Medicare and Medicaid Programs; CY 2017 Home Health Prospective Payment System Rate Update; Home Health Value-Based Purchasing Model; and Home Health Quality Reporting Requirements, 43713-43788 [2016-15448]
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Vol. 81
Tuesday,
No. 128
July 5, 2016
Part II
Department of Health and Human Services
sradovich on DSK3GDR082PROD with PROPOSALS2
Centers for Medicare & Medicaid Services
42 CFR Parts 409 and 484
Medicare and Medicaid Programs; CY 2017 Home Health Prospective
Payment System Rate Update; Home Health Value-Based Purchasing
Model; and Home Health Quality Reporting Requirements; Proposed Rule
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Federal Register / Vol. 81, No. 128 / Tuesday, July 5, 2016 / Proposed Rules
DEPARTMENT OF HEALTH AND
HUMAN SERVICES
Centers for Medicare & Medicaid
Services
42 CFR Parts 409 and 484
[CMS–1648–P]
RIN 0938–AS80
Medicare and Medicaid Programs; CY
2017 Home Health Prospective
Payment System Rate Update; Home
Health Value-Based Purchasing Model;
and Home Health Quality Reporting
Requirements
Centers for Medicare &
Medicaid Services (CMS), HHS.
ACTION: Proposed rule.
AGENCY:
This proposed rule would
update the Home Health Prospective
Payment System (HH PPS) payment
rates, including the national,
standardized 60-day episode payment
rates, the national per-visit rates, and
the non-routine medical supply (NRS)
conversion factor, effective for home
health episodes of care ending on or
after January 1, 2017. This proposed
rule also: Implements the last year of the
4-year phase-in of the rebasing
adjustments to the HH PPS payment
rates; updates the HH PPS case-mix
weights using the most current,
complete data available at the time of
rulemaking; implements the 2nd-year of
a 3-year phase-in of a reduction to the
national, standardized 60-day episode
payment to account for estimated casemix growth unrelated to increases in
patient acuity (that is, nominal case-mix
growth) between CY 2012 and CY 2014;
proposes changes to the methodology
used to calculate outlier payments (with
regards to payments made under the HH
PPS for high-cost ‘‘outlier’’ episodes of
care (that is, episodes of care with
unusual variations in the type or
amount of medically necessary care));
proposes changes in payment for
Negative Pressure Wound Therapy
(NPWT) performed using a disposable
device for patient’s under a home health
plan of care; discusses our efforts to
monitor the potential impacts of the
rebasing adjustments mandated;
includes an update on subsequent
research and analysis as a result of the
findings from the home health study;
solicits comments on a potential process
for grouping HH PPS claims centrally
during claims processing; and proposes
changes to the Home Health ValueBased Purchasing (HHVBP) Model,
which was implemented on January 1,
2016; and proposes updates to the Home
sradovich on DSK3GDR082PROD with PROPOSALS2
SUMMARY:
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Health Quality Reporting Program (HH
QRP).
DATES: To be assured consideration,
comments must be received at one of
the addresses provided below, no later
than 5 p.m. on August 26, 2016.
ADDRESSES: In commenting, please refer
to file code CMS–1648–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 https://www.regulations.gov. Follow
the instructions under the ‘‘More Search
Options’’ tab.
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–1648–P, P.O. Box 8016, Baltimore,
MD 21244–8016.
Please allow sufficient time for mailed
comments to be received before the
close of the comment period.
3. By express or overnight mail. You
may send written comments to the
following address ONLY: Centers for
Medicare & Medicaid Services,
Department of Health and Human
Services, Attention: CMS–1648–P, Mail
Stop C4–26–05, 7500 Security
Boulevard, Baltimore, MD 21244–1850.
4. By hand or courier. If you prefer,
you may deliver (by hand or courier)
your written comments before the close
of the comment period to either of the
following addresses:
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
Comments 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: For
general information about the HH PPS,
please send your inquiry via email to:
HomehealthPolicy@cms.hhs.gov.
For information about the HHVBP
Model, please send your inquiry via
email to: HHVBPquestions@
cms.hhs.gov.
Michelle Brazil, (410) 786–1648 for
information about the HH quality
reporting program.
Lori Teichman, (410) 786–6684, for
information about HHCAHPS.
SUPPLEMENTARY INFORMATION:
Inspection of Public Comments: All
comments received before the close of
the comment period are available for
viewing by the public, including any
personally identifiable or confidential
business information that is included in
a comment. We post all comments
received before the close of the
comment period on the following Web
site as soon as possible after they have
been received at https://
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. EST. To schedule an
appointment to view public comments,
phone 1–800–743–3951.
(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.)
I. Executive Summary
A. Purpose
B. Summary of the Major Provisions
C. Summary of Costs and Benefits
II. Background
A. Statutory Background
B. System for Payment of Home Health
Services
C. Updates to the Home Health Prospective
Payment System
III. Proposed Provisions of the Home Health
Prospective Payment System
A. Monitoring for Potential Impacts—
Affordable Care Act Rebasing
Adjustments
B. Proposed CY 2017 HH PPS Case-Mix
Weights
C. Proposed CY 2017 Home Health Rate
Update
1. Proposed CY 2017 Home Health Market
Basket Update
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 (410) 786–7195 in advance to
schedule your arrival with one of our
staff members.
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Table of Contents
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2. Proposed CY 2017 Home Health Wage
Index
3. Proposed CY 2017 Annual Payment
Update
D. Payments for High-Cost Outliers Under
the HH PPS
1. Background
2. Proposed Changes to the Methodology
Used To Estimate Episode Cost
3. Proposed Fixed Dollar Loss (FDL) Ratio
E. Proposed Payment Policies for Negative
Pressure Wound Therapy Using a
Disposable Device
F. Update on Subsequent Research and
Analysis Related to Section 3131(d) of
the Affordable Care Act
G. Update on Future Plans to Group HH
PPS Claims Centrally During Claims
Processing
IV. Proposed Provisions of the Home Health
Value-Based Purchasing (HHVBP) Model
A. Background
B. Smaller- and Larger-Volume Cohorts
C. Quality Measures
D. Appeals Process
E. Discussion of the Public Display of Total
Performance Scores
V. Proposed Updates to the Home Health
Care Quality Reporting Program
(HHQRP)
A. Background and Statutory Authority
B. General Considerations Used for the
Selection of Quality Measures for the HH
QRP
C. Policy for Retaining HH QRP Quality
Measures Adopted for Future Payment
Determination
D. Process for Adoption of Changes to HH
QRP Measures
E. HH QRP Quality, Resource Use, and
Other Measures for CY 2018 Payment
Determination and Subsequent Years
1. Proposal To Address the IMPACT Act
Domain of Resource Use and Other
Measures: MSPB–PAC HH QRP
2. Proposal To Address the IMPACT Act
Domain of Resource Use and Other
Measures: Discharge to Community—
Post Acute Care Home Health Quality
Reporting Program
3. Proposal To Address the IMPACT Act of
2014 Domain of Resource Use and Other
Measures: Potentially Preventable 30Day Post-Discharge Readmission
Measure for Post-Acute Care Home
Health Quality Reporting Program.
4. Proposal To Address the IMPACT Act
Domain of Medication Reconciliation:
Drug Regimen Review Conducted With
Follow-Up for Identified Issues-PostAcute Care Home Health Quality
Reporting Program.
F. HH QRP Quality Measures and Measure
Concepts Under Consideration for Future
Years
G. Form Manner and Timing of OASIS
Data Submission and OASIS Data for
Annual Payment Update
1. Regulatory Authority
2. Home Health Quality Reporting Program
Requirements for CY 2017 Payment and
Subsequent Years
3. Previously Established Pay-for-Reporting
Performance Requirement for
Submission of OASIS Quality Data
4. Proposed Timeline and Data Submission
Mechanisms for Measures Proposed for
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the CY 2018 Payment Determination and
Subsequent Years
5. Proposed Timeline and Data Submission
Mechanisms for the CY 2018 Payment
Determination and Subsequent Years for
New HH QRP Assessment-Based Quality
Measure
6. Data Collection Timelines and
Requirements for the CY 2019 Payment
Determinations and Subsequent Years
7. Proposed Data Review and Correction
Timeframes for Data Submitted Using
the OASIS Instrument
H. Public Display of Quality Measure Data
and Opportunity for Providers To
Review and Correct Data and
Information to be Made Public
I. Mechanism for Providing Feedback
Reports to HHAs
J. Home Health Care CAHPS® Survey
(HHCAHPS)
1. Background and Description of
HHCAHPS
2. HHCAHPS Oversight Activities
3. HHCAHPS Requirements for the CY
2017 APU
4. HHCAHPS Requirements for the CY
2018 APU
5. HHCAHPS Requirements for the CY
2019 APU
6. HHCAHPS Requirements for the CY
2020 APU
7. HHCAHPS Reconsideration and Appeals
Process
8. Summary
VI. Collection of Information Requirements
VII. Response to Comments
VIII. Regulatory Impact Analysis
IX. Federalism Analysis
Regulations Text
Acronyms
In addition, because of the many
terms to which we refer by abbreviation
in this proposed rule, we are listing
these abbreviations and their
corresponding terms in alphabetical
order below:
ACH LOS Acute Care Hospital Length of
Stay
ADL Activities of Daily Living
APU Annual Payment Update
BBA Balanced Budget Act of 1997, Pub. L.
105–33
BBRA Medicare, Medicaid, and SCHIP
Balanced Budget Refinement Act of 1999,
(Pub. L. 106–113)
CAD Coronary Artery Disease
CAH Critical Access Hospital
CBSA Core-Based Statistical Area
CASPER Certification and Survey Provider
Enhanced Reports
CHF Congestive Heart Failure
CMI Case-Mix Index
CMP Civil Money Penalty
CMS Centers for Medicare & Medicaid
Services
CoPs Conditions of Participation
COPD Chronic Obstructive Pulmonary
Disease
CVD Cardiovascular Disease
CY Calendar Year
DM Diabetes Mellitus
DRA Deficit Reduction Act of 2005, Pub. L.
109–171, enacted February 8, 2006
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FDL Fixed Dollar Loss
FI Fiscal Intermediaries
FISS Fiscal Intermediary Shared System
FR Federal Register
FY Fiscal Year
HAVEN Home Assessment Validation and
Entry System
HCC Hierarchical Condition Categories
HCIS Health Care Information System
HH Home Health
HHA Home Health Agency
HHCAHPS Home Health Care Consumer
Assessment of Healthcare Providers and
Systems Survey
HH PPS Home Health Prospective Payment
System
HHRG Home Health Resource Group
HHVBP Home Health Value-Based
Purchasing
HIPPS Health Insurance Prospective
Payment System
HVBP Hospital Value-Based Purchasing
ICD–9–CM International Classification of
Diseases, Ninth Revision, Clinical
Modification
ICD–10–CM International Classification of
Diseases, Tenth Revision, Clinical
Modification
IH Inpatient Hospitalization
IMPACT Act Improving Medicare PostAcute Care Transformation Act of 2014
(Pub. L. 113–185)
IRF Inpatient Rehabilitation Facility
LEF Linear Exchange Function
LTCH Long-Term Care Hospital
LUPA Low-Utilization Payment
Adjustment
MEPS Medical Expenditures Panel Survey
MMA Medicare Prescription Drug,
Improvement, and Modernization Act of
2003, Pub. L. 108–173, enacted December
8, 2003
MSA Metropolitan Statistical Area
MSS Medical Social Services
NQF National Quality Forum
NQS National Quality Strategy
NRS Non-Routine Supplies
OASIS Outcome and Assessment
Information Set
OBRA Omnibus Budget Reconciliation Act
of 1987, Pub. L. 100–2–3, enacted
December 22, 1987
OCESAA Omnibus Consolidated and
Emergency Supplemental Appropriations
Act, Pub. L. 105–277, enacted October 21,
1998
OES Occupational Employment Statistics
OIG Office of Inspector General
OT Occupational Therapy
OMB Office of Management and Budget
MFP Multifactor productivity
PAMA Protecting Access to Medicare Act
of 2014
PAC–PRD Post-Acute Care Payment
Reform Demonstration
PEP Partial Episode Payment Adjustment
PT Physical Therapy
PY Performance Year
PRRB Provider Reimbursement Review
Board
QAP Quality Assurance Plan
RAP Request for Anticipated Payment
RF Renal Failure
RFA Regulatory Flexibility Act, Pub. L. 96–
354
RHHIs Regional Home Health
Intermediaries
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RIA Regulatory Impact Analysis
SAF Standard Analytic File
SLP Speech-Language Pathology
SN Skilled Nursing
SNF Skilled Nursing Facility
TPS Total Performance Score
UMRA Unfunded Mandates Reform Act of
1995
VBP Value-Based Purchasing
sradovich on DSK3GDR082PROD with PROPOSALS2
I. Executive Summary
A. Purpose
This proposed rule would update the
payment rates for home health agencies
(HHAs) for calendar year (CY) 2017, as
required under section 1895(b) of the
Social Security Act (the Act). This
would reflect the final year of the 4-year
phase-in of the rebasing adjustments to
the national, standardized 60-day
episode payment rate, the national pervisit rates, and the NRS conversion
factor finalized in the CY 2014 HH PPS
final rule (78 FR 72256), as required
under section 3131(a) of the Patient
Protection and Affordable Care Act of
2010 (Pub. L. 111–148), as amended by
the Health Care and Education
Reconciliation Act of 2010 (Pub. L. 111–
152) (collectively referred to as the
‘‘Affordable Care Act’’).
This proposed rule would update the
case-mix weights under section
1895(b)(4)(A)(i) and (b)(4)(B) of the Act
and includes a reduction to the national,
standardized 60-day episode payment
rate in CY 2017 of 0.97 percent, to
account for case-mix growth unrelated
to increases in patient acuity (nominal
case-mix growth) between CY 2012 and
CY 2014 under the authority of section
1895(b)(3)(B)(iv) of the Act. With
regards to payments made under the HH
PPS for high-cost ‘‘outlier’’ episodes of
care (that is, episodes of care with
unusual variations in the type or
amount of medically necessary care),
this rule proposes changes to the
methodology used to calculate outlier
payments under the authority of section
1895(b)(5) of the Act. Also, in
accordance with section 1834(s)(1) of
the Act, as amended by the
Consolidated Appropriations Act of
2016 (Pub. L. 114–113), this rule
proposes changes in payment for
Negative Pressure Wound Therapy
(NPWT) performed using a disposable
device for patient’s under a home health
plan of care for which payment would
otherwise be made under section
1895(b) of the Act. This proposed rule
also discusses our efforts to monitor for
potential impacts of the rebasing
adjustments mandated by section
3131(a) of the Affordable Care Act,
provides an update on subsequent
research and analysis as a result of the
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findings from the home health study
required by section 3131(d) of the
Affordable Care Act, and provides and
update and solicits comments on a
process to group HH PPS claims
centrally during claims processing.
Additionally, this rule proposes changes
to the HHVBP Model, in which
Medicare-certified HHAs in certain
states are required to participate as of
January 1, 2016, under the authority of
section 1115A of the Act; and proposes
changes to the home health quality
reporting program requirements under
the authority of section
1895(b)(3)(B)(v)(II) of the Act.
B. Summary of the Major Provisions
As required by section 3131(a) of the
Affordable Care Act, and finalized in the
CY 2014 HH PPS final rule (78 FR
77256, December 2, 2013), we are
implementing the final year of the 4year phase-in of the rebasing
adjustments to the national,
standardized 60-day episode payment
amount, the national per-visit rates and
the NRS conversion factor in section
III.C.3. The rebasing adjustments for CY
2017 will reduce the national,
standardized 60-day episode payment
amount by $80.95, increase the national
per-visit payment amounts by 3.5
percent of the national per-visit
payment amounts in CY 2010 with the
increases ranging from $1.79 for home
health aide services to $6.34 for medical
social services, and reduce the NRS
conversion factor by 2.82 percent. In
addition, in section III.C.3 of this rule,
we are implementing a reduction to the
national, standardized 60-day episode
payment rate in CY 2017 of 0.97 percent
to account for estimated case-mix
growth unrelated to increases in patient
acuity (that is, nominal case-mix
growth) between CY 2012 and CY 2014.
This reduction was finalized in the CY
2016 HH PPS final rule (80 FR 68624).
Section III.A of this proposed rule
discusses our efforts to monitor for
potential impacts due to the rebasing
adjustments mandated by section
3131(a) of the Affordable Care Act.
In the CY 2015 HH PPS final rule (79
FR 66072), we finalized our proposal to
recalibrate the case-mix weights every
year with more current data. In section
III.B.1 of this rule, we are recalibrating
the HH PPS case-mix weights, using the
most current cost and utilization data
available, in a budget neutral manner. In
section III.C.1 of this rule, we propose
to update the payment rates under the
HH PPS by the home health payment
update percentage of 2.3 percent (using
the 2010-based Home Health Agency
(HHA) market basket update of 2.8
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percent, minus 0.5 percentage point for
productivity), as required by section
1895(b)(3)(B)(vi)(I) of the Act, and in
section III.C.2 of this rule, we propose
to update the CY 2017 home health
wage index using more current hospital
wage data. In section III.D, we are
proposing to revise the current
methodology used to estimate the cost
of an episode of care to determine
whether the episode of care would
receive an outlier payment. The
methodology change includes
calculating the cost of an episode of care
using a cost-per-unit calculation, which
takes into account visit length, rather
than the current methodology that uses
a cost-per-visit calculation. In section
III.E of this proposed rule, as a result of
the Consolidated Appropriations Act of
2016 (Pub. L. 114–113), we are
proposing changes in payment for when
Negative Pressure Wound Therapy
(NPWT) is performed using a disposable
device for a patient under a home health
plan of care and for which payment is
otherwise made under the HH PPS. In
section III.F of this rule, we provide an
update on our recent research and
analysis pertaining to the home health
study required by section 3131(d) of the
Affordable Care Act. Finally, in section
III.G of this proposed rule, we provide
an update and solicit comments on a
process for grouping the HH PPS claims
centrally during claims processing.
In section IV of this rule, we are
proposing the following changes to the
HHVBP Model implemented January 1,
2016. We propose to remove the
definition for ‘‘starter set’’; propose to
revise the definition for ‘‘benchmark’’;
propose to calculate benchmarks and
achievement thresholds at the state
level; propose a minimum requirement
of eight HHAs in a cohort; propose to
increase the time frame for submitting
New Measure data; propose to remove
four measures from the set of applicable
measures; propose to adjust the
reporting period and submission date
for one of the New Measures; propose to
add an appeals process that includes the
existing recalculation process; and we
are providing an update on the progress
towards developing public reporting of
performance under the HHVBP Model.
This proposed rule also proposes
updates to the Home Health Quality
Reporting Program in section V,
including the adoption of four new
quality measures, the removal of a
number of measures, data submission
requirements, and data review and
correction policies.
C. Summary of Costs and Transfers
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TABLE 1—SUMMARY OF COSTS AND TRANSFERS
Provision description
Costs
Transfers
CY 2017 HH PPS Payment Rate Update
........................
CY 2017 HHVBP Model ...........................
........................
The overall economic impact of the HH PPS payment rate update is an estimated
¥$180 million (¥1.0 percent) in payments to HHAs.
The overall economic impact of the HHVBP Model provision for CY 2018 through
2022 is an estimated $378 million in total savings from a reduction in unnecessary hospitalizations and SNF usage as a result of greater quality improvements
in the HH industry. As for payments to HHAs, there are no aggregate increases
or decreases to the HHAs competing in the model.
II. Background
sradovich on DSK3GDR082PROD with PROPOSALS2
A. Statutory Background
The Balanced Budget Act of 1997
(BBA) (Pub. L. 105–33, enacted August
5, 1997), significantly changed the way
Medicare pays for Medicare HH
services. Section 4603 of the BBA
mandated the development of the HH
PPS. Until the implementation of the
HH PPS on October 1, 2000, HHAs
received payment under a retrospective
reimbursement system.
Section 4603(a) of the BBA mandated
the development of a HH PPS for all
Medicare-covered HH services provided
under a plan of care (POC) that were
paid on a reasonable cost basis by
adding section 1895 of the Act, entitled
‘‘Prospective Payment For Home Health
Services.’’ Section 1895(b)(1) of the Act
requires the Secretary to establish a HH
PPS for all costs of HH services paid
under Medicare.
Section 1895(b)(3)(A) of the Act
requires the following: (1) The
computation of a standard prospective
payment amount, to include all costs for
HH services covered and paid for on a
reasonable cost basis, and that such
amounts be initially based on the most
recent audited cost report data available
to the Secretary; and (2) the
standardized prospective payment
amount is to be adjusted to account for
the effects of case-mix and wage levels
among HHAs.
Section 1895(b)(3)(B) of the Act
requires an annual update to the
standard prospective payment amounts
by the HH applicable percentage
increase. Section 1895(b)(4) of the Act
governs the payment computation.
Sections 1895(b)(4)(A)(i) and
(b)(4)(A)(ii) of the Act require the
standard prospective payment amount
to be adjusted for case-mix and
geographic differences in wage levels,
respectively. Section 1895(b)(4)(B) of
the Act requires the establishment of an
appropriate case-mix change adjustment
factor for significant variation in costs
among different units of services.
Similarly, section 1895(b)(4)(C) of the
Act requires the establishment of wage
adjustment factors that reflect the
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relative level of wages, and wage-related
costs applicable to HH services
furnished in a geographic area
compared to the applicable national
average level. Under section
1895(b)(4)(C) of the Act, the wageadjustment factors used by the Secretary
may be the factors used under section
1886(d)(3)(E) of the Act.
Section 1895(b)(5) of the Act gives the
Secretary the option to make additions
or adjustments to the payment amount
otherwise paid in the case of outliers
due to unusual variations in the type or
amount of medically necessary care.
Section 3131(b)(2) of the Patient
Protection and Affordable Care Act of
2010 (the Affordable Care Act) (Pub. L.
111–148, enacted March 23, 2010)
revised section 1895(b)(5) of the Act so
that total outlier payments in a given
year would not exceed 2.5 percent of
total payments projected or estimated.
The provision also made permanent a
10 percent agency-level outlier payment
cap.
In accordance with the statute, as
amended by the BBA, we published a
final rule in the July 3, 2000 Federal
Register (65 FR 41128) to implement the
HH PPS legislation. The July 2000 final
rule established requirements for the
new HH PPS for HH services as required
by section 4603 of the BBA, as
subsequently amended by section 5101
of the Omnibus Consolidated and
Emergency Supplemental
Appropriations Act (OCESAA) for Fiscal
Year 1999, (Pub. L. 105–277, enacted
October 21, 1998); and by sections 302,
305, and 306 of the Medicare, Medicaid,
and SCHIP Balanced Budget Refinement
Act (BBRA) of 1999, (Pub. L. 106–113,
enacted November 29, 1999). The
requirements include the
implementation of a HH PPS for HH
services, consolidated billing
requirements, and a number of other
related changes. The HH PPS described
in that rule replaced the retrospective
reasonable cost-based system that was
used by Medicare for the payment of HH
services under Part A and Part B. For a
complete and full description of the HH
PPS as required by the BBA, see the July
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2000 HH PPS final rule (65 FR 41128
through 41214).
Section 5201(c) of the Deficit
Reduction Act of 2005 (DRA) (Pub. L.
109–171, enacted February 8, 2006)
added new section 1895(b)(3)(B)(v) to
the Act, requiring HHAs to submit data
for purposes of measuring health care
quality, and links the quality data
submission to the annual applicable
percentage increase. This data
submission requirement is applicable
for CY 2007 and each subsequent year.
If an HHA does not submit quality data,
the HH market basket percentage
increase is reduced by 2 percentage
points. In the November 9, 2006 Federal
Register (71 FR 65884, 65935), we
published a final rule to implement the
pay-for-reporting requirement of the
DRA, which was codified at
§ 484.225(h) and (i) in accordance with
the statute. The pay-for-reporting
requirement was implemented on
January 1, 2007.
The Affordable Care Act made
additional changes to the HH PPS. One
of the changes set out in section 3131 of
the Affordable Care Act was an
amendment to section 421(a) of the
Medicare Prescription Drug,
Improvement, and Modernization Act of
2003 (MMA) (Pub. L. 108–173, enacted
on December 8, 2003) as amended by
section 5201(b) of the DRA. Section
421(a) of the MMA, as amended by
section 3131 of the Affordable Care Act,
requires that the Secretary increase, by
3 percent, the payment amount
otherwise made under section 1895 of
the Act, for HH services furnished in a
rural area (as defined in section
1886(d)(2)(D) of the Act) with respect to
episodes and visits ending on or after
April 1, 2010, and before January 1,
2016. Section 210 of the Medicare
Access and CHIP Reauthorization Act of
2015 (MACRA) (Pub. L. 114–10)
amended section 421(a) of the MMA to
extend the rural add-on for 2 more
years. Section 421(a) of the MMA, as
amended by section 210 of the MACRA,
requires that the Secretary increase, by
3 percent, the payment amount
otherwise made under section 1895 of
the Act, for HH services provided in a
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rural area (as defined in section
1886(d)(2)(D) of the Act) with respect to
episodes and visits ending on or after
April 1, 2010, and before January 1,
2018.
Section 2(a) of the Improving
Medicare Post-Acute Care
Transformation Act of 2014 (the
IMPACT Act) (Pub. L. 113–185, enacted
on Oct. 6, 2014) amended Title XVIII of
the Act, in part, by adding a new section
1899B, which imposes new data
reporting requirements for certain postacute care (PAC) providers, including
HHAs. Under section 1899B(a)(1) of the
Act, certain post-acute care (PAC)
providers (defined in section
1899B(a)(2)(A) of the Act as HHAs,
SNFs, IRFs, and LTCHs) must submit
standardized patient assessment data in
accordance with section 1899B(b) of the
Act, data on quality measures required
under section 1899B(c)(1) of the Act,
and data on resource use, and other
measures required under section
1899B(d)(1) of the Act. The Act also
requires the Secretary to specify these
measures insofar as they are respect to
certain domains no later than the
applicable specified application date
that applies to each domain. The
specific specified application dates that
apply to each PAC provider type and
domain are described in section
1899B(a)(2)(E) of the Act.
B. System for Payment of Home Health
Services
Generally, Medicare makes payment
under the HH PPS on the basis of a
national standardized 60-day episode
payment rate that is adjusted for the
applicable case-mix and wage index.
The national standardized 60-day
episode rate includes the six HH
disciplines (skilled nursing, HH aide,
physical therapy, speech-language
pathology, occupational therapy, and
medical social services). Payment for
non-routine supplies (NRS) is no longer
part of the national standardized 60-day
episode rate and is computed by
multiplying the relative weight for a
particular NRS severity level by the NRS
conversion factor (See section II.D.4.e).
Payment for durable medical equipment
covered under the HH benefit is made
outside the HH PPS payment system. To
adjust for case-mix, the HH PPS uses a
153-category case-mix classification
system to assign patients to a home
health resource group (HHRG). The
clinical severity level, functional
severity level, and service utilization are
computed from responses to selected
data elements in the OASIS assessment
instrument and are used to place the
patient in a particular HHRG. Each
HHRG has an associated case-mix
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weight which is used in calculating the
payment for an episode.
For episodes with four or fewer visits,
Medicare pays national per-visit rates
based on the discipline(s) providing the
services. An episode consisting of four
or fewer visits within a 60-day period
receives what is referred to as a lowutilization payment adjustment (LUPA).
Medicare also adjusts the national
standardized 60-day episode payment
rate for certain intervening events that
are subject to a partial episode payment
adjustment (PEP adjustment). For
certain cases that exceed a specific cost
threshold, an outlier adjustment may
also be available.
C. Updates to the Home Health
Prospective Payment System
As required by section 1895(b)(3)(B)
of the Act, we have historically updated
the HH PPS rates annually in the
Federal Register. The August 29, 2007
final rule with comment period set forth
an update to the 60-day national
episode rates and the national per-visit
rates under the HH PPS for CY 2008.
The CY 2008 HH PPS final rule
included an analysis performed on CY
2005 HH claims data, which indicated
a 12.78 percent increase in the observed
case-mix since 2000. Case-mix
represents the variations in conditions
of the patient population served by the
HHAs. Subsequently, a more detailed
analysis was performed on the 2005
case-mix data to evaluate if any portion
of the 12.78 percent increase was
associated with a change in the actual
clinical condition of HH patients. We
examined data on demographics, family
severity, and non-HH Part A Medicare
expenditures to predict the average
case-mix weight for 2005. We identified
8.03 percent of the total case-mix
change as real, and therefore, decreased
the 12.78 percent of total case-mix
change by 8.03 percent to get a final
nominal case-mix increase measure of
11.75 percent (0.1278 * (1 ¥ 0.0803) =
0.1175).
To account for the changes in casemix that were not related to an
underlying change in patient health
status, we implemented a reduction,
over 4 years, to the national,
standardized 60-day episode payment
rates. That reduction was to be 2.75
percent per year for 3 years beginning in
CY 2008 and 2.71 percent for the fourth
year in CY 2011. In the CY 2011 HH PPS
final rule (76 FR 68532), we updated our
analyses of case-mix change and
finalized a reduction of 3.79 percent,
instead of 2.71 percent, for CY 2011 and
deferred finalizing a payment reduction
for CY 2012 until further study of the
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case-mix change data and methodology
was completed.
In the CY 2012 HH PPS final rule (76
FR 68526), we updated the 60-day
national episode rates and the national
per-visit rates. In addition, as discussed
in the CY 2012 HH PPS final rule (76
FR 68528), our analysis indicated that
there was a 22.59 percent increase in
overall case-mix from 2000 to 2009 and
that only 15.76 percent of that overall
observed case-mix percentage increase
was due to real case-mix change. As a
result of our analysis, we identified a
19.03 percent nominal increase in casemix. At that time, to fully account for
the 19.03 percent nominal case-mix
growth identified from 2000 to 2009, we
finalized a 3.79 percent payment
reduction in CY 2012 and a 1.32 percent
payment reduction for CY 2013.
In the CY 2013 HH PPS final rule (77
FR 67078), we implemented a 1.32
percent reduction to the payment rates
for CY 2013 to account for nominal
case-mix growth from 2000 through
2010. When taking into account the total
measure of case-mix change (23.90
percent) and the 15.97 percent of total
case-mix change estimated as real from
2000 to 2010, we obtained a final
nominal case-mix change measure of
20.08 percent from 2000 to 2010 (0.2390
* (1 ¥ 0.1597) = 0.2008). To fully
account for the remainder of the 20.08
percent increase in nominal case-mix
beyond that which was accounted for in
previous payment reductions, we
estimated that the percentage reduction
to the national, standardized 60-day
episode rates for nominal case-mix
change would be 2.18 percent. Although
we considered proposing a 2.18 percent
reduction to account for the remaining
increase in measured nominal case-mix,
we finalized the 1.32 percent payment
reduction to the national, standardized
60-day episode rates in the CY 2012 HH
PPS final rule (76 FR 68532).
Section 3131(a) of the Affordable Care
Act also required that, beginning in CY
2014, we apply an adjustment to the
national, standardized 60-day episode
rate and other amounts that reflect
factors such as changes in the number
of visits in an episode, the mix of
services in an episode, the level of
intensity of services in an episode, the
average cost of providing care per
episode, and other relevant factors.
Additionally, we were required to phase
in any adjustment over a 4-year period
in equal increments, not to exceed 3.5
percent of the amount (or amounts) as
of the date of enactment of the
Affordable Care Act, and fully
implement the rebasing adjustments by
CY 2017. The statute specified that the
maximum rebasing adjustment was to
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be no more than 3.5 percent per year of
the CY 2010 rates. Therefore, in the CY
2014 HH PPS final rule (78 FR 72256)
for each year, CY 2014 through CY 2017,
we finalized a fixed-dollar reduction to
the national, standardized 60-day
episode payment rate of $80.95 per year,
increases to the national per-visit
payment rates per year as reflected in
Table 2, and a decrease to the NRS
conversion factor of 2.82 percent per
year. We also finalized three separate
LUPA add-on factors for skilled nursing,
physical therapy, and speech-language
pathology and removed 170 diagnosis
codes from assignment to diagnosis
groups in the HH PPS Grouper. In the
CY 2015 HH PPS final rule (79 FR
43719
66032), we implemented the 2nd year of
the 4 year phase-in of the rebasing
adjustments to the HH PPS payment
rates and made changes to the HH PPS
case-mix weights. In addition, we
simplified the face-to-face encounter
regulatory requirements and the therapy
reassessment timeframes.
TABLE 2—MAXIMUM ADJUSTMENTS TO THE NATIONAL PER-VISIT PAYMENT RATES
[Not to exceed 3.5 percent of the amount(s) in CY 2010]
2010 National
per-visit
payment rates
Skilled Nursing .............................................................................................................................................
Home Health Aide .......................................................................................................................................
Physical Therapy .........................................................................................................................................
Occupational Therapy ..................................................................................................................................
Speech-Language Pathology ......................................................................................................................
Medical Social Services ...............................................................................................................................
In the CY 2016 HH PPS final rule (80
FR 68624), we implemented the 3rd
year of the 4-year phase-in of the
rebasing adjustments to the national,
standardized 60-day episode payment
amount, the national per-visit rates and
the NRS conversion factor (as outlined
above).
In the CY 2016 HH PPS final rule, we
also recalibrated the HH PPS case-mix
weights, using the most current cost and
utilization data available, in a budget
neutral manner, and finalized
reductions to the national, standardized
60-day episode payment rate in CY
2016, CY 2017, and CY 2018 of 0.97
percent in each year to account for
estimated case-mix growth unrelated to
increases in patient acuity (that is,
nominal case-mix growth) between CY
2012 and CY 2014. Finally, we
continued to apply the payment
increase of 3 percent for HH services
provided in rural areas (as defined in
section 1886(d)(2)(D) of the Act) to
episodes or visits ending before January
1, 2018.
III. Proposed Provisions of the Home
Health Prospective Payment System
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A. Monitoring for Potential Impacts—
Affordable Care Act Rebasing
Adjustments
1. Analysis of FY 2014 HHA Cost Report
Data
As part of our efforts in monitoring
the potential impacts of the rebasing
adjustments finalized in the CY 2014
HH PPS final rule (78 FR 72293), we
continue to update our analysis of home
health cost report and claims data. In
the CY 2014 HH PPS final rule, using
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2011 cost report and 2012 claims data,
we estimated the 2013 60-day episode
cost to be $2,565.51 (78 FR 72277). In
that final rule, we stated that our
analysis of 2011 cost report data and
2012 claims data indicated a need for a
¥3.45 percent rebasing adjustment to
the national, standardized 60-day
episode payment rate each year for 4
years. However, as specified by statute,
the rebasing adjustment is limited to 3.5
percent of the CY 2010 national,
standardized 60-day episode payment
rate of $2,312.94 (74 FR 58106), or
$80.95. We stated that given that a
¥3.45 percent adjustment for CY 2014
through CY 2017 would result in larger
dollar amount reductions than the
maximum dollar amount allowed under
section 3131(a) of the Affordable Care
Act of $80.95, we were limited to
implementing a reduction of $80.95
(approximately 2.8 percent of the
standardized payment amount for CY
2014) to the national, standardized 60day episode payment amount each year
for CY 2014 through CY 2017.
In the CY 2015 HH PPS final rule, (79
FR 66032–66118) using 2012 cost report
and 2013 claims data, we estimated the
2013 60-day episode cost to be
$2,485.24 (79 FR 66037). Similar to our
discussion in the CY 2014 HH PPS final
rule, we stated that absent the
Affordable Care Act’s limit to rebasing,
in order to align payments with costs, a
¥4.21 percent adjustment would have
been applied to the national,
standardized 60-day episode payment
amount each year for CY 2014 through
CY 2017.
In the CY 2016 HH PPS proposed rule
(80 FR 39846–39866), using 2013 cost
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$113.01
51.18
123.57
124.40
134.27
181.16
Maximum
adjustments
per year
(CY 2014
through CY 2017)
$3.96
1.79
4.32
4.35
4.70
6.34
report and 2013 claims data, we
estimated the 2013 60-day episode cost
to be $2,402.11 (80 FR 39846). Similar
to our discussion in the CY 2014 HH
PPS final rule and the CY 2015 HH PPS
final rule, we stated that absent the
Affordable Care Act’s limit to rebasing,
in order to align payments with costs, a
¥5.02 percent adjustment would have
been applied to the national,
standardized 60-day episode payment
amount each year for CY 2014 through
CY 2017.
For this proposed rule, we analyzed
2014 HHA cost report data and 2014
HHA claims data to determine whether
the average cost per episode was higher
using 2014 cost report data compared to
the 2011 cost report and 2012 claims
da006used in calculating the rebasing
adjustments. To determine the 2014
average cost per visit per discipline, we
applied the same trimming methodology
outlined in the CY 2014 HH PPS
proposed rule (78 FR 40284) and
weighted the costs per visit from the
2014 cost reports by size, facility type,
and urban/rural location so the costs per
visit were nationally representative
according to 2014 claims data. The 2014
average number of visits was taken from
2014 claims data. We estimate the cost
of a 60-day episode in CY 2014 to be
$2,373.87 using 2014 cost report data
(Table 3). Our latest analysis of 2014
cost report and 2014 claims data
suggests that an even larger reduction
(¥5.30 percent) than the reduction
described in the CY 2014 HH PPS final
rule (¥3.45 percent) or the reductions
described in the CY 2015 HH PPS final
rule and the CY 2016 HH PPS proposed
rule (¥4.21 and ¥5.02 percent,
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respectively) would have been needed
in order to align payments with costs.
The decrease in the estimated 60-day
episode cost from $2,402.11 in CY 2013
to $2,373.87 in CY 2014 was due to both
a lower average cost per visit for skilled
nursing and home health aide services
in 2014 compared to 2013 and lower
average number of visits for skilled
nursing and home health aide services
per episode in 2014 compared to 2013.
TABLE 3—2014 ESTIMATED COST PER EPISODE
2014 Average
costs per visit
2014 Average
number of
visits
2014 60-Day
episode costs
Skilled Nursing .............................................................................................................................
Home Health Aide .......................................................................................................................
Physical Therapy .........................................................................................................................
Occupational Therapy ..................................................................................................................
Speech-Language Pathology ......................................................................................................
Medical Social Services ...............................................................................................................
$128.68
56.59
155.90
153.69
166.98
210.48
9.09
2.19
5.18
1.30
0.26
0.14
$1,169.70
123.93
807.56
199.80
43.41
29.47
Total ......................................................................................................................................
........................
18.16
2,373.87
Discipline
Source: FY 2014 Medicare cost report data and 2014 Medicare claims data from the standard analytic file (as of June 30, 2015) for episodes
(excluding low-utilization payment adjusted episodes and partial-episode-payment adjusted episodes) ending on or before December 31, 2014 for
which we could link an OASIS assessment.
2. Analysis of CY 2015 HHA Claims
Data
In the CY 2014 HH PPS final rule (78
FR 72256), some commenters expressed
concern that the rebasing of the HH PPS
payment rates would result in HHA
closures and would therefore diminish
access to home health services. In
addition to examining more recent cost
report data, for this proposed rule we
examined home health claims data from
the first 2 years (CY 2014 and CY 2015)
of the 4-year phase-in of the rebasing
adjustments (CY 2014 through CY
2017), the first calendar year of the HH
PPS (CY 2001), and claims data for the
3 years before implementation of the
rebasing adjustments (CY 2011–2013).
Preliminary analysis of CY 2015 home
health claims data indicates that the
number of episodes decreased by 3.8
percent from 2013 to 2014, and
decreased by 1.7 percent from 2014 to
2015. In addition, the number of home
health users that received at least one
episode of care decreased by 2.95
percent between 2013 and 2014, and
decreased slightly by 0.5 percent from
2014 to 2015.The number of FFS
beneficiaries has remained the relatively
constant between 2013 and 2015.
Between 2013 and 2014 there appears to
be a net decrease in the number of
HHAs billing Medicare for home health
services of 1.6 percent, and a continued
decrease of 2.7 percent from 2014 to
2015. We note that in CY 2015 there
were 2.9 HHAs per 10,000 FFS
beneficiaries, which is still markedly
higher than the 1.9 HHAs per 10,000
FFS beneficiaries before the
implementation of the HH PPS
methodology in 2001. The number of
home health users, as a percentage of
FFS beneficiaries, has been decreasing
since 2011, from 9.2 percent to 8.7
percent in 2015. We would note that
preliminary FFS data on per-enrollee
hospital and skilled nursing facility
discharges and days indicates that there
was a decrease in hospital discharges of
approximately 0.7 percent and a
decrease in SNF days of approximately
0.9 percent in CY 2015. Any decreases
in hospital discharges and skilled
nursing facility days could, in turn,
impact home health utilization as those
settings serve as important sources of
home health referrals.
TABLE 4—HOME HEALTH STATISTICS, CY 2001 AND CY 2011 THROUGH CY 2015
2001
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2012
2013
2014
2015
3,896,502
6,821,459
6,727,875
6,708,923
6,451,283
6,340,932
2,412,318
34,899,167
3,449,231
37,686,526
3,446,122
38,224,640
3,484,579
38,505,609
3,381,635
38,506,534
3,365,512
38,592,533
0.11
0.18
0.18
0.17
0.17
0.16
6.9%
6,511
9.2%
11,446
9.0%
11,746
9.0%
11,889
8.8%
11,693
8.7%
11,381
1.9
Number of episodes .................................
Beneficiaries receiving at least 1 episode
(Home Health Users) ...........................
Part A and/or B FFS beneficiaries ...........
Episodes per Part A and/or B FFS beneficiaries .................................................
Home health users as a percentage of
Part A and/or B FFS beneficiaries .......
HHAs providing at least 1 episode ..........
HHAs per 10,000 Part A and/or B FFS
beneficiaries .........................................
2011
3.0
3.1
3.1
3.0
2.9
Source: National claims history (NCH) data obtained from Chronic Condition Warehouse (CCW)—Accessed on May 14, 2014 and August 19,
2014 for CY 2011, CY 2012, and CY 2013 data; accessed on May 7, 2015 for CY 2001 and CY 2014 data, and accessed on April 7, 2016 for
CY 2015 data Medicare enrollment information obtained from the CCW Master Beneficiary Summary File. Beneficiaries are the total number of
beneficiaries in a given year with at least 1 month of Part A and/or Part B Fee-for-Service coverage without having any months of Medicare Advantage coverage.
Note(s): These results include all episode types (Normal, PEP, Outlier, LUPA) and also include episodes from outlying areas (outside of 50
States and District of Columbia). Only episodes with a through date in the year specified are included. Episodes with a claim frequency code
equal to ‘‘0’’ (‘‘Non-payment/zero claims’’) and ‘‘2’’ (‘‘Interim—first claim’’) are excluded. If a beneficiary is treated by providers from multiple
states within a year the beneficiary is counted within each state’s unique number of beneficiaries served.
In addition to examining home health
claims data from the first 2 years of the
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implementation of rebasing adjustments
required by the Affordable Care Act and
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comparing utilization in those years (CY
2014 & CY 2015) to the 3 years prior to
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payments was implemented. As noted
in section II.C, we also implemented a
series of reductions to the national,
standardized 60-day episode payment
rate to account for increases in nominal
case-mix, starting in CY 2008. The
reductions to the 60-day episode rate
were: 2.75 percent each year for CY
2008, CY 2009, and CY 2010; 3.79
percent for CY 2011 and CY 2012; and
a 1.32 percent payment reduction for CY
2013. Figure 2 displays the average
number of visits by discipline type for
a 60-day episode of care and shows that
while the number of therapy visits per
60-day episode of care has increased
steadily, the number of skilled nursing
and home health aide visits have
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decreased, between CY 2009 and CY
2015. Section III.F describes the results
of the home health study required by
section 3131(d) of the Affordable Care
Act, which suggests that the current
home health payment system may
discourage HHAs from serving patients
with clinically complex and/or poorly
controlled chronic conditions who do
not qualify for therapy but require a
large number of skilled nursing visits.
The home health study results seem to
be consistent with the recent trend in
the decreased number of visits per
episode of care driven by decreases in
skilled nursing and home health aide
services evident in Figures 1 and 2.
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and to the first calendar year following
the implementation of the HH PPS (CY
2001), we subsequently examined
trends in home health utilization for all
years starting in CY 2001 and up
through CY 2015. Figure 1, displays the
average number of visits per 60-day
episode of care and the average payment
per visit. While the average payment per
visit has steadily increased from
approximately $116 in CY 2001 to $166
for CY 2015, the average total number of
visits per 60-day episode of care has
declined, most notably between CY
2009 (21.7 visits per episode) and CY
2010 (19.8 visits per episode), which
was the first year that the 10 percent
agency-level cap on HHA outlier
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As part of our monitoring efforts, we
also examined the trends in episode
timing and service use over time.
Currently, the first two 60-day episodes
of care are considered ‘‘early’’ and third
or later 60-day episodes of care are
considered ‘‘late’’, as long as there is no
more than a 60-day gap in care between
one episode and the next. Specifically,
we examined the percentage of early
episodes with 0 to 19 therapy visits, late
episodes with 0 to 19 therapy visits, and
episodes with 20+ therapy visits from
CY 2008 to CY 2015. In CY 2008, we
implemented refinements to the HH PPS
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case-mix system. As part of those
refinements, we added additional
therapy thresholds and differentiated
between early and late episodes for
those episodes with less than 20+
therapy visits. Table 5 shows that the
percentage of early and late episodes
from CY 2008 to CY 2015 has remained
relatively stable over time. There has
been a slight decrease in the percentage
of early episodes with 0 to 19 therapy
visits from 65.9 percent in CY 2008 to
59.8 percent in CY 2015 and a slight
increase in the percentage of late
episodes with 0 to 19 therapy visits
from 29.5 percent in CY 2008 to 33.5
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percent in CY 2015. From CY 2014 to
CY 2015, there was a slight decrease in
the percentage of early and late episodes
with 0 to 19 therapy visits and there was
a slight increase in the percentage of
episodes with 20+ therapy visits. In
2015, the case-mix weights for the third
and later episodes of care with 0 to 19
therapy visits decreased as a result of
the CY 2015 recalibration of the casemix weights. Despite the decreases in
the case-mix weights for the later
episodes, the percentage of later
episodes with 0 to 19 therapy visits did
not change substantially.
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43723
TABLE 5—HOME HEALTH EPISODES BY EPISODE TIMING, CY 2008 THROUGH CY 2015
Year
2008
2009
2010
2011
2012
2013
2014
2015
All episodes
.............................
.............................
.............................
.............................
.............................
.............................
.............................
.............................
Number of
early
episodes
(excluding
episodes with
20+ visits)
5,423,037
6,530,200
6,877,598
6,857,885
6,767,576
6,733,146
6,616,875
6,340,931
% of early episodes
(excluding episodes with
20+ visits)
Number of late
episodes
(excluding
episodes with
20+ visits)
65.9
56.7
56.3
57.1
58.4
59.8
60.2
59.8
1,600,587
2,456,308
2,586,493
2,564,859
2,458,734
2,347,420
2,263,638
2,123,485
3,571,619
3,701,652
3,872,504
3,912,982
3,955,207
4,023,486
3,980,151
3,789,676
% of late
episodes
(excluding
episodes with
20+ visits)
29.5
37.6
37.6
37.4
36.3
34.9
34.2
33.5
Number of
episodes with
20+ visits
250,831
372,240
418,601
380,044
353,635
362,240
373,086
427,770
% of episodes
with 20+ visits
4.6
5.7
6.1
5.5
5.2
5.4
5.6
6.7
Source: National claims history (NCH) data obtained from Chronic Condition Warehouse (CCW)—Accessed on April 7, 2016.
Note(s): Only episodes with a through date in the year specified are included. Episodes with a claim frequency code equal to ‘‘0’’ (‘‘Non-payment/zero claims’’) and ‘‘2’’ (‘‘Interim—first claim’’) are excluded.
sradovich on DSK3GDR082PROD with PROPOSALS2
We also examined trends in
admission source for home health
episodes over time. Specifically, we
examined the admission source for the
‘‘first or only’’ episodes of care (first
episodes in a sequence of adjacent
episodes of care or the only episode of
care) from CY 2008 through CY 2015
(Figure 3). The percentage of first or
only episodes with an acute admission
source, defined as episodes with an
inpatient hospital stay within the 14
days prior to a home health episode, has
decreased from 38.6 percent in CY 2008
to 33.9 percent in CY 2015. The
percentage of first or only episodes with
a post-acute admission source, defined
as episodes which had a stay at a skilled
nursing facility (SNF), inpatient
rehabilitation facility (IRF), or long term
care hospital (LTCH) within 14 days
prior to the home health episode,
slightly increased from 16.5 percent in
CY 2008 to 18.1 percent in CY 2015.
The percentage of first or only episodes
with a community admission source,
defined as episodes which did not have
an acute or post-acute stay in the 14
days prior to the home health episode,
increased from 37.4 percent in CY 2008
to 41.9 percent in CY 2015. Our findings
on the trends in admission source are
consistent to MedPAC’s as outlined in
their 2015 Report to the Congress.1
However, MedPAC examined admission
source trends from 2002 up through
2013 and concluded that ‘‘there has
been tremendous growth in the use of
home health for patients residing in the
community, episodes not preceded by a
prior hospitalization. The high rates of
volume growth for these types of
episodes, which have more than
doubled since 2001, suggest there is
significant potential for overuse,
particularly since Medicare does not
currently require any cost sharing for
home health care.’’
1 Medicare Payment Advisory Commission
(MedPAC), ‘‘Report to the Congress: Medicare
Payment Policy’’. March 2015. P. 214. Washington,
DC. Accessed on 4/21/2016 at https://medpac.gov/
documents/reports/march-2015-report-to-thecongress-medicare-payment-policy.pdf?sfvrsn=0.
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18:04 Jul 01, 2016
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Federal Register / Vol. 81, No. 128 / Tuesday, July 5, 2016 / Proposed Rules
We will continue to monitor for
potential impacts due to the rebasing
adjustments required by section 3131(a)
of the Affordable Care Act and other
policy changes in the future.
Independent effects of any one policy
may be difficult to discern in years
where multiple policy changes occur in
any given year.
sradovich on DSK3GDR082PROD with PROPOSALS2
B. Proposed CY 2017 HH PPS Case-Mix
Weights
In the CY 2015 HH PPS final rule (79
FR 66072), we finalized a policy to
annually recalibrate the HH PPS casemix weights—adjusting the weights
relative to one another—using the most
current, complete data available. To
recalibrate the HH PPS case-mix weights
for CY 2017, we will use the same
methodology finalized in the CY 2008
HH PPS final rule (72 FR 49762), the CY
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18:04 Jul 01, 2016
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2012 HH PPS final rule (76 FR 68526),
and the CY 2015 HH PPS final rule (79
FR 66032). Annual recalibration of the
HH PPS case-mix weights ensures that
the case-mix weights reflect, as
accurately as possible, current home
health resource use and changes in
utilization patterns.
To generate the proposed CY 2017 HH
PPS case-mix weights, we used CY 2015
home health claims data (as of
December 31, 2015) with linked OASIS
data. These data are the most current
and complete data available at this time.
We will use CY 2015 home health
claims data (as of June 30, 2016) with
linked OASIS data to generate the CY
2017 HH PPS case-mix weights in the
CY 2017 HH PPS final rule. The process
we used to calculate the HH PPS casemix weights are outlined below.
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Step 1: Re-estimate the four-equation
model to determine the clinical and
functional points for an episode using
wage-weighted minutes of care as our
dependent variable for resource use.
The wage-weighted minutes of care are
determined using the CY 2014 Bureau of
Labor Statistics national hourly wage
plus fringe rates for the six home health
disciplines and the minutes per visit
from the claim. The points for each of
the variables for each leg of the model,
updated with CY 2015 home health
claims data, are shown in Table 6. The
points for the clinical variables are
added together to determine an
episode’s clinical score. The points for
the functional variables are added
together to determine an episode’s
functional score.
BILLING CODE 4120–01–P
E:\FR\FM\05JYP2.SGM
05JYP2
EP05JY16.002</GPH>
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Federal Register / Vol. 81, No. 128 / Tuesday, July 5, 2016 / Proposed Rules
TABLE 6: Case-Mix Adjustment Variables and Scores
Therapy visits
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
sradovich on DSK3GDR082PROD with PROPOSALS2
16
17
VerDate Sep<11>2014
EQUATION:
CLINICAL DIMENSION
Primary or Other Diagnosis = Blindness/Low Vision
Primary or Other Diagnosis = Blood disorders
Primary or Other Diagnosis= Cancer, selected benign
neoplasms
Primary Diagnosis =Diabetes
Other Diagnosis =Diabetes
Primary or Other Diagnosis = Dysphagia
AND
Primary or Other Diagnosis= Neuro 3- Stroke
Primary or Other Diagnosis = Dysphagia
AND
M1030 (Therapy at home)= 3 (Enteral)
Primary or Other Diagnosis= Gastrointestinal disorders
Primary or Other Diagnosis= Gastrointestinal disorders
AND
M1630 (ostomy)= 1 or 2
Primary or Other Diagnosis= Gastrointestinal disorders
AND
Primary or Other Diagnosis= Neuro 1 -Brain disorders and
paralysis, OR Neuro 2 -Peripheral neurological disorders, OR
Neuro 3 - Stroke, OR Neuro 4 -Multiple Sclerosis
Primary or Other Diagnosis= Heart Disease OR Hypertension
Primary Diagnosis= Neuro 1 -Brain disorders and paralysis
Primary or Other Diagnosis= Neuro 1 -Brain disorders and
paralysis
AND
M1840 (Toilet transfer)= 2 or more
Primary or Other Diagnosis= Neuro 1 -Brain disorders and
paralysis OR Neuro 2 -Peripheral neurological disorders
AND
M1810 or M1820 (Dressing upper or lower body)= 1, 2, or 3
Primary or Other Diagnosis= Neuro 3 - Stroke
Primary or Other Diagnosis= Neuro 3 - Stroke AND
M1810 or M1820 (Dressing upper or lower body)= 1, 2, or 3
Primary or Other Diagnosis= Neuro 3 - Stroke
AND
M1860 (Ambulation) = 4 or more
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E:\FR\FM\05JYP2.SGM
05JYP2
1
or
2
013
I
1 or
2
14+
2
3+
013
3
3+
14+
4
5
3
5
2
2
18
12
1
3
5
3
12
7
4
2
10
9
4
1
3
EP05JY16.003</GPH>
Episode number within sequence of adjacent episodes
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Federal Register / Vol. 81, No. 128 / Tuesday, July 5, 2016 / Proposed Rules
Therapy visits
18
19
20
21
22
23
24
25
26
27
sradovich on DSK3GDR082PROD with PROPOSALS2
28
29
30
31
32
33
VerDate Sep<11>2014
1
or
2
013
EQUATION:
Primary or Other Diagnosis= Neuro 4 -Multiple Sclerosis
AND AT LEAST ONE OF THE FOLLOWING:
M1830 (Bathing)= 2 or more
OR
M1840 (Toilet transfer)= 2 or more
OR
M1850 (Transferring)= 2 or more
OR
M1860 (Ambulation) = 4 or more
Primary or Other Diagnosis= Ortho 1 -Leg Disorders or Gait
Disorders
AND
M1324 (most problematic pressure ulcer stage)= 1, 2, 3 or 4
Primary or Other Diagnosis = Ortho 1 - Leg OR Ortho 2 Other orthopedic disorders
AND
M1030 (Therapy at home)= 1 (IV/Infusion) or 2 (Parenteral)
Primary or Other Diagnosis = Psych 1 -Affective and other
psychoses, depression
Primary or Other Diagnosis = Psych 2 -Degenerative and
other organic psychiatric disorders
Primary or Other Diagnosis = Pulmonary disorders
Primary or Other Diagnosis= Pulmonary disorders AND
M1860 (Ambulation) = 1 or more
Primary Diagnosis = Skin 1 -Traumatic wounds, bums, and
post-operative complications
Other Diagnosis = Skin 1 - Traumatic wounds, bums, postoperative complications
Primary or Other Diagnosis = Skin 1 -Traumatic wounds,
bums, and post-operative complications OR Skin 2 - Ulcers
and other skin conditions
AND
M1030 (Therapy at home)= 1 (IV/Infusion) or 2 (Parenteral)
Primary or Other Diagnosis= Skin 2- Ulcers and other skin
conditions
Primary or Other Diagnosis = Tracheostomy
Primary or Other Diagnosis= Urostomy/Cystostomy
M1030 (Therapy at home)= 1 (IV/Infusion) or 2 (Parenteral)
M1030 (Therapy at home)= 3 (Enteral)
M1200 (Vision)= 1 or more
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E:\FR\FM\05JYP2.SGM
05JYP2
I
1 or
2
3+
3+
14+
013
14+
2
3
4
8
7
7
2
2
2
4
1
2
1
1
3
3
5
19
5
11
5
9
5
9
1
14
6
14
3
15
18
18
19
3
15
13
18
12
2
1
6
EP05JY16.004</GPH>
Episode number within sequence of adjacent episodes
sradovich on DSK3GDR082PROD with PROPOSALS2
BILLING CODE 4120–01–C
In updating the four-equation model
for CY 2017, using 2015 home health
claims data (the last update to the fourequation model for CY 2016 used CY
2014 home health claims data), there
were few changes to the point values for
the variables in the four-equation
model. These relatively minor changes
reflect the change in the relationship
between the grouper variables and
resource use between CY 2014 and CY
2015. The CY 2017 four-equation model
resulted in 110 point-giving variables
being used in the model (as compared
to the 124 variables for the CY 2016
recalibration). There were ten variables
that were added to the model and 24
variables that were dropped from the
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18:04 Jul 01, 2016
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model due to the absence of additional
resources associated with the variable.
Of the variables that were in both the
four-equation model for CY 2016 and
the four-equation model for CY 2017,
the points for 37 variables increased in
the CY 2017 four-equation model and
the points for 38 variables decreased in
the CY 2017 4-equation model. There
were 25 variables with the same point
values.
Step 2: Re-defining the clinical and
functional thresholds so they are
reflective of the new points associated
with the CY 2017 four-equation model.
After estimating the points for each of
the variables and summing the clinical
and functional points for each episode,
we look at the distribution of the
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43727
clinical score and functional score,
breaking the episodes into different
steps. The categorizations for the steps
are as follows:
• Step 1: First and second episodes,
0–13 therapy visits.
• Step 2.1: First and second episodes,
14–19 therapy visits.
• Step 2.2: Third episodes and
beyond, 14–19 therapy visits.
• Step 3: Third episodes and beyond,
0–13 therapy visits.
• Step 4: Episodes with 20+ therapy
visits.
We then divide the distribution of the
clinical score for episodes within a step
such that a third of episodes are
classified as low clinical score, a third
of episodes are classified as medium
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05JYP2
EP05JY16.005</GPH>
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Federal Register / Vol. 81, No. 128 / Tuesday, July 5, 2016 / Proposed Rules
clinical score, and a third of episodes
are classified as high clinical score. The
same approach is then done looking at
the functional score. It was not always
possible to evenly divide the episodes
within each step into thirds due to
many episodes being clustered around
one particular score.2 Also, we looked at
the average resource use associated with
each clinical and functional score and
used that as a guide for setting our
thresholds. We grouped scores with
similar average resource use within the
same level (even if it meant that more
or less than a third of episodes were
placed within a level). The new
thresholds, based off of the CY 2017
four-equation model points are shown
in Table 7.
TABLE 7—CY 2017 CLINICAL AND FUNCTIONAL THRESHOLDS
1st and 2nd Episodes
3rd+ Episodes
All episodes
0 to 13
therapy visits
Grouping Step: ......................................................
Equation(s) used to calculate points: (see Table
6).
Dimension
Functional ................................
C1
C2
C3
F1
F2
F3
............
............
............
............
............
............
Step 3: Once the clinical and
functional thresholds are determined
and each episode is assigned a clinical
and functional level, the payment
regression is estimated with an
episode’s wage-weighted minutes of
care as the dependent variable.
