriatric rehabilitation unit. Archives of
physical medicine and rehabilitation.
2000;81(10):1388–1393.
43 Hall RK, Toles M, Massing M, et al. Utilization
of acute care among patients with ESRD discharged
home from skilled nursing facilities. Clinical
journal of the American Society of Nephrology:
CJASN. 2015;10(3):428–434.

PO 00000

Frm 00026

Fmt 4701

Sfmt 4702

study of 23 LTCHs demonstrated that
28.8 percent of 1,061 patients who were
ventilator-dependent on admission were
discharged to home.46 A single-center
study revealed that 31 percent of LTCH
hemodialysis patients were discharged
to home.47 One study noted that 64
percent of beneficiaries who were
discharged from the home health
episode did not use any other acute or
post-acute services paid by Medicare in
the 30 days after discharge.48 However,
significant numbers of patients were
admitted to hospitals (29 percent) and
lesser numbers to SNFs (7.6 percent),
IRFs (1.5 percent), home health (7.2
percent) or hospice (3.3 percent).49
Discharge to community is an
actionable health care outcome, as
targeted interventions have been shown
to successfully increase discharge to
community rates in a variety of postacute settings.50 51 52 53 Many of these
interventions involve discharge
planning or specific rehabilitation
strategies, such as addressing discharge
barriers and improving medical and
functional status.54 55 56 57 The
44 Stearns SC, Dalton K, Holmes GM, Seagrave
SM. Using propensity stratification to compare
patient outcomes in hospital-based versus
freestanding skilled-nursing facilities. Medical care
research and review: MCRR. 2006;63(5):599–622.
45 Wodchis WP, Teare GF, Naglie G, et al. Skilled
nursing facility rehabilitation and discharge to
home after stroke. Archives of physical medicine
and rehabilitation. 2005;86(3):442–448.
46 Scheinhorn DJ, Hassenpflug MS, Votto JJ, et al.
Post-ICU mechanical ventilation at 23 long-term
care hospitals: a multicenter outcomes study. Chest.
2007;131(1):85–93.
47 Thakar CV, Quate-Operacz M, Leonard AC,
Eckman MH. Outcomes of hemodialysis patients in
a long-term care hospital setting: A single-center
study. American journal of kidney diseases: The
official journal of the National Kidney Foundation.
2010;55(2):300–306.
48 Wolff JL, Meadow A, Weiss CO, Boyd CM, Leff
B. Medicare home health patients’ transitions
through acute and post-acute care settings. Medical
care. 2008;46(11):1188–1193.
49 Ibid.
50 Kushner DS, Peters KM, Johnson-Greene D.
Evaluating Siebens Domain Management Model for
Inpatient Rehabilitation to Increase Functional
Independence and Discharge Rate to Home in
Geriatric Patients. Archives of physical medicine
and rehabilitation. 2015;96(7):1310–1318.
51 Wodchis WP, Teare GF, Naglie G, et al. Skilled
nursing facility rehabilitation and discharge to
home after stroke. Archives of physical medicine
and rehabilitation. 2005;86(3):442–448.
52 Berkowitz RE, Jones RN, Rieder R, et al.
Improving disposition outcomes for patients in a
geriatric skilled nursing facility. Journal of the
American Geriatrics Society. 2011;59(6):1130–1136.
53 Kushner DS, Peters KM, Johnson-Greene D.
Evaluating use of the Siebens Domain Management
Model during inpatient rehabilitation to increase
functional independence and discharge rate to
home in stroke patients. PM & R: The journal of
injury, function, and rehabilitation. 2015;7(4):354–
364.
54 Kushner DS, Peters KM, Johnson-Greene D.
Evaluating Siebens Domain Management Model for
Inpatient Rehabilitation to Increase Functional

E:\FR\FM\25APP2.SGM

25APP2

Federal Register / Vol. 81, No. 79 / Monday, April 25, 2016 / Proposed Rules

asabaliauskas on DSK3SPTVN1PROD with PROPOSALS

effectiveness of these interventions
suggests that improvement in discharge
to community rates among post-acute
care patients is possible through
modifying provider-led processes and
interventions.
A TEP convened by our measure
development contractor was strongly
supportive of the importance of
measuring discharge to community
outcomes, and implementing the
proposed measure, Discharge to
Community-PAC IRF QRP in the IRF
QRP. The panel provided input on the
technical specifications of this proposed
measure, including the feasibility of
implementing the measure, as well as
the overall measure reliability and
validity. A summary of the TEP
proceedings is available on the PAC
Quality Initiatives Downloads and
Videos Web site at: https://
www.cms.gov/Medicare/QualityInitiatives-Patient-AssessmentInstruments/Post-Acute-Care-QualityInitiatives/IMPACT-Act-of-2014/
IMPACT-Act-Downloads-andVideos.html.
We also solicited stakeholder
feedback on the development of this
measure through a public comment
period held from November 9, 2015,
through December 8, 2015. Several
stakeholders and organizations,
including the MedPAC, among others,
supported this measure for
implementation. The public comment
summary report for the proposed
measure is available on the CMS Web
site at: https://www.cms.gov/Medicare/
Quality-Initiatives-Patient-AssessmentInstruments/Post-Acute-Care-QualityInitiatives/IMPACT-Act-of-2014/
IMPACT-Act-Downloads-andVideos.html.
The NQF-convened MAP met on
December 14 and 15, 2015, and
provided input on the use of this
proposed Discharge to Community-PAC
IRF QRP measure in the IRF QRP. The
MAP encouraged continued
development of the proposed measure
to meet the mandate of the IMPACT Act.
Independence and Discharge Rate to Home in
Geriatric Patients. Archives of physical medicine
and rehabilitation. 2015;96(7):1310–1318.
55 Wodchis WP, Teare GF, Naglie G, et al. Skilled
nursing facility rehabilitation and discharge to
home after stroke. Archives of physical medicine
and rehabilitation. 2005;86(3):442–448.
56 Berkowitz RE, Jones RN, Rieder R, et al.
Improving disposition outcomes for patients in a
geriatric skilled nursing facility. Journal of the
American Geriatrics Society. 2011;59(6):1130–1136.
57 Kushner DS, Peters KM, Johnson-Greene D.
Evaluating use of the Siebens Domain Management
Model during inpatient rehabilitation to increase
functional independence and discharge rate to
home in stroke patients. PM & R: The journal of
injury, function, and rehabilitation. 2015;7(4):354–
364.

VerDate Sep<11>2014

19:36 Apr 22, 2016

Jkt 238001

The MAP supported the alignment of
this proposed measure across PAC
settings, using standardized claims data.
More information about the MAP’s
recommendations for this measure is
available at: http://
www.qualityforum.org/Publications/
2016/02/MAP_2016_Considerations_
for_Implementing_Measures_in_
Federal_Programs_-_PAC-LTC.aspx.
Since the MAP’s review and
recommendation of continued
development, we have continued to
refine risk-adjustment models and
conduct measure testing for this
measure, as recommended by the MAP.
This proposed measure is consistent
with the information submitted to the
MAP and is scientifically acceptable for
current specification in the IRF QRP. As
discussed with the MAP, we fully
anticipate that additional analyses will
continue as we submit this measure to
the ongoing measure maintenance
process.
We reviewed the NQF’s consensusendorsed measures and were unable to
identify any NQF-endorsed resource use
or other measures for post-acute care
focused on discharge to community. In
addition, we are unaware of any other
post-acute care measures for discharge
to community that have been endorsed
or adopted by other consensus
organizations. Therefore, we are
proposing the measure, Discharge to
Community-PAC IRF QRP, under the
Secretary’s authority to specify nonNQF-endorsed measures under section
1899B(e)(2)(B) of the Act.
We are proposing to use data from the
Medicare FFS claims and Medicare
eligibility files to calculate this
proposed measure. We are proposing to
use data from the ‘‘Patient Discharge
Status Code’’ on Medicare FFS claims to
determine whether a patient was
discharged to a community setting for
calculation of this proposed measure. In
all PAC settings, we tested the accuracy
of determining discharge to a
community setting using the ‘‘Patient
Discharge Status Code’’ on the PAC
claim by examining whether discharge
to community coding based on PAC
claim data agreed with discharge to
community coding based on PAC
assessment data. We found excellent
agreement between the two data sources
in all PAC settings, ranging from 94.6
percent to 98.8 percent. Specifically, in
the IRF setting, using 2013 data, we
found 98.8 percent agreement in coding
of community and non-community
discharges when comparing discharge
status codes on claims and the
Discharge to Living Setting (item 44A)
codes on the IRF–PAI. We further
examined the accuracy of the ‘‘Patient

PO 00000

Frm 00027

Fmt 4701

Sfmt 4702

24203

Discharge Status Code’’ on the PAC
claim by assessing how frequently
discharges to an acute care hospital
were confirmed by follow-up acute care
claims. We discovered that 88 percent to
91 percent of IRF, LTCH, and SNF
claims with acute care discharge status
codes were followed by an acute care
claim on the day of, or day after, PAC
discharge. We believe these data
support the use of the claims ‘‘Patient
Discharge Status Code’’ for determining
discharge to a community setting for
this measure. In addition, this measure
can feasibly be implemented in the IRF
QRP because all data used for measure
calculation are derived from Medicare
FFS claims and eligibility files, which
are already available to CMS.
Based on the evidence discussed
above, we are proposing to adopt the
measure, Discharge to Community-PAC
IRF QRP, for the IRF QRP for FY 2018
payment determination and subsequent
years. This proposed measure is
calculated using 2 years of data. We are
proposing a minimum of 25 eligible
stays in a given IRF for public reporting
of the proposed measure for that IRF.
Since Medicare FFS claims data are
already reported to the Medicare
program for payment purposes, and
Medicare eligibility files are also
available, IRFs will not be required to
report any additional data to CMS for
calculation of this measure. The
proposed measure denominator is the
risk-adjusted expected number of
discharges to community. The proposed
measure numerator is the risk-adjusted
estimate of the number of patients who
are discharged to the community, do not
have an unplanned readmission to an
acute care hospital or LTCH in the 31day post-discharge observation window,
and who remain alive during the postdischarge observation window. The
measure is risk-adjusted for variables
such as age and sex, principal diagnosis,
comorbidities, ESRD status, and
dialysis, among other variables. For
technical information about this
proposed measure, including
information about the measure
calculation, risk adjustment, and
denominator exclusions, we refer
readers to the document titled, Proposed
Measure Specifications for Measures
Proposed in the FY 2017 IRF QRP
proposed rule, available at: https://
www.cms.gov/Medicare/QualityInitiatives-Patient-AssessmentInstruments/IRF-Quality-Reporting/IRFQuality-Reporting-Program-MeasuresInformation-.html.
If this proposed measure is finalized,
we intend to provide initial confidential
feedback to IRFs, prior to public
reporting of this measure, based on

E:\FR\FM\25APP2.SGM

25APP2

24204

Federal Register / Vol. 81, No. 79 / Monday, April 25, 2016 / Proposed Rules

asabaliauskas on DSK3SPTVN1PROD with PROPOSALS

Medicare FFS claims data from
discharges in CY 2015 and 2016. We
intend to publicly report this measure
using claims data from discharges in CY
2016 and 2017. We plan to submit this
proposed measure to the NQF for
consideration for endorsement.
We are inviting public comment on
our proposal to adopt the measure,
Discharge to Community-PAC IRF QRP,
for the IRF QRP.
3. Proposal To Address the IMPACT Act
Domain of Resource Use and Other
Measures: Potentially Preventable 30Day Post-Discharge Readmission
Measure for Inpatient Rehabilitation
Facility Quality Reporting Program
Sections 1899B(a)(2)(E)(ii) and
1899B(d)(1)(C) of the Act require the
Secretary to specify measures to address
the domain of all-condition riskadjusted potentially preventable
hospital readmission rates by SNFs,
LTCHs, and IRFs by October 1, 2016,
and HHAs by January 1, 2017. We are
proposing the measure Potentially
Preventable 30-Day Post-Discharge
Readmission Measure for IRF QRP as a
Medicare FFS claims-based measure to
meet this requirement for the FY 2018
payment determination and subsequent
years.
The proposed measure assesses the
facility-level risk-standardized rate of
unplanned, potentially preventable
hospital readmissions for Medicare FFS
beneficiaries in the 30 days post IRF
discharge. The IRF admission must have
occurred within up to 30 days of
discharge from a prior proximal hospital
stay which is defined as an inpatient
admission to an acute care hospital
(including IPPS, CAH, or a psychiatric
hospital). Hospital readmissions include
readmissions to a short-stay acute-care
hospital or an LTCH, with a diagnosis
considered to be unplanned and
potentially preventable. This proposed
measure is claims-based, requiring no
additional data collection or submission
burden for IRFs. Because the measure
denominator is based on IRF
admissions, each Medicare beneficiary
may be included in the measure
multiple times within the measurement
period. Readmissions counted in this
measure are identified by examining
Medicare FFS claims data for
readmissions to either acute care
hospitals (IPPS or CAH) or LTCHs that
occur during a 30-day window
beginning two days after IRF discharge.
This measure is conceptualized
uniformly across the PAC settings, in
terms of the measure definition, the
approach to risk adjustment, and the
measure calculation. Our approach for
defining potentially preventable

VerDate Sep<11>2014

19:36 Apr 22, 2016

Jkt 238001

hospital readmissions is described in
more detail below.
Hospital readmissions among the
Medicare population, including
beneficiaries that utilize PAC, are
common, costly, and often
preventable.58 59 MedPAC and a study
by Jencks et al. estimated that 17 to 20
percent of Medicare beneficiaries
discharged from the hospital were
readmitted within 30 days. MedPAC
found that more than 75 percent of 30day and 15-day readmissions and 84
percent of 7-day readmissions were
considered ‘‘potentially preventable.’’60
In addition, MedPAC calculated that
annual Medicare spending on
potentially preventable readmissions
would be $12 billion for 30-day, $8
billion for 15-day, and $5 billion for 7day readmissions.61 For hospital
readmissions from one post-acute care
setting, SNFs, MedPAC deemed 76
percent of these readmissions as
‘‘potentially avoidable’’—associated
with $12 billion in Medicare
expenditures.62 Mor et al. analyzed 2006
Medicare claims and SNF assessment
data (Minimum Data Set), and reported
a 23.5 percent readmission rate from
SNFs, associated with $4.3 billion in
expenditures.63 Fewer studies have
investigated potentially preventable
readmission rates from the remaining
post-acute care settings.
We have addressed the high rates of
hospital readmissions in the acute care
setting as well as in PAC. For example,
we developed the following measure:
All-Cause Unplanned Readmission
Measure for 30 Days Post-Discharge
from IRFs (NQF #2502), as well as
similar measures for other PAC
providers (NQF #2512 for LTCHs and
NQF #2510 for SNFs).64 These measures
are endorsed by the NQF, and the NQF58 Friedman, B., and Basu, J.: The rate and cost
of hospital readmissions for preventable conditions.
Med. Care Res. Rev. 61(2):225–240, 2004.
doi:10.1177/1077558704263799.
59 Jencks, S.F., Williams, M.V., and Coleman,
E.A.: Rehospitalizations among patients in the
Medicare Fee-for-Service Program. N. Engl. J. Med.
360(14):1418–1428, 2009. doi:10.1016/
j.jvs.2009.05.045.
60 MedPAC: Payment policy for inpatient
readmissions, in Report to the Congress: Promoting
Greater Efficiency in Medicare. Washington, DC, pp.
103–120, 2007. Available from http://
www.medpac.gov/documents/reports/Jun07_
EntireReport.pdf.
61 Ibid.
62 Ibid.
63 Mor, V., Intrator, O., Feng, Z., et al.: The
revolving door of rehospitalization from skilled
nursing facilities. Health Aff. 29(1):57–64, 2010.
doi:10.1377/hlthaff.2009.0629.
64 National Quality Forum: All-Cause Admissions
and Readmissions Measures. pp. 1–319, April 2015.
Available from http://www.qualityforum.org/
Publications/2015/04/All-Cause_Admissions_and_
Readmissions_Measures_-_Final_Report.aspx.

PO 00000

Frm 00028

Fmt 4701

Sfmt 4702

endorsed IRF measure (NQF #2502) was
adopted into the IRF QRP in the FY
2016 IRF PPS final rule (80 FR 47087
through 47089). Note that these NQFendorsed measures assess all-cause
unplanned readmissions.
Several general methods and
algorithms have been developed to
assess potentially avoidable or
preventable hospitalizations and
readmissions for the Medicare
population. These include the Agency
for Healthcare Research and Quality’s
(AHRQ’s) Prevention Quality Indicators,
approaches developed by MedPAC, and
proprietary approaches, such as the
3MTM algorithm for Potentially
Preventable Readmissions.65 66 67 Recent
work led by Kramer et al. for MedPAC
identified 13 conditions for which
readmissions were deemed as
potentially preventable among SNF and
IRF populations.68 69 Although much of
the existing literature addresses hospital
readmissions more broadly and
potentially avoidable hospitalizations
for specific settings like long-term care,
these findings are relevant to the
development of potentially preventable
readmission measures for PAC.70 71 72
Potentially Preventable Readmission
Measure Definition: We conducted a
65 Goldfield, N.I., McCullough, E.C., Hughes, J.S.,
et al.: Identifying potentially preventable
readmissions. Health Care Finan. Rev. 30(1):75–91,
2008. Available from http://www.ncbi.nlm.nih.gov/
pmc/articles/PMC4195042/.
66 National Quality Forum: Prevention Quality
Indicators Overview. 2008.
67 MedPAC: Online Appendix C: Medicare
Ambulatory Care Indicators for the Elderly. pp. 1–
12, prepared for Chapter 4, 2011. Available from
http://www.medpac.gov/documents/reports/Mar11_
Ch04_APPENDIX.pdf?sfvrsn=0.
68 Kramer, A., Lin, M., Fish, R., et al.:
Development of Inpatient Rehabilitation Facility
Quality Measures: Potentially Avoidable
Readmissions, Community Discharge, and
Functional Improvement. pp. 1–42, 2015. Available
from http://www.medpac.gov/documents/
contractor-reports/development-of-inpatientrehabilitation-facility-quality-measures-potentiallyavoidable-readmissions-community-discharge-andfunctional-improvement.pdf?sfvrsn=0.
69 Kramer, A., Lin, M., Fish, R., et al.:
Development of Potentially Avoidable Readmission
and Functional Outcome SNF Quality Measures.
pp. 1–75, 2014. Available from http://
www.medpac.gov/documents/contractor-reports/
mar14_snfqualitymeasures_
contractor.pdf?sfvrsn=0.
70 Allaudeen, N., Vidyarthi, A., Maselli, J., et al.:
Redefining readmission risk factors for general
medicine patients. J. Hosp. Med. 6(2):54–60, 2011.
doi:10.1002/jhm.805.
71 4 Gao, J., Moran, E., Li, Y.-F., et al.: Predicting
potentially avoidable hospitalizations. Med. Care
52(2):164–171, 2014. doi:10.1097/
MLR.0000000000000041.
72 Walsh, E.G., Wiener, J.M., Haber, S., et al.:
Potentially avoidable hospitalizations of dually
eligible Medicare and Medicaid beneficiaries from
nursing facility and home-and community-based
services waiver programs. J. Am. Geriatr. Soc.
60(5):821–829, 2012. doi:10.1111/j.1532–
5415.2012.03920.x.