Independent variables in the model are
indicators for the step of the episode as
well as the clinical and functional levels
within each step of the episode. Like the
four-equation model, the payment
regression model is also estimated with
robust standard errors that are clustered
at the beneficiary level. Table 8 shows
the regression coefficients for the
variables in the payment regression
model updated with CY 2015 home
health claims data. The R-squared value
for the payment regression model is
0.4919 (an increase from 0.4822 for the
CY 2016 recalibration).
TABLE 8—PAYMENT REGRESSION
MODEL
sradovich on DSK3GDR082PROD with PROPOSALS2
Step 1, Clinical Score Medium ..................................
Step 1, Clinical Score High ..
Step 1, Functional Score Medium ..................................
Step 1, Functional Score
High ...................................
New payment
regression
coefficients
$25.75
60.84
71.60
108.83
2 For Step 1, 62% of episodes were in the medium
functional level (All with score 14).
For Step 2.1, 71.0% of episodes were in the low
functional level (Most with score 6).
VerDate Sep<11>2014
18:04 Jul 01, 2016
0 to 13
therapy visits
14 to 19
therapy visits
20+ therapy
visits
1 .......................
1 .......................
2.1 ....................
2 .......................
3 .......................
3 .......................
2.2 ....................
4 .......................
4.
(2&4).
0 to 1 ................
2 to 3 ................
4+ .....................
0 to 13 ..............
14 .....................
15+ ...................
0 to 1 ................
2 to 7 ................
8+ .....................
0 to 7 ................
8 to 13 ..............
14+ ...................
0 .......................
1 .......................
2+ .....................
0 to 6 ................
7 to 10 ..............
11+ ...................
0 to 1 ................
2 to 9 ................
10+ ...................
0 .......................
1 to 11 ..............
12+ ...................
0 to 3.
4 to 17.
18+.
0 to 2.
3 to 6.
7+.
Severity ....
level.
Clinical .....................................
Variable description
14 to 19
therapy visits
Jkt 238001
TABLE 8—PAYMENT REGRESSION
MODEL—Continued
Variable description
Step 2.1, Clinical Score Medium ..................................
Step 2.1, Clinical Score High
Step 2.1, Functional Score
Medium .............................
Step 2.1, Functional Score
High ...................................
Step 2.2, Clinical Score Medium ..................................
Step 2.2, Clinical Score High
Step 2.2, Functional Score
Medium .............................
Step 2.2, Functional Score
High ...................................
Step 3, Clinical Score Medium ..................................
Step 3, Clinical Score High ..
Step 3, Functional Score Medium ..................................
Step 3, Functional Score
High ...................................
Step 4, Clinical Score Medium ..................................
Step 4, Clinical Score High ..
Step 4, Functional Score Medium ..................................
Step 4, Functional Score
High ...................................
Step 2.1, 1st and 2nd Episodes, 14 to 19 Therapy
Visits ..................................
Step 2.2, 3rd+ Episodes, 14
to 19 Therapy Visits ..........
New payment
regression
coefficients
53.35
129.94
11.54
67.03
33.94
188.53
0.31
63.34
9.35
95.01
56.44
88.01
76.63
261.74
22.89
73.10
498.19
515.73
For Step 2.2, 83.2% of episodes were in the
medium functional level (Most with score 2 or 3).
For Step 3, 51.3% of episodes were in the
medium functional level (Most with score 10).
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TABLE 8—PAYMENT REGRESSION
MODEL—Continued
Variable description
Step 3, 3rd+ Episodes, 0–13
Therapy Visits ...................
Step 4, All Episodes, 20+
Therapy Visits ...................
Intercept ................................
New payment
regression
coefficients
¥73.96
906.64
393.43
Source: CY 2015 Medicare claims data for
episodes ending on or before December 31,
2015 (as of December 31, 2015) for which we
had a linked OASIS assessment.
Step 4: We use the coefficients from
the payment regression model to predict
each episode’s wage-weighted minutes
of care (resource use). We then divide
these predicted values by the mean of
the dependent variable (that is, the
average wage-weighted minutes of care
across all episodes used in the payment
regression). This division constructs the
weight for each episode, which is
simply the ratio of the episode’s
predicted wage-weighted minutes of
care divided by the average wageweighted minutes of care in the sample.
Each episode is then aggregated into one
of the 153 home health resource groups
(HHRGs) and the ‘‘raw’’ weight for each
HHRG was calculated as the average of
the episode weights within the HHRG.
Step 5: The raw weights associated
with 0 to 5 therapy visits are then
For Step 4, 54.4% of episodes were in the
medium functional level (Most with score 6).
E:\FR\FM\05JYP2.SGM
05JYP2
Federal Register / Vol. 81, No. 128 / Tuesday, July 5, 2016 / Proposed Rules
increased by 3.75 percent, the weights
associated with 14–15 therapy visits are
decreased by 2.5 percent, and the
weights associated with 20+ therapy
visits are decreased by 5 percent. These
adjustments to the case-mix weights
were finalized in the CY 2012 HH PPS
final rule (76 FR 68557) and were done
to address MedPAC’s concerns that the
HH PPS overvalues therapy episodes
and undervalues non-therapy episodes
and to better align the case-mix weights
with episode costs estimated from cost
report data.3
Step 6: After the adjustments in step
5 are applied to the raw weights, the
weights are further adjusted to create an
increase in the payment weights for the
therapy visit steps between the therapy
thresholds. Weights with the same
clinical severity level, functional
severity level, and early/later episode
status were grouped together. Then
within those groups, the weights for
each therapy step between thresholds
are gradually increased. We do this by
interpolating between the main
thresholds on the model (from 0–5 to
14–15 therapy visits, and from 14–15 to
20+ therapy visits). We use a linear
model to implement the interpolation so
43729
the payment weight increase for each
step between the thresholds (such as the
increase between 0–5 therapy visits and
6 therapy visits and the increase
between 6 therapy visits and 7–9
therapy visits) are constant. This
interpolation is identical to the process
finalized in the CY 2012 HH PPS final
rule (76 FR 68555).
Step 7: The interpolated weights are
then adjusted so that the average casemix for the weights is equal to 1.0000.4
This last step creates the proposed CY
2017 case-mix weights shown in
Table 9.
TABLE 9—PROPOSED CY 2017 CASE-MIX PAYMENT WEIGHTS
Step
(episode and/or therapy visit ranges)
sradovich on DSK3GDR082PROD with PROPOSALS2
Payment group
10111
10112
10113
10114
10115
10121
10122
10123
10124
10125
10131
10132
10133
10134
10135
10211
10212
10213
10214
10215
10221
10222
10223
10224
10225
10231
10232
10233
10234
10235
10311
10312
10313
10314
10315
10321
10322
10323
10324
10325
10331
10332
10333
10334
10335
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
1st
1st
1st
1st
1st
1st
1st
1st
1st
1st
1st
1st
1st
1st
1st
1st
1st
1st
1st
1st
1st
1st
1st
1st
1st
1st
1st
1st
1st
1st
1st
1st
1st
1st
1st
1st
1st
1st
1st
1st
1st
1st
1st
1st
1st
and
and
and
and
and
and
and
and
and
and
and
and
and
and
and
and
and
and
and
and
and
and
and
and
and
and
and
and
and
and
and
and
and
and
and
and
and
and
and
and
and
and
and
and
and
2nd
2nd
2nd
2nd
2nd
2nd
2nd
2nd
2nd
2nd
2nd
2nd
2nd
2nd
2nd
2nd
2nd
2nd
2nd
2nd
2nd
2nd
2nd
2nd
2nd
2nd
2nd
2nd
2nd
2nd
2nd
2nd
2nd
2nd
2nd
2nd
2nd
2nd
2nd
2nd
2nd
2nd
2nd
2nd
2nd
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
3 Medicare Payment Advisory Commission
(MedPAC), Report to the Congress: Medicare
Payment Policy. March 2011, P. 176.
VerDate Sep<11>2014
Clinical and
functional
levels
(1 = low;
2 = medium;
3 = high)
18:04 Jul 01, 2016
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0 to 5 Therapy Visits ...........................................................................
6 Therapy Visits ..................................................................................
7 to 9 Therapy Visits ...........................................................................
10 Therapy Visits ................................................................................
11 to 13 Therapy Visits .......................................................................
0 to 5 Therapy Visits ...........................................................................
6 Therapy Visits ..................................................................................
7 to 9 Therapy Visits ...........................................................................
10 Therapy Visits ................................................................................
11 to 13 Therapy Visits .......................................................................
0 to 5 Therapy Visits ...........................................................................
6 Therapy Visits ..................................................................................
7 to 9 Therapy Visits ...........................................................................
10 Therapy Visits ................................................................................
11 to 13 Therapy Visits .......................................................................
0 to 5 Therapy Visits ...........................................................................
6 Therapy Visits ..................................................................................
7 to 9 Therapy Visits ...........................................................................
10 Therapy Visits ................................................................................
11 to 13 Therapy Visits .......................................................................
0 to 5 Therapy Visits ...........................................................................
6 Therapy Visits ..................................................................................
7 to 9 Therapy Visits ...........................................................................
10 Therapy Visits ................................................................................
11 to 13 Therapy Visits .......................................................................
0 to 5 Therapy Visits ...........................................................................
6 Therapy Visits ..................................................................................
7 to 9 Therapy Visits ...........................................................................
10 Therapy Visits ................................................................................
11 to 13 Therapy Visits .......................................................................
0 to 5 Therapy Visits ...........................................................................
6 Therapy Visits ..................................................................................
7 to 9 Therapy Visits ...........................................................................
10 Therapy Visits ................................................................................
11 to 13 Therapy Visits .......................................................................
0 to 5 Therapy Visits ...........................................................................
6 Therapy Visits ..................................................................................
7 to 9 Therapy Visits ...........................................................................
10 Therapy Visits ................................................................................
11 to 13 Therapy Visits .......................................................................
0 to 5 Therapy Visits ...........................................................................
6 Therapy Visits ..................................................................................
7 to 9 Therapy Visits ...........................................................................
10 Therapy Visits ................................................................................
11 to 13 Therapy Visits .......................................................................
4 When computing the average, we compute a
weighted average, assigning a value of one to each
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C1F1S1
C1F1S2
C1F1S3
C1F1S4
C1F1S5
C1F2S1
C1F2S2
C1F2S3
C1F2S4
C1F2S5
C1F3S1
C1F3S2
C1F3S3
C1F3S4
C1F3S5
C2F1S1
C2F1S2
C2F1S3
C2F1S4
C2F1S5
C2F2S1
C2F2S2
C2F2S3
C2F2S4
C2F2S5
C2F3S1
C2F3S2
C2F3S3
C2F3S4
C2F3S5
C3F1S1
C3F1S2
C3F1S3
C3F1S4
C3F1S5
C3F2S1
C3F2S2
C3F2S3
C3F2S4
C3F2S5
C3F3S1
C3F3S2
C3F3S3
C3F3S4
C3F3S5
Proposed CY
2017 weights
0.5972
0.7322
0.8671
1.0021
1.1370
0.7059
0.8224
0.9389
1.0554
1.1719
0.7624
0.8835
1.0045
1.1255
1.2466
0.6363
0.7787
0.9210
1.0634
1.2057
0.7450
0.8689
0.9928
1.1167
1.2406
0.8015
0.9300
1.0584
1.1868
1.3153
0.6896
0.8431
0.9967
1.1502
1.3038
0.7983
0.9334
1.0685
1.2036
1.3387
0.8548
0.9944
1.1341
1.2737
1.4133
normal episode and a value equal to the episode
length divided by 60 for PEPs.
E:\FR\FM\05JYP2.SGM
05JYP2
43730
Federal Register / Vol. 81, No. 128 / Tuesday, July 5, 2016 / Proposed Rules
TABLE 9—PROPOSED CY 2017 CASE-MIX PAYMENT WEIGHTS—Continued
Step
(episode and/or therapy visit ranges)
sradovich on DSK3GDR082PROD with PROPOSALS2
Payment group
21111
21112
21113
21121
21122
21123
21131
21132
21133
21211
21212
21213
21221
21222
21223
21231
21232
21233
21311
21312
21313
21321
21322
21323
21331
21332
21333
22111
22112
22113
22121
22122
22123
22131
22132
22133
22211
22212
22213
22221
22222
22223
22231
22232
22233
22311
22312
22313
22321
22322
22323
22331
22332
22333
30111
30112
30113
30114
30115
30121
30122
30123
30124
30125
30131
30132
30133
30134
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
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................
................
................
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................
................
................
................
................
................
................
................
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................
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................
................
................
................
................
................
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VerDate Sep<11>2014
Clinical and
functional
levels
(1 = low;
2 = medium;
3 = high)
1st and 2nd Episodes, 14 to 15 Therapy Visits .......................................................................
1st and 2nd Episodes, 16 to 17 Therapy Visits .......................................................................
1st and 2nd Episodes, 18 to 19 Therapy Visits .......................................................................
1st and 2nd Episodes, 14 to 15 Therapy Visits .......................................................................
1st and 2nd Episodes, 16 to 17 Therapy Visits .......................................................................
1st and 2nd Episodes, 18 to 19 Therapy Visits .......................................................................
1st and 2nd Episodes, 14 to 15 Therapy Visits .......................................................................
1st and 2nd Episodes, 16 to 17 Therapy Visits .......................................................................
1st and 2nd Episodes, 18 to 19 Therapy Visits .......................................................................
1st and 2nd Episodes, 14 to 15 Therapy Visits .......................................................................
1st and 2nd Episodes, 16 to 17 Therapy Visits .......................................................................
1st and 2nd Episodes, 18 to 19 Therapy Visits .......................................................................
1st and 2nd Episodes, 14 to 15 Therapy Visits .......................................................................
1st and 2nd Episodes, 16 to 17 Therapy Visits .......................................................................
1st and 2nd Episodes, 18 to 19 Therapy Visits .......................................................................
1st and 2nd Episodes, 14 to 15 Therapy Visits .......................................................................
1st and 2nd Episodes, 16 to 17 Therapy Visits .......................................................................
1st and 2nd Episodes, 18 to 19 Therapy Visits .......................................................................
1st and 2nd Episodes, 14 to 15 Therapy Visits .......................................................................
1st and 2nd Episodes, 16 to 17 Therapy Visits .......................................................................
1st and 2nd Episodes, 18 to 19 Therapy Visits .......................................................................
1st and 2nd Episodes, 14 to 15 Therapy Visits .......................................................................
1st and 2nd Episodes, 16 to 17 Therapy Visits .......................................................................
1st and 2nd Episodes, 18 to 19 Therapy Visits .......................................................................
1st and 2nd Episodes, 14 to 15 Therapy Visits .......................................................................
1st and 2nd Episodes, 16 to 17 Therapy Visits .......................................................................
1st and 2nd Episodes, 18 to 19 Therapy Visits .......................................................................
3rd+ Episodes, 14 to 15 Therapy Visits ..................................................................................
3rd+ Episodes, 16 to 17 Therapy Visits ..................................................................................
3rd+ Episodes, 18 to 19 Therapy Visits ..................................................................................
3rd+ Episodes, 14 to 15 Therapy Visits ..................................................................................
3rd+ Episodes, 16 to 17 Therapy Visits ..................................................................................
3rd+ Episodes, 18 to 19 Therapy Visits ..................................................................................
3rd+ Episodes, 14 to 15 Therapy Visits ..................................................................................
3rd+ Episodes, 16 to 17 Therapy Visits ..................................................................................
3rd+ Episodes, 18 to 19 Therapy Visits ..................................................................................
3rd+ Episodes, 14 to 15 Therapy Visits ..................................................................................
3rd+ Episodes, 16 to 17 Therapy Visits ..................................................................................
3rd+ Episodes, 18 to 19 Therapy Visits ..................................................................................
3rd+ Episodes, 14 to 15 Therapy Visits ..................................................................................
3rd+ Episodes, 16 to 17 Therapy Visits ..................................................................................
3rd+ Episodes, 18 to 19 Therapy Visits ..................................................................................
3rd+ Episodes, 14 to 15 Therapy Visits ..................................................................................
3rd+ Episodes, 16 to 17 Therapy Visits ..................................................................................
3rd+ Episodes, 18 to 19 Therapy Visits ..................................................................................
3rd+ Episodes, 14 to 15 Therapy Visits ..................................................................................
3rd+ Episodes, 16 to 17 Therapy Visits ..................................................................................
3rd+ Episodes, 18 to 19 Therapy Visits ..................................................................................
3rd+ Episodes, 14 to 15 Therapy Visits ..................................................................................
3rd+ Episodes, 16 to 17 Therapy Visits ..................................................................................
3rd+ Episodes, 18 to 19 Therapy Visits ..................................................................................
3rd+ Episodes, 14 to 15 Therapy Visits ..................................................................................
3rd+ Episodes, 16 to 17 Therapy Visits ..................................................................................
3rd+ Episodes, 18 to 19 Therapy Visits ..................................................................................
3rd+ Episodes, 0 to 5 Therapy Visits ......................................................................................
3rd+ Episodes, 6 Therapy Visits ..............................................................................................
3rd+ Episodes, 7 to 9 Therapy Visits ......................................................................................
3rd+ Episodes, 10 Therapy Visits ............................................................................................
3rd+ Episodes, 11 to 13 Therapy Visits ..................................................................................
3rd+ Episodes, 0 to 5 Therapy Visits ......................................................................................
3rd+ Episodes, 6 Therapy Visits ..............................................................................................
3rd+ Episodes, 7 to 9 Therapy Visits ......................................................................................
3rd+ Episodes, 10 Therapy Visits ............................................................................................
3rd+ Episodes, 11 to 13 Therapy Visits ..................................................................................
3rd+ Episodes, 0 to 5 Therapy Visits ......................................................................................
3rd+ Episodes, 6 Therapy Visits ..............................................................................................
3rd+ Episodes, 7 to 9 Therapy Visits ......................................................................................
3rd+ Episodes, 10 Therapy Visits ............................................................................................
18:04 Jul 01, 2016
Jkt 238001
PO 00000
Frm 00018
Fmt 4701
Sfmt 4702
E:\FR\FM\05JYP2.SGM
05JYP2
C1F1S1
C1F1S2
C1F1S3
C1F2S1
C1F2S2
C1F2S3
C1F3S1
C1F3S2
C1F3S3
C2F1S1
C2F1S2
C2F1S3
C2F2S1
C2F2S2
C2F2S3
C2F3S1
C2F3S2
C2F3S3
C3F1S1
C3F1S2
C3F1S3
C3F2S1
C3F2S2
C3F2S3
C3F3S1
C3F3S2
C3F3S3
C1F1S1
C1F1S2
C1F1S3
C1F2S1
C1F2S2
C1F2S3
C1F3S1
C1F3S2
C1F3S3
C2F1S1
C2F1S2
C2F1S3
C2F2S1
C2F2S2
C2F2S3
C2F3S1
C2F3S2
C2F3S3
C3F1S1
C3F1S2
C3F1S3
C3F2S1
C3F2S2
C3F2S3
C3F3S1
C3F3S2
C3F3S3
C1F1S1
C1F1S2
C1F1S3
C1F1S4
C1F1S5
C1F2S1
C1F2S2
C1F2S3
C1F2S4
C1F2S5
C1F3S1
C1F3S2
C1F3S3
C1F3S4
Proposed CY
2017 weights
1.2720
1.4503
1.6287
1.2884
1.4719
1.6554
1.3676
1.5480
1.7283
1.3481
1.5366
1.7251
1.3645
1.5582
1.7518
1.4437
1.6342
1.8247
1.4573
1.6952
1.9330
1.4738
1.7168
1.9597
1.5530
1.7928
2.0326
1.2970
1.4670
1.6370
1.2974
1.4779
1.6584
1.3873
1.5611
1.7349
1.3454
1.5348
1.7242
1.3458
1.5457
1.7455
1.4358
1.6289
1.8220
1.5659
1.7676
1.9692
1.5664
1.7785
1.9906
1.6563
1.8617
2.0671
0.4850
0.6474
0.8098
0.9722
1.1346
0.5706
0.7160
0.8614
1.0067
1.1521
0.6186
0.7723
0.9261
1.0798
Federal Register / Vol. 81, No. 128 / Tuesday, July 5, 2016 / Proposed Rules
43731
TABLE 9—PROPOSED CY 2017 CASE-MIX PAYMENT WEIGHTS—Continued
Step
(episode and/or therapy visit ranges)
Payment group
sradovich on DSK3GDR082PROD with PROPOSALS2
30135
30211
30212
30213
30214
30215
30221
30222
30223
30224
30225
30231
30232
30233
30234
30235
30311
30312
30313
30314
30315
30321
30322
30323
30324
30325
30331
30332
30333
30334
30335
40111
40121
40131
40211
40221
40231
40311
40321
40331
................
................
................
................
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................
................
3rd+ Episodes, 11 to 13 Therapy Visits ..................................................................................
3rd+ Episodes, 0 to 5 Therapy Visits ......................................................................................
3rd+ Episodes, 6 Therapy Visits ..............................................................................................
3rd+ Episodes, 7 to 9 Therapy Visits ......................................................................................
3rd+ Episodes, 10 Therapy Visits ............................................................................................
3rd+ Episodes, 11 to 13 Therapy Visits ..................................................................................
3rd+ Episodes, 0 to 5 Therapy Visits ......................................................................................
3rd+ Episodes, 6 Therapy Visits ..............................................................................................
3rd+ Episodes, 7 to 9 Therapy Visits ......................................................................................
3rd+ Episodes, 10 Therapy Visits ............................................................................................
3rd+ Episodes, 11 to 13 Therapy Visits ..................................................................................
3rd+ Episodes, 0 to 5 Therapy Visits ......................................................................................
3rd+ Episodes, 6 Therapy Visits ..............................................................................................
3rd+ Episodes, 7 to 9 Therapy Visits ......................................................................................
3rd+ Episodes, 10 Therapy Visits ............................................................................................
3rd+ Episodes, 11 to 13 Therapy Visits ..................................................................................
3rd+ Episodes, 0 to 5 Therapy Visits ......................................................................................
3rd+ Episodes, 6 Therapy Visits ..............................................................................................
3rd+ Episodes, 7 to 9 Therapy Visits ......................................................................................
3rd+ Episodes, 10 Therapy Visits ............................................................................................
3rd+ Episodes, 11 to 13 Therapy Visits ..................................................................................
3rd+ Episodes, 0 to 5 Therapy Visits ......................................................................................
3rd+ Episodes, 6 Therapy Visits ..............................................................................................
3rd+ Episodes, 7 to 9 Therapy Visits ......................................................................................
3rd+ Episodes, 10 Therapy Visits ............................................................................................
3rd+ Episodes, 11 to 13 Therapy Visits ..................................................................................
3rd+ Episodes, 0 to 5 Therapy Visits ......................................................................................
3rd+ Episodes, 6 Therapy Visits ..............................................................................................
3rd+ Episodes, 7 to 9 Therapy Visits ......................................................................................
3rd+ Episodes, 10 Therapy Visits ............................................................................................
3rd+ Episodes, 11 to 13 Therapy Visits ..................................................................................
All Episodes, 20+ Therapy Visits .............................................................................................
All Episodes, 20+ Therapy Visits .............................................................................................
All Episodes, 20+ Therapy Visits .............................................................................................
All Episodes, 20+ Therapy Visits .............................................................................................
All Episodes, 20+ Therapy Visits .............................................................................................
All Episodes, 20+ Therapy Visits .............................................................................................
All Episodes, 20+ Therapy Visits .............................................................................................
All Episodes, 20+ Therapy Visits .............................................................................................
All Episodes, 20+ Therapy Visits .............................................................................................
To ensure the changes to the HH PPS
case-mix weights are implemented in a
budget neutral manner, we then apply a
case-mix budget neutrality factor to the
proposed CY 2017 national,
standardized 60-day episode payment
rate (see section III.C.3. of this proposed
rule). The case-mix budget neutrality
factor is calculated as the ratio of total
payments when the CY 2017 HH PPS
case-mix weights (developed using CY
2015 home health claims data) are
applied to CY 2015 utilization (claims)
data to total payments when CY 2016
HH PPS case-mix weights (developed
using CY 2014 home health claims data)
are applied to CY 2015 utilization data.
This produces a case-mix budget
neutrality factor for CY 2017 of 1.0062,
based on CY 2015 claims data as of
December 31, 2015.
VerDate Sep<11>2014
Clinical and
functional
levels
(1 = low;
2 = medium;
3 = high)
18:04 Jul 01, 2016
Jkt 238001
C. Proposed CY 2017 Home Health
Payment Rate Update
1. Proposed CY 2017 Home Health
Market Basket Update
Section 1895(b)(3)(B) of the Act
requires that the standard prospective
payment amounts for CY 2017 be
increased by a factor equal to the
applicable HH market basket update for
those HHAs that submit quality data as
required by the Secretary. The home
health market basket was rebased and
revised in CY 2013. A detailed
description of how we derive the HHA
market basket is available in the CY
2013 HH PPS final rule (77 FR 67080–
67090).
Section 3401(e) of the Affordable Care
Act, adding new section
1895(b)(3)(B)(vi) to the Act, requires
that, in CY 2015 (and in subsequent
PO 00000
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C1F3S5
C2F1S1
C2F1S2
C2F1S3
C2F1S4
C2F1S5
C2F2S1
C2F2S2
C2F2S3
C2F2S4
C2F2S5
C2F3S1
C2F3S2
C2F3S3
C2F3S4
C2F3S5
C3F1S1
C3F1S2
C3F1S3
C3F1S4
C3F1S5
C3F2S1
C3F2S2
C3F2S3
C3F2S4
C3F2S5
C3F3S1
C3F3S2
C3F3S3
C3F3S4
C3F3S5
C1F1S1
C1F2S1
C1F3S1
C2F1S1
C2F2S1
C2F3S1
C3F1S1
C3F2S1
C3F3S1
Proposed CY
2017 weights
1.2336
0.4992
0.6684
0.8377
1.0069
1.1761
0.5848
0.7370
0.8892
1.0414
1.1936
0.6328
0.7934
0.9540
1.1146
1.2752
0.6292
0.8165
1.0039
1.1912
1.3786
0.7149
0.8852
1.0555
1.2258
1.3961
0.7628
0.9415
1.1202
1.2989
1.4776
1.8071
1.8389
1.9087
1.9136
1.9454
2.0152
2.1709
2.2027
2.2725
calendar years), the market basket
percentage under the HHA prospective
payment system as described in section
1895(b)(3)(B) of the Act be annually
adjusted by changes in economy-wide
productivity. The statute defines the
productivity adjustment, described in
section 1886(b)(3)(B)(xi)(II) of the Act, to
be equal to the 10-year moving average
of change in annual economy-wide
private nonfarm business multifactor
productivity (MFP) (as projected by the
Secretary for the 10-year period ending
with the applicable fiscal year, calendar
year, cost reporting period, or other
annual period) (the ‘‘MFP adjustment’’).
The Bureau of Labor Statistics (BLS) is
the agency that publishes the official
measure of private nonfarm business
MFP. Please see https://www.bls.gov/mfp
to obtain the BLS historical published
MFP data.
E:\FR\FM\05JYP2.SGM
05JYP2
43732
Federal Register / Vol. 81, No. 128 / Tuesday, July 5, 2016 / Proposed Rules
Using IHS Global Insight’s (IGI) first
quarter 2016 forecast, the MFP
adjustment for CY 2017 (the 10-year
moving average of MFP for the period
ending CY 2017) is projected to be 0.5
percent. Thus, in accordance with
section 1895(b)(3)(B)(iii) of the Act, we
propose to base the CY 2017 market
basket update, which is used to
determine the applicable percentage
increase for the HH payments, on the
most recent estimate of the proposed
2010-based HH market basket (currently
estimated to be 2.8 percent based on
IGI’s first quarter 2016 forecast). We
propose to then reduce this percentage
increase by the current estimate of the
MFP adjustment for CY 2017 of 0.5
percentage point (the 10-year moving
average of MFP for the period ending
CY 2017 based on IGI’s first quarter
2016 forecast), in accordance with
1895(b)(3)(B)(vi). Therefore, the current
estimate of the CY 2017 HH payment
update is 2.3 percent (2.8 percent
market basket update, less 0.5
percentage point MFP adjustment).
Furthermore, we note that if more recent
data are subsequently available (for
example, a more recent estimate of the
market basket and MFP adjustment), we
would use such data to determine the
CY 2017 market basket update and MFP
adjustment in the final rule.
Section 1895(b)(3)(B) of the Act
requires that the home health update be
decreased by 2 percentage points for
those HHAs that do not submit quality
data as required by the Secretary. For
HHAs that do not submit the required
quality data for CY 2017, the home
health payment update would be 0.3
percent (2.3 percent minus 2 percentage
points).
sradovich on DSK3GDR082PROD with PROPOSALS2
2. Proposed CY 2017 Home Health Wage
Index
a. Background
Sections 1895(b)(4)(A)(ii) and (b)(4)(C)
of the Act require the Secretary to
provide appropriate adjustments to the
proportion of the payment amount
under the HH PPS that account for area
wage differences, using adjustment
factors that reflect the relative level of
wages and wage-related costs applicable
to the furnishing of HH services. Since
the inception of the HH PPS, we have
used inpatient hospital wage data in
developing a wage index to be applied
to HH payments. We propose to
continue this practice for CY 2017, as
we continue to believe that, in the
absence of HH-specific wage data, using
inpatient hospital wage data is
appropriate and reasonable for the HH
PPS. Specifically, we propose to
continue to use the pre-floor, pre-
VerDate Sep<11>2014
18:04 Jul 01, 2016
Jkt 238001
reclassified hospital wage index as the
wage adjustment to the labor portion of
the HH PPS rates. For CY 2017, the
updated wage data are for hospital cost
reporting periods beginning on or after
October 1, 2012 and before October 1,
2013 (FY 2013 cost report data). We
would apply the appropriate wage index
value to the labor portion of the HH PPS
rates based on the site of service for the
beneficiary (defined by section 1861(m)
of the Act as the beneficiary’s place of
residence).
b. Updates
Previously, we determined each
HHA’s labor market area based on
definitions of metropolitan statistical
areas (MSAs) issued by the Office of
Management and Budget (OMB). In the
CY 2006 HH PPS final rule (70 FR
68132), we adopted revised labor market
area definitions as discussed in the
OMB Bulletin No. 03–04 (June 6, 2003).
This bulletin announced revised
definitions for MSAs and the creation of
micropolitan statistical areas and corebased statistical areas (CBSAs). The
bulletin is available online at
www.whitehouse.gov/omb/bulletins/
b03-04.html.
On February 28, 2013, OMB issued
Bulletin No. 13–01, announcing
revisions to the delineations of MSAs,
Micropolitan Statistical Areas, and
CBSAs, and guidance on uses of the
delineation of these areas. This bulletin
is available online at https://
www.whitehouse.gov/sites/default/files/
omb/bulletins/2013/b-13-01.pdf. This
bulletin states that it ‘‘provides the
delineations of all Metropolitan
Statistical Areas, Metropolitan
Divisions, Micropolitan Statistical
Areas, Combined Statistical Areas, and
New England City and Town Areas in
the United States and Puerto Rico based
on the standards published on June 28,
2010, in the Federal Register (75 FR
37246–37252) and Census Bureau data.’’
While the revisions OMB published
on February 28, 2013 are not as
sweeping as the changes made when we
adopted the CBSA geographic
designations for CY 2006, the February
28, 2013 bulletin does contain a number
of significant changes. For example,
there are new CBSAs, urban counties
that have become rural, rural counties
that have become urban, and existing
CBSAs that have been split apart.
In the CY 2015 HH PPS final rule (79
FR 66085 through 66087), we finalized
changes to the HH PPS wage index
based on the OMB delineations, as
described in OMB Bulletin No. 13–01.
In CY 2015, we included a one-year
transition to those delineations by using
a blended wage index for CY 2015.
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Fmt 4701
Sfmt 4702
The OMB’s most recent update to the
geographic area delineations was
published on July 15, 2015 in OBM
bulletin 15–01. This bulletin is available
online at https://www.whitehouse.gov/
sites/default/files/omb/bulletins/2015/
15-01.pdf. The revisions to the
delineations that affect the HH PPS are
changes to CBSA titles and the addition
of CBSA 21420, Enid, Oklahoma. CBSA
21420 encompasses Garfield County,
Oklahoma.
In order to address those geographic
areas in which there are no inpatient
hospitals, and thus, no hospital wage
data on which to base the calculation of
the CY 2017 HH PPS wage index, we
propose to continue to use the same
methodology discussed in the CY 2007
HH PPS final rule (71 FR 65884) to
address those geographic areas in which
there are no inpatient hospitals. For
rural areas that do not have inpatient
hospitals, we would use the average
wage index from all contiguous CBSAs
as a reasonable proxy. For FY 2017,
there are no rural geographic areas
without hospitals for which we would
apply this policy. For rural Puerto Rico,
we would not apply this methodology
due to the distinct economic
circumstances that exist there (for
example, due to the close proximity to
one another of almost all of Puerto
Rico’s various urban and non-urban
areas, this methodology would produce
a wage index for rural Puerto Rico that
is higher than that in half of its urban
areas). Instead, we would continue to
use the most recent wage index
previously available for that area. For
urban areas without inpatient hospitals,
we would use the average wage index of
all urban areas within the state as a
reasonable proxy for the wage index
for that CBSA. For CY 2017, the only
urban area without inpatient hospital
wage data is Hinesville, GA (CBSA
25980).
The proposed CY 2017 wage index is
available on the CMS Web site at https://
www.cms.gov/Medicare/Medicare-Feefor-Service-Payment/HomeHealthPPS/
Home-Health-Prospective-PaymentSystem-Regulations-and-Notices.html
3. Proposed CY 2017 Annual Payment
Update
a. Background
The Medicare HH PPS has been in
effect since October 1, 2000. As set forth
in the July 3, 2000 final rule (65 FR
41128), the base unit of payment under
the Medicare HH PPS is a national,
standardized 60-day episode payment
rate. As set forth in 42 CFR 484.220, we
adjust the national, standardized 60-day
episode payment rate by a case-mix
E:\FR\FM\05JYP2.SGM
05JYP2
sradovich on DSK3GDR082PROD with PROPOSALS2
Federal Register / Vol. 81, No. 128 / Tuesday, July 5, 2016 / Proposed Rules
relative weight and a wage index value
based on the site of service for the
beneficiary.
To provide appropriate adjustments to
the proportion of the payment amount
under the HH PPS to account for area
wage differences, we apply the
appropriate wage index value to the
labor portion of the HH PPS rates. The
labor-related share of the case-mix
adjusted 60-day episode rate would
continue to be 78.535 percent and the
non-labor-related share would continue
to be 21.465 percent as set out in the CY
2013 HH PPS final rule (77 FR 67068).
The CY 2017 HH PPS rates would use
the same case-mix methodology as set
forth in the CY 2008 HH PPS final rule
with comment period (72 FR 49762) and
would be adjusted as described in
section III.C. of this rule. The following
are the steps we take to compute the
case-mix and wage-adjusted 60-day
episode rate:
(1) Multiply the national 60-day
episode rate by the patient’s applicable
case-mix weight.
(2) Divide the case-mix adjusted
amount into a labor (78.535 percent)
and a non-labor portion (21.465
percent).
(3) Multiply the labor portion by the
applicable wage index based on the site
of service of the beneficiary.
(4) Add the wage-adjusted portion to
the non-labor portion, yielding the casemix and wage adjusted 60-day episode
rate, subject to any additional applicable
adjustments.
In accordance with section
1895(b)(3)(B) of the Act, this document
constitutes the annual update of the HH
PPS rates. Section 484.225 sets forth the
specific annual percentage update
methodology. In accordance with
§ 484.225(i), for a HHA that does not
submit HH quality data, as specified by
the Secretary, the unadjusted national
prospective 60-day episode rate is equal
to the rate for the previous calendar year
increased by the applicable HH market
basket index amount minus two
percentage points. Any reduction of the
percentage change would apply only to
the calendar year involved and would
not be considered in computing the
prospective payment amount for a
subsequent calendar year.
Medicare pays the national,
standardized 60-day case-mix and wage-
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adjusted episode payment on a split
percentage payment approach. The split
percentage payment approach includes
an initial percentage payment and a
final percentage payment as set forth in
§ 484.205(b)(1) and (b)(2). We may base
the initial percentage payment on the
submission of a request for anticipated
payment (RAP) and the final percentage
payment on the submission of the claim
for the episode, as discussed in § 409.43.
The claim for the episode that the HHA
submits for the final percentage
payment determines the total payment
amount for the episode and whether we
make an applicable adjustment to the
60-day case-mix and wage-adjusted
episode payment. The end date of the
60-day episode as reported on the
claim determines which calendar year
rates Medicare would use to pay the
claim.
We may also adjust the 60-day casemix and wage-adjusted episode
payment based on the information
submitted on the claim to reflect the
following:
• A low-utilization payment
adjustment (LUPA) is provided on a pervisit basis as set forth in § 484.205(c)
and § 484.230.
• A partial episode payment (PEP)
adjustment as set forth in § 484.205(d)
and § 484.235.
• An outlier payment as set forth in
§ 484.205(e) and § 484.240.
b. Proposed CY 2017 National,
Standardized 60-Day Episode Payment
Rate
Section 1895(3)(A)(i) of the Act
required that the 60-day episode base
rate and other applicable amounts be
standardized in a manner that
eliminates the effects of variations in
relative case mix and area wage
adjustments among different home
health agencies in a budget neutral
manner. To determine the CY 2017
national, standardized 60-day episode
payment rate, we would apply a wage
index standardization factor, a case-mix
budget neutrality factor described in
section III.B, a reduction of 0.97 percent
to account for nominal case-mix growth
from 2012 to 2014 as finalized in the CY
2016 HH PPS final rule (80 FR 68646),
the rebasing adjustment described in
section II.C, and the MFP-adjusted
home health market basket update
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43733
discussed in section III.C.1 of this
proposed rule.
To calculate the wage index
standardization factor, henceforth
referred to as the wage index budget
neutrality factor, we simulated total
payments for non-LUPA episodes using
the proposed CY 2017 wage index and
compared it to our simulation of total
payments for non-LUPA episodes using
the CY 2016 wage index. By dividing
the total payments for non-LUPA
episodes using the proposed CY 2017
wage index by the total payments for
non-LUPA episodes using the CY 2016
wage index, we obtain a wage index
budget neutrality factor of 0.9990. We
would apply the wage index budget
neutrality factor of 0.9990 to the
proposed CY 2017 national,
standardized 60-day episode rate.
As discussed in section III.B of this
proposed rule, to ensure the changes to
the case-mix weights are implemented
in a budget neutral manner, we would
apply a case-mix weight budget
neutrality factor to the CY 2017
national, standardized 60-day episode
payment rate. The case-mix weight
budget neutrality factor is calculated as
the ratio of total payments when CY
2017 case-mix weights are applied to CY
2015 utilization (claims) data to total
payments when CY 2016 case-mix
weights are applied to CY 2015
utilization data. The case-mix budget
neutrality factor for CY 2017 would be
1.0062 as described in section III.B.1 of
this proposed rule.
Next, as discussed in the CY 2016 HH
PPS final rule (80 FR 68646), we would
apply a reduction of 0.97 percent to the
national, standardized 60-day episode
payment rate in CY 2017 to account for
nominal case-mix growth between CY
2012 and CY 2014. Then, we would
apply the ¥$80.95 rebasing adjustment
finalized in the CY 2014 HH PPS final
rule (78 FR 72256), and discussed in
section II.C. Lastly, we would update
the proposed payment rates by the
proposed CY 2017 HH payment update
percentage of 2.3 percent (MFP-adjusted
home health market basket update) as
described in section III.C.1 of this
proposed rule. The proposed CY 2017
national, standardized 60-day episode
payment rate is calculated in Table 10.
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Federal Register / Vol. 81, No. 128 / Tuesday, July 5, 2016 / Proposed Rules
TABLE 10—PROPOSED CY 2017 60-DAY NATIONAL, STANDARDIZED 60-DAY EPISODE PAYMENT AMOUNT
CY 2016 National, standardized 60-day
episode payment
Wage index
budget
neutrality
factor
Case-mix
weights
budget
neutrality
factor
Nominal casemix growth
adjustment
(1–0.0097)
CY 2017
Rebasing
adjustment
Proposed CY
2017 HH
payment
update
Proposed CY
2017 national,
standardized
60-day
episode
payment
$2,965.12 .................................................
× 0.9990
× 1.0062
× 0.9903
¥$80.95
1.023
$2,936.68
The proposed CY 2017 national,
standardized 60-day episode payment
rate for an HHA that does not submit the
required quality data is updated by the
proposed CY 2017 HH payment update
(2.3 percent) minus 2 percentage points
and is shown in Table 11.
TABLE 11—PROPOSED CY 2017 NATIONAL, STANDARDIZED 60-DAY EPISODE PAYMENT AMOUNT FOR HHAS THAT DO
NOT SUBMIT THE QUALITY DATA
CY 2016 National, standardized 60-day
episode payment
Wage index
budget
neutrality
factor
Case-mix
weights
budget
neutrality
factor
$2,965.12 .................................................
× 0.9990
× 1.0062
CY 2017
Rebasing
adjustment
× 0.9903
c. Proposed CY 2017 National Per-Visit
Rates
The national per-visit rates are used to
pay LUPAs (episodes with four or fewer
visits) and are also used to compute
imputed costs in outlier calculations.
The per-visit rates are paid by type of
visit or HH discipline. The six HH
disciplines are as follows:
• Home health aide (HH aide);
• Medical Social Services (MSS);
• Occupational therapy (OT);
• Physical therapy (PT);
• Skilled nursing (SN); and
• Speech-language pathology (SLP).
To calculate the proposed CY 2017
national per-visit rates, we start with the
CY 2016 national per-visit rates. We
then apply a wage index budget
neutrality factor to ensure budget
neutrality for LUPA per-visit payments
and then we increase each of the six
per-visit rates by the maximum rebasing
adjustments described in section II.C. of
this rule. We calculate the wage index
budget neutrality factor by simulating
total payments for LUPA episodes using
the proposed CY 2017 wage index and
comparing it to simulated total
payments for LUPA episodes using the
CY 2016 wage index. By dividing the
total payments for LUPA episodes using
the proposed CY 2017 wage index by
the total payments for LUPA episodes
using the CY 2016 wage index, we
obtain a wage index budget neutrality
factor of 0.9998. We would apply the
wage index budget neutrality factor of
0.9998 in order to calculate the CY 2017
national per-visit rates.
Proposed CY
2017 HH
payment
update minus
2
percentage
points
Proposed CY
2017 national,
standardized
60-day
episode
payment
¥$80.95
Nominal casemix growth
adjustment
(1–0.0097)
× 1.003
$2,879.27
The LUPA per-visit rates are not
calculated using case-mix weights.
Therefore, there is no case-mix weights
budget neutrality factor needed to
ensure budget neutrality for LUPA
payments. Finally, the per-visit rates for
each discipline are updated by the
proposed CY 2017 HH payment update
percentage of 2.3 percent. The national
per-visit rates are adjusted by the wage
index based on the site of service of the
beneficiary. The per-visit payments for
LUPAs are separate from the LUPA addon payment amount, which is paid for
episodes that occur as the only episode
or initial episode in a sequence of
adjacent episodes. The proposed CY
2017 national per-visit rates are shown
in Tables 12 and 13.
TABLE 12: PROPOSED CY 2017 NATIONAL PER-VISIT PAYMENT AMOUNTS FOR HHAS THAT DO SUBMIT THE REQUIRED
QUALITY DATA
sradovich on DSK3GDR082PROD with PROPOSALS2
Home Health Aide ...........................................................
Medical Social Services ...................................................
Occupational Therapy ......................................................
Physical Therapy .............................................................
Skilled Nursing .................................................................
Speech Language Pathology ..........................................
The proposed CY 2017 per-visit
payment rates for an HHA that does not
submit the required quality data are
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Wage index
budget
neutrality
factor
CY 2016 pervisit payment
HH Discipline type
$60.87
215.47
147.95
146.95
134.42
159.71
×
×
×
×
×
×
0.9998
0.9998
0.9998
0.9998
0.9998
0.9998
..........
..........
..........
..........
..........
..........
updated by the proposed CY 2017 HH
payment update percentage (2.3
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Proposed CY
2017 HH
payment
update
CY 2017
Rebasing
adjustment
+
+
+
+
+
+
$1.79 ...........
6.34 .............
4.35 .............
4.32 ............
3.96 .............
4.70 .............
×
×
×
×
×
×
1.023
1.023
1.023
1.023
1.023
1.023
............
............
............
............
............
............
Proposed CY
2017 per-visit
payment
$64.09
226.87
155.77
154.72
141.54
168.16
percent) minus 2 percentage points and
is shown in Table 13.
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Federal Register / Vol. 81, No. 128 / Tuesday, July 5, 2016 / Proposed Rules
TABLE 13—PROPOSED CY 2017 NATIONAL PER-VISIT PAYMENT AMOUNTS FOR HHAS THAT DO NOT SUBMIT THE
REQUIRED QUALITY DATA
CY 2016 pervisit rates
HH Discipline type
Home Health Aide ................................................................
Medical Social Services .......................................................
Occupational Therapy ..........................................................
Physical Therapy .................................................................
Skilled Nursing .....................................................................
Speech Language Pathology ...............................................
d. Low-Utilization Payment Adjustment
(LUPA) Add-On Factors
LUPA episodes that occur as the only
episode or as an initial episode in a
sequence of adjacent episodes are
adjusted by applying an additional
amount to the LUPA payment before
adjusting for area wage differences. In
the CY 2014 HH PPS final rule, we
changed the methodology for
calculating the LUPA add-on amount by
finalizing the use of three LUPA add-on
factors: 1.8451 for SN; 1.6700 for PT;
and 1.6266 for SLP (78 FR 72306). We
multiply the per-visit payment amount
for the first SN, PT, or SLP visit in
LUPA episodes that occur as the only
Wage index
budget
neutrality
factor
$60.87
215.47
147.95
146.95
134.42
159.71
×
×
×
×
×
×
CY 2017
Rebasing
adjustment
0.9998
0.9998
0.9998
0.9998
0.9998
0.9998
+ $1.79
+ 6.34
+ 4.35
+ 4.32
+ 3.96
+ 4.70
Proposed CY
2017 HH
payment update minus 2
percentage
points
×
×
×
×
×
×
1.003
1.003
1.003
1.003
1.003
1.003
Proposed CY
2017 per-visit
rates
$62.84
222.43
152.73
151.69
138.77
164.87
conversion factor. To determine the
proposed CY 2017 NRS conversion
factor, we start with the CY 2016 NRS
conversion factor ($52.71) and apply the
¥2.82 percent rebasing adjustment
described in section II.C. of this rule
(1—0.0282 = 0.9718). We then update
the conversion factor by the proposed
CY 2017 HH payment update percentage
(2.3 percent). We do not apply a
standardization factor as the NRS
payment amount calculated from the
conversion factor is not wage or casemix adjusted when the final claim
payment amount is computed. The
proposed NRS conversion factor for CY
2017 is shown in Table 14.
episode or an initial episode in a
sequence of adjacent episodes by the
appropriate factor to determine the
LUPA add-on payment amount. For
example, for LUPA episodes that occur
as the only episode or an initial episode
in a sequence of adjacent episodes, if
the first skilled visit is SN, the payment
for that visit would be $261.16 (1.8451
multiplied by $141.54), subject to area
wage adjustment.
e. Proposed CY 2017 Non-routine
Medical Supply (NRS) Payment Rates
Payments for NRS are computed by
multiplying the relative weight for a
particular severity level by the NRS
TABLE 14—PROPOSED CY 2017 NRS CONVERSION FACTOR FOR HHAS THAT DO SUBMIT THE REQUIRED QUALITY DATA
CY 2016 NRS conversion factor
CY 2017
Rebasing
adjustment
Proposed CY
2017 HH
payment
update
Proposed CY
2017 NRS
conversion
factor
$52.71 ..........................................................................................................................................
× 0.9718
× 1.023
$52.40
Using the CY 2015 NRS conversion
factor, the payment amounts for the six
severity levels are shown in Table 15.
TABLE 15—PROPOSED CY 2017 NRS PAYMENT AMOUNTS FOR HHAS THAT DO SUBMIT THE REQUIRED QUALITY DATA
Points
(scoring)
Severity level
sradovich on DSK3GDR082PROD with PROPOSALS2
1
2
3
4
5
6
...................................................................................................................................................
...................................................................................................................................................
...................................................................................................................................................
...................................................................................................................................................
...................................................................................................................................................
...................................................................................................................................................
For HHAs that do not submit the
required quality data, we begin with the
CY 2016 NRS conversion factor ($52.71)
and apply the ¥2.82 percent rebasing
adjustment discussed in section II.C of
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0 .....................
1 to 14 ...........
15 to 27 .........
28 to 48 .........
49 to 98 .........
99+ .................
this proposed rule (1–0.0282 = 0.9718).
We then update the NRS conversion
factor by the proposed CY 2017 HH
payment update percentage (2.3
percent) minus 2 percentage points. The
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Relative
weight
0.2698
0.9742
2.6712
3.9686
6.1198
10.5254
Proposed CY
2017 NRS
payment
amounts
$14.14
51.05
139.97
207.95
320.68
551.53
proposed CY 2017 NRS conversion
factor for HHAs that do not submit
quality data is shown in Table 16.
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Federal Register / Vol. 81, No. 128 / Tuesday, July 5, 2016 / Proposed Rules
TABLE 16—PROPOSED CY 2017 NRS CONVERSION FACTOR FOR HHAS THAT DO NOT SUBMIT THE REQUIRED QUALITY
DATA
CY 2015 NRS Conversion factor
CY 2017
Rebasing
adjustment
Proposed
CY 2017 HH
payment
update
percentage
minus 2
percentage
Points
$52.71 ..........................................................................................................................................
× 0.9718
× 1.003
The payment amounts for the various
severity levels based on the updated
conversion factor for HHAs that do not
Proposed
CY 2017 NRS
conversion
factor
$51.38
submit quality data are calculated in
Table 17.
TABLE 17—PROPOSED CY 2017 NRS PAYMENT AMOUNTS FOR HHAS THAT DO NOT SUBMIT THE REQUIRED QUALITY
DATA
Points
(scoring)
Severity level
1
2
3
4
5
6
...................................................................................................................................................
...................................................................................................................................................
...................................................................................................................................................
...................................................................................................................................................
...................................................................................................................................................
...................................................................................................................................................
f. Rural Add-On
Section 421(a) of the MMA required,
for HH services furnished in a rural
areas (as defined in section
1886(d)(2)(D) of the Act), for episodes or
visits ending on or after April 1, 2004,
and before April 1, 2005, that the
Secretary increase the payment amount
that otherwise would have been made
under section 1895 of the Act for the
services by 5 percent.
Section 5201 of the DRA amended
section 421(a) of the MMA. The
amended section 421(a) of the MMA
required, for HH services furnished in a
rural area (as defined in section
1886(d)(2)(D) of the Act), on or after
January 1, 2006 and before January 1,
2007, that the Secretary increase the
payment amount otherwise made under
section 1895 of the Act for those
services by 5 percent.
0 .....................
1 to 14 ...........
15 to 27 .........
28 to 48 .........
49 to 98 .........
99+ .................
Section 3131(c) of the Affordable Care
Act amended section 421(a) of the MMA
to provide an increase of 3 percent of
the payment amount otherwise made
under section 1895 of the Act for HH
services furnished in a rural area (as
defined in section 1886(d)(2)(D) of the
Act), for episodes and visits ending on
or after April 1, 2010, and before
January 1, 2016.
Section 210 of the Medicare Access
and CHIP Reauthorization Act of 2015
(MACRA) (Public Law 114–10)
amended section 421(a) of the MMA to
extend the rural add-on by providing an
increase of 3 percent of the payment
amount otherwise made under section
1895 of the Act for HH services
provided in a rural area (as defined in
section 1886(d)(2)(D) of the Act), for
episodes and visits ending before
January 1, 2018.
Relative
weight
0.2698
0.9742
2.6712
3.9686
6.1198
10.5254
Proposed
CY 2017
NRS payment
amounts
$13.86
50.05
137.25
203.91
314.44
540.80
Section 421 of the MMA, as amended,
waives budget neutrality related to this
provision, as the statute specifically
states that the Secretary shall not reduce
the standard prospective payment
amount (or amounts) under section 1895
of the Act applicable to HH services
furnished during a period to offset the
increase in payments resulting in the
application of this section of the statute.
For CY 2017, home health payment
rates for services provided to
beneficiaries in areas that are defined as
rural under the OMB delineations
would be increased by 3 percent as
mandated by section 210 of the
MACRA. The 3 percent rural add-on is
applied to the national, standardized 60day episode payment rate, national per
visit rates, and NRS conversion factor
when HH services are provided in rural
(non-CBSA) areas. Refer to Tables 18
through 21 for these payment rates.
TABLE 18—PROPOSED CY 2017 PAYMENT AMOUNTS FOR 60-DAY EPISODES FOR SERVICES PROVIDED IN A RURAL AREA
sradovich on DSK3GDR082PROD with PROPOSALS2
For HHAs that DO submit quality data
For HHAs that DO NOT submit quality data
Proposed CY 2017 national, standardized 60-day episode
payment rate
Multiply by the
3 percent rural
add-on
$2,936.68 .............................................................................
Proposed CY
2017 rural
national,
standardized
60-day
episode
payment rate
× 1.03
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$3,024.78
Sfmt 4702
Proposed CY
2017 national,
standardized
60-day
episode
payment rate
$2,879.27
E:\FR\FM\05JYP2.SGM
05JYP2
Multiply by the
3 percent rural
add-on
× 1.03
Proposed CY
2017 rural
national,
standardized
60-day
episode
payment rate
$2,965.65
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Federal Register / Vol. 81, No. 128 / Tuesday, July 5, 2016 / Proposed Rules
TABLE 19—PROPOSED CY 2017 PER-VISIT AMOUNTS FOR SERVICES PROVIDED IN A RURAL AREA
For HHAs that DO submit quality data
HH Discipline
type
Multiply by the 3
percent rural addon
Proposed CY 2017
per-visit rate
HH Aide ............
MSS ..................
OT .....................
PT .....................
SN .....................
SLP ...................
×
×
×
×
×
×
$64.09
226.87
155.77
154.72
141.54
168.16
For HHAs that DO NOT submit quality data
Proposed CY 2017
rural per-visit rates
Proposed CY 2017
per-visit rate
$66.01
233.68
160.44
159.36
145.79
173.20
Multiply by the 3
percent rural addon
$62.84
222.43
152.73
151.69
138.77
164.87
1.03
1.03
1.03
1.03
1.03
1.03
×
×
×
×
×
×
Proposed CY 2017
rural per-visit rates
1.03
1.03
1.03
1.03
1.03
1.03
$64.73
229.10
157.31
156.24
142.93
169.82
TABLE 20—PROPOSED CY 2017 NRS CONVERSION FACTORS FOR SERVICES PROVIDED IN A RURAL AREA
For HHAs that DO submit quality data
For HHAs that DO NOT submit quality
data
Proposed
CY 2017 conversion factor
Multiply by
the 3
percent
rural
add-on
$52.40 ......................................................................................................
Proposed
CY 2017
rural NRS
conversion
factor
× 1.03
Proposed
CY 2017
conversion
factor
$53.97
$51.38
Multiply by
the 3
percent
rural
add-on
Proposed
CY 2017
rural NRS
conversion
factor
× 1.03
$52.92
TABLE 21—PROPOSED CY 2017 NRS PAYMENT AMOUNTS FOR SERVICES PROVIDED IN A RURAL AREA
For HHAs that DO submit
quality data
Severity level
1
2
3
4
5
6
Points (scoring)
........................................................
........................................................
........................................................
........................................................
........................................................
........................................................
0 ........................................................
1 to 14 ..............................................
15 to 27 ............................................
28 to 48 ............................................
49 to 98 ............................................
99+ ....................................................
D. Payments for High-Cost Outliers
Under the HH PPS
sradovich on DSK3GDR082PROD with PROPOSALS2
1. Background
Section 1895(b)(5) of the Act allows
for the provision of an addition or
adjustment to the national, standardized
60-day case-mix and wage-adjusted
episode payment amounts in the case of
episodes that incur unusually high costs
due to patient care needs. Prior to the
enactment of the Affordable Care Act,
section 1895(b)(5) of the Act stipulated
that projected total outlier payments
could not exceed 5 percent of total
projected or estimated HH payments in
a given year. In the July 3, 2000
Medicare Program; Prospective Payment
System for Home Health Agencies final
rule (65 FR 41188 through 41190), we
described the method for determining
outlier payments. Under this system,
outlier payments are made for episodes
whose estimated costs exceed a
threshold amount for each Home Health
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Relative
weight
Jkt 238001
0.2698
0.9742
2.6712
3.9686
6.1198
10.5254
Resource Group (HHRG). The episode’s
estimated cost is the sum of the national
wage-adjusted per-visit payment
amounts for all visits delivered during
the episode. The outlier threshold for
each case-mix group or Partial Episode
Payment (PEP) adjustment is defined as
the 60-day episode payment or PEP
adjustment for that group plus a fixeddollar loss (FDL) amount. The outlier
payment is defined to be a proportion of
the wage-adjusted estimated cost
beyond the wage-adjusted threshold.
The threshold amount is the sum of the
wage and case-mix adjusted PPS
episode amount and wage-adjusted FDL
amount. The proportion of additional
costs over the outlier threshold amount
paid as outlier payments is referred to
as the loss-sharing ratio.
In the CY 2010 HH PPS proposed rule
(74 FR 40948), we stated that outlier
payments increased as a percentage of
total payments from 4.1 percent in CY
2005, to 5.0 percent in CY 2006, to 6.4
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Proposed CY
2017
NRS payment
amounts for
rural areas
$14.56
52.58
144.16
214.19
330.29
568.06
For HHAs that DO NOT submit
quality data
Relative
weight
0.2698
0.9742
2.6712
3.9686
6.1198
10.5254
Proposed CY
2017
NRS payment
amounts for
rural areas
$14.28
51.55
141.36
210.02
323.86
557.00
percent in CY 2007 and that this
excessive growth in outlier payments
was primarily the result of unusually
high outlier payments in a few areas of
the country. In that discussion, we
noted that despite program integrity
efforts associated with excessive outlier
payments in targeted areas of the
country, we discovered that outlier
expenditures still exceeded the 5
percent target in CY 2007 and, in the
absence of corrective measures, would
continue do to so. Consequently, we
assessed the appropriateness of taking
action to curb outlier abuse. As
described in the HH PPS final rule (74
FR 58080 through 58087), to mitigate
possible billing vulnerabilities
associated with excessive outlier
payments and adhere to our statutory
limit on outlier payments, we finalized
an outlier policy that included a 10
percent agency-level cap on outlier
payments. This cap was implemented in
concert with a reduced FDL ratio of
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sradovich on DSK3GDR082PROD with PROPOSALS2
0.67. These policies resulted in a
projected target outlier pool of
approximately 2.5 percent. (The
previous outlier pool was 5 percent of
total home health expenditures). For CY
2010, we first returned the 5 percent
held for the previous target outlier pool
to the national, standardized 60-day
episode rates, the national per-visit
rates, the LUPA add-on payment
amount, and the NRS conversion factor.
Then, we reduced the CY 2010 rates by
2.5 percent to account for the new
outlier pool of 2.5 percent. This outlier
policy was adopted for CY 2010 only.
As we noted in the CY 2011 HH PPS
final rule (75 FR 70397 through 70399),
section 3131(b)(1) of the Affordable Care
Act amended section 1895(b)(3)(C) of
the Act, and required the Secretary to
reduce the HH PPS payment rates such
that aggregate HH PPS payments were
reduced by 5 percent. In addition,
section 3131(b)(2) of the Affordable Care
Act amended section 1895(b)(5) of the
Act by re-designating the existing
language as section 1895(b)(5)(A) of the
Act, and revising the language to state
that the total amount of the additional
payments or payment adjustments for
outlier episodes may not exceed 2.5
percent of the estimated total HH PPS
payments for that year. Section
3131(b)(2)(C) of the Affordable Care Act
also added subparagraph (B) which
capped outlier payments as a percent of
total payments for each HHA at 10
percent.