E:\FR\FM\25APP2.SGM

25APP2

asabaliauskas on DSK3SPTVN1PROD with PROPOSALS

Federal Register / Vol. 81, No. 79 / Monday, April 25, 2016 / Proposed Rules
comprehensive environmental scan,
analyzed claims data, and obtained
input from a TEP to develop a definition
and list of conditions for which hospital
readmissions are potentially
preventable. The Ambulatory Care
Sensitive Conditions and Prevention
Quality Indicators, developed by AHRQ,
served as the starting point in this work.
For patients in the 30-day post-PAC
discharge period, a potentially
preventable readmission refers to a
readmission for which the probability of
occurrence could be minimized with
adequately planned, explained, and
implemented post-discharge
instructions, including the
establishment of appropriate follow-up
ambulatory care. Our list of PPR
conditions is categorized by 3 clinical
rationale groupings:
• Inadequate management of chronic
conditions;
• Inadequate management of
infections; and
• Inadequate management of other
unplanned events.
Additional details regarding the
definition for potentially preventable
readmissions are available in the
document titled, Proposed Measure
Specifications for Measures Proposed in
the FY 2017 IRF QRP proposed rule,
available at https://www.cms.gov/
Medicare/Quality-Initiatives-PatientAssessment-Instruments/IRF-QualityReporting/IRF-Quality-ReportingProgram-Measures-Information-.html.
This proposed measure focuses on
readmissions that are potentially
preventable and also unplanned.
Similar to the All-Cause Unplanned
Readmission Measure for 30 Days PostDischarge from IRFs (NQF #2502), this
proposed measure uses the current
version of the CMS Planned
Readmission Algorithm as the main
component for identifying planned
readmissions. A complete description of
the CMS Planned Readmission
Algorithm, which includes lists of
planned diagnoses and procedures, can
be found on the CMS Web site at http://
www.cms.gov/Medicare/QualityInitiatives-Patient-AssessmentInstruments/HospitalQualityInits/
Measure-Methodology.html. In addition
to the CMS Planned Readmission
Algorithm, this proposed measure
incorporates procedures that are
considered planned in post-acute care
settings, as identified in consultation
with TEPs. Full details on the planned
readmissions criteria used, including
the CMS Planned Readmission
Algorithm and additional procedures
considered planned for post-acute care,
can be found in the document titled,
Proposed Measure Specifications for

VerDate Sep<11>2014

19:36 Apr 22, 2016

Jkt 238001

Measures Proposed in the FY 2017 IRF
QRP proposed rule, available at https://
www.cms.gov/Medicare/QualityInitiatives-Patient-AssessmentInstruments/IRF-Quality-Reporting/IRFQuality-Reporting-Program-MeasuresInformation-.html.
The proposed measure, Potentially
Preventable 30-Day Post-Discharge
Readmission Measure for IRF QRP,
assesses potentially preventable
readmission rates while accounting for
patient demographics, principal
diagnosis in the prior hospital stay,
comorbidities, and other patient factors.
While estimating the predictive power
of patient characteristics, the model also
estimates a facility-specific effect,
common to patients treated in each
facility. This proposed measure is
calculated for each IRF based on the
ratio of the predicted number of riskadjusted, unplanned, potentially
preventable hospital readmissions that
occur within 30 days after an IRF
discharge, including the estimated
facility effect, to the estimated predicted
number of risk-adjusted, unplanned
inpatient hospital readmissions for the
same patients treated at the average IRF.
A ratio above 1.0 indicates a higher than
expected readmission rate (worse) while
a ratio below 1.0 indicates a lower than
expected readmission rate (better). This
ratio is referred to as the standardized
risk ratio (SRR). The SRR is then
multiplied by the overall national raw
rate of potentially preventable
readmissions for all IRF stays. The
resulting rate is the risk-standardized
readmission rate (RSRR) of potentially
preventable readmissions.
An eligible IRF stay is followed until:
(1) The 30-day post-discharge period
ends; or (2) the patient is readmitted to
an acute care hospital (IPPS or CAH) or
LTCH. If the readmission is unplanned
and potentially preventable, it is
counted as a readmission in the measure
calculation. If the readmission is
planned, the readmission is not counted
in the measure rate.
This measure is risk adjusted. The
risk adjustment modeling estimates the
effects of patient characteristics,
comorbidities, and select health care
variables on the probability of
readmission. More specifically, the riskadjustment model for IRFs accounts for
demographic characteristics (age, sex,
original reason for Medicare
entitlement), principal diagnosis during
the prior proximal hospital stay, body
system specific surgical indicators, IRF
case-mix groups which capture motor
function, comorbidities, and number of
acute care hospitalizations in the
preceding 365 days.

PO 00000

Frm 00029

Fmt 4701

Sfmt 4702

24205

The proposed measure is calculated
using 2 consecutive calendar years of
FFS claims data, to ensure the statistical
reliability of this measure for facilities.
In addition, we are proposing a
minimum of 25 eligible stays for public
reporting of the proposed measure.
A TEP convened by our measure
contractor provided recommendations
on the technical specifications of this
proposed measure, including the
development of an approach to define
potentially preventable hospital
readmission for PAC. Details from the
TEP meetings, including TEP members’
ratings of conditions proposed as being
potentially preventable, are available in
the TEP summary report available on
the CMS Web site at: https://
www.cms.gov/Medicare/QualityInitiatives-Patient-AssessmentInstruments/Post-Acute-Care-QualityInitiatives/IMPACT-Act-of-2014/
IMPACT-Act-Downloads-andVideos.html. We also solicited
stakeholder feedback on the
development of this measure through a
public comment period held from
November 2 through December 1, 2015.
Comments on the measure varied, with
some commenters supportive of the
proposed measure, while others either
were not in favor of the measure, or
suggested potential modifications to the
measure specifications, such as
including standardized function data. A
summary of the public comments is also
available on the CMS Web site at:
https://www.cms.gov/Medicare/QualityInitiatives-Patient-AssessmentInstruments/Post-Acute-Care-QualityInitiatives/IMPACT-Act-of-2014/
IMPACT-Act-Downloads-andVideos.html.
The MAP encouraged continued
development of the proposed measure.
Specifically, the MAP stressed the need
to promote shared accountability and
ensure effective care transitions. More
information about the MAP’s
recommendations for this measure is
available at: http://
www.qualityforum.org/Publications/
2016/02/MAP_2016_Considerations
_for_Implementing_Measures_
in_Federal_Programs_-_PAC-LTC.aspx.
At the time, the risk-adjustment model
was still under development. Following
completion of that development work,
we were able to test for measure validity
and reliability as identified in the
measure specifications document
provided above. Testing results are
within range for similar outcome
measures finalized in public reporting
and value-based purchasing programs,
including the All-Cause Unplanned
Readmission Measure for 30 Days Post

E:\FR\FM\25APP2.SGM

25APP2

24206

Federal Register / Vol. 81, No. 79 / Monday, April 25, 2016 / Proposed Rules

asabaliauskas on DSK3SPTVN1PROD with PROPOSALS

Discharge from IRFs (NQF #2502)
adopted into the IRF QRP.
We reviewed the NQF’s consensus
endorsed measures and were unable to
identify any NQF-endorsed measures
focused on potentially preventable
hospital readmissions. We are unaware
of any other measures for this IMPACT
Act domain that have been endorsed or
adopted by other consensus
organizations. Therefore, we are
proposing the Potentially Preventable
30-Day Post-Discharge Readmission
Measure for IRF QRP, under the
Secretary’s authority to specify nonNQF-endorsed measures under section
1899B(e)(2)(B) of the Act, for the IRF
QRP for the FY 2018 payment
determination and subsequent years,
given the evidence previously discussed
above.
We plan to submit the proposed
measure to the NQF for consideration of
endorsement. If this proposed measure
is finalized, we intend to provide initial
confidential feedback to providers, prior
to public reporting of this proposed
measure, based on 2 calendar years of
data from discharges in CY 2015 and
2016. We intend to publicly report this
proposed measure using data from CY
2016 and 2017.
We are inviting public comment on
our proposal to adopt the measure,
Potentially Preventable 30-Day PostDischarge Readmission Measure for IRF
QRP.
4. Potentially Preventable Within Stay
Readmission Measure for Inpatient
Rehabilitation Facilities
In addition to the measure proposed
in section VII.F.3. of the proposed rule,
Potentially Preventable 30-Day PostDischarge Readmission Measure for IRF
QRP, we are proposing the Potentially
Preventable Within Stay Readmission
Measure for IRFs for the FY 2018
payment determination and subsequent
years. This measure is similar to the
Potentially Preventable 30-Day PostDischarge Readmission Measure for IRF
QRP; however, the readmission window
for this proposed measure focuses on
potentially preventable hospital
readmissions that take place during the
IRF stay as opposed to during the 30day post-discharge period. The two
proposed PPR measures are intended to
function in tandem, covering
readmissions during the IRF stay and for
30 days following discharge from the
IRF. Our proposal for two PPR measures
for use in the IRF QRP will enable us
to assess different aspects of care and
care coordination. The proposed within
stay measure focuses on the care
transition into inpatient rehabilitation
as well as the care provided during the

VerDate Sep<11>2014

19:36 Apr 22, 2016

Jkt 238001

IRF stay, whereas the 30-day post-IRF
discharge measure focuses on
transitions from the IRF into lessintensive levels of care or the
community.
Similar to the Potentially Preventable
30-Day Post-Discharge Readmission
Measure for IRF QRP proposed measure
for IRFs, this measure assesses the
facility-level risk-standardized rate of
unplanned, potentially preventable
hospital readmissions during the IRF
stay. Hospital readmissions include
readmissions to a short-stay acute-care
hospital or an LTCH, with a diagnosis
considered to be unplanned and
potentially preventable. This Medicare
FFS measure is claims-based, requiring
no additional data collection or
submission burden for IRFs.
As described in section VII.F.3. of this
proposed rule, we developed the
approach for defining PPR measure
based on a comprehensive
environmental scan, analysis of claims
data, and TEP input. Also, we obtained
public comment.
The definition for PPRs differs by
readmission window. For the withinIRF stay window, PPRs should be
avoidable with sufficient medical
monitoring and appropriate patient
treatment. The list of PPR conditions for
the Potentially Preventable Within Stay
Readmission Measure for IRFs are
categorized by 4 clinical rationale
groupings:
• Inadequate management of chronic
conditions;
• Inadequate management of
infections;
• Inadequate management of other
unplanned events; and
• Inadequate injury prevention.
Additional details regarding the
definition for PPRs are available in our
document titled, Proposed Measure
Specifications for Measures Proposed in
the FY 2017 IRF QRP proposed rule
which can be found at https://
www.cms.gov/Medicare/QualityInitiatives-Patient-AssessmentInstruments/IRF-Quality-Reporting/IRFQuality-Reporting-Program-MeasuresInformation-.html.
Refer to section VII.F of this proposed
rule for the relevant background and
details that are also relevant for this
measure. This proposed measure
defines planned readmissions in the
same manner as described in section
VII.F.3 of this proposed rule, for the
Potentially Preventable 30-Day PostDischarge Readmission Measure for IRF
QRP. In addition, similar to the
Potentially Preventable 30-Day PostDischarge Readmission Measure for IRF
QRP proposed measure, this proposed
measure uses the same risk-adjustment

PO 00000

Frm 00030

Fmt 4701

Sfmt 4702

and statistical approach as described in
section VII.F.3 of this proposed rule.
Note the full methodology is detailed in
the document titled, Proposed Measure
Specifications for Measures Proposed in
the FY 2017 IRF QRP proposed rule, at
https://www.cms.gov/Medicare/QualityInitiatives-Patient-AssessmentInstruments/IRF-Quality-Reporting/IRFQuality-Reporting-Program-MeasuresInformation-.html. This measure is also
based on 2 consecutive calendar years of
Medicare FFS claims data.
A TEP convened by our measure
contractor provided recommendations
on the technical specifications of this
proposed measure, including the
development of an approach to define
potentially preventable hospital
readmission for PAC. Details from the
TEP meetings, including TEP members’
ratings of conditions proposed as being
potentially preventable, are available in
the TEP Summary Report available on
the CMS Web site at: https://
www.cms.gov/Medicare/QualityInitiatives-Patient-AssessmentInstruments/Post-Acute-Care-QualityInitiatives/IMPACT-Act-of-2014/
IMPACT-Act-Downloads-andVideos.html. We also solicited
stakeholder feedback on the
development of this measure through a
public comment period held from
November 2 through December 1, 2015.
Comments on this and other PAC
measures of PPR measures varied, with
some commenters supportive of the
proposed measure, while others either
were not in favor of the measure, or
suggested potential modifications to the
measure specifications, such as
including standardized function data. A
summary of our public comment period
is also available on the CMS Web site at:
https://www.cms.gov/Medicare/QualityInitiatives-Patient-AssessmentInstruments/Post-Acute-Care-QualityInitiatives/IMPACT-Act-of-2014/
IMPACT-Act-Downloads-andVideos.html.
The MAP encouraged continued
development of the proposed measure.
Specifically, the MAP stressed the need
to promote shared accountability and
ensure effective care transitions. More
information about the MAP’s
recommendations for this measure is
available at: http://
www.qualityforum.org/Publications/
2016/02/MAP_2016_Considerations
_for_Implementing_Measures_in_
Federal_Programs_-_PAC-LTC.aspx. At
the time, the risk-adjustment model was
still under development. Following
completion of that development work,
we were able to test for measure validity
and reliability as described in the
measure specifications document

E:\FR\FM\25APP2.SGM

25APP2

Federal Register / Vol. 81, No. 79 / Monday, April 25, 2016 / Proposed Rules
provided above. Testing results are
within range for similar outcome
measures finalized in public reporting
and value-based purchasing programs,
including the All-Cause Unplanned
Readmission Measure for 30 Days PostDischarge from IRFs (NQF #2502) that
we previously adopted into the IRF
QRP.
We plan to submit the proposed
measure to the NQF for consideration of
endorsement. If this proposed measure
is finalized, we intend to provide initial
confidential feedback to providers, prior
to public reporting of this proposed
measure, based on 2 calendar years of
claims data from discharges in 2015 and
2016. We propose a minimum of 25
eligible stays in a given IRF for public
reporting of the proposed measure for
that IRF. We intend to publicly report
this proposed measure using claims data
from calendar years 2016 and 2017.
We are inviting public comment on
our proposal to adopt this measure,
Potentially Preventable Within Stay
Readmission Measure for IRFs.

asabaliauskas on DSK3SPTVN1PROD with PROPOSALS

G. IRF QRP Quality Measure Proposed
for the FY 2020 Payment Determination
and Subsequent Years
In addition to the measures we are
retaining as described in section VII.E.
of this proposed rule under our policy
described in section VII.C. of this
proposed rule and the new quality
measures proposed in section VII.F of
this proposed rule for the FY 2018
payment determinations and subsequent
years, we are proposing one new quality
measure to meet the requirements of the
IMPACT Act for the FY 2020 payment
determination and subsequent years.
The proposed measure, Drug Regimen
Review Conducted with Follow-Up for
Identified Issues—PAC IRF QRP,
addresses the IMPACT Act quality
domain of Medication Reconciliation.
1. Quality Measure Addressing the
IMPACT Act Domain of Medication
Reconciliation: Drug Regimen Review
Conducted With Follow-Up for
Identified Issues-Post Acute Care IRF
QRP
Sections 1899B(a)(2)(E)(i)(III) and
1899B(c)(1)(C) of the Act, as added by
the IMPACT Act, require the Secretary
to specify a quality measure to address
the quality domain of medication
reconciliation by October 1, 2018 for
IRFs, LTCHs and SNFs by January 1,
2017 for HHAs. We are proposing to
adopt the quality measure, Drug
Regimen Review Conducted with
Follow-Up for Identified Issues–PAC
IRF QRP, for the IRF QRP as a patientassessment based, cross-setting quality
measure to meet the IMPACT Act

VerDate Sep<11>2014

19:36 Apr 22, 2016

Jkt 238001

requirements with data collection
beginning October 1, 2018 for the FY
2020 payment determinations and
subsequent years.
This proposed measure assesses
whether PAC providers were responsive
to potential or actual clinically
significant medication issue(s) when
such issues were identified.
Specifically, the proposed quality
measure reports the percentage of
patient stays in which a drug regimen
review was conducted at the time of
admission and timely follow-up with a
physician occurred each time potential
clinically significant medication issues
were identified throughout that stay.
For this proposed quality measure,
drug regimen review is defined as the
review of all medications or drugs the
patient is taking to identify any
potential clinically significant
medication issues. The proposed quality
measure utilizes both the processes of
medication reconciliation and a drug
regimen review, in the event an actual
or potential medication issue occurred.
The proposed measure informs whether
the PAC facility identified and
addressed each clinically significant
medication issue and if the facility
responded or addressed the medication
issue in a timely manner. Of note, drug
regimen review in PAC settings is
generally considered to include
medication reconciliation and review of
the patient’s drug regimen to identify
potential clinically significant
medication issues.73 This measure is
applied uniformly across the PAC
settings.
Medication reconciliation is a process
of reviewing an individual’s complete
and current medication list. Medication
reconciliation is a recognized process
for reducing the occurrence of
medication discrepancies that may lead
to Adverse Drug Events (ADEs).74
Medication discrepancies occur when
there is conflicting information
documented in the medical records. The
World Health Organization regards
medication reconciliation as a standard
operating protocol necessary to reduce
the potential for ADEs that cause harm
to patients. Medication reconciliation is
an important patient safety process that
addresses medication accuracy during
transitions in patient care and in
identifying preventable ADEs.75 The
Joint Commission added medication
reconciliation to its list of National
73 Institute of Medicine. Preventing Medication
Errors. Washington DC: National Academies Press;
2006.
74 Ibid.
75 Leotsakos A., et al. Standardization in patient
safety: The WHO High 5s project. Int J Qual Health
Care. 2014:26(2):109–116.