As such, beginning in CY 2011, our
HH PPS outlier policy is that we reduce
payment rates by 5 percent and target
up to 2.5 percent of total estimated HH
PPS payments to be paid as outliers. To
do so, we first returned the 2.5 percent
held for the target CY 2010 outlier pool
to the national, standardized 60-day
episode rates, the national per visit
rates, the LUPA add-on payment
amount, and the NRS conversion factor
for CY 2010. We then reduced the rates
by 5 percent as required by section
1895(b)(3)(C) of the Act, as amended by
section 3131(b)(1) of the Affordable Care
Act. For CY 2011 and subsequent
calendar years we target up to 2.5
percent of estimated total payments to
be paid as outlier payments, and apply
a 10 percent agency-level outlier cap.
2. Proposed Changes to the
Methodology Used To Estimate Episode
Cost
As stated earlier, an episode’s
estimated cost is determined by
multiplying the national wage-adjusted
per-visit payment amounts by discipline
by the number of visits by discipline
reported on the home health claim. An
episode’s estimated cost is then used to
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determine whether an episode will
receive an outlier payment and the
amount of the outlier payment. Analysis
of CY 2015 home health claims data
indicates that there is significant
variation in the visit length by
discipline for outlier episodes. Those
agencies with 10 percent of their total
payments as outlier payments are
providing shorter but more frequent
skilled nursing visits than agencies with
less than 10 percent of their total
payments as outlier payments (see Table
22).
TABLE 22—AVERAGE NUMBER AND
LENGTH OF SKILLED NURSING VISITS
BY THE PERCENTAGE OF OUTLIER
PAYMENTS TO TOTAL PAYMENTS AT
THE
AGENCY LEVEL (CURRENT
OUTLIER METHODOLOGY), CY 2015
Avg. # of
skilled
nursing
visits
<1% Total
Outlier Payments ............
1% to <5% Total
Outlier Payments ............
5% to <10%
Total Outlier
Payments ......
10% Total
Outlier Payments ............
Avg.
minutes
per skilled
nursing visit
21.7
47.2
26.7
44.0
26.7
44.3
44.5
35.6
Source: CY 2015 home health claims data
from the standard analytic file (as of December 31, 2015) for which we had a linked
OASIS assessment.
Note(s): These results are based on simulations using CY 2015 utilization and the
CY2017 payment parameters.
As shown in Table 23, the number of
skilled nursing visits is significantly
higher than the number of visits for the
five other disciplines of care and
therefore, outlier payments are
predominately driven by the provision
of skilled nursing services.
TABLE 23—AVERAGE NUMBER OF VISITS BY DISCIPLINE FOR OUTLIER EPISODES
Discipline
Speech-language pathology .....
Average
number of
visits
0.7
Source: CY 2015 home health claims data
from the standard analytic file (as of December 31, 2015) for which we had a linked
OASIS assessment.
Note(s): These results are based on simulations using CY 2015 utilization and the
CY2017 payment parameters.
As a result of the analysis of CY 2015
home health claims data, we are
concerned the current methodology for
calculating outlier payments may create
a financial disincentive for providers to
treat medically complex beneficiaries
who require longer visits. The home
health environment differs from
hospitals and other institutional
environments. In the home setting, the
patient has a greater role in determining
how, when, and even if, certain
interventions will be implemented.
Individual skill, cognitive and
functional ability, and financial
resources affect the ability of home
health patients to safely manage their
health care needs, interventions, and
medication regimens.5 Clinically
complex patients generally use more
health services, have functional
limitations, need more assistance to
perform activities of daily living (ADLs),
require social support and community
resources, and require more complex
medical interventions.6 For example,
patients using home total parenteral
nutrition (TPN) must cope with very
high-tech needs at home and because of
the complexity of TPN therapy, a high
level of knowledge and expertise is
required in the clinical management of
these patients.7 In addition to the direct
patient care needs, patient education
aims at instruction on the care of the
central venous access device,
administration procedures and
monitoring for complications, overall
well-being, parenteral nutrition
composition and frequency, test results,
medications, practical and psychosocial
5 Ibid.
Average
number of
visits
Discipline
Home health aide .....................
Medical social services .............
Occupational therapy ................
Physical therapy .......................
Skilled nursing ..........................
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8.8
0.3
2.3
5.1
34.0
6 Rich, E., Lipson, D., Libersky, J., Parchman, M.
(2012). Coordinating Care for Adults with Complex
Care Needs in the Patient-Centered Medical Home:
Challenges and Solutions. AHRQ Publication No.
12–0010, https://pcmh.ahrq.gov/page/coordinatingcare-adults-complex-care-needs-patient-centeredmedical-home-challenges-and.
7 Huisman-deWaal, G. Achterberg, T., Jansen, J.,
Wanten, G., Schoonhoven, L. (2010). ‘‘High-tech’’
home care: Overview of professional care in
patients on home parenteral nutrition and
implications for nursing care. Journal of Clinical
Nursing. (20), 2125–2134.
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issues.8 Visit frequency for home TPN
patients varies and length of nursing
visits can range from 15 minutes for
infusion site and catheter assessment to
10 hours for direct patient care.9 For
those patients who require assistance
with bathing, research has shown older
persons are more likely to have negative
expectations regarding the inevitability
of further physical decline after they
experience bathing difficulties.10 As
older home health patients decline, they
may be more likely to accept assistance
with bathing and this may have the
unintended consequence of reliance on
bathing assistance, which could lead to
further functional decline in the
performance of other ADLs. To mitigate
further functional decline, home health
nursing intensity and visit time
increases as home nursing interventions
are targeted to work with patients and
caregivers on bathing sub-tasks,
assistance in modifying the home
environment through the acquisition
and use of adaptive equipment and
devising strategies to support patients in
dealing with pain and fatigue that could
prevent independent bathing.11
Higher nursing visit intensity and
longer visits are a generally a response
to instability of the patient’s condition,
and/or inability to effectively and safely
manage their condition and self-care
activities; therefore, more clinically
complex, frail, elderly patients will
require more intensive and frequent
home health surveillance, increased
home health care utilization, and
costs.12 13
In addition to the clinical information
described above, Mathematica Policy
Research published a report in 2010
titled ‘‘Home Health Independence
Patients: High Use, but Not Financial
Outliers.’’ 14 In this report, Mathematica
described their analysis of the
relationships among the proxy
demonstration target group for the
Home Health Independence
Demonstration, patients who receive
outlier payments, and the agencies that
serve them. As part of their research,
Mathematica examined the degree of
overlap between the proxy
demonstration target group, who are ill,
permanently disabled beneficiaries, and
those beneficiaries receiving outlier
payments. The study found that ‘‘Only
a small fraction of proxy demonstration
patients generate outlier payments and
that differences between the proxy
demonstration and outlier patient
groups examined in this study suggest
that outlier payments are not generally
being used to serve the types of
severely, permanently disabled
beneficiaries that were addressed by the
demonstration concept.’’
Therefore, we are proposing to change
the methodology used to calculate
outlier payments, using a cost-per-unit
approach rather than a cost-per-visit
approach. Using this approach, we
would convert the national per-visit
rates in section III.C.3. into per 15
minute unit rates (see Table 24). The
new per-unit rates by discipline would
then be used, along with the visit length
data by discipline reported on the home
health claim in 15 minute increments
(15 minutes = 1 unit), to calculate the
estimated cost of an episode to
determine whether the claim will
receive an outlier payment and the
amount of payment for an episode of
care. We note that this change in the
methodology would be budget neutral
as we would still target to pay out 2.5
percent of total payments as outlier
payments in accordance with section
1895(b)(5)(A) of the Act, which requires
us to pay up to, but no more than, 2.5
percent of total HH PPS payments as
outlier payments.
TABLE 24—PROPOSED COST-PER-UNIT PAYMENT RATES FOR THE CALCULATION OF OUTLIER PAYMENTS
Proposed CY
2017 national
per-visit
payment rates
Visit type
Home health aide ........................................................................................................................
Medical social services ................................................................................................................
Occupational therapy ...................................................................................................................
Physical therapy ..........................................................................................................................
Skilled nursing .............................................................................................................................
Speech-language pathology ........................................................................................................
$64.09
226.87
155.77
154.72
141.54
168.16
Average
minutesper-visit
62.2
56.4
47.1
46.6
44.7
48.1
Cost-per-unit
(1 unit = 15
minutes)
$15.46
60.34
49.61
49.80
47.50
52.44
SOURCE: CY 2015 home health claims data from the standard analytic file (as of December 31, 2015) for which we had a linked OASIS assessment.
NOTE(S): Excludes LUPAs.
sradovich on DSK3GDR082PROD with PROPOSALS2
We believe that this proposed change
to the outlier methodology will result in
more accurate outlier payments where
the calculated cost per episode accounts
for not only the number of visits during
an episode of care, but also the length
of the visits performed. This, in turn,
8 Ibid.
9 Piamjariyakul,
U., Ross, V., Yadrich, D.M.,
Williams, A., Howard, L., Smith, C. (2010).
Complex Home Care: Part I-Utilization and Costs to
Families for Health Care Services Each Year.
Nursing Economics. 28(4), 255–263
10 Friedman, B., Yanen, L., Liebel, D., Powers, B.
(2014). Effects of Home Visiting Nurse Intervention
versus Care as Usual on Individual Activities of
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may address some of the findings from
the home health study, where margins
were lower for patients with medically
complex needs that typically require
longer visits, thus potentially creating
an incentive to treat less complex
patients.
Table 25 shows the difference in the
average number of visits and the average
minutes per visit for outlier episodes
under the current outlier methodology
and the proposed outlier methodology
by the percentage of outlier payments to
total payments at the agency level.
Daily Living: A Secondary Analysis of a
Randomized Trial. BMC Geriatrics. 14(24), 1–13.
11 Ibid.
12 Fried. L., Ferrucci, L., Darer, J., Williamson, J.,
Anderson, G. (2004). Untangling the Concepts of
Disability, Frailty and Comorbidity: Implications for
Improved Targeting and Care. Journal of
Gerontology. 59(3), 255–263.
13 Riggs, J., Madigan, E., Fortinsky, R. (2011).
Home Health Care Nursing Visit Intensity and Heart
Failure Patient Outcomes. Home Health Care
Managing Practice. 23(6), 412–420.
14 Cheh, Valerie and Schurrer, John. Home Health
Independence Patients: High Use, but Not Financial
Outliers, Report to Centers for Medicare and
Medicaid, Mathematical Policy Research. March 31,
2010.
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TABLE 25—AVERAGE NUMBER OF VISITS AND MINUTES PER VISIT BY THE PERCENTAGE OF OUTLIER PAYMENTS TO TOTAL
PAYMENTS AT THE AGENCY LEVEL FOR OUTLIER EPISODES FOR THE CURRENT AND PROPOSED OUTLIER METHODOLOGIES, CY 2015
Current Outlier
Methodology
(Cost per Visit)
Avg. # of
visits
<1% Total Outlier Payments ............................................................................................
1% to <5% Total Outlier Payments .................................................................................
5% to <10% Total Outlier Payments ...............................................................................
10% Total Outlier Payments ............................................................................................
Proposed Outlier
Methodology
(Cost per Unit)
Avg. minutes per
visit
39.7
44.7
44.7
60.7
Avg. # of
visits
48.9
49.2
49.6
44.0
38.5
43.5
54.8
56.4
Avg. minutes per
visit
52.6
52.0
55.2
65.6
Source: CY 2015 home health claims data from the standard analytic file (as of December 31, 2015) for which we had a linked OASIS assessment.
Note(s): These results are based on simulations using CY 2015 utilization and the CY2017 payment parameters.
Analysis of the impact of the change
from a cost-per-visit to a cost-per-unit
approach indicates that approximately
two-thirds of outlier episodes under the
cost-per-unit approach would have still
received outlier payments under the
current cost-per-visit approach, while
about one-third of outlier episodes
under the current cost per visit
approach would not receive outlier
payments under the cost-per-unit
approach. Table 26 shows the average
number of visits and the visit length for
the episodes that would receive outlier
payments under the current cost-pervisit approach, but not under the
proposed cost-per-unit approach, as
well as the average number of visits and
the visit length for the episodes that
would receive outlier payments under
the proposed cost-per-unit approach,
but not under the current cost-per-visit
approach. Those episodes that would
only receive outlier payments under the
current cost-per-visit approach have less
average resource use (calculated by
multiplying the number of visits with
the number of minutes) than those
episodes that would only receive outlier
payments under the proposed cost-perunit approach. These results indicate
that the change from the current costper-visit methodology to the proposed
cost-per-unit methodology would result
in more accurate outlier payments that
better account for the intensity of the
visits performed rather than only visit
volume.
TABLE 26—AVERAGE NUMBER OF VISITS AND VISIT LENGTH FOR EPISODES THAT RECEIVE OUTLIER PAYMENTS ONLY
UNDER THE CURRENT OUTLIER METHODOLOGY AND FOR EPISODES THAT RECEIVE OUTLIER PAYMENTS ONLY UNDER
THE PROPOSED OUTLIER METHODOLOGY, CY 2015
Episodes that only would receive outlier payments under
the current methodology
Avg. # of visits
<1% Total Outlier Payments ............................................................................
1% to <5% Total Outlier Payments .................................................................
5% to <10% Total Outlier Payments ...............................................................
10% Total Outlier Payments ............................................................................
Avg.
minutes per
visit
36.8
37.6
43.8
46.1
39.9
38.5
36.4
27.5
Episodes that only would receive outlier payments under
the proposed methodology
Avg. # of visits
29.8
30.6
30.2
31.9
Avg.
minutes per
visit
63.4
65.6
85.9
104.5
sradovich on DSK3GDR082PROD with PROPOSALS2
Source: CY 2015 home health claims data from the standard analytic file (as of December 31, 2015) for which we had a linked OASIS assessment.
Note(s): These results are based on simulations using CY 2015 utilization and the CY2017 payment parameters.
In addition, we examined the impact
of changing from the current cost-pervisit methodology to the proposed costper-unit methodology on a subset of the
vulnerable patient populations
identified in the home health study. Our
simulations indicate that certain
subgroups identified in the home health
study may benefit from the change from
the current outlier methodology to the
proposed outlier methodology. Table 27
shows some of the vulnerable patient
populations that may benefit from the
proposed changes to the outlier
methodology. As shown in Table 27,
preliminary analysis indicates that a
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larger percentage of episodes of care for
patients with a fragile overall health
status will qualify for outlier payments
under the proposed methodology than
under the current methodology (24.1
percent versus 20.1 percent). Similarly,
a larger percentage of episodes of care
for patients who need assistance with
bathing will qualify for outlier payments
under the proposed methodology than
under the current methodology (29.1
percent versus 27.0 percent). In
addition, a larger percentage of episodes
of care for patients who need caregiver
assistance or who have surgical wounds
will qualify for outlier payments under
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the proposed methodology versus under
the current methodology (7.7 percent
versus 6.7 percent and 19.0 percent
versus 18.1 percent, respectively).
Furthermore, there are small increases
in the percentage of episodes of care
that would qualify for outlier payments
for the patients who need parenteral
nutrition or have poorly controlled
cardiac dysrhythmia or pulmonary
disorders. These results suggest that the
proposed change to the outlier
methodology may address some of the
findings from the home health study
and may alleviate potential financial
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disincentives to treat patients with
medically complex needs.
TABLE 27—IMPACT OF THE PROPOSED OUTLIER METHODOLOGY CHANGE ON SUBGROUPS OF VULNERABLE PATIENT
POPULATIONS IDENTIFIED IN THE HOME HEALTH STUDY
Overall percentage for
all non-LUPA
episodes
(%)
Subgroups identified in the home health study
Needs caregiver assistance ....................................................................
Fragile-serious overall status ...................................................................
Needs assistance with bathing ................................................................
Parenteral Nutrition ..................................................................................
Poorly Controlled Cardiac Dysrhythmia ..................................................
Poorly Controlled Pulmonary Disorder ....................................................
Surgical Wound .......................................................................................
Percent of outliers
based on cost-pervisit approach
(%)
6.8
21.9
20.1
0.2
4.3
7.8
17.6
6.7
20.1
27.0
0.2
3.4
5.4
18.1
Percent of outliers
based on cost-per-unit
approach
(%)
7.7
24.1
29.1
0.4
3.8
6.0
19.0
sradovich on DSK3GDR082PROD with PROPOSALS2
Source: CY 2015 home health claims data from the standard analytic file (as of December 31, 2015) for which we had a linked OASIS assessment.
Note(s): These results are based on simulations using CY 2015 utilization and the CY2017 payment parameters.
In concert with our proposal to
change to a cost-per-unit approach to
estimate episode costs and determine
whether an outlier episode should
receive outlier payments, we are
proposing to implement a cap on the
amount of time per day that would be
counted toward the estimation of an
episode’s costs for outlier calculation
purposes. Specifically, we propose to
limit the amount of time per day
(summed across the six disciplines of
care) to 8 hours or 32 units per day
when estimating the cost of an episode
for outlier calculation purposes. We
note that this proposal is consistent
with the definition of ‘‘part-time’’ or
‘‘intermittent’’ set out in section
1861(m) of the Act, which limits the
amount of skilled nursing and home
health aide minutes combined to less
than 8 hours each day and 28 or fewer
hours each week (or, subject to review
on a case-by-case basis as to the need for
care, less than 8 hours each day and 35
or fewer hours per week). We also note
that we are not limiting the amount of
care that can be provided on any given
day. We are only limiting the time per
day that can be credited towards the
estimated cost of an episode when
determining if an episode should
receive outlier payments and calculating
the amount of the outlier payment. For
instances when more than 8 hours of
care is provided by one discipline of
care, the number of units for the line
item will be capped at 32 units for the
day for outlier calculation purposes. For
rare instances when more than one
discipline of care is provided and there
is more than 8 hours of care provided
in one day, the episode cost associated
with the care provided during that day
will be calculated using a hierarchical
method based on the cost per unit per
discipline shown in Table 24. The
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discipline of care with the lowest
associated cost per unit will be
discounted in the calculation of episode
cost in order to cap the estimation of an
episode’s cost at 8 hours of care per day.
For example, if an HHA provided 4.5
hours of skilled nursing and 4.5 hours
of home health aide services, all 4.5
hours of skilled nursing would be
counted in the episode’s estimated cost
and 3.5 hours of home health aide
services would be counted in the
episode’s estimated cost (8 hours ¥ 4.5
hours = 3.5 hours) since home health
aide services has a lower cost-per-unit
than skilled nursing services.
We note that preliminary analysis
suggests that this proposed cap will
have a limited impact on episodes
overall. Out of approximately 5.4
million episodes in our preliminary
analytic file for 2015, only 15,384
episodes or 0.28 percent of all home
health episodes reported instances
where over 8 hours of care were
provided in a single day (which could
have resulted from data entry errors as
we currently do not use visit length for
payment). Of those 15,384 episodes,
only 1,591 would be outlier episodes
under the proposed outlier
methodology. Therefore, we estimate
that only 1,600 episodes or so, out of 5.4
million episodes, would be impacted
due to the proposed 8 hour cap.
3. Proposed Fixed Dollar Loss (FDL)
Ratio
For a given level of outlier payments,
there is a trade-off between the values
selected for the FDL ratio and the losssharing ratio. A high FDL ratio reduces
the number of episodes that can receive
outlier payments, but makes it possible
to select a higher loss-sharing ratio, and
therefore, increase outlier payments for
qualifying outlier episodes.
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Alternatively, a lower FDL ratio means
that more episodes can qualify for
outlier payments, but outlier payments
per episode must then be lower.
The FDL ratio and the loss-sharing
ratio must be selected so that the
estimated total outlier payments do not
exceed the 2.5 percent aggregate level
(as required by section 1895(b)(5)(A) of
the Act). Historically, we have used a
value of 0.80 for the loss-sharing ratio
which, we believe, preserves incentives
for agencies to attempt to provide care
efficiently for outlier cases. With a losssharing ratio of 0.80, Medicare pays 80
percent of the additional estimated costs
above the outlier threshold amount.
In the CY 2011 HH PPS final rule (75
FR 70398), in targeting total outlier
payments as 2.5 percent of total HH PPS
payments, we implemented an FDL
ratio of 0.67, and we maintained that
ratio in CY 2012. Simulations based on
CY 2010 claims data completed for the
CY 2013 HH PPS final rule showed that
outlier payments were estimated to
comprise approximately 2.18 percent of
total HH PPS payments in CY 2013, and
as such, we lowered the FDL ratio from
0.67 to 0.45. We stated that lowering the
FDL ratio to 0.45, while maintaining a
loss-sharing ratio of 0.80, struck an
effective balance of compensating for
high-cost episodes while allowing more
episodes to qualify as outlier payments
(77 FR 67080). The national,
standardized 60-day episode payment
amount is multiplied by the FDL ratio.
That amount is wage-adjusted to derive
the wage-adjusted FDL amount, which
is added to the case-mix and wageadjusted 60-day episode payment
amount to determine the outlier
threshold amount that costs have to
exceed before Medicare would pay 80
percent of the additional estimated
costs.
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For this proposed rule, simulating
payments using preliminary CY 2015
claims data (as of December 31, 2015)
and the CY 2016 payment rates (80 FR
68649 through 68652), we estimate that
outlier payments in CY 2016 would
comprise 2.23 percent of total payments.
Based on simulations using CY 2015
claims data and the CY 2017 payment
rates in section III.C.3 of this proposed
rule, we estimate that outlier payments
would comprise approximately 2.58
percent of total HH PPS payments in CY
2017 under the current outlier
methodology, a percent change of
approximately 15.7 percent. This
increase is attributable to the increase in
the national per-visit amounts through
the rebasing adjustments and the
decrease in the national, standardized
60-day episode payment amount as a
result of the rebasing adjustment and
the nominal case-mix growth reduction.
Given the statutory requirement to
target up to, but no more than, 2.5
percent of total payments as outlier
payments, we are proposing a change to
the FDL ratio for CY 2017 as we believe
that maintaining an FDL ratio of 0.45
with a loss-sharing ratio of 0.80 is no
longer appropriate given the percentage
of outlier payments projected for CY
2017. We note that we are not proposing
a change to the loss-sharing ratio (0.80)
in order for the HH PPS to remain
consistent with payment for high-cost
outliers in other Medicare payment
systems (for example, IRF PPS, IPPS,
etc.) Under the current outlier
methodology, the FDL ratio would need
to be changed from 0.45 to 0.48 to pay
up to, but no more than, 2.5 percent of
total payments as outlier payments.
Under the proposed outlier
methodology which would use a cost
per unit rather than a cost per visit
when calculating episode costs, we
estimate that we will pay out 2.74
percent in outlier payments in CY 2017
using an FDL ratio of 0.48 and that the
FDL ratio will need to be changed to
0.56 to pay up to, but no more than, 2.5
percent of total payments as outlier
payments.
Therefore, in addition to the proposal
to change the methodology used to
calculate outlier payments, we are
proposing to change the FDL ratio from
0.45 to 0.56 for CY 2017. We note that
in the final rule, we will update our
estimate of outlier payments as a
percent of total HH PPS payments using
the most current and complete year of
HH PPS data (CY 2015 claims data as of
June 30, 2016) and therefore, we may
adjust the final FDL ratio accordingly.
We invite public comments on the
proposed changes to the outlier
payment calculation methodology and
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the associated changes in the
regulations text at § 484.240 as well as
the proposed change to the FDL ratio.
E. Proposed Payment Policies for
Negative Pressure Wound Therapy
(NPWT) Using a Disposable Device
1. Background
Negative pressure wound therapy
(NPWT) is a medical procedure in
which a vacuum dressing is used to
enhance and promote healing in acute,
chronic, and burn wounds. The therapy
involves using a sealed wound dressing
attached to a pump to create a negative
pressure environment in the wound.
Applying continued or intermittent
vacuum pressure helps to increase
blood flow to the area and draw out
excess fluid from the wound. Moreover,
the therapy promotes wound healing by
preparing the wound bed for closure, by
reducing edema, by promoting
granulation tissue formation and
perfusion, and by removing exudate and
infectious material. The wound type
and/or the location of the wound
determine whether the vacuum can
either be applied continuously or
intermittently. NPWT can be utilized for
varying lengths of time, as indicated by
the severity of the wound, from a few
days of use up to a span of several
months.
In addition to the conventional NPWT
systems classified as durable medical
equipment (DME), NPWT can also be
performed with a single-use disposable
system that consists of a non-manual
vacuum pump, a receptacle for
collecting exudate, and dressings for the
purposes of wound therapy. These
disposable systems consist of a small
pump, which eliminates the need for a
bulky canister. Unlike conventional
NPWT systems classified as DME,
disposable NPWT systems have a preset
continuous negative pressure, there is
no intermittent setting, they are pocketsized and easily transportable, and they
are generally battery-operated with
disposable batteries.15
Section 1895 of the Act requires that
the HH PPS includes payment for all
covered home health services. Section
1861(m) of the Act defines what items
and services are considered to be ‘‘home
health services’’ when furnished to a
Medicare beneficiary under a home
health plan of care when provided in
the beneficiary’s place of residence.
Those services include:
• Part-time or intermittent nursing
care
• Physical or occupational therapy or
speech-language pathology services
15 Single use negative pressure wound therapy.
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• Medical social services
• Part-time or intermittent services of
a home health aide
• Medical supplies
• A covered osteoporosis drug
• Durable medical equipment (DME)
The unit of payment under the HH
PPS is a national, standardized 60-day
episode payment amount with
applicable adjustments. The national,
standardized 60-day episode payment
amount includes costs for the home
health services outlined above per
section 1861(m) of the Act, except for
DME and the covered osteoporosis drug.
Section 1814(k) of the Act specifically
excludes DME from the national,
standardized 60-day episode rate and
consolidated billing requirements. DME
continues to be paid outside of the HH
PPS. The cost of the covered
osteoporosis drug (injectable calcitonin),
which is covered where a woman is
postmenopausal and has a bone
fracture, is also not included in the
national, standardized 60-day episode
payment amount, but must be billed by
the HHA while a patient is under a
home health plan of care since the law
requires consolidated billing of
osteoporosis drugs. The osteoporosis
drug itself continues to be paid on a
reasonable cost basis.
Medical supplies are included in the
definition of ‘‘home health services’’
and the cost of such supplies is
included in the national, standardized
60-day episode payment amount.
Medical supplies are items that, due to
their therapeutic or diagnostic
characteristics, are essential in enabling
HHA personnel to conduct home visits
or to carry out effectively the care the
physician has ordered for the treatment
or diagnosis of the patient’s illness or
injury. Supplies are classified into two
categories, specifically:
• Routine: Supplies used in small
quantities for patients during the usual
course of most home visits; or
• Non-routine: Supplies needed to
treat a patient’s specific illness or injury
in accordance with the physician’s plan
of care and meet further conditions.
Both routine and non-routine medical
supplies are included in the national,
standardized 60-day episode payment
amount for every Medicare home health
patient regardless of whether or not the
patient requires medical supplies during
the episode. The law requires that all
medical supplies (routine and nonroutine) be provided by the HHA while
the patient is under a home health plan
of care. A disposable NPWT system
would be considered a non-routine
supply for home health.
As required under sections
1814(a)(2)(C) and 1835(a)(2)(A) of the
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Act, for home health services to be
covered, the patient must receive such
services under a plan of care established
and periodically reviewed by a
physician. As described in § 484.18 of
the Medicare Conditions of
Participation (CoPs), the plan of care
that is developed in consultation with
the agency staff, is to cover all pertinent
diagnoses, including the types of
services and equipment required for the
treatment of those diagnoses as well as
any other appropriate items, including
DME. Consolidated billing requirements
ensure that only the HHA can bill for
home health services, with the
exception of DME and therapy services
provided by physicians, when a patient
is under a home health plan of care. The
types of service most affected by the
consolidated billing edits tend to be
non-routine supplies and outpatient
therapies, since these services are
routinely billed by providers other than
HHAs, or are delivered by HHAs to
patients not under home health plans of
care.
As provided under section 1834(k)(5)
of the Act, a therapy code list was
created based on a uniform coding
system (that is, the HCPCS) to identify
and track these outpatient therapy
services paid under the Medicare
Physician Fee Schedule (MPFS). The
list of therapy codes, along with their
respective designation, can be found on
the CMS Web site, specifically at https://
www.cms.hhs.gov/TherapyServices/05_
Annual_Therapy_
Update.asp#TopOfPage. Two of the
designations that are used for therapy
services are: ‘‘Always therapy’’ and
‘‘sometimes therapy.’’ An ‘‘always
therapy’’ service must be performed by
a qualified therapist under a certified
therapy plan of care, and a ‘‘sometimes
therapy’’ service may be performed by
physician or a non-physician
practitioner outside of a certified
therapy plan of care. CPT codes 97607
and 97608 are categorized as a
‘‘sometimes’’ therapy, which may be
performed by either a physician or a
non-physician practitioner outside of a
certified therapy plan of care, as
described in section 200.9 of Chapter 4
of the Medicare Claims Processing
Manual.16
2. The Consolidated Appropriations Act
of 2016
As mentioned in section III.A.1 above,
for patients under a home health plan of
care, payment for part-time or
intermittent skilled nursing, physical
16 https://www.cms.gov/Regulations-andGuidance/Guidance/Manuals/Downloads/
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therapy, speech-language pathology,
occupational therapy, medical social
services, part-time or intermittent home
health aide visits, and routine and nonroutine supplies are included in the
episode payment amount. A disposable
NPWT system is currently considered a
non-routine supply and thus payment
for the disposable NPWT system is
included in the episode payment
amount. The Consolidated
Appropriations Act of 2016 (Pub. L 114–
113) amends both section 1834 of the
Act (42 U.S.C. 1395m) and section
1861(m)(5) of the Act (42 U.S.C.
1395x(m)(5)), requiring a separate
payment to a HHA for an applicable
disposable device when furnished on or
after January 1, 2017, to an individual
who receives home health services for
which payment is made under the
Medicare home health benefit. Section
1834(s)(2) of the Act defines an
applicable device as a disposable
negative pressure wound therapy device
that is an integrated system comprised
of a non-manual vacuum pump, a
receptacle for collecting exudate, and
dressings for the purposes of wound
therapy used in lieu of a conventional
NPWT DME system.
As required by the Consolidated
Appropriations Act of 2016 (Pub. L 114–
113), the separate payment amount for
NPWT using a disposable system is to
be set equal to the amount of the
payment that would be made under the
Medicare Hospital Outpatient
Prospective Payment System (OPPS)
using the Level I Healthcare Common
Procedure Coding System (HCPCS)
code, otherwise referred to as Current
Procedural Terminology (CPT–4) codes,
for which the description for a
professional service includes the
furnishing of such a device.
Under the OPPS, CPT codes 97607
and 97608 (APC 5052—Level 2 Skin
Procedures), include furnishing the
service as well as the disposable NPWT
device. The codes are defined as
follows:
• HCPCS 97607—Negative pressure
wound therapy, (for example, vacuum
assisted drainage collection), utilizing
disposable, non-durable medical
equipment including provision of
exudate management collection system,
topical application(s), wound
assessment, and instructions for ongoing
care, per session; total wound(s) surface
area less than or equal to 50 square
centimeters.
• HCPCS 97608—Negative pressure
wound therapy, (for example, vacuum
assisted drainage collection), utilizing
disposable, non-durable medical
equipment including provision of
exudate management collection system,
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topical application(s), wound
assessment, and instructions for ongoing
care, per session; total wound(s) surface
area greater than 50 square centimeters.
3. Proposed Payment Policies for NPWT
Using a Disposable Device
For the purposes of paying for NPWT
using a disposable device for a patient
under a Medicare home health plan of
care and for which payment is
otherwise made under section 1895(b)
of the Act, CMS is proposing that for
instances where the sole purpose for an
HHA visit is to furnish NPWT using a
disposable device, Medicare will not
pay for the visit under the HH PPS.
Instead, we propose that since
furnishing NPWT using a disposable
device for a patient under a home health
plan of care is to be paid separately,
based on the OPPS amount, which
includes payment for both the device
and furnishing the service, the HHA
must bill these visits separately under
type of bill 34x (used for patients not
under a HH plan of care, Part B medical
and other health services, and
osteoporosis injections) along with the
appropriate HCPCS code (97607 or
97608). Visits performed solely for the
purposes of furnishing NPWT using a
disposable device are not to be reported
on the HH PPS claim (type of bill 32x).
If NPWT using a disposable device is
performed during the course of an
otherwise covered HHA visit (for
example, while also furnishing a
catheter change), we propose that the
HHA must not include the time spent
furnishing NPWT in their visit charge or
in the length of time reported for the
visit on the HH PPS claim (type of bill
32x). Providing NPWT using a
disposable device for a patient under a
home health plan of care will be
separately paid based on the OPPS
amount relating to payment for covered
OPD services. In this situation, the HHA
bills for NPWT performed using a
disposable device under type of bill 34x
along with the appropriate HCPCS code
(97607 or 97608). Additionally, this
same visit should also be reported on
the HH PPS claim (type of bill 32x), but
only for the time spent furnishing the
services unrelated to the provision of
NPWT.
As noted in section III.E.1, since these
two CPT codes (97607 and 97608) are
considered ‘‘sometimes’’ therapy codes,
NPWT using a disposable device for
patients under a home health plan of
care can be performed, in accordance to
State law, by a registered nurse,
physical therapist, or occupational
therapist and the visits would be
reported on the type of bill 34x using
revenue codes 0559, 042X, 043X. The
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descriptions for CPT codes 97607 and
97608 include performing a wound
assessment, therefore we believe that it
would only be appropriate for these
visits to be performed by a registered
nurse, physical therapist, or
occupational therapist as defined in
§ 484.4 of the Medicare Conditions of
Participation (CoPs).
The payment amount for both
97607and 97608 will be set equal to the
amount of the payment that would be
made under the OPPS and subject to the
area wage adjustment policies in place
under the OPPS, for CY 2017 and each
subsequent year. Please see Medicare
Hospital OPPS Web page for Addenda A
and B at https://www.cms.gov/
Medicare/Medicare-Fee-for-ServicePayment/HospitalOutpatientPPS/
Addendum-A-and-Addendum-BUpdates.html. These addenda are a
‘‘snapshot’’ of HCPCS codes and their
status indicators, APC groups, and
OPPS payment rates that are in effect at
the beginning of each quarter. Section
504(b)(1) of the Consolidated
Appropriations Act of 2016 (Pub. L 114–
113) amends section 1833(a)(1) of the
Act, which requires that furnishing the
NPWT using a disposable device be
subject to beneficiary coinsurance in the
amount of 20 percent. The amount paid
to the HHA by Medicare will be equal
to 80 percent of the lesser of the actual
charge or the payment amount as
determined by the OPPS for the year.
In order for a beneficiary to receive
NPWT using a disposable device under
the home health benefit, the beneficiary
must also qualify for the home health
benefit in accordance with the existing
eligibility requirements. To be eligible
for Medicare home health services, as
set out in sections 1814(a) and 1835(a)
of the Act, a physician must certify that
the Medicare beneficiary (patient) meets
the following criteria:
• Is confined to the home
• Needs skilled nursing care on an
intermittent basis or physical therapy
or speech-language pathology; or have
a continuing need for occupational
therapy
• Is under the care of a physician
• Receive services under a plan of care
established and reviewed by a
physician; and
• Has had a face-to-face encounter
related to the primary reason for home
health care with a physician or
allowed Non-Physician Practitioner
(NPP) within a required timeframe.
As set forth in §§ 409.32 and 409.44,
to be considered a skilled service, the
service must be so inherently complex
that it can be safely and effectively
performed only by, or under the
supervision of, professional or technical
personnel. Additionally, care is deemed
as ‘‘reasonable and necessary’’ based on
information reflected in the home health
plan of care, the OASIS as required by
§ 484.55, or a medical record of the
individual patient. Coverage for NPWT
using a disposable device will be
determined based upon a doctor’s order
as well as patient preference. Research
has shown that patients prefer wound
dressing materials that afford the
quickest wound healing, pain reduction,
maximum exudate absorption to
minimize drainage and odor, and they
indicated some willingness to pay out of
pocket costs.17 Treatment decisions as
to whether to use a disposable NPWT
system versus a conventional NPWT
DME system is determined by the
characteristics of the wound, as well as,
patient goals and preferences discussed
with the ordering physician to best
achieve wound healing and reduction.
We are soliciting public comment on
all aspects of the proposed payment
policies for furnishing a disposable
NPWT device as articulated in this
section as well as the corresponding
proposed changes to the regulations at
§ 409.50 in section VII of this proposed
rule.
F. Update on Subsequent Research and
Analysis Related to Section 3131(d) of
the Affordable Care Act
Section 3131(d) of the Patient
Protection and Affordable Care Act
(Pub. L. 111–148), as amended by the
Health Care and Education
Reconciliation Act of 2010 (Pub. L. 111–
152), (collectively referred to as ‘‘The
Affordable Care Act’’), directed the
Secretary of Health and Human Services
(the Secretary) to conduct a study on
HHA costs involved with providing
ongoing access to care to low-income
Medicare beneficiaries or beneficiaries
in medically underserved areas and in
treating beneficiaries with high levels of
severity of illness and to submit a
Report to Congress on the study’s
findings and recommendations. As part
of the study, the Affordable Care Act
stated that we may also analyze
methods to potentially revise the home
health prospective payment system (HH
PPS). In the CY 2016 HH PPS proposed
rule (80 FR 39840), we summarized the
Report to Congress on the home health
study, required by section 3131(d) of the
Affordable Care Act, and provided
information on the initial research and
analysis conducted to potentially revise
the HH PPS case-mix methodology to
address the home health study findings
outlined in the Report to Congress. In
this proposed rule, we are providing an
update on additional research and
analysis conducted on the Home Health
Groupings Model (HHGM), one of the
model options referenced in the CY
2016 HH PPS proposed rule (80 FR
39866).
The premise of the HHGM starts with
a clinical foundation where home health
episodes are grouped by primary
diagnosis based on what home health
interventions would be required during
the episode of care. In addition to the
clinical groupings, the HHGM
incorporates other information from the
OASIS and claims data to further group
home health episodes for payment. Each
home health episode is categorized into
different sub-groups within each of the
five categories below:
• Timing (early or late; that is, episode
is placed into 1 of 2 groups)
• Referral source (community, acute, or
post-acute admission source; that is,
episode is placed into 1 of 3 groups)
• Clinical grouping (musculoskeletal
rehab, neuro/stroke rehab, wounds,
MMTA, behavioral, or complex; that
is, episode is placed into 1 of 6
groups)
• Functional/cognitive level (low,
medium, or high; that is, episode is
placed into 1 of 3 groups)
• Comorbidity adjustment (first, second,
or third, tier based on secondary
diagnoses; that is, episode is placed
into 1 of 3 groups)
In total there would be 324 possible
payment groupings an episode can be
grouped into under the HHGM. Unlike
the current payment model, the HHGM
does not rely on the number of therapy
visits performed to influence payment.
Similar to the current payment
system, episodes under the HHGM are
first classified as ‘‘early’’ or ‘‘late’’
depending on when they occur within
a sequence of adjacent episodes, as
outlined in our regulations at § 484.230.
Currently, the first two 60-day episodes
of care are considered ‘‘early’’ and third
or later 60-day episodes of care are
considered ‘‘late’’. However, recent
analysis shows that there is a substantial
difference in the number of visits that
occur during the first 30 days of a 60day episode of care compared to the
second 30 days in a 60-day episode of
care (see Figure 4, below).
17 Corbett, L., Ennis, W. (2014). What Do Patients
Want? Patient Preferences in Wound Care. 3(8),
537–543.
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Given the differences in the number
of visits occurring in the first 30 days
versus the second 30 days in a 60-day
episode of care, and to better account for
the relationship between episode
characteristics and episode cost, we
modeled all episodes as 30-day episodes
of care, instead of 60-day episodes of
care as in the current payment system.
Under the HHGM, the first 30-day
episode in a sequence of adjacent
episodes was classified as an early
episode. All subsequent episodes in a
sequence (second or later) of adjacent
episodes were classified as late episodes
if separated by no more than a 60-day
gap in care.
After taking into account whether the
30-day episode of care was ‘‘early’’
versus ‘‘late’’, each episode was then
classified into one of three referral
source categories depending on whether
the beneficiary was admitted from an
acute or post-acute care facility within
14 days prior to being admitted to home
health (community, acute, or postacute). Patients admitted to home health
from the community, an acute setting of
care, or a post-acute setting of care had
different observable patterns of resource
use and thus, under the HHGM,
episodes of care for those patients
would be paid differently.
We then grouped episodes into one of
six clinical groups based on the primary
diagnosis listed on the OASIS for each
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episode. We created these groups to
describe the most common types of care
that HHAs provide. We have reviewed
all possible ICD–9–CM codes that could
be recorded on the OASIS and assigned
each code into one of the following
clinical groups: Musculoskeletal
Rehabilitation; Neuro/Stroke
Rehabilitation; Wound Care; Medication
Management, Teaching and Assessment
(MMTA); Behavioral Health Care; and
Complex Medical Care.
The HHGM designates a functional/
cognitive level for each episode based
on items identified on the OASIS that
impact resource use. Using home health
episodes from 2013, we estimated a
regression model that determines the
relationship between the responses for
certain OASIS items and resource use.18
The coefficients from the regression
show how much more or less, on
average, an episode’s resource use is
depending on responses to these items
which is then used to predict resource
use for each individual episodes.
Ranking the episodes by predicted
resource use and then identifying
thresholds that divides episodes into
three groups of roughly the same size
allows us to assign each episode to into
18 ‘‘Resource use’’ is an estimate of the cost of an
episode. It is measured by multiplying the number
of minutes of services that occur during an episode
by a wage rate for the disciplines providing the
care.
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a low, medium or high functional/
cognitive level.
Finally, our exploratory analyses have
determined that secondary diagnoses
(comorbidities) provide additional
information that can predict resource
use even after controlling for episode
timing, referral source, the clinical
grouping (based in the patient’s primary
diagnosis) and functional/cognitive
level. Therefore, we further
differentiated episodes into based on the
presence of certain secondary diagnoses.
We explored two options. For the first
option we determined the commonly
occurring comorbidities (incidence of
over 0.1 percent) reported on the OASIS
that were also associated with above
average resource use. We then divided
the comorbidities into a low or high
group based on average resource use
associated with the comorbidity. We
then placed episodes into three tiers:
Episodes for beneficiaries with no
comorbidities reported on the OASIS in
the low or high group (Tier 1); episodes
for beneficiaries with comorbidities in
the low, but not high group as reported
on the OASIS (Tier 2); and episodes for
beneficiaries with comorbidities in the
high group reported on the OASIS (Tier
3). For the second option, we used the
major complication or comorbidity
(MCC) and complication and
comorbidity (CC) list from the Inpatient
Prospective Payment System (IPPS).
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Using the CC and MMC list we placed
episodes into three tiers: Episodes
where beneficiaries had no MCC or CC
diagnoses reported on either the OASIS
or any inpatient or professional claim
within 90 days of the start of home care
(Tier 1); episodes where beneficiaries
had CC but no MCC diagnoses reported
on either the OASIS or any inpatient or
professional claim within 90 days of the
start of home care (Tier 2); and episodes
where beneficiaries had at least one
MCC diagnosis reported on either the
OASIS or any inpatient or professional
claim within 90 days of the start of
home care (Tier 3).
We determined the case-mix weight
for each of the 324 different HHGM
payment groups by estimating a
regression between episode resource use
and binary variables controlling for the
five dimensions described above
(episode timing, admission source,
HHGM clinical group, functional/
cognitive level, and comorbidities).
After estimating this model on home
health episodes from 2013 (excluding
LUPA and outlier episodes), we then
used the results of the model to predict
the expected average resource use of
each episode based on these six
characteristics. We divide the predicted
resource use of each episode by the
overall average resource use (of all 2013
episodes) to calculate the average casemix of all episodes within a particular
payment group (that is, each
combination of the sub-groups within
the five main groups). That case-mix
weight is then used to adjust the base
payment rate to then determine each
episode’s payment.
In many ways, the structure of the
HHGM is similar to the current payment
system. However, by either adding to or
removing certain components of the
current payment system, the HHGM
could help to strengthen the HH PPS by
addressing the margin differences noted
in the home health study and by
removing unintended financial
incentives (for example, the current
therapy thresholds). As noted in the
3131(d) study, margin differences exist
across beneficiary characteristics such
as parenteral nutrition, traumatic
wounds, whether bathing assistance was
needed, and admission source. These
margin differences would be addressed
by moving to a HHGM approach where
those characteristics are better
accounted for in the model.
Additionally, the HHGM aligns with
how clinicians generally identify the
types of patients they see in home
health, which, in turn, better defines the
home health benefit in a more
transparent manner so that the payer
understands the primary reason for
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home care. We feel that the HHGM will
address the findings highlighted in the
3131(d) report, specifically improving
the payment accuracy for purchased
home health services, promote fair
compensation to HHAs, and increase
the quality of care for beneficiaries. We
plan to release a more detailed
Technical Report in the future on this
additional research and analysis
conducted on the HHGM. When we
release the technical report, we are also
planning to release a list of the ICD–9–
CM and ICD–10–CM codes assigned to
each of the clinical groups within the
HHGM to further assist the industry in
analyzing the HHGM model. While we
are not soliciting comments on the
HHGM in this proposed rule, once the
Technical Report is released, we will
post a link on our Home Health Agency
(HHA) Center Web site (https://
www.cms.gov/center/provider-Type/
home-Health-Agency-HHA-Center.html)
to receive comments and feedback on
the model.
FF. Update on Future Plans To Group
HH PPS Claims Centrally During Claims
Processing
In the CY 2011 HH PPS proposed rule
(75 FR 43236) we solicited comments on
potential plans to group HH PPS claims
centrally during claims processing and
received many comments in support of
this initiative. In grouping HH PPS
Claims centrally during processing, we
are describing a process whereby all of
the information necessary to group the
claim and assign a Health Insurance
Prospective Payment System (HIPPS)
score which determines payment is
available and processed within the
Fiscal Intermediary Shared System
(FISS). In that rule, we discussed the
potential use of the treatment
authorization field to group HH PPS
claims within the claims processing
system. In conducting further analysis,
we determined that the use of the
treatment authorization field was not a
viable option. In our analysis, we
determined that the information we
planned to report in this field was not
permitted by the Health Insurance
Portability Accountability Act (HIPAA).
In this section, we are soliciting
comments on another process identified
whereby all of the information
necessary to group HH PPS claims
occurs centrally during claims
processing.
As we outlined in the previous rule,
Medicare makes payment under the HH
PPS on the basis of a national,
standardized 60-day episode payment
amount that is adjusted for case-mix and
geographic wage variations. The
national, standardized 60-day episode
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payment amount includes services from
the six HH disciplines (skilled nursing,
HH aide, physical therapy, speechlanguage pathology, occupational
therapy, and medical social services)
and non-routine medical supplies.
Durable medical equipment covered
under HH is paid for outside the HH
PPS payment. To adjust for case-mix,
the HH PPS uses a 153-category casemix classification to assign patients to a
home health resource group (HHRG).
Clinical needs, functional status, and
service utilization are computed from
responses to selected data elements in
the Outcome & Assessment Information
Set (OASIS) instrument. On Medicare
claims, the HHRGs are represented as
HIPPS codes.
At a patient’s start of care and before
the start of each subsequent 60-day
episode, the HHA is required to perform
a comprehensive clinical assessment of
the patient and complete the OASIS
assessment instrument. The OASIS
instrument collects data concerning 3
dimensions of the patient’s condition:
(1) Clinical severity (orthopedic,
neurological or diabetic conditions,
etc.); (2) Functional status (comprised of
6 activities of daily living (ADLs)); and
(3) Service utilization (therapy visits
provided during episode). HHAs enter
data collected from their patients’
OASIS assessments into a data
collection software tool. For Medicare
patients, the data collection software
invokes HH PPS Grouper software to
assign a HIPPS code to the patient’s
OASIS assessment. The HHA includes
the HIPPS code assigned by HH PPS
Grouper software on the Medicare HH
PPS bill, ultimately enabling our claims
processing system to reimburse the
HHA for services provided to patients
receiving Medicare home health
services.
The HHA is separately required to
electronically submit OASIS
assessments for their Medicare and
Medicaid patients to us. On the HH PPS
Web site at https://www.qtso.com/
havendownload.html, we provide a free
OASIS assessment data collection tool
(JHAVEN) which includes the HH PPS
grouper software, a separate HH PPS
grouper program which can be
incorporated into an HHA’s own data
collection software, and HH PPS data
specifications for use by HHAs or
software vendors desiring to build their
own HH PPS grouper. Most HHAs do
not use the JHAVEN freeware, instead
preferring to employ software vendors
to create and maintain a customized
assessment data collection tool which
can be integrated into the HHA’s billing
software. Likewise, many vendors
employed by HHAs do not utilize the
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HH PPS grouper freeware, instead
preferring to build their own HH PPS
grouper from the data specifications
which we provide.
Prior to the CY 2008, we made
infrequent, minor changes to the HH
PPS Grouper software. Since CY 2008,
the HH PPS Grouper became more
complex and more sensitive to annual
diagnosis coding changes. As a result, in
recent years, HHAs have been required
to update their grouper software twice a
year. Most HHAs employ software
vendors to effectuate these updates.
HHAs have expressed concerns to us
that the bi-annual grouper updates
coupled with the additional complexity
of the grouper has increased provider
and vendor burden.
We continue to identify OASIS
assessments submitted with erroneous
HIPPS codes through a process of
comparing the submitted HIPPS code to
the HIPPS code returned by our
assessment system. These errors may
occur when HHAs or their software
vendors inaccurately replicate the HH
PPS Grouper algorithm into the HHA’s
customized software. HHAs have
expressed concerns that the HH PPS
Grouper complexities increase their
vulnerability to submit an inaccurate
HIPPS code on the Medicare bill. We
believe that embedding the HH PPS
Grouper within the claims processing
system would mitigate the provider’s
vulnerability and improve payment
accuracy.
We recently implemented a process
where we match the claim and the
OASIS assessment in order to validate
the HIPPS code on the Medicare bill. In
addition, we have conducted an
analysis and prototype testing of a javabased grouper with our FISS
maintenance contractor. We believe that
making additional enhancements to the
claim and OASIS matching process
would enable us to collect all of the
other necessary information to assign a
HIPPS code within the claims
processing system. Adopting such a
process would improve payment
accuracy by improving the accuracy for
HIPPS codes on bills, decrease costs,
and burden to HHAs.
We are soliciting public comments on
this potential enhancement as described
above. If we implemented grouping HH
PPS claims centrally within the claims
processing system, the HHA would no
longer have to maintain a separate
process outside of our claims processing
system, thus reducing the costs and
burden to HHAs associated with the
updates of the grouper software as well
as the ongoing agency costs associated
with embedding the HH PPS Grouper
within JHAVEN. Finally, this
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enhancement would also address
current payment vulnerabilities
associated with the reporting of
incorrect HIPPS codes on the claim.
IV. Proposed Provisions of the Home
Health Value-Based Purchasing
(HHVBP) Model
A. Background
As authorized by section 1115A of the
Act and finalized in the CY 2016 HH
PPS final rule, we implemented the
HHVBP Model to begin on January 1,
2016. The HHVBP Model has an overall
purpose of improving the quality and
delivery of home health care services to
Medicare beneficiaries. The specific
goals of the Model are to: (1) Provide
incentives for better quality care with
greater efficiency; (2) study new
potential quality and efficiency
measures for appropriateness in the
home health setting; and, (3) enhance
the current public reporting process.
Using the randomized selection
methodology finalized in the CY 2016
HH PPS final rule, nine states were
selected for inclusion in the HHVBP
Model, representing each geographic
area across the nation. All Medicarecertified HHAs that provide services in
Arizona, Florida, Iowa, Maryland,
Massachusetts, Nebraska, North
Carolina, Tennessee, and Washington
(competing HHAs), are required to
compete in the Model. Requiring all
Medicare-certified HHAs in the selected
states to participate in the Model
ensures that: (1) There is no selection
bias; (2) participating HHAs are
representative of HHAs nationally; and,
(3) there is sufficient participation to
generate meaningful results.
As finalized in the CY 2016 HH PPS
final rule, the HHVBP Model will utilize
the waiver authority under section
1115A(d)(1) of the Act to adjust
Medicare payment rates under section
1895(b) of the Act beginning in calendar
year (CY) 2018 based on performance on
applicable measures. Payment
adjustments will be increased
incrementally over the course of the
HHVBP Model in the following manner:
(1) A maximum payment adjustment of
3 percent (upward or downward) in CY
2018; (2) a maximum payment
adjustment of 5 percent (upward or
downward) in CY 2019; (3) a maximum
payment adjustment of 6 percent
(upward or downward) in CY 2020; (4)
a maximum payment adjustment of 7
percent (upward or downward) in CY
2021; and, (5) a maximum payment
adjustment of 8 percent (upward or
downward) in CY 2022. Payment
adjustments will be based on each
HHA’s Total Performance Score (TPS) in
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43747
a given performance year (PY) on (1) a
set of measures already reported via
OASIS and HHCAHPS for all patients
serviced by the HHA, or determined by
claims data and, (2) three New Measures
where points are achieved for reporting
data.
B. Smaller- and Larger-Volume Cohorts
Proposals
The HHVBP Model compares a
competing HHA’s performance on
quality measures against the
performance of other competing HHAs
within the same state and size cohort.
Within each of the nine selected states,
each competing HHA is grouped to
either the smaller-volume cohort or the
larger-volume cohort, as defined in
§ 484.305. The larger-volume cohort is
defined as the group of competing
HHAs within the boundaries of selected
states that are participating in
HHCAHPS in accordance with § 484.250
and the smaller-volume cohort is
defined as the group of competing
HHAs within the boundaries of selected
states that are exempt from participation
in HHCAHPS in accordance with
§ 484.250 (80 FR 68664). An HHA can
be exempt from the HHCAHPS reporting
requirements for a calendar year period
if it has less than 60 eligible unique
HHCAHPS patients annually as
specified in § 484.250. In the CY 2016
HH PPS final rule, we finalized that
when there are too few HHAs in the
smaller-volume cohort in each state
(such as when there are only one or two
HHAs competing within a smallervolume cohort in a given state) to
compete in a fair manner, the HHAs
would be included in the larger-volume
cohort for purposes of calculating the
TPS and payment adjustment
percentage without being measured on
HHCAHPS (80 FR 68664).
1. Proposal to Eliminate Smaller- and
Larger-Volume Cohorts Solely for
Purposes of Setting Performance
Benchmarks and Thresholds
In the CY 2016 HH PPS final rule (80
FR 68681–68682), we finalized a scoring
methodology for determining
achievement points for each measure
under which HHAs will receive points
along an achievement range, which is a
scale between the achievement
threshold and a benchmark. The
achievement thresholds are calculated
as the median of all HHAs’ performance
on the specified quality measure during
the baseline period and the benchmark
is calculated as the mean of the top
decile of all HHAs’ performance on the
specified quality measure during the
baseline period.
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We previously finalized that under
the HHVBP Model, we would calculate
both the achievement threshold and the
benchmark separately for each selected
state and for HHA cohort size. Under
this methodology, benchmarks and
achievement thresholds would be
calculated for both the larger-volume
cohort and for the smaller-volume
cohort of HHAs in each state (which we
defined in each state based on a baseline
period from January 1, 2015 through
December 31, 2015). We also finalized
that, in determining improvement
points for each measure, HHAs would
receive points along an improvement
range, which we defined as a scale
indicating the change between an
HHA’s performance during the
performance period and the HHA’s
performance in the baseline period
divided by the difference between the
benchmark and the HHAs performance
in the baseline period. We finalized that
both the benchmarks and the
achievement thresholds would be
calculated separately for each state and
for HHA cohort size.
We finalized the above policies based
on extensive analyses of the 2013–2014
OASIS, claims, and HHCAHPS archived
data. We believed that these data were
sufficient to predict the effect of using
cohorts for benchmarking and threshold
purposes because they have been used
for several years in other CMS quality
initiatives such as the Home Health
Quality Reporting Program.
Since the publication of the CY 2016
HH PPS final rule, we have continued
to evaluate the calculation of the
benchmarks and achievement
thresholds using the most recent CY
2015 data that is now available. We
have calculated benchmarks and
achievement thresholds for the OASIS
measures for the smaller- and largervolume cohorts and state-wide for each
of the nine states using these data. Our
review of the benchmarks and
achievement thresholds for each of the
cohorts and states indicates that the
benchmark values for the smallervolume cohorts varied considerably
more from state-to-state than the
benchmark values for the larger-volume
cohorts. Some inter-state variation in
the benchmarks and achievement
thresholds for each of the measures was
expected due to different state
regulatory environments. However, the
overall variation in these values was
more than we expected, given the
previous analyses we did. For example,
with respect to the Improvement in Bed
Transferring measure, we discovered
that variation in the benchmark values
between the smaller-volume cohorts
was nearly three times greater than the
variation in the benchmark values for
the larger-volume cohorts or the
statewide benchmarks. We also
discovered that this large variation
affected most of the measures. We are
concerned that this high variation is not
the result of expected differences like
state regulatory policy, but is instead the
result of (1) the cohort is so small that
there are not enough HHAs in the cohort
to calculate the values using the
finalized methodology (mean of the top
decile); or (2) the cohort is large enough
to calculate the values using the
finalized methodology, but there are not
enough HHAs in the cohort to generate
reliable values.
We have included three tables in this
proposed rule to help illustrate this
issue. Each of the three tables include
the 10 benchmarks for the OASIS
measures that were calculated for the
Model using the 2015 QIES roll-up file
data for each state. We did not include
the claims measures and the HHCAHPS
measures in this example because we do
not have all of the 2015 data available.
These three tables demonstrate the
relationship between the size of the
cohort and degree of variation of the
different benchmark values among the
states. Table 28, Table 29 and Table 30
represent the benchmarks for the OASIS
measures for the smaller-volume
cohorts, larger-volume cohorts and
state-wide (which includes HHAs from
both smaller- and larger-volume
cohorts) respectively. For example, the
difference in benchmark values for Iowa
and Nebraska (two of the four states that
have smaller-volume cohorts) for the
Improvement in Bed Transfers measure
is 13.1 (72.7 for Iowa and 85.8 for
Nebraska) for the smaller-volume cohort
(Table 28), 4.1 (78.1 for Iowa to 82.2 for
Nebraska) for the larger-volume cohort
(Table 29) and 5.5 (77.6 for Iowa to 83.1
for Nebraska) for the state level cohort
(Table 30). We believe that the higher
range for the smaller-volume cohorts is
a result of there being a fewer number
of HHAs in these cohorts.
TABLE 28—SMALLER-VOLUME COHORT BENCHMARKS
State
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AZ
Oasis-Based Measures:
Discharged to Community ......................
Drug Education on All Medications Provided to Patient/Caregiver during all
Episodes of Care .................................
Improvement in Ambulation- Locomotion
Improvement in Bathing ..........................
Improvement in Bed Transferring ...........
Improvement in Dyspnea ........................
Improvement in Management of Oral
Medications .........................................
Improvement in Pain Interfering with Activity .....................................................
Influenza Immunization Received for
Current Flu Season .............................
Pneumococcal Polysaccharide Vaccine
Ever Received .....................................
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FL
IA
MA
MD
NC
NE
TN
77.0
88.8
73.6
82.0
..............
75.1
81.1
79.4
100.0
90.6
82.0
68.8
84.2
100.0
90.5
91.2
80.4
90.4
100.0
72.7
79.5
72.7
81.3
100.0
75.6
71.8
74.1
62.6
..............
..............
..............
..............
..............
98.5
60.1
72.1
55.1
62.5
100.0
84.0
77.4
85.8
80.3
100.0
85.2
81.5
79.0
93.7
63.0
74.0
58.4
62.0
..............
62.8
65.8
58.9
83.2
97.3
82.6
82.3
..............
58.5
78.2
69.0
73.4
89.8
90.8
83.8
..............
89.2
83.6
88.9
95.8
91.5
95.8
95.3
..............
83.6
97.0
100.0
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TABLE 29—LARGER-VOLUME COHORT BENCHMARKS
State
AZ
Oasis-Based Measures:
Discharged to Community ......................