PO 00000

Frm 00031

Fmt 4701

Sfmt 4702

24207

Patient Safety Goals (2005), suggesting
that medication reconciliation is an
integral component of medication
safety.76 The Society of Hospital
Medicine published a statement in
agreement of the Joint Commission’s
emphasis and value of medication
reconciliation as a patient safety goal.77
There is universal agreement that
medication reconciliation directly
addresses patient safety issues that can
result from medication
miscommunication and unavailable or
incorrect information.78 79 80
The performance of timely medication
reconciliation is valuable to the process
of drug regimen review. Preventing and
responding to ADEs is of critical
importance as ADEs account for
significant increases in health services
utilization and costs 81 82 83 including
subsequent emergency room visits and
re-hospitalizations.84 Annual health
care costs in the United States are
estimated at $3.5 billion, resulting in
7,000 deaths annually.85 86
Medication errors include the
duplication of medications, delivery of
an incorrect drug, inappropriate drug
omissions, or errors in the dosage, route,
frequency, and duration of medications.
76 The Joint Commission. 2016 Long Term Care:
National Patient Safety Goals Medicare/Medicaid
Certification-based Option. (NPSG.03.06.01).
77 Greenwald, J.L., Halasyamani, L., Greene, J.,
LaCivita, C., et al. (2010). Making inpatient
medication reconciliation patient centered,
clinically relevant and implementable: A consensus
statement on key principles and necessary first
steps. Journal of Hospital Medicine, 5(8), 477–485.
78 Leotsakos A., et al. Standardization in patient
safety: The WHO High 5s project. Int J Qual Health
Care. 2014:26(2):109–116.
79 The Joint Commission. 2016 Long Term Care:
National Patient Safety Goals Medicare/Medicaid
Certification-based Option. (NPSG.03.06.01).
80 IHI. Medication Reconciliation to Prevent
Adverse Drug Events [Internet]. Cambridge, MA:
Institute for Healthcare Improvement; [cited 2016
Jan 11]. Available from: http://www.ihi.org/topics/
adesmedicationreconciliation/Pages/default.aspx.
81 Institute of Medicine. Preventing Medication
Errors. Washington DC: National Academies Press;
2006.
82 Jha A.K., Kuperman G.J., Rittenberg E., et al.
Identifying hospital admissions due to adverse drug
events using a computer-based monitor.
Pharmacoepidemiol Drug Saf. 2001;10(2):113–119.
83 Hohl C.M., Nosyk B., Kuramoto L., et al.
Outcomes of emergency department patients
presenting with adverse drug events. Ann Emerg
Med. 2011;58:270–279.
84 Kohn L.T., Corrigan J.M., Donaldson M.S. To
Err Is Human: Building a Safer Health System
Washington, DC: National Academies Press; 1999.
85 Greenwald, J.L., Halasyamani, L., Greene, J.,
LaCivita, C., et al. (2010). Making inpatient
medication reconciliation patient centered,
clinically relevant and implementable: A consensus
statement on key principles and necessary first
steps. Journal of Hospital Medicine, 5(8), 477–485.
86 Phillips, David P.; Christenfeld, Nicholas; and
Glynn, Laura M. Increase in US Medication-Error
Deaths between 1983 and 1993. The Lancet.
351:643–644, 1998.

E:\FR\FM\25APP2.SGM

25APP2

24208

Federal Register / Vol. 81, No. 79 / Monday, April 25, 2016 / Proposed Rules

asabaliauskas on DSK3SPTVN1PROD with PROPOSALS

Medication errors are one of the most
common types of medical error and can
occur at any point in the process of
ordering and delivering a medication.
Medication errors have the potential to
result in an ADE.87 88 89 90 91 92
Inappropriately prescribed medications
are also considered a major healthcare
concern in the United States for the
elderly population, with costs of
roughly $7.2 billion annually.93
There is strong evidence that
medication discrepancies occur during
transfers from acute care facilities to
post-acute care facilities. Discrepancies
occur when there is conflicting
information documented in the medial
records. Almost one-third of medication
discrepancies have the potential to
cause patient harm.94 An estimated 50
percent of patients experienced a
clinically important medication error
after hospital discharge in an analysis of
two tertiary care academic hospitals.95
Medication reconciliation has been
identified as an area for improvement
during transfer from the acute care
facility to the receiving post-acute care
facility. PAC facilities report gaps in
medication information between the
acute care hospital and the receiving
post-acute-care setting when performing
medication reconciliation.96 97 Hospital
87 Institute of Medicine. To err is human:
Building a safer health system. Washington, DC:
National Academies Press; 2000.
88 Lesar, T.S., Briceland, L., Stein, D.S. Factors
related to errors in medication prescribing. JAMA.
1997:277(4): 312–317.
89 Bond, C.A., Raehl, C.L., & Franke, T. Clinical
pharmacy services, hospital pharmacy staffing, and
medication errors in United States hospitals.
Pharmacotherapy. 2002:22(2): 134–147.
90 Bates, D.W., Cullen D.J., Laird, N., Petersen,
L.A., Small, S.D., et al. Incidence of adverse drug
events and potential adverse drug events.
Implications for prevention. JAMA. 1995:274(1):
29–34.
91 Barker, K.N., Flynn, E.A., Pepper, G.A., Bates,
D.W., & Mikeal, R.L. Medication errors observed in
36 health care facilities. JAMA. 2002: 162(16):1897–
1903.
92 Bates, D.W., Boyle, D.L., Vander, Vliet M.B.,
Schneider, J., & Leape, L. Relationship between
medication errors and adverse drug events. J Gen
Intern Med. 1995:10(4): 199–205.
93 Fu, Alex Z., et al. ‘‘Potentially inappropriate
medication use and healthcare expenditures in the
US community-dwelling elderly.’’ Medical care
45.5 (2007): 472–476.
94 Wong, Jacqueline D., et al. ‘‘Medication
reconciliation at hospital discharge: Evaluating
discrepancies.’’ Annals of Pharmacotherapy 42.10
(2008): 1373–1379.
95 Kripalani, S., Roumie, C.L., Dalal, A.K., et al.
Effect of a pharmacist intervention on clinically
important medication errors after hospital
discharge: A randomized controlled trial. Ann
Intern Med. 2012:157(1):1–10.
96 Gandara, Esteban, et al. ‘‘Communication and
information deficits in patients discharged to
rehabilitation facilities: An evaluation of five acute
care hospitals.’’ Journal of Hospital Medicine 4.8
(2009): E28–E33.
97 Gandara, Esteban, et al. ‘‘Deficits in discharge
documentation in patients transferred to

VerDate Sep<11>2014

19:36 Apr 22, 2016

Jkt 238001

discharge has been identified as a
particularly high risk time point, with
evidence that medication reconciliation
identifies high levels of discrepancy.98
99 100 101 102 103 Also, there is evidence
that medication reconciliation
discrepancies occur throughout the
patient stay.104 105 For older patients,
who may have multiple comorbid
conditions and thus multiple
medications, transitions between acute
and post-acute care settings can be
further complicated,106 and medication
reconciliation and patient knowledge
(medication literacy) can be inadequate
post-discharge.107 The proposed quality
measure, Drug Regimen Review
Conducted with Follow-Up for
Identified Issues—PAC IRF QRP,
provides an important component of
care coordination for PAC settings and
would affect a large proportion of the
Medicare population who transfer from
hospitals into PAC services each year.
For example, in 2013, 1.7 million
rehabilitation facilities on anticoagulation: Results
of a system wide evaluation.’’ Joint Commission
Journal on Quality and Patient Safety 34.8 (2008):
460–463.
98 Coleman, E.A., Smith, J.D., Raha, D., Min, S.J.
Post hospital medication discrepancies: Prevalence
and contributing factors. Arch Intern Med. 2005
165(16):1842–1847.
99 Wong, J.D., Bajcar, J.M., Wong, G.G., et al.
Medication reconciliation at hospital discharge:
Evaluating discrepancies. Ann Pharmacother. 2008
42(10):1373–1379.
100 Hawes, E.M., Maxwell, W.D., White, S.F.,
Mangun, J., Lin, F.C. Impact of an outpatient
pharmacist intervention on medication
discrepancies and health care resource utilization
in post hospitalization care transitions. Journal of
Primary Care & Community Health. 2014; 5(1):14–
18.
101 Foust, J.B., Naylor, M.D., Bixby, M.B.,
Ratcliffe, S.J. Medication problems occurring at
hospital discharge among older adults with heart
failure. Research in Gerontological Nursing. 2012,
5(1): 25–33.
102 Pherson, E.C., Shermock, K.M., Efird, L.E., et
al. Development and implementation of a post
discharge home-based medication management
service. Am J Health Syst Pharm. 2014; 71(18):
1576–1583.
103 Pronovosta, P., Weasta, B., Scwarza, M., et al.
Medication reconciliation: A practical tool to
reduce the risk of medication errors. J Crit Care.
2003; 18(4): 201–205.
104 Bates, D.W., Cullen, D.J., Laird, N., Petersen,
L.A., Small SD, et al. Incidence of adverse drug
events and potential adverse drug events.
Implications for prevention. JAMA. 1995:274(1):
29–34.
105 Himmel, W., M. Tabache, and M.M. Kochen.
‘‘What happens to long-term medication when
general practice patients are referred to hospital?.’’
European journal of clinical pharmacology 50.4
(1996): 253–257.
106 Chhabra, P.T., et al. (2012). ‘‘Medication
reconciliation during the transition to and from
long-term care settings: A systematic review.’’ Res
Social Adm Pharm 8(1): 60–75.
107 Kripalani, S., Roumie, C.L., Dalal, A.K., et al.
Effect of a pharmacist intervention on clinically
important medication errors after hospital
discharge: A randomized controlled trial. Ann
Intern Med. 2012:157(1):1–10.

PO 00000

Frm 00032

Fmt 4701

Sfmt 4702

Medicare FFS beneficiaries had SNF
stays, 338,000 beneficiaries had IRF
stays, and 122,000 beneficiaries had
LTCH stays.108
A TEP convened by our measure
development contractor provided input
on the technical specifications of this
proposed quality measure, Drug
Regimen Review Conducted with
Follow-Up for Identified Issues—PAC
IRF QRP, including components of
reliability, validity, and the feasibility of
implementing the measure across PAC
settings. The TEP supported the
measure’s implementation across PAC
settings and was supportive of our plans
to standardize this measure for crosssetting development. A summary of the
TEP proceedings is available on the PAC
Quality Initiatives Downloads and
Video Web site at https://www.cms.gov/
Medicare/Quality-Initiatives-PatientAssessment-Instruments/Post-AcuteCare-Quality-Initiatives/IMPACT-Act-of2014/IMPACT-Act-Downloads-andVideos.html.
We solicited stakeholder feedback on
the development of this measure by
means of a public comment period held
from September 18 through October 6,
2015. Through public comments
submitted by several stakeholders and
organizations, we received support for
implementation of this proposed
measure. The public comment summary
report for the proposed measure is
available on the CMS Web site at:
https://www.cms.gov/Medicare/QualityInitiatives-Patient-AssessmentInstruments/Post-Acute-Care-QualityInitiatives/IMPACT-Act-of-2014/
IMPACT-Act-Downloads-andVideos.html.
The NQF-convened MAP met on
December 14 and 15, 2015, and
provided input on the use of this
proposed measure, Drug Regimen
Review Conducted with Follow-Up for
Identified Issues—PAC IRF QRP. The
MAP encouraged continued
development of the proposed quality
measure to meet the mandate added by
the IMPACT Act. The MAP agreed with
the measure gaps identified by CMS,
including medication reconciliation,
and stressed that medication
reconciliation be present as an ongoing
process. More information about the
MAPs recommendations for this
measure is available at: http://
www.qualityforum.org/Publications/
2016/02/MAP_2016_Considerations_
for_Implementing_Measures_in_
Federal_Programs_-_PAC-LTC.aspx.
108 March 2015 Report to the Congress: Medicare
Payment Policy. Medicare Payment Advisory
Commission; 2015.

E:\FR\FM\25APP2.SGM

25APP2

asabaliauskas on DSK3SPTVN1PROD with PROPOSALS

Federal Register / Vol. 81, No. 79 / Monday, April 25, 2016 / Proposed Rules
Since the MAP’s review and
recommendation of continued
development, we have continued to
refine this proposed measure in
compliance with the MAP’s
recommendations. The proposed
measure is both consistent with the
information submitted to the MAP and
support its scientific acceptability for
use in quality reporting programs.
Therefore, we are proposing this
measure for implementation in the IRF
QRP as required by the IMPACT Act.
We reviewed the NQF’s endorsed
measures and identified one NQFendorsed cross-setting and quality
measure related to medication
reconciliation, which applies to the
SNF, LTCH, IRF, and HHA settings of
care: Care for Older Adults (COA), (NQF
#0553). The quality measure, Care for
Older Adults (COA), (NQF #0553)
assesses the percentage of adults 66
years and older who had a medication
review. The Care for Older Adults
(COA), (NQF #0553) measure requires at
least one medication review conducted
by a prescribing practitioner or clinical
pharmacist during the measurement
year and the presence of a medication
list in the medical record. This is in
contrast to the proposed quality
measure, Drug Regimen Review
Conducted with Follow-Up for
Identified Issues—PAC IRF QRP, which
reports the percentage of patient stays in
which a drug regimen review was
conducted at the time of admission and
that timely follow-up with a physician
occurred each time one or more
potential clinically significant
medication issues were identified
throughout that stay.
After careful review of both quality
measures, we have decided to propose
the quality measure, Drug Regimen
Review Conducted with Follow-Up for
Identified Issues—PAC IRF QRP for the
following reasons:
• The IMPACT Act requires the
implementation of quality measures,
using patient assessment data that are
standardized and interoperable across
PAC settings. The proposed quality
measure, Drug Regimen Review
Conducted with Follow-Up for
Identified Issues—PAC IRF QRP,
employs three standardized patientassessment data elements for each of the
four PAC settings so that data are
standardized, interoperable, and
comparable; whereas, the Care for Older
Adults (COA), (NQF #0553) quality
measure does not contain data elements
that are standardized across all four
PAC settings.
• The proposed quality measure,
Drug Regimen Review Conducted with
Follow-Up for Identified Issues—PAC

VerDate Sep<11>2014

19:36 Apr 22, 2016

Jkt 238001

IRF QRP, requires the identification of
potential clinically significant
medication issues at the beginning,
during, and at the end of the patient’s
stay to capture data on each patient’s
complete PAC stay; whereas, the Care
for Older Adults (COA), (NQF #0553)
quality measure only requires annual
documentation in the form of a
medication list in the medical record of
the target population.
• The proposed quality measure,
Drug Regimen Review Conducted with
Follow-Up for Identified Issues—PAC
IRF QRP, includes identification of the
potential clinically significant
medication issues and communication
with the physician (or physician
designee) as well as resolution of the
issue(s) within a rapid timeframe (by
midnight of the next calendar day);
whereas, the Care for Older Adults
(COA), (NQF #0553) quality measure
does not include any follow-up or
timeframe in which the follow-up
would need to occur.
• The proposed quality measure,
Drug Regimen Review Conducted with
Follow-Up for Identified Issues—PAC
IRF QRP, does not have age exclusions;
whereas, the Care for Older Adults
(COA), (NQF #0553) quality measure
limits the measure’s population to
patients aged 66 and older.
• The proposed quality measure,
Drug Regimen Review Conducted with
Follow-Up for Identified Issues—PAC
IRF QRP, would be reported to IRFs
quarterly to facilitate internal quality
monitoring and quality improvement in
areas such as patient safety, care
coordination, and patient satisfaction;
whereas, the Care for Older Adults
(COA), (NQF #0553) quality measure
would not enable quarterly quality
updates, and thus data comparisons
within and across PAC providers would
be difficult due to the limited data and
scope of the data collected.
Therefore, based on the evidence
discussed above, we are proposing to
adopt the quality measure entitled, Drug
Regimen Review Conducted with
Follow-Up for Identified Issues—PAC
IRF QRP, for the IRF QRP for FY 2020
payment determination and subsequent
years. We plan to submit the quality
measure to the NQF for consideration
for endorsement.
The calculation of the proposed
quality measure would be based on the
data collection of three standardized
items to be included in the IRF–PAI.
The collection of data by means of the
standardized items would be obtained at
admission and discharge. For more
information about the data submission
required for this proposed measure, we

PO 00000

Frm 00033

Fmt 4701

Sfmt 4702

24209

refer readers to section VII.I.c of this
proposed rule.
The standardized items used to
calculate this proposed quality measure
do not duplicate existing items
currently used for data collection within
the IRF–PAI. The proposed measure
denominator is the number of patient
stays with a discharge assessment
during the reporting period. The
proposed measure numerator is the
number of stays in the denominator
where the medical record contains
documentation of a drug regimen review
conducted at: (1) Admission and (2)
discharge with a lookback through the
entire patient stay with all potential
clinically significant medication issues
identified during the course of care and
followed up with a physician or
physician designee by midnight of the
next calendar day. This measure is not
risk adjusted. For technical information
about this proposed measure, including
information about the measure
calculation and discussion pertaining to
the standardized items used to calculate
this measure, we refer readers to the
document titled, Proposed Measure
Specifications for Measures Proposed in
the FY 2017 IRF QRP proposed rule
available at https://www.cms.gov/
Medicare/Quality-Initiatives-PatientAssessment-Instruments/IRF-QualityReporting/IRF-Quality-ReportingProgram-Measures-Information-.html.
Data for the proposed quality
measure, Drug Regimen Review
Conducted with Follow-Up for
Identified Issues—PAC IRF QRP, would
be collected using the IRF–PAI with
submission through the Quality
Improvement Evaluation System (QIES)
Assessment Submission and Processing
(ASAP) system.
We invite public comment on our
proposal to adopt the quality measure,
Drug Regimen Review Conducted with
Follow-Up for Identified Issues—PAC
IRF QRP for the IRF QRP.
H. IRF QRP Quality Measures and
Measure Concepts Under Consideration
for Future Years
We invite comment on the
importance, relevance, appropriateness,
and applicability of each of the quality
measures listed in Table 8 for future
years in the IRF QRP. We are developing
a measure related to the IMPACT Act
domain, ‘‘Accurately communicating
the existence of and providing for the
transfer of health information and care
preferences of an individual to the
individual, family caregiver of the
individual, and providers of services
furnishing items and services to the
individual, when the individual
transitions.’’ We are considering the

E:\FR\FM\25APP2.SGM

25APP2

24210

Federal Register / Vol. 81, No. 79 / Monday, April 25, 2016 / Proposed Rules

possibility of adding quality measures
that rely on the patient’s perspective;
that is, measures that include patientreported experience of care and health
status data. We recently posted a
‘‘Request for Information to Aid in the

Design and Development of a Survey
Regarding Patient and Family Member
Experiences with Care Received in
Inpatient Rehabilitation Facilities’’ (80
FR 72725 through 72727). Also, we are
considering a measure focused on pain

that relies on the collection of patientreported pain data. Finally, we are
considering a measure related to patient
safety, Venous Thromboembolism
Prophylaxis.

TABLE 8—IRF QRP QUALITY MEASURES UNDER CONSIDERATION FOR FUTURE YEARS
IMPACT Act Domain .......................
IMPACT Act Measure .....................
NQS Priority ....................................
Measures ........................................
NQS Priority ....................................
Measure ..........................................

Accurately communicating the existence of and providing for the transfer of health information and care
preferences of an individual to the individual, family caregiver of the individual, and providers of services
furnishing items and services to the individual, when the individual transitions.
• Transfer of health information and care preferences when an individual transitions.
Patient- and Caregiver-Centered Care.
• Patient Experience of Care.
• Percent of Patients with Moderate to Severe Pain.
Patient Safety.
• Venous Thromboembolism Prophylaxis.

I. Proposed Form, Manner, and Timing
of Quality Data Submission for the FY
2018 Payment Determination and
Subsequent Years
1. Background
Section 1886(j)(7)(C) of the Act
requires that, for the FY 2014 payment
determination and subsequent years,
each IRF submit to the Secretary data on
quality measures specified by the
Secretary. In addition, section
1886(j)(7)(F) of the Act requires that, for
the fiscal year beginning on the
specified application date, as defined in
section 1899B(a)(2)(E) of the Act, and
each subsequent year, each IRF submit
to the Secretary data on measures
specified by the Secretary under section
1899B of the Act. The data required
under section 1886(j)(7)(C) and (F) of
the Act must be submitted in a form and
manner, and at a time, specified by the
Secretary. As required by section
1886(j)(7)(A)(i) of the Act, for any IRF
that does not submit data in accordance
with section 1886(j)(7)(C) and (F) of the
Act for a given fiscal year, the annual
increase factor for payments for
discharges occurring during the fiscal
year must be reduced by 2 percentage
points.

a. Timeline for Data Submission Under
the IRF QRP for the FY 2018, FY 2019
and Subsequent Year Payment
Determinations
Tables 9 through 17 represent our
finalized data collection and data
submission quarterly reporting periods,
as well as the quarterly review and
correction periods and submission
deadlines for the quality measure data
submitted via the IRF–PAI and the CDC/
NHSN affecting the FY 2018 and
subsequent year payment
determinations. We also provide in
Table 17 our previously finalized
claims-based measures for FY 2018 and
subsequent years, although we note that,
for claims-based measures, there is no
corresponding quarterly-based data
collection or submission reporting
periods with quarterly-based review and
correction deadline periods.
Further, in the FY 2016 IRF PPS final
rule (80 FR 47122 through 47123), we
established that the IRF–PAI-based
measures finalized for adoption into the
IRF QRP would transition from
reporting based on the fiscal year to an
annual schedule consistent with the
calendar year, with quarterly reporting
periods followed by quarterly review
and correction periods and submission
deadlines, unless there is a clinical
reason for an alternative data collection
time frame. The pattern for annual,
calendar year-based data reporting, in

which we use 4 quarters of data, is
illustrated in Table 9 and is in place for
all Annual Payment Update (APU) years
except for the measure in Table 10 for
which the FY 2018 APU determination
will be based on 5 calendar year
quarters in order to transition this
measure from FY to CY reporting. We
also wish to clarify that payment
determinations for the measures
finalized for use in the IRF QRP that use
the IRF–PAI or CDC NHSN data sources
will subsequently use the quarterly data
collection/submission and review,
correction and submission deadlines
described in Table 9 unless otherwise
specified, as is with the measure NQF
#0680: Percent of Residents or Patients
Who Were Assessed and Appropriately
Given the Seasonal Influenza Vaccine.
For this measure, we clarify in a
subsequent discussion that the data
collection and reporting periods span
two consecutive years from July 1
through June 30th and we therefore
separately illustrate those collection/
submission quarterly reporting periods
and review and correction periods and
submission deadlines for FY 2019 and
subsequent years in Table 15. We also
separately distinguish the reporting
periods and data submission timeframes
for the finalized measure Influenza
Vaccination Coverage among Healthcare
Personnel which spans two consecutive
years in Table 16.

asabaliauskas on DSK3SPTVN1PROD with PROPOSALS

TABLE 9—ANNUAL QRP CY IRF–PAI & CDC/NHSN DATA COLLECTION/SUBMISSION REPORTING PERIODS AND DATA
SUBMISSION/CORRECTION DEADLINES ** PAYMENT DETERMINATIONS ∧
Proposed CY data
collection quarter
Quarter
Quarter
Quarter
Quarter

1
2
3
4

...................
...................
...................
...................

Data collection/submission quarterly
reporting period
January 1–March 31 * .........................
April 1–June 30 ...................................
July 1–September 30 ..........................
October 1–December 31 * ...................

QRP quarterly review and correction periods data submission deadlines for
payment determination **
April 1–August 15 * ..............................
July 1–November 15 ...........................
October 1–February 15 .......................
January 1–May 15 * .............................

Deadline:
Deadline:
Deadline:
Deadline:

August 15.*
November 15.
February 15.
May 15.*

* We refer readers to Table 16 for the annual data collection time frame for the measure, Influenza Vaccination Coverage among Healthcare
Personnel.

VerDate Sep<11>2014

19:36 Apr 22, 2016

Jkt 238001

PO 00000

Frm 00034

Fmt 4701

Sfmt 4702

E:\FR\FM\25APP2.SGM

25APP2

Federal Register / Vol. 81, No. 79 / Monday, April 25, 2016 / Proposed Rules

24211

** We note that the submission of IRF–PAI data must also adhere to the IRF PPS deadlines.
∧ We refer readers to Table 15 for the 12 month (July–June) data collection/submission quarterly reporting periods, review and correction periods and submission deadlines for APU determinations for the measure NQF #0680: Percent of Residents or Patients Who Were Assessed and
Appropriately Given the Seasonal Influenza Vaccine.

TABLE 10—SUMMARY DETAILS ON DATA COLLECTION PERIOD AND DATA SUBMISSION TIMELINE FOR PREVIOUSLY ADOPTED QUALITY MEASURE AFFECTING THE FY 2018 PAYMENT DETERMINATION THAT WILL USE 5 CY QUARTERS IN
ORDER TO TRANSITION FROM A FY TO A CY REPORTING CYCLE
Submission method

Data collection/submission quarterly
reporting period(s)

Quarterly review and correction periods data submission deadlines for
payment determination * * *

APU determination affected

Finalized Measure:
• NQF #0678 Percent of Residents or Patients with Pressure Ulcers That Are New or Worsened (Short Stay) (80 FR 47122)
IRF–PAI/QIES ASAP System

CY
CY
CY
CY
CY

15
16
16
16
16

Q4—10/1/15–12/31/15 ............
Q1—1/1/16–3/31/16 ................
Q2—4/1/16–6/30/16 ................
Q3—7/1/16–9/30/16 ................
Q4—10/01/16–12/31/16 ..........

1/1/2016–5/15/16 deadline .................
4/1/2016–8/15/16 deadline.
7/1/16–11/15/16 deadline.
10/1/16–2/15/17 deadline.
1/1/17–5/15/17 deadline.

FY 2018.

TABLE 11—SUMMARY DETAILS ON DATA COLLECTION PERIOD AND DATA SUBMISSION TIMELINE FOR PREVIOUSLY ADOPTED IRF–PAI QUALITY MEASURE, NQF #0680 PERCENT OF RESIDENTS OR PATIENTS WHO WERE ASSESSED AND APPROPRIATELY GIVEN THE SEASONAL INFLUENZA VACCINE, AFFECTING THE FY 2018 PAYMENT DETERMINATION
Submission method

Data collection/submission quarterly
reporting period(s)

Quarterly review and correction periods data submission deadlines for
payment determination *

APU determination affected

Finalized Measure:
• NQF #0680 Percent of Residents or Patients Who Were Assessed and Appropriately Given the Seasonal Influenza Vaccine (80 FR
47122)
IRF–PAI/QIES ASAP System

CY 15 Q4—10/1/15–12/31/15 ............
CY 16 Q1—1/1/16–3/31/16 ................
CY 16 Q2—4/1/16–6/30/16 ................

1/1/2016–5/15/16 deadline .................
4/1/2016–8/15/16 deadline.
7/1/16–11/15/16 deadline.

FY 2018.

* We note that the submission of IRF–PAI data must also adhere to the IRF PPS deadlines.

TABLE 12—SUMMARY DETAILS ON DATA COLLECTION PERIOD AND DATA SUBMISSION TIMELINE FOR PREVIOUSLY ADOPTED QUALITY MEASURES AFFECTING THE FY 2018 PAYMENT DETERMINATION THAT WILL USE ONLY 1 CY QUARTER
OF DATA INITIALLY FOR THE PURPOSE OF DETERMINING PROVIDER COMPLIANCE
Submission method

Data collection/submission quarterly
reporting period(s)

Quarterly review and correction periods data submission deadlines for
payment determination * * *

APU determination affected

Finalized Measure:
• NQF #0674 Application of Percent of Residents Experiencing One or More Falls with Major Injury (Long Stay) (80 FR 47122)
• NQF #2631 Application of Percent of Long-Term Care Hospital Patients with an Admission and Discharge Functional Assessment and a
Care Plan That Addresses Function (80 FR 47122)
• NQF #2633 IRF Functional Outcome Measure: Change in Self-Care Score for Medical Rehabilitation Patients (80 FR 47122)
• NQF #2634 IRF Functional Outcome Measure: Change in Mobility Score for Medical Rehabilitation Patients (80 FR 47122)
• NQF #2635 IRF Functional Outcome Measure: Discharge Self-Care Score for Medical Rehabilitation Patients (80 FR 47122)
• NQF #2636 IRF Functional Outcome Measure: Discharge Mobility Score for Medical Rehabilitation Patients (80 FR 47122)
IRF–PAI/QIES ASAP System

CY 16 Q4—10/1/16–12/31/16 ............

1/1/2017–5/15/17 ................................

FY 2018.

asabaliauskas on DSK3SPTVN1PROD with PROPOSALS

* We refer readers to the Table 9 for an illustration of the data collection/submission quarterly reporting periods and correction and submission
deadlines, which will be followed for the above measures, for all payment determinations subsequent to that of FY 2018.
** We note that the submission of IRF–PAI data must also adhere to the IRF PPS deadlines.

TABLE 13—SUMMARY DETAILS ON DATA COLLECTION PERIOD AND DATA SUBMISSION TIMELINE FOR PREVIOUSLY ADOPTED CDC/NHSN QUALITY MEASURES AFFECTING THE FY 2018 PAYMENT DETERMINATION AND SUBSEQUENT YEARS
THAT WILL USE 4 CY QUARTERS *
Submission method

Data collection/submission quarterly
reporting period(s)

Quarterly review and correction periods data submission deadlines for
payment determination

Finalized Measure:

VerDate Sep<11>2014

20:19 Apr 22, 2016

Jkt 238001

PO 00000

Frm 00035

Fmt 4701

Sfmt 4702

E:\FR\FM\25APP2.SGM

25APP2

APU determination affected

24212

Federal Register / Vol. 81, No. 79 / Monday, April 25, 2016 / Proposed Rules

Data collection/submission quarterly
reporting period(s)

Quarterly review and correction periods data submission deadlines for
payment determination

APU determination affected

• NQF #0138 NHSN Catheter-Associated Urinary Tract Infection (CAUTI) Outcome Measure (80 FR 47122 through 47123)
• NQF #1716 NHSN Facility-wide Inpatient Hospital-onset Methicillin-resistant Staphylococcus aureus (MRSA) Bacteremia Outcome Measure (80 FR 47122 through 47123)
• NQF #1717 NHSN Facility-wide Inpatient Hospital-onset Clostridium difficile Infection (CDI) Outcome Measure (79 FR 45917)
CDC/NHSN ..............................

CY 16 Q1—1/1/16–3/31/16 and Q1 of
subsequent Calendar Years.
CY 16 Q2—4/1/16–6/30/16 and Q2 of
subsequent Calendar Years.
CY 16 Q3—7/1/16–9/30/16 and Q3 of
subsequent Calendar Years.
CY 16 Q4—10/1/16–12/31/16 and Q4
of subsequent Calendar Years.

4/1/2016–8/15/16 ** and 4/1–8/15
subsequent years.
7/1/16–11/15/16 **nand 7/1–11/15
subsequent years.
10/1/16–2/15/17 ** and 10/1–2/15
subsequent years.
1/1/17–5/15/17 ** and 1/1–5/15
subsequent years.

FY 2018 and subsequent
years.**

of
of
of

* We refer readers to the Table 9 for an illustration of the data collection/submission quarterly reporting periods and correction and submission
deadlines.
** As is illustrated in Table 9: Subsequent years follow the same CY Quarterly Data Collection/submission Quarterly Reporting Periods and
Quarterly Review and Correction Periods Deadlines for Payment Determination in which every CY quarter is followed by approximately 135 days
for IRFs to review and correct their data until midnight on the final submission deadline dates.

TABLE 14—SUMMARY DETAILS ON DATA COLLECTION PERIOD AND DATA SUBMISSION TIMELINE FOR PREVIOUSLY ADOPTED IRF–PAI QUALITY MEASURES AFFECTING THE FY 2019 PAYMENT DETERMINATION AND SUBSEQUENT YEARS
THAT WILL USE 4 CY QUARTERS
Submission method

Data collection/submission quarterly
reporting period(s)

Quarterly review and correction periods data submission deadlines for
payment determination * * *

APU determination affected

Finalized Measure:
• NQF #0678 Percent of Residents or Patients with Pressure Ulcers That Are New or Worsened (Short Stay) (80 FR 47122)
• NQF #0674 Application of Percent of Residents Experiencing One or More Falls with Major Injury (Long Stay) (80 FR 47122)
• NQF #2631 Application of Percent of Long-Term Care Hospital Patients with an Admission and Discharge Functional Assessment and a
Care Plan That Addresses Function (80 FR 47122)
• NQF #2633 IRF Functional Outcome Measure: Change in Self-Care Score for Medical Rehabilitation Patients (80 FR 47122)
• NQF #2634 IRF Functional Outcome Measure: Change in Mobility Score for Medical Rehabilitation Patients (80 FR 47122)
• NQF #2635 IRF Functional Outcome Measure: Discharge Self-Care Score for Medical Rehabilitation Patients (80 FR 47122)
• NQF #2636 IRF Functional Outcome Measure: Discharge Mobility Score for Medical Rehabilitation Patients (80 FR 47122)
IRF–PAI/QIES ASAP System

CY 17 Q1—1/1/17–3/31/17 and Q1 of
subsequent Calendar Years.
CY 17 Q2—4/1/17–6/30/17 and Q2 of
subsequent Calendar Years.
CY 17 Q3—7/1/17–9/30/17 and Q3 of
subsequent Calendar Years.
CY 17 Q4—10/1/17–12/31/17 and Q4
of subsequent Calendar Years.

4/1/2017–8/15/17 *** and 4/1–8/15
subsequent years.
7/1/17–11/15/17 *** and 7/1–11/15
subsequent years.
10/1/17–2/15/18 *** and 10/1–1/15
subsequent years.
1/1/18–5/15/18 *** and 1/1–5/15
subsequent years.

FY 2019 and subsequent
years.***

of
of
of

asabaliauskas on DSK3SPTVN1PROD with PROPOSALS

* We refer readers to the Table 9 for an illustration of the data collection/submission quarterly reporting periods and correction and submission
deadlines.
** We note that the submission of IRF–PAI data must also adhere to the IRF PPS deadlines.
*** As is illustrated in Table 9: Subsequent years follow the same CY Quarterly Data Collection/submission Quarterly Reporting Periods and
Quarterly Review and Correction Periods) and Data Submission Deadlines for Payment Determination in which every CY quarter is followed by
approximately 135 days for IRFs to review and correct their data until midnight on the final submission deadline dates.

In the FY 2014 IRF PPS final rule, we
adopted the Percent of Residents or
Patients Who Were Assessed and
Appropriately Given the Seasonal
Influenza Vaccine (Short Stay) (NQF
#0680) measure for the FY 2017
payment determination and subsequent
years (78 FR 47910 through 47911). In
the FY 2014 IRF PPS final rule (78 FR
47917 through 47919), we finalized the
data submission timelines and
submission deadlines for the measures

VerDate Sep<11>2014

20:28 Apr 22, 2016

Jkt 238001

for FY 2017 payment determination.
Refer to the FY 2014 final rule for a
more detailed discussion of these
timelines and deadlines.
We would like to clarify that this
measure includes all patients in the IRF
one or more days during the influenza
vaccination season (IVS) (October 1 of
any given CY through March 31 of the
subsequent CY). This includes, for
example, a patient is admitted
September 15, 2015, and discharged

PO 00000

Frm 00036

Fmt 4701

Sfmt 4702

April 1, 2016 (thus, the patient was in
the IRF during the 2015–2016 influenza
vaccination season). If a patient’s stay
did not include one or more days in the
IRF during the IVS, IRFs must also
complete the influenza items. For
example, if a patient was admitted after
April 1, 2016, and discharged
September 30, 2016, and the patient did
not receive the influenza vaccine during
the IVS, IRFs should code the reason the
patient did not receive the influenza

E:\FR\FM\25APP2.SGM

25APP2

Federal Register / Vol. 81, No. 79 / Monday, April 25, 2016 / Proposed Rules
vaccination as ‘‘patient was not in the
facility during this year’s influenza
vaccination season.’’
Further, we wish to clarify that the
data submission timeline for this
measure includes 4 calendar quarters
and is based on the influenza season
(July 1 through June 30 of the
subsequent year), rather than on the
calendar year. For the purposes of APU
determination and for public reporting,
data calculation and analysis uses data
from an influenza vaccination season
that is within the influenza season
itself. While the influenza vaccination
season is October 1 of a given year (or
when the vaccine becomes available)
through March 31 of the subsequent
year, this timeframe rests within a
greater time period of the influenza
season which spans 12 months—that is
July 1 of a given year through June 30
of the subsequent year. Thus for this
measure, we utilize data from a
timeframe of 12 months that mirrors the
influenza season which is July 1 of a
given year through June 30th of the
subsequent year. Additionally, for the
APU determination, we review data that
has been submitted beginning on July 1

of the calendar year 2 years prior to the
calendar year of the APU effective date
and ending June 30 of the subsequent
calendar year, one year prior to the
calendar year of the APU effective date.
For example, and as provided in Table
15 for the FY 2019 (October 1, 2018)
APU determination, we review data
submission beginning July 1 of 2016
through June 30th of June 2017 for the
2016/2017 influenza vaccination season,
so as to capture all data that an IRF will
have submitted with regard to the 2016/
2017 Influenza season itself. We will
use assessment data for that time period
as well for public reporting. Further,
because we enable the opportunity to
review and correct data for all
assessment based IRF–PAI measures
within the IRF QRP, we continue to
follow quarterly calendar data
collection/submission quarterly
reporting period(s) and their subsequent
quarterly review and correction periods
with data submission deadlines for
public reporting and payment
determinations. However, rather than
using CY timeframe, these quarterly
data collection/submission periods and
their subsequent quarterly review and

24213

correction periods and submission
deadlines begin with CY quarter 3, July
1, of a given year and end June 30th, CY
quarter 2, of the following year. For
further information on data collection
for this measure, please refer to section
4 of the IRF–PAI training manual, which
is available on the CMS IRF QRP
Measures Information Web site at
https://www.cms.gov/Medicare/QualityInitiatives-Patient-AssessmentInstruments/IRF-Quality-Reporting/IRFQuality-Reporting-Program-MeasuresInformation-.html, under the downloads
section. For further information on data
submission of the IRF–PAI, please refer
to the IRF–PAI Data Specifications
Version 1.12.1 (FINAL)—in effect on
October 1, 2015, available for download
at https://www.cms.gov/Medicare/
Medicare-Fee-for-Service-Payment/
InpatientRehabFacPPS/Software.html.
Refer to Table 15 for details about the
quarterly data collection/submission
and the review and correction deadlines
for FY 2019 and subsequent years for
NQF #0680 Percent of Residents or
Patients Who Were Assessed and
Appropriately Given the Seasonal
Influenza Vaccine.

TABLE 15—SUMMARY DETAILS ON DATA COLLECTION PERIOD AND DATA SUBMISSION TIMELINE FOR PREVIOUSLY ADOPTED IRF–PAI QUALITY MEASURE, NQF #0680 PERCENT OF RESIDENTS OR PATIENTS WHO WERE ASSESSED AND APPROPRIATELY GIVEN THE SEASONAL INFLUENZA VACCINE, AFFECTING THE FY 2019 PAYMENT DETERMINATION AND
SUBSEQUENT YEARS *
Submission method

Data collection/submission quarterly
reporting period(s)

Quarterly review and correction periods data submission deadlines for
payment determination **

APU determination affected

Finalized Measure:
• NQF #0680 Percent of Residents or Patients Who Were Assessed and Appropriately Given the Seasonal Influenza Vaccine (80 FR
47122)
IRF–PAI/QIES ASAP System

CY 16 Q3—7/1/16–9/30/16 and Q3 of
subsequent Calendar Years.
CY 16 Q4—10/1/16–12/31/16 and Q4
of subsequent Calendar Years.
CY 17 Q1—1/1/17–3/31/17 and Q1 of
subsequent Calendar Years.
CY 17 Q2—4/1/17–6/30/17 and Q2 of
subsequent Calendar Years.