Drug Education on All Medications Provided to Patient/Caregiver during all
Episodes of Care .................................
Improvement in Ambulation- Locomotion
Improvement in Bathing ..........................
Improvement in Bed Transferring ...........
Improvement in Dyspnea ........................
Improvement in Management of Oral
Medications .........................................
Improvement in Pain Interfering with Activity .....................................................
Influenza Immunization Received for
Current Flu Season .............................
Pneumococcal Polysaccharide Vaccine
Ever Received .....................................
FL
IA
MA
MD
NC
NE
TN
WA
82.1
85.6
78.3
81.2
81.1
78.2
80.3
81.0
83.1
99.8
76.4
84.2
76.4
85.9
100.0
92.4
94.2
85.4
90.5
99.9
76.7
81.9
78.1
81.3
100.0
76.1
81.0
80.2
82.2
99.9
76.5
81.0
77.5
85.1
99.7
75.2
78.9
74.5
85.5
99.9
80.8
86.6
82.2
80.7
99.8
77.2
83.5
76.8
84.2
99.7
70.8
77.7
73.5
80.7
69.4
80.5
68.1
73.2
71.7
63.9
68.1
72.2
64.0
88.6
96.7
81.0
89.5
84.4
81.5
86.0
81.7
75.5
88.0
93.3
88.1
90.1
87.9
88.0
95.2
88.2
87.0
92.5
93.6
94.4
93.8
92.1
93.4
97.0
92.7
92.7
TABLE 30—STATE LEVEL COHORT BENCHMARKS
State
AZ
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Oasis-Based Measures:
Discharged to Community ......................
Drug Education on All Medications Provided to Patient/Caregiver during all
Episodes of Care .................................
Improvement in Ambulation- Locomotion
Improvement in Bathing ..........................
Improvement in Bed Transferring ...........
Improvement in Dyspnea ........................
Improvement in Management of Oral
Medications .........................................
Improvement in Pain Interfering with Activity .....................................................
Influenza Immunization Received for
Current Flu Season .............................
Pneumococcal Polysaccharide Vaccine
Ever Received .....................................
The three tables are based on the
analysis using the most current data
available. The results highlight that
there is a greater degree of interstate
variation in the benchmark values for
the cohorts that have fewer HHAs as
compared to the variation in benchmark
values for the cohorts that have a greater
number of HHAs.
We also performed a similar analysis
with the achievement thresholds and
comparing how the individual
benchmarks and achievement
thresholds would fluctuate from one
year to the next for the smaller-volume
cohorts, larger-volume cohorts, and the
state level cohorts. The results of those
analyses were similar.
Based on the analyses that we have
described, we are concerned that if we
separate HHAs into smaller- and largervolume cohorts by state for purposes of
calculating the benchmarks and
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FL
IA
MA
MD
NC
NE
TN
WA
81.8
86.3
77.7
81.9
81.1
78.2
80.5
80.9
83.1
99.8
77.5
84.1
75.9
85.8
100.0
92.1
93.8
84.8
90.5
100.0
76.2
81.8
77.6
81.9
100.0
76.3
80.3
80.1
81.7
99.9
76.5
81.0
77.5
85.1
99.7
75.2
78.9
74.5
85.5
99.9
82.9
84.6
83.1
81.3
99.8
77.9
83.5
77.3
85.8
99.7
70.8
77.7
73.5
80.7
69.1
79.6
67.3
72.0
71.7
64.1
68.3
72.2
64.0
88.1
96.8
81.5
88.4
84.4
81.5
84.3
81.7
75.5
87.6
92.9
88.9
90.1
87.9
88.3
94.4
88.2
87.0
92.9
93.3
94.8
94.2
92.1
93.4
97.0
93.3
92.7
achievement thresholds, HHAs in the
smaller-volume cohorts could be
required to meet performance standards
that are greater than the level of
performance that HHAs in the largervolume cohorts would be required to
achieve. For this reason, we are
proposing to calculate the benchmarks
and achievement thresholds at the state
level rather than at the smaller- and
larger-volume cohort level for all model
years, beginning with CY 2016. This
change will eliminate the increased
variation caused by having few HHAs in
the cohort but still takes into account
that there will be some inter-state
variation in the values due to state
regulatory differences.
We seek public comments on this
proposal.
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2. The Payment Adjustment
Methodology
We finalized in the CY 2016 HH PPS
final rule that we would use a linear
exchange function (LEF) to translate a
competing HHA’s TPS into a valuebased payment adjustment percentage
under the HHVBP Model (80 FR 68686).
We also finalized that we would
calculate the LEF separately for each
smaller-volume cohort and largervolume cohort. In addition, we finalized
that if an HHA does not have a
minimum of 20 episodes of care during
a performance year to generate a
performance score on at least five
measures, we would not include the
HHA in the LEF and we would not
calculate a payment adjustment
percentage for that HHA.
Since the publication of the CY 2016
HH PPS final rule, we have continued
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to evaluate the payment adjustment
methodology using the most recent data
available. We updated our analysis of
the 10 OASIS quality measures and two
claims-based measures using the newly
available 2014 QIES Roll Up File data,
which was not available prior to the
issuance of that final rule.19 We also
determined the size of the cohorts using
the 2014 Quality Episode File based on
OASIS assessments rather than archived
quality data sources that were used in
the CY 2016 rule, whereby the HHAs
reported at least five measures with over
20 episodes of care. Based on this data,
we determined that with respect to
performance year 2016, there were only
three states (AZ, FL, NE) that have more
than 10 HHAs in the smaller-volume
cohort; one state (IA) that has 8–10
HHAs in the smaller-volume cohort,
three states (NC, MA, TN) that have 1–
3 HHAs in the smaller-volume cohort;
and two states (MD, WA) that have no
HHAs in the smaller-volume cohort. In
the CY 2016 HH PPS final rule (80 FR
68664), we finalized that when there are
too few HHAs in the smaller-volume
cohort in each state to compete in a fair
manner, the HHAs in that cohort would
be included in the larger-volume cohort
for purposes of calculating their
payment adjustment percentage. The CY
2016 rule further defines too few as
when there is only one or two HHAs
competing within a smaller-volume
cohort in a given state.
We also used the more current data
source mentioned above to analyze the
effects of outliers on the LEF. As
indicated by the payment distributions
set forth in Table 23 of this rule, the LEF
is designed so that the majority of the
payment adjustment values fall closer to
the median and only a small percentage
of HHAs receive adjustments at the
higher and lower ends of the
distribution. However, when we looked
at the more recent data, we discovered
that if there are only three or four HHAs
in the cohort, one HHA outlier could
skew the payment adjustments and
deviate the payment distribution from
the intended design of the LEF payment
methodology where HHAs should fall
close to the median of the payment
distribution. For example, if there are
only three HHAs in the cohort, we
concluded that there is a high likelihood
that those HHAs would have payment
adjustments of ¥2.5 percent, ¥2.0
percent and +4.5 percent when the
maximum payment adjustment is 5
percent, none falling close to the mean,
with the result that those HHAs would
19 We did not update our analysis of the
HHCAHPS measures because more recent data was
not available.
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receive payment adjustments at the
higher or lower ends of the distribution.
As the size of the cohort increases, we
determined that this became less of an
issue, and that the majority of the HHAs
would have payment adjustments that
are close to the median. This is
illustrated in the payment distribution
in Table 23 of this rule. Under the
payment distribution for the largervolume cohorts, 80 percent of the HHAs
in AZ, IA, FL and NE would receive a
payment adjustment ranging from ¥2.2
percent to +2.2 percent when the
maximum payment adjustment is 5
percent (See state level cohort in Table
23). Arizona is a state that has a smallervolume cohort with only nine HHAs but
its payment distribution is comparable,
ranging from ¥1 percent to +1 percent
even with one outlier that is at 5
percent.
In order to determine the minimum
number of HHAs that would have to be
in a smaller-volume cohort in order to
insulate that cohort from the effect of
outliers, we analyzed performance
results related to the OASIS and claimsbased measures, as well as HHCAHPS,
using 2013 and 2014 data. We
specifically simulated the impact that
outliers would have on cohort sizes
ranging from four HHAs to twelve
HHAs. We found that the LEF was less
susceptible to large variation from
outlier impacts once the cohort size
reached a minimum of eight HHAs. We
also found that a minimum of eight
HHAs would allow for four states with
smaller-volume cohorts to have 80
percent of their payment adjustments
fall between ¥2.3 percent and + 2.4
percent. As a result of this analysis, we
are proposing that a smaller-volume
cohort have a minimum eight HHAs in
order for the HHAs in that cohort to be
compared only against each other, and
not against the HHAs in the largervolume cohort. We believe this proposal
would better mitigate the impact of
outliers as compared to our current
policy, while also enabling us to
evaluate the impact of the Model on
competition between smaller-volume
HHAs.
We are also proposing that if a
smaller-volume cohort in a state has
fewer than eight HHAs, those HHAs
would be included in the larger-volume
cohort for that state for purposes of
calculating the LEF and payment
adjustment percentages. If finalized, this
change would apply to the CY 2018
payment adjustments and thereafter. We
will continue to analyze and review the
most current cohort size data as it
becomes available. We seek public
comments on this proposal.
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C. Quality Measure Proposals
In the CY 2016 HH PPS final rule, we
finalized a set of quality measures in
Figure 4a: Final PY1 Measures and
Figure 4b: Final PY1 New Measures (80
FR 68671–68673) for the HHVBP Model
to be used in the first performance year
(PY1), referred to as the ‘‘starter set’’.
The measures were selected for the
Model using the following guiding
principles: (1) Use a broad measure set
that captures the complexity of the
services HHAs provide; (2) Incorporate
the flexibility for future inclusion of the
Improving Medicare Post-Acute Care
Transformation (IMPACT) Act of 2014
measures that cut across post-acute care
settings; (3) Develop ‘second generation’
(of the HHVBP Model) measures of
patient outcomes, health and functional
status, shared decision making, and
patient activation; (4) Include a balance
of process, outcome and patient
experience measures; (5) Advance the
ability to measure cost and value; (6)
Add measures for appropriateness or
overuse; and (7) Promote infrastructure
investments. This set of quality
measures encompasses the multiple
National Quality Strategy (NQS)
domains 20 (80 FR 68668). The NQS
domains include six priority areas
identified in the CY 2016 HH PPS final
rule (80 FR 68668) as the CMS
Framework for Quality Measurement
Mapping. These areas are: (1) Clinical
quality of care, (2) Care coordination, (3)
Population & community health, (4)
Person- and Caregiver-centered
experience and outcomes, (5) Safety,
and (6) Efficiency and cost reduction.
Figures 5 and 6 of the CY 2016 HH PPS
final rule identified 15 outcome
measures (five from the HHCAHPS,
eight from OASIS, and two from the
Chronic Care Warehouse (claims)), and
nine process measures (six from OASIS,
and three New Measures, which were
not previously reported in the home
health setting).
During implementation of the Model,
we determined that four of the measures
finalized for PY1 require further
consideration before inclusion in the
HHVBP Model measure set as described
below. Specifically, we are proposing to
remove the following measures, as
described in Figure 4a of the CY 2016
HH PPS final rule, from the set of
applicable measures: (1) Care
Management: Types and Sources of
Assistance; (2) Prior Functioning ADL/
IADL; (3) Influenza Vaccine Data
Collection Period: Does this episode of
care include any dates on or between
20 2015 Annual Report to Congress, https://
www.ahrq.gov/workingforquality/reports/annualreports/nqs2015annlrpt.htm.
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Federal Register / Vol. 81, No. 128 / Tuesday, July 5, 2016 / Proposed Rules
October 1 and March 31?; and (4)
Reason Pneumococcal Vaccine Not
Received. We are proposing to remove
these four measures, for the reasons
discussed below, beginning with the CY
2016 Performance Year (PY1)
calculations, and believe this will not
cause substantial change in the first
annual payment adjustment that will
occur in CY 2018, as each measure is
equally weighted and will not be
represented in the calculations. The
proposed revisions to the measure set,
as set forth in Table 31 would be
applicable to each performance year
subject to any changes made through
future rulemaking.
We are proposing to remove the ‘‘Care
Management: Types and Sources of
Assistance’’ measure because (1) a
numerator and denominator for the
measure were not made available in the
CY2016 HH PPS final rule; and (2) the
potential OASIS items that could be
utilized in the development of the
measure were not fully specified in the
CY 2016 HH PPS final rule. We want to
further consider the appropriate
numerator and denominator for the
OASIS data source before proposing the
inclusion of this measure in the HHVBP
Model.
We are proposing to remove the
‘‘Prior Functioning ADL/IADL’’ measure
because (1) the NQF endorsed measure
(NQF0430) included in the 2016 HH
PPS final rule does not apply to home
health agencies; and (2) the NQF
endorsed measure (NQF0430) refers to a
measure that utilizes the AM–PAC
(Activity Measure for Post-Acute Care)
tool that is not currently (and has never
been) collected by home health
agencies.
We are proposing to remove the
‘‘Influenza Vaccine Data Collection
Period: Does this episode of care
include any dates on or between
October 1 and March 31?’’ measure
because this datum element (OASIS
item M1041) is used to calculate another
HHVBP measure ‘‘Influenza
Immunization Received for Current Flu
Season’’ and was not designed as an
additional and separate measure of
performance.
We are proposing to remove the
‘‘Reason Pneumococcal Vaccine Not
Received’’ measure because (1) these
data are reported as an element of the
record for clinical decision making and
inform agency policy (that is, so that the
agency knows what proportion of its
patients did not receive the vaccine
because it was contraindicated
(harmful) for the patient or that the
patient chose to not receive the
vaccine); and (2) this measure itemizes
the reason for the removal of
individuals for whom the vaccine is not
43751
appropriate, which is already included
in the numerator of the ‘‘Pneumococcal
Polysaccharide Vaccine Ever Received’’
measure also included in the HHVBP
Model.
Because the starter set is defined as
the quality measures selected for the
first year of the Model only, we propose
to revise § 484.315 to refer to ‘‘a set of
quality measures’’ rather than ‘‘a starter
set of quality measures’’ and to revise
§ 484.320 (a), (b), (c), and (d) to remove
the phrase ‘‘in the starter set’’. We are
also proposing to delete the definition of
‘‘Starter set’’ in § 484.305 because that
definition would no longer be used in
the HHVBP Model regulations following
the proposed revisions to §§ 484.315
and 484.320.
The proposed revised set of
applicable measures is presented in
Table 31, which excludes the four
measures we propose to be removed. We
propose that this measure set will be
applicable to PY1 and each subsequent
performance year until such time that
another set of applicable measures, or
changes to this measure set, are
proposed and finalized in future
rulemaking. Moving forward, we plan to
utilize an implementation contractor
who will invite a group of measure
experts to provide advice on the
adjustment of the current measure set.
TABLE 31—PROPOSED MEASURE SET FOR THE HHVBP MODEL 21
NQS domains
Identifier
Data source
Numerator
Improvement in AmbulationLocomotion.
Outcome .............
NQF0167 .....................
OASIS (M1860) ..
Clinical Quality of Care ..........
Improvement in Bed Transferring.
Outcome .............
NQF0175 .....................
OASIS (M1850) ..
Clinical Quality of Care ..........
Improvement in Bathing ........
Outcome .............
NQF0174 .....................
OASIS (M1830) ..
Clinical Quality of Care ..........
sradovich on DSK3GDR082PROD with PROPOSALS2
Measure type
Clinical Quality of Care ..........
Measure title
Improvement in Dyspnea ......
Outcome .............
NA ................................
OASIS (M1400) ..
Number of home health episodes of care where the
value recorded on the discharge assessment indicates less impairment in
ambulation/locomotion at
discharge than at the start
(or resumption) of care.
Number of home health episodes of care where the
value recorded on the discharge assessment indicates less impairment in
bed transferring at discharge than at the start (or
resumption) of care.
Number of home health episodes of care where the
value recorded on the discharge assessment indicates less impairment in
bathing at discharge than
at the start (or resumption)
of care.
Number of home health episodes of care where the
discharge assessment indicates less dyspnea at discharge than at start (or resumption) of care.
21 For more detailed information on the proposed
measures utilizing OASIS refer to the OASIS–C1/
ICD–9, Changed Items & Data Collection Resources
dated September 3, 2014 available at
www.oasisanswers.com/
LiteratureRetrieve.aspx?ID=215074.
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For NQF endorsed measures see The NQF Quality
Positioning System available at https://
www.qualityforum.org/QPS. For non-NQF measures
using OASIS see links for data tables related to
OASIS measures at https://www.cms.gov/Medicare/
Quality-Initiatives-Patient-Assessment-Instruments/
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Denominator
Number of home health episodes of care ending with
a discharge during the reporting period, other than
those covered by generic
or measure-specific exclusions.
Number of home health episodes of care ending with
a discharge during the reporting period, other than
those covered by generic
or measure-specific exclusions.
Number of home health episodes of care ending with
a discharge during the reporting period, other than
those covered by generic
or measure-specific exclusions.
Number of home health episodes of care ending with
a discharge during the reporting period, other than
those covered by generic
or measure-specific exclusions.
HomeHealthQualityInits/
HHQIQualityMeasures.html. For information on
HHCAHPS measures see https://
homehealthcahps.org/SurveyandProtocols/
SurveyMaterials.aspx.
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Federal Register / Vol. 81, No. 128 / Tuesday, July 5, 2016 / Proposed Rules
TABLE 31—PROPOSED MEASURE SET FOR THE HHVBP MODEL 21—Continued
NQS domains
Measure type
Identifier
Data source
Numerator
Denominator
Discharged to Community .....
Outcome .............
NA ................................
OASIS (M2420) ..
Number of home health episodes where the assessment completed at the discharge indicates the patient
remained in the community
after discharge.
Efficiency & Cost Reduction ..
Acute Care Hospitalization:
Unplanned Hospitalization
during first 60 days of
Home Health.
Outcome .............
NQF0171 .....................
CCW (Claims) ....
Number of home health stays
for patients who have a
Medicare claim for an unplanned admission to an
acute care hospital in the
60 days following the start
of the home health stay.
Efficiency & Cost Reduction ..
Emergency Department Use
without Hospitalization.
Outcome .............
NQF0173 .....................
CCW (Claims) ....
Patient Safety ........................
Improvement in Pain Interfering with Activity.
Outcome .............
NQF0177 .....................
OASIS (M1242) ..
Patient Safety ........................
Improvement in Management
of Oral Medications.
Outcome .............
NQF0176 .....................
OASIS (M2020) ..
Influenza Immunization Received for Current Flu Season.
Process ..............
NQF0522 .....................
OASIS (M1046) ..
Population/Community Health
Pneumococcal Polysaccharide Vaccine Ever
Received.
Process ..............
NQF0525 .....................
OASIS (M1051) ..
Number of home health stays
for patients who have a
Medicare claim for outpatient emergency department use and no claims for
acute care hospitalization
in the 60 days following the
start of the home health
stay.
Number of home health episodes of care where the
value recorded on the discharge assessment indicates less frequent pain at
discharge than at the start
(or resumption) of care.
Number of home health episodes of care where the
value recorded on the discharge assessment indicates less impairment in
taking oral medications correctly at discharge than at
start (or resumption) of
care.
Number of home health episodes during which patients (a) received vaccination from the HHA or (b)
had received vaccination
from HHA during earlier
episode of care, or (c) was
determined to have received vaccination from another provider.
Number of home health episodes during which patients were determined to
have ever received Pneumococcal Polysaccharide
Vaccine (PPV).
Number of home health episodes of care ending with
discharge or transfer to inpatient facility during the
reporting period, other than
those covered by generic
or measure-specific exclusions.
Number of home health stays
that begin during the 12month observation period.
A home health stay is a
sequence of home health
payment episodes separated from other home
health payment episodes
by at least 60 days.
Number of home health stays
that begin during the 12month observation period.
A home health stay is a
sequence of home health
payment episodes separated from other home
health payment episodes
by at least 60 days.
Number of home health episodes of care ending with
a discharge during the reporting period, other than
those covered by generic
or measure-specific exclusions.
Number of home health episodes of care ending with
a discharge during the reporting period, other than
those covered by generic
or measure-specific exclusions.
Population/Community Health
Clinical Quality of Care ..........
sradovich on DSK3GDR082PROD with PROPOSALS2
Measure title
Communication & Care Coordination.
Drug Education on All Medications Provided to Patient/
Caregiver during all Episodes of Care.
Process ..............
NA ................................
OASIS (M2015) ..
Patient & Caregiver-Centered
Experience.
Patient & Caregiver-Centered
Experience.
Patient & Caregiver-Centered
Experience.
Patient & Caregiver-Centered
Experience.
Patient & Caregiver-Centered
Experience.
Care of Patients ....................
Outcome .............
Communications between
Providers and Patients.
Specific Care Issues .............
Outcome .............
CAHPS ...............
NA ..........................................
NA.
Outcome .............
CAHPS ...............
NA ..........................................
NA.
Outcome .............
CAHPS ...............
NA ..........................................
NA.
Outcome .............
CAHPS ...............
NA ..........................................
NA.
VerDate Sep<11>2014
Overall rating of home health
care.
Willingness to recommend
the agency.
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CAHPS ...............
Fmt 4701
Sfmt 4702
Number of home health episodes of care during which
patient/caregiver was instructed on how to monitor
the effectiveness of drug
therapy, how to recognize
potential adverse effects,
and how and when to report problems (since the
previous OASIS assessment).
NA ..........................................
E:\FR\FM\05JYP2.SGM
05JYP2
Number of home health episodes of care ending with
discharge, or transfer to inpatient facility during the
reporting period, other than
those covered by generic
or measure-specific exclusions.
Number of home health episodes of care ending with
discharge or transfer to inpatient facility during the
reporting period, other than
those covered by generic
or measure-specific exclusions.
Number of home health episodes of care ending with
a discharge or transfer to
inpatient facility during the
reporting period, other than
those covered by generic
or measure-specific exclusions.
NA.
Federal Register / Vol. 81, No. 128 / Tuesday, July 5, 2016 / Proposed Rules
43753
TABLE 31—PROPOSED MEASURE SET FOR THE HHVBP MODEL 21—Continued
NQS domains
Measure title
Measure type
Identifier
Data source
Influenza Vaccination Coverage for Home Health
Care Personnel.
Process ..............
NQF0431 (Used in
other care settings,
not Home Health).
Reported by
HHAs through
Web Portal.
Population/Community Health
Herpes zoster (Shingles) vaccination: Has the patient
ever received the shingles
vaccination?.
Process ..............
NA ................................
Reported by
HHAs through
Web Portal.
Communication & Care Coordination.
sradovich on DSK3GDR082PROD with PROPOSALS2
Population/Community Health
Advance Care Plan ...............
Process ..............
NQF0326 .....................
Reported by
HHAs through
Web Portal.
In the CY 2016 HH PPS final rule, we
finalized that HHAs will be required to
begin reporting data on each of the three
New Measures no later than October 7,
2016 for the period July 2016 through
September 2016 and quarterly
thereafter. We now propose to require
annual, rather than quarterly reporting
for one of the three New Measures,
‘‘Influenza Vaccination Coverage for
Home Health Personnel,’’ with the first
annual submission in April 2017 for
PY2. Specifically, we are proposing to
require an annual submission in April
for the prior 6-month reporting period of
October 1–March 31 to coincide with
the flu season. Under this proposal, for
PY1, the HHA would report on this
measure in October 2016 and January
2017. HHAs would report on this
measure in April 2017 for PY2 and
annually in April thereafter. We believe
that changing the reporting and
submission periods for this measure
from quarterly to annually would avoid
the need for HHAs to have to report
zeroes in multiple data fields for the two
quarters (July through September, and
April through June) that fall outside of
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18:04 Jul 01, 2016
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the parameters of the denominator
(October through March).
We are not proposing to change the
quarterly reporting and submission
requirements as set forth in the CY 2016
HH PPS final rule (80 FR 68674–68678)
for the other two New Measures,
‘‘Advanced Care Planning’’, and
‘‘Herpes zoster (Shingles) vaccination:
Has the patient ever received the
shingles vaccination?’’
We are also proposing to increase the
timeframe for submitting New Measures
data from seven calendar days (80 FR
68675–68678) to fifteen calendar days
following the end of each reporting
period to account for weekends and
holidays.
We invite public comment on our
proposals.
D. Appeals Process Proposal
In the CY 2016 HH PPS final rule (80
FR 68689), we stated that we intended
to propose an appeals mechanism in
future rulemaking prior to the
application of the first payment
adjustments scheduled for CY 2018. We
are proposing an appeals process for the
HHVBP Model which includes the
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Numerator
Denominator
Healthcare personnel in the
denominator population
who during the time from
October 1 (or when the
vaccine became available)
through March 31 of the
following year: (a) received
an influenza vaccination
administered at the
healthcare facility, or reported in writing or provided documentation that
influenza vaccination was
received elsewhere: or (b)
were determined to have a
medical contraindication/
condition of severe allergic
reaction to eggs or to other
components of the vaccine
or history of Guillain-Barre
Syndrome within 6 weeks
after a previous influenza
vaccination; or (c) declined
influenza vaccination; or (d)
persons with unknown vaccination status or who do
not otherwise meet any of
the definitions of the
above-mentioned numerator categories.
Total number of Medicare
beneficiaries aged 60 years
and over who report having
ever received zoster vaccine (shingles vaccine).
Patients who have an advance care plan or surrogate decision maker documented in the medical
record or documentation in
the medical record that an
advanced care plan was
discussed but the patient
did not wish or was not
able to name a surrogate
decision maker or provide
an advance care plan.
Number of healthcare personnel who are working in
the healthcare facility for at
least 1 working day between October 1 and
March 31 of the following
year, regardless of clinical
responsibility or patient
contact.
Total number of Medicare
beneficiaries aged 60 years
and over receiving services
from the HHA.
All patients aged 65 years
and older.
period to review and request
recalculation of both the Interim
Performance Reports and the Annual
TPS and Payment Adjustment Reports,
as finalized in the CY 2016 HH PPS
final rule (80 FR 68688–68689) and
subject to the modifications we are
proposing here, and reconsideration
request process for the Annual TPS and
Payment Adjustment Report only, as
described later in this section, which
may only occur after an HHA has first
submitted a recalculation request for the
Annual TPS and Payment Adjustment
Report.
As finalized in the CY 2016 HH PPS
final rule, HHAs have the opportunity to
review their Interim Performance Report
following each quarterly posting. The
Interim Performance Reports are posted
on the HHVBP Secure Portal quarterly,
setting forth the HHA’s measure scores
based on available data to date. The first
Interim Performance Report will be
provided to all competing HHAs in July
2016 and will include performance
scores for the OASIS-based measures for
the first quarter of CY 2016. See Table
32 for data provided in each report. The
quarterly Interim Performance Reports
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will provide competing HHAs with the
opportunity to identify and correct
calculation errors and resolve
discrepancies, thereby minimizing
challenges to the annual performance
scores linked to payment adjustment.
Competing HHAs also have the
opportunity to review their Annual TPS
and Payment Adjustment Report. We
will inform each competing HHA of its
TPS and payment adjustment
percentage in an Annual TPS and
Payment Adjustment Report provided
prior to the calendar year for which the
payment adjustment will be applied.
The annual TPS will be calculated
based on the calculation of performance
measures contained in the Interim
Performance Reports that have already
been received by the HHAs for the
performance year.
We are proposing specific timeframes
for the submission of recalculation and
reconsideration requests to ensure that
the final payment adjustment
percentage for each competing
Medicare-certified HHA can be
submitted to the Fiscal Intermediary
Shared Systems in time to allow for
application of the payment adjustments
beginning in January of the following
calendar year. We believe HHVBP
payment adjustments should be timely
and that the appeals process should be
designed so that determinations on
recalculations and reconsiderations can
be made in advance of the applicable
payment year to reduce burden and
uncertainty for competing HHAs.
In this proposed rule, we are
proposing to add new § 484.335, titled
‘‘Appeals Process for the Home Health
Value-Based Purchasing Model,’’ which
would codify the recalculation request
process finalized in the CY 2016 HH
PPS final rule and also a proposed
reconsideration request process for the
Annual TPS and Payment Adjustment
Report. The first level of this appeals
process would be the recalculation
request process, as finalized in the CY
2016 HH PPS final rule and subject to
the proposed modifications described
later in this section. We are proposing
that the reconsideration request process
for the Annual TPS and Payment
Adjustment Report would complete the
appeals process, and would be available
only when an HHA has first submitted
a recalculation request for the Annual
TPS and Payment Adjustment Report
under the process finalized in the CY
2016 HH PPS final rule, subject to the
modifications we are proposing here.
We believe that this proposed appeals
process will allow the HHAs to seek
timely corrections for errors that may be
introduced during the Interim
Performance Reports that could affect an
HHA’s payments.
To inform our proposal for an appeals
process under the HHVBP Model we
reviewed the appeals policies for two
CMS programs that are similar in their
program goals to the HHVBP Model, the
Medicare Shared Savings Program 22
and Hospital Value-Based Purchasing
Program,23 as well as the appeals policy
for the Comprehensive Care for Joint
Replacement Model 24 that is being
tested by the Center for Medicare and
Medicaid Innovation (CMMI).
Under section 1115A(d) of the Act,
there is no administrative or judicial
review under sections 1869 or 1878 of
the Act or otherwise for the following:
• The selection of models for testing
or expansion under section 1115A of the
Act.
• The selection of organizations, sites
or participants to test those models
selected.
• The elements, parameters, scope,
and duration of such models for testing
or dissemination.
• Determinations regarding budget
neutrality under section 1115A(b)(3) of
the Act.
• The termination or modification of
the design and implementation of a
model under section 1115A(b)(3)(B) of
the Act.
• Decisions about expansion of the
duration and scope of a model under
section 1115A(c) of the Act, including
the determination that a model is not
expected to meet criteria described in
section 1115A(c)(1) or (2) of the Act.
TABLE 32—HHVBP MODEL PERFORMANCE REPORT DATA SCHEDULE
Publication
date
OASIS-Based measures and
new measures
Claims- and HHCAHPS-based measures
Interim Performance Scores .....................
January .......
Interim Performance Scores .....................
April .............
3 quarters of previous PY (9 months);
[Jan–Sept].
12 months of previous PY [Jan–Dec] ......
Interim Performance Scores .....................
July ..............
2 quarters of previous PY (6 months);
[Jan–Jun].
3 quarters of previous PY (9 months);
[Jan–Sept].
12 months of previous PY; [Jan–Dec].
Interim Performance Scores .....................
October .......
Annual TPS and Payment Adjustment
Percentage.
August .........
Entire 12 months of previous PY; [Jan–Dec].
Annual TPS and Payment Adjustment
Percentage; (Final).
sradovich on DSK3GDR082PROD with PROPOSALS2
Report type
November ....
Entire 12 months of previous PY [Jan–Dec] after all recalculations and reconsideration requests processed.
22 Title 42—Public Health, Chapter IV—Centers
for Medicare & Medicaid Services, Department of
Health and Human Services, Subchapter B, Part
425—Medicare Shared Savings Program, Subpart
I—Reconsideration Review Process. (https://
www.ecfr.gov/cgi-bin/text-idx?SID=880f6bd18190
4fc648f0e9a885103dba&mc=true&node=
sp42.3.425.i&rgn=div6)
23 Title 42—Public Health, Chapter IV—Centers
for Medicare & Medicaid Services, Department of
VerDate Sep<11>2014
18:04 Jul 01, 2016
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1st quarter of next PY (3 months); [Jan–
Mar].
2 quarters of next PY (6 months); [Jan–
Jun].
Health and Human Services, Subchapter B, Part
412—Prospective Payment System for Inpatient
Hospital Services, Subpart I—Adjustments to the
Base Operating DRG Payment Amounts Under the
Prospective Payment Systems for Inpatient
Operating Costs (https://www.ecfr.gov/cgi-bin/textidx?SID=dd15db0a13792035b9b42b342270fad6
&mc=true&node=sg42.2.412_1155_6412_1159.sg4
&rgn=div7)
PO 00000
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Fmt 4701
Sfmt 4702
1st quarter of next PY (3 months); [Jan–
Mar].
24 Title 42—Public Health, Chapter IV—Centers
for Medicare & Medicaid Services, Department of
Health and Human Services, Subchapter H—Health
Care Infrastructure and Model Programs, Part 510—
Comprehensive Care for Joint Replacement Model.
(https://www.ecfr.gov/cgi-bin/text-idx?SID=a18d6f
5665d1fbf2e1ae955e1bf1b97c&mc=true&node=pt
42.5.510&rgn=div5)
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Federal Register / Vol. 81, No. 128 / Tuesday, July 5, 2016 / Proposed Rules
change, altering performance measure
scores or the HHA’s TPS;
HHAs may submit recalculation
• Conduct a review of quality data if
requests for both the Interim
recalculation results in a performance
Performance Reports and the Annual
score or TPS change, and recalculate the
TPS and Payment Adjustment Report
TPS using the corrected performance
via a form located on the HHVBP Secure
data if an error is found; and,
Portal that is only accessible to the
• Provide a formal response to the
competing HHAs. The request form
HHA contact, using the contact
would be entered by a person who has
information provided in the
legal authority to sign on behalf of the
recalculation request, notifying the HHA
HHA and, as finalized in the CY 2016
of the outcome of the review and
HH PPS final rule, must be submitted
recalculation process.
within 30 calendar days of the posting
We anticipate providing this response
of each performance report on the
as soon as administratively feasible
model-specific Web site. For the reasons following the submission of the request.
discussed later in this section, we are
We will not be responsible for
proposing to change this policy to
providing HHAs with the underlying
require that recalculation requests for
source data utilized to generate
both the Interim Performance Report
performance measure scores because
and the Annual TPS and Payment
HHAs have access to this data via the
Adjustment Report be submitted within QIES system.
15 calendar days of the posting of the
We are proposing that recalculation
Interim Performance Report and the
requests for the Interim Performance
Annual TPS and Payment Adjustment
Reports must be submitted within 15
Report on the HHVBP Secure Portal
calendar days of these reports being
instead of 30 calendar days.
posted on the HHVBP Secure Portal,
For both the Interim Performance
rather than 30 calendar days as finalized
Reports and the Annual TPS and
in the CY 2016 HH PPS final rule. We
Payment Adjustment Report, requests
believe this would allow recalculations
for recalculation must contain specific
of the Interim Performance Reports
information, as set forth in the CY 2016
posted in July to be completed prior to
HH PPS final rule (80 FR 68688). We are the posting of the Annual TPS and
proposing that requests for
Payment Adjustment Report in August.
reconsideration of the Annual TPS and
We are proposing that recalculation
Payment Adjustment Report must also
requests for the TPS or payment
contain this same information.
adjustment percentage must be
• The provider’s name, address
submitted within 15 calendar days of
associated with the services delivered,
the Annual TPS and Payment
and CMS Certification Number (CCN);
Adjustment Report being posted on the
• The basis for requesting
HHVBP Secure Portal, rather than 30
recalculation to include the specific
days as finalized in the CY 2016 HH
quality measure data that the HHA
PPS final rule. We are proposing to
believes is inaccurate or the calculation
shorten this timeframe to allow for a
the HHA believes is incorrect;
second level of appeals, the proposed
• Contact information for a person at
reconsideration request process, to be
the HHA with whom CMS or its agent
completed prior to the generation of the
can communicate about this request,
final data files containing the payment
including name, email address,
adjustment percentage for each
telephone number, and mailing address competing Medicare-certified HHA and
(must include physical address, not just the submission of those data files to the
a post office box); and,
Fiscal Intermediary Share Systems. We
• A copy of any supporting
contemplated longer timeframes for the
documentation the HHA wishes to
submission of both recalculation and
submit in electronic form via the model- reconsideration requests for the Annual
specific Web page.
TPS and Payment Adjustment Reports,
Following receipt of a request for
but believe that this would result in
recalculation of an Interim Performance appeals not being resolved in advance of
Report or the Annual TPS and Payment
the payment adjustments being applied
Adjustment Report, CMS or its agent
beginning in January of the following
will:
calendar year. We invite comments on
• Provide an email acknowledgement, this proposed timeframe for
using the contact information provided
recalculation requests, as well as any
in the recalculation request, to the HHA alternatives.
contact notifying the HHA that the
2. Reconsideration
request has been received;
We are proposing that if we determine
• Review the request to determine
that the calculation was correct and
validity, and determine whether the
deny the HHA request for recalculation
recalculation request results in a score
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1. Recalculation
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43755
of the Annual TPS and Payment
Adjustment Report, or if the HHA
disagrees with the results of a CMS
recalculation of such report, the HHA
may submit a reconsideration request
for the Annual TPS and Payment
Adjustment Report. The reconsideration
request and supporting documentation
would be required to be submitted via
the form on the HHVBP Secure Portal
within 15 calendar days of CMS’
notification to the HHA contact of the
outcome of the recalculation request for
the Annual TPS and Payment
Adjustment Report.
We propose that an HHA may request
reconsideration of the outcome of a
recalculation request for its Annual TPS
and Payment Adjustment Report only.
We believe that the ability to review the
Interim Performance Reports and submit
recalculation requests on a quarterly
basis provides competing HHAs with a
mechanism to address potential errors
in advance of receiving their annual
TPS and payment adjustment
percentage. Therefore, we expect that in
many cases, the reconsideration request
process proposed in this rule would
result in a mechanical review of the
application of the formulas for the TPS
and the LEF, which could result in the
determination that a formula was not
accurately applied. Reconsiderations
would be conducted by a CMS official
who was not involved with the original
recalculation request.
We are proposing that an HHA must
submit the reconsideration request and
supporting documentation via the
HHVBP Secure Portal within 15
calendar days of CMS’ notification to
the HHA contact of the outcome of the
recalculation process so that a decision
on the reconsideration can be made
prior to the generation of the final data
files containing the payment adjustment
percentage for each competing
Medicare-certified HHA and the
submission of those data files to the
Fiscal Intermediary Share Systems. We
believe that this would allow for
finalization of the interim performance
scores, TPS, and annual payment
adjustment percentages in advance of
the application of the payment
adjustments for the applicable
performance year. As noted above, we
contemplated longer timeframes for the
submission of both recalculation and
reconsideration requests, but believe
this would result in appeals not being
resolved in advance of the payment
adjustments being applied beginning in
January of the following calendar year.
CMS invites comments on its proposed
timeframe for reconsideration requests,
as well as any alternatives.
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We finalized in the CY 2016 HH PPS
final rule (80 FR 68688) that the final
TPS and payment adjustment
percentage would be provided to
competing HHAs in a final report no
later than 60 calendar days in advance
of the payment adjustment taking effect.
We are now proposing that the final TPS
and payment adjustment percentage be
provided to competing HHAs in a final
report no later than 30 calendar days in
advance of the payment adjustment
taking effect to account for unforeseen
delays that could occur between the
time the Annual TPS and Payment
Adjustment Reports are posted and the
appeals process is completed.
We solicit comments on our proposals
related to the appeals process for the
HHVBP Model described in this section
and the associated proposed regulation
text at § 484.335.
E. Public Display of Total Performance
Scores for the HHVBP Model
In the CY 2016 HH PPS final rule (80
FR 68658), we stated that one of the
three goals of the HHVBP Model is to
‘‘Enhance current public reporting
processes’’. Annual publicly-available
performance reports would be a means
of developing greater transparency of
Medicare data on quality and aligning
the competitive forces within the market
to deliver care based on value over
volume. The publicly-reported reports
will inform home health industry
stakeholders (consumers, physicians,
hospitals) as well as all competing
HHAs delivering care to Medicare
beneficiaries within selected state
boundaries on their level of quality
relative to both their peers and their
own past performance. These public
reports would provide home health
industry stakeholders, including
providers and suppliers that refer their
patients to HHAs, an opportunity to
confirm that the beneficiaries they are
referring for home health services are
being provided the best possible quality
of care available.
We received support via public
comments to publicly report the HHVBP
Model performance data because they
would inform industry stakeholders of
quality improvements. These comments
noted several areas of value in
performance data. Specifically,
commenters suggested that public
reports would permit providers to direct
patients to a source of information about
higher-performing HHAs based on
quality reports. Commenters offered that
to the extent possible, accurate
comparable data will encourage HHAs
to improve care delivery and patient
outcomes, while better predicting and
managing quality performance and
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payment updates. Although competing
HHAs have direct technical support and
other tools to encourage best practices,
we believe public reporting of their
Total Performance Score will encourage
providers and patients to utilize this
information when selecting a HHA to
provide quality care.
We have employed a variety of means
to ensure that we maintain transparency
while developing and implementing the
HHVBP Model. This same care is being
taken as we plan public reporting in
collaboration with other CMS
components that use many of the same
quality measures. We continue to
engage and inform stakeholders about
various aspects of the HHVBP Model
through CMS Open Door Forums and
updates to the HHVBP Model
Innovation Center Web page (https://
innovation.cms.gov/initiatives/homehealth-value-based-purchasing-model).
We have held several webinars since
December 2015 to educate competing
HHAs. Topics of the webinars ranged
from an overview of the HHVBP Model
to specific content areas addressed in
the CY 2016 HH PPS final rule. The
primary purpose of the focused
attention provided to the competing
HHAs through the HHVBP learning
systems and webinars is to facilitate
direct communication, sharing of
information, and collaboration.
Section 1895(b)(3)(B)(v) of the Act
requires HHAs to submit patient-level
quality of care data using the Outcome
and Information Assessment Set
(OASIS) and the Home Health
Consumer Assessment of Health Care
Providers and Systems (HHCAHPS).
Section 1895(b)(3)(B)(v)(III) of the Act
states that this quality data is to be made
available to the public. Thus, home
health agencies have been required to
collect OASIS data since 1999 and
report HHCAHPS data since 2012. Use
of OASIS measures for the HHVBP
Model logically follows, as the
validation through experience creates
greater efficiency than constructing an
entirely new set of measures.
We are considering various public
reporting platforms for the HHVBP
Model including Home Health Compare
(HHC) and the Center for Medicare and
Medicaid Innovation (CMMI) Web page
as a vehicle for maintaining information
in a centralized location and making
information available over the Internet.
We believe the public reporting of
competing HHAs’ performance scores
under the HHVBP Model supports our
continuing efforts to empower
consumers by providing more
information to help them make health
care decisions, while also encouraging
providers to strive for higher levels of
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quality. As the public reporting
mechanism for the HHVBP Model is
being developed, we are considering
which data elements reported will be
meaningful to stakeholders and may
inform the selection of HHAs for care.
We are considering public reporting
for the HHVBP Model, beginning no
earlier than CY 2019, to allow analysis
of at least eight quarters of performance
data for the Model and the opportunity
to compare how those results align with
other publicly reported quality data. We
are encouraged by the previous
stakeholder comments and support for
public reporting that could assist
patients, physicians, discharge planners,
and other referral sources to choose
higher-performing HHAs.
V. Proposed Updates to the Home
Health Care Quality Reporting Program
(HH QRP)
A. Background and Statutory Authority
Section 1895(b)(3)(B)(v)(II) of the Act
requires that for 2007 and subsequent
years, each HHA submit to the Secretary
in a form and manner, and at a time,
specified by the Secretary, such data
that the Secretary determines are
appropriate for the measurement of
health care quality. To the extent that an
HHA does not submit data in
accordance with this clause, the
Secretary is directed to reduce the home
health market basket percentage
increase applicable to the HHA for such
year by 2 percentage points. As
provided at section 1895(b)(3)(B)(vi) of
the Act, depending on the market basket
percentage for a particular year, the 2
percentage point reduction under
section 1895(b)(3)(B)(v)(I) of the Act
may result in this percentage increase,
after application of the productivity
adjustment under section
1895(b)(3)(B)(vi)(I) of the Act, being less
than 0.0 percent for a year, and may
result in payment rates under the Home
Health PPS for a year being less than
payment rates for the preceding year.
The Improving Medicare Post-Acute
Care Transformation Act of 2014 (the
IMPACT Act) imposed new data
reporting requirements for certain postacute care (PAC) providers, including
HHAs. For more information on the
statutory background of the IMPACT
Act, please refer to the CY 2016 HH PPS
final rule (80 FR 68690 through 68692).
In that final rule, we established our
approach for identifying cross-setting
measures and processes for the adoption
of measures, including the application
and purpose of the Measures
Application Partnership (MAP) and the
notice and comment rulemaking
process. More information on the
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IMPACT Act is also available at https://
www.govtrack.us/congress/bills/113/
hr4994.
In the CY 2016 HH PPS final rule (80
FR 68692), we also discussed the
reporting of OASIS data as it relates to
the implementation of ICD–10 on
October 1, 2015. We submitted a new
request for approval to OMB for the
OASIS–C1/ICD–10 version under the
Paperwork Reduction Act (PRA)
process, including a new OMB control
number (see 80 FR 15796). The new
information collection request for
OASIS–C1/ICD–10 version was
approved under OMB control number
0938–1279 with a current expiration
date of May 31, 2018. To satisfy
requirements in the IMPACT Act that
HHAs submit standardized patient
assessment data in accordance with
section 1899B(b) and to create
consistency in the lookback period
across selected OASIS items, we have
created a modified version of the
OASIS, OASIS–C2. We have submitted
request for approval to OMB for the
OASIS–C2 version under the PRA
process (81 FR 18855); also see https://
www.cms.gov/Regulations-andGuidance/Legislation/
PaperworkReductionActof1995/PRAListing.html. The OASIS–C2 version
will replace the OASIS–C1/ICD–10 and
will be effective for data collected with
an assessment completion date (M0090)
on and after January 1, 2017.
Information regarding the OASIS–C1/
ICD–10 and C2 can be located on the
OASIS Data Sets Web page at https://
www.cms.gov/Medicare/QualityInitiatives-Patient-AssessmentInstruments/HomeHealthQualityInits/
OASIS-Data-Sets.html.
B. General Considerations Used for the
Selection of Quality Measures for the
HH QRP
We refer readers to the CY 2016 HH
PPS final rule (80 FR 68695 through
68698) for a detailed discussion of the
considerations we apply in measure
selection for the Home Health Quality
Reporting Program (HH QRP), such as
alignment with the CMS Quality
Strategy,25 which incorporates the three
broad aims of the National Quality
Strategy.26 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 highest
quality health care requires continuous
25 https://www.cms.gov/Medicare/QualityInitiatives-Patient-Assessment-Instruments/
QualityInitiativesGenInfo/CMS-QualityStrategy.html.
26 https://www.ahrq.gov/workingforquality/nqs/
nqs2011annlrpt.htm.
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evaluation to identify and address
performance gaps and reduce the
unintended consequences that may arise
in treating a large, vulnerable, and aging
population. Quality reporting programs
(QRPs), coupled with public reporting
of quality information are critical to the
advancement of health care quality
improvement efforts. Valid, reliable, and
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 HH QRP one measure that
we are specifying under section
1899B(c)(1)(C) of the Act to meet the
Medication Reconciliation domain: (1)
Drug Regimen Review Conducted with
Follow-Up for Identified Issues-PostAcute Care Home Health Quality
Reporting Program (Drug Regimen
Review Conducted with Follow-Up for
Identified Issues-PAC HH QRP).
Further, we are proposing to adopt for
the HH QRP three measures to meet the
‘‘Resource Use and other Measures’’
domains required by section
1899B(d)(1) of the Act: (1) Total
Estimated Medicare Spending per
Beneficiary—Post Acute Care Home
Health Quality Reporting Program
(MSPB–PAC HH QRP); (2) Discharge to
Community—Post Acute Care Home
Health Quality Reporting Program
(Discharge to Community-PAC HH
QRP); and (3) Potentially Preventable
30-Day Post-Discharge Readmission
Measure for Post-Acute Care Home
Health Quality Reporting Program
(Potentially Preventable 30-Day PostDischarge Readmission Measure for HH
QRP).
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
panels (TEPs) that included stakeholder
experts and patient representatives on
July 29, 2015 for the Drug Regimen
Review Conducted with Follow-Up for
Identified Issues-PAC HH QRP; on
August 25, 2015, September 25, 2015,
and October 5, 2015, for the Discharge
to Community-PAC HH QRP; on August
12–13, 2015, and October 14, 2015, for
the Potentially Preventable 30-Day PostDischarge Readmission Measure for HH
QRP; and on October 29–30, 2015, for
the MSPB–PAC HH QRP measures. In
addition, we released draft quality
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43757
measure specifications for public
comment on the Drug Regimen Review
Conducted with Follow-Up for
Identified Issues-PAC HH QRP from
September 18, 2015 to October 6, 2015,
for the Discharge to Community-PAC
HH QRP from November 9, 2015 to
December 8, 2015, for the Potentially
Preventable 30-Day Post-Discharge
Readmission Measure for HH QRP from
November 2, 2015 to December 1, 2015,
and for the MSPB–PAC HH QRP
measures from January 13, 2016 to
February 5, 2016. Further, we opened a
public mailbox, PACQualityInitiative@
cms.hhs.gov, for the submission of
public comments. This PAC mailbox is
accessible on our post-acute care quality
initiatives Web site, on the IMPACT Act
of 2014 Data Standardization & Cross
Setting Measures Web page at https://
www.cms.gov/Medicare/QualityInitiatives-Patient-AssessmentInstruments/Post-Acute-Care-QualityInitiatives/IMPACT-Act-of-2014/
IMPACT-Act-of-2014-DataStandardization-and-Cross-SettingMeasuresMeasures.html.
Additionally, we sought public input
from the MAP Post-Acute Care, LongTerm Care Workgroup during the
annual public meeting held December
14–15, 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 measure proposed
in this rule for use in the HH QRP. For
more information on the MAP, we refer
readers to the CY 2016 HH PPS final
rule (80 FR 68692 through 68694).
Further, for more information on the
MAP’s recommendations, we refer
readers to the MAP 2015–2016
Considerations for Implementing
Measures in Federal Programs public
report at https://www.qualityforum.org/
Publications/2016/02/MAP_2016_
Considerations_for_Implementing_
Measures_in_Federal_Programs_-_PACLTC.aspx.
For measures that do not have NQF
endorsement, or which are not fully
supported by the MAP for use in the HH
QRP, we are proposing measures for the
HH QRP for the purposes of satisfying
the measure domains required under the
IMPACT Act measures that most closely
align with the national priorities
identified in the National Quality
Strategy (https://www.ahrq.gov/
workingforquality/) and with respect to
which the MAP supports the measure
concept. Further, we discuss below the
importance and high-priority status of
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these proposed measures in the HH
setting.
C. Process for Retaining, Removing, and
Replacing Previously Adopted Home
Health Quality Reporting Program
Measures for Subsequent Payment
Determinations
Consistent with the policies of other
provider QRPs, including the Hospital
Inpatient Quality Reporting Program
(Hospital IQR) (77 FR 53512 through
53513), the Hospital Outpatient Quality
Reporting Program (Hospital OQR) (77
FR 68471), the LTCH QRP (77 FR 53614
through 53615), and the IRF QRP (77 FR
68500 through 68507), we are proposing
that when we initially adopt a measure
for the HH QRP for a payment
determination, this measure will be
automatically retained for all
subsequent payment determinations
unless we propose to remove or replace
the measure, or unless the exception
discussed below applies.
We are proposing to define the term
‘‘remove’’ to mean that the measure is
no longer a part of the HH QRP measure
set, data on the measure will no longer
be collected for purposes of the HH
QRP, and the performance data for the
measure will no longer be displayed on
HH Compare. We are also proposing to
use the following criteria when
considering a quality measure for
removal: (1) Measure performance
among HHAs is so high and unvarying
that meaningful distinctions in
improvements in performance can no
longer be made; (2) performance or
improvement on a measure does not
result in better patient outcomes; (3) a
measure does not align with current
clinical guidelines or practice; (4) a
more broadly applicable measure
(across settings, populations, or
conditions) for the particular topic is
available; (5) a measure that is more
proximal in time to desired patient
outcomes for the particular topic is
available; and (6) a measure that is more
strongly associated with desired patient
outcomes for the particular topic is
available. These items may still appear
on OASIS for previously established
purposes that are non-related to our HH
QRP. HHAs will be able to access these
reports using the Certification and
Survey Provider Enhanced Reports
(CASPER) system and can use the
information for their own monitoring
and quality improvement efforts.
Further, we are proposing to define
‘‘replace’’ to mean that we would adopt
a different quality measure in place of
a currently used quality measure, for
one or more of the reasons described
above. Additionally, we are proposing
that any such ‘‘removal’’ or
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‘‘replacement’’ will take place through
notice-and-comment rulemaking, unless
we determine that a measure is causing
concern for patient safety. Specifically,
in the case of a HH QRP measure for
which there is a reason to believe that
the continued collection raises possible
safety concerns or would cause other
unintended consequences, we propose
to promptly remove the measure and
publish the justification for the removal
in the Federal Register during the next
rulemaking cycle. In addition, we will
immediately notify HHAs and the
public through the usual
communication channels, including
listening session, memos, email
notification, and Web postings. If we
removed a measure under these
circumstances, we would also not
continue to collect data on that measure
under our alternative authorities for
purposes other than the HH QRP.
We invite public comment on our
proposed policy for retaining, removing
and replacing previously adopted
quality measures, including the criteria
we propose to use when considering
whether to remove a quality measure
from the HH QRP.
D. Quality Measures That Will Be
Removed From the Home Health
Quality Initiative, and Quality Measures
That Are Proposed for Removal From
the HH QRP Beginning With the CY
2018 Payment Determination
In 2015, we undertook a
comprehensive reevaluation of all 81
HH quality measures, some of which are
used only in the Home Health Quality
Initiative (HHQI), and others which are
also used in the HH QRP. This review
of all the measures was performed in
accordance with the guidelines from the
CMS Measure Management System
(MMS) (https://www.cms.gov/Medicare/
Quality-Initiatives-Patient-AssessmentInstruments/MMS/MMSBlueprint.html). The goal of this
reevaluation was to streamline the
measure set, consistent with MMS
guidance and in response to stakeholder
feedback. This reevaluation included a
review of the current scientific basis for
each measure, clinical relevance,
usability for quality improvement, and
evaluation of measure properties,
including reportability, and variability.
Our measure development and
maintenance contractor convened a
Technical Expert Panel (TEP) on August
21, 2015, to review and advise on the
reevaluation results. The TEP provided
feedback on which measures are most
useful for patients, caregivers,
clinicians, and stakeholders, and on
analytics and an environmental scan
conducted to inform measure set
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revisions. Further information about the
TEP feedback is available at https://
www.cms.gov/Medicare/QualityInitiatives-Patient-AssessmentInstruments/MMS/Downloads/HealthQuality-Reporting-Program-HHQRPTEP-.zip.
As a result of the comprehensive
reevaluation described above, we
identified 28 HHQI measures that were
either ‘‘topped out’’ and/or determined
to be of limited clinical and quality
improvement value by TEP members.
Therefore, these measures will no longer
be included in the HHQI. A list of these
measures, along with our reasons for no
longer including them in the HHQI, can
be found at the following link https://
www.cms.gov/Medicare/QualityInitiatives-Patient-AssessmentInstruments/HomeHealthQualityInits/
HHQIQualityMeasures.html.
In addition, based on the results of the
comprehensive reevaluation and the
TEP input, we are proposing to remove
6 process measures from the HH QRP,
beginning with the CY 2018 payment
determination, because they are ‘‘topped
out’’ and therefore no longer have
sufficient variability to distinguish
between providers in public reporting.
These 6 measures are different than the
28 measures that will no longer be
included within the HHQI. If this
proposal is finalized, items used to
calculate one or more of these six
measures may still appear on the OASIS
for previously established purposes that
are not related to the HH QRP.
The 6 process measures we are
proposing to remove from the HH QRP
are:
• Pain Assessment Conducted;
• Pain Interventions Implemented
During All Episodes of Care;
• Pressure Ulcer Risk Assessment
Conducted;
• Pressure Ulcer Prevention in Plan of
Care;
• Pressure Ulcer Prevention
Implemented During All Episodes of
Care; and
• Heart Failure Symptoms Addressed
During All Episodes of Care.
The technical analysis that supports
our proposal to remove the six process
measures can be found at https://
www.cms.gov/Medicare/QualityInitiatives-Patient-AssessmentInstruments/HomeHealthQualityInits/
HHQIQualityMeasures.html.
We invite public comment on our
above proposal to remove 6 process
measures from the HH QRP.
E. Proposed Process for Adoption of
Updates to HH QRP Measures
We believe that it is important to have
in place a sub-regulatory process to
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incorporate non-substantive updates
into the measure specifications so that
these measures remain up-to-date. We
also recognize that some changes are
substantive in nature and might not be
appropriate for adoption using a subregulatory process.
Therefore, in the FY 2013 IPPS/LTCH
PPS final rule (77 FR 53504 through
53505), we finalized a policy for the
Hospital IQR Program under which we
use a subregulatory process to make
nonsubstantive updates to measures
used for that program. For what
constitutes substantive versus
nonsubstantive changes, we make this
determination on a case-by-case basis.
Examples of nonsubstantive changes to
measures might include: Updated
diagnosis or procedure codes,
medication updates for categories of
medications, broadening of age ranges,
and exclusions for a measure.
Nonsubstantive changes may also
include updates to NQF-endorsed
measures based upon changes to
guidelines upon which the measures are
based. Examples of changes that we
might consider to be substantive would
be those in which: The changes are so
significant that the measure is no longer
the same measure, or when a standard
of performance assessed by a measure
becomes more stringent (for example,
changes in acceptable timing of
medication, procedure/process, or test
administration). Another example of a
substantive change might be where the
NQF has extended its endorsement of a
previously endorsed measure to a new
setting, such as extending a measure
from the inpatient setting to hospice.
We are proposing to implement the
same process for adopting updates to
measures in the HH QRP, and would
apply this process, including our policy
for determining on a case-by-case basis
whether an update is substantive or
nonsubstantive. We believe this process
adequately balances our need to
incorporate updates to the HH QRP
measures in the most expeditious
manner possible while preserving the
public’s ability to comment on updates
that do not fundamentally change a
measure that it is no longer the same
measure that we originally adopted.
We invite public comment on this
proposal.
F. Modifications to Guidance Regarding
Assessment Data Reporting in the
OASIS
We are proposing modifications to our
coding guidance modifications related
to certain pressure ulcer items on the
OASIS. In the CY 2016 HH PPS final
rule (80 FR 68700), we adopted the NQF
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with Pressure Ulcers that are New or
Worsened (Short Stay) measure for use
in the HH QRP for the CY 2018 HH QRP
payment determination and subsequent
years. Concurrent with the effective date
for OASIS–C2 of January 1, 2017, we
would use modified guidance for the
reporting of current pressure ulcers. The
purpose of this modification is to align
with reporting guidance used in other
post-acute care settings and with the
policies of relevant clinical associations.
Chapter 3 of the OASIS–C1/ICD–10
Guidance Manual currently states
‘‘Stage III and IV (full thickness)
pressure ulcers heal through a process
of contraction, granulation, and
epithelialization. They can never be
considered ‘fully healed’ but they can be
considered closed when they are fully
granulated and the wound surface is
covered with new epithelial tissue.’’ We
utilize professional organizations, such
as the National Pressure Ulcer Advisory
Panel (NPUAP) to provide clinical
insight and expertise related to the use
and completion of relevant OASIS
items. Based on the currently published
position statements and best practices
available from the NPUAP,27 effective
January 1, 2017, full-thickness (Stage 3
or 4) pressure ulcers should not be
reported on OASIS as unhealed pressure
ulcers once complete reepithelialization has occurred. This
represents a change in past guidance,
and will allow OASIS data collection to
conform to professional clinical
guidelines, and align with pressure
ulcer reporting practices in other postacute care settings. In addition to
revising guidance related to closed Stage
3 and 4 pressure ulcers, we are changing
the reporting instructions when a graft
is applied to a pressure ulcer. Current
guidance states that when a graft is
placed on a pressure ulcer, the wound
remains a pressure ulcer and is not
concurrently reported as a surgical
wound on the OASIS. In order to align
with reporting guidance in other postacute care settings, effective January 1,
2017, once a graft is applied to a
pressure ulcer, the wound will be
reported on OASIS as a surgical wound,
and no longer be reported as a pressure
ulcer.