10/1/16–2/15/17 ** and
subsequent years.
1/1/17–5/15/17 ** and
subsequent years.
4/1/17–8/15/17 ** and
subsequent years.
7/1/17–11/15/17 ** and
subsequent years.

10/1–2/15 of
1/1–5/15

4/1–8/15

FY 2019 and subsequent
years.**

7/1–11/15 of

asabaliauskas on DSK3SPTVN1PROD with PROPOSALS

* We note that the submission of IRF–PAI data must also adhere to the IRF PPS deadlines.
** As is illustrated in Table 9: Subsequent years follow the same CY Quarterly Data Collection/submission Quarterly Reporting Periods and
Quarterly Review and Correction Periods (IRF–PAI) and Data Submission (CDC/NHSN) Deadlines for Payment Determination in which every CY
quarter is followed by approximately 135 days for IRFs to review and correct their data until midnight on the final submission deadline dates.

We finalized in the FY 2014 IRF PPS
final rule (78 FR 47905 through 47906)
that for FY 2018 and subsequent years
IRFs would submit data on the quality
measure Influenza Vaccination Coverage
among Healthcare Personnel (NQF
#0431) beginning with data submission
starting October 1, 2015. To clarify that
while the data collected by IRFs for this
measure includes vaccination
information for a flu vaccination season
that begins October 1 (or when the

VerDate Sep<11>2014

19:36 Apr 22, 2016

Jkt 238001

vaccine becomes available) of a given
year through March 31 of the
subsequent year, the CDC/NHSN system
only allows for the submission of the
corresponding data any time between
October 1 of a given year until March 31
of the subsequent year; however,
corrections can be made to such data
until May 15th of that year. Quality data
for this measure are only required to be
submitted once per IVS (Oct 1 through
March 31), but must be submitted prior

PO 00000

Frm 00037

Fmt 4701

Sfmt 4702

to the May 15 deadline for the year in
which the IVS ends; quarterly reporting
is not required. For example, for FY
2018 payment determinations, while
IRFs can begin immunizing their staff
when the vaccine is available
throughout the influenza vaccine season
which ends on March 31, 2016, IRFs can
only begin submitting the data for this
measure via the CDC/NHSN system
starting on October 1, 2015, and may do
so up until May 15 of 2016.

E:\FR\FM\25APP2.SGM

25APP2

24214

Federal Register / Vol. 81, No. 79 / Monday, April 25, 2016 / Proposed Rules

TABLE 16—SUMMARY DETAILS ON THE DATA SUBMISSION TIMELINE AND CORRECTION DEADLINE TIMELINE FOR THE
PREVIOUSLY ADOPTED INFLUENZA VACCINATION COVERAGE AMONG HEALTHCARE PERSONNEL AFFECTING CY 2018
AND SUBSEQUENT YEARS
Influenza vaccination coverage
among healthcare personnel
data submission quarters+

Data submission period

CY QTR 4 through Subsequent
CY QTR 1.

10/1/15–3/31/16 and 10/1–3/31 of
subsequent years.

Review and correction periods data submission (CDC/NHSN) deadlines for payment determination++
4/1/16–5/15/16 and 4/1–5/15 of
subsequent years.

Deadline: May 15, 2016 and May
15 of subsequent years.

+ Data on this measure may be submitted via the CDC/NHSN system from October 1 of a given year through May 15 of the subsequent year.
++ A time period of April 1-May 15th is also allotted for the submission, review, and corrections.

TABLE 17—FINALIZED IRF QRP CLAIMS-BASED MEASURE AFFECTING FY 2018 AND SUBSEQUENT YEARS
Quality measure

Data submission method

Performance period

NQF #2502 All-Cause Unplanned Readmission
Measure for 30 Days Post-Discharge from
Inpatient Rehabilitation Facilities (80 FR
47087 through 47089).

Medicare FFS Claims .......................................

CY 2013 and 2014 for public reporting in
2016.
CY 2014 and 2015 for public reporting in
2017.

b. Proposed Timeline and Data
Submission Mechanisms for the FY
2018 Payment Determination and
Subsequent Years for the Proposed IRF
QRP Resource Use and Other Measures
Claims-Based Measures

IRFs, and CYs 2016 and 2017 claims
data for public reporting,
We invite public comments on this
proposal.

Payment/InpatientRehabFacPPS/
IRFPAI.html.
For the FY 2020 payment
determinations, we propose to collect
CY 2018 4th quarter data, that is
beginning with discharges on October 1,
2018, through discharges on December
31, 2018, to remain consistent with the
usual October release schedule for the
IRF–PAI, to give IRFs sufficient time to
update their systems so that they can
comply with the new data reporting
requirements, and to give us sufficient
time to determine compliance for the FY
2020 program. The proposed use of 1
quarter of data for the initial year of
assessment data reporting in the IRF
QRP is consistent with the approach we
used previously for the SNF, LTCH, and
Hospice QRPs.
Table 18 presents the proposed data
collection period and data submission
timelines for the new proposed IRF QRP
Quality Measure for the FY 2020
Payment Determination. We invite
public comments on this proposal.

The MSPB PAC IRF QRP measure;
Discharge to Community PAC IRF QRP
measure; Potentially Preventable 30-Day
Post-Discharge Readmission Measure for
IRF QRP, and Potentially Preventable
Within Stay Readmission Measure for
IRFs, which we have proposed in this
proposed rule, are Medicare FFS claimsbased measures. Because claims-based
measures can be calculated based on
data that are already reported to the
Medicare program for payment
purposes, no additional information
collection will be required from IRFs.
As discussed in section VII.F of this
proposed rule, these measures will use
2 years of claims-based data beginning
with CY 2015 and CY 2016 claims to
inform confidential feedback reports for

c. Proposed Timeline and Data
Submission Mechanisms for the IRF
QRP Quality Measure for the FY 2020
Payment Determination and Subsequent
Years
As discussed in section VII.F of this
proposed rule, we propose that the data
for the proposed quality measure, Drug
Regimen Review Conducted with
Follow-Up for Identified Issues—PAC
IRF QRP, affecting FY 2020 payment
determination and subsequent years, be
collected by completing data elements
that would be added to the IRF–PAI
with submission through the QIES–
ASAP system. Data collection would
begin on October 1, 2018. More
information on IRF reporting using the
QIES–ASAP system is located at the
Web site at http://www.cms.gov/
Medicare/Medicare-Fee-for-Service-

TABLE 18—DETAILS ON THE PROPOSED DATA COLLECTION PERIOD AND DATA SUBMISSION TIMELINE FOR RESOURCE
USE AND OTHER MEASURES AFFECTING THE FY 2020 PAYMENT DETERMINATION
Quality measure

asabaliauskas on DSK3SPTVN1PROD with PROPOSALS

Drug Regimen Review Conducted with Follow-Up for
Identified Issues PAC IRF
QRP.

Submission method
IRF–PAI/QIES
ASAP.

Data collection period

Data correction deadlines*

CY 2018 Q4 10/1/18–12/31/18;
Quarterly for each subsequent calendar year.

5/15/19 Quarterly approximately
135 days after the end of
each quarter for subsequent
years.

APU determination
affected
FY 2020.

* We note that the submission of IRF–PAI data must also adhere to the IRF PPS deadlines.

Following the close of the reporting
quarter, October 1, 2018, through
December 31, 2018, for the FY 2020
payment determination, IRFs would
have the already established additional
4.5 months to correct their quality data
and that the final deadline for correcting

VerDate Sep<11>2014

19:36 Apr 22, 2016

Jkt 238001

data for the FY 2020 payment
determination would be May 15, 2019
for these measures. We further propose
that for the FY 2021 payment
determination and subsequent years, we
will collect data using the calendar year
reporting cycle as described in section

PO 00000

Frm 00038

Fmt 4701

Sfmt 4702

VII.I.c of this proposed rule, and
illustrated in Table 19. We invite public
comments on this proposal.

E:\FR\FM\25APP2.SGM

25APP2

Federal Register / Vol. 81, No. 79 / Monday, April 25, 2016 / Proposed Rules

24215

TABLE 19—PROPOSED DATA COLLECTION PERIOD AND DATA CORRECTION DEADLINES* AFFECTING THE FY 2021
PAYMENT DETERMINATION AND SUBSEQUENT YEARS

Quality measure

Drug Regimen Review Conducted with Follow-Up for
Identified Issues PAC IRF
QRP.

Submission method

IRF–PAI/QIES
ASAP.

Proposed CY data collection
quarter

Proposed data collection period

Proposed quarterly
review and data
correction periods *
deadlines for payment determination

Quarter 1 ...................................

January 1– March 31 ................

April 1– August 15.

Quarter 2 ...................................

April 1–June 30 .........................

Quarter 3 ...................................

July 1– September 30 ...............

Quarter 4 ...................................

October 1– December 31 .........

July 1–November
15.
October 1– February 15.
January 1– May
15.

asabaliauskas on DSK3SPTVN1PROD with PROPOSALS

* We note that the submission of IRF–PAI data must also adhere to the IRF PPS deadlines

J. IRF QRP Data Completion Thresholds
for the FY 2016 Payment Determination
and Subsequent Years
In the FY 2015 IRF PPS final rule (79
FR 45921 through 45923), we finalized
IRF QRP thresholds for completeness of
IRF data submissions. To ensure that
IRFs are meeting an acceptable standard
for completeness of submitted data, we
finalized the policy that, beginning with
the FY 2016 payment determination and
for each subsequent year, IRFs must
meet or exceed two separate data
completeness thresholds: One threshold
set at 95 percent for completion of
quality measures data collected using
the IRF–PAI submitted through the
QIES and a second threshold set at 100
percent for quality measures data
collected and submitted using the CDC
NHSN.
Additionally, we stated that we will
apply the same thresholds to all
measures adopted as the IRF QRP
expands and IRFs begin reporting data
on previously finalized measure sets.
That is, as we finalize new measures
through the regulatory process, IRFs
will be held accountable for meeting the
previously finalized data completion
threshold requirements for each
measure until such time that updated
threshold requirements are proposed
and finalized through a subsequent
regulatory cycle.
Further, we finalized the requirement
that an IRF must meet or exceed both
thresholds to avoid receiving a 2
percentage point reduction to their
annual payment update for a given
fiscal year, beginning with FY 2016 and
for all subsequent payment updates. For
a detailed discussion of the finalized
IRF QRP data completion requirements,
please refer to the FY 2015 IRF PPS final
rule (79 FR 45921 through 45923). We
propose to codify the IRF QRP Data
Completion Thresholds at § 412.634. We

VerDate Sep<11>2014

19:36 Apr 22, 2016

Jkt 238001

invite public comments on this
proposal.
K. IRF QRP Data Validation Process for
the FY 2016 Payment Determination
and Subsequent Years
Validation is intended to provide
added assurance of the accuracy of the
data that will be reported to the public
as required by sections 1886(j)(7)(E) and
1899B(g) of the Act. In the FY 2015 IRF
PPS rule (79 FR 45923), we finalized, for
the FY 2016 adjustments to the IRF PPS
annual increase factor and subsequent
years, a process to validate the data
submitted for quality purposes.
However, in the FY 2016 IRF PPS final
rule (80 FR 47124), we finalized our
decision to temporarily suspend the
implementation of this policy. We are
not proposing a data validation policy at
this time, as we are developing a policy
that could be applied to several PAC
QRPs. We intend to propose a data
validation policy through future
rulemaking.
L. Previously Adopted and Codified IRF
QRP Submission Exception and
Extension Policies
Refer to § 412.634 for requirements
pertaining to submission exception and
extension for the FY 2017 payment
determination and subsequent years. At
this time, we are proposing to revise
§ 412.634 to change the timing for
submission of these exception and
extension requests from 30 days to 90
days from the date of the qualifying
event which is preventing an IRF from
submitting their quality data for the IRF
QRP. We are proposing the increased
time allotted for the submission of the
requests from 30 to 90 days to be
consistent with other quality reporting
programs; for example, the Hospital
Inpatient Quality Reporting (IQR)
Program is also proposing to extend the

PO 00000

Frm 00039

Fmt 4701

Sfmt 4702

deadline to 90 days in section
VIII.A.15.a. of the FY 2017 IPPS/LTCH
PPS proposed rule published elsewhere
in this issue of the Federal Register. We
believe that this increased time will
assist providers experiencing an event
in having the time needed to submit
such a request. We believe that allowing
only 30 days was insufficient. With the
exception of this one change, we are not
proposing any additional changes to the
exception and extension policies for the
IRF QRP at this time.
We invite public comments on the
proposal to revise § 412.634 to change
the timing for submission of these
exception and extension requests from
30 days to 90 days from the date of the
qualifying event which is preventing an
IRF from submitting their quality data
for the IRF QRP.
M. Previously Adopted and Finalized
IRF QRP Reconsideration and Appeals
Procedures
Refer to § 412.634 for a summary of
our finalized reconsideration and
appeals procedures for the IRF QRP for
FY 2017 payment determination and
subsequent years. We are not proposing
any changes to this policy. However, we
wish to clarify that in order to notify
IRFs found to be non-compliant with
the reporting requirements set forth for
a given payment determination, we may
include the QIES mechanism in
addition to US Mail, and we may elect
to utilize the MACs to administer such
notifications.
N. Public Display of Measure Data for
the IRF QRP & Procedures for the
Opportunity To Review and Correct
Data and Information
1. Public Display of Measures
Section 1886(j)(7)(E) of the Act
requires the Secretary to establish
procedures for making the IRF QRP data

E:\FR\FM\25APP2.SGM

25APP2

asabaliauskas on DSK3SPTVN1PROD with PROPOSALS

24216

Federal Register / Vol. 81, No. 79 / Monday, April 25, 2016 / Proposed Rules

available to the public. In the FY 2016
IRF PPS final rule (80 FR 47126 through
47127), we finalized our proposals to
display performance data for the IRF
QRP quality measures by Fall 2016 on
a CMS Web site, such as the Hospital
Compare, after a 30-day preview period,
and to give providers an opportunity to
review and correct data submitted to the
QIES–ASAP system or to the CDC
NHSN. The procedures for the
opportunity to review and correct data
are provided in the following section. In
addition, we finalized the proposal to
publish a list of IRFs that successfully
meet the reporting requirements for the
applicable payment determination on
the IRF QRP Web site at https://
www.cms.gov/Medicare/QualityInitiatives-Patient-AssessmentInstruments/IRF-Quality-Reporting/
Spotlights-Announcements.html. In the
FY 2016 IRF PPS final rule, we finalized
that we would update the list after the
reconsideration requests are processed
on an annual basis.
Also, in the FY 2016 IRF PPS final
rule (80 FR 47126 through 47127), we
also finalized that the display of
information for fall 2016 contains
performance data on three quality
measures:
• Percent of Residents or Patients
with Pressure Ulcers That Are New or
Worsened (Short Stay) (NQF #0678);
• NHSN CAUTI Outcome Measure
(NQF #0138); and
• All-Cause Unplanned Readmission
Measure for 30 Days Post-Discharge
from IRFs (NQF #2502).
The measures Percent of Residents or
Patients with Pressure Ulcers That Are
New or Worsened (Short Stay) (NQF
#0678) and NHSN CAUTI Outcome
Measure (NQF #0138) are based on data
collected beginning with the first
quarter of 2015 or discharges beginning
on January 1, 2015. With the exception
of the All-Cause Unplanned
Readmission Measure for 30 Days PostDischarge from IRFs (NQF #2502), rates
are displayed based on 4 rolling quarters
of data and would initially use
discharges from January 1, 2015,
through December 31, 2015 (CY 2015)
for Percent of Residents or Patients with
Pressure Ulcers That Are New or
Worsened (Short Stay) (NQF #0678) and
data collected from January 1, 2015,
through December 31, 2015 (CY 2015)
for NHSN CAUTI Outcome Measure
(NQF #0138). For the readmissions
measure, data will be publicly report
beginning with data collected for
discharges beginning January 1, 2013,
and rates would be displayed based on
2 consecutive years of data. For IRFs
with fewer than 25 eligible cases, we
propose to assign the IRF to a separate

VerDate Sep<11>2014

19:36 Apr 22, 2016

Jkt 238001

category: ‘‘The number of cases is too
small (fewer than 25) to reliably tell
how well the IRF is performing.’’ If an
IRF has fewer than 25 eligible cases, the
IRF’s readmission rates and interval
estimates will not be publicly reported
for the measure.
Calculations for all three measures are
discussed in detail in the FY 2016 IRF
PPS final rule (80 FR 47126 through
47127).
Pending the availability of data, we
are proposing to publicly report data in
CY 2017 on 4 additional measures
beginning with data collected on these
measures for the first quarter of 2015, or
discharges beginning on January 1,
2015: (1) Facility-wide Inpatient
Hospital-onset Methicillin-resistant
Staphylococcus aureus (MRSA)
Bacteremia Outcome Measure (NQF
#1716) ; (2) Facility-wide Inpatient
Hospital-onset Clostridium difficile
Infection (CDI) Outcome Measure (NQF
#1717) and, beginning with the 2015–16
influenza vaccination season, these two
measures; (3) Influenza Vaccination
Coverage Among Healthcare Personnel
(NQF #0431); and (4) Percent of
Residents or Patients Who Were
Assessed and Appropriately Given the
Seasonal Influenza Vaccine (NQF
#0680).
Standardized infection ratios (SIRs)
for the Facility-wide Inpatient Hospitalonset Methicillin-resistant
Staphylococcus aureus (MRSA)
Bacteremia Outcome Measure (NQF
#1716) and Facility-wide Inpatient
Hospital-onset Clostridium difficile
Infection (CDI) Outcome Measure (NQF
#1717) would be displayed based on 4
rolling quarters of data and would
initially use MRSA bacteremia and CDI
events that occurred from January 1,
2015 through December 31, 2015 (CY
2015), for calculations. We are
proposing that the display of these
ratios would be updated quarterly.
Rates for the Influenza Vaccination
Coverage Among Healthcare Personnel
(NQF #0431) would be displayed for
personnel working in the reporting
facility October 1, 2015 through March
31, 2016. Rates for the Percent of
Residents or Patients Who Were
Assessed and Appropriately Given the
Seasonal Influenza Vaccine (NQF
#0680) would be displayed for patients
in the IRF during the influenza
vaccination season, from October 1,
2015, through March 31, 2016. We are
proposing that the display of these rates
would be updated annually for
subsequent influenza vaccination
seasons.
Calculations for the MRSA and CDI
Healthcare Associated Infection (HAI)
measures adjust for differences in the

PO 00000

Frm 00040

Fmt 4701

Sfmt 4702

characteristics of hospitals and patients
using a SIR. The SIR is a summary
measure that takes into account
differences in the types of patients that
a hospital treats. For a more detailed
discussion of the SIR, please refer to the
FY 2016 IRF PPS final rule (80 FR 47126
through 47127). The MRSA and CDI
SIRs may take into account the
laboratory methods, bed size of the
hospital, and other facility-level factors.
It compares the actual number of HAIs
in a facility or state to a national
benchmark based on previous years of
reported data and adjusts the data based
on several factors. A confidence interval
with a lower and upper limit is
displayed around each SIR to indicate
that there is a high degree of confidence
that the true value of the SIR lies within
that interval. A SIR with a lower limit
that is greater than 1.0 means that there
were more HAIs in a facility or state
than were predicted, and the facility is
classified as ‘‘Worse than the U.S.
National Benchmark.’’ If the SIR has an
upper limit that is less than 1, the
facility had fewer HAIs than were
predicted and is classified as ‘‘Better
than the U.S. National Benchmark.’’ If
the confidence interval includes the
value of 1, there is no statistical
difference between the actual number of
HAIs and the number predicted, and the
facility is classified as ‘‘No Different
than U.S. National Benchmark.’’ If the
number of predicted infections is less
than 1.0, the SIR and confidence
interval are not calculated by CDC.
Calculations for the Influenza
Vaccination Coverage Among
Healthcare Personnel (NQF #0431) are
based on reported numbers of personnel
who received an influenza vaccine at
the reporting facility or who provided
written documentation of influenza
vaccination outside the reporting
facility. The sum of these two numbers
is divided by the total number of
personnel working at the facility for at
least 1 day from October 1 through
March 31 of the following year, and the
result is multiplied by 100 to produce
a compliance percentage (vaccination
coverage). No risk adjustment is
applicable to these calculations. More
information on these calculations and
measure specifications is available at
http://www.cdc.gov/nhsn/pdfs/hpsmanual/vaccination/4-hcp-vaccinationmodule.pdf. We propose that this data
will be displayed on an annual basis
and will include data submitted by IRFs
for a specific, annual influenza
vaccination season. A single compliance
(vaccination coverage) percentage for all
eligible healthcare personnel will be
displayed for each facility.

E:\FR\FM\25APP2.SGM

25APP2

asabaliauskas on DSK3SPTVN1PROD with PROPOSALS

Federal Register / Vol. 81, No. 79 / Monday, April 25, 2016 / Proposed Rules
We are inviting public comment on
our proposal to begin publicly reporting
in CY 2017 pending the availability of
data on Facility-wide Inpatient
Hospital-onset Methicillin-resistant
Staphylococcus aureus (MRSA)
Bacteremia Outcome Measure (NQF
#1716); Facility-wide Inpatient
Hospital-onset Clostridium difficile
Infection (CDI) Outcome Measure (NQF
#1716); and Influenza Vaccination
Coverage Among Healthcare Personnel
(NQF #0431).
For the Percent of Residents or
Patients Who Were Assessed and
Appropriately Given the Seasonal
Influenza Vaccine (Short Stay) (NQF
#0680), we propose to display rates
annually based on the influenza season
to avoid reporting for more than one
influenza vaccination within a CY. For
example, in 2017 we would display
rates for the patient vaccination measure
based on discharges starting on July 1,
2015, to June 30, 2016. This is proposed
because it includes the entire influenza
vaccination season (October 1, 2015, to
March 31, 2016).
Calculations for Percent of Residents
or Patients Who Were Assessed and
Appropriately Given the Seasonal
Influenza Vaccine (Short Stay) (NQF
#0680) will be based on patients
meeting any one of the following
criteria: Patients who received the
influenza vaccine during the influenza
season, patients who were offered and
declined the influenza vaccine, and
patients who were ineligible for the
influenza vaccine due to
contraindication(s). The facility’s
summary observed score will be
calculated by combining the observed
counts of all the criteria. This is
consistent with the publicly reported
patient influenza vaccination measure
for Nursing Home Compare.
Additionally, for the patient influenza
measure, we will exclude IRFs with
fewer than 20 stays in the measure
denominator. For additional
information on the specifications for
this measure, please refer to the IRF
Quality Reporting Measures Information
Web page at https://www.cms.gov/
Medicare/Quality-Initiatives-PatientAssessment-Instruments/IRF-QualityReporting/IRF-Quality-ReportingProgram-Measures-Information-.html.
We invite public comments on our
proposal to begin publicly reporting the
Percent of Residents or Patients Who
Were Assessed and Appropriately Given
the Seasonal Influenza Vaccine (Short
Stay) (NQF #0680) measure on
discharges from July 1st of the previous
calendar year to June 30th of the current
calendar year. We invite comments on
the public display of the measure

VerDate Sep<11>2014

19:36 Apr 22, 2016

Jkt 238001

Percent of Residents or Patients Who
Were Assessed and Appropriately Given
the Seasonal Influenza Vaccine (NQF
#0680) in 2017 pending the availability
of data.
Additionally, we are requesting
public comments on whether to include,
in the future, public display comparison
rates based on CMS regions or US
census regions for Percent of Residents
or Patients with Pressure Ulcers That
Are New or Worsened (Short Stay) (NQF
#0678); All-Cause Unplanned
Readmission Measure for 30 Days PostDischarge from IRFs (NQF #2502); and
Percent of Residents or Patients Who
Were Assessed and Appropriately Given
the Seasonal Influenza Vaccine (Short
Stay) (NQF #0680) for CY 2017 public
display.
2. Procedures for the Opportunity To
Review and Correct Data and
Information
Section 1899B(g) of the Act requires
the Secretary to establish procedures for
public reporting of IRFs’ performance,
including the performance of individual
IRFs, on quality measures specified
under section 1899B(c)(1) of the Act and
resource use and other measures
specified under section 1899B(d)(1) of
the Act (collectively, IMPACT Act
measures) beginning not later than 2
years after the applicable specified
application date under section
1899B(a)(2)(E) of the Act. Under section
1899B(g)(2) of the Act, the procedures
must ensure, including through a
process consistent with the process
applied under section
1886(b)(3)(B)(viii)(VII) of the Act, which
refers to public display and review
requirements in the Hospital IQR
Program, that each IRF has the
opportunity to review and submit
corrections to its data and information
that are to be made public prior to the
information being made public.
In the FY 2016 IRF PPS final rule (80
FR 47126 through 47128), and as
illustrated in Table 9 in section VII.I.a
of this proposed rule, we finalized that
once the provider has an opportunity to
review and correct quarterly data related
to measures submitted via the QIES–
ASAP system or CDC NHSN, we would
consider the provider to have been
given the opportunity to review and
correct this data. We wish to clarify that
although the correction of data
(including claims) can occur after the
submission deadline, if such corrections
are made after a particular quarter’s
submission and correction deadline,
such corrections will not be captured in
the file that contains data for calculation
of measures for public reporting
purposes. To have publicly displayed

PO 00000

Frm 00041

Fmt 4701

Sfmt 4702

24217

performance data that is based on
accurate underlying data, it will be
necessary for IRFs to review and correct
this data before the quarterly
submission and correction deadline.
In this proposed rule, we are restating
and proposing additional details
surrounding procedures that would
allow individual IRFs to review and
correct their data and information on
measures that are to be made public
before those measure data are made
public.
For assessment-based measures, we
propose a process by which we would
provide each IRF with a confidential
feedback report that would allow the
IRF to review its performance on such
measures and, during a review and
correction period, to review and correct
the data the IRF submitted to CMS via
the CMS QIES–ASAP system for each
such measure. In addition, during the
review and correction period, the IRF
would be able to request correction of
any errors in the assessment-based
measure rate calculations.
We propose that these confidential
feedback reports would be available to
each IRF using the CASPER system. We
refer to these reports as the IRF Quality
Measure (QM) Reports. We propose to
provide monthly updates to the data
contained in these reports as data
become available. We propose to
provide the reports so that providers
would be able to view their data and
information at both the facility and
patient level for its quality measures.
The CASPER facility level QM Reports
may contain information such as the
numerator, denominator, facility rate,
and national rate. The CASPER patientlevel QM Reports may contain
individual patient information which
will provide information related to
which patients were included in the
quality measures to identify any
potential errors for those measures in
which we receive patient-level data.
Currently, we do not receive patientlevel data on the CDC measure data
received via the NHSN system. In
addition, we would make other reports
available in the CASPER system, such as
IRF–PAI assessment data submission
reports and provider validation reports,
which would disclose the IRFs data
submission status providing details on
all items submitted for a selected
assessment and the status of records
submitted. We refer providers to the
CDC/NHSN system Web site for
information on obtaining reports
specific to NHSN submitted data at
http://www.cdc.gov/nhsn/inpatientrehab/index.html. Additional
information regarding the content and
availability of these confidential

E:\FR\FM\25APP2.SGM

25APP2

asabaliauskas on DSK3SPTVN1PROD with PROPOSALS

24218

Federal Register / Vol. 81, No. 79 / Monday, April 25, 2016 / Proposed Rules

feedback reports would be provided on
an ongoing basis on our Web site(s) at
https://www.cms.gov/Medicare/QualityInitiatives-Patient-AssessmentInstruments/IRF-Quality-Reporting/
index.html.
As previously finalized in the FY
2016 IRF PPS final rule and illustrated
in Table 10 in section VII.I.c of this
proposed rule, IRFs would have
approximately 4.5 months after the
reporting quarter to correct any errors of
their assessment-based data (that appear
on the CASPER generated QM reports)
and NHSN data used to calculate the
measures. During the time of data
submission for a given quarterly
reporting period and up until the
quarterly submission deadline, IRFs
could review and perform corrections to
errors in the assessment data used to
calculate the measures and could
request correction of measure
calculations. However, as already
established, once the quarterly
submission deadline occurs, the data is
‘‘frozen’’ and calculated for public
reporting and providers can no longer
submit any corrections. We would
encourage IRFs to submit timely
assessment data during a given quarterly
reporting period and review their data
and information early during the review
and correction period so that they can
identify errors and resubmit data before
the data submission deadline.
As noted above, the assessment data
would be populated into the
confidential feedback reports, and we
intend to update the reports monthly
with all data that have been submitted
and are available. We believe that the
data collection/submission quarterly
reporting periods plus 4.5 months to
review correct and review the data is
sufficient time for IRFs to submit,
review and, where necessary, correct
their data and information. These time
frames and deadlines for review and
correction of such measures and data
satisfy the statutory requirement that
IRFs be provided the opportunity to
review and correct their data and
information and are consistent with the
informal process hospitals follow in the
Hospital IQR Program.
In FY 2016 IRF PPS final rule (80 FR
47126 through 47128), we finalized the
data submission/correction and review
period. Also, we afford IRFs a 30-day
preview period prior to public display
during which IRFs may preview the
performance information on their
measures that will be made public. We
would like to clarify that we will
provide the preview report using the
CASPER system, with which IRFs are
familiar. The CASPER preview reports
inform providers of their performance

VerDate Sep<11>2014

19:36 Apr 22, 2016

Jkt 238001

on each measure which will be publicly
reported. Please note that the CASPER
preview reports for the reporting quarter
will be available after the 4.5 month
correction period and the applicable
data submission/correction deadline
have passed and are refreshed on a
quarterly basis for those measures
publicly reported quarterly, and
annually for those measure publicly
reported annually. We propose to give
IRFs 30 days to review the preview
report beginning from the date on which
they can access the report. As already
finalized, corrections to the underlying
data would not be permitted during this
time; however, IRFs may ask for a
correction to their measure calculations
during the 30-day preview period. We
are proposing that if it determines that
the measure, as it is displayed in the
preview report, contains a calculation
error, we could suppress the data on the
public reporting Web site, recalculate
the measure and publish it at the time
of the next scheduled public display
date. This process would be consistent
with informal processes used in the
Hospital IQR Program. If finalized, we
intend to utilize a subregulatory
mechanism, such as our IRF QRP Web
site, to provide more information about
the preview reports, such as when they
will be made available and explain the
process for how and when providers
may ask for a correction to their
measure calculations. We invite public
comment on these proposals to provide
preview reports using the CASPER
system, giving IRFs 30 days review the
preview report and ask for a correction,
and to use a subregulatory mechanism
to explain the process for how and
when providers may ask for a
correction.
In addition to assessment-based
measures and CDC measure data
received via the NHSN system, we have
also proposed claims-based measures
for the IRF QRP. The claims-based
measures include those proposed to
meet the requirements of the IMPACT
Act as well as the All-Cause Unplanned
Readmission Measure for 30 Days PostDischarge from IRFs (NQF #2502) which
was finalized for public display in the
FY 2016 IRF PPS final rule (80 FR 47126
through 47127). As noted in section
VII.N.2., section 1899B(g)(2) of the Act
requires prepublication provider review
and correction procedures that are
consistent with those followed in the
Hospital IQR Program. Under the
Hospital IQR Program’s informal
procedures, for claims-based measures,
we provide hospitals 30 days to preview
their claims-based measures and data in
a preview report containing aggregate

PO 00000

Frm 00042

Fmt 4701

Sfmt 4702

hospital-level data. We propose to adopt
a similar process for the IRF QRP.
Prior to the public display of our
claims-based measures, in alignment
with the Hospital IQR, HAC and
Hospital VBP Programs, we propose to
make available through the CASPER
system, a confidential preview report
that will contain information pertaining
to claims-based measure rate
calculations, for example, facility and
national rates. The data and information
would be for feedback purposes only
and could not be corrected. This
information would be accompanied by
additional confidential information
based on the most recent administrative
data available at the time we extract the
claims data for purposes of calculating
the measures. Because the claims-based
measures are recalculated on an annual
basis, these confidential CASPER QM
reports for claims-based measures will
be refreshed annually. As previously
finalized in the FY 2016 IRF PPS final
rule (80 FR 47126 through 47128), IRFs
would have 30 days from the date the
preview report is made available in
which to review this information. The
30-day preview period is the only time
when IRFs would be able to see claimsbased measures before they are publicly
displayed. IRFs would not be able to
make corrections to underlying claims
data during this preview period, nor
would they be able to add new claims
to the data extract. However, IRFs may
request that we correct our measure
calculation if the IRF believes it is
incorrect during the 30 day preview
period. We propose that if we agree that
the measure, as it is displayed in the
preview report, contains a calculation
error, we could suppress the data on the
public reporting Web site, recalculate
the measure, and publish it at the time
of the next scheduled public display
date. This process would be consistent
with informal policies followed in the
Hospital IQR Program. If finalized, we
intend to utilize a subregulatory
mechanism, such as our IRF QRP Web
site, to explain the process for how and
when providers may contest their
measure calculations.
The proposed claims-based
measures—The MSPB–PAC IRF QRP
measure; Discharge to Community—
PAC, Potentially Preventable 30-Day
Post-Discharge Readmission Measure for
IRF QRP, and Potentially Preventable
Within Stay Readmission Measure for
IRFs—use Medicare administrative data
from hospitalizations for Medicare FFS
beneficiaries. Public reporting of data
will be based on 2 consecutive calendar
years of data, which is consistent with
the specifications of the proposed
measures. We propose to create data

E:\FR\FM\25APP2.SGM

25APP2

asabaliauskas on DSK3SPTVN1PROD with PROPOSALS

Federal Register / Vol. 81, No. 79 / Monday, April 25, 2016 / Proposed Rules
extracts using claims data for the
proposed claims-based measures—The
MSPB–PAC IRF QRP measure;
Discharge to Community—PAC,
Potentially Preventable 30-Day PostDischarge Readmission Measure for IRF
QRP, and Potentially Preventable
Within Stay Readmission Measure for
IRFs—at least 90 days after the last
discharge date in the applicable period,
which we will use for the calculations.
For example, if the last discharge date
in the applicable period for a measure
is December 31, 2017, for data collection
January 1, 2016, through December 31,
2017, we would create the data extract
on approximately March 31, 2018, at the
earliest, and use that data to calculate
the claims-based measures for that
applicable period. Since IRFs would not
be able to submit corrections to the
underlying claims snapshot nor add
claims (for measures that use IRF
claims) to this data set at the conclusion
of the at least the 90-day period
following the last date of discharge used
in the applicable period, at that time we
would consider IRF claims data to be
complete for purposes of calculating the
claims-based measures.
We propose that beginning with data
that will be publicly displayed in 2018,
claims-based measures will be
calculated using claims data at least 90
days after the last discharge date in the
applicable period, at which time we
would create a data extract or snapshot
of the available claims data to use for
the measures calculation. This
timeframe allows us to balance the need
to provide timely program information
to IRFs with the need to calculate the
claims-based measures using as
complete a data set as possible. As
noted, under this proposed procedure,
during the 30-day preview period, IRFs
would not be able to submit corrections
to the underlying claims data or to add
new claims to the data extract. This is
for two reasons: First, for certain
measures, the claims data used to
calculate the measure is derived not
from the IRF’s claims, but from the
claims of another provider. For
example, the proposed measure
Potentially Preventable 30-Day PostDischarge Readmission Measure for IRF
QRP uses claims data submitted by the
hospital to which the patient was
readmitted. The claims are not those of
the IRF and, therefore, the IRF could not
make corrections to them. Second, even
where the claims used to calculate the
measures are those of the IRF, it would

VerDate Sep<11>2014

19:36 Apr 22, 2016

Jkt 238001

not be not possible to correct the data
after it is extracted for the measures
calculation. This is because it is
necessary to take a static ‘‘snapshot’’ of
the claims in order to perform the
necessary measure calculations.
We seek to have as complete a data set
as possible. We recognize that the
proposed at least 90-day ‘‘run-out’’
period when we would take the data
extract to calculate the claims-based
measures is less than the Medicare
program’s current timely claims filing
policy under which providers have up
to 1 year from the date of discharge to
submit claims. We considered a number
of factors in determining that the
proposed at least 90-day run-out period
is appropriate to calculate the claimsbased measures. After the data extract is
created, it takes several months to
incorporate other data needed for the
calculations (particularly in the case of
risk-adjusted or episode-based
measures). We then need to generate
and check the calculations. Because
several months lead time is necessary
after acquiring the data to generate the
claims-based calculations, if we were to
delay our data extraction point to 12
months after the last date of the last
discharge in the applicable period, we
would not be able to deliver the
calculations to IRFs sooner than 18 to 24
months after the last discharge. We
believe this would create an
unacceptably long delay both for IRFs
and for us to deliver timely calculations
to IRFs for quality improvement.
We invite public comment on these
proposals.
O. Mechanism for Providing Feedback
Reports to IRFs
Section 1899B(f) of the Act requires
the Secretary to provide confidential
feedback reports to post-acute care
providers on their performance to the
measures specified under section
1899B(c)(1) and (d)(1) of the Act,
beginning 1 year after the specified
application date that applies to such
measures and PAC providers. As
discussed earlier, the reports we
proposed to provide for use by IRFs to
review their data and information
would be confidential feedback reports
that would enable IRFs to review their
performance on the measures required
under the IRF QRP. We propose that
these confidential feedback reports
would be available to each IRF using the
CASPER system. Data contained within
these CASPER reports would be

PO 00000

Frm 00043

Fmt 4701

Sfmt 4702

24219

updated as previously described, on a
monthly basis as the data become
available except for our claims-based
measures, which are only updated on an
annual basis.
We intend to provide detailed
procedures to IRFs on how to obtain
their confidential feedback CASPER
reports on the IRF QRP Web site at
https://www.cms.gov/Medicare/QualityInitiatives-Patient-AssessmentInstruments/IRF-Quality-Reporting/
index.html. We propose to use the CMS
QIES–ASAP system to provide quality
measure reports in a manner consistent
with how providers obtain various
reports to date. The QIES–ASAP system
is a confidential and secure system with
access granted to providers, or their
designees.
We seek public comment on this
proposal to satisfy the requirement to
provide confidential feedback reports to
IRFs.
P. Proposed Method for Applying the
Reduction to the FY 2017 IRF Increase
Factor for IRFs That Fail To Meet the
Quality Reporting Requirements
As previously noted, section
1886(j)(7)(A)(i) of the Act requires the
application of a 2-percentage point
reduction of the applicable market
basket increase factor for IRFs that fail
to comply with the quality data
submission requirements. In compliance
with section 1886(j)(7)(A)(i) of the Act,
we will apply a 2-percentage point
reduction to the applicable FY 2017
market basket increase factor (1.45
percent) in calculating a proposed
adjusted FY 2017 standard payment
conversion factor to apply to payments
for only those IRFs that failed to comply
with the data submission requirements.
As previously noted, application of the
2-percentage point reduction may result
in an update that is less than 0.0 for a
fiscal year and in payment rates for a
fiscal year being less than such payment
rates for the preceding fiscal year. Also,
reporting-based reductions to the market
basket increase factor will not be
cumulative; they will only apply for the
FY involved. Table 13 shows the
calculation of the proposed adjusted FY
2017 standard payment conversion
factor that will be used to compute IRF
PPS payment rates for any IRF that
failed to meet the quality reporting
requirements for the applicable
reporting period(s).