G. Proposed HH QRP Quality, Resource
Use, and Other Measures for the CY
2018 Payment Determination and
Subsequent Years
For the CY 2018 payment
determination and subsequent years, in
addition to the quality measures we
would retain if our proposed policy on
27 https://www.npuap.org/wp-content/uploads/
2012/01/Reverse-Staging-Position-Statement.pdf.
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retaining measures is finalized, we are
proposing to adopt four new measures.
These four measures were developed to
meet the requirements of the IMPACT
Act. These proposed measures are:
• MSPB–PAC HH QRP;
• Discharge to Community-PAC HH
QRP;
• Potentially Preventable 30-Day
Post-Discharge Readmission Measure for
HH QRP; and
• Drug Regimen Review Conducted
With Follow-Up for Identified IssuesPAC HH QRP
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 agencies
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 agencies’
results on our measures.
The NQF is currently undertaking a 2year 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 2 years, NQF
will conduct a trial of temporarily
allowing inclusion of sociodemographic
factors in the risk-adjustment 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, 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.
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1. Proposal To Address the IMPACT Act
Domain of Resource Use and Other
Measures: MSPB–PAC HH QRP
Section 1899B(d)(1)(A) of the Act
requires that no later than the specified
application date (which under section
1899B(a)(1)(E)(ii) is October 1, 2016 for
SNFs, IRFs and LTCHs and January 1,
2017 for HHAs), the Secretary specify a
measure to address the domain of
resource use measures, including total
estimated Medicare spending per
beneficiary. We are proposing to adopt
the measure, MSPB–PAC HH QRP, for
which we would begin to collect data on
January 1, 2017 for the CY 2018
payment determination and subsequent
years as a Medicare fee-for-service (FFS)
claims-based measure to meet this
requirement.
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
average 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.28 A study commissioned
by the Institute of Medicine found that
variation in PAC spending explains 73
percent of variation in total Medicare
spending across the United States.29
We reviewed the NQF’s consensusendorsed measures and were unable to
identify any NQF-endorsed resource use
measures for PAC settings. Therefore,
we are proposing to adopt this MSPB–
PAC HH QRP measure under section
1899B(e)(2)(B) of the Act, which allows
us to specify a measure under section
1899B that is not NQF-endorsed if the
measure deals with a specified area or
medical topic the Secretary has
determined to be appropriate for which
there is no feasible or practical NQFendorsed measure. We recognize that
there are other measures that address
Medicare spending per beneficiary, but
we are not aware of any such measures
that have been endorsed or adopted
specifically for the home health setting.
Given the current lack of resource use
measures for PAC settings, our proposed
MSPB–PAC HH QRP measure has the
potential to provide valuable
information to HHAs on their relative
Medicare spending in delivering
28 MedPAC, ‘‘A Data Book: Health Care Spending
and the Medicare Program,’’ (2015). 114.
29 Institute of Medicine, ‘‘Variation in Health Care
Spending: Target Decision Making, Not
Geography,’’ (Washington, DC: National Academies
2013). 2.
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services to approximately 3.5 million
Medicare beneficiaries.30
The proposed MSPB–PAC HH QRP
episode-based measure would provide
actionable and transparent information
to support HHAs’ efforts to promote care
coordination and deliver high quality
care at a lower cost to Medicare. The
MSPB–PAC HH QRP measure holds
HHAs accountable for the Medicare
payments within an ‘‘episode of care’’
(episode), which includes the period
during which a patient is directly under
the HHA’s care, as well as a defined
period after the end of the HHA
treatment, which may be reflective of
and influenced by the services
furnished by the HHA. MSPB–PAC HH
QRP episodes, constructed according to
the methodology described below, have
high levels of Medicare spending with
substantial variation. In FY 2014,
Medicare FFS beneficiaries experienced
5,379,410 MSPB–PAC HH QRP episodes
triggered by admission to a HHA. The
mean payment-standardized, riskadjusted episode spending for these
episodes was $10,348 during that fiscal
year. There was substantial variation in
the Medicare payments for these MSPB–
PAC HH QRP episodes—ranging from
approximately $2,480 at the 5th
percentile to approximately $31,964 at
the 95th percentile. This variation was
partially driven by variation in
payments occurring following HH
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 MSPB–PAC
measures and believe that measuring
Medicare spending is critical for
improving efficiency, others believe that
resource use measures do not reflect
quality of care in that they do not take
into account patient outcomes or
experience beyond those observable in
claims data. However, we believe that
HHAs involved in the provision of high
quality PAC care as well as appropriate
discharge planning and post-discharge
care coordination will perform well on
this measure because beneficiaries will
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 HHAs that
30 Figures for 2013. MedPAC, ‘‘Medicare Payment
Policy,’’ Report to the Congress (2015). xvii–xviii.
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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. In addition to this
measure proposal, we proposed a LTCHspecific MSPB–PAC measure in the FY
2017 IPPS/LTCH proposed rule (81 FR
25216 through 25220), an IRF-specific
MSPB–PAC measure in the FY 2017 IRF
PPS proposed rule (81 FR 24197
through 24201), and a SNF-specific
MSPB–PAC measure in the FY 2017
SNF PPS proposed rule (81 FR 24258
through 24262). These four settingspecific 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, the MSPB–
PAC HH QRP measure compares
episodes triggered by Partial Episode
Payment (PEP) and Low-Utilization
Payment Adjustment (LUPA) claims
only with episodes of the same type, as
detailed below.
The MSPB–PAC measures mirror the
general construction of the inpatient
prospective payment system (IPPS)
hospital MSPB measure, which was
adopted for the Hospital IQR Program
beginning with the FY 2014 program,
and was implemented in the Hospital
VBP Program beginning with the FY
2015 program. The measure was
endorsed by the NQF on December 6,
2013 (NQF #2158).31 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 hospital MSPB
episode, which comprises the periods
immediately prior to, during, and
following a patient’s hospital inpatient
stay.32 33 Similarly, the MSPB–PAC
31 QualityNet, ‘‘Measure Methodology Reports:
Medicare Spending Per Beneficiary (MSPB)
Measure,’’ (2015). https://www.qualitynet.org/dcs/
ContentServer?pagename=QnetPublic%2F
Page%2FQnetTier3&cid=1228772053996.
32 QualityNet, ‘‘Measure Methodology Reports:
Medicare Spending Per Beneficiary (MSPB)
Measure,’’ (2015). https://www.qualitynet.org/dcs/
ContentServer?pagename=QnetPublic%2FPage%2F
QnetTier3&cid=1228772053996.
33 FY 2012 IPPS/LTCH PPS final rule (76 FR
51619).
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measures assess all Medicare Part A and
Part B payments for FFS claims with a
start date that begins at the episode
trigger and continues for the length of
the episode window (which, as
discussed in this section, is the time
period during which Medicare FFS Part
A and Part B services are counted
towards the MSPB–PAC HH QRP
episode). However, there are differences
between the MSPB–PAC measures, as
proposed, and the hospital MSPB
measure that 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, for clinically unrelated
services) provided to a beneficiary
during the episode window while the
hospital MSPB measure does not
exclude any services.34
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. A home health episode
beginning within 30 days of discharge
from an inpatient hospital will therefore
be included: Once in the hospital’s
MSPB measure, and once in the HHA’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/Downloads/Technical-Expert
-Panel-on-Medicare-Spending-PerBeneficiary.pdf. The measures were also
presented to the MAP 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: Encourage continued
development, do not encourage further
consideration, and insufficient
34 FY
2012 IPPS/LTCH PPS final rule (76 FR
51620).
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information.35 The MAP PAC/LTC
Workgroup voted to ‘‘encourage
continued development’’ for each of the
MSPB–PAC measures.36 The MAP PAC/
LTC Workgroup’s vote of ‘‘encourage
continued development’’ was affirmed
by the MAP Coordinating Committee on
January 26, 2016.37 The MAP’s concerns
about the MSPB–PAC measures, as
outlined in its final report, ‘‘MAP 2016
Considerations for Implementing
Measures in Federal Programs: PostAcute Care and Long-Term Care,’’ and
Spreadsheet of Final Recommendations
were taken into consideration during
our measure development process and
are discussed as part of our responses to
public comments we received during
the measure development process,
described below.38 39
Since the MAP’s review and
recommendation of continued
development, we have continued to
refine the risk adjustment model and
conduct measure testing for the
proposed MSPB–PAC measures. The
proposed MSPB–PAC 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.
A total of 45 comments on the MSPB–
PAC measures were received during this
3.5 week period. The comments
received also covered each of the MAP’s
concerns as outlined in their Final
Recommendations.40 The MSPB–PAC
35 National Quality Forum, Measure Applications
Partnership, ‘‘Process and Approach for MAP PreRulemaking Deliberations, 2015–2016’’ (February
2016) https://www.qualityforum.org/WorkArea/
linkit.aspx?LinkIdentifier=id&ItemID=81693.
36 National Quality Forum, Measure Applications
Partnership Post-Acute Care/Long-Term Care
Workgroup, ‘‘Meeting Transcript—Day 2 of 2’’
(December 15, 2015) 104–106 https://www.quality
forum.org/WorkArea/linkit.aspx?LinkIdentifier=id&
ItemID=81470.
37 National Quality Forum, Measure Applications
Partnership, ‘‘Meeting Transcript—Day 1 of 2’’
(January 26, 2016) 231–232 https://www.quality
forum.org/WorkArea/linkit.aspx?LinkIdentifier=
id&ItemID=81637.
38 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) https://www.qualityforum.org/
Publications/2016/02/MAP_2016_Considerations_
for_Implementing_Measures_in_Federal_Programs_
-_PAC-LTC.aspx.
39 National Quality Forum, Measure Applications
Partnership, ‘‘Spreadsheet of MAP 2016 Final
Recommendations’’ (February 1, 2016) https://
www.qualityforum.org/WorkArea/linkit.aspx?Link
Identifier=id&ItemID=81593.
40 National Quality Forum, Measure Applications
Partnership, ‘‘Spreadsheet of MAP 2016 Final
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43761
Public Comment Summary Report is
available https://www.cms.gov/
Medicare/Quality-Initiatives-PatientAssessment-Instruments/Post-AcuteCare-Quality-Initiatives/Downloads/
2016_03_24_mspb_pac_public_
comment_summary_report.pdf and
contains the public comments. If
finalized, the proposed MSPB–PAC HH
QRP measure, along with the other
MSPB–PAC measures, as applicable,
will be submitted for NQF consideration
of endorsement.
To calculate the MSPB–PAC HH QRP
measure for each HHA, we first define
the construction of the MSPB–PAC HH
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 in this section. More
detailed specifications for the proposed
MSPB–PAC measures, including the
MSPB–PAC HH QRP measure in this
proposed rule, are available at https://
www.cms.gov/Medicare/QualityInitiatives-Patient-AssessmentInstruments/Post-Acute-Care-QualityInitiatives/Downloads/2016_04_06_
mspb_pac_measure_specifications_for_
rulemaking.pdf.
a. Episode Construction
An MSPB–PAC HH QRP episode
begins at the episode trigger, which is
defined as the patient’s admission to a
HHA. This admitting HHA is the
provider for whom the MSPB–PAC HH
QRP measure is calculated (that is, the
attributed provider). The episode
window is the time period during which
Medicare FFS Part A and Part B services
are counted towards the MSPB–PAC HH
QRP episode. Because Medicare FFS
claims are already reported to the
Medicare program for payment
purposes, HHAs 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.
Our proposed MSPB–PAC HH QRP
episode construction methodology
differentiates between episodes
triggered by standard HH claims (for
which there is no PEP or LUPA
adjustment) and claims for which PEP
and LUPA adjustments apply, reflecting
the HHA PPS payment policy. Standard,
PEP, and LUPA episodes would be
compared only with standard, PEP and
LUPA episodes, respectively.
Differences in episode construction
Recommendations’’ (February 1, 2016) https://
www.qualityforum.org/WorkArea/
linkit.aspx?LinkIdentifier=id&ItemID=81593.
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between these three episode types are
noted below; they otherwise share the
same definition.
The episode window is comprised of
a treatment period and an associated
services period. For MSPB–PAC HH
Standard and LUPA QRP episodes, the
treatment period begins at the trigger
(that is, on the first day of the home
health claim) and ends after 60 days.
For MSPB–PAC PEP QRP episodes, the
treatment period begins at the trigger
(that is, on the first day of the home
health claim) and ends at discharge. The
treatment period includes those services
that are provided directly or reasonably
managed by the HHA 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 HH QRP
episodes because they are clinically
unrelated to HHA care, and/or because
HHAs may have limited influence over
certain Medicare services delivered by
other providers during the episode
window. These limited service-level
exclusions are not counted towards a
given HHA’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
a HHA 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 HH 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 HH QRP episode in the
30 days post-treatment. One possible
scenario occurs where a HHA
discharges a beneficiary who is then
admitted to a SNF within 30 days. The
SNF claim would be included once as
an associated service for the attributed
provider of the first MSPB–PAC HH
QRP episode and once as a treatment
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service for the attributed provider of the
second MSPB–PAC SNF 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 HH setting, one MSPB–PAC
HH QRP episode may begin in the
associated services period of another
MSPB–PAC HH QRP episode in the 30
days post-treatment. The second HH
claim would be included once as an
associated service for the attributed
HHA of the first MSPB–PAC HH QRP
episode and once as a treatment service
for the attributed HHA of the second
MSPB–PAC HH QRP episode. Again,
this ensures that HHAs have the same
incentives throughout both MSPB–PAC
HH QRP episodes to deliver quality care
and engage in patient-focused care
planning and coordination. If the
second MSPB–PAC HH QRP episode
were excluded from the second HHA’s
MSPB–PAC HH QRP measure, that HHA
would not share the same incentives as
the first HHA of the first MSPB–PAC
HH QRP episode. The MSPB–PAC HH
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 HH QRP episodes, defined
according to the methodology
previously discussed, are used to
calculate the MSPB–PAC HH 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.
The measure calculation is performed
separately for MSPB–PAC HH QRP
standard, PEP, and LUPA episodes to
ensure that they are compared only to
other standard, PEP, and LUPA
episodes, respectively. The final MSPB–
PAC HH QRP measure would combine
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the three ratios above to construct one
HHA score as described below.
(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
MSPB–PAC HH QRP measure to ensure
that the MSPB–PAC HH QRP measure
accurately reflects resource use and
facilitates fair and meaningful
comparisons between HHAs. The
proposed episode-level exclusions are
as follows:
• Any episode that is triggered by a
HH claim outside the 50 states, DC,
Puerto Rico, and U.S. territories.
• Any episode where the claim(s)
constituting the attributed HHA
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 HHA
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 HH 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
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other add-on payments that support
broader Medicare program goals
including indirect graduate medical
education (IME) and hospitals serving a
disproportionate share of uninsured
patients (DSH).41
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 HHA. To assist with risk
adjustment for MSPB–PAC HH 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 HH QRP
episode. The beneficiaries in these
clinical case mix categories have a
greater degree of clinical similarity than
the overall HHA patient population, and
allow us to more accurately estimate
Medicare spending. Our proposed
MSPB–PAC HH QRP model, adapted for
the HH 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. During the public comment
period that ran from January 13 to
February 5, 2016 discussed above, we
sought and considered public comment
regarding the treatment of hospice
services occurring within the MSPB–
PAC HH 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 HH QRP
episodes with hospice are compared to
a benchmark reflecting other MSPB–
PAC HH QRP episodes with hospice.
We believe that this provides a balance
between the measure’s intent of
evaluating Medicare spending and
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41 QualityNet, ‘‘CMS Price (Payment)
Standardization—Detailed Methods’’ (Revised May
2015) https://qualitynet.org/dcs/
ContentServer?c=Page&pagename=QnetPublic%
2FPage%2FQnetTier4&cid=1228772057350.
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ensuring that providers do not have
incentives against the appropriate use of
hospice services in a patient-centered
continuum of care.
As noted previously, we understand
the important role that
sociodemographic status, beyond age,
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 outcomes of
disadvantaged populations. We
routinely monitor the impact of
sociodemographic status on providers’
results on our measures.
The NQF is currently undertaking a 2year 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 2 years, NQF
will conduct a trial of temporarily
allowing inclusion of sociodemographic
factors in the risk-adjustment 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
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 HH QRP riskadjustment model, we are not proposing
to adjust the MSPB–PAC HH measure
for socioeconomic and demographic
factors at this time. As this MSPB–PAC
HH QRP measure will be submitted to
the NQF for consideration of
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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 HH QRP measure.
(3) Measure Numerator and
Denominator
The MPSB–PAC HH QRP measure is
a payment-standardized, risk-adjusted
ratio that compares a given HHA’s
Medicare spending against the Medicare
spending of other HHAs 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 HH QRP measure is
calculated as the ratio of the MSPB–PAC
Amount for each HHA divided by the
episode-weighted median MSPB–PAC
Amount across all HHAs. To calculate
the MSPB–PAC Amount for each HHA,
one calculates the average of the ratio of
the standardized spending for HHA
standard episodes over the expected
spending (as predicted in risk
adjustment) for HHA standard episodes,
the average of the ratio of the
standardized spending for HHA PEP
episodes over the expected spending (as
predicted in risk adjustment) for HHA
PEP episodes, and the average of the
ratio of the standardized spending for
HHA LUPA episodes over the expected
spending (as predicted in risk
adjustment) for HHA LUPA episodes.
This quantity is then multiplied by the
average episode spending level across
all HHAs nationally for standard, PEP,
and LUPA episodes. The denominator
for a HHA’s MSPB–PAC HH QRP
measure is the episode-weighted
national median of the MSPB–PAC
Amounts across all HHAs. An MSPB–
PAC HH QRP measure of less than 1
indicates that a given HHA’s Medicare
spending is less than that of the national
median HHA during a performance
period. Mathematically, this is
represented in equation (A) below:
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Where:
• Yij = attributed standardized spending for
episode i and provider j
ˆ
• 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.
c. 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 2016. We intend to
publicly report this measure using
claims data from discharges in CY 2017.
We are proposing a minimum of 20
episodes for reporting and inclusion in
the HH QRP. For the reliability
calculation, as described in the measure
specifications provided above, we used
data from FY 2014. The reliability
results support the 20 episode case
minimum, and 94.27 percent of HHAs
had moderate or high reliability (above
0.4).
We invite public comment on our
proposal to adopt the MSPB–PAC HH
QRP measure for the HH QRP.
2017 for HHAs), the Secretary specify a
measure to address the domain of
discharge to community. We are
proposing to adopt the measure,
Discharge to Community—PAC HH QRP
for the HH QRP, beginning with the CY
2018 payment determination and
subsequent years as a Medicare fee-forservice (FFS) claims-based measure to
meet this requirement.
This proposed measure assesses
successful discharge to the community
from a HH setting, with successful
discharge to the community including
no unplanned hospitalizations and no
deaths in the 31 days following
discharge from the HH agency setting.
Specifically, this proposed measure
reports a HHA’s risk-standardized rate
of Medicare FFS patients who are
discharged to the community following
a HH episode, do not have an
unplanned admission to an acute care
hospital or LTCH in the 31 days
following discharge to community, and
remain alive during the 31 days
following discharge to community. The
term ’’community,’’ for this measure, is
defined as home/self-care, without
home health services, based on Patient
Discharge Status Codes 01 and 81 on the
Medicare FFS claim.42 43 This measure
is specified 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
2. Proposal To Address the IMPACT Act
Domain of Resource Use and Other
Measures: Discharge to Community-Post
Acute Care Home Health Quality
Reporting Program
Section 1899B(d)(1)(B) of the Act
requires that no later than the specified
application date (which under section
1899B(a)(1)(E)(ii) is October 1, 2016 for
SNFs, IRFs and LTCHs and January 1,
42 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.
43 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.
a. Data Sources
The MSPB–PAC HH 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.
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b. Cohort
The measure cohort includes
Medicare FFS beneficiaries with a HHA
treatment period ending during the data
collection period.
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outcome for many patients who are not
expected to make functional
improvement during their HH episode
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.44 45
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 patients discharged to
institutional settings.46 47 Given the high
costs of care in institutional settings,
encouraging post-acute providers to
prepare patients for discharge to
community, when clinically
appropriate, may have cost-saving
implications for the Medicare
program.48 Also, providers have
discovered that successful discharge to
the community was a major driver of
their ability to achieve savings, where
capitated payments for post-acute care
were in place.49 For patients who
44 El-Solh AA, Saltzman SK, Ramadan FH,
Naughton BJ. Validity of an artificial neural
network in predicting discharge destination from a
post-acute geriatric rehabilitation unit. Archives of
physical medicine and rehabilitation.
2000;81(10):1388–1393.
45 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.
46 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.
47 Gage B, Morley M, Spain P, Ingber M.
Examining Post Acute Care Relationships in an
Integrated Hospital System Final Report. RTI
International;2009.
48 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. Med
Care. 2016 Mar;54(3):221–228.
49 Doran JP, Zabinski SJ. Bundled payment
initiatives for Medicare and non-Medicare total
joint arthroplasty patients at a community hospital:
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sradovich on DSK3GDR082PROD with PROPOSALS2
require long-term care due to persistent
disability, discharge to community
could result in lower long-term care
costs for Medicaid and for patients’ outof-pocket expenditures.50
Analyses conducted for ASPE on PAC
episodes, using a 5 percent sample of
2006 Medicare claims, revealed that
relatively high average, unadjusted
Medicare payments associated with
discharge from IRFs, SNFs, LTCHs, or
HHAs to institutional settings, as
compared with payments associated
with discharge from these PAC
providers to community settings.51
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.52
Measuring and comparing agencylevel discharge to community rates is
expected to help differentiate among
agencies 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),
freestanding or hospital-based units,
and across patient-level characteristics
such as race and gender.53 54 55 56 57 58 In
bundles in the real world. The Journal of
arthroplasty. 2015;30(3):353–355.
50 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. Med
Care. 2016 Jan 12. Epub ahead of print.
51 Gage B, Morley M, Spain P, Ingber M.
Examining Post Acute Care Relationships in an
Integrated Hospital System. Final Report. RTI
International;2009.
52 Ibid.
53 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.
54 El-Solh AA, Saltzman SK, Ramadan FH,
Naughton BJ. Validity of an artificial neural
network in predicting discharge destination from a
post-acute geriatric rehabilitation unit. Archives of
physical medicine and rehabilitation.
2000;81(10):1388–1393.
55 March 2015 Report to the Congress: Medicare
Payment Policy. Medicare Payment Advisory
Commission;2015.
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the HH Medicare FFS population, using
CY 2013 national claims data, we found
that approximately 82 percent of
episodes ended with a discharge to the
community. A multi-center study of 23
LTCHs demonstrated that 28.8 percent
of 1,061 patients who were ventilatordependent on admission were
discharged to home.59 A single-center
study revealed that 31 percent of LTCH
hemodialysis patients were discharged
to home.60 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 61 and a
second study noted that between 58
percent and 63 percent of beneficiates
were discharged to home with rates
varying by admission site.62 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).63
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.64 65 66 67 68 Many of these
56 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.
57 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.
58 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.
59 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.
60 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.
61 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.
62 Riggs JS, Madigan EA. Describing Variation in
Home Health Care Episodes for Patients with Heart
Failure. Home Health Care Management & Practice
2012; 24(3) 146–152.
63 Ibid.
64 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.
65 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.
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interventions involve discharge
planning or specific rehabilitation
strategies, such as addressing discharge
barriers and improving medical and
functional status.69 70 71 72 73 The
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 HH QRP into the HH
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 page at https://
www.cms.gov/Medicare/QualityInitiatives-Patient-AssessmentInstruments/Post-Acute-Care-QualityInitiatives/IMPACT-Act-of-2014/
IMPACT-Act-Downloads-andVideos.html.
66 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.
67 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.
68 Parker, E., Zimmerman, S., Rodriguez, S., &
Lee, T. Exploring best practices in home health
care: a review of available evidence on select
innovations. Home Health Care Management and
Practice, 2014; 26(1): 17–33.
69 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.
70 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.
71 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.
72 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.
73 Parker, E., Zimmerman, S., Rodriguez, S., &
Lee, T. Exploring best practices in home health
care: a review of available evidence on select
innovations. Home Health Care Management and
Practice, 2014; 26(1): 17–33.
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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
HH QRP measure in the HH QRP. The
MAP encouraged continued
development of the proposed measure
to meet the mandate of the IMPACT Act.
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 https://
www.qualityforum.org/Publications/
2016/02/MAP_2016_Considerations_
for_Implementing_Measures_in_
Federal_Programs_-_PAC-LTC.aspx.
Since the MAP review the measure
and recommended continued
development, we have continued to
refine the risk adjustment model and
conduct measure testing for this
measure. This proposed measure is
consistent with the information
submitted to the MAP and is
scientifically acceptable for current
specification in the HH QRP.
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 the 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 HH 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
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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 HH setting, using 2013 data, we
found 97 percent agreement in
discharge to community codes when
comparing ‘‘Patient Discharge Status
Code’’ from claims and Discharge
Disposition (M2420) and Inpatient
Facility (M2410) on the OASIS C
discharge assessment, when the claims
and OASIS assessment had the same
discharge date. We further examined the
accuracy of ‘‘Patient Discharge Status
Code’’ on the PAC claim by assessing
how frequently discharges to an acute
care hospital were confirmed by followup acute care claims. We found that 50
percent of HH claims with acute care
discharge status codes were followed by
an acute care claim in the 31 days after
HH discharge. We believe these data
support the use of the ‘‘Patient
Discharge Status Code’’ for determining
discharge to a community setting for
this measure. In addition, the proposed
measure has high feasibility because all
data used for measure calculation are
derived from Medicare FFS claims and
eligibility files, which are already
available to us.
Based on the evidence discussed
above, we are proposing to adopt the
measure entitled, ‘‘Discharge to
Community-PAC HH QRP’’, for the HH
QRP for the CY 2018 payment
determination and subsequent years.
This proposed measure is calculated
utilizing 2 years of data as defined
below. We are proposing a minimum of
20 eligible episodes in a given HHA for
public reporting of the proposed
measure for that HHA. Since Medicare
FFS claims data are already reported to
the Medicare program for payment
purposes, and Medicare eligibility files
are also available, HHAs 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 home health
patients who are discharged to the
community, do not have an unplanned
readmission to an acute care hospital or
LTCH in the 31-day post-discharge
observation window, and who remain
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alive during the post-discharge
observation window. The measure is
risk-adjusted for variables such as age
and sex, principal diagnosis,
comorbidities, and ESRD status among
other variables. For technical
information about this proposed
measure, including information about
the measure calculation, risk
adjustment, and denominator
exclusions, we refer readers the
document titled Proposed Measure
Specifications for Measures Proposed in
the CY 2017 HH QRP proposed rule,
available at https://www.cms.gov/
Medicare/Quality-Initiatives-PatientAssessment-Instruments/
HomeHealthQualityInits/
HHQIQualityMeasures.html.
If this proposed measure is finalized,
we intend to provide initial confidential
feedback to home health agencies, prior
to the public reporting of this measure,
based on Medicare FFS claims data from
discharges in CYs 2015 and 2016. We
intend to publicly report this measure
using claims data from discharges in
CYs 2016 and 2017. We plan to submit
this proposed measure to the NQF for
consideration for endorsement.
We invite public comment on our
proposal to adopt the measure,
Discharge to Community—PAC HH QRP
for the HH QRP.
3. Proposal To Address the IMPACT Act
Domain of Resource Use and Other
Measures: Potentially Preventable 30Day Post-Discharge Readmission
Measure for Post-Acute Care Home
Health Quality Reporting Program
Section 1899B(d)(1)(C) of the Act
requires that no later than the specified
application date (which under section
1899B(a)(1)(E)(ii) is October 1, 2016 for
SNFs, IRFs and LTCHs and January 1,
2017 for HHAs), the Secretary specify
measures to address the domain of allcondition risk-adjusted potentially
preventable hospital readmission rates.
We are proposing the measure
Potentially Preventable 30-Day PostDischarge Readmission Measure for HH
QRP as a Medicare FFS claims-based
measure to meet this requirement
beginning with the CY 2018 payment
determination.
The proposed measure assesses the
facility-level risk-standardized rate of
unplanned, potentially preventable
hospital readmissions for Medicare FFS
beneficiaries that take place within 30
days of a HH discharge. The HH
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
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readmissions include readmissions to a
short-stay acute-care hospital or a
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 HHAs.
Because the measure denominator is
based on HH 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 HH 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
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.74 75 The MedPAC 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 30-day and 15-day
readmissions and 84 percent of 7-day
readmissions were considered
‘‘potentially preventable.’’ 76 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
7-day readmissions.77 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.78 Mor et al. analyzed
2006 Medicare claims and SNF
assessment data (Minimum Data Set),
and reported a 23.5 percent readmission
74 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.
75 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
76 MedPAC: Payment policy for inpatient
readmissions, in Report to the Congress: Promoting
Greater Efficiency in Medicare. Washington, DC,
pp. 103–120, 2007. Available from https://
www.medpac.gov/documents/reports/Jun07_
EntireReport.pdf.
77 ibid.
78 ibid.
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rate from SNFs, associated with $4.3
billion in expenditures.79 An analysis of
data from a nationally representative
sample of Medicare FFS beneficiaries
receiving home health services in 2004
show that home health patients receive
significant amounts of acute and postacute services after discharge from home
health care. Within 30 days of discharge
from home health, 29 percent of patients
were admitted to a hospital.80 Focusing
on readmissions, Madigan and
colleagues studied 74,580 Medicare
home health patients with a
rehospitalization within 30 days of the
index hospital discharge. The 30-day
rehospitalization rate was 26 percent
with the largest proportion related to a
cardiac-related diagnosis (42 percent).81
Fewer studies have investigated
potentially preventable readmission
rates from other 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:
Rehospitalization During the First 30
Days of Home Health (NQF #2380), as
well as similar measures for other PAC
providers (NQF #2502 for IRFs, NQF
#2510 for SNFs NQF #2512 for
LTCHs).82 These measures are endorsed
by the NQF, and the NQF-endorsed
measure (NQF #2380) was adopted into
the HH QRP in the CY 2014 HH PPS
final rule (80 FR 68691 through 68692).
Note that these NQF-endorsed 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.83 84 85 Recent
79 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.
80 Wolff, J. L., Meadow, A., Weiss, C.O., Boyd,
C.M., Leff, B. Medicare Home Health Patients’
Transitions Through Acute And Post-Acute Care
Settings.’’ Medicare Care 11(46) 2008; 1188–1193.
81 Madigan, E. A., N. H. Gordon, et al.
‘‘Rehospitalization in a national population of home
health care patients with heart failure.’’ Health Serv
Res 47(6): 2013; 2316–2338.
82 National Quality Forum: All-Cause Admissions
and Readmissions Measures. pp. 1–319, April 2015.
Available from https://www.qualityforum.org/
Publications/2015/04/All-Cause_Admissions_and_
Readmissions_Measures_-_Final_Report.aspx.
83 Goldfield, N.I., McCullough, E.C., Hughes, J.S.,
et al. Identifying potentially preventable
readmissions. Health Care Finan. Rev. 30(1):75–91,
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work led by Kramer et al. for MedPAC
identified 13 conditions for which
readmissions were deemed as
potentially preventable among SNF and
IRF populations.86 87 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.88 89 90
Potentially Preventable Readmission
Measure Definition: We conducted a
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
2008. Available from https://www.ncbi.nlm.nih.gov/
pmc/articles/PMC4195042/.
84 National Quality Forum: Prevention Quality
Indicators Overview. 2008.
85 MedPAC: Online Appendix C: Medicare
Ambulatory Care Indicators for the Elderly. pp. 1–
12, prepared for Chapter 4, 2011. Available from
https://www.medpac.gov/documents/reports/Mar11_
Ch04_APPENDIX.pdf?sfvrsn=0.
86 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 https://www.medpac.gov/documents/
contractor-reports/development-of-inpatientrehabilitation-facility-quality-measures-potentiallyavoidable-readmissions-community-discharge-andfunctional-improvement.pdf?sfvrsn=0.
87 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 https://
www.medpac.gov/documents/contractor-reports/
mar14_snfqualitymeasures_
contractor.pdf?sfvrsn=0.
88 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.
89 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.
90 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.
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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 CY 2017 HH QRP proposed rule
available at https://www.cms.gov/
Medicare/Quality-Initiatives-PatientAssessment-Instruments/
HomeHealthQualityInits/
HHQIQualityMeasures.html.
This proposed measure focuses on
readmissions that are potentially
preventable and also unplanned.
Similar to the Rehospitalization During
the First 30 Days of Home Health
measure (NQF #2380), 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 https://www.cms.gov/
Medicare/Quality-Initiatives-PatientAssessment-Instruments/
HospitalQualityInits/MeasureMethodology.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 postacute care, can be found in the
document titled Proposed Measure
Specifications for Measures Proposed in
the CY 2017 HH QRP proposed rule
available at https://www.cms.gov/
Medicare/Quality-Initiatives-PatientAssessment-Instruments/
HomeHealthQualityInits/
HHQIQualityMeasures.html.
The proposed measure, Potentially
Preventable 30-Day Post-Discharge
Readmission Measure for HH 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 an agency-specific effect,
common to patients treated in each
agency. This proposed measure is
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calculated for each HHA based on the
ratio of the predicted number of riskadjusted, unplanned, potentially
preventable hospital readmissions that
occur within 30 days after an HH
discharge, including the estimated
agency effect, to the estimated predicted
number of risk-adjusted, unplanned
hospital readmissions for the same
patients treated at the average HHA. 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 HH
episodes. The resulting rate is the riskstandardized readmission rate (RSRR) of
potentially preventable readmissions.
An eligible HH episode 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 HHAs accounts
for demographic characteristics (age,
sex, original reason for Medicare
entitlement), principal diagnosis during
the prior proximal hospital stay, body
system specific surgical indicators,
comorbidities, length of stay during the
patient’s prior proximal hospital stay,
intensive care and coronary care unit
(ICU and CCU) utilization, ESRD status,
and number of acute care
hospitalizations in the preceding 365
days.
The proposed measure is calculated
using 3 consecutive calendar years of
FFS data, in order to ensure the
statistical reliability of this measure for
smaller agencies. In addition, we are
proposing a minimum of 20 eligible
episodes for public reporting of the
proposed measure. For technical
information about this proposed
measure including information about
the measure calculation, risk
adjustment, and exclusions, we refer
readers to our Proposed Measure
Specifications for Measures Proposed in
the CY 2017 HH QRP proposed rule at
https://www.cms.gov/Medicare/QualityInitiatives-Patient-Assessment-
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Instruments/HomeHealthQualityInits/
HHQIQualityMeasures.html.
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 NQF-convened 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 https://
www.qualityforum.org/Publications/
2016/02/MAP_2016_Considerations_
for_Implementing_Measures_in_
Federal_Programs_-_PAC-LTC.aspx.
At the time of the MAP, the riskadjustment 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
Rehospitalization During the First 30
Days of Home Health Measure (NQF
#2380) adopted into the HH QRP.
We reviewed the NQF’s consensus
endorsed measures and were unable to
identify any NQF-endorsed measures
focused on potentially preventable
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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 HH QRP under the
Secretary’s authority to specify nonNQF-endorsed measures under section
1899B(e)(2)(B) of the Act, for the HH
QRP for the CY 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 3 calendar years of
claims data from discharges in CYs
2014, 2015 and 2016. We intend to
publicly report this proposed measure
using claims data from CYs 2015, 2016
and 2017.
We are inviting public comment on
our proposal to adopt the measure,
Potentially Preventable 30-Day PostDischarge Readmission Measure for HH
QRP.
4. Proposal To Address the IMPACT Act
Domain of Medication Reconciliation:
Drug Regimen Review Conducted With
Follow-Up for Identified Issues—PostAcute Care Home Health Quality
Reporting Program
Section 1899B(c)(1)(C) of the Act
requires that no later than the specified
application date (which under section
1899B(a)(1)(E)(i) is October 1, 2018 for
SNFs, IRFs and LTCHs and January 1,
2017 for HHAs), the Secretary specify
quality measures to address the domain
of medication reconciliation. We are
proposing to adopt the quality measure,
Drug Regimen Review Conducted with
Follow-Up for Identified Issues—PAC
HH QRP for the HH QRP as a patientassessment based, cross-setting quality
measure to meet this requirement with
data collection beginning January 1,
2017, beginning with the CY 2018
payment determination.
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 episodes in which a drug
regimen review was conducted at the
start of care or resumption of care and
timely follow-up with a physician
occurred each time potential clinically
significant medication issues were
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identified throughout that episode. For
this proposed quality measure, a drug
regimen review is defined as the review
of all medications or drugs the patient
is taking in order to identify potential
clinically significant medication issues.
This 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 agency identified and
addressed each clinically significant
medication issue and if the agency
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.91 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).
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.92 The Joint Commission added
medication reconciliation to its list of
National Patient Safety Goals (2005),
suggesting that medication
reconciliation is an integral component
of medication safety.93 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.94 There is universal
91 Institute of Medicine. Preventing Medication
Errors. Washington, DC: National Academies Press;
2006.
92 Leotsakos A., et al. Standardization in patient
safety: The WHO High 5s project. Int J Qual Health
Care. 2014:26(2):109–116.
93 The Joint Commission. 2016 Long Term Care:
National Patient Safety Goals Medicare/Medicaid
Certification-based Option. (NPSG.03.06.01).
94 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.
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agreement that medication
reconciliation directly addresses patient
safety issues that can result from
medication miscommunication and
unavailable or incorrect
information.95 96 97 98
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,99 100 including
subsequent emergency room visits and
re-hospitalizations. ADEs are associated
with an estimated $3.5 billion in annual
health care costs and 7,000 deaths
annually.101
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.
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.102 103 104 105 106 107
95 IHI. Medication Reconciliation to Prevent
Adverse Drug Events [Internet]. Cambridge, MA:
Institute for Healthcare Improvement; [cited 2016
Jan 11]. Available from: https://www.ihi.org/topics/
adesmedicationreconciliation/Pages/default.aspx.
Leotsakos A., et al. Standardization in patient
safety: The WHO High 5s project. Int J Qual Health
Care. 2014:26(2):109–116.
96 The Joint Commission. 2016 Long Term Care:
National Patient Safety Goals Medicare/Medicaid
Certification-based Option. (NPSG.03.06.01).
97 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.
98 The Joint Commission. 2016 Long Term Care:
National Patient Safety Goals Medicare/Medicaid
Certification-based Option. (NPSG.03.06.01).
99 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.
100 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.
101 Kohn L.T., Corrigan J.M., Donaldson M.S., ‘‘To
Err Is Human: Building a Safer Health System,’’
National Academies Press, Washington, DC 1999
102 Institute of Medicine. To err is human:
Building a safer health system. Washington, DC:
National Academies Press; 2000.
103 Lesar T.S., Briceland L., Stein D.S. Factors
related to errors in medication prescribing. JAMA.
1997:277(4): 312–317.
104 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.
105 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.
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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.108 109
There is strong evidence that
medication discrepancies can occur
during transfers from acute care
facilities to post-acute care facilities.
Discrepancies can occur when there is
conflicting information documented in
the medical records. Almost one-third of
medication discrepancies have the
potential to cause patient harm.110
Potential medication problems upon
admission to HHAs have been reported
as occurring at a rate of 39 percent of
reviewed charts 111 and mean
medication discrepancies between 2.0
± 2.3 and 2.1 ± 2.4.112 Similarly,
medication discrepancies were noted as
patients transitioned from the hospital
to home health settings.113 An estimated
fifty percent of patients experienced a
clinically important medication error
after hospital discharge in an analysis of
two tertiary care academic hospitals.114
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
106 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.
107 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.
108 Institute of Medicine. To err is human:
Building a safer health system. Washington, DC:
National Academies Press; 2000
109 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.
110 Wong, J.D.., et al. ‘‘Medication reconciliation
at hospital discharge: Evaluating discrepancies.’’
Annals of Pharmacotherapy 42.10 (2008): 1373–
1379.
111 Vink J., Morton D., Ferreri S. MedicationRelated Problems in the Home Care Setting. The
Consultant Pharmacist. Vol 26 No 7 2011 478–484
112 Setter S.M., Corbett C.F., Neumiller J.J., Gates
B.J., et al. Effectiveness of a pharmacist-nurse
intervention on resolving medication discrepancies
for patients transitioning from hospital to home
health care, Am J Health-Syst Pharm, vol. 66, pp.
2027–2031, 2009
113 Zillich A.J., Snyder M.E., Frail C.K., Lewis J.L.,
et al. A Randomized, Controlled Pragmatic Trial of
Telephonic Medication Therapy Management to
Reduce Hospitalization in Home Health Patient,
Health Services Research, vol. 49, no. 5, pp. 1537–
1554, 2014.
114 Kripalani, Sunil, et al. ‘‘Effect of a pharmacist
intervention on clinically important medication
errors after hospital discharge: A randomized trial.
‘‘Annals of internal medicine 157.1 (2012): 1–10.
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medication reconciliation.115 116
Hospital discharge has been identified
as a particularly high risk time point,
with evidence that medication
reconciliation identifies high levels of
discrepancy.117 118 119 120 121 122 Also,
there is evidence that medication
reconciliation discrepancies occur
throughout the patient stay.123 124 With
respect to older patients who may have
multiple comorbid conditions and thus
multiple medications, transitions
between acute and post-acute care
settings can be further complicated,125
and medication reconciliation and
patient knowledge (medication literacy)
can be inadequate post-discharge.126
The proposed quality measure, Drug
Regimen Review Conducted with
Follow-Up for Identified Issues-PAC HH
115 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.
116 Gandara, Esteban, et al. ‘‘Deficits in discharge
documentation in patients transferred to
rehabilitation facilities on anticoagulation: Results
of a system wide evaluation.’’ Joint Commission
Journal on Quality and Patient Safety 34.8 (2008):
460–463.
117 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.
118 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.
119 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.
120 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.
121 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.
122 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.
123 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.
124 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.
125 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.
126 Hume K., Tomsik E. Enhancing Patient
Education and Medication Reconciliation Strategies
to Reduce Readmission Rates. Hosp Pharm; 2014;
49(2):112–114.
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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 settings each
year. For example, in 2013, 3.2 million
Medicare FFS beneficiaries had a home
health episode.
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 HH
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 quality measure, Drug
Regimen Review Conducted with
Follow-Up for Identified Issues-PAC HH
QRP. The MAP encouraged continued
development of the proposed quality
measure for the HH QRP to meet the
mandate of 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 https://
www.qualityforum.org/Setting_
Priorities/Partnership/MAP_Final_
Reports.aspx.
Since the MAP’s review, we have
continued to refine this proposed
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measure in compliance with the MAP’s
recommendations. The proposed
measure is both consistent with the
information submitted to the MAP and
supports its scientific acceptability for
use in the HH QRP. Therefore, we are
proposing this measure for
implementation in the HH 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 HH 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 HH QRP, which
reports the percentage of patient
episodes in which a drug regimen
review was conducted at the time of
admission and that timely follow-up
with a physician or physician-designee
occurred each time one or more
potential clinically significant
medication issues were identified
throughout that episode.
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 HH 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 HH QRP, employs
three standardized patient-assessment
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 HH
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QRP, requires the identification of
clinically potential medication issues at
the beginning, during and at the end of
the patient’s episode to capture data on
each patient’s complete HH episode;
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 HH
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 time frame (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 time
frame in which the follow-up would
need to occur;
• The proposed quality measure,
Drug Regimen Review Conducted with
Follow-Up for Identified Issues-PAC HH
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; and
• The proposed quality measure,
Drug Regimen Review Conducted with
Follow-Up for Identified Issues-PAC HH
QRP, would be reported to HHAs
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 HH
QRP, for the HH QRP for CY 2018
payment determination and subsequent
years. We plan to submit the quality
measure to the NQF for consideration of
endorsement.
The calculation of the proposed
quality measure would be based on the
data collection of three standardized
items that would be added to the
OASIS. The collection of data by means
of the standardized items would be
obtained at start or resumption of care
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and end of care. For more information
about the data submission required for
this proposed measure, we refer readers
to Section I. Form, Manner, and Timing
of OASIS Data Submission and OASIS
Data for Annual Payment Update.
The standardized items used to
calculate this proposed quality measure
will replace existing items currently
used for data collection within the
OASIS. The proposed measure
denominator is the number of patient
episodes with an end of care assessment
during the reporting period. The
proposed measure numerator is the
number of episodes in the denominator
where the medical record contains
documentation of a drug regimen review
conducted at: (1) Start or resumption of
care; and (2) end of care with a look
back through the home health patient
episode with all potential clinically
significant medication issues identified
during the course of care and followedup 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 CY 2017 HH QRP proposed rule
available at https://www.cms.gov/
Medicare/Quality-Initiatives-PatientAssessment-Instruments/
HomeHealthQualityInits/
HHQIQualityMeasures.html.
Data for the proposed quality
measure, Drug Regimen Review
Conducted with Follow-Up for
Identified Issues—PAC HH QRP, would
be collected using the OASIS with
submission through the QIES 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
HH QRP for CY 2018 APU
determination and subsequent years.
H. HH QRP Quality Measures and
Measure Concepts Under Consideration
for Future Years
We invite public comment on the
importance, relevance, appropriateness,
and applicability of each of the quality
measures listed in Table 33 for use in
future years in the HH QRP.
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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 also
considering application of two IMPACT
Act measures to the HH QRP, to assess
the incidence of falls with major injury
and functional assessment and goals
setting. We are additionally considering
application of four standardized
functional measures to the HH QRP; two
that would assess change in function
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across the HH episode and two that
would assess actual function at
discharge relative to expected function.
Finally, we are considering a measure
related to health and well-being, Percent
of Residents or Patients Who Were
Assessed and Appropriately Given the
Seasonal Influenza Vaccine (Short Stay).
Based on input from stakeholders, we
have identified additional concept areas
for potential future measure
development for the HH QRP. These
include ‘‘efficacy’’ measures that pair
processes, such as assessment and care
planning, with outcomes, such as
emergency treatment for injuries or
increase in pain. The prevalence of
mental health and behavioral problems
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was identified as an option to address
outcomes for special populations. In
addition, CMS is considering
development of measures that assess if
functional abilities were maintained
during a care episode and composite
measures that combine multiple
evidence-based processes. CMS invites
feedback on the importance, relevance,
appropriateness, and applicability of
these measure constructs.
I. Form Manner and Timing of OASIS
Data Submission and OASIS Data for
Annual Payment Update
1. Regulatory Authority
The HH conditions of participation
(CoPs) at § 484.55(d) require that the
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comprehensive assessment be updated
and revised (including the
administration of the OASIS) no less
frequently than: (1) The last 5 days of
every 60 days beginning with the start
of care date, unless there is a
beneficiary-elected transfer, significant
change in condition, or discharge and
return to the same HHA during the 60day episode; (2) within 48 hours of the
patient’s return to the home from a
hospital admission of 24-hours or more
for any reason other than diagnostic
tests; and (3) at discharge.
It is important to note that to calculate
quality measures from OASIS data,
there must be a complete quality
episode, which requires both a Start of
Care (initial assessment) or Resumption
of Care OASIS assessment and a
Transfer or Discharge OASIS
assessment. Failure to submit sufficient
OASIS assessments to allow calculation
of quality measures, including transfer
and discharge assessments, is a failure
to comply with the CoPs.
HHAs are not required to submit
OASIS data for patients who are
excluded from the OASIS submission
requirements as described in the
December 23, 2005, final rule ‘‘Medicare
and Medicaid Programs: Reporting
Outcome and Assessment Information
Set Data as Part of the Conditions of
Participation for Home Health
Agencies’’ (70 FR 76202).
As set forth in the CY 2008 HH PPS
final rule (72 FR 49863), HHAs that
become Medicare certified on or after
May 31 of the preceding year are not
subject to the OASIS quality reporting
requirement nor any payment penalty
for quality reporting purposes for the
following year. For example, HHAs
certified on or after May 31, 2014, are
not subject to the 2 percentage point
reduction to their market basket update
for CY 2015. These exclusions only
affect quality reporting requirements
and payment reductions, and do not
affect the HHA’s reporting
responsibilities as announced in the
December 23, 2005 OASIS final rules
(70 FR 76202).
2. Home Health Quality Reporting
Program Requirements for CY 2017
Payment and Subsequent Years
In the CY 2014 HH PPS final rule (78
FR 72297), we finalized a proposal to
consider OASIS assessments submitted
by HHAs to CMS in compliance with
HH CoPs and Conditions for Payment
for episodes beginning on or after July
1, 2012, and before July 1, 2013, as
fulfilling one portion of the quality
reporting requirement for CY 2014.
In addition, we finalized a proposal to
continue this pattern for each
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subsequent year beyond CY 2014.
OASIS assessments submitted for
episodes beginning on July 1 of the
calendar year 2 years prior to the
calendar year of the Annual Payment
Update (APU) effective date and ending
June 30 of the calendar year one year
prior to the calendar year of the APU
effective date; fulfill the OASIS portion
of the HH QRP requirement.
3. Previously Established Pay-forReporting Performance Requirement for
Submission of OASIS Quality Data
Section 1895(b)(3)(B)(v)(I) of the Act
states that for 2007 and each subsequent
year, the home health market basket
percentage increase applicable under
such clause for such year shall be
reduced by 2 percentage points if a
home health agency does not submit
quality data to the Secretary in
accordance with subclause (II) for such
a year. This pay-for-reporting
requirement was implemented on
January 1, 2007. In the CY 2016 HH PPS
final rule (80 FR 68703 through 68705),
we finalized a proposal to define the
quantity of OASIS assessments each
HHA must submit to meet the pay-forreporting requirement. We designed a
pay-for-reporting performance system
model that could accurately measure the
level of an HHA’s submission of OASIS
data. The performance system is based
on the principle that each HHA is
expected to submit a minimum set of
two matching assessments for each
patient admitted to their agency. These
matching assessments together create
what is considered a quality episode of
care, consisting ideally of a Start of Care
(SOC) or Resumption of Care (ROC)
assessment and a matching End of Care
(EOC) assessment.
Section 80 of Chapter 10 of the
Medicare Claims Processing Manual
states, ‘‘If a Medicare beneficiary is
covered under an MA Organization
during a period of home care, and
subsequently decides to change to
Medicare FFS coverage, a new start of
care OASIS assessment must be
completed that reflects the date of the
beneficiary’s change to this pay source.’’
We wish to clarify that the SOC OASIS
assessment submitted when this change
in coverage occurs will not be used in
our determination of a quality
assessment for the purpose of
determining compliance with data
submission requirements. In such a
circumstance, the original SOC or ROC
assessment submitted while the
Medicare beneficiary is covered under
an MA Organization would be
considered a quality assessment within
the pay-for-reporting, APU, Quality
Assessments Only methodology. For
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further information on successful
submission of OASIS assessments, types
of assessments submitted by an HHA
that fit the definition of a quality
assessment, defining the ‘‘Quality
Assessments Only’’ (QAO) formula, and
implementing a pay-for-reporting
performance requirement over a 3-year
period, please see the CY 2016 HH PPS
final rule (80 FR 68704 to 68705). HHAs
must score at least 70 percent on the
QAO metric of pay-for-reporting
performance requirement for CY 2017
(reporting period July 1, 2015 to June
30, 2016), 80 percent for CY 2018
(reporting period July 1, 2016 to June
30, 2017) and 90 percent for CY 2019
(reporting period July 1, 2017 to June
30, 2018) or be subject to a 2 percentage
point reduction to their market basket
update for that reporting period.
In this proposed rule we are not
proposing any additional policies
related to the pay-for-reporting
performance requirement.
4. Proposed Timeline and Data
Submission Mechanisms for Measures
Proposed for the CY 2018 Payment
Determination and Subsequent Years
a. Claims Based Measures
The MSPB–PAC HH QRP, Discharge
to Community—PAC HH QRP, and
Potentially Preventable 30-Day PostDischarge Readmission Measure for HH
QRP, 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 HHAs.
As previously discussed in V.G., for the
Discharge to Community—PAC HH QRP
measure we propose to use 2 years of
claims data, beginning with CYs 2015
and 2016 claims data to inform
confidential feedback and CYs 2016 and
2017 claims data for public reporting.
For the Potentially Preventable 30-Day
Post-Discharge Readmission Measure for
HH QRP we propose to use 3 years of
claims data, beginning with CY 2014,
2015 and 2016 claims data to inform
confidential feedback reports for HHAs,
and CY 2015, 2016 and 2017 claims data
for public reporting. For the MSPB–PAC
HH QRP measure, we propose to use
one year of claims data beginning with
CY 2016 claims data to inform
confidential feedback reports for HHAs,
and CY 2017 claims data for public
reporting for the HH QRP.
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b. Assessment-Based Measures Using
OASIS Data Collection
As discussed in section V.G of this
proposed rule, for the proposed
measure, Drug Regimen Review
Conducted with Follow-Up for
Identified Issues—PAC HH QRP,
affecting CY 2018 payment
determination and subsequent years, we
are proposing that HHAs would submit
data by completing data elements on the
OASIS and then submitting the OASIS
to CMS through the QIES ASAP system
beginning January 1, 2017. For more
information on HH QRP reporting
through the QIES ASAP system, refer to
CMS Web site at https://www.cms.gov/
Medicare/Quality-Initiatives-PatientAssessment-Instruments/
HomeHealthQualityInits/
HHQIOASISUserManual.html.
We propose to use standardized data
elements in OASIS C2 to calculate the
proposed measure: Drug Regimen
Review Conducted with Follow-Up for
Identified Issues—PAC HH QRP. The
data elements necessary to calculate this
measure using the OASIS are available
on our Web site at https://www.cms.gov/
Medicare/Quality-Initiatives-PatientAssessment-Instruments/
HomeHealthQualityInits/
HHQIQualityMeasures.html.
We invite public comments on the
proposed HH QRP data collection
requirements for the proposed measure
affecting CY 2018 payment
determination and subsequent years.
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5. Proposed Timeline and Data
Submission Mechanisms for the CY
2018 Payment Determination and
Subsequent Years for New HH QRP
Assessment-Based Quality Measure
In the CY 2016 HH PPS final rule (80
FR 68695 through 68698) for the FY
2018 payment determination, we
finalized that HHAs must submit data
on the quality measure NQF #0678
Percent of Residents or Patients with
Pressure Ulcers that are New or
Worsened (Short Stay) using CY 2017
data, for example, patients who are
admitted to the HHA on and after
January 1, 2017, and discharged from
the HHA up to and including December
31, 2017. However, for CY 2018 APU
purposes this timeframe would be
impossible to achieve, given the
processes we have established
associated with APU determinations,
such as the opportunity for providers to
seek reconsideration for determinations
of non-compliance. Therefore, for both
the measure NQF #0678 Percent of
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Residents or Patients with Pressure
Ulcers that are New or Worsened (Short
Stay) that we finalized in the CY 2016
HH PPS rule, and the CY 2017 HH PPS
proposed measure, Drug Regimen
Review Conducted with Follow-Up for
Identified Issues—PAC HH QRP, we
propose that we would collect two
quarters of data for CY 2018 APU
determination to remain consistent with
the January release schedule for the
OASIS and to give HHAs sufficient time
to update their systems so that they can
comply with the new data reporting
requirements, and to give us a sufficient
amount of time to determine
compliance for the CY 2018 program.
The proposed use of two quarters of
data for the initial year of quality
reporting is consistent with the
approach we have used to implement
new measures in a number of other
QRPs, including the LTCH, IRF, and
Hospice QRPs in which only one
quarter of data was used.
We invite public comments on our
proposal to adopt a calendar year data
collection time frame, using an initial 6month reporting period from January 1,
2017, to June 30, 2017 for CY 2018
payment determinations, for the
application of measure NQF #0678
Percent of Residents or Patients with
Pressure Ulcers that are New or
Worsened (Short Stay) that we finalized
in the CY 2016 HH PPS rule, and the CY
2017 HH PPS proposed measure, Drug
Regimen Review Conducted with
Follow-Up for Identified Issues—PAC
HH QRP.
6. Data Collection Timelines and
Requirements for the CY 2019 Payment
Determinations and Subsequent Years
In CY 2014 HH PPS final rule (78 FR
72297), we finalized our use of a July 1–
June 30 time frame for APU
determinations. In alignment with the
previously established timeframe data
collection for a given calendar year APU
determination time period, beginning
with the CY 2019 payment
determination, we propose for both the
finalized measure, NQF #0678 Percent
of Residents or Patients with Pressure
Ulcers that are New or Worsened (Short
Stay), and the proposed measure, Drug
Regimen Review Conducted with
Follow-Up for Identified Issues—PAC
HH QRP, to use 12 months of data
collection, specifically assessments
submitted July 1, 2017 through June 30,
2018, for the CY 2019 payment
determination. We further propose to
continue to use the same 12-month
timeframe of July 1–June 30 for these
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measures for subsequent years for APU
determinations.
We invite comment on these
proposals for the data collection
timelines and requirements.
7. Proposed Data Review and Correction
Timeframes for Data Submitted Using
the OASIS Instrument
In addition, to remain consistent with
the SNF, LTCH and IRF QRPs, as well
as to comply with the requirements of
section of section 1899B(g) of the Act,
we are also proposing to implement
calendar year provider review and
correction periods for the OASIS
assessment-based quality measures
implemented into the HH QRP in
satisfaction of the IMPACT Act, that is,
finalized NQF #0678 Percent of
Residents or Patients with Pressure
Ulcers that are New or Worsened (Short
Stay) and the proposed Drug Regimen
Review Conducted with Follow-Up for
Identified Issues—PAC HH QRP. More
specifically, we are proposing that
HHAs would have approximately 4.5
months after the reporting quarter to
correct any errors of their assessmentbased data (that appear on the CASPER
generated Quality Measure reports) to
calculate the measures. During the time
of data submission for a given quarterly
reporting period and up until the
quarterly submission deadline, HHAs
could review and perform corrections to
errors in the assessment data used to
calculate the measures and could
request correction of measure
calculations. However, once the
quarterly submission deadline occurs,
the data is ‘‘frozen’’ and calculated for
public reporting and providers can no
longer submit any corrections. As laid
out in Table 34, the first calendar year
reporting quarter is January 1, 2017
through March 31, 2017. The final
deadline for submitting corrected data
would be August 15, 2017 for CY
Quarter 1, and subsequently and
sequentially, November 15, 2017 for CY
2017 Quarter 2, February 15, 2018 for
CY 2017 Quarter 3 and May 15, 2018 for
CY 2017 Quarter 4. We note that this
proposal to review and correct data does
not replace other requirements
associated with timely data submission.
We would encourage HHAs 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.
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We invite public comments on our
proposal to adopt a calendar year data
collection time frame, with a 4.5 month
period of time for review and correction
beginning with CY 2017 for the measure
NQF #0678 Percent of Residents or
Patients with Pressure Ulcers that are
New or Worsened (Short Stay) that we
finalized in the CY 2016 HH PPS rule,
and the CY 2017 HH PPS proposed
measure, Drug Regimen Review
Conducted with Follow-Up for
Identified Issues-PAC HH QRP for the
HH QRP.
Further, we propose that the OASIS
assessment-based measures already
finalized for adoption into the HH QRP
follow a similar CY schedule of data
reporting using quarterly data
collection/submission reporting periods
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followed by 4.5 months during which
providers will have an opportunity to
review and correct their data up until
the quarterly data submission deadlines
as provided in Table 35 for all reporting
years unless otherwise specified. This
policy would apply to all proposed and
finalized assessment-based measures in
the HH QRP.
TABLE 35—PROPOSED CY DATA COLLECTION SUBMISSION QUARTERLY REPORTING PERIODS, QUARTERLY REVIEW AND
CORRECTION PERIODS AND DATA SUBMISSION DEADLINES FOR MEASURES SPECIFIED IN SATISFACTION OF THE IMPACT ACT IN SUBSEQUENT YEARS
Proposed data
collection/submission
quarterly reporting
period
Proposed quarterly
review and correction
periods and data
submission quarterly deadlines *
Proposed
correction
deadlines *
January 1–March 31 ...............................
April 1–June 30 .......................................
July 1–September 30 ..............................
October 1–December 31 ........................
April 1–August 15 ...................................
July 1–November 15 ...............................