E:\FR\FM\25APP2.SGM

25APP2

24220

Federal Register / Vol. 81, No. 79 / Monday, April 25, 2016 / Proposed Rules

TABLE 20—CALCULATIONS TO DETERMINE THE PROPOSED ADJUSTED FY 2017 STANDARD PAYMENT CONVERSION
FACTOR FOR IRFS THAT FAILED TO MEET THE QUALITY REPORTING REQUIREMENT
Explanation for adjustment

Calculations

Standard Payment Conversion Factor for FY 2016 ..........................................................................................
Market Basket Increase Factor for FY 2017 (2.7 percent), reduced by 0.5 percentage point for the productivity adjustment as required by section 1886(j)(3)(C)(ii)(I) of the Act, reduced by 0.75 percentage point in
accordance with sections 1886(j)(3)(C) and (D) of the Act and further reduced by 2 percentage points for
IRFs that failed to meet the quality reporting requirement.
Budget Neutrality Factor for the Wage Index and Labor-Related Share ..........................................................
Budget Neutrality Factor for the Revisions to the CMG Relative Weights .......................................................
Proposed Adjusted FY 2017 Standard Payment Conversion Factor ................................................................

We invite public comment on the
proposed method for applying the
reduction to the FY 2017 IRF increase
factor for IRFs that fail to meet the
quality reporting requirements.
VIII. Collection of Information
Requirements

asabaliauskas on DSK3SPTVN1PROD with PROPOSALS

A. Statutory Requirement for
Solicitation of Comments
Under the Paperwork Reduction Act
of 1995 (PRA), we are required to
provide 60-day notice in the Federal
Register and solicit public comment
before a collection of information
requirement is submitted to the OMB for
review and approval. To fairly evaluate
whether an information collection
should be approved by OMB, section
3506(c)(2)(A) of the PRA requires that
we solicit comment on the following
issues:
• The need for the information
collection and its usefulness in carrying
out the proper functions of our agency.
• The accuracy of our estimate of the
information collection burden.
• The quality, utility, and clarity of
the information to be collected.
• Recommendations to minimize the
information collection burden on the
affected public, including automated
collection techniques.
This proposed rule makes reference to
associated information collections that
are not discussed in the regulation text
contained in this document.
B. Collection of Information
Requirements for Updates Related to the
IRF QRP
Failure to submit data required under
section 1886(j)(7)(C) and (F) of the Act
will result in the reduction of the
annual update to the standard federal
rate for discharges occurring during
such fiscal year by 2 percentage points
for any IRF that does not comply with
the requirements established by the
Secretary. At the time that this analysis
was prepared, 91, or approximately 8
percent, of the 1166 active Medicarecertified IRFs did not receive the full
annual percentage increase for the FY

VerDate Sep<11>2014

19:36 Apr 22, 2016

Jkt 238001

2015 annual payment update
determination. Information is not
available to determine the precise
number of IRFs that will not meet the
requirements to receive the full annual
percentage increase for the FY 2017
payment determination.
We believe that the burden associated
with the IRF QRP is the time and effort
associated with data collection and
reporting. As of February 1, 2016 there
are approximately 1131 IRFs currently
reporting quality data to CMS. In this
proposed rule, we are proposing 5
measures. For the FY 2018 payment
determinations and subsequent years,
we are proposing four new measures: (1)
MSPB–PAC IRF QRP; (2) Discharge to
Community–PAC IRF QRP, and (3)
Potentially Preventable 30-Day PostDischarge Readmission Measure for IRF
QRP; (4) Potentially Preventable 30-Day
Within Stay Readmission Measure for
IRF QRP. These four measures are
Medicare claims-based measures;
because claims-based measures can be
calculated based on data that are already
reported to the Medicare program for
payment purposes, we believe there will
be no additional impact.
For the FY 2020 payment
determination and subsequent years, we
are proposing one measure: Drug
Regimen Review Conducted with
Follow-Up for Identified Issues—PAC
IRF QRP. Additionally we propose that
data for this new measure will be
collected and reported using the IRF–
PAI (version effective October 1, 2018).
Our burden calculations take into
account all ‘‘new’’ items required on the
IRF–PAI (version effective October 1,
2018) to support data collection and
reporting for this proposed measure.
The addition of the new items required
to collect the newly proposed measure
is for the purpose of achieving
standardization of data elements.
We estimate the additional elements
for the newly proposed Drug Regimen
Review Conducted with Follow-Up for
Identified Issues—PAC IRF QRP
measure will take 6 minutes of nursing/
clinical staff time to report data on

PO 00000

Frm 00044

Fmt 4701

Sfmt 4702

$15,478
× 0.9945

× 0.9992
× 0.9990
= $15,365

admission and 4 minutes of nursing/
clinical staff time to report data on
discharge, for a total of 10 minutes. We
estimate that the additional IRF–PAI
items we are proposing will be
completed by Registered Nurses (RN) for
approximately 75 percent of the time
required, and Pharmacists for
approximately 25 percent of the time
required. Individual providers
determine the staffing resources
necessary. In accordance with OMB
control number 0938–0842, we estimate
398,254 discharges from all IRFs
annually, with an additional burden of
10 minutes. This would equate to
66,375.67 total hours or 58.69 hours per
IRF. We believe this work will be
completed by RNs (75 percent) and
Pharmacists (25 percent). We obtained
mean hourly wages for these staff from
the U.S. Bureau of Labor Statistics’ May
2014 National Occupational
Employment and Wage Estimates
(http://www.bls.gov/oes/current/oes_
nat.htm), and to account for overhead
and fringe benefits, we have doubled the
mean hourly wage. Per the U.S. Bureau
of Labor and Statistics, the mean hourly
wage for a RN is $33.55. However, to
account for overhead and fringe
benefits, we have doubled the mean
hourly wage, making it $67.10 for an
RN. Per the U.S. Bureau of Labor and
Statistics, the mean hourly wage for a
pharmacist is $56.98. However, to
account for overhead and fringe
benefits, we have doubled the mean
hourly wage, making it $113.96 for a
pharmacist. Given these wages and time
estimates, the total cost related to the
newly proposed measures is estimated
at $4,625.46 per IRF annually, or
$5,231,398.17 for all IRFs annually.
For the quality reporting during
extraordinary circumstances, section
VII.M of this proposed rule proposes to
add a previously finalized process that
IRFs may request an exception or
extension from the FY 2019 payment
determination and that of subsequent
payment determinations. The request
must be submitted by email within 90

E:\FR\FM\25APP2.SGM

25APP2

Federal Register / Vol. 81, No. 79 / Monday, April 25, 2016 / Proposed Rules
days from the date that the
extraordinary circumstances occurred.
While the preparation and submission
of the request is an information
collection, unlike the aforementioned
temporary exemption of the data
collection requirements for the new
drug regimen review measure, the
request is not expected to be submitted
to OMB for formal review and approval
since we estimate less than two requests
(total) per year. Since we estimate fewer
than 10 respondents annually, the
information collection requirement and
associated burden is not subject as
stated in 5 CFR 1320.3(c) of the
implementing regulations of the
Paperwork Reduction Act of 1995.
As discussed in section VII.N of this
proposed rule, this rule proposes to add
a previously finalized process that will
enable IRFs to request reconsiderations
of our initial non-compliance decision
in the event that it believes that it was
incorrectly identified as being subject to
the 2-percentage point reduction to its
annual increase factor due to noncompliance with the IRF QRP reporting
requirements. While there is burden
associated with filing a reconsideration
request, 5 CFR 1320.4 of OMB’s
implementing regulations for PRA
excludes activities during the conduct
of administrative actions such as
reconsiderations.
If you comment on these information
collection and recordkeeping
requirements, please submit your
comments electronically as specified in
the ADDRESSES section of this proposed
rule.
IX. Response to Public Comments
Because of the large number of public
comments we normally receive on
Federal Register documents, we are not
able to acknowledge or respond to them
individually. We will consider all
comments we receive by the date and
time specified in the DATES section of
this preamble, and, when we proceed
with a subsequent document, we will
respond to the comments in the
preamble to that document.

asabaliauskas on DSK3SPTVN1PROD with PROPOSALS

X. Regulatory Impact Analysis
A. Statement of Need
This proposed rule updates the IRF
prospective payment rates for FY 2017
as required under section 1886(j)(3)(C)
of the Act. It responds to section
1886(j)(5) of the Act, which requires the
Secretary to publish in the Federal
Register on or before the August 1 that
precedes the start of each fiscal year, the
classification and weighting factors for
the IRF PPS’s case-mix groups and a
description of the methodology and data
used in computing the prospective
payment rates for that fiscal year.

VerDate Sep<11>2014

19:36 Apr 22, 2016

Jkt 238001

This proposed rule also implements
sections 1886(j)(3)(C) and (D) of the Act.
Section 1886(j)(3)(C)(ii)(I) of the Act
requires the Secretary to apply a multifactor productivity adjustment to the
market basket increase factor, and to
apply other adjustments as defined by
the Act. The productivity adjustment
applies to FYs from 2012 forward. The
other adjustments apply to FYs 2010
through 2019.
Furthermore, this proposed rule also
adopts policy changes under the
statutory discretion afforded to the
Secretary under section 1886(j)(7) of the
Act. Specifically, we propose to revise
and update the quality measures and
reporting requirements under the IRF
quality reporting program.
B. Overall Impacts
We have examined the impacts of this
proposed rule as required by Executive
Order 12866 (September 30, 1993,
Regulatory Planning and Review),
Executive Order 13563 on Improving
Regulation and Regulatory Review
(January 18, 2011), the Regulatory
Flexibility Act (September 19, 1980,
Pub. L. 96–354) (RFA), section 1102(b)
of the Act, section 202 of the Unfunded
Mandates Reform Act of 1995 (Pub. L.
104–4), Executive Order 13132 on
Federalism (August 4, 1999), and the
Congressional Review Act (5 U.S.C.
804(2)).
Executive Orders 12866 and 13563
direct agencies to assess all costs and
benefits of available regulatory
alternatives and, if regulation is
necessary, to select regulatory
approaches that maximize net benefits
(including potential economic,
environmental, public health and safety
effects, distributive impacts, and
equity). Executive Order 13563
emphasizes the importance of
quantifying both costs and benefits, of
reducing costs, of harmonizing rules,
and of promoting flexibility. A
regulatory impact analysis (RIA) must
be prepared for a major final rule with
economically significant effects ($100
million or more in any 1 year). We
estimate the total impact of the policy
updates described in this proposed rule
by comparing the estimated payments in
FY 2017 with those in FY 2016. This
analysis results in an estimated $125
million increase for FY 2017 IRF PPS
payments. As a result, this proposed
rule is designated as economically
‘‘significant’’ under section 3(f)(1) of
Executive Order 12866, and hence a
major rule under the Congressional
Review Act. Also, the rule has been
reviewed by OMB.
The Regulatory Flexibility Act (RFA)
requires agencies to analyze options for
regulatory relief of small entities, if a

PO 00000

Frm 00045

Fmt 4701

Sfmt 4702

24221

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 IRFs and most other
providers and suppliers are small
entities, either by having revenues of
$7.5 million to $38.5 million or less in
any 1 year depending on industry
classification, or by being nonprofit
organizations that are not dominant in
their markets. (For details, see the Small
Business Administration’s final rule that
set forth size standards for health care
industries, at 65 FR 69432 at http://
www.sba.gov/sites/default/files/files/
Size_Standards_Table.pdf, effective
March 26, 2012 and updated on
February 26, 2016.) Because we lack
data on individual hospital receipts, we
cannot determine the number of small
proprietary IRFs or the proportion of
IRFs’ revenue that is derived from
Medicare payments. Therefore, we
assume that all IRFs (an approximate
total of 1,100 IRFs, of which
approximately 60 percent are nonprofit
facilities) are considered small entities
and that Medicare payment constitutes
the majority of their revenues. The HHS
generally uses a revenue impact of 3 to
5 percent as a significance threshold
under the RFA. As shown in Table 21,
we estimate that the net revenue impact
of this proposed rule on all IRFs is to
increase estimated payments by
approximately 1.6 percent. The rates
and policies set forth in this proposed
rule will not have a significant impact
(not greater than 3 percent) on a
substantial number of small entities.
Medicare Administrative Contractors
are not considered to be small entities.
Individuals and states are not included
in the definition of a small entity.
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
detail below in this section, the rates
and policies set forth in this proposed
rule will not have a significant impact
(not greater than 3 percent) on a
substantial number of rural hospitals
based on the data of the 140 rural units
and 11 rural hospitals in our database of
1,131 IRFs for which data were
available.

E:\FR\FM\25APP2.SGM

25APP2

24222

Federal Register / Vol. 81, No. 79 / Monday, April 25, 2016 / Proposed Rules

Section 202 of the Unfunded
Mandates Reform Act of 1995 (Pub. L.
104–04, enacted on March 22, 1995)
also requires that agencies assess
anticipated costs and benefits before
issuing any rule whose mandates
require spending in any 1 year of $100
million in 1995 dollars, updated
annually for inflation. In 2016, that
threshold level is approximately $146
million. This proposed rule will not
mandate spending costs on state, local,
or tribal governments, in the aggregate,
or by the private sector, of greater than
$146 million.
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.
As stated, this proposed rule will not
have a substantial effect on state and
local governments, preempt state law, or
otherwise have a federalism
implication.

asabaliauskas on DSK3SPTVN1PROD with PROPOSALS

C. Detailed Economic Analysis
1. Basis and Methodology of Estimates
This proposed rule proposes updates
to the IRF PPS rates contained in the FY
2016 IRF PPS final rule (80 FR 47036).
Specifically, this proposed rule would
update the CMG relative weights and
average length of stay values, the wage
index, and the outlier threshold for
high-cost cases. This proposed rule
would apply a MFP adjustment to the
FY 2017 IRF market basket increase
factor in accordance with section
1886(j)(3)(C)(ii)(I) of the Act, and a 0.75
percentage point reduction to the FY
2017 IRF market basket increase factor
in accordance with sections
1886(j)(3)(C)(ii)(II) and (D)(v) of the Act.
Further, this proposed rule contains
proposed revisions to the IRF quality
reporting requirements that are expected
to result in some additional financial
effects on IRFs. In addition, section VII
of this proposed rule discusses the
implementation of the required 2
percentage point reduction of the
market basket increase factor for any IRF
that fails to meet the IRF quality
reporting requirements, in accordance
with section 1886(j)(7) of the Act.
We estimate that the impact of the
changes and updates described in this
proposed rule will be a net estimated
increase of $125 million in payments to
IRF providers. This estimate does not
include the implementation of the
required 2 percentage point reduction of
the market basket increase factor for any
IRF that fails to meet the IRF quality
reporting requirements (as discussed in

VerDate Sep<11>2014

19:36 Apr 22, 2016

Jkt 238001

section X.C.7. of this proposed rule).
The impact analysis in Table 21 of this
proposed rule represents the projected
effects of the updates to IRF PPS
payments for FY 2017 compared with
the estimated IRF PPS payments in FY
2016. We determine the effects by
estimating payments while holding all
other payment variables constant. We
use the best data available, but we do
not attempt to predict behavioral
responses to these changes, and we do
not make adjustments for future changes
in such variables as number of
discharges or case-mix.
We note that certain events may
combine to limit the scope or accuracy
of our impact analysis, because such an
analysis is future-oriented and, thus,
susceptible to forecasting errors because
of other changes in the forecasted
impact time period. Some examples
could be legislative changes made by
the Congress to the Medicare program
that would impact program funding, or
changes specifically related to IRFs.
Although some of these changes may
not necessarily be specific to the IRF
PPS, the nature of the Medicare program
is such that the changes may interact,
and the complexity of the interaction of
these changes could make it difficult to
predict accurately the full scope of the
impact upon IRFs.
In updating the rates for FY 2017, we
are proposing standard annual revisions
described in this proposed rule (for
example, the update to the wage and
market basket indexes used to adjust the
federal rates). We are also implementing
a productivity adjustment to the FY
2017 IRF market basket increase factor
in accordance with section
1886(j)(3)(C)(ii)(I) of the Act, and a 0.75
percentage point reduction to the FY
2017 IRF market basket increase factor
in accordance with sections
1886(j)(3)(C)(ii)(II) and –(D)(v) of the
Act. We estimate the total increase in
payments to IRFs in FY 2017, relative to
FY 2016, will be approximately $125
million.
This estimate is derived from the
application of the FY 2017 IRF market
basket increase factor, as reduced by a
productivity adjustment in accordance
with section 1886(j)(3)(C)(ii)(I) of the
Act, and a 0.75 percentage point
reduction in accordance with sections
1886(j)(3)(C)(ii)(II) and (D)(v) of the Act,
which yields an estimated increase in
aggregate payments to IRFs of $110
million. Furthermore, there is an
additional estimated $15 million
increase in aggregate payments to IRFs
due to the proposed update to the
outlier threshold amount. Outlier
payments are estimated to increase from
approximately 2.8 percent in FY 2016 to