October 1–February 15 ...........................
January 1–May 15 ..................................
August 15.
November 15.
February 15.
May 15.
Proposed CY data
collection quarter
Quarter
Quarter
Quarter
Quarter
1
2
3
4
..................................................
..................................................
..................................................
..................................................
We invite public comment on our use
of CY quarterly data collection/
submission reporting periods with
quarterly data submission deadlines that
follow a period of approximately 4.5
months of time to enable the review and
correction of such data for OASIS
assessment-based measures.
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J. Public Display of Quality Measure
Data for the HH QRP and Procedures for
the Opportunity To Review and Correct
Data and Information
Medicare home health regulations, as
codified at § 484.250(a), require HHAs
to submit OASIS assessments and Home
Health Care Consumer Assessment of
Healthcare Providers and Systems
Survey® (HHCAHPS) data to meet the
quality reporting requirements of
section 1895(b)(3)(B)(v) of the Act.
Section 1899B(g) of the Act requires that
data and information of provider
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performance on quality measures and
resource use and other measures be
made publicly available beginning not
later than 2 years after the applicable
specified application date. In future
rulemaking, we intend to propose a
policy to publicly display performance
information for individual HHAs on
IMPACT Act measures, as required
under the Act. In addition, sections
1895(b)(3)(B)(v)(III) and 1899B(g) of the
Act require the Secretary to establish
procedures for making data submitted
under subclause (II) available to the
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public. Under section 1899B(g)(2), such
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 a home health agency has
the opportunity to review and submit
corrections to its data and information
that are to be made public for the agency
prior to such data being made public
through a process consistent with the
Hospital Inpatient Quality Reporting
Program (Hospital IQR). We recognize
that public reporting of quality data is
a vital component of a robust quality
reporting program and are fully
committed to ensuring that the data
made available to the public are
meaningful. Further, we agree that
measures for comparing performance
across home health agencies requires
should be constructed from data
collected in a standardized and uniform
manner. In this proposed rule, we are
proposing procedures that would allow
individual HHAs to review and correct
their data and information on IMPACT
Act measures that are to be made public
before those measure data are made
public.
1. Proposals for the Review and
Correction of Data Used To Calculate
the Assessment-Based Measures Prior to
Public Display
As provided in section V.I.7., and in
Table 34, for assessment-based
measures, we are proposing to provide
confidential feedback reports to HHAs
that contain performance information
that the HHAs can review, during the
review and correction period, and
correct the data used to calculate the
measures for the HH QRP that the HHA
submitted via the QIES ASAP system. In
addition, during the review period, the
HHA 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 HHA using the Certification and
Survey Provider Enhanced Reporting
(CASPER) System. We refer to these
reports as the HH Quality Measure (QM)
Reports. We intend to provide monthly
updates to the data contained in these
reports that pertain to assessment-based
data, as data become available. The
reports will contain both agency- and
patient-level data used to calculate the
assessment-based quality measures. The
CASPER facility level QM reporting
would include the numerator,
denominator, agency rate, and national
rate. The CASPER patient-level QM
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Reports would also contain individual
patient information that HHAs can use
to identify patients that were included
in the quality measures so as to identify
any potential errors. In addition, we
would make other reports available to
HHAs through the CASPER System,
including OASIS data submission
reports and provider validation reports,
which would contain information on
each HHA’s data submission status,
including details on all items the HHA
submitted in relation to individual
assessments and the status of the HHA’s
assessment (OASIS) records that they
submitted. When available, additional
information regarding the content and
availability of these confidential
feedback reports would be provided on
the HH QRP Web site https://
www.cms.gov/Medicare/QualityInitiatives-Patient-AssessmentInstruments/HomeHealthQualityInits/
index.html.
As previously proposed in section
V.I.7., for those measures that use
assessment-based data, HHAs would
have 4.5 months after the conclusion of
each reporting quarter to review and
update their reported measure data for
the quarter, including correcting any
errors that they find on the CASPERgenerated Review and Correct, QM
reports pertaining to their assessmentbased data used to calculate the
assessment-based measures. However, at
the conclusion of this 4.5 month review
and correction period, the data reported
for that quarter would be ‘‘frozen’’ and
used to calculate measure rates for
public reporting. We would encourage
HHAs to submit timely assessment data
during each quarterly reporting period
and to review their data and information
early during the 4.5 month review and
correction period so they can identify
errors and resubmit data before the data
submission deadline.
We believe that the proposed data
submission period along with a review
and correction period, consisting of the
reporting quarter plus approximately 4.5
months, is sufficient time for HHAs to
submit, review and, where necessary,
correct their data and information. We
also propose that, in addition to the data
submission/correction and review
period, HHAs will have a 30-day
preview period prior to public display
during which they can preview the
performance information on their
measures that will be made public. We
also propose to provide this preview
report using the Certification and
Survey Provider Enhanced Reporting
(CASPER) System because HHAs are
familiar with this system. The CASPER
preview reports for the reporting quarter
would be available after the 4.5 month
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review and correction period ends, and
would be refreshed quarterly or
annually for each measure, depending
on the length of the reporting period for
that measure. We propose to give HHAs
30 days to review this information,
beginning from the date on which they
can access the preview report.
Corrections to the underlying data
would not be permitted during this
time; however, HHAs would be able to
ask for a correction to their measure
calculations during the 30-day preview
period. If we determine that the
measure, as it is displayed in the
preview report, contains a calculation
error, we would suppress the data on
the public reporting Web site,
recalculate the measure and publish the
corrected rate at the time of the next
scheduled public display date. This
process is consistent with informal
processes used in the Hospital IQR
program. If finalized, we intend to
utilize a subregulatory mechanism, such
as our HH QRP Web site, to explain the
technical details for how and when
providers may contest their measure
calculations. We further propose to
increase the current preview period of
15 days to 30 days beginning with the
public display of the measures finalized
for the CY 2018 payment determination.
This preview period would include all
measures that are to be publicly
displayed under the current quarterly
refresh schedule used for posting
quality measure data on the
Medicare.gov Home Health Compare
site.
We invite public comment on these
proposals.
2. Proposals for Review and Correction
of Data Used To Calculate Claims-Based
Measures Prior To Public Display
In addition to assessment-based
measures, we have also proposed
claims-based measures for the HH QRP.
As noted previously, 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 procedures, for claims-based
measures, we give hospitals 30 days to
preview their claims-based measures
and data in a preview report containing
aggregate hospital-level data. We
propose to adopt a similar process for
the HH 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
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to their claims-based measure rate
calculations, including agency and
national rates. 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 rates.
We propose to create data extracts
using claims data for these claims based
measures, at least 90 days after the last
discharge date in the applicable period
(12 calendar months preceding), 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, 2017, 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 the 2017
reporting period. We propose that
beginning with data for measures that
will be publicly displayed by January 1,
2019, and for which will need to
coincide with the quarterly refresh
schedule on Home Health Compare, the
claims-based measures will be
calculated at least 90 days after the last
discharge date using claims data from
the applicable reporting period. This
timeframe allows us to balance the need
to provide timely program information
to HHAs with the need to calculate the
claims-based measures using as
complete a data set as possible. Since
HHAs would not be able to submit
corrections to the underlying claims
snapshot or add claims (for those
measures that use HH claims) to this
data set, at the conclusion of the 90-day
period following the last date of
discharge used in the applicable period,
we would consider the HH claims data
to be complete for purposes of
calculating the claims-based measures.
We wish to convey the importance that
HHAs ensure the completeness and
correctness of their claims prior to the
claims ‘‘snapshot’’. We seek to have as
complete a data set as possible. We
recognize that the proposed
approximately 90 day ‘‘run-out’’ period
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 approximately 90 day run-out
period is appropriate to calculate the
claims-based 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, and/or episode-
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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 HHAs sooner than 18
to 24 months after the last discharge. We
believe this would create an
unacceptably long delay, both for HHAs
and for us to deliver timely calculations
to HHAs for quality improvement.
As noted, under this proposed
procedure, during the 30-day preview
period, HHAs would not be able to
submit corrections to the underlying
claims data or add new claims to the
data extract. This is for two reasons.
First, for certain measures, some of the
claims data used to calculate the
measure are derived not from the HHA’s
claims, but from the claims of another
provider. For example, the proposed
measure Potentially Preventable 30-Day
Post-Discharge Readmission Measure for
HH QRP uses claims data submitted by
the hospital to which the patient was
readmitted. HHAs are not able to make
corrections to these hospital claims,
although the agency could request that
the hospital reconfirm that its
submissions are correct. Second, even
where HHA claims are used to calculate
the measures, it would 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.
As noted previously, we propose to
provide HHAs a 30-day preview period
to review their confidential preview
reports. HHAs would have 30 days from
the date the preview report is made
available to review this information.
The 30-day preview period would be
the only time when HHAs would be
able to see their claims-based measure
rates before they are publicly displayed.
HHAs could request that we correct our
measure calculation during the 30-day
preview period if the HHA believes the
measure rate is incorrect. If we agree
that the measure rate, as it is displayed
in the preview report, contains a
calculation error, we would suppress
the data on the public reporting Web
site, recalculate the measure, and
publish the corrected measure rate at
the time of the next scheduled public
display date. If finalized, we intend to
utilize a subregulatory mechanism, such
as our HH QRP Web site, to explain the
technical details regarding how and
when providers may contest their
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measure calculations. We refer readers
to the discussion inV.I.2 for additional
information on these preview reports.
In addition, because the claims-based
measures used for the HH QRP are recalculated on an annual basis, these
confidential CASPER QM preview
reports for claims-based measures
would be refreshed annually. An annual
refresh is being utilized to ensure
consistency in our display of claims
based measures, and it will include both
claims-based measures that satisfy the
IMPACT Act, as well as all other HH
QRP claims-based measures.
We invite public comment on these
proposals for the public display of
quality measure data.
K. Mechanism for Providing Feedback
Reports to HHAs
Section 1899B(f) of the Act requires
the Secretary to provide confidential
feedback measure reports to post-acute
care providers on their performance on
the measures specified under
paragraphs (c)(1) and (d)(1), beginning 1
year after the specified application date
that applies to such measures and PAC
providers. We propose to build upon the
current confidential quality measure
reports we already generate for HHAs so
as to also provide data and information
on the measures implemented in
satisfaction of the IMPACT Act. As a
result, HHAs could review their
performance on these measures, as well
as those already adopted in the HH
QRP. We propose that these additional
confidential feedback reports would be
made available to each HHA through the
CASPER System. Data contained within
these CASPER reports would be
updated, as previously described, on a
monthly basis as the data become
available except for claims-based
measures, which will only be updated
on an annual basis.
We intend to provide detailed
procedures to HHAs on how to obtain
their new confidential feedback reports
in CASPER on the HH QRP Web site at
https://www.cms.gov/Medicare/QualityInitiatives-Patient-AssessmentInstruments/HomeHealthQualityInits/
Home-Health-Quality-ReportingRequirements.html. We also propose to
use the QIES ASAP system to provide
these new confidential quality measure
reports in a manner consistent with how
HHAs have obtained such reports to
date. The QIES ASAP system is a
confidential and secure system with
access granted to providers, or their
designees.
We invite public comment on this
proposal to satisfy the requirement to
provide confidential feedback reports to
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L. Home Health Care CAHPS® Survey
(HHCAHPS)
In the CY 2016 HH PPS final rule (80
FR 68623), we stated that the home
health quality measures reporting
requirements for Medicare-certified
agencies includes the Home Health Care
CAHPS® (HHCAHPS) Survey for the CY
2017 and 2018 Annual Payment Update
(APU) periods. We are continuing to
maintain the stated HHCAHPS data
requirements for CY 2017 and CY 2018
that were stated in CY 2016 and in
previous HH PPS rules, for the
continuous monthly data collection and
quarterly data submission of HHCAHPS
data.
1. Background and Description of
HHCAHPS
As part of the HHS Transparency
Initiative, we implemented a process to
measure and publicly report patient
experiences with home health care,
using a survey developed by the Agency
for Healthcare Research and Quality’s
(AHRQ’s) Consumer Assessment of
Healthcare Providers and Systems
(CAHPS®) program and endorsed by the
National Quality Forum (NQF) in March
2009 (NQF Number 0517) and NQF reendorsed in 2015. The HHCAHPS
Survey is approved under OMB Control
Number 0938–1066. The HHCAHPS
survey is part of a family of CAHPS®
surveys that asks patients to report on
and rate their experiences with health
care. The Home Health Care CAHPS®
(HHCAHPS) survey presents home
health patients with a set of
standardized questions about their
home health care providers and about
the quality of their home health care.
Prior to this survey, there was no
national standard for collecting
information about patient experiences
that enabled valid comparisons across
all HHAs. The history and development
process for HHCAHPS has been
described in previous rules and is also
available on the official HHCAHPS Web
site at https://homehealthcahps.org and
in the annually-updated HHCAHPS
Protocols and Guidelines Manual,
which is downloadable from https://
homehealthcahps.org.
Since April 2012, for public reporting
purposes, we report five measures from
the HHCAHPS Survey—three composite
measures and two global ratings of care
that are derived from the questions on
the HHCAHPS survey. The publicly
reported data are adjusted for
differences in patient mix across HHAs.
We update the HHCAHPS data on Home
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quarterly. Each HHCAHPS composite
measure consists of four or more
individual survey items regarding one of
the following related topics:
• Patient care (Q9, Q16, Q19, and
Q24);
• Communications between providers
and patients (Q2, Q15, Q17, Q18, Q22,
and Q23); and
• Specific care issues on medications,
home safety, and pain (Q3, Q4, Q5, Q10,
Q12, Q13, and Q14).
The two global ratings are the overall
rating of care given by the HHA’s care
providers (Q20), and the patient’s
willingness to recommend the HHA to
family and friends (Q25).
The HHCAHPS survey is currently
available in English, Spanish, Chinese,
Russian, and Vietnamese. The OMB
number on these surveys is the same
(0938–1066). All of these surveys are on
the Home Health Care CAHPS® Web
site, https://homehealthcahps.org. We
continue to consider additional
language translations of the HHCAHPS
in response to the needs of the home
health patient population.
All of the requirements about home
health patient eligibility for the
HHCAHPS survey and conversely,
which home health patients are
ineligible for the HHCAHPS survey are
delineated and detailed in the
HHCAHPS Protocols and Guidelines
Manual, which is downloadable at
https://homehealthcahps.org. Home
health patients are eligible for
HHCAHPS if they received at least two
skilled home health visits in the past 2
months, which are paid for by Medicare
or Medicaid.
Home health patients are ineligible for
inclusion in HHCAHPS surveys if one of
these conditions pertains to them:
• Are under the age of 18;
• Are deceased prior to the date the
sample is pulled;
• Receive hospice care;
• Receive routine maternity care only;
• Are not considered survey eligible
because the state in which the patient
lives restricts release of patient
information for a specific condition or
illness that the patient has; or
• Are ‘‘No Publicity’’ patients,
defined as patients who on their own
initiative at their first encounter with
the HHAs make it very clear that no one
outside of the agencies can be advised
of their patient status, and no one
outside of the HHAs can contact them
for any reason.
We stated in previous rules that
Medicare-certified HHAs are required to
contract with an approved HHCAHPS
survey vendor. This requirement
continues, and Medicare-certified
agencies also must provide on a
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monthly basis a list of their patients
served to their respective HHCAHPS
survey vendors. Agencies are not
allowed to influence at all how their
patients respond to the HHCAHPS
survey.
As previously required, HHCAHPS
survey vendors are required to attend
introductory and all update trainings
conducted by CMS and the HHCAHPS
Survey Coordination Team, as well as to
pass a post-training certification test.
We have approximately 30 approved
HHCAHPS survey vendors. The list of
approved HHCAHPS survey vendors is
available at https://
homehealthcahps.org.
2. HHCAHPS Oversight Activities
We stated in prior final rules that all
approved HHCAHPS survey vendors are
required to participate in HHCAHPS
oversight activities to ensure
compliance with HHCAHPS protocols,
guidelines, and survey requirements.
The purpose of the oversight activities
is to ensure that approved HHCAHPS
survey vendors follow the HHCAHPS
Protocols and Guidelines Manual.
In the CY 2013 HH PPS final rule (77
FR 67094, 67164), we codified the
current guideline that all approved
HHCAHPS survey vendors fully comply
with all HHCAHPS oversight activities.
We included this survey requirement at
§ 484.250(c)(3).
3. HHCAHPS Requirements for the CY
2017 APU
For the CY 2017 APU, we require
continuous monthly HHCAHPS data
collection and reporting for four
quarters. The data collection period for
the CY 2017, APU includes the second
quarter 2015 through the first quarter
2016 (the months of April 2015 through
March 2016). HHAs are required to
submit their HHCAHPS data files to the
HHCAHPS Data Center for the second
quarter 2015 by 11:59 p.m., EST on
October 15, 2015; for the third quarter
2015 by 11:59 p.m., EST on January 21,
2016; for the fourth quarter 2015 by
11:59 p.m., EST on April 21, 2016; and
for the first quarter 2016 by 11:59 p.m.,
EST on July 21, 2016. These deadlines
are firm; no exceptions are permitted.
For the CY 2017 APU, we require that
all HHAs with fewer than 60
HHCAHPS-eligible unduplicated or
unique patients in the period of April 1,
2014, through March 31, 2015, are
exempt from the HHCAHPS data
collection and submission requirements
for the CY 2017 APU, upon completion
of the CY 2017 HHCAHPS Participation
Exemption Request form, and upon
CMS verification of the HHA patient
counts. Agencies with fewer than 60
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HHCAHPS-eligible, unduplicated or
unique patients in the period of April 1,
2014, through March 31, 2015, are
required to submit their patient counts
on the CY 2017 HHCAHPS Participation
Exemption Request form posted on
https://homehealthcahps.org from April
1, 2015, to 11:59 p.m., EST to March 31,
2016. This deadline is firm, as are all of
the quarterly data submission deadlines
for the HHAs that participate in
HHCAHPS.
We automatically exempt HHAs
receiving Medicare certification after the
period in which HHAs do their patient
count. HHAs receiving Medicarecertification on or after April 1, 2015,
are exempt from the HHCAHPS
reporting requirement for the CY 2017
APU. These newly-certified HHAs do
not need to complete the HHCAHPS
Participation Exemption Request Form
for the CY 2017 APU.
4. HHCAHPS Requirements for the CY
2018 APU
For the CY 2018 APU, we require
continuous monthly HHCAHPS data
collection and reporting for four
quarters. The data collection period for
the CY 2018, APU includes the second
quarter 2016 through the first quarter
2017 (the months of April 2016 through
March 2017). HHAs will be required to
submit their HHCAHPS data files to the
HHCAHPS Data Center for the second
quarter 2016 by 11:59 p.m., EST on
October 20, 2016; for the third quarter
2016 by 11:59 p.m., EST on January 19,
2017; for the fourth quarter 2016 by
11:59 p.m., EST on April 20, 2017; and
for the first quarter 2017 by 11:59 p.m.,
EST on July 20, 2017. These deadlines
are firm; no exceptions will be
permitted.
For the CY 2018 APU, we require that
all HHAs with fewer than 60
HHCAHPS-eligible unduplicated or
unique patients in the period of April 1,
2015 through March 31, 2016, are
exempt from the HHCAHPS data
collection and submission requirements
for the CY 2018 APU, upon completion
of the CY 2018 HHCAHPS Participation
Exemption Request form, and upon
CMS verification of the HHA patient
counts. Agencies with fewer than 60
HHCAHPS-eligible, unduplicated or
unique patients in the period of April 1,
2015, through March 31, 2016, are
required to submit their patient counts
on the CY 2018 HHCAHPS Participation
Exemption Request form posted on
https://homehealthcahps.org from April
1, 2016, to 11:59 p.m., EST to March 31,
2017. This deadline is firm, as are all of
the quarterly data submission deadlines
for the HHAs that participate in
HHCAHPS.
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We automatically exempt HHAs
receiving Medicare certification after the
period in which HHAs do their patient
count. HHAs receiving Medicarecertification on or after April 1, 2016,
are exempt from the HHCAHPS
reporting requirement for the CY 2018
APU. These newly-certified HHAs do
not need to complete the HHCAHPS
Participation Exemption Request Form
for the CY 2018 APU.
5. HHCAHPS Requirements for the CY
2019 APU
For the CY 2019 APU, we require
continuous monthly HHCAHPS data
collection and reporting for four
quarters. The data collection period for
the CY 2018, APU includes the second
quarter 2017 through the first quarter
2018 (the months of April 2017 through
March 2018). HHAs will be required to
submit their HHCAHPS data files to the
HHCAHPS Data Center for the second
quarter 2017 by 11:59 p.m., EST on
October 19, 2017; for the third quarter
2017 by 11:59 p.m., EST on January 18,
2018; for the fourth quarter 2017 by
11:59 p.m., EST on April 19, 2018; and
for the first quarter 2018 by 11:59 p.m.,
EST on July 19, 2018. These deadlines
are firm; no exceptions will be
permitted.
For the CY 2019 APU, we require that
all HHAs with fewer than 60
HHCAHPS-eligible unduplicated or
unique patients in the period of April 1,
2016 through March 31, 2017, are
exempt from the HHCAHPS data
collection and submission requirements
for the CY 2019 APU, upon completion
of the CY 2019 HHCAHPS Participation
Exemption Request form, and upon
CMS verification of the HHA patient
counts. Agencies with fewer than 60
HHCAHPS-eligible, unduplicated or
unique patients in the period of April 1,
2016, through March 31, 2017, are
required to submit their patient counts
on the CY 2019 HHCAHPS Participation
Exemption Request form posted on
https://homehealthcahps.org from April
1, 2017, to 11:59 p.m., EST to March 31,
2018. This deadline is firm, as are all of
the quarterly data submission deadlines
for the HHAs that participate in
HHCAHPS.
We automatically exempt HHAs
receiving Medicare certification after the
period in which HHAs do their patient
count. HHAs receiving Medicarecertification on or after April 1, 2017,
are exempt from the HHCAHPS
reporting requirement for the CY 2019
APU. These newly-certified HHAs do
not need to complete the HHCAHPS
Participation Exemption Request Form
for the CY 2019 APU.
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6. HHCAHPS Requirements for the CY
2020 APU
For the CY 2020 APU, we require
continued monthly HHCAHPS data
collection and reporting for four
quarters. The data collection period for
the CY 2020, APU includes the second
quarter 2018 through the first quarter
2019 (the months of April 2018 through
March 2019). HHAs will be required to
submit their HHCAHPS data files to the
HHCAHPS Data Center for the second
quarter 2018 by 11:59 p.m., EST on
October 18, 2018; for the third quarter
2018 by 11:59 p.m., EST on January 17,
2019; for the fourth quarter 2018 by
11:59 p.m., EST on April 18, 2019; and
for the first quarter 2019 by 11:59 p.m.,
EST on July 19, 2019. These deadlines
are firm; no exceptions will be
permitted.
For the CY 2020 APU, we require that
all HHAs with fewer than 60
HHCAHPS-eligible unduplicated or
unique patients in the period of April 1,
2017, through March 31, 2018, are
exempt from the HHCAHPS data
collection and submission requirements
for the CY 2020 APU, upon completion
of the CY 2020 HHCAHPS Participation
Exemption Request form, and upon
CMS verification of the HHA patient
counts. Agencies with fewer than 60
HHCAHPS-eligible, unduplicated or
unique patients in the period of April 1,
2017, through March 31, 2018, are
required to submit their patient counts
on the CY 2020 HHCAHPS Participation
Exemption Request form posted on
https://homehealthcahps.org from April
1, 2018, to 11:59 p.m., EST to March 31,
2019. This deadline is firm, as are all of
the quarterly data submission deadlines
for the HHAs that participate in
HHCAHPS.
We automatically exempt HHAs
receiving Medicare certification after the
period in which HHAs do their patient
count. HHAs receiving Medicarecertification on or after April 1, 2018 are
exempt from the HHCAHPS reporting
requirement for the CY 2020 APU.
These newly-certified HHAs do not
need to complete the HHCAHPS
Participation Exemption Request Form
for the CY 2020 APU.
7. HHCAHPS Reconsiderations and
Appeals Process
HHAs should monitor their respective
HHCAHPS survey vendors to ensure
that vendors submit their HHCAHPS
data on time, by accessing their
HHCAHPS Data Submission Reports on
https://homehealthcahps.org. This
helps HHAs ensure that their data are
submitted in the proper format for data
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processing to the HHCAHPS Data
Center.
We continue the OASIS and
HHCAHPS reconsiderations and appeals
process that we have finalized and that
we have used for prior all periods cited
in the previous rules, and utilized in the
CY 2012 to CY 2016 APU
determinations. We have described the
HHCAHPS reconsiderations and appeals
process requirements in the APU
Notification Letter that we send to the
affected HHAs annually in September.
HHAs have 30 days from their receipt of
the letter informing them that they did
not meet the HHCAHPS requirements to
reply to us with documentation that
supports their requests for
reconsideration of the annual payment
update to us. It is important that the
affected HHAs send in comprehensive
information in their reconsideration
letter/package because we will not
contact the affected HHAs to request
additional information or to clarify
incomplete or inconclusive information.
If clear evidence to support a finding of
compliance is not present, then the 2
percent reduction in the annual
payment update will be upheld. If clear
evidence of compliance is present, then
the 2 percent reduction for the APU will
be reversed. We notify affected HHAs by
December 31 of the decisions that
affects payments in the annual year
beginning on January 1. If we determine
to uphold the 2 percent reduction for
the annual payment update, the affected
HHA may further appeal the 2 percent
reduction via the Provider
Reimbursement Review Board (PRRB)
appeals process, which is described in
the December letter.
8. Summary
We did not propose any changes to
the participation requirements, or to the
requirements pertaining to the
implementation of the Home Health
CAHPS® Survey (HHCAHPS). We only
updated the information to reflect the
dates for future APU years. We again
strongly encourage HHAs to keep up-todate about the HHCAHPS by regularly
viewing the official Web site for the
HHCAHPS at https://
homehealthcahps.org. HHAs can also
send an email to the HHCAHPS Survey
Coordination Team at hhcahps@rti.org
or to CMS at homehealthcahps@
cms.hhs.gov, or telephone toll-free (1–
866–354–0985) for more information
about the HHCAHPS Survey.
VI. Collection of Information
Requirements
While this proposed rule contains
information collection requirements,
this rule does not add new, nor revise
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any of the existing information
collection requirements, or burden
estimate. The information collection
requirements discussed in this rule for
the OASIS–C1 data item set had been
previously approved by the Office of
Management and Budget (OMB) on
February 6, 2014 and scheduled for
implementation on October 1, 2014. The
extension of OASIS–C1/ICD–9 version
was reapproved under OMB control
number 0938–0760 with a current
expiration date of March 31, 2018. This
version of the OASIS will be
discontinued once the OASIS–C1/ICD–
10 version is approved and
implemented. In addition, to facilitate
the reporting of OASIS data as it relates
to the implementation of ICD–10 on
October 1, 2015, CMS submitted a new
request for approval to OMB for the
OASIS–C1/ICD–10 version under the
Paperwork Reduction Act (PRA)
process. CMS is requesting a new OMB
control number for the proposed revised
OASIS item as announced in the 30-day
Federal Register notice (80 FR 15797).
The new information collection request
is currently pending OMB approval.
VII. Response to Comments
Because of the large number of public
comments we normally receive on
Federal Register documents, we are not
able to acknowledge or respond to them
individually. We will consider all
comments we receive by the date and
time specified in the DATES section of
this preamble, and, when we proceed
with a subsequent document, we will
respond to the comments in the
preamble to that document.
VIII. Regulatory Impact Analysis
A. Statement of Need
Section 1895(b)(1) of the Act requires
the Secretary to establish a HH PPS for
all costs of HH services paid under
Medicare. In addition, section
1895(b)(3)(A) of the Act requires (1) the
computation of a standard prospective
payment amount include all costs for
HH services covered and paid for on a
reasonable cost basis and that such
amounts be initially based on the most
recent audited cost report data available
to the Secretary, and (2) the
standardized prospective payment
amount be adjusted to account for the
effects of case-mix and wage levels
among HHAs. Section 1895(b)(3)(B) of
the Act addresses the annual update to
the standard prospective payment
amounts by the HH applicable
percentage increase. Section 1895(b)(4)
of the Act governs the payment
computation. Sections 1895(b)(4)(A)(i)
and (b)(4)(A)(ii) of the Act require the
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standard prospective payment amount
to be adjusted for case-mix and
geographic differences in wage levels.
Section 1895(b)(4)(B) of the Act requires
the establishment of appropriate casemix adjustment factors for significant
variation in costs among different units
of services. Lastly, section 1895(b)(4)(C)
of the Act requires the establishment of
wage adjustment factors that reflect the
relative level of wages, and wage-related
costs applicable to HH services
furnished in a geographic area
compared to the applicable national
average level.
Section 1895(b)(3)(B)(iv) of the Act
provides the Secretary with the
authority to implement adjustments to
the standard prospective payment
amount (or amounts) for subsequent
years to eliminate the effect of changes
in aggregate payments during a previous
year or years that was the result of
changes in the coding or classification
of different units of services that do not
reflect real changes in case-mix. Section
1895(b)(5) of the Act provides the
Secretary with the option to make
changes to the payment amount
otherwise paid in the case of outliers
because of unusual variations in the
type or amount of medically necessary
care. Section 1895(b)(3)(B)(v) of the Act
requires HHAs to submit data for
purposes of measuring health care
quality, and links the quality data
submission to the annual applicable
percentage increase.
Section 421(a) of the MMA requires
that HH services furnished in a rural
area, for episodes and visits ending on
or after April 1, 2010, and before
January 1, 2016, receive an increase of
3 percent of the payment amount
otherwise made under section 1895 of
the Act. Section 210 of the MACRA
amended section 421(a) of the MMA to
extend the 3 percent increase to the
payment amounts for serviced furnished
in rural areas for episodes and visits
ending before January 1, 2018.
Section 3131(a) of the Affordable Care
Act mandates that starting in CY 2014,
the Secretary must apply an adjustment
to the national, standardized 60-day
episode payment rate and other
amounts applicable under section
1895(b)(3)(A)(i)(III) of the Act to reflect
factors such as changes in the number
of visits in an episode, the mix of
services in an episode, the level of
intensity of services in an episode, the
average cost of providing care per
episode, and other relevant factors. In
addition, section 3131(a) of the
Affordable Care Act mandates that
rebasing must be phased-in over a 4year period in equal increments, not to
exceed 3.5 percent of the amount (or
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amounts) as of the date of enactment
(2010) under section 1895(b)(3)(A)(i)(III)
of the Act, and be fully implemented in
CY 2017.
The HHVBP Model will apply a
payment adjustment based on an HHA’s
performance on quality measures to test
the effects on quality and costs of care.
The HHVBP Model was implemented in
January 2016 as described in the CY
2016 HH PPS final rule.
B. Overall Impact
We have examined the impacts of this
rule as required by Executive Order
12866 on Regulatory Planning and
Review (September 30, 1993), Executive
Order 13563 on Improving Regulation
and Regulatory Review (January 18,
2011), the Regulatory Flexibility Act
(RFA) (September 19, 1980, Pub. L. 96–
354), section 1102(b) of the Act, section
202 of the Unfunded Mandates Reform
Act of 1995 (UMRA, March 22, 1995;
Pub. L. 104–4), Executive Order 13132
on Federalism (August 4, 1999), and the
Congressional Review Act (5 U.S.C.
804(2)).
Executive Orders 12866 and 13563
direct agencies to assess all costs and
benefits of available regulatory
alternatives and, if regulation is
necessary, to select regulatory
approaches that maximize net benefits
(including potential economic,
environmental, public health and safety
effects, distributive impacts, and
equity).
Section 3(f) of Executive Order 12866
defines a ‘‘significant regulatory action’’
as an action that is likely to result in a
rule: (1) Having an annual effect on the
economy of $100 million or more in any
1 year, or adversely and materially
affecting a sector of the economy,
productivity, competition, jobs, the
environment, public health or safety, or
state, local or tribal governments or
communities (also referred to as
‘‘economically significant’’); (2) creating
a serious inconsistency or otherwise
interfering with an action taken or
planned by another agency; (3)
materially altering the budgetary
impacts of entitlement grants, user fees,
or loan programs or the rights and
obligations of recipients thereof; or (4)
raising novel legal or policy issues
arising out of legal mandates, the
President’s priorities, or the principles
set forth in the Executive Order.
A regulatory impact analysis (RIA)
must be prepared for major rules with
economically significant effects ($100
million or more in any 1 year).The net
transfer impacts related to the changes
in payments under the HH PPS for CY
2017 are estimated to be ¥$180 million.
The savings impacts related to the
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HHVBP model are estimated at a total
projected 5-year gross savings of $378
million assuming a very conservative
savings estimate of a 6 percent annual
reduction in hospitalizations and a 1.0
percent annual reduction in SNF
admissions. Therefore, we estimate that
this rulemaking is ‘‘economically
significant’’ as measured by the $100
million threshold, and hence also a
major rule under the Congressional
Review Act. Accordingly, we have
prepared a Regulatory Impact Analysis
that to the best of our ability presents
the costs and benefits of the rulemaking.
In accordance with the provisions of
Executive Order 12866, this regulation
was reviewed by the Office of
Management and Budget.
In addition, section 1102(b) of the Act
requires us to prepare a RIA if a rule
may have a significant impact on the
operations of a substantial number of
small rural hospitals. This analysis must
conform to the provisions of section 603
of 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. This
proposed rule is applicable exclusively
to HHAs. Therefore, the Secretary has
determined this rule would not have a
significant economic impact on the
operations of small rural hospitals.
Executive Order 13563 emphasizes the
importance of quantifying both costs
and benefits, of reducing costs, of
harmonizing rules, and of promoting
flexibility. The net transfer impacts
related to the changes in payments
under the HH PPS for CY 2017 are
estimated to be ¥$180 million. The
savings impacts related to the HHVBP
Model are estimated at a total projected
6-year gross savings of $378 million
assuming a very conservative savings
estimate of a 6 percent annual reduction
in hospitalizations and a 1.0 percent
annual reduction in SNF admissions.
Section 202 of the Unfunded
Mandates Reform Act of 1995 (UMRA)
also requires that agencies assess
anticipated costs and benefits before
issuing any rule whose mandates
require spending in any 1 year of $100
million in 1995 dollars, updated
annually for inflation. In 2016, that
threshold is approximately $146
million. This proposed rule is not
anticipated to have an effect on State,
local, or tribal governments, in the
aggregate, or on the private sector of
$146 million or more.
1. HH PPS
The update set forth in this rule
applies to Medicare payments under HH
PPS in CY 2017. Accordingly, the
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43781
following analysis describes the impact
in CY 2017 only. We estimate that the
net impact of the policies in this rule is
approximately $180 million in
decreased payments to HHAs in CY
2017. We applied a wage index budget
neutrality factor and a case-mix weights
budget neutrality factor to the rates as
discussed in section III.C.3 of this
proposed rule. Therefore, the estimated
impact of the 2017 wage index and the
recalibration of the case-mix weights for
2017 is zero. The ¥$180 million impact
reflects the distributional effects of the
2.3 percent HH payment update
percentage ($420 million increase), the
effects of the fourth year of the four-year
phase-in of the rebasing adjustments to
the national, standardized 60-day
episode payment amount, the national
per-visit payment rates, and the NRS
conversion factor for an impact of ¥2.3
percent ($420 million decrease), the
effects of the ¥0.97 percent adjustment
to the national, standardized 60-day
episode payment rate to account for
nominal case-mix growth for an impact
of ¥0.9 percent ($160 million decrease),
and the effects of the proposed change
to the FDL ratio of 0.45 to 0.56 for an
impact of ¥0.1 percent ($20 million
decrease). The $180 million in
decreased payments is reflected in the
last column of the first row in Table 36
as a 1.0 percent decrease in
expenditures when comparing CY 2016
payments to estimated CY 2017
payments.
The RFA requires agencies to analyze
options for regulatory relief of small
entities, if a rule has a significant impact
on a substantial number of small
entities. For purposes of the RFA, small
entities include small businesses,
nonprofit organizations, and small
governmental jurisdictions. Most
hospitals and most other providers and
suppliers are small entities, either by
nonprofit status or by having revenues
of less than $7.5 million to $38.5
million in any one year. For the
purposes of the RFA, we estimate that
almost all HHAs are small entities as
that term is used in the RFA.
Individuals and states are not included
in the definition of a small entity. The
economic impact assessment is based on
estimated Medicare payments
(revenues) and HHS’s practice in
interpreting the RFA is to consider
effects economically ‘‘significant’’ only
if greater than 5 percent of providers
reach a threshold of 3 to 5 percent or
more of total revenue or total costs. The
majority of HHAs’ visits are Medicarepaid visits and therefore the majority of
HHAs’ revenue consists of Medicare
payments. Based on our analysis, we
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conclude that the policies proposed in
this rule would result in an estimated
total impact of 3 to 5 percent or more
on Medicare revenue for greater than 5
percent of HHAs. Therefore, the
Secretary has determined that this HH
PPS proposed rule would have a
significant economic impact on a
substantial number of small entities.
Further detail is presented in Table 39,
by HHA type and location.
With regards to options for regulatory
relief, we note that in the CY 2014 HH
PPS final rule we finalized rebasing
adjustments to the national,
standardized 60-day episode rate, nonroutine supplies (NRS) conversion
factor, and the national per-visit
payment rates for each year, 2014
through 2017 as described in section
II.C and III.C.3 of this proposed rule.
Since the rebasing adjustments are
mandated by section 3131(a) of the
Affordable Care Act, we cannot offer
HHAs relief from the rebasing
adjustments for CY 2017. For the 0.97
percent reduction to the national,
standardized 60-day episode payment
amount for CY 2017 described in
section III.C.3 of this proposed rule, we
believe it is appropriate to reduce the
national, standardized 60-day episode
payment amount to account for the
estimated increase in nominal case-mix
in order to move towards more accurate
payment for the delivery of home health
services where payments better align
with the costs of providing such
services. In the alternatives considered
section for the CY 2016 HH PPS
proposed rule (80 FR 39839), we note
that we considered reducing the 60-day
episode rate in CY 2016 only to account
for nominal case-mix growth between
CY 2012 and CY 2014. However, we
instead finalized a reduction to the 60day episode rate over a three-year
period (CY 2016, CY 2017, and CY
2018) to account for estimated nominal
case-mix growth between CY 2012 and
CY 2014 in order to lessen the impact
on HHAs in a given year (80 FR 68646).
Executive Order 13563 specifies, to
the extent practicable, agencies should
assess the costs of cumulative
regulations. However, given potential
utilization pattern changes, wage index
changes, changes to the market basket
forecasts, and unknowns regarding
future policy changes, we believe it is
neither practicable nor appropriate to
forecast the cumulative impact of the
rebasing adjustments on Medicare
payments to HHAs for future years at
this time. Changes to the Medicare
program may continue to be made as a
result of the Affordable Care Act, or new
statutory provisions. Although these
changes may not be specific to the HH
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PPS, the nature of the Medicare program
is such that the changes may interact,
and the complexity of the interaction of
these changes would make it difficult to
predict accurately the full scope of the
impact upon HHAs for future years
beyond CY 2017. We note that the
rebasing adjustments to the national,
standardized 60-day episode payment
rate and the national per-visit rates are
capped at the statutory limit of 3.5
percent of the CY 2010 amounts (as
described in the preamble in section
II.C. of this proposed rule) for each year,
2014 through 2017. The NRS rebasing
adjustment will be ¥2.82 percent in
each year, 2014 through 2017.
2. HHVBP Model
Under the HHVBP Model, the first
payment adjustment will apply in CY
2018 based on PY1 (CY 2016) data and
the final payment adjustment will apply
in CY 2022 based on PY5 (CY 2020)
data. In the CY 2016 HH PPS final rule,
the overall impact of HHVBP Model
from CY 2018–CY 2022 was
approximately a reduction of $380
million. That estimate was based on the
five performance years of the Model and
only two payment adjustment years. We
now estimate that this will be
approximately a decrease of $378
million. This estimate represents the
five performance years (CY 2016–CY
2020) and applying the payment
adjustments from CY 2018 through CY
2021. We assume that the behavior
changes and savings will continue into
2021 because HHAs will continue to
receive quality reports until July 2021.
Although behavior changes and savings
could persist into CY 2022, HHAs
would not be receiving quality reports
so we did not include it in our savings
assumptions.
C. Detailed Economic Analysis
1. HH PPS
This rule proposes updates for CY
2017 to the HH PPS rates contained in
the CY 2016 HH PPS final rule (80 FR
68624 through 68719). The impact
analysis of this proposed rule presents
the estimated expenditure effects of
policy changes proposed in this rule.
We use the latest data and best analysis
available, but we do not make
adjustments for future changes in such
variables as number of visits or casemix.
This analysis incorporates the latest
estimates of growth in service use and
payments under the Medicare HH
benefit, based primarily on Medicare
claims data from 2015. We note that
certain events may combine to limit the
scope or accuracy of our impact
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analysis, because such an analysis is
future-oriented and, thus, susceptible to
errors resulting from other changes in
the impact time period assessed. Some
examples of such possible events are
newly-legislated general Medicare
program funding changes made by the
Congress, or changes specifically related
to HHAs. In addition, changes to the
Medicare program may continue to be
made as a result of the Affordable Care
Act, or new statutory provisions.
Although these changes may not be
specific to the HH 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 HHAs.
Table 36 represents how HHA
revenues are likely to be affected by the
policy changes proposed in this rule.
For this analysis, we used an analytic
file with linked CY 2015 OASIS
assessments and HH claims data for
dates of service that ended on or before
December 31, 2015 (as of March 31,
2016). The first column of Table 36
classifies HHAs according to a number
of characteristics including provider
type, geographic region, and urban and
rural locations. The second column
shows the number of facilities in the
impact analysis. The third column
shows the payment effects of the CY
2017 wage index. The fourth column
shows the payment effects of the CY
2016 case-mix weights. The fifth
column shows the effects the 0.97
percent reduction to the national,
standardized 60-day episode payment
amount to account for nominal case-mix
growth. The sixth column shows the
effects of the rebasing adjustments to the
national, standardized 60-day episode
payment rate, the national per-visit
payment rates, and NRS conversion
factor. For CY 2017, the average impact
for all HHAs due to the effects of
rebasing is an estimated 2.3 percent
decrease in payments. The seventh
column shows the effects of revising the
FDL ratio used to compute outlier
payments from 0.45 to 0.56. The eighth
column shows the effects of the change
to the outlier methodology. The ninth
column shows the effects of the CY 2017
home health payment update
percentage.
The last column shows the combined
effects of all the policies proposed in
this rule. Overall, it is projected that
aggregate payments in CY 2017 would
decrease by 1.0 percent. As illustrated
in Table 36, the combined effects of all
of the changes vary by specific types of
providers and by location. We note that
some individual HHAs within the same
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group may experience different impacts
on payments than others due to the
distributional impact of the CY 2017
wage index, the extent to which HHAs
had episodes in case-mix groups where
the case-mix weight decreased for CY
2017 relative to CY 2016, the percentage
of total HH PPS payments that were
subject to the low-utilization payment
adjustment (LUPA) or paid as outlier
payments, and the degree of Medicare
utilization.
TABLE 36— ESTIMATED HOME HEALTH AGENCY IMPACTS BY FACILITY TYPE AND AREA OF THE COUNTRY, CY 2017
Number of
Agencies
All Agencies ................................................
11,167
CY 2017
wage
index 1
%
60-day
episode
rate nominal casemix reduction 3
%
CY 2017
case-mix
weights 2
%
0.0
0.0
Rebasing 4
%
¥0.9
Revised
outlier FDL
%
Revised
outlier
methodology
%
HH
payment
update
percentage 5
%
Total
%
¥2.3
¥0.1
0.0
2.3
¥1.0
¥2.2
¥2.3
¥2.2
¥2.2
¥2.2
¥2.3
¥2.3
¥2.2
¥2.2
¥2.3
¥2.3
¥0.1
¥0.1
¥0.1
¥0.1
¥0.1
¥0.1
¥0.1
¥0.1
¥0.1
¥0.1
¥0.1
0.9
¥0.3
0.3
0.8
0.4
0.8
¥0.1
0.8
0.9
¥0.3
0.5
2.3
2.3
2.3
2.3
2.3
2.3
2.3
2.3
2.3
2.3
2.3
¥0.3
¥1.2
¥0.4
¥0.3
¥0.5
¥0.5
¥1.1
¥0.2
¥0.3
¥1.2
¥0.5
¥2.2
¥2.3
¥2.4
¥2.2
¥2.3
¥2.2
¥0.1
¥0.1
¥0.1
¥0.1
¥0.1
¥0.1
0.8
0.2
¥0.2
0.5
0.5
0.4
2.3
2.3
2.3
2.3
2.3
2.3
0.1
¥0.9
¥1.1
0.0
¥0.5
¥0.2
¥2.2
¥2.3
¥2.3
¥2.2
¥2.2
¥2.3
¥0.1
¥0.1
¥0.1
¥0.1
¥0.1
¥0.1
0.9
¥0.4
0.2
0.9
0.3
1.1
2.3
2.3
2.3
2.3
2.3
2.3
¥0.5
¥1.3
¥0.8
¥0.3
¥0.6
¥0.6
¥2.3
¥2.3
¥0.1
¥0.1
0.0
0.0
2.3
2.3
¥0.8
¥1.0
¥2.1
¥2.4
¥2.3
¥2.3
¥2.2
¥2.2
¥0.1
¥0.1
¥0.1
¥0.1
¥0.1
¥0.1
0.8
0.4
¥0.6
0.3
0.9
0.5
2.3
2.3
2.3
2.3
2.3
2.3
¥0.4
¥0.7
¥1.7
¥0.1
¥0.2
¥0.7
¥2.1
¥2.1
¥2.4
¥2.3
¥2.3
¥2.4
¥2.3
¥2.3
¥2.3
¥0.1
¥0.1
¥0.1
¥0.1
¥0.1
¥0.1
¥0.1
¥0.1
¥0.1
0.3
1.1
0.4
0.6
¥0.6
0.0
¥0.8
¥0.2
0.6
2.3
2.3
2.3
2.3
2.3
2.3
2.3
2.3
2.3
¥1.1
¥0.1
¥0.6
¥0.5
¥2.0
¥1.1
¥1.5
¥0.9
0.3
¥2.3
¥2.4
¥2.3
¥2.3
¥2.3
¥0.1
¥0.1
¥0.1
¥0.1
¥0.1
0.4
0.1
0.0
¥0.1
0.0
2.3
2.3
2.3
2.3
2.3
¥0.3
¥0.7
¥0.9
¥1.1
¥1.1
Facility Type and Control
Free-Standing/Other Vol/NP .......................
Free-Standing/Other Proprietary .................
Free-Standing/Other Government ...............
Facility-Based Vol/NP .................................
Facility-Based Proprietary ...........................
Facility-Based Government .........................
Subtotal: Freestanding .........................
Subtotal: Facility-based ........................
Subtotal: Vol/NP ...................................
Subtotal: Proprietary ............................
Subtotal: Government ..........................
1,087
8,715
362
690
109
204
10,164
1,003
1,777
8,824
566
¥0.2
0.1
0.1
¥0.1
0.0
¥0.3
0.0
¥0.1
¥0.2
0.1
¥0.1
¥0.1
0.0
0.1
¥0.1
0.0
0.0
0.0
0.0
¥0.1
0.0
0.1
¥0.9
¥0.9
¥0.9
¥0.9
¥0.9
¥0.9
¥0.9
¥0.9
¥0.9
¥0.9
¥0.9
Facility Type and Control: Rural
Free-Standing/Other Vol/NP .......................
Free-Standing/Other Proprietary .................
Free-Standing/Other Government ...............
Facility-Based Vol/NP .................................
Facility-Based Proprietary ...........................
Facility-Based Government .........................
279
873
261
333
54
152
0.1
0.0
0.2
0.3
¥0.1
0.1
Free-Standing/Other Vol/NP .......................
Free-Standing/Other Proprietary .................
Free-Standing/Other Government ...............
Facility-Based Vol/NP .................................
Facility-Based Proprietary ...........................
Facility-Based Government .........................
807
7,837
101
357
55
52
¥0.3
0.1
0.0
¥0.2
0.1
¥0.6
0.1
¥0.1
0.0
0.1
0.1
0.2
¥0.9
¥0.9
¥0.9
¥0.9
¥0.9
¥0.9
Facility Type and Control: Urban
¥0.2
0.0
0.0
¥0.1
¥0.1
¥0.1
¥0.9
¥0.9
¥0.9
¥0.9
¥0.9
¥0.9
Facility Location: Urban or Rural
Rural ............................................................
Urban ...........................................................
1,952
9,209
Northeast .....................................................
Midwest .......................................................
South ...........................................................
West ............................................................
Other ...........................................................
Puerto Rico .................................................
848
2,992
5,310
1,968
49
41
0.2
0.0
0.0
0.0
¥0.9
¥0.9
Facility Location: Region of the Country
¥0.4
0.0
¥0.1
0.6
¥0.3
¥0.5
0.0
0.0
0.0
0.0
0.1
0.1
¥0.9
¥0.9
¥0.9
¥0.9
¥0.9
¥0.8
Facility Location: Region of the Country (Census Region)
New England ...............................................
Mid Atlantic ..................................................
East North Central ......................................
West North Central .....................................
South Atlantic ..............................................
East South Central ......................................
West South Central .....................................
Mountain ......................................................
Pacific ..........................................................
347
501
2,271
721
1,791
426
3,093
672
1,296
¥0.7
¥0.3
0.0
0.0
¥0.3
¥0.1
0.3
0.2
0.7
0.1
¥0.1
0.1
¥0.1
¥0.1
0.0
0.0
0.1
0.0
¥0.9
¥0.9
¥0.9
¥0.9
¥0.9
¥0.9
¥0.9
¥0.9
¥0.9
sradovich on DSK3GDR082PROD with PROPOSALS2
Facility Size (Number of 1st Episodes)
<100 episodes .............................................
100 to 249 ...................................................
250 to 499 ...................................................
500 to 999 ...................................................
1,000 or More ..............................................
3,177
2,733
2,342
1,597
1,318
0.0
0.1
0.1
0.0
0.0
0.3
0.2
0.0
0.0
¥0.1
¥0.9
¥0.9
¥0.9
¥0.9
¥0.9
Source: CY 2015 Medicare claims data for episodes ending on or before December 31, 2015 (as of December 31, 2015) for which we had a linked OASIS assessment.
1 The impact of the CY 2017 home health wage index is offset by the wage index budget neutrality factor described in section III.C.3 of this proposed rule.
2 The impact of the CY 2017 home health case-mix weights reflects the recalibration of the case-mix weights as outlined in section III.B of this proposed rule offset
by the case-mix weights budget neutrality factor described in section III.C.3 of this proposed rule.
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sradovich on DSK3GDR082PROD with PROPOSALS2
3 The 0.97 percent reduction to the national, standardized 60-day episode payment amount in CY 2017 is estimated to have a 0.9 percent impact on overall HH
PPS expenditures.
4 The impact of rebasing includes the rebasing adjustments to the national, standardized 60-day episode payment rate (¥2.74 percent after the CY 2017 payment
rate was adjusted for the wage index and case-mix weight budget neutrality factors and the nominal case-mix reduction), the national per-visit rates (+2.9 percent),
and the NRS conversion factor (¥2.82 percent). The estimated impact of the NRS conversion factor rebasing adjustment is an overall -0.01 percent decrease in estimated payments to HHAs
4 The CY 2017 home health payment update percentage reflects the home health market basket update of 2.8 percent, reduced by a 0.5 percentage point multifactor productivity (MFP) adjustment as required under section 1895(b)(3)(B)(vi)(I) of the Act, as described in section III.C.1 of this proposed rule.
Region Key:
New England = Connecticut, Maine, Massachusetts, New Hampshire, Rhode Island, Vermont;
Middle Atlantic = Pennsylvania, New Jersey, New York;
South Atlantic = Delaware, District of Columbia, Florida, Georgia, Maryland, North Carolina, South Carolina, Virginia, West Virginia;
East North Central = Illinois, Indiana, Michigan, Ohio, Wisconsin;
East South Central = Alabama, Kentucky, Mississippi, Tennessee;
West North Central = Iowa, Kansas, Minnesota, Missouri, Nebraska, North Dakota, South Dakota;
West South Central = Arkansas, Louisiana, Oklahoma, Texas;
Mountain = Arizona, Colorado, Idaho, Montana, Nevada, New Mexico, Utah, Wyoming;
Pacific = Alaska, California, Hawaii, Oregon, Washington;
Other = Guam, Puerto Rico, Virgin Islands
2. HHVBP Model
Table 37 displays our analysis of the
distribution of possible payment
adjustments at the 3-percent, 5-percent,
6-percent, 7-percent, and 8-percent rates
that are being used in the Model using
the 2013 and 2014 OASIS measures,
hospitalization measure and Emergency
Department (ED) measure from QIES,
and Home Health CAHPS data. The
impacts below also account for the
proposals to change the smaller-volume
cohort size determination, calculate
achievement threshold and benchmark
proposals at the state level, and revise
the applicable measures. We determined
the distribution of possible payment
adjustments based on ten (10) OASIS
quality measures, two (2) claims-based
measures in QIES, the three (3)New
Measures (with the assumption that all
HHAs reported on all New Measures
and received full points), and QIES Roll
Up File data in the same manner as they
would be in the Model. The five (5)
HHCAHPS measures are based on
archived data. The size of the cohorts
were determined using the 2014 Quality
Episode File based on OASIS
assessments (the Model will use the
year before each performance year),
whereby the HHAs reported at least five
measures with over 20 observations.
The basis of the payment adjustment
was derived from complete 2014 claims
data. We note that this impact analysis
is based on the aggregate value of all
nine (9) selected states.
Table 38 displays our analysis of the
distribution of possible payment
adjustments based on the same 2013–
2014 data used to calculate Table 37,
providing information on the estimated
impact of this proposed rule. We note
that this impact analysis is based on the
aggregate value of all nine (9) selected
states. All Medicare-certified HHAs that
provide services in Massachusetts,
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Maryland, North Carolina, Florida,
Washington, Arizona, Iowa, Nebraska,
and Tennessee are required to compete
in this Model. Value-based incentive
payment adjustments for the estimated
1,900 plus HHAs in the selected states
that compete in the HHVBP Model are
stratified by size as described in this
proposed rule. Under the proposal
described, there must be a minimum of
eight (8) HHAs in any cohort.
Those HHAs that are in states that do
not have at least eight small HHAs
would not have a smaller-volume cohort
and thus there would only be one cohort
that would include all the HHAS in that
state. As indicated in Table 38, under
this proposal, Massachusetts, Maryland,
North Carolina, Tennessee and
Washington would only have one cohort
and Florida, Arizona, Iowa, Nebraska
would have a smaller-volume cohort
and a larger-volume cohort. For
example, Iowa has 29 HHAs eligible to
be exempt from being required to have
their beneficiaries complete HHCAHPS
surveys because they provided HHA
services to less than 60 beneficiaries in
2013. Therefore, those 29 HHAs would
be competing in Iowa’s smaller-volume
cohort if the performance year was
2014.
Using 2013–2014 data and the
payment adjustment of 5-percent (as
applied in CY 2019), based on the ten
(10) OASIS quality measures, two (2)
claims-based measures in QIES, the five
(5) HHCAHPS measures (based on the
archived data), and the three (3) New
Measures (with the assumption that all
HHAs submitted data), Table 38
illustrates that smaller-volume HHAs in
Iowa would have a mean payment
adjustment of positive 0.62 percent and
the payment adjustment ranges from
¥2.3 percent at the 10th percentile to
+3.8 percent at the 90th percentile. As
a result of using the OASIS quality and
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claims-based measures, the same source
data (from QIES rather than archived
data) that the Model will use for
implementation, and adding the
assumption that all HHAs will submit
data for each of the New Measures when
calculating the payment adjustments,
the range of payment adjustments for all
cohorts in this proposed rule is lower
than that was included in HH PPS 2016
rule. This difference is largely due to the
lowered variation in TPS caused by the
assumption that all HHAs will submit
data for each of the New Measures.
Table 39 provides the payment
adjustment distribution based on
proportion of dually-eligible
beneficiaries, average case mix (using
HCC scores), proportion that reside in
rural areas, as well as HHA
organizational status. Besides the
observation that higher proportion of
dually-eligible beneficiaries serviced is
related to better performance, the
payment adjustment distribution is
consistent with respect to these four
categories.
The payment adjustment percentages
were calculated at the state and size
level so that each HHA’s payment
adjustment was calculated as it would
be in the Model. Hence, the values of
each separate analysis in the tables are
representative of what they would be if
the baseline year was 2013 and the
performance year was 2014. There were
1,839 HHAs in the nine selected states
out of 1,991 HHAs that were found in
the HHA data sources that yielded a
sufficient number of measures to receive
a payment adjustment in the Model. It
is expected that a certain number of
HHAs will not be subject to the payment
adjustment because they may be
servicing too small of a population to
report on an adequate number of
measures to calculate a TPS.
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TABLE 37—HHVBP MODEL: ADJUSTMENT DISTRIBUTION BY PERCENTILE LEVEL OF QUALITY TOTAL PERFORMANCE
SCORE AT DIFFERENT MODEL PAYMENT ADJUSTMENT RATES
[Percentage]
Payment adjustment distribution
3%
5%
6%
7%
8%
Payment
Payment
Payment
Payment
Payment
Adjustment
Adjustment
Adjustment
Adjustment
Adjustment
For
For
For
For
For
Performance
Performance
Performance
Performance
Performance
year
year
year
year
year
1
2
3
4
5
Range
of
of
of
of
of
the
the
the
the
the
Model
Model
Model
Model
Model
.....
.....
.....
.....
.....
3.08
5.12
6.15
7.18
8.25
10%
20%
30%
40%
Median
¥1.23
¥2.04
¥2.45
¥2.86
¥3.27
¥0.87
¥1.45
¥1.74
¥2.03
¥2.32
¥0.56
¥0.94
¥1.13
¥1.32
¥1.50
¥0.30
¥0.50
¥0.61
¥0.71
¥0.81
¥0.02
¥0.03
¥0.04
¥0.04
¥0.05
60%
70%
0.27
0.46
0.55
0.64
0.73
0.61
1.01
1.21
1.42
1.62
80%
1.11
1.85
2.22
2.59
2.96
90%
1.85
3.08
3.70
4.32
4.93
TABLE 38—HHVBP MODEL: HHA COHORT PAYMENT ADJUSTMENT DISTRIBUTIONS BY STATE/COHORT
[Based on a 5-percent payment adjustment]
# of
HHA
COHORT
Average
payment
adj.
(%)
10%
20%
30%
40%
Median
60%
70%
80%
90%
HHA Cohort in States with no small cohorts (percent)
MA .................................................................................
MD .................................................................................
NC .................................................................................
TN ..................................................................................
WA .................................................................................
127
53
172
135
59
0.00
0.56
0.16
0.36
0.71
¥2.20
¥1.50
¥1.90
¥2.00
¥1.70
¥1.50
¥1.10
¥1.50
¥1.30
¥0.70
¥1.10
¥0.80
¥1.00
¥0.80
¥0.30
¥0.70
¥0.10
¥0.50
¥0.40
0.20
¥0.30
0.20
0.10
¥0.10
0.50
0.00
0.50
0.50
0.30
0.80
0.80
1.40
0.90
0.90
1.70
1.40
2.00
1.70
2.00
2.30
2.70
3.60
2.40
3.10
2.90
¥0.30
¥0.20
0.30
¥0.40
¥0.10
0.10
0.90
1.30
0.60
0.40
1.70
2.20
0.90
1.20
2.30
2.40
5.00
1.80
3.80
4.00
¥0.30
0.00
¥0.20
¥0.10
0.10
0.60
0.10
0.30
0.50
1.30
0.50
0.70
1.30
2.20
1.00
1.80
2.30
3.30
1.80
3.70
Smaller-volume HHA Cohort in states with small cohort (percent)
AZ small ........................................................................
FL small .........................................................................
IA small .........................................................................
NE small ........................................................................
9
130
29
16
0.53
¥0.14
0.62
0.48
¥1.20
¥2.20
¥2.30
¥1.70
¥0.70
¥1.70
¥1.10
¥1.60
¥0.70
¥1.20
¥0.80
¥1.20
¥0.50
¥0.60
0.00
¥0.60
Larger-volume HHA Cohort in states with small cohorts (percent)
AZ large .........................................................................
FL large .........................................................................
IA large ..........................................................................
NE large ........................................................................
112
889
107
49
¥0.06
0.37
¥0.21
0.31
¥2.20
¥2.10
¥2.30
¥1.80
¥1.50
¥1.50
¥1.60
¥1.20
¥1.10
¥0.90
¥1.30
¥0.90
¥0.70
¥0.40
¥0.70
¥0.60
TABLE 39—PAYMENT ADJUSTMENT DISTRIBUTIONS BY CHARACTERISTICS
[Based on a 5-percent payment adjustment]
# of
HHA
COHORT
Low % Dually-eligible ....................................................
Medium % Dually-eligible ..............................................
High % Dually-eligible ...................................................
Low acuity .....................................................................
Mid acuity ......................................................................
High acuity ....................................................................
All non-rural ...................................................................
Up to 35% rural .............................................................
Over 35% rural ..............................................................
Church ...........................................................................
Private NP .....................................................................
Other .............................................................................
Private FP .....................................................................
Federal ..........................................................................
State ..............................................................................
Local ..............................................................................
sradovich on DSK3GDR082PROD with PROPOSALS2
D. Alternatives Considered
As described in the CY 2016 HH PPS
proposed rule (80 FR 39911), we
considered proposing to reduce the
national, standardized 60-day episode
payment rate by 3.41 percent in CY
2016 to account for nominal case-mix
growth between CY 2012 and CY 2014.
If we were to reduce the national,
standardized 60-day episode payment
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621
841
416
459
1089
338
989
141
172
62
168
84
1315
72
5
57
Average
payment
adj.
(%)
0.18
¥0.15
1.21
0.97
0.83
¥0.16
0.57
0.01
0.54
0.80
0.22
0.40
0.20
0.37
¥0.39
0.50
10%
20%
30%
40%
Median
60%
¥1.80
¥2.20
¥1.80
¥1.70
¥2.10
¥2.10
¥2.10
¥2.10
¥1.80
¥1.70
¥1.90
¥1.60
¥2.10
¥2.20
¥2.50
¥1.50
¥1.30
¥1.70
¥0.80
¥1.00
¥1.50
¥1.60
¥1.50
¥1.50
¥1.30
¥0.90
¥1.30
¥1.10
¥1.50
¥1.60
¥1.90
¥1.10
¥0.90
¥1.20
¥0.20
¥0.40
¥1.00
¥1.30
¥0.90
¥1.10
¥0.90
¥0.80
¥0.90
¥0.70
¥1.00
¥1.10
¥1.40
¥0.70
¥0.50
¥0.80
0.50
0.10
¥0.60
¥0.90
¥0.40
¥0.60
¥0.50
0.10
¥0.30
¥0.40
¥0.60
¥0.40
¥0.50
0.00
0.00
¥0.40
1.10
0.70
¥0.10
¥0.50
0.10
¥0.20
0.00
0.40
0.10
0.20
¥0.10
0.20
0.30
0.30
0.40
0.00
1.80
1.30
0.30
¥0.10
1.00
0.20
0.50
1.10
0.50
0.60
0.30
0.60
0.50
0.60
rate by 3.41 percent, we estimated that
the aggregate impact would have been a
decrease of $600 million in payments to
HHAs. However, instead of
implementing a one-time reduction in
the national, standardized 60-day
episode payment rate of 3.41 percent in
CY 2016 to account for nominal casemix growth from CY 2012 through CY
2014, we finalized a reduction to the
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70%
0.90
0.50
2.60
2.10
0.80
0.50
1.80
0.70
1.10
1.70
0.90
1.00
1.00
1.40
0.60
0.90
80%
1.50
1.20
3.30
2.90
1.50
1.30
2.70
1.40
1.70
2.60
1.70
1.80
1.90
2.10
0.80
1.40
90%
2.50
2.20
4.20
4.00
2.60
2.40
3.80
2.30
2.90
3.70
2.50
2.60
3.10
2.80
1.00
2.40
national, standardized 60-day episode
payment rate of 0.97 percent in CY
2016, CY 2017, and CY 2018 to account
for nominal case-mix growth from CY
2012 through CY 2014 (80 FR 68646).
Since the 0.97 percent reduction to the
national, standardized 60-day episode
payment rate to account for nominal
case-mix growth from 2012 to 2014 was
finalized in the CY 2016 HH PPS final
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rule, we did not consider alternatives to
implementing this reduction for CY
2017.
Section 3131(a) of the Affordable Care
Act mandates that starting in CY 2014,
the Secretary must apply an adjustment
to the national, standardized 60-day
episode payment rate and other
amounts applicable under section
1895(b)(3)(A)(i)(III) of the Act to reflect
factors such as changes in the number
of visits in an episode, the mix of
services in an episode, the level of
intensity of services in an episode, the
average cost of providing care per
episode, and other relevant factors. In
addition, section 3131(a) of the
Affordable Care Act mandates that
rebasing must be phased-in over a 4year period in equal increments, not to
exceed 3.5 percent of the amount (or
amounts) as of the date of enactment
(2010) under section 1895(b)(3)(A)(i)(III)
of the Act, and be fully implemented in
CY 2017. Therefore, in the CY 2014 HH
PPS final rule (78 FR 77256), we
finalized rebasing adjustments to the
national, standardized 60-day episode
payment amount, the national per-visit
rates and the NRS conversion factor. As
we noted in the CY 2014 HH PPS final
rule, because section 3131(a) of the
Affordable Care Act requires a four year
phase-in of rebasing, in equal
increments, to start in CY 2014 and be
fully implemented in CY 2017, we do
not have the discretion to delay, change,
or eliminate the rebasing adjustments
once we have determined that rebasing
is necessary (78 FR 72283).
Section 1895(b)(3)(B) of the Act
requires that the standard prospective
payment amounts for CY 2016 be
increased by a factor equal to the
applicable HH market basket update for
those HHAs that submit quality data as
required by the Secretary. For CY 2016,
section 3401(e) of the Affordable Care
Act, requires that, in CY 2015 (and in
subsequent calendar years), the market
basket update under the HHA
prospective payment system, as
described in section 1895(b)(3)(B) of the
Act, be annually adjusted by changes in
economy-wide productivity. Beginning
in CY 2015, section 1895(b)(3)(B)(vi)(I)
of the Act, as amended by section
3401(e) of the Affordable Care Act,
requires the application of the
productivity adjustment described in
section 1886(b)(3)(B)(xi)(II) of the Act to
the HHA PPS for CY 2015 and each
subsequent CY. The ¥0.5 percentage
point productivity adjustment to the
proposed CY 2017 home health market
basket update (2.8 percent), is discussed
in the preamble of this rule and is not
discretionary as it is a requirement in
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section 1895(b)(3)(B)(vi)(I) of the Act (as
amended by the Affordable Care Act).
With regards to payments made under
the HH PPS for high-cost ‘‘outlier’’
episodes of care (that is, episodes of care
with unusual variations in the type or
amount of medically necessary care), we
did not consider maintaining the fixeddollar loss (FDL) ratio at 0.45 in section
III.D.3 of this proposed rule because
simulations using CY 2015 utilization
data (that is, home health claims data)
the proposed CY 2017 HH PPS payment
rates resulted in an estimated 2.58
percent of total HH PPS payments being
paid as outlier payments using the
existing methodology (cost-per-visit) for
calculating the cost of an episode of
care. Likewise, simulations using CY
2015 utilization data (that is, home
health claims data) the proposed CY
2017 HH PPS payment rates resulted in
an estimated 3.10 percent of total HH
PPS payments being paid as outlier
payments using the proposed
methodology (cost-per-unit) for
calculating the cost of an episode of
care. The FDL ratio and the loss-sharing
ratio must be selected so that the
estimated outlier payments do not
exceed the 2.5 percent of total HH PPS
payments (as required by section
1895(b)(5)(A) of the Act). We did not
consider proposing a change to the losssharing ratio (0.80) in order for the HH
PPS to remain consistent with payment
for high-cost outliers in other Medicare
payment systems (for example, IRF PPS,
IPPS, etc.)
With regards to the methodology used
to calculate the cost of an episode of
care in order to determine the payment
amount under the HH PPS for high-cost
‘‘outliers’’ (that is, episodes of care with
unusual variations in the type or
amount of medically necessary care), in
section III.D.2, we considered
maintaining the current methodology
used to calculate the cost of an episode
of care (cost-per-visit). However, due to
the findings from the home health study
required as a result of section 3131(d) of
the Affordable Care Act (as discussed in
section III.D.2 of this proposed rule and
in the CY 2016 HH PPS proposed rule
(80 FR 39864), we believe that the
proposed methodology change (cost-perunit) helps to alleviate financial
disincentives for providers to treat
medically complex beneficiaries who
require longer visits. Since the
projection of the percentage of outlier
dollars is the same as before the change,
the impact of this proposal is budget
neutral.
As described in Section III.E of this
proposed rule, the Consolidated
Appropriations Act of 2016 (Pub. L 114–
113) amends both Section 1834 of the
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Act (42 U.S.C. 1395m) and Section
1861(m)(5) of the Act (42 U.S.C.
1395x(m)(5)), requiring a separate
payment to a HHA for an applicable
disposable device when furnished on or
after January 1, 2017, to an individual
who receives home health services for
which payment is made under the
Medicare home health benefit.
Therefore, we do not have the discretion
to delay or eliminate the
implementation of a separate payment
amount for NPWT performed using a
disposable device and thus we did not
consider any alternatives regarding this
proposal.
We invite comments on the
alternatives discussed in this analysis.
E. Accounting Statement and Table
As required by OMB Circular A–4
(available at https://
www.whitehouse.gov/omb/circulars_
a004_a-4), in Table 40, we have
prepared an accounting statement
showing the classification of the
transfers and costs associated with the
HH PPS provisions of this proposed
rule. Table 40 provides our best estimate
of the decrease in Medicare payments
under the HH PPS as a result of the
changes presented in this proposed rule
for the HH PPS provisions.
TABLE 40—ACCOUNTING STATEMENT:
HH PPS CLASSIFICATION OF ESTIMATED TRANSFERS AND COSTS,
FROM THE CYS 2016 TO 2017 *
Category
Annualized Monetized
Transfers.
From Whom to
Whom?
Transfers
¥$180 million.
Federal Government
to HHAs.
Table 41 provides our best estimate of
the decrease in Medicare payments
under the HHVBP Model as a result of
the proposed changes presented in this
proposed rule for the HHVBP Model.
TABLE 41—ACCOUNTING STATEMENT:
HHVBP MODEL CLASSIFICATION OF
ESTIMATED COST SAVINGS FOR CY
2016–2021
Category
6-Year Gross Savings
Medicare Payments ..
Savings
¥$378 million.
Hospitals and SNFs.
F. Conclusion
1. HH PPS
In conclusion, we estimate that the
net impact of the HH PPS policies in
this rule is a decrease of 1.0 percent, or
$180 million, in Medicare payments to
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HHAs for CY 2017. The ¥$180 million
impact reflects the effects of the 2.3
percent CY 2017 HH payment update
percentage ($420 million increase), a 0.9
percent decrease in payments due to the
0.97 percent reduction to the national,
standardized 60-day episode payment
rate in CY 2016 to account for nominal
case-mix growth from 2012 through
2014 ($160 million decrease), the 0.1
percent decrease in payments due to the
change to the FDL ratio ($20 million
decrease), and a 2.3 percent decrease in
in payments due to the third year of the
4-year phase-in of the rebasing
adjustments required by section 3131(a)
of the Affordable Care Act ($420 million
decrease).
This analysis, together with the
remainder of this preamble, provides an
initial Regulatory Flexibility Analysis.
2. HHVBP Model
In conclusion, we estimate there
would be no net impact (to include
either a net increase or reduction in
payments) in this proposed rule in
Medicare payments to HHAs competing
in the HHVBP Model for CY 2017.
However, the overall economic impact
of the HHVBP Model provision is an
estimated $378 million in total savings
from a reduction in unnecessary
hospitalizations and SNF usage as a
result of greater quality improvements
in the home health industry over the life
of the HHVBP Model. The financial
estimates were based on the analysis of
hospital, home health and skilled
nursing facility claims data from nine
states using the most recent 2014
Medicare claims data. A study
published in 2002 by the Journal of the
American Geriatric Society (JAGS),
‘‘Improving patient outcomes of home
health care: findings from two
demonstration trials of outcome-based
quality improvement,’’ formed the basis
for CMMI’s projections.127 That study
observed a hospitalization relative rate
of decline of 22-percent to 26-percent
over the 3-year and 4-year
demonstration periods (the 1st year of
each being the base year) for the
national and New York trials. CMMI
assumed a conservative savings estimate
of up to a 6-percent ultimate annual
reduction in hospitalizations and up to
a 1.0-percent ultimate annual reduction
in SNF admissions and took into
account costs incurred from the
beneficiary remaining in the HHA if the
hospitalization did not occur; resulting
in total projected six performance year
127 Shaughnessy, et al. ‘‘Improving patient
outcomes of home health care: findings from two
demonstration trials of outcome-based quality
improvement,’’ available at https://
www.ncbi.nlm.nih.gov/pubmed/12164991.
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gross savings of $378 million. Based on
the JAGS study, which observed
hospitalization reductions of over 20percent, the 6-percent ultimate annual
hospitalization reduction assumptions
are considered reasonable.
IX. Federalism Analysis
Executive Order 13132 on Federalism
(August 4, 1999) 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. We have
reviewed this proposed rule under the
threshold criteria of Executive Order
13132, Federalism, and have
determined that it will not have
substantial direct effects on the rights,
roles, and responsibilities of states, local
or tribal governments.
List of Subjects
42 CFR part 409
42 CFR Part 484
Health facilities, Health professions,
Medicare, and Reporting and
recordkeeping requirements.
For the reasons set forth in the
preamble, the Centers for Medicare &
Medicaid Services amends 42 CFR
chapter IV as set forth below:
PART 409—HOSPITAL INSURANCE
BENEFITS
1. The authority citation for part 409
continues to read as follows:
■
Authority: Secs. 1102 and 1871 of the Act
(42 U.S.C. 1302 and 1395hh).
2. Section 409.50 is revised to read as
follows:
■
§ 409.50 Coinsurance for durable medical
equipment (DME) and applicable disposable
devices furnished as a home health service.
The coinsurance liability of the
beneficiary or other person for DME or
applicable disposable devices (as
defined in section 1834(s)(2)) furnished
as a home health service is 20 percent
of the customary (insofar as reasonable)
charge for the services.
PART 484—HOME HEALTH SERVICES
3. The authority citation for part 484
continues to read as follows:
■
Authority: Secs 1102 and 1871 of the Act
(42 U.S.C. 1302 and 1395(hh)) unless
otherwise indicated.
4. Section 484.240 is amended by
revising paragraph (d) to read as
follows:
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§ 484.240 Methodology used for the
calculation of the outlier payment.
*
*
*
*
*
(d) CMS imputes the cost for each
episode by multiplying the national per15 minute unit amount of each
discipline by the number of 15 minute
units in the discipline and computing
the total imputed cost for all disciplines.
*
*
*
*
*
■ 5. Section 484.305 is amended by
revising the definition of ‘‘Benchmark’’
and removing the definition of ‘‘Starter
Set’’ and to read as follows:
§ 484.305
Definitions.
*
*
*
*
*
Benchmark refers to the mean of the
top decile of Medicare-certified HHA
performance on the specified quality
measure during the baseline period,
calculated for each state.
*
*
*
*
*
■ 6. Section 484.315 is amended by
revising paragraph (a) to read as follows:
§ 484.315 Data reporting for measures and
evaluation under the Home Health ValueBased Purchasing (HHVBP) Model.
Health facilities, Medicare
■
43787
(a) Competing home health agencies
will be evaluated using a set of quality
measures.
*
*
*
*
*
§ 484.320
[Amended]
7. Section 484.320 is amended by:
a. Amending paragraphs (a), (b), and
(c) by removing the phrase ‘‘in the
starter set,’’.
■ b. Amending paragraph (d) by
removing the phrase ‘‘in the starter set’’.
■ 8. Section 484.335 is added to read as
follows:
■
■
§ 484.335 Appeals Process for the Home
Health Value-Based Purchasing (HHVBP)
Model.
(a) Requests for recalculation—(1)
Matters for recalculation. Subject to the
limitations on review under section
1115A of the Act, a HHA may submit a
request for recalculation under this
section if it wishes to dispute the
calculation of the following:
(i) Interim performance scores.
(ii) Annual total performance scores.
(iii) Application of the formula to
calculate annual payment adjustment
percentages.
(2) Time for filing a request for
recalculation. A recalculation request
must be submitted in writing within 15
calendar days after CMS posts the HHAspecific information on the HHVBP
Secure Portal, in a time and manner
specified by CMS.
(3) Content of request. (i) The
provider’s name, address associated
with the services delivered, and CMS
Certification Number (CCN).
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(ii) The basis for requesting
recalculation to include the specific
quality measure data that the HHA
believes is inaccurate or the calculation
the HHA believes is incorrect.
(iii) Contact information for a person
at the HHA with whom CMS or its agent
can communicate about this request,
including name, email address,
telephone number, and mailing address
(must include physical address, not just
a post office box).
(iv) The HHA may include in the
request for reconsideration additional
documentary evidence that CMS should
consider. Such documents may not
include data that was to have been filed
by the applicable data submission
deadline, but may include evidence of
timely submission.
(4) Scope of review for recalculation.
In conducting the recalculation, CMS
will review the applicable measures and
performance scores, the evidence and
findings upon which the determination
was based, and any additional
documentary evidence submitted by the
home health agency. CMS may also
review any other evidence it believes to
be relevant to the recalculation.
(5) Recalculation decision. CMS will
issue a written notification of findings.
A recalculation decision is subject to the
request for reconsideration process in
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accordance with paragraph (b) of this
section.
(b) Requests for reconsideration—(1)
Matters for reconsideration. A home
health agency may request
reconsideration of the recalculation of
the annual total performance score and
payment adjustment percentage
following a recalculation request
submitted under § 484.335(a) or the
decision to deny a HHA’s recalculation
request submitted under paragraph (a)
of this section.
(2) Time for filing a request for
reconsideration. The request for
reconsideration must be submitted via
the HHVBP Secure Portal within 15
calendar days from CMS’ notification to
the HHA contact of the outcome of the
recalculation process.
(3) Content of request. (i) The name of
the HHA, address associated with the
services delivered, and CMS
Certification Number (CCN).
(ii) The basis for requesting
reconsideration to include the specific
quality measure data that the HHA
believes is inaccurate or the calculation
the HHA believes is incorrect.
(iii) Contact information for a person
at the HHA with whom CMS or its agent
can communicate about this request,
including name, email address,
telephone number, and mailing address
(must include physical address, not just
a post office box).
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(iv) The HHA may include in the
request for reconsideration additional
documentary evidence that CMS should
consider. Such documents may not
include data that was to have been filed
by the applicable data submission
deadline, but may include evidence of
timely submission.
(4) Scope of review for
reconsideration. In conducting the
reconsideration review, CMS will
review the applicable measures and
performance scores, the evidence and
findings upon which the determination
was based, and any additional
documentary evidence submitted by the
HHA. CMS may also review any other
evidence it believes to be relevant to the
reconsideration. The HHA must prove
its case by a preponderance of the
evidence with respect to issues of fact
(5) Reconsideration decision. CMS
reconsideration officials will issue a
written determination.
Dated: June 2, 2016.
Andrew M. Slavitt,
Acting Administrator, Centers for Medicare
& Medicaid Services.
Dated: June 23, 2016.
Sylvia M. Burwell,
Secretary, Department of Health and Human
Services.
[FR Doc. 2016–15448 Filed 6–27–16; 4:15 pm]
BILLING CODE 4120–01–P
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]]>Agencies
[Federal Register Volume 81, Number 128 (Tuesday, July 5, 2016)]
[Proposed Rules]
[Pages 43713-43788]
From the Federal Register Online via the Government Publishing Office [www.gpo.gov]
[FR Doc No: 2016-15448]
[[Page 43713]]
Vol. 81
Tuesday,
No. 128
July 5, 2016
Part II
Department of Health and Human Services
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Centers for Medicare & Medicaid Services
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42 CFR Parts 409 and 484
Medicare and Medicaid Programs; CY 2017 Home Health Prospective Payment
System Rate Update; Home Health Value-Based Purchasing Model; and Home
Health Quality Reporting Requirements; Proposed Rule
Federal Register / Vol. 81 , No. 128 / Tuesday, July 5, 2016 /
Proposed Rules
[[Page 43714]]
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DEPARTMENT OF HEALTH AND HUMAN SERVICES
Centers for Medicare & Medicaid Services
42 CFR Parts 409 and 484
[CMS-1648-P]
RIN 0938-AS80
Medicare and Medicaid Programs; CY 2017 Home Health Prospective
Payment System Rate Update; Home Health Value-Based Purchasing Model;
and Home Health Quality Reporting Requirements
AGENCY: Centers for Medicare & Medicaid Services (CMS), HHS.
ACTION: Proposed rule.
-----------------------------------------------------------------------
SUMMARY: This proposed rule would update the Home Health Prospective
Payment System (HH PPS) payment rates, including the national,
standardized 60-day episode payment rates, the national per-visit
rates, and the non-routine medical supply (NRS) conversion factor,
effective for home health episodes of care ending on or after January
1, 2017. This proposed rule also: Implements the last year of the 4-
year phase-in of the rebasing adjustments to the HH PPS payment rates;
updates the HH PPS case-mix weights using the most current, complete
data available at the time of rulemaking; implements the 2nd-year of a
3-year phase-in of a reduction to the national, standardized 60-day
episode payment to account for estimated case-mix growth unrelated to
increases in patient acuity (that is, nominal case-mix growth) between
CY 2012 and CY 2014; proposes changes to the methodology used to
calculate outlier payments (with regards to payments made under the HH
PPS for high-cost ``outlier'' episodes of care (that is, episodes of
care with unusual variations in the type or amount of medically
necessary care)); proposes changes in payment for Negative Pressure
Wound Therapy (NPWT) performed using a disposable device for patient's
under a home health plan of care; discusses our efforts to monitor the
potential impacts of the rebasing adjustments mandated; includes an
update on subsequent research and analysis as a result of the findings
from the home health study; solicits comments on a potential process
for grouping HH PPS claims centrally during claims processing; and
proposes changes to the Home Health Value-Based Purchasing (HHVBP)
Model, which was implemented on January 1, 2016; and proposes updates
to the Home Health Quality Reporting Program (HH QRP).
DATES: To be assured consideration, comments must be received at one of
the addresses provided below, no later than 5 p.m. on August 26, 2016.
ADDRESSES: In commenting, please refer to file code CMS-1648-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 https://www.regulations.gov. Follow the instructions under
the ``More Search Options'' tab.
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-1648-P, P.O. Box 8016,
Baltimore, MD 21244-8016.
Please allow sufficient time for mailed comments to be received
before the close of the comment period.
3. By express or overnight mail. You may send written comments to
the following address ONLY: Centers for Medicare & Medicaid Services,
Department of Health and Human Services, Attention: CMS-1648-P, Mail
Stop C4-26-05, 7500 Security Boulevard, Baltimore, MD 21244-1850.
4. By hand or courier. If you prefer, you may deliver (by hand or
courier) your written comments before the close of the comment period
to either of the following addresses:
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 (410) 786-7195 in advance to schedule your arrival with one
of our staff members.
Comments 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: For general information about the HH
PPS, please send your inquiry via email to:
HomehealthPolicy@cms.hhs.gov.
For information about the HHVBP Model, please send your inquiry via
email to: HHVBPquestions@cms.hhs.gov.
Michelle Brazil, (410) 786-1648 for information about the HH
quality reporting program.
Lori Teichman, (410) 786-6684, for information about HHCAHPS.
SUPPLEMENTARY INFORMATION:
Inspection of Public Comments: All comments received before the
close of the comment period are available for viewing by the public,
including any personally identifiable or confidential business
information that is included in a comment. We post all comments
received before the close of the comment period on the following Web
site as soon as possible after they have been received at https://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. EST. To schedule an appointment to view public comments,
phone 1-800-743-3951.
Table of Contents
I. Executive Summary
A. Purpose
B. Summary of the Major Provisions
C. Summary of Costs and Benefits
II. Background
A. Statutory Background
B. System for Payment of Home Health Services
C. Updates to the Home Health Prospective Payment System
III. Proposed Provisions of the Home Health Prospective Payment
System
A. Monitoring for Potential Impacts--Affordable Care Act
Rebasing Adjustments
B. Proposed CY 2017 HH PPS Case-Mix Weights
C. Proposed CY 2017 Home Health Rate Update
1. Proposed CY 2017 Home Health Market Basket Update
[[Page 43715]]
2. Proposed CY 2017 Home Health Wage Index
3. Proposed CY 2017 Annual Payment Update
D. Payments for High-Cost Outliers Under the HH PPS
1. Background
2. Proposed Changes to the Methodology Used To Estimate Episode
Cost
3. Proposed Fixed Dollar Loss (FDL) Ratio
E. Proposed Payment Policies for Negative Pressure Wound Therapy
Using a Disposable Device
F. Update on Subsequent Research and Analysis Related to Section
3131(d) of the Affordable Care Act
G. Update on Future Plans to Group HH PPS Claims Centrally
During Claims Processing
IV. Proposed Provisions of the Home Health Value-Based Purchasing
(HHVBP) Model
A. Background
B. Smaller- and Larger-Volume Cohorts
C. Quality Measures
D. Appeals Process
E. Discussion of the Public Display of Total Performance Scores
V. Proposed Updates to the Home Health Care Quality Reporting
Program (HHQRP)
A. Background and Statutory Authority
B. General Considerations Used for the Selection of Quality
Measures for the HH QRP
C. Policy for Retaining HH QRP Quality Measures Adopted for
Future Payment Determination
D. Process for Adoption of Changes to HH QRP Measures
E. HH QRP Quality, Resource Use, and Other Measures for CY 2018
Payment Determination and Subsequent Years
1. Proposal To Address the IMPACT Act Domain of Resource Use and
Other Measures: MSPB-PAC HH QRP
2. Proposal To Address the IMPACT Act Domain of Resource Use and
Other Measures: Discharge to Community--Post Acute Care Home Health
Quality Reporting Program
3. Proposal To Address the IMPACT Act of 2014 Domain of Resource
Use and Other Measures: Potentially Preventable 30-Day Post-
Discharge Readmission Measure for Post-Acute Care Home Health
Quality Reporting Program.
4. Proposal To Address the IMPACT Act Domain of Medication
Reconciliation: Drug Regimen Review Conducted With Follow-Up for
Identified Issues-Post-Acute Care Home Health Quality Reporting
Program.
F. HH QRP Quality Measures and Measure Concepts Under
Consideration for Future Years
G. Form Manner and Timing of OASIS Data Submission and OASIS
Data for Annual Payment Update
1. Regulatory Authority
2. Home Health Quality Reporting Program Requirements for CY
2017 Payment and Subsequent Years
3. Previously Established Pay-for-Reporting Performance
Requirement for Submission of OASIS Quality Data
4. Proposed Timeline and Data Submission Mechanisms for Measures
Proposed for the CY 2018 Payment Determination and Subsequent Years
5. Proposed Timeline and Data Submission Mechanisms for the CY
2018 Payment Determination and Subsequent Years for New HH QRP
Assessment-Based Quality Measure
6. Data Collection Timelines and Requirements for the CY 2019
Payment Determinations and Subsequent Years
7. Proposed Data Review and Correction Timeframes for Data
Submitted Using the OASIS Instrument
H. Public Display of Quality Measure Data and Opportunity for
Providers To Review and Correct Data and Information to be Made
Public
I. Mechanism for Providing Feedback Reports to HHAs
J. Home Health Care CAHPS[supreg] Survey (HHCAHPS)
1. Background and Description of HHCAHPS
2. HHCAHPS Oversight Activities
3. HHCAHPS Requirements for the CY 2017 APU
4. HHCAHPS Requirements for the CY 2018 APU
5. HHCAHPS Requirements for the CY 2019 APU
6. HHCAHPS Requirements for the CY 2020 APU
7. HHCAHPS Reconsideration and Appeals Process
8. Summary
VI. Collection of Information Requirements
VII. Response to Comments
VIII. Regulatory Impact Analysis
IX. Federalism Analysis
Regulations Text
Acronyms
In addition, because of the many terms to which we refer by
abbreviation in this proposed rule, we are listing these abbreviations
and their corresponding terms in alphabetical order below:
ACH LOS Acute Care Hospital Length of Stay
ADL Activities of Daily Living
APU Annual Payment Update
BBA Balanced Budget Act of 1997, Pub. L. 105-33
BBRA Medicare, Medicaid, and SCHIP Balanced Budget Refinement Act of
1999, (Pub. L. 106-113)
CAD Coronary Artery Disease
CAH Critical Access Hospital
CBSA Core-Based Statistical Area
CASPER Certification and Survey Provider Enhanced Reports
CHF Congestive Heart Failure
CMI Case-Mix Index
CMP Civil Money Penalty
CMS Centers for Medicare & Medicaid Services
CoPs Conditions of Participation
COPD Chronic Obstructive Pulmonary Disease
CVD Cardiovascular Disease
CY Calendar Year
DM Diabetes Mellitus
DRA Deficit Reduction Act of 2005, Pub. L. 109-171, enacted February
8, 2006
FDL Fixed Dollar Loss
FI Fiscal Intermediaries
FISS Fiscal Intermediary Shared System
FR Federal Register
FY Fiscal Year
HAVEN Home Assessment Validation and Entry System
HCC Hierarchical Condition Categories
HCIS Health Care Information System
HH Home Health
HHA Home Health Agency
HHCAHPS Home Health Care Consumer Assessment of Healthcare Providers
and Systems Survey
HH PPS Home Health Prospective Payment System
HHRG Home Health Resource Group
HHVBP Home Health Value-Based Purchasing
HIPPS Health Insurance Prospective Payment System
HVBP Hospital Value-Based Purchasing
ICD-9-CM International Classification of Diseases, Ninth Revision,
Clinical Modification
ICD-10-CM International Classification of Diseases, Tenth Revision,
Clinical Modification
IH Inpatient Hospitalization
IMPACT Act Improving Medicare Post-Acute Care Transformation Act of
2014 (Pub. L. 113-185)
IRF Inpatient Rehabilitation Facility
LEF Linear Exchange Function
LTCH Long-Term Care Hospital
LUPA Low-Utilization Payment Adjustment
MEPS Medical Expenditures Panel Survey
MMA Medicare Prescription Drug, Improvement, and Modernization Act
of 2003, Pub. L. 108-173, enacted December 8, 2003
MSA Metropolitan Statistical Area
MSS Medical Social Services
NQF National Quality Forum
NQS National Quality Strategy
NRS Non-Routine Supplies
OASIS Outcome and Assessment Information Set
OBRA Omnibus Budget Reconciliation Act of 1987, Pub. L. 100-2-3,
enacted December 22, 1987
OCESAA Omnibus Consolidated and Emergency Supplemental
Appropriations Act, Pub. L. 105-277, enacted October 21, 1998
OES Occupational Employment Statistics
OIG Office of Inspector General
OT Occupational Therapy
OMB Office of Management and Budget
MFP Multifactor productivity
PAMA Protecting Access to Medicare Act of 2014
PAC-PRD Post-Acute Care Payment Reform Demonstration
PEP Partial Episode Payment Adjustment
PT Physical Therapy
PY Performance Year
PRRB Provider Reimbursement Review Board
QAP Quality Assurance Plan
RAP Request for Anticipated Payment
RF Renal Failure
RFA Regulatory Flexibility Act, Pub. L. 96-354
RHHIs Regional Home Health Intermediaries
[[Page 43716]]
RIA Regulatory Impact Analysis
SAF Standard Analytic File
SLP Speech-Language Pathology
SN Skilled Nursing
SNF Skilled Nursing Facility
TPS Total Performance Score
UMRA Unfunded Mandates Reform Act of 1995
VBP Value-Based Purchasing
I. Executive Summary
A. Purpose
This proposed rule would update the payment rates for home health
agencies (HHAs) for calendar year (CY) 2017, as required under section
1895(b) of the Social Security Act (the Act). This would reflect the
final year of the 4-year phase-in of the rebasing adjustments to the
national, standardized 60-day episode payment rate, the national per-
visit rates, and the NRS conversion factor finalized in the CY 2014 HH
PPS final rule (78 FR 72256), as required under section 3131(a) of the
Patient Protection and Affordable Care Act of 2010 (Pub. L. 111-148),
as amended by the Health Care and Education Reconciliation Act of 2010
(Pub. L. 111-152) (collectively referred to as the ``Affordable Care
Act'').
This proposed rule would update the case-mix weights under section
1895(b)(4)(A)(i) and (b)(4)(B) of the Act and includes a reduction to
the national, standardized 60-day episode payment rate in CY 2017 of
0.97 percent, to account for case-mix growth unrelated to increases in
patient acuity (nominal case-mix growth) between CY 2012 and CY 2014
under the authority of section 1895(b)(3)(B)(iv) of the Act. With
regards to payments made under the HH PPS for high-cost ``outlier''
episodes of care (that is, episodes of care with unusual variations in
the type or amount of medically necessary care), this rule proposes
changes to the methodology used to calculate outlier payments under the
authority of section 1895(b)(5) of the Act. Also, in accordance with
section 1834(s)(1) of the Act, as amended by the Consolidated
Appropriations Act of 2016 (Pub. L. 114-113), this rule proposes
changes in payment for Negative Pressure Wound Therapy (NPWT) performed
using a disposable device for patient's under a home health plan of
care for which payment would otherwise be made under section 1895(b) of
the Act. This proposed rule also discusses our efforts to monitor for
potential impacts of the rebasing adjustments mandated by section
3131(a) of the Affordable Care Act, provides an update on subsequent
research and analysis as a result of the findings from the home health
study required by section 3131(d) of the Affordable Care Act, and
provides and update and solicits comments on a process to group HH PPS
claims centrally during claims processing. Additionally, this rule
proposes changes to the HHVBP Model, in which Medicare-certified HHAs
in certain states are required to participate as of January 1, 2016,
under the authority of section 1115A of the Act; and proposes changes
to the home health quality reporting program requirements under the
authority of section 1895(b)(3)(B)(v)(II) of the Act.
B. Summary of the Major Provisions
As required by section 3131(a) of the Affordable Care Act, and
finalized in the CY 2014 HH PPS final rule (78 FR 77256, December 2,
2013), we are implementing the final year of the 4-year phase-in of the
rebasing adjustments to the national, standardized 60-day episode
payment amount, the national per-visit rates and the NRS conversion
factor in section III.C.3. The rebasing adjustments for CY 2017 will
reduce the national, standardized 60-day episode payment amount by
$80.95, increase the national per-visit payment amounts by 3.5 percent
of the national per-visit payment amounts in CY 2010 with the increases
ranging from $1.79 for home health aide services to $6.34 for medical
social services, and reduce the NRS conversion factor by 2.82 percent.
In addition, in section III.C.3 of this rule, we are implementing a
reduction to the national, standardized 60-day episode payment rate in
CY 2017 of 0.97 percent to account for estimated case-mix growth
unrelated to increases in patient acuity (that is, nominal case-mix
growth) between CY 2012 and CY 2014. This reduction was finalized in
the CY 2016 HH PPS final rule (80 FR 68624). Section III.A of this
proposed rule discusses our efforts to monitor for potential impacts
due to the rebasing adjustments mandated by section 3131(a) of the
Affordable Care Act.
In the CY 2015 HH PPS final rule (79 FR 66072), we finalized our
proposal to recalibrate the case-mix weights every year with more
current data. In section III.B.1 of this rule, we are recalibrating the
HH PPS case-mix weights, using the most current cost and utilization
data available, in a budget neutral manner. In section III.C.1 of this
rule, we propose to update the payment rates under the HH PPS by the
home health payment update percentage of 2.3 percent (using the 2010-
based Home Health Agency (HHA) market basket update of 2.8 percent,
minus 0.5 percentage point for productivity), as required by section
1895(b)(3)(B)(vi)(I) of the Act, and in section III.C.2 of this rule,
we propose to update the CY 2017 home health wage index using more
current hospital wage data. In section III.D, we are proposing to
revise the current methodology used to estimate the cost of an episode
of care to determine whether the episode of care would receive an
outlier payment. The methodology change includes calculating the cost
of an episode of care using a cost-per-unit calculation, which takes
into account visit length, rather than the current methodology that
uses a cost-per-visit calculation. In section III.E of this proposed
rule, as a result of the Consolidated Appropriations Act of 2016 (Pub.
L. 114-113), we are proposing changes in payment for when Negative
Pressure Wound Therapy (NPWT) is performed using a disposable device
for a patient under a home health plan of care and for which payment is
otherwise made under the HH PPS. In section III.F of this rule, we
provide an update on our recent research and analysis pertaining to the
home health study required by section 3131(d) of the Affordable Care
Act. Finally, in section III.G of this proposed rule, we provide an
update and solicit comments on a process for grouping the HH PPS claims
centrally during claims processing.
In section IV of this rule, we are proposing the following changes
to the HHVBP Model implemented January 1, 2016. We propose to remove
the definition for ``starter set''; propose to revise the definition
for ``benchmark''; propose to calculate benchmarks and achievement
thresholds at the state level; propose a minimum requirement of eight
HHAs in a cohort; propose to increase the time frame for submitting New
Measure data; propose to remove four measures from the set of
applicable measures; propose to adjust the reporting period and
submission date for one of the New Measures; propose to add an appeals
process that includes the existing recalculation process; and we are
providing an update on the progress towards developing public reporting
of performance under the HHVBP Model.
This proposed rule also proposes updates to the Home Health Quality
Reporting Program in section V, including the adoption of four new
quality measures, the removal of a number of measures, data submission
requirements, and data review and correction policies.
C. Summary of Costs and Transfers
[[Page 43717]]
Table 1--Summary of Costs and Transfers
----------------------------------------------------------------------------------------------------------------
Provision description Costs Transfers
----------------------------------------------------------------------------------------------------------------
CY 2017 HH PPS Payment Rate Update....... .............. The overall economic impact of the HH PPS payment
rate update is an estimated -$180 million (-1.0
percent) in payments to HHAs.
CY 2017 HHVBP Model...................... .............. The overall economic impact of the HHVBP Model
provision for CY 2018 through 2022 is an estimated
$378 million in total savings from a reduction in
unnecessary hospitalizations and SNF usage as a
result of greater quality improvements in the HH
industry. As for payments to HHAs, there are no
aggregate increases or decreases to the HHAs
competing in the model.
----------------------------------------------------------------------------------------------------------------
II. Background
A. Statutory Background
The Balanced Budget Act of 1997 (BBA) (Pub. L. 105-33, enacted
August 5, 1997), significantly changed the way Medicare pays for
Medicare HH services. Section 4603 of the BBA mandated the development
of the HH PPS. Until the implementation of the HH PPS on October 1,
2000, HHAs received payment under a retrospective reimbursement system.
Section 4603(a) of the BBA mandated the development of a HH PPS for
all Medicare-covered HH services provided under a plan of care (POC)
that were paid on a reasonable cost basis by adding section 1895 of the
Act, entitled ``Prospective Payment For Home Health Services.'' Section
1895(b)(1) of the Act requires the Secretary to establish a HH PPS for
all costs of HH services paid under Medicare.
Section 1895(b)(3)(A) of the Act requires the following: (1) The
computation of a standard prospective payment amount, to include all
costs for HH services covered and paid for on a reasonable cost basis,
and that such amounts be initially based on the most recent audited
cost report data available to the Secretary; and (2) the standardized
prospective payment amount is to be adjusted to account for the effects
of case-mix and wage levels among HHAs.
Section 1895(b)(3)(B) of the Act requires an annual update to the
standard prospective payment amounts by the HH applicable percentage
increase. Section 1895(b)(4) of the Act governs the payment
computation. Sections 1895(b)(4)(A)(i) and (b)(4)(A)(ii) of the Act
require the standard prospective payment amount to be adjusted for
case-mix and geographic differences in wage levels, respectively.
Section 1895(b)(4)(B) of the Act requires the establishment of an
appropriate case-mix change adjustment factor for significant variation
in costs among different units of services.
Similarly, section 1895(b)(4)(C) of the Act requires the
establishment of wage adjustment factors that reflect the relative
level of wages, and wage-related costs applicable to HH services
furnished in a geographic area compared to the applicable national
average level. Under section 1895(b)(4)(C) of the Act, the wage-
adjustment factors used by the Secretary may be the factors used under
section 1886(d)(3)(E) of the Act.
Section 1895(b)(5) of the Act gives the Secretary the option to
make additions or adjustments to the payment amount otherwise paid in
the case of outliers due to unusual variations in the type or amount of
medically necessary care. Section 3131(b)(2) of the Patient Protection
and Affordable Care Act of 2010 (the Affordable Care Act) (Pub. L. 111-
148, enacted March 23, 2010) revised section 1895(b)(5) of the Act so
that total outlier payments in a given year would not exceed 2.5
percent of total payments projected or estimated. The provision also
made permanent a 10 percent agency-level outlier payment cap.
In accordance with the statute, as amended by the BBA, we published
a final rule in the July 3, 2000 Federal Register (65 FR 41128) to
implement the HH PPS legislation. The July 2000 final rule established
requirements for the new HH PPS for HH services as required by section
4603 of the BBA, as subsequently amended by section 5101 of the Omnibus
Consolidated and Emergency Supplemental Appropriations Act (OCESAA) for
Fiscal Year 1999, (Pub. L. 105-277, enacted October 21, 1998); and by
sections 302, 305, and 306 of the Medicare, Medicaid, and SCHIP
Balanced Budget Refinement Act (BBRA) of 1999, (Pub. L. 106-113,
enacted November 29, 1999). The requirements include the implementation
of a HH PPS for HH services, consolidated billing requirements, and a
number of other related changes. The HH PPS described in that rule
replaced the retrospective reasonable cost-based system that was used
by Medicare for the payment of HH services under Part A and Part B. For
a complete and full description of the HH PPS as required by the BBA,
see the July 2000 HH PPS final rule (65 FR 41128 through 41214).
Section 5201(c) of the Deficit Reduction Act of 2005 (DRA) (Pub. L.
109-171, enacted February 8, 2006) added new section 1895(b)(3)(B)(v)
to the Act, requiring HHAs to submit data for purposes of measuring
health care quality, and links the quality data submission to the
annual applicable percentage increase. This data submission requirement
is applicable for CY 2007 and each subsequent year. If an HHA does not
submit quality data, the HH market basket percentage increase is
reduced by 2 percentage points. In the November 9, 2006 Federal
Register (71 FR 65884, 65935), we published a final rule to implement
the pay-for-reporting requirement of the DRA, which was codified at
Sec. 484.225(h) and (i) in accordance with the statute. The pay-for-
reporting requirement was implemented on January 1, 2007.
The Affordable Care Act made additional changes to the HH PPS. One
of the changes set out in section 3131 of the Affordable Care Act was
an amendment to section 421(a) of the Medicare Prescription Drug,
Improvement, and Modernization Act of 2003 (MMA) (Pub. L. 108-173,
enacted on December 8, 2003) as amended by section 5201(b) of the DRA.
Section 421(a) of the MMA, as amended by section 3131 of the Affordable
Care Act, requires that the Secretary increase, by 3 percent, the
payment amount otherwise made under section 1895 of the Act, for HH
services furnished in a rural area (as defined in section 1886(d)(2)(D)
of the Act) with respect to episodes and visits ending on or after
April 1, 2010, and before January 1, 2016. Section 210 of the Medicare
Access and CHIP Reauthorization Act of 2015 (MACRA) (Pub. L. 114-10)
amended section 421(a) of the MMA to extend the rural add-on for 2 more
years. Section 421(a) of the MMA, as amended by section 210 of the
MACRA, requires that the Secretary increase, by 3 percent, the payment
amount otherwise made under section 1895 of the Act, for HH services
provided in a
[[Page 43718]]
rural area (as defined in section 1886(d)(2)(D) of the Act) with
respect to episodes and visits ending on or after April 1, 2010, and
before January 1, 2018.
Section 2(a) of the Improving Medicare Post-Acute Care
Transformation Act of 2014 (the IMPACT Act) (Pub. L. 113-185, enacted
on Oct. 6, 2014) amended Title XVIII of the Act, in part, by adding a
new section 1899B, which imposes new data reporting requirements for
certain post-acute care (PAC) providers, including HHAs. Under section
1899B(a)(1) of the Act, certain post-acute care (PAC) providers
(defined in section 1899B(a)(2)(A) of the Act as HHAs, SNFs, IRFs, and
LTCHs) must submit standardized patient assessment data in accordance
with section 1899B(b) of the Act, data on quality measures required
under section 1899B(c)(1) of the Act, and data on resource use, and
other measures required under section 1899B(d)(1) of the Act. The Act
also requires the Secretary to specify these measures insofar as they
are respect to certain domains no later than the applicable specified
application date that applies to each domain. The specific specified
application dates that apply to each PAC provider type and domain are
described in section 1899B(a)(2)(E) of the Act.
B. System for Payment of Home Health Services
Generally, Medicare makes payment under the HH PPS on the basis of
a national standardized 60-day episode payment rate that is adjusted
for the applicable case-mix and wage index. The national standardized
60-day episode rate includes the six HH disciplines (skilled nursing,
HH aide, physical therapy, speech-language pathology, occupational
therapy, and medical social services). Payment for non-routine supplies
(NRS) is no longer part of the national standardized 60-day episode
rate and is computed by multiplying the relative weight for a
particular NRS severity level by the NRS conversion factor (See section
II.D.4.e). Payment for durable medical equipment covered under the HH
benefit is made outside the HH PPS payment system. To adjust for case-
mix, the HH PPS uses a 153-category case-mix classification system to
assign patients to a home health resource group (HHRG). The clinical
severity level, functional severity level, and service utilization are
computed from responses to selected data elements in the OASIS
assessment instrument and are used to place the patient in a particular
HHRG. Each HHRG has an associated case-mix weight which is used in
calculating the payment for an episode.
For episodes with four or fewer visits, Medicare pays national per-
visit rates based on the discipline(s) providing the services. An
episode consisting of four or fewer visits within a 60-day period
receives what is referred to as a low-utilization payment adjustment
(LUPA). Medicare also adjusts the national standardized 60-day episode
payment rate for certain intervening events that are subject to a
partial episode payment adjustment (PEP adjustment). For certain cases
that exceed a specific cost threshold, an outlier adjustment may also
be available.
C. Updates to the Home Health Prospective Payment System
As required by section 1895(b)(3)(B) of the Act, we have
historically updated the HH PPS rates annually in the Federal Register.
The August 29, 2007 final rule with comment period set forth an update
to the 60-day national episode rates and the national per-visit rates
under the HH PPS for CY 2008. The CY 2008 HH PPS final rule included an
analysis performed on CY 2005 HH claims data, which indicated a 12.78
percent increase in the observed case-mix since 2000. Case-mix
represents the variations in conditions of the patient population
served by the HHAs. Subsequently, a more detailed analysis was
performed on the 2005 case-mix data to evaluate if any portion of the
12.78 percent increase was associated with a change in the actual
clinical condition of HH patients. We examined data on demographics,
family severity, and non-HH Part A Medicare expenditures to predict the
average case-mix weight for 2005. We identified 8.03 percent of the
total case-mix change as real, and therefore, decreased the 12.78
percent of total case-mix change by 8.03 percent to get a final nominal
case-mix increase measure of 11.75 percent (0.1278 * (1 - 0.0803) =
0.1175).
To account for the changes in case-mix that were not related to an
underlying change in patient health status, we implemented a reduction,
over 4 years, to the national, standardized 60-day episode payment
rates. That reduction was to be 2.75 percent per year for 3 years
beginning in CY 2008 and 2.71 percent for the fourth year in CY 2011.
In the CY 2011 HH PPS final rule (76 FR 68532), we updated our analyses
of case-mix change and finalized a reduction of 3.79 percent, instead
of 2.71 percent, for CY 2011 and deferred finalizing a payment
reduction for CY 2012 until further study of the case-mix change data
and methodology was completed.
In the CY 2012 HH PPS final rule (76 FR 68526), we updated the 60-
day national episode rates and the national per-visit rates. In
addition, as discussed in the CY 2012 HH PPS final rule (76 FR 68528),
our analysis indicated that there was a 22.59 percent increase in
overall case-mix from 2000 to 2009 and that only 15.76 percent of that
overall observed case-mix percentage increase was due to real case-mix
change. As a result of our analysis, we identified a 19.03 percent
nominal increase in case-mix. At that time, to fully account for the
19.03 percent nominal case-mix growth identified from 2000 to 2009, we
finalized a 3.79 percent payment reduction in CY 2012 and a 1.32
percent payment reduction for CY 2013.
In the CY 2013 HH PPS final rule (77 FR 67078), we implemented a
1.32 percent reduction to the payment rates for CY 2013 to account for
nominal case-mix growth from 2000 through 2010. When taking into
account the total measure of case-mix change (23.90 percent) and the
15.97 percent of total case-mix change estimated as real from 2000 to
2010, we obtained a final nominal case-mix change measure of 20.08
percent from 2000 to 2010 (0.2390 * (1 - 0.1597) = 0.2008). To fully
account for the remainder of the 20.08 percent increase in nominal
case-mix beyond that which was accounted for in previous payment
reductions, we estimated that the percentage reduction to the national,
standardized 60-day episode rates for nominal case-mix change would be
2.18 percent. Although we considered proposing a 2.18 percent reduction
to account for the remaining increase in measured nominal case-mix, we
finalized the 1.32 percent payment reduction to the national,
standardized 60-day episode rates in the CY 2012 HH PPS final rule (76
FR 68532).
Section 3131(a) of the Affordable Care Act also required that,
beginning in CY 2014, we apply an adjustment to the national,
standardized 60-day episode rate and other amounts that reflect factors
such as changes in the number of visits in an episode, the mix of
services in an episode, the level of intensity of services in an
episode, the average cost of providing care per episode, and other
relevant factors. Additionally, we were required to phase in any
adjustment over a 4-year period in equal increments, not to exceed 3.5
percent of the amount (or amounts) as of the date of enactment of the
Affordable Care Act, and fully implement the rebasing adjustments by CY
2017. The statute specified that the maximum rebasing adjustment was to
[[Page 43719]]
be no more than 3.5 percent per year of the CY 2010 rates. Therefore,
in the CY 2014 HH PPS final rule (78 FR 72256) for each year, CY 2014
through CY 2017, we finalized a fixed-dollar reduction to the national,
standardized 60-day episode payment rate of $80.95 per year, increases
to the national per-visit payment rates per year as reflected in Table
2, and a decrease to the NRS conversion factor of 2.82 percent per
year. We also finalized three separate LUPA add-on factors for skilled
nursing, physical therapy, and speech-language pathology and removed
170 diagnosis codes from assignment to diagnosis groups in the HH PPS
Grouper. In the CY 2015 HH PPS final rule (79 FR 66032), we implemented
the 2nd year of the 4 year phase-in of the rebasing adjustments to the
HH PPS payment rates and made changes to the HH PPS case-mix weights.
In addition, we simplified the face-to-face encounter regulatory
requirements and the therapy reassessment timeframes.
Table 2--Maximum Adjustments to the National Per-Visit Payment Rates
[Not to exceed 3.5 percent of the amount(s) in CY 2010]
------------------------------------------------------------------------
Maximum
2010 National per- adjustments per
visit payment year (CY 2014
rates through CY 2017)
------------------------------------------------------------------------
Skilled Nursing................... $113.01 $3.96
Home Health Aide.................. 51.18 1.79
Physical Therapy.................. 123.57 4.32
Occupational Therapy.............. 124.40 4.35
Speech-Language Pathology......... 134.27 4.70
Medical Social Services........... 181.16 6.34
------------------------------------------------------------------------
In the CY 2016 HH PPS final rule (80 FR 68624), we implemented the
3rd year of the 4-year phase-in of the rebasing adjustments to the
national, standardized 60-day episode payment amount, the national per-
visit rates and the NRS conversion factor (as outlined above).
In the CY 2016 HH PPS final rule, we also recalibrated the HH PPS
case-mix weights, using the most current cost and utilization data
available, in a budget neutral manner, and finalized reductions to the
national, standardized 60-day episode payment rate in CY 2016, CY 2017,
and CY 2018 of 0.97 percent in each year to account for estimated case-
mix growth unrelated to increases in patient acuity (that is, nominal
case-mix growth) between CY 2012 and CY 2014. Finally, we continued to
apply the payment increase of 3 percent for HH services provided in
rural areas (as defined in section 1886(d)(2)(D) of the Act) to
episodes or visits ending before January 1, 2018.
III. Proposed Provisions of the Home Health Prospective Payment System
A. Monitoring for Potential Impacts--Affordable Care Act Rebasing
Adjustments
1. Analysis of FY 2014 HHA Cost Report Data
As part of our efforts in monitoring the potential impacts of the
rebasing adjustments finalized in the CY 2014 HH PPS final rule (78 FR
72293), we continue to update our analysis of home health cost report
and claims data. In the CY 2014 HH PPS final rule, using 2011 cost
report and 2012 claims data, we estimated the 2013 60-day episode cost
to be $2,565.51 (78 FR 72277). In that final rule, we stated that our
analysis of 2011 cost report data and 2012 claims data indicated a need
for a -3.45 percent rebasing adjustment to the national, standardized
60-day episode payment rate each year for 4 years. However, as
specified by statute, the rebasing adjustment is limited to 3.5 percent
of the CY 2010 national, standardized 60-day episode payment rate of
$2,312.94 (74 FR 58106), or $80.95. We stated that given that a -3.45
percent adjustment for CY 2014 through CY 2017 would result in larger
dollar amount reductions than the maximum dollar amount allowed under
section 3131(a) of the Affordable Care Act of $80.95, we were limited
to implementing a reduction of $80.95 (approximately 2.8 percent of the
standardized payment amount for CY 2014) to the national, standardized
60-day episode payment amount each year for CY 2014 through CY 2017.
In the CY 2015 HH PPS final rule, (79 FR 66032-66118) using 2012
cost report and 2013 claims data, we estimated the 2013 60-day episode
cost to be $2,485.24 (79 FR 66037). Similar to our discussion in the CY
2014 HH PPS final rule, we stated that absent the Affordable Care Act's
limit to rebasing, in order to align payments with costs, a -4.21
percent adjustment would have been applied to the national,
standardized 60-day episode payment amount each year for CY 2014
through CY 2017.
In the CY 2016 HH PPS proposed rule (80 FR 39846-39866), using 2013
cost report and 2013 claims data, we estimated the 2013 60-day episode
cost to be $2,402.11 (80 FR 39846). Similar to our discussion in the CY
2014 HH PPS final rule and the CY 2015 HH PPS final rule, we stated
that absent the Affordable Care Act's limit to rebasing, in order to
align payments with costs, a -5.02 percent adjustment would have been
applied to the national, standardized 60-day episode payment amount
each year for CY 2014 through CY 2017.
For this proposed rule, we analyzed 2014 HHA cost report data and
2014 HHA claims data to determine whether the average cost per episode
was higher using 2014 cost report data compared to the 2011 cost report
and 2012 claims da006used in calculating the rebasing adjustments. To
determine the 2014 average cost per visit per discipline, we applied
the same trimming methodology outlined in the CY 2014 HH PPS proposed
rule (78 FR 40284) and weighted the costs per visit from the 2014 cost
reports by size, facility type, and urban/rural location so the costs
per visit were nationally representative according to 2014 claims data.
The 2014 average number of visits was taken from 2014 claims data. We
estimate the cost of a 60-day episode in CY 2014 to be $2,373.87 using
2014 cost report data (Table 3). Our latest analysis of 2014 cost
report and 2014 claims data suggests that an even larger reduction (-
5.30 percent) than the reduction described in the CY 2014 HH PPS final
rule (-3.45 percent) or the reductions described in the CY 2015 HH PPS
final rule and the CY 2016 HH PPS proposed rule (-4.21 and -5.02
percent,
[[Page 43720]]
respectively) would have been needed in order to align payments with
costs. The decrease in the estimated 60-day episode cost from $2,402.11
in CY 2013 to $2,373.87 in CY 2014 was due to both a lower average cost
per visit for skilled nursing and home health aide services in 2014
compared to 2013 and lower average number of visits for skilled nursing
and home health aide services per episode in 2014 compared to 2013.
Table 3--2014 Estimated Cost per Episode
----------------------------------------------------------------------------------------------------------------
2014 Average 2014 Average
Discipline costs per number of 2014 60-Day
visit visits episode costs
----------------------------------------------------------------------------------------------------------------
Skilled Nursing................................................. $128.68 9.09 $1,169.70
Home Health Aide................................................ 56.59 2.19 123.93
Physical Therapy................................................ 155.90 5.18 807.56
Occupational Therapy............................................ 153.69 1.30 199.80
Speech-Language Pathology....................................... 166.98 0.26 43.41
Medical Social Services......................................... 210.48 0.14 29.47
-----------------------------------------------
Total....................................................... .............. 18.16 2,373.87
----------------------------------------------------------------------------------------------------------------
Source: FY 2014 Medicare cost report data and 2014 Medicare claims data from the standard analytic file (as of
June 30, 2015) for episodes (excluding low-utilization payment adjusted episodes and partial-episode-payment
adjusted episodes) ending on or before December 31, 2014 for which we could link an OASIS assessment.
2. Analysis of CY 2015 HHA Claims Data
In the CY 2014 HH PPS final rule (78 FR 72256), some commenters
expressed concern that the rebasing of the HH PPS payment rates would
result in HHA closures and would therefore diminish access to home
health services. In addition to examining more recent cost report data,
for this proposed rule we examined home health claims data from the
first 2 years (CY 2014 and CY 2015) of the 4-year phase-in of the
rebasing adjustments (CY 2014 through CY 2017), the first calendar year
of the HH PPS (CY 2001), and claims data for the 3 years before
implementation of the rebasing adjustments (CY 2011-2013). Preliminary
analysis of CY 2015 home health claims data indicates that the number
of episodes decreased by 3.8 percent from 2013 to 2014, and decreased
by 1.7 percent from 2014 to 2015. In addition, the number of home
health users that received at least one episode of care decreased by
2.95 percent between 2013 and 2014, and decreased slightly by 0.5
percent from 2014 to 2015.The number of FFS beneficiaries has remained
the relatively constant between 2013 and 2015. Between 2013 and 2014
there appears to be a net decrease in the number of HHAs billing
Medicare for home health services of 1.6 percent, and a continued
decrease of 2.7 percent from 2014 to 2015. We note that in CY 2015
there were 2.9 HHAs per 10,000 FFS beneficiaries, which is still
markedly higher than the 1.9 HHAs per 10,000 FFS beneficiaries before
the implementation of the HH PPS methodology in 2001. The number of
home health users, as a percentage of FFS beneficiaries, has been
decreasing since 2011, from 9.2 percent to 8.7 percent in 2015. We
would note that preliminary FFS data on per-enrollee hospital and
skilled nursing facility discharges and days indicates that there was a
decrease in hospital discharges of approximately 0.7 percent and a
decrease in SNF days of approximately 0.9 percent in CY 2015. Any
decreases in hospital discharges and skilled nursing facility days
could, in turn, impact home health utilization as those settings serve
as important sources of home health referrals.
Table 4--Home Health Statistics, CY 2001 and CY 2011 Through CY 2015
--------------------------------------------------------------------------------------------------------------------------------------------------------
2001 2011 2012 2013 2014 2015
--------------------------------------------------------------------------------------------------------------------------------------------------------
Number of episodes...................................... 3,896,502 6,821,459 6,727,875 6,708,923 6,451,283 6,340,932
Beneficiaries receiving at least 1 episode (Home Health 2,412,318 3,449,231 3,446,122 3,484,579 3,381,635 3,365,512
Users).................................................
Part A and/or B FFS beneficiaries....................... 34,899,167 37,686,526 38,224,640 38,505,609 38,506,534 38,592,533
Episodes per Part A and/or B FFS beneficiaries.......... 0.11 0.18 0.18 0.17 0.17 0.16
Home health users as a percentage of Part A and/or B FFS 6.9% 9.2% 9.0% 9.0% 8.8% 8.7%
beneficiaries..........................................
HHAs providing at least 1 episode....................... 6,511 11,446 11,746 11,889 11,693 11,381
HHAs per 10,000 Part A and/or B FFS beneficiaries....... 1.9 3.0 3.1 3.1 3.0 2.9
--------------------------------------------------------------------------------------------------------------------------------------------------------
Source: National claims history (NCH) data obtained from Chronic Condition Warehouse (CCW)--Accessed on May 14, 2014 and August 19, 2014 for CY 2011, CY
2012, and CY 2013 data; accessed on May 7, 2015 for CY 2001 and CY 2014 data, and accessed on April 7, 2016 for CY 2015 data Medicare enrollment
information obtained from the CCW Master Beneficiary Summary File. Beneficiaries are the total number of beneficiaries in a given year with at least 1
month of Part A and/or Part B Fee-for-Service coverage without having any months of Medicare Advantage coverage.
Note(s): These results include all episode types (Normal, PEP, Outlier, LUPA) and also include episodes from outlying areas (outside of 50 States and
District of Columbia). Only episodes with a through date in the year specified are included. Episodes with a claim frequency code equal to ``0''
(``Non-payment/zero claims'') and ``2'' (``Interim--first claim'') are excluded. If a beneficiary is treated by providers from multiple states within
a year the beneficiary is counted within each state's unique number of beneficiaries served.
In addition to examining home health claims data from the first 2
years of the implementation of rebasing adjustments required by the
Affordable Care Act and comparing utilization in those years (CY 2014 &
CY 2015) to the 3 years prior to
[[Page 43721]]
and to the first calendar year following the implementation of the HH
PPS (CY 2001), we subsequently examined trends in home health
utilization for all years starting in CY 2001 and up through CY 2015.
Figure 1, displays the average number of visits per 60-day episode of
care and the average payment per visit. While the average payment per
visit has steadily increased from approximately $116 in CY 2001 to $166
for CY 2015, the average total number of visits per 60-day episode of
care has declined, most notably between CY 2009 (21.7 visits per
episode) and CY 2010 (19.8 visits per episode), which was the first
year that the 10 percent agency-level cap on HHA outlier payments was
implemented. As noted in section II.C, we also implemented a series of
reductions to the national, standardized 60-day episode payment rate to
account for increases in nominal case-mix, starting in CY 2008. The
reductions to the 60-day episode rate were: 2.75 percent each year for
CY 2008, CY 2009, and CY 2010; 3.79 percent for CY 2011 and CY 2012;
and a 1.32 percent payment reduction for CY 2013. Figure 2 displays the
average number of visits by discipline type for a 60-day episode of
care and shows that while the number of therapy visits per 60-day
episode of care has increased steadily, the number of skilled nursing
and home health aide visits have decreased, between CY 2009 and CY
2015. Section III.F describes the results of the home health study
required by section 3131(d) of the Affordable Care Act, which suggests
that the current home health payment system may discourage HHAs from
serving patients with clinically complex and/or poorly controlled
chronic conditions who do not qualify for therapy but require a large
number of skilled nursing visits. The home health study results seem to
be consistent with the recent trend in the decreased number of visits
per episode of care driven by decreases in skilled nursing and home
health aide services evident in Figures 1 and 2.
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As part of our monitoring efforts, we also examined the trends in
episode timing and service use over time. Currently, the first two 60-
day episodes of care are considered ``early'' and third or later 60-day
episodes of care are considered ``late'', as long as there is no more
than a 60-day gap in care between one episode and the next.
Specifically, we examined the percentage of early episodes with 0 to 19
therapy visits, late episodes with 0 to 19 therapy visits, and episodes
with 20+ therapy visits from CY 2008 to CY 2015. In CY 2008, we
implemented refinements to the HH PPS case-mix system. As part of those
refinements, we added additional therapy thresholds and differentiated
between early and late episodes for those episodes with less than 20+
therapy visits. Table 5 shows that the percentage of early and late
episodes from CY 2008 to CY 2015 has remained relatively stable over
time. There has been a slight decrease in the percentage of early
episodes with 0 to 19 therapy visits from 65.9 percent in CY 2008 to
59.8 percent in CY 2015 and a slight increase in the percentage of late
episodes with 0 to 19 therapy visits from 29.5 percent in CY 2008 to
33.5 percent in CY 2015. From CY 2014 to CY 2015, there was a slight
decrease in the percentage of early and late episodes with 0 to 19
therapy visits and there was a slight increase in the percentage of
episodes with 20+ therapy visits. In 2015, the case-mix weights for the
third and later episodes of care with 0 to 19 therapy visits decreased
as a result of the CY 2015 recalibration of the case-mix weights.
Despite the decreases in the case-mix weights for the later episodes,
the percentage of later episodes with 0 to 19 therapy visits did not
change substantially.
[[Page 43723]]
Table 5--Home Health Episodes by Episode Timing, CY 2008 Through CY 2015
--------------------------------------------------------------------------------------------------------------------------------------------------------
Number of
early % of early Number of late % of late
episodes episodes episodes episodes Number of % of episodes
Year All episodes (excluding (excluding (excluding (excluding episodes with with 20+
episodes with episodes with episodes with episodes with 20+ visits visits
20+ visits) 20+ visits) 20+ visits) 20+ visits)
--------------------------------------------------------------------------------------------------------------------------------------------------------
2008.................................... 5,423,037 3,571,619 65.9 1,600,587 29.5 250,831 4.6
2009.................................... 6,530,200 3,701,652 56.7 2,456,308 37.6 372,240 5.7
2010.................................... 6,877,598 3,872,504 56.3 2,586,493 37.6 418,601 6.1
2011.................................... 6,857,885 3,912,982 57.1 2,564,859 37.4 380,044 5.5
2012.................................... 6,767,576 3,955,207 58.4 2,458,734 36.3 353,635 5.2
2013.................................... 6,733,146 4,023,486 59.8 2,347,420 34.9 362,240 5.4
2014.................................... 6,616,875 3,980,151 60.2 2,263,638 34.2 373,086 5.6
2015.................................... 6,340,931 3,789,676 59.8 2,123,485 33.5 427,770 6.7
--------------------------------------------------------------------------------------------------------------------------------------------------------
Source: National claims history (NCH) data obtained from Chronic Condition Warehouse (CCW)--Accessed on April 7, 2016.
Note(s): Only episodes with a through date in the year specified are included. Episodes with a claim frequency code equal to ``0'' (``Non-payment/zero
claims'') and ``2'' (``Interim--first claim'') are excluded.
We also examined trends in admission source for home health
episodes over time. Specifically, we examined the admission source for
the ``first or only'' episodes of care (first episodes in a sequence of
adjacent episodes of care or the only episode of care) from CY 2008
through CY 2015 (Figure 3). The percentage of first or only episodes
with an acute admission source, defined as episodes with an inpatient
hospital stay within the 14 days prior to a home health episode, has
decreased from 38.6 percent in CY 2008 to 33.9 percent in CY 2015. The
percentage of first or only episodes with a post-acute admission
source, defined as episodes which had a stay at a skilled nursing
facility (SNF), inpatient rehabilitation facility (IRF), or long term
care hospital (LTCH) within 14 days prior to the home health episode,
slightly increased from 16.5 percent in CY 2008 to 18.1 percent in CY
2015. The percentage of first or only episodes with a community
admission source, defined as episodes which did not have an acute or
post-acute stay in the 14 days prior to the home health episode,
increased from 37.4 percent in CY 2008 to 41.9 percent in CY 2015. Our
findings on the trends in admission source are consistent to MedPAC's
as outlined in their 2015 Report to the Congress.\1\ However, MedPAC
examined admission source trends from 2002 up through 2013 and
concluded that ``there has been tremendous growth in the use of home
health for patients residing in the community, episodes not preceded by
a prior hospitalization. The high rates of volume growth for these
types of episodes, which have more than doubled since 2001, suggest
there is significant potential for overuse, particularly since Medicare
does not currently require any cost sharing for home health care.''
---------------------------------------------------------------------------
\1\ Medicare Payment Advisory Commission (MedPAC), ``Report to
the Congress: Medicare Payment Policy''. March 2015. P. 214.
Washington, DC. Accessed on 4/21/2016 at https://medpac.gov/documents/reports/march-2015-report-to-the-congress-medicare-payment-policy.pdf?sfvrsn=0.
---------------------------------------------------------------------------
[[Page 43724]]
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We will continue to monitor for potential impacts due to the
rebasing adjustments required by section 3131(a) of the Affordable Care
Act and other policy changes in the future. Independent effects of any
one policy may be difficult to discern in years where multiple policy
changes occur in any given year.
B. Proposed CY 2017 HH PPS Case-Mix Weights
In the CY 2015 HH PPS final rule (79 FR 66072), we finalized a
policy to annually recalibrate the HH PPS case-mix weights--adjusting
the weights relative to one another--using the most current, complete
data available. To recalibrate the HH PPS case-mix weights for CY 2017,
we will use the same methodology finalized in the CY 2008 HH PPS final
rule (72 FR 49762), the CY 2012 HH PPS final rule (76 FR 68526), and
the CY 2015 HH PPS final rule (79 FR 66032). Annual recalibration of
the HH PPS case-mix weights ensures that the case-mix weights reflect,
as accurately as possible, current home health resource use and changes
in utilization patterns.
To generate the proposed CY 2017 HH PPS case-mix weights, we used
CY 2015 home health claims data (as of December 31, 2015) with linked
OASIS data. These data are the most current and complete data available
at this time. We will use CY 2015 home health claims data (as of June
30, 2016) with linked OASIS data to generate the CY 2017 HH PPS case-
mix weights in the CY 2017 HH PPS final rule. The process we used to
calculate the HH PPS case-mix weights are outlined below.
Step 1: Re-estimate the four-equation model to determine the
clinical and functional points for an episode using wage-weighted
minutes of care as our dependent variable for resource use. The wage-
weighted minutes of care are determined using the CY 2014 Bureau of
Labor Statistics national hourly wage plus fringe rates for the six
home health disciplines and the minutes per visit from the claim. The
points for each of the variables for each leg of the model, updated
with CY 2015 home health claims data, are shown in Table 6. The points
for the clinical variables are added together to determine an episode's
clinical score. The points for the functional variables are added
together to determine an episode's functional score.
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In updating the four-equation model for CY 2017, using 2015 home
health claims data (the last update to the four-equation model for CY
2016 used CY 2014 home health claims data), there were few changes to
the point values for the variables in the four-equation model. These
relatively minor changes reflect the change in the relationship between
the grouper variables and resource use between CY 2014 and CY 2015. The
CY 2017 four-equation model resulted in 110 point-giving variables
being used in the model (as compared to the 124 variables for the CY
2016 recalibration). There were ten variables that were added to the
model and 24 variables that were dropped from the model due to the
absence of additional resources associated with the variable. Of the
variables that were in both the four-equation model for CY 2016 and the
four-equation model for CY 2017, the points for 37 variables increased
in the CY 2017 four-equation model and the points for 38 variables
decreased in the CY 2017 4-equation model. There were 25 variables with
the same point values.
Step 2: Re-defining the clinical and functional thresholds so they
are reflective of the new points associated with the CY 2017 four-
equation model. After estimating the points for each of the variables
and summing the clinical and functional points for each episode, we
look at the distribution of the clinical score and functional score,
breaking the episodes into different steps. The categorizations for the
steps are as follows:
Step 1: First and second episodes, 0-13 therapy visits.
Step 2.1: First and second episodes, 14-19 therapy visits.
Step 2.2: Third episodes and beyond, 14-19 therapy visits.
Step 3: Third episodes and beyond, 0-13 therapy visits.
Step 4: Episodes with 20+ therapy visits.
We then divide the distribution of the clinical score for episodes
within a step such that a third of episodes are classified as low
clinical score, a third of episodes are classified as medium
[[Page 43728]]
clinical score, and a third of episodes are classified as high clinical
score. The same approach is then done looking at the functional score.
It was not always possible to evenly divide the episodes within each
step into thirds due to many episodes being clustered around one
particular score.\2\ Also, we looked at the average resource use
associated with each clinical and functional score and used that as a
guide for setting our thresholds. We grouped scores with similar
average resource use within the same level (even if it meant that more
or less than a third of episodes were placed within a level). The new
thresholds, based off of the CY 2017 four-equation model points are
shown in Table 7.
---------------------------------------------------------------------------
\2\ For Step 1, 62% of episodes were in the medium functional
level (All with score 14).
For Step 2.1, 71.0% of episodes were in the low functional level
(Most with score 6).
For Step 2.2, 83.2% of episodes were in the medium functional
level (Most with score 2 or 3).
For Step 3, 51.3% of episodes were in the medium functional
level (Most with score 10).
For Step 4, 54.4% of episodes were in the medium functional
level (Most with score 6).
TABLE 7--CY 2017 Clinical and Functional Thresholds
------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
1st and 2nd Episodes 3rd+ Episodes All episodes
----------------------------------------------------------------------------------------------------------------------------------------
0 to 13 therapy visits 14 to 19 therapy visits 0 to 13 therapy visits 14 to 19 therapy visits 20+ therapy visits
------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
Grouping Step:......................................... 1......................... 2.1....................... 3........................ 2.2...................... 4.
Equation(s) used to calculate points: (see Table 6).... 1......................... 2......................... 3........................ 4........................ (2&4).
------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
Dimension Severity...........
level..............
------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
,s,nClinical.................. C1................. 0 to 1.................... 0 to 1.................... 0........................ 0 to 1................... 0 to 3.
C2................. 2 to 3.................... 2 to 7.................... 1........................ 2 to 9................... 4 to 17.
C3................. 4+........................ 8+........................ 2+....................... 10+...................... 18+.
Functional.................... F1................. 0 to 13................... 0 to 7.................... 0 to 6................... 0........................ 0 to 2.
F2................. 14........................ 8 to 13................... 7 to 10.................. 1 to 11.................. 3 to 6.
F3................. 15+....................... 14+....................... 11+...................... 12+...................... 7+.
------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
Step 3: Once the clinical and functional thresholds are determined
and each episode is assigned a clinical and functional level, the
payment regression is estimated with an episode's wage-weighted minutes
of care as the dependent variable. Independent variables in the model
are indicators for the step of the episode as well as the clinical and
functional levels within each step of the episode. Like the four-
equation model, the payment regression model is also estimated with
robust standard errors that are clustered at the beneficiary level.
Table 8 shows the regression coefficients for the variables in the
payment regression model updated with CY 2015 home health claims data.
The R-squared value for the payment regression model is 0.4919 (an
increase from 0.4822 for the CY 2016 recalibration).
Table 8--Payment Regression Model
------------------------------------------------------------------------
New payment
Variable description regression
coefficients
------------------------------------------------------------------------
Step 1, Clinical Score Medium........................... $25.75
Step 1, Clinical Score High............................. 60.84
Step 1, Functional Score Medium......................... 71.60
Step 1, Functional Score High........................... 108.83
Step 2.1, Clinical Score Medium......................... 53.35
Step 2.1, Clinical Score High........................... 129.94
Step 2.1, Functional Score Medium....................... 11.54
Step 2.1, Functional Score High......................... 67.03
Step 2.2, Clinical Score Medium......................... 33.94
Step 2.2, Clinical Score High........................... 188.53
Step 2.2, Functional Score Medium....................... 0.31
Step 2.2, Functional Score High......................... 63.34
Step 3, Clinical Score Medium........................... 9.35
Step 3, Clinical Score High............................. 95.01
Step 3, Functional Score Medium......................... 56.44
Step 3, Functional Score High........................... 88.01
Step 4, Clinical Score Medium........................... 76.63
Step 4, Clinical Score High............................. 261.74
Step 4, Functional Score Medium......................... 22.89
Step 4, Functional Score High........................... 73.10
Step 2.1, 1st and 2nd Episodes, 14 to 19 Therapy Visits. 498.19
Step 2.2, 3rd+ Episodes, 14 to 19 Therapy Visits........ 515.73
Step 3, 3rd+ Episodes, 0-13 Therapy Visits.............. -73.96
Step 4, All Episodes, 20+ Therapy Visits................ 906.64
Intercept............................................... 393.43
------------------------------------------------------------------------
Source: CY 2015 Medicare claims data for episodes ending on or before
December 31, 2015 (as of December 31, 2015) for which we had a linked
OASIS assessment.
Step 4: We use the coefficients from the payment regression model
to predict each episode's wage-weighted minutes of care (resource use).
We then divide these predicted values by the mean of the dependent
variable (that is, the average wage-weighted minutes of care across all
episodes used in the payment regression). This division constructs the
weight for each episode, which is simply the ratio of the episode's
predicted wage-weighted minutes of care divided by the average wage-
weighted minutes of care in the sample. Each episode is then aggregated
into one of the 153 home health resource groups (HHRGs) and the ``raw''
weight for each HHRG was calculated as the average of the episode
weights within the HHRG.
Step 5: The raw weights associated with 0 to 5 therapy visits are
then
[[Page 43729]]
increased by 3.75 percent, the weights associated with 14-15 therapy
visits are decreased by 2.5 percent, and the weights associated with
20+ therapy visits are decreased by 5 percent. These adjustments to the
case-mix weights were finalized in the CY 2012 HH PPS final rule (76 FR
68557) and were done to address MedPAC's concerns that the HH PPS
overvalues therapy episodes and undervalues non-therapy episodes and to
better align the case-mix weights with episode costs estimated from
cost report data.\3\
---------------------------------------------------------------------------
\3\ Medicare Payment Advisory Commission (MedPAC), Report to the
Congress: Medicare Payment Policy. March 2011, P. 176.
---------------------------------------------------------------------------
Step 6: After the adjustments in step 5 are applied to the raw
weights, the weights are further adjusted to create an increase in the
payment weights for the therapy visit steps between the therapy
thresholds. Weights with the same clinical severity level, functional
severity level, and early/later episode status were grouped together.
Then within those groups, the weights for each therapy step between
thresholds are gradually increased. We do this by interpolating between
the main thresholds on the model (from 0-5 to 14-15 therapy visits, and
from 14-15 to 20+ therapy visits). We use a linear model to implement
the interpolation so the payment weight increase for each step between
the thresholds (such as the increase between 0-5 therapy visits and 6
therapy visits and the increase between 6 therapy visits and 7-9
therapy visits) are constant. This interpolation is identical to the
process finalized in the CY 2012 HH PPS final rule (76 FR 68555).
Step 7: The interpolated weights are then adjusted so that the
average case-mix for the weights is equal to 1.0000.\4\ This last step
creates the proposed CY 2017 case-mix weights shown in Table 9.
---------------------------------------------------------------------------
\4\ When computing the average, we compute a weighted average,
assigning a value of one to each normal episode and a value equal to
the episode length divided by 60 for PEPs.
Table 9--Proposed CY 2017 Case-Mix Payment Weights
----------------------------------------------------------------------------------------------------------------
Clinical and functional levels
Payment group Step (episode and/or (1 = low; 2 = medium; 3 = Proposed CY
therapy visit ranges) high) 2017 weights
----------------------------------------------------------------------------------------------------------------
10111............................ 1st and 2nd Episodes, 0 to 5 C1F1S1 0.5972
Therapy Visits.
10112............................ 1st and 2nd Episodes, 6 C1F1S2 0.7322
Therapy Visits.
10113............................ 1st and 2nd Episodes, 7 to 9 C1F1S3 0.8671
Therapy Visits.
10114............................ 1st and 2nd Episodes, 10 C1F1S4 1.0021
Therapy Visits.
10115............................ 1st and 2nd Episodes, 11 to C1F1S5 1.1370
13 Therapy Visits.
10121............................ 1st and 2nd Episodes, 0 to 5 C1F2S1 0.7059
Therapy Visits.
10122............................ 1st and 2nd Episodes, 6 C1F2S2 0.8224
Therapy Visits.
10123............................ 1st and 2nd Episodes, 7 to 9 C1F2S3 0.9389
Therapy Visits.
10124............................ 1st and 2nd Episodes, 10 C1F2S4 1.0554
Therapy Visits.
10125............................ 1st and 2nd Episodes, 11 to C1F2S5 1.1719
13 Therapy Visits.
10131............................ 1st and 2nd Episodes, 0 to 5 C1F3S1 0.7624
Therapy Visits.
10132............................ 1st and 2nd Episodes, 6 C1F3S2 0.8835
Therapy Visits.
10133............................ 1st and 2nd Episodes, 7 to 9 C1F3S3 1.0045
Therapy Visits.
10134............................ 1st and 2nd Episodes, 10 C1F3S4 1.1255
Therapy Visits.
10135............................ 1st and 2nd Episodes, 11 to C1F3S5 1.2466
13 Therapy Visits.
10211............................ 1st and 2nd Episodes, 0 to 5 C2F1S1 0.6363
Therapy Visits.
10212............................ 1st and 2nd Episodes, 6 C2F1S2 0.7787
Therapy Visits.
10213............................ 1st and 2nd Episodes, 7 to 9 C2F1S3 0.9210
Therapy Visits.
10214............................ 1st and 2nd Episodes, 10 C2F1S4 1.0634
Therapy Visits.
10215............................ 1st and 2nd Episodes, 11 to C2F1S5 1.2057
13 Therapy Visits.
10221............................ 1st and 2nd Episodes, 0 to 5 C2F2S1 0.7450
Therapy Visits.
10222............................ 1st and 2nd Episodes, 6 C2F2S2 0.8689
Therapy Visits.
10223............................ 1st and 2nd Episodes, 7 to 9 C2F2S3 0.9928
Therapy Visits.
10224............................ 1st and 2nd Episodes, 10 C2F2S4 1.1167
Therapy Visits.
10225............................ 1st and 2nd Episodes, 11 to C2F2S5 1.2406
13 Therapy Visits.
10231............................ 1st and 2nd Episodes, 0 to 5 C2F3S1 0.8015
Therapy Visits.
10232............................ 1st and 2nd Episodes, 6 C2F3S2 0.9300
Therapy Visits.
10233............................ 1st and 2nd Episodes, 7 to 9 C2F3S3 1.0584
Therapy Visits.
10234............................ 1st and 2nd Episodes, 10 C2F3S4 1.1868
Therapy Visits.
10235............................ 1st and 2nd Episodes, 11 to C2F3S5 1.3153
13 Therapy Visits.
10311............................ 1st and 2nd Episodes, 0 to 5 C3F1S1 0.6896
Therapy Visits.
10312............................ 1st and 2nd Episodes, 6 C3F1S2 0.8431
Therapy Visits.
10313............................ 1st and 2nd Episodes, 7 to 9 C3F1S3 0.9967
Therapy Visits.
10314............................ 1st and 2nd Episodes, 10 C3F1S4 1.1502
Therapy Visits.
10315............................ 1st and 2nd Episodes, 11 to C3F1S5 1.3038
13 Therapy Visits.
10321............................ 1st and 2nd Episodes, 0 to 5 C3F2S1 0.7983
Therapy Visits.
10322............................ 1st and 2nd Episodes, 6 C3F2S2 0.9334
Therapy Visits.
10323............................ 1st and 2nd Episodes, 7 to 9 C3F2S3 1.0685
Therapy Visits.
10324............................ 1st and 2nd Episodes, 10 C3F2S4 1.2036
Therapy Visits.
10325............................ 1st and 2nd Episodes, 11 to C3F2S5 1.3387
13 Therapy Visits.
10331............................ 1st and 2nd Episodes, 0 to 5 C3F3S1 0.8548
Therapy Visits.
10332............................ 1st and 2nd Episodes, 6 C3F3S2 0.9944
Therapy Visits.
10333............................ 1st and 2nd Episodes, 7 to 9 C3F3S3 1.1341
Therapy Visits.
10334............................ 1st and 2nd Episodes, 10 C3F3S4 1.2737
Therapy Visits.
10335............................ 1st and 2nd Episodes, 11 to C3F3S5 1.4133
13 Therapy Visits.
[[Page 43730]]
21111............................ 1st and 2nd Episodes, 14 to C1F1S1 1.2720
15 Therapy Visits.
21112............................ 1st and 2nd Episodes, 16 to C1F1S2 1.4503
17 Therapy Visits.
21113............................ 1st and 2nd Episodes, 18 to C1F1S3 1.6287
19 Therapy Visits.
21121............................ 1st and 2nd Episodes, 14 to C1F2S1 1.2884
15 Therapy Visits.
21122............................ 1st and 2nd Episodes, 16 to C1F2S2 1.4719
17 Therapy Visits.
21123............................ 1st and 2nd Episodes, 18 to C1F2S3 1.6554
19 Therapy Visits.
21131............................ 1st and 2nd Episodes, 14 to C1F3S1 1.3676
15 Therapy Visits.
21132............................ 1st and 2nd Episodes, 16 to C1F3S2 1.5480
17 Therapy Visits.
21133............................ 1st and 2nd Episodes, 18 to C1F3S3 1.7283
19 Therapy Visits.
21211............................ 1st and 2nd Episodes, 14 to C2F1S1 1.3481
15 Therapy Visits.
21212............................ 1st and 2nd Episodes, 16 to C2F1S2 1.5366
17 Therapy Visits.
21213............................ 1st and 2nd Episodes, 18 to C2F1S3 1.7251
19 Therapy Visits.
21221............................ 1st and 2nd Episodes, 14 to C2F2S1 1.3645
15 Therapy Visits.
21222............................ 1st and 2nd Episodes, 16 to C2F2S2 1.5582
17 Therapy Visits.
21223............................ 1st and 2nd Episodes, 18 to C2F2S3 1.7518
19 Therapy Visits.
21231............................ 1st and 2nd Episodes, 14 to C2F3S1 1.4437
15 Therapy Visits.
21232............................ 1st and 2nd Episodes, 16 to C2F3S2 1.6342
17 Therapy Visits.
21233............................ 1st and 2nd Episodes, 18 to C2F3S3 1.8247
19 Therapy Visits.
21311............................ 1st and 2nd Episodes, 14 to C3F1S1 1.4573
15 Therapy Visits.
21312............................ 1st and 2nd Episodes, 16 to C3F1S2 1.6952
17 Therapy Visits.
21313............................ 1st and 2nd Episodes, 18 to C3F1S3 1.9330
19 Therapy Visits.
21321............................ 1st and 2nd Episodes, 14 to C3F2S1 1.4738
15 Therapy Visits.
21322............................ 1st and 2nd Episodes, 16 to C3F2S2 1.7168
17 Therapy Visits.
21323............................ 1st and 2nd Episodes, 18 to C3F2S3 1.9597
19 Therapy Visits.
21331............................ 1st and 2nd Episodes, 14 to C3F3S1 1.5530
15 Therapy Visits.
21332............................ 1st and 2nd Episodes, 16 to C3F3S2 1.7928
17 Therapy Visits.
21333............................ 1st and 2nd Episodes, 18 to C3F3S3 2.0326
19 Therapy Visits.
22111............................ 3rd+ Episodes, 14 to 15 C1F1S1 1.2970
Therapy Visits.
22112............................ 3rd+ Episodes, 16 to 17 C1F1S2 1.4670
Therapy Visits.
22113............................ 3rd+ Episodes, 18 to 19 C1F1S3 1.6370
Therapy Visits.
22121............................ 3rd+ Episodes, 14 to 15 C1F2S1 1.2974
Therapy Visits.
22122............................ 3rd+ Episodes, 16 to 17 C1F2S2 1.4779
Therapy Visits.
22123............................ 3rd+ Episodes, 18 to 19 C1F2S3 1.6584
Therapy Visits.
22131............................ 3rd+ Episodes, 14 to 15 C1F3S1 1.3873
Therapy Visits.
22132............................ 3rd+ Episodes, 16 to 17 C1F3S2 1.5611
Therapy Visits.
22133............................ 3rd+ Episodes, 18 to 19 C1F3S3 1.7349
Therapy Visits.
22211............................ 3rd+ Episodes, 14 to 15 C2F1S1 1.3454
Therapy Visits.
22212............................ 3rd+ Episodes, 16 to 17 C2F1S2 1.5348
Therapy Visits.
22213............................ 3rd+ Episodes, 18 to 19 C2F1S3 1.7242
Therapy Visits.
22221............................ 3rd+ Episodes, 14 to 15 C2F2S1 1.3458
Therapy Visits.
22222............................ 3rd+ Episodes, 16 to 17 C2F2S2 1.5457
Therapy Visits.
22223............................ 3rd+ Episodes, 18 to 19 C2F2S3 1.7455
Therapy Visits.
22231............................ 3rd+ Episodes, 14 to 15 C2F3S1 1.4358
Therapy Visits.
22232............................ 3rd+ Episodes, 16 to 17 C2F3S2 1.6289
Therapy Visits.
22233............................ 3rd+ Episodes, 18 to 19 C2F3S3 1.8220
Therapy Visits.
22311............................ 3rd+ Episodes, 14 to 15 C3F1S1 1.5659
Therapy Visits.
22312............................ 3rd+ Episodes, 16 to 17 C3F1S2 1.7676
Therapy Visits.
22313............................ 3rd+ Episodes, 18 to 19 C3F1S3 1.9692
Therapy Visits.
22321............................ 3rd+ Episodes, 14 to 15 C3F2S1 1.5664
Therapy Visits.
22322............................ 3rd+ Episodes, 16 to 17 C3F2S2 1.7785
Therapy Visits.
22323............................ 3rd+ Episodes, 18 to 19 C3F2S3 1.9906
Therapy Visits.
22331............................ 3rd+ Episodes, 14 to 15 C3F3S1 1.6563
Therapy Visits.
22332............................ 3rd+ Episodes, 16 to 17 C3F3S2 1.8617
Therapy Visits.
22333............................ 3rd+ Episodes, 18 to 19 C3F3S3 2.0671
Therapy Visits.
30111............................ 3rd+ Episodes, 0 to 5 C1F1S1 0.4850
Therapy Visits.
30112............................ 3rd+ Episodes, 6 Therapy C1F1S2 0.6474
Visits.
30113............................ 3rd+ Episodes, 7 to 9 C1F1S3 0.8098
Therapy Visits.
30114............................ 3rd+ Episodes, 10 Therapy C1F1S4 0.9722
Visits.
30115............................ 3rd+ Episodes, 11 to 13 C1F1S5 1.1346
Therapy Visits.
30121............................ 3rd+ Episodes, 0 to 5 C1F2S1 0.5706
Therapy Visits.
30122............................ 3rd+ Episodes, 6 Therapy C1F2S2 0.7160
Visits.
30123............................ 3rd+ Episodes, 7 to 9 C1F2S3 0.8614
Therapy Visits.
30124............................ 3rd+ Episodes, 10 Therapy C1F2S4 1.0067
Visits.
30125............................ 3rd+ Episodes, 11 to 13 C1F2S5 1.1521
Therapy Visits.
30131............................ 3rd+ Episodes, 0 to 5 C1F3S1 0.6186
Therapy Visits.
30132............................ 3rd+ Episodes, 6 Therapy C1F3S2 0.7723
Visits.
30133............................ 3rd+ Episodes, 7 to 9 C1F3S3 0.9261
Therapy Visits.
30134............................ 3rd+ Episodes, 10 Therapy C1F3S4 1.0798
Visits.
[[Page 43731]]
30135............................ 3rd+ Episodes, 11 to 13 C1F3S5 1.2336
Therapy Visits.
30211............................ 3rd+ Episodes, 0 to 5 C2F1S1 0.4992
Therapy Visits.
30212............................ 3rd+ Episodes, 6 Therapy C2F1S2 0.6684
Visits.
30213............................ 3rd+ Episodes, 7 to 9 C2F1S3 0.8377
Therapy Visits.
30214............................ 3rd+ Episodes, 10 Therapy C2F1S4 1.0069
Visits.
30215............................ 3rd+ Episodes, 11 to 13 C2F1S5 1.1761
Therapy Visits.
30221............................ 3rd+ Episodes, 0 to 5 C2F2S1 0.5848
Therapy Visits.
30222............................ 3rd+ Episodes, 6 Therapy C2F2S2 0.7370
Visits.
30223............................ 3rd+ Episodes, 7 to 9 C2F2S3 0.8892
Therapy Visits.
30224............................ 3rd+ Episodes, 10 Therapy C2F2S4 1.0414
Visits.
30225............................ 3rd+ Episodes, 11 to 13 C2F2S5 1.1936
Therapy Visits.
30231............................ 3rd+ Episodes, 0 to 5 C2F3S1 0.6328
Therapy Visits.
30232............................ 3rd+ Episodes, 6 Therapy C2F3S2 0.7934
Visits.
30233............................ 3rd+ Episodes, 7 to 9 C2F3S3 0.9540
Therapy Visits.
30234............................ 3rd+ Episodes, 10 Therapy C2F3S4 1.1146
Visits.
30235............................ 3rd+ Episodes, 11 to 13 C2F3S5 1.2752
Therapy Visits.
30311............................ 3rd+ Episodes, 0 to 5 C3F1S1 0.6292
Therapy Visits.
30312............................ 3rd+ Episodes, 6 Therapy C3F1S2 0.8165
Visits.
30313............................ 3rd+ Episodes, 7 to 9 C3F1S3 1.0039
Therapy Visits.
30314............................ 3rd+ Episodes, 10 Therapy C3F1S4 1.1912
Visits.
30315............................ 3rd+ Episodes, 11 to 13 C3F1S5 1.3786
Therapy Visits.
30321............................ 3rd+ Episodes, 0 to 5 C3F2S1 0.7149
Therapy Visits.
30322............................ 3rd+ Episodes, 6 Therapy C3F2S2 0.8852
Visits.
30323............................ 3rd+ Episodes, 7 to 9 C3F2S3 1.0555
Therapy Visits.
30324............................ 3rd+ Episodes, 10 Therapy C3F2S4 1.2258
Visits.
30325............................ 3rd+ Episodes, 11 to 13 C3F2S5 1.3961
Therapy Visits.
30331............................ 3rd+ Episodes, 0 to 5 C3F3S1 0.7628
Therapy Visits.
30332............................ 3rd+ Episodes, 6 Therapy C3F3S2 0.9415
Visits.
30333............................ 3rd+ Episodes, 7 to 9 C3F3S3 1.1202
Therapy Visits.
30334............................ 3rd+ Episodes, 10 Therapy C3F3S4 1.2989
Visits.
30335............................ 3rd+ Episodes, 11 to 13 C3F3S5 1.4776
Therapy Visits.
40111............................ All Episodes, 20+ Therapy C1F1S1 1.8071
Visits.
40121............................ All Episodes, 20+ Therapy C1F2S1 1.8389
Visits.
40131............................ All Episodes, 20+ Therapy C1F3S1 1.9087
Visits.
40211............................ All Episodes, 20+ Therapy C2F1S1 1.9136
Visits.
40221............................ All Episodes, 20+ Therapy C2F2S1 1.9454
Visits.
40231............................ All Episodes, 20+ Therapy C2F3S1 2.0152
Visits.
40311............................ All Episodes, 20+ Therapy C3F1S1 2.1709
Visits.
40321............................ All Episodes, 20+ Therapy C3F2S1 2.2027
Visits.
40331............................ All Episodes, 20+ Therapy C3F3S1 2.2725
Visits.
----------------------------------------------------------------------------------------------------------------
To ensure the changes to the HH PPS case-mix weights are
implemented in a budget neutral manner, we then apply a case-mix budget
neutrality factor to the proposed CY 2017 national, standardized 60-day
episode payment rate (see section III.C.3. of this proposed rule). The
case-mix budget neutrality factor is calculated as the ratio of total
payments when the CY 2017 HH PPS case-mix weights (developed using CY
2015 home health claims data) are applied to CY 2015 utilization
(claims) data to total payments when CY 2016 HH PPS case-mix weights
(developed using CY 2014 home health claims data) are applied to CY
2015 utilization data. This produces a case-mix budget neutrality
factor for CY 2017 of 1.0062, based on CY 2015 claims data as of
December 31, 2015.
C. Proposed CY 2017 Home Health Payment Rate Update
1. Proposed CY 2017 Home Health Market Basket Update
Section 1895(b)(3)(B) of the Act requires that the standard
prospective payment amounts for CY 2017 be increased by a factor equal
to the applicable HH market basket update for those HHAs that submit
quality data as required by the Secretary. The home health market
basket was rebased and revised in CY 2013. A detailed description of
how we derive the HHA market basket is available in the CY 2013 HH PPS
final rule (77 FR 67080-67090).
Section 3401(e) of the Affordable Care Act, adding new section
1895(b)(3)(B)(vi) to the Act, requires that, in CY 2015 (and in
subsequent calendar years), the market basket percentage under the HHA
prospective payment system as described in section 1895(b)(3)(B) of the
Act be annually adjusted by changes in economy-wide productivity. The
statute defines the productivity adjustment, described in section
1886(b)(3)(B)(xi)(II) of the Act, to be equal to the 10-year moving
average of change in annual economy-wide private nonfarm business
multifactor productivity (MFP) (as projected by the Secretary for the
10-year period ending with the applicable fiscal year, calendar year,
cost reporting period, or other annual period) (the ``MFP
adjustment''). The Bureau of Labor Statistics (BLS) is the agency that
publishes the official measure of private nonfarm business MFP. Please
see https://www.bls.gov/mfp to obtain the BLS historical published MFP
data.
[[Page 43732]]
Using IHS Global Insight's (IGI) first quarter 2016 forecast, the
MFP adjustment for CY 2017 (the 10-year moving average of MFP for the
period ending CY 2017) is projected to be 0.5 percent. Thus, in
accordance with section 1895(b)(3)(B)(iii) of the Act, we propose to
base the CY 2017 market basket update, which is used to determine the
applicable percentage increase for the HH payments, on the most recent
estimate of the proposed 2010-based HH market basket (currently
estimated to be 2.8 percent based on IGI's first quarter 2016
forecast). We propose to then reduce this percentage increase by the
current estimate of the MFP adjustment for CY 2017 of 0.5 percentage
point (the 10-year moving average of MFP for the period ending CY 2017
based on IGI's first quarter 2016 forecast), in accordance with
1895(b)(3)(B)(vi). Therefore, the current estimate of the CY 2017 HH
payment update is 2.3 percent (2.8 percent market basket update, less
0.5 percentage point MFP adjustment). Furthermore, we note that if more
recent data are subsequently available (for example, a more recent
estimate of the market basket and MFP adjustment), we would use such
data to determine the CY 2017 market basket update and MFP adjustment
in the final rule.
Section 1895(b)(3)(B) of the Act requires that the home health
update be decreased by 2 percentage points for those HHAs that do not
submit quality data as required by the Secretary. For HHAs that do not
submit the required quality data for CY 2017, the home health payment
update would be 0.3 percent (2.3 percent minus 2 percentage points).
2. Proposed CY 2017 Home Health Wage Index
a. Background
Sections 1895(b)(4)(A)(ii) and (b)(4)(C) of the Act require the
Secretary to provide appropriate adjustments to the proportion of the
payment amount under the HH PPS that account for area wage differences,
using adjustment factors that reflect the relative level of wages and
wage-related costs applicable to the furnishing of HH services. Since
the inception of the HH PPS, we have used inpatient hospital wage data
in developing a wage index to be applied to HH payments. We propose to
continue this practice for CY 2017, as we continue to believe that, in
the absence of HH-specific wage data, using inpatient hospital wage
data is appropriate and reasonable for the HH PPS. Specifically, we
propose to continue to use the pre-floor, pre-reclassified hospital
wage index as the wage adjustment to the labor portion of the HH PPS
rates. For CY 2017, the updated wage data are for hospital cost
reporting periods beginning on or after October 1, 2012 and before
October 1, 2013 (FY 2013 cost report data). We would apply the
appropriate wage index value to the labor portion of the HH PPS rates
based on the site of service for the beneficiary (defined by section
1861(m) of the Act as the beneficiary's place of residence).
b. Updates
Previously, we determined each HHA's labor market area based on
definitions of metropolitan statistical areas (MSAs) issued by the
Office of Management and Budget (OMB). In the CY 2006 HH PPS final rule
(70 FR 68132), we adopted revised labor market area definitions as
discussed in the OMB Bulletin No. 03-04 (June 6, 2003). This bulletin
announced revised definitions for MSAs and the creation of micropolitan
statistical areas and core-based statistical areas (CBSAs). The
bulletin is available online at www.whitehouse.gov/omb/bulletins/b03-04.html.
On February 28, 2013, OMB issued Bulletin No. 13-01, announcing
revisions to the delineations of MSAs, Micropolitan Statistical Areas,
and CBSAs, and guidance on uses of the delineation of these areas. This
bulletin is available online at https://www.whitehouse.gov/sites/default/files/omb/bulletins/2013/b-13-01.pdf. This bulletin states that
it ``provides the delineations of all Metropolitan Statistical Areas,
Metropolitan Divisions, Micropolitan Statistical Areas, Combined
Statistical Areas, and New England City and Town Areas in the United
States and Puerto Rico based on the standards published on June 28,
2010, in the Federal Register (75 FR 37246-37252) and Census Bureau
data.''
While the revisions OMB published on February 28, 2013 are not as
sweeping as the changes made when we adopted the CBSA geographic
designations for CY 2006, the February 28, 2013 bulletin does contain a
number of significant changes. For example, there are new CBSAs, urban
counties that have become rural, rural counties that have become urban,
and existing CBSAs that have been split apart.
In the CY 2015 HH PPS final rule (79 FR 66085 through 66087), we
finalized changes to the HH PPS wage index based on the OMB
delineations, as described in OMB Bulletin No. 13-01. In CY 2015, we
included a one-year transition to those delineations by using a blended
wage index for CY 2015.
The OMB's most recent update to the geographic area delineations
was published on July 15, 2015 in OBM bulletin 15-01. This bulletin is
available online at https://www.whitehouse.gov/sites/default/files/omb/bulletins/2015/15-01.pdf. The revisions to the delineations that affect
the HH PPS are changes to CBSA titles and the addition of CBSA 21420,
Enid, Oklahoma. CBSA 21420 encompasses Garfield County, Oklahoma.
In order to address those geographic areas in which there are no
inpatient hospitals, and thus, no hospital wage data on which to base
the calculation of the CY 2017 HH PPS wage index, we propose to
continue to use the same methodology discussed in the CY 2007 HH PPS
final rule (71 FR 65884) to address those geographic areas in which
there are no inpatient hospitals. For rural areas that do not have
inpatient hospitals, we would use the average wage index from all
contiguous CBSAs as a reasonable proxy. For FY 2017, there are no rural
geographic areas without hospitals for which we would apply this
policy. For rural Puerto Rico, we would not apply this methodology due
to the distinct economic circumstances that exist there (for example,
due to the close proximity to one another of almost all of Puerto
Rico's various urban and non-urban areas, this methodology would
produce a wage index for rural Puerto Rico that is higher than that in
half of its urban areas). Instead, we would continue to use the most
recent wage index previously available for that area. For urban areas
without inpatient hospitals, we would use the average wage index of all
urban areas within the state as a reasonable proxy for the wage index
for that CBSA. For CY 2017, the only urban area without inpatient
hospital wage data is Hinesville, GA (CBSA 25980).
The proposed CY 2017 wage index is available on the CMS Web site at
https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/HomeHealthPPS/Home-Health-Prospective-Payment-System-Regulations-and-Notices.html
3. Proposed CY 2017 Annual Payment Update
a. Background
The Medicare HH PPS has been in effect since October 1, 2000. As
set forth in the July 3, 2000 final rule (65 FR 41128), the base unit
of payment under the Medicare HH PPS is a national, standardized 60-day
episode payment rate. As set forth in 42 CFR 484.220, we adjust the
national, standardized 60-day episode payment rate by a case-mix
[[Page 43733]]
relative weight and a wage index value based on the site of service for
the beneficiary.
To provide appropriate adjustments to the proportion of the payment
amount under the HH PPS to account for area wage differences, we apply
the appropriate wage index value to the labor portion of the HH PPS
rates. The labor-related share of the case-mix adjusted 60-day episode
rate would continue to be 78.535 percent and the non-labor-related
share would continue to be 21.465 percent as set out in the CY 2013 HH
PPS final rule (77 FR 67068). The CY 2017 HH PPS rates would use the
same case-mix methodology as set forth in the CY 2008 HH PPS final rule
with comment period (72 FR 49762) and would be adjusted as described in
section III.C. of this rule. The following are the steps we take to
compute the case-mix and wage-adjusted 60-day episode rate:
(1) Multiply the national 60-day episode rate by the patient's
applicable case-mix weight.
(2) Divide the case-mix adjusted amount into a labor (78.535
percent) and a non-labor portion (21.465 percent).
(3) Multiply the labor portion by the applicable wage index based
on the site of service of the beneficiary.
(4) Add the wage-adjusted portion to the non-labor portion,
yielding the case-mix and wage adjusted 60-day episode rate, subject to
any additional applicable adjustments.
In accordance with section 1895(b)(3)(B) of the Act, this document
constitutes the annual update of the HH PPS rates. Section 484.225 sets
forth the specific annual percentage update methodology. In accordance
with Sec. 484.225(i), for a HHA that does not submit HH quality data,
as specified by the Secretary, the unadjusted national prospective 60-
day episode rate is equal to the rate for the previous calendar year
increased by the applicable HH market basket index amount minus two
percentage points. Any reduction of the percentage change would apply
only to the calendar year involved and would not be considered in
computing the prospective payment amount for a subsequent calendar
year.
Medicare pays the national, standardized 60-day case-mix and wage-
adjusted episode payment on a split percentage payment approach. The
split percentage payment approach includes an initial percentage
payment and a final percentage payment as set forth in Sec.
484.205(b)(1) and (b)(2). We may base the initial percentage payment on
the submission of a request for anticipated payment (RAP) and the final
percentage payment on the submission of the claim for the episode, as
discussed in Sec. 409.43. The claim for the episode that the HHA
submits for the final percentage payment determines the total payment
amount for the episode and whether we make an applicable adjustment to
the 60-day case-mix and wage-adjusted episode payment. The end date of
the 60-day episode as reported on the claim determines which calendar
year rates Medicare would use to pay the claim.
We may also adjust the 60-day case-mix and wage-adjusted episode
payment based on the information submitted on the claim to reflect the
following:
A low-utilization payment adjustment (LUPA) is provided on
a per-visit basis as set forth in Sec. 484.205(c) and Sec. 484.230.
A partial episode payment (PEP) adjustment as set forth in
Sec. 484.205(d) and Sec. 484.235.
An outlier payment as set forth in Sec. 484.205(e) and
Sec. 484.240.
b. Proposed CY 2017 National, Standardized 60-Day Episode Payment Rate
Section 1895(3)(A)(i) of the Act required that the 60-day episode
base rate and other applicable amounts be standardized in a manner that
eliminates the effects of variations in relative case mix and area wage
adjustments among different home health agencies in a budget neutral
manner. To determine the CY 2017 national, standardized 60-day episode
payment rate, we would apply a wage index standardization factor, a
case-mix budget neutrality factor described in section III.B, a
reduction of 0.97 percent to account for nominal case-mix growth from
2012 to 2014 as finalized in the CY 2016 HH PPS final rule (80 FR
68646), the rebasing adjustment described in section II.C, and the MFP-
adjusted home health market basket update discussed in section III.C.1
of this proposed rule.
To calculate the wage index standardization factor, henceforth
referred to as the wage index budget neutrality factor, we simulated
total payments for non-LUPA episodes using the proposed CY 2017 wage
index and compared it to our simulation of total payments for non-LUPA
episodes using the CY 2016 wage index. By dividing the total payments
for non-LUPA episodes using the proposed CY 2017 wage index by the
total payments for non-LUPA episodes using the CY 2016 wage index, we
obtain a wage index budget neutrality factor of 0.9990. We would apply
the wage index budget neutrality factor of 0.9990 to the proposed CY
2017 national, standardized 60-day episode rate.
As discussed in section III.B of this proposed rule, to ensure the
changes to the case-mix weights are implemented in a budget neutral
manner, we would apply a case-mix weight budget neutrality factor to
the CY 2017 national, standardized 60-day episode payment rate. The
case-mix weight budget neutrality factor is calculated as the ratio of
total payments when CY 2017 case-mix weights are applied to CY 2015
utilization (claims) data to total payments when CY 2016 case-mix
weights are applied to CY 2015 utilization data. The case-mix budget
neutrality factor for CY 2017 would be 1.0062 as described in section
III.B.1 of this proposed rule.
Next, as discussed in the CY 2016 HH PPS final rule (80 FR 68646),
we would apply a reduction of 0.97 percent to the national,
standardized 60-day episode payment rate in CY 2017 to account for
nominal case-mix growth between CY 2012 and CY 2014. Then, we would
apply the -$80.95 rebasing adjustment finalized in the CY 2014 HH PPS
final rule (78 FR 72256), and discussed in section II.C. Lastly, we
would update the proposed payment rates by the proposed CY 2017 HH
payment update percentage of 2.3 percent (MFP-adjusted home health
market basket update) as described in section III.C.1 of this proposed
rule. The proposed CY 2017 national, standardized 60-day episode
payment rate is calculated in Table 10.
[[Page 43734]]
Table 10--Proposed CY 2017 60-Day National, Standardized 60-Day Episode Payment Amount
--------------------------------------------------------------------------------------------------------------------------------------------------------
Proposed CY
Wage index Case-mix Nominal case- CY 2017 Proposed CY 2017 national,
CY 2016 National, standardized 60-day episode budget weights budget mix growth Rebasing 2017 HH standardized 60-
payment neutrality neutrality adjustment (1- adjustment payment update day episode
factor factor 0.0097) payment
--------------------------------------------------------------------------------------------------------------------------------------------------------
$2,965.12......................................... x 0.9990 x 1.0062 x 0.9903 -$80.95 1.023 $2,936.68
--------------------------------------------------------------------------------------------------------------------------------------------------------
The proposed CY 2017 national, standardized 60-day episode payment
rate for an HHA that does not submit the required quality data is
updated by the proposed CY 2017 HH payment update (2.3 percent) minus 2
percentage points and is shown in Table 11.
Table 11--Proposed CY 2017 National, Standardized 60-Day Episode Payment Amount for HHAs That DO NOT Submit the Quality Data
--------------------------------------------------------------------------------------------------------------------------------------------------------
Proposed CY
Wage index Case-mix Nominal case- 2017 HH Proposed CY
CY 2016 National, standardized 60-day episode budget weights budget mix growth CY 2017 payment update 2017 national,
payment neutrality neutrality adjustment (1- Rebasing minus 2 standardized 60-
factor factor 0.0097) adjustment percentage day episode
points payment
--------------------------------------------------------------------------------------------------------------------------------------------------------
$2,965.12......................................... x 0.9990 x 1.0062 x 0.9903 -$80.95 x 1.003 $2,879.27
--------------------------------------------------------------------------------------------------------------------------------------------------------
c. Proposed CY 2017 National Per-Visit Rates
The national per-visit rates are used to pay LUPAs (episodes with
four or fewer visits) and are also used to compute imputed costs in
outlier calculations. The per-visit rates are paid by type of visit or
HH discipline. The six HH disciplines are as follows:
Home health aide (HH aide);
Medical Social Services (MSS);
Occupational therapy (OT);
Physical therapy (PT);
Skilled nursing (SN); and
Speech-language pathology (SLP).
To calculate the proposed CY 2017 national per-visit rates, we
start with the CY 2016 national per-visit rates. We then apply a wage
index budget neutrality factor to ensure budget neutrality for LUPA
per-visit payments and then we increase each of the six per-visit rates
by the maximum rebasing adjustments described in section II.C. of this
rule. We calculate the wage index budget neutrality factor by
simulating total payments for LUPA episodes using the proposed CY 2017
wage index and comparing it to simulated total payments for LUPA
episodes using the CY 2016 wage index. By dividing the total payments
for LUPA episodes using the proposed CY 2017 wage index by the total
payments for LUPA episodes using the CY 2016 wage index, we obtain a
wage index budget neutrality factor of 0.9998. We would apply the wage
index budget neutrality factor of 0.9998 in order to calculate the CY
2017 national per-visit rates.
The LUPA per-visit rates are not calculated using case-mix weights.
Therefore, there is no case-mix weights budget neutrality factor needed
to ensure budget neutrality for LUPA payments. Finally, the per-visit
rates for each discipline are updated by the proposed CY 2017 HH
payment update percentage of 2.3 percent. The national per-visit rates
are adjusted by the wage index based on the site of service of the
beneficiary. The per-visit payments for LUPAs are separate from the
LUPA add-on payment amount, which is paid for episodes that occur as
the only episode or initial episode in a sequence of adjacent episodes.
The proposed CY 2017 national per-visit rates are shown in Tables 12
and 13.
Table 12: Proposed CY 2017 National Per-Visit Payment Amounts for HHAs That DO Submit the Required Quality Data
----------------------------------------------------------------------------------------------------------------
Wage index
CY 2016 per- budget CY 2017 Proposed CY Proposed CY
HH Discipline type visit payment neutrality Rebasing 2017 HH 2017 per-visit
factor adjustment payment update payment
----------------------------------------------------------------------------------------------------------------
Home Health Aide............. $60.87 x 0.9998....... + $1.79........ x 1.023........ $64.09
Medical Social Services...... 215.47 x 0.9998....... + 6.34......... x 1.023........ 226.87
Occupational Therapy......... 147.95 x 0.9998....... + 4.35......... x 1.023........ 155.77
Physical Therapy............. 146.95 x 0.9998....... + 4.32......... x 1.023........ 154.72
Skilled Nursing.............. 134.42 x 0.9998....... + 3.96......... x 1.023........ 141.54
Speech Language Pathology.... 159.71 x 0.9998....... + 4.70......... x 1.023........ 168.16
----------------------------------------------------------------------------------------------------------------
The proposed CY 2017 per-visit payment rates for an HHA that does
not submit the required quality data are updated by the proposed CY
2017 HH payment update percentage (2.3 percent) minus 2 percentage
points and is shown in Table 13.
[[Page 43735]]
Table 13--Proposed CY 2017 National Per-Visit Payment Amounts for HHAs That DO NOT Submit the Required Quality
Data
----------------------------------------------------------------------------------------------------------------
Proposed CY
Wage index 2017 HH
CY 2016 per- budget CY 2017 payment update Proposed CY
HH Discipline type visit rates neutrality Rebasing minus 2 2017 per-visit
factor adjustment percentage rates
points
----------------------------------------------------------------------------------------------------------------
Home Health Aide................ $60.87 x 0.9998 + $1.79 x 1.003 $62.84
Medical Social Services......... 215.47 x 0.9998 + 6.34 x 1.003 222.43
Occupational Therapy............ 147.95 x 0.9998 + 4.35 x 1.003 152.73
Physical Therapy................ 146.95 x 0.9998 + 4.32 x 1.003 151.69
Skilled Nursing................. 134.42 x 0.9998 + 3.96 x 1.003 138.77
Speech Language Pathology....... 159.71 x 0.9998 + 4.70 x 1.003 164.87
----------------------------------------------------------------------------------------------------------------
d. Low-Utilization Payment Adjustment (LUPA) Add-On Factors
LUPA episodes that occur as the only episode or as an initial
episode in a sequence of adjacent episodes are adjusted by applying an
additional amount to the LUPA payment before adjusting for area wage
differences. In the CY 2014 HH PPS final rule, we changed the
methodology for calculating the LUPA add-on amount by finalizing the
use of three LUPA add-on factors: 1.8451 for SN; 1.6700 for PT; and
1.6266 for SLP (78 FR 72306). We multiply the per-visit payment amount
for the first SN, PT, or SLP visit in LUPA episodes that occur as the
only episode or an initial episode in a sequence of adjacent episodes
by the appropriate factor to determine the LUPA add-on payment amount.
For example, for LUPA episodes that occur as the only episode or an
initial episode in a sequence of adjacent episodes, if the first
skilled visit is SN, the payment for that visit would be $261.16
(1.8451 multiplied by $141.54), subject to area wage adjustment.
e. Proposed CY 2017 Non-routine Medical Supply (NRS) Payment Rates
Payments for NRS are computed by multiplying the relative weight
for a particular severity level by the NRS conversion factor. To
determine the proposed CY 2017 NRS conversion factor, we start with the
CY 2016 NRS conversion factor ($52.71) and apply the -2.82 percent
rebasing adjustment described in section II.C. of this rule (1--0.0282
= 0.9718). We then update the conversion factor by the proposed CY 2017
HH payment update percentage (2.3 percent). We do not apply a
standardization factor as the NRS payment amount calculated from the
conversion factor is not wage or case-mix adjusted when the final claim
payment amount is computed. The proposed NRS conversion factor for CY
2017 is shown in Table 14.
Table 14--Proposed CY 2017 NRS Conversion Factor for HHAs That DO Submit the Required Quality Data
----------------------------------------------------------------------------------------------------------------
Proposed CY
CY 2017 Proposed CY 2017 NRS
CY 2016 NRS conversion factor Rebasing 2017 HH conversion
adjustment payment update factor
----------------------------------------------------------------------------------------------------------------
$52.71....................................................... x 0.9718 x 1.023 $52.40
----------------------------------------------------------------------------------------------------------------
Using the CY 2015 NRS conversion factor, the payment amounts for
the six severity levels are shown in Table 15.
Table 15--Proposed CY 2017 NRS Payment Amounts for HHAs That DO Submit the Required Quality Data
----------------------------------------------------------------------------------------------------------------
Proposed CY
Relative 2017 NRS
Severity level Points (scoring) weight payment
amounts
----------------------------------------------------------------------------------------------------------------
1........................................... 0................................. 0.2698 $14.14
2........................................... 1 to 14........................... 0.9742 51.05
3........................................... 15 to 27.......................... 2.6712 139.97
4........................................... 28 to 48.......................... 3.9686 207.95
5........................................... 49 to 98.......................... 6.1198 320.68
6........................................... 99+............................... 10.5254 551.53
----------------------------------------------------------------------------------------------------------------
For HHAs that do not submit the required quality data, we begin
with the CY 2016 NRS conversion factor ($52.71) and apply the -2.82
percent rebasing adjustment discussed in section II.C of this proposed
rule (1-0.0282 = 0.9718). We then update the NRS conversion factor by
the proposed CY 2017 HH payment update percentage (2.3 percent) minus 2
percentage points. The proposed CY 2017 NRS conversion factor for HHAs
that do not submit quality data is shown in Table 16.
[[Page 43736]]
Table 16--Proposed CY 2017 NRS Conversion Factor for HHAs That DO NOT Submit the Required Quality Data
----------------------------------------------------------------------------------------------------------------
Proposed CY
2017 HH payment
CY 2017 update Proposed CY
CY 2015 NRS Conversion factor Rebasing percentage 2017 NRS
adjustment minus 2 conversion
percentage factor
Points
----------------------------------------------------------------------------------------------------------------
$52.71....................................................... x 0.9718 x 1.003 $51.38
----------------------------------------------------------------------------------------------------------------
The payment amounts for the various severity levels based on the
updated conversion factor for HHAs that do not submit quality data are
calculated in Table 17.
Table 17--Proposed CY 2017 NRS Payment Amounts for HHAs That DO NOT Submit the Required Quality Data
----------------------------------------------------------------------------------------------------------------
Proposed CY
Relative 2017 NRS
Severity level Points (scoring) weight payment
amounts
----------------------------------------------------------------------------------------------------------------
1........................................... 0................................. 0.2698 $13.86
2........................................... 1 to 14........................... 0.9742 50.05
3........................................... 15 to 27.......................... 2.6712 137.25
4........................................... 28 to 48.......................... 3.9686 203.91
5........................................... 49 to 98.......................... 6.1198 314.44
6........................................... 99+............................... 10.5254 540.80
----------------------------------------------------------------------------------------------------------------
f. Rural Add-On
Section 421(a) of the MMA required, for HH services furnished in a
rural areas (as defined in section 1886(d)(2)(D) of the Act), for
episodes or visits ending on or after April 1, 