PO 00000

Frm 00046

Fmt 4701

Sfmt 4702

3.0 percent in FY 2017. Therefore,
summed together, we estimate that these
updates will result in a net increase in
estimated payments of $125 million
from FY 2016 to FY 2017.
The effects of the proposed updates
that impact IRF PPS payment rates are
shown in Table 21. The following
proposed updates that affect the IRF
PPS payment rates are discussed
separately below:
• The effects of the proposed update
to the outlier threshold amount, from
approximately 2.8 percent to 3.0 percent
of total estimated payments for FY 2017,
consistent with section 1886(j)(4) of the
Act.
• The effects of the proposed annual
market basket update (using the IRF
market basket) to IRF PPS payment
rates, as required by section
1886(j)(3)(A)(i) and sections
1886(j)(3)(C) and (D) of the Act,
including a productivity adjustment in
accordance with section
1886(j)(3)(C)(i)(I) of the Act, and a 0.75
percentage point reduction in
accordance with sections
1886(j)(3)(C)(ii)(II) and (D)(v) of the Act.
• The effects of applying the
proposed budget-neutral labor-related
share and wage index adjustment, as
required under section 1886(j)(6) of the
Act.
• The effects of the proposed budgetneutral changes to the CMG relative
weights and average length of stay
values, under the authority of section
1886(j)(2)(C)(i) of the Act.
• The total change in estimated
payments based on the proposed FY
2017 payment changes relative to the
estimated FY 2016 payments.
2. Description of Table 21
Table 21 categorizes IRFs by
geographic location, including urban or
rural location, and location for CMS’s 9
Census divisions (as defined on the cost
report) of the country. In addition, the
table divides IRFs into those that are
separate rehabilitation hospitals
(otherwise called freestanding hospitals
in this section), those that are
rehabilitation units of a hospital
(otherwise called hospital units in this
section), rural or urban facilities,
ownership (otherwise called for-profit,
non-profit, and government), by
teaching status, and by disproportionate
share patient percentage (DSH PP). The
top row of Table 21 shows the overall
impact on the 1,131 IRFs included in
the analysis.
The next 12 rows of Table 21 contain
IRFs categorized according to their
geographic location, designation as

E:\FR\FM\25APP2.SGM

25APP2

Federal Register / Vol. 81, No. 79 / Monday, April 25, 2016 / Proposed Rules

asabaliauskas on DSK3SPTVN1PROD with PROPOSALS

either a freestanding hospital or a unit
of a hospital, and by type of ownership;
all urban, which is further divided into
urban units of a hospital, urban
freestanding hospitals, and by type of
ownership; and all rural, which is
further divided into rural units of a
hospital, rural freestanding hospitals,
and by type of ownership. There are 980
IRFs located in urban areas included in
our analysis. Among these, there are 729
IRF units of hospitals located in urban
areas and 251 freestanding IRF hospitals
located in urban areas. There are 151
IRFs located in rural areas included in
our analysis. Among these, there are 140
IRF units of hospitals located in rural
areas and 11 freestanding IRF hospitals
located in rural areas. There are 408 forprofit IRFs. Among these, there are 355
IRFs in urban areas and 53 IRFs in rural
areas. There are 652 non-profit IRFs.
Among these, there are 562 urban IRFs
and 90 rural IRFs. There are 71
government-owned IRFs. Among these,
there are 63 urban IRFs and 8 rural IRFs.
The remaining four parts of Table 21
show IRFs grouped by their geographic
location within a region, by teaching
status, and by DSH PP. First, IRFs
located in urban areas are categorized
for their location within a particular one
of the nine Census geographic regions.
Second, IRFs located in rural areas are
categorized for their location within a
particular one of the nine Census
geographic regions. In some cases,
especially for rural IRFs located in the
New England, Mountain, and Pacific

VerDate Sep<11>2014

19:36 Apr 22, 2016

Jkt 238001

regions, the number of IRFs represented
is small. IRFs are then grouped by
teaching status, including non-teaching
IRFs, IRFs with an intern and resident
to average daily census (ADC) ratio less
than 10 percent, IRFs with an intern and
resident to ADC ratio greater than or
equal to 10 percent and less than or
equal to 19 percent, and IRFs with an
intern and resident to ADC ratio greater
than 19 percent. Finally, IRFs are
grouped by DSH PP, including IRFs
with zero DSH PP, IRFs with a DSH PP
less than 5 percent, IRFs with a DSH PP
between 5 and less than 10 percent,
IRFs with a DSH PP between 10 and 20
percent, and IRFs with a DSH PP greater
than 20 percent.
The estimated impacts of each policy
described in this proposed rule to the
facility categories listed are shown in
the columns of Table 21. The
description of each column is as
follows:
• Column (1) shows the facility
classification categories.
• Column (2) shows the number of
IRFs in each category in our FY 2016
analysis file.
• Column (3) shows the number of
cases in each category in our FY 2016
analysis file.
• Column (4) shows the estimated
effect of the proposed adjustment to the
outlier threshold amount.
• Column (5) shows the estimated
effect of the proposed update to the IRF
labor-related share and wage index, in a
budget-neutral manner.

PO 00000

Frm 00047

Fmt 4701

Sfmt 4702

24223

• Column (6) shows the estimated
effect of the proposed update to the
CMG relative weights and average
length of stay values, in a budget-neutral
manner.
• Column (7) compares our estimates
of the payments per discharge,
incorporating all of the proposed
policies reflected in this proposed rule
for FY 2017 to our estimates of
payments per discharge in FY 2016.
The average estimated increase for all
IRFs is approximately 1.6 percent. This
estimated net increase includes the
effects of the proposed IRF market
basket increase factor for FY 2017 of 2.7
percent, reduced by a productivity
adjustment of 0.5 percentage point in
accordance with section
1886(j)(3)(C)(ii)(I) of the Act, and further
reduced by 0.75 percentage point in
accordance with sections
1886(j)(3)(C)(ii)(II) and (D)(v) of the Act.
It also includes the approximate 0.2
percent overall increase in estimated
IRF outlier payments from the proposed
update to the outlier threshold amount.
Since we are making the proposed
updates to the IRF wage index and the
CMG relative weights in a budgetneutral manner, they will not be
expected to affect total estimated IRF
payments in the aggregate. However, as
described in more detail in each section,
they will be expected to affect the
estimated distribution of payments
among providers.

E:\FR\FM\25APP2.SGM

25APP2

24224

Federal Register / Vol. 81, No. 79 / Monday, April 25, 2016 / Proposed Rules

TABLE 21: IRF Impact Table for FY 2017 (Columns 4 through 7 in percentage)

Facility Classification
(1)
Total
Urban unit
Rural unit
Urban hospital
Rural hospital
Urban For-Profit
Rural For-Profit
Urban Non-Profit
Rural Non-Profit
Urban Govemment
Rural Govemment
Urban
Rural
Urban by region
Urban New England
Urban Middle Atlantic
Urban South Atlantic
Urban East North Central
Urban East South Central
Urban West North Central
Urban West South Central
Urban Mountain
Urban Pacific
Rural by region
Rural New England
Rural Middle Atlantic
Rural South Atlantic
Rural East North Central
Rural East South Central
Rural West North Central
Rural West South Central
Rural Mountain
Rural Pacific
Teaching status
Non-teaching
Resident to Ar::x::: less than 10"/o
Resident to Ar::x::: 10%-19%
Resident to Ar::x::: greater than 1

Number of Number of
IRFs
Cases
(2)
(3)
1,131
398,075
729
178,205
140
23,046
251
192,374
11
4,450
355
180,930
53
10,205
562
170,450
90
15,809
63
19,199
8
1,482
980
370,579
151
27,496

Outlier
(4)
0.2
0.3
0.3
0.1
0.0
0.1
0.2
0.2
0.3
0.3
0.2
0.2
0.2

FY2017
CBSA
wage index
and laborshare
(5)
0.0
0.0
-0.6
0.1
-1.6
-0.1
-0.9
0.3
-0.7
-0.4
-1.0
0.1
-0.8

CMG
Weights
(6)
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.0

Change
(7)
1.6
1.8
1.1
1.5
-0.1
1.4
0.8
2.0
1.0
1.4
0.8
1.7
0.9

Total
Percent
1

31
144
145
170
57
74
182
77
100

16,679
57,389
72,613
50,122
26,048
19,952
77,509
26,254
24,013

0.1
0.1
0.1
0.2
0.1
0.2
0.1
0.2
0.3

0.2
0.8
-0.1
-0.1
-0.5
-0.7
-0.1
0.0
0.4

0.0
0.0
0.0
0.1
-0.1
0.0
0.0
0.0
0.0

1.8
2.4
1.4
1.6
1.1
1.0
1.5
1.6
2.2

5
12
17
28
18
21
40
7
3

1,311
1,700
4,519
4,878
3,485
3,084
7,711
600
208

0.3
0.2
0.1
0.2
0.2
0.3
0.2
0.7
0.8

-1.5
-2.0
-0.5
0.1
-0.6
-0.5
-1.4
-0.4
0.2

0.0
0.2
0.0
0.0
0.0
0.0
0.1
0.0
-0.2

0.2
-0.2
1.1
1.7
1.1
1.3
0.3
1.7
2.3

1,024
62
36
9

355,155
28,619
12,780
1,521

0.2
0.2
0.3
0.1

0.0
-0.2
0.6
-0.4

0.0
0.0
0.0
-0.1

1.6
1.4
2.4
1.1

35
169
316
368
243

7,396
64,316
127,745
135,677
62,941

0.3
0.1
0.2
0.2
0.2

0.0
0.4
0.0
-0.2
0.0

0.0
0.0
0.0
0.0
0.0

1.7
2.0
1.6
1.4
1.7

Dis proportionate share patient
(DSHPP)

I percentage

DSHPP~O%

DSHPP<5%
DSH PP 5%-10%
DSH PP 10%-20"/o
DSH PP greater than 20"/o

This column includes the impact of the updates in columns (4), (5), and (6) above, and of the IRF market basket
increase factor for FY 2017 (2.7 percent), reduced by 0.5 percentage point for the productivity adjustment as
required by section 1886(j)(3)(C)(ii)(I) of the Act, and reduced by 0.75 percentage point in accordance with sections
1886(j)(3)(C)(ii)(II) and -(D)(v) of the Act.

VerDate Sep<11>2014

19:36 Apr 22, 2016

Jkt 238001

PO 00000

Frm 00048

Fmt 4701

Sfmt 4725

E:\FR\FM\25APP2.SGM

25APP2

EP25AP16.013

asabaliauskas on DSK3SPTVN1PROD with PROPOSALS

Federal Register / Vol. 81, No. 79 / Monday, April 25, 2016 / Proposed Rules
3. Impact of the Proposed Update to the
Outlier Threshold Amount
The estimated effects of the proposed
update to the outlier threshold
adjustment are presented in column 4 of
Table 21. In the FY 2016 IRF PPS final
rule (80 FR 47036), we used FY 2014
IRF claims data (the best, most complete
data available at that time) to set the
outlier threshold amount for FY 2016 so
that estimated outlier payments would
equal 3 percent of total estimated
payments for FY 2016.
For this proposed rule, we are using
preliminary FY 2015 IRF claims data,
and, based on that preliminary analysis,
we estimate that IRF outlier payments as
a percentage of total estimated IRF
payments would be 2.8 percent in FY
2016. Thus, we propose to adjust the
outlier threshold amount in this final
rule to set total estimated outlier
payments equal to 3 percent of total
estimated payments in FY 2017. The
estimated change in total IRF payments
for FY 2017, therefore, includes an
approximate 0.2 percent increase in
payments because the estimated outlier
portion of total payments is estimated to
increase from approximately 2.8 percent
to 3 percent.
The impact of this proposed outlier
adjustment update (as shown in column
4 of Table 21) is to increase estimated
overall payments to IRFs by about 0.2
percent. We estimate the largest increase
in payments from the update to the
outlier threshold amount to be 0.8
percent for rural IRFs in the Pacific
region.
4. Impact of the Proposed CBSA Wage
Index and Labor-Related Share

asabaliauskas on DSK3SPTVN1PROD with PROPOSALS

In column 5 of Table 21, we present
the effects of the proposed budgetneutral update of the wage index and
labor-related share. The proposed
changes to the wage index and the
labor-related share are discussed
together because the wage index is
applied to the labor-related share
portion of payments, so the proposed
changes in the two have a combined
effect on payments to providers. As
discussed in section V.C. of this
proposed rule, we are proposing to keep
the labor-related share unchanged from
FY 2016 to FY 2017 at 71.0 percent.
5. Impact of the Proposed Update to the
CMG Relative Weights and Average
Length of Stay Values.
In column 6 of Table 21, we present
the effects of the proposed budgetneutral update of the CMG relative
weights and average length of stay
values. In the aggregate, we do not
estimate that these proposed updates

VerDate Sep<11>2014

19:36 Apr 22, 2016

Jkt 238001

will affect overall estimated payments of
IRFs. However, we do expect these
updates to have small distributional
effects.
6. Effects of Proposed Requirements for
the IRF QRP for FY 2018
In accordance with section 1886(j)(7)
of the Act, we will implement a 2
percentage point reduction in the FY
2018 increase factor for IRFs that have
failed to report the required quality
reporting data to us during the most
recent IRF quality reporting period. In
section VII.P of this proposed rule, we
discuss the proposed method for
applying the 2 percentage point
reduction to IRFs that fail to meet the
IRF QRP requirements. At the time that
this analysis was prepared, 91, or
approximately 8 percent, of the 1166
active Medicare-certified IRFs did not
receive the full annual percentage
increase for the FY 2015 annual
payment update determination.
Information is not available to
determine the precise number of IRFs
that will not meet the requirements to
receive the full annual percentage
increase for the FY 2017 payment
determination.
In section VII.L of this proposed rule,
we discuss our proposal to suspend the
previously finalized data accuracy
validation policy for IRFs. While we
cannot estimate the increase in the
number of IRFs that will meet IRF QRP
compliance standards at this time, we
believe that this number will increase
due to the temporary suspension of this
policy. Thus, we estimate that the
suspension of this policy will decrease
impact on overall IRF payments, by
increasing the rate of compliance, in
addition to decreasing the cost of the
IRF QRP to each IRF provider by
approximately $47,320 per IRF, which
was the estimated cost to each IRF
provider to the implement the
previously finalized policy.
In section VII.F of this proposed rule,
we are proposing four measures for the
FY 2018 payment determinations and
subsequent years: (1) MSPB–PAC IRF
QRP; (2) Discharge to Community-PAC
IRF QRP, and (3) Potentially Preventable
30-Day Post-Discharge Readmission
Measure for IRF QRP; (4) Potentially
Preventable Within Stay Readmission
Measure IRFs. These four measures are
Medicare claims-based measures;
because claims-based measures can be
calculated based on data that are already
reported to the Medicare program for
payment purposes, we believe there will
be no additional impact.
In section VII.G of this proposed rule,
we are also proposing to adopt one
measure for the FY 2020 payment

PO 00000

Frm 00049

Fmt 4701

Sfmt 4702

24225

determination and subsequent years:
Drug Regimen Review Conducted with
Follow-Up for Identified Issues—PAC
IRF QRP. Additionally, we propose that
data for this measure will be collected
and reported using the IRF–PAI (version
effective October 1, 2018). While the
reporting of data on quality measures is
an information collection, we believe
that the burden associated with
modifications to the IRF–PAI discussed
in this proposed rule fall under the PRA
exceptions provided in 1899B(m) of the
Act because they are required to achieve
the standardization of patient
assessment data. Section 1899B(m) of
the Act provides that the PRA does not
apply to section 1899B and the sections
referenced in section 1899B(a)(2)(B) of
the Act that require modification to
achieve the standardization of patient
assessment data. The requirement and
burden will, however, be submitted to
OMB for review and approval when the
modifications to the IRF–PAI or other
applicable PAC assessment instrument
are not used to achieve the
standardization of patient assessment
data.
The total cost related to the proposed
measures is estimated at $4,625.46 per
IRF annually, or $5,231,398.17 for all
IRFs annually.
We intend to continue to closely
monitor the effects of this new quality
reporting program on IRF providers and
help perpetuate successful reporting
outcomes through ongoing stakeholder
education, national trainings, IRF
provider announcements, Web site
postings, CMS Open Door Forums, and
general and technical help desks.
D. Alternatives Considered
The following is a discussion of the
alternatives considered for the IRF PPS
updates contained in this proposed rule.
Section 1886(j)(3)(C) of the Act
requires the Secretary to update the IRF
PPS payment rates by an increase factor
that reflects changes over time in the
prices of an appropriate mix of goods
and services included in the covered
IRF services Thus, we did not consider
alternatives to updating payments using
the estimated IRF market basket
increase factor for FY 2017. However, as
noted previously in this proposed rule,
section 1886(j)(3)(C)(ii)(I) of the Act
requires the Secretary to apply a
productivity adjustment to the market
basket increase factor for FY 2017, and
sections 1886(j)(3)(C)(ii)(II) and
1886(j)(3)(D)(v) of the Act require the
Secretary to apply a 0.75 percentage
point reduction to the market basket
increase factor for FY 2017. Thus, in
accordance with section 1886(j)(3)(C) of
the Act, we propose to update the IRF

E:\FR\FM\25APP2.SGM

25APP2

24226

Federal Register / Vol. 81, No. 79 / Monday, April 25, 2016 / Proposed Rules

federal prospective payments in this
proposed rule by 1.45 percent (which
equals the 2.7 percent estimated IRF
market basket increase factor for FY
2017 reduced by a 0.5 percentage point
productivity adjustment as required by
section 1886(j)(3)(C)(ii)(I) of the Act and
further reduced by 0.75 percentage
point).
We considered maintaining the
existing CMG relative weights and
average length of stay values for FY
2017. However, in light of recently
available data and our desire to ensure
that the CMG relative weights and
average length of stay values are as
reflective as possible of recent changes
in IRF utilization and case mix, we
believe that it is appropriate to propose
to update the CMG relative weights and
average length of stay values at this time
to ensure that IRF PPS payments
continue to reflect as accurately as
possible the current costs of care in
IRFs.

We considered updating facility-level
adjustment factors for FY 2017.
However, as discussed in more detail in
the FY 2015 final rule (79 FR 45872), we
believe that freezing the facility-level
adjustments at FY 2014 levels for FY
2015 and all subsequent years (unless
and until the data indicate that they
need to be further updated) will allow
us an opportunity to monitor the effects
of the substantial changes to the
adjustment factors for FY 2014, and will
allow IRFs time to adjust to the previous
changes.
We considered maintaining the
existing outlier threshold amount for FY
2017. However, analysis of updated FY
2015 data indicates that estimated
outlier payments would be lower than 3
percent of total estimated payments for
FY 2017, by approximately 0.2 percent,
unless we updated the outlier threshold
amount. Consequently, we propose
adjusting the outlier threshold amount
in this proposed rule to reflect a 0.2

percent increase thereby setting the total
outlier payments equal to 3 percent,
instead of 2.8 percent, of aggregate
estimated payments in FY 2017.
E. Accounting Statement
As required by OMB Circular A–4
(available at http://
www.whitehouse.gov/sites/default/files/
omb/assets/omb/circulars/a004/a4.pdf), in Table 22, we have prepared an
accounting statement showing the
classification of the expenditures
associated with the provisions of this
proposed rule. Table 22 provides our
best estimate of the increase in Medicare
payments under the IRF PPS as a result
of the proposed updates presented in
this proposed rule based on the data for
1,131 IRFs in our database. In addition,
Table 22 presents the costs associated
with the proposed new IRF quality
reporting program for FY 2017.

TABLE 22—ACCOUNTING STATEMENT: CLASSIFICATION OF ESTIMATED EXPENDITURES
Category

Transfers

Change in Estimated Transfers from FY 2016 IRF PPS to FY 2017 IRF
PPS:
Annualized Monetized Transfers ..............................................................
From Whom to Whom? ............................................................................

$125 million.
Federal Government to IRF Medicare Providers.

File Type	application/pdf
File Modified	2016-04-23
File Created	2016-04-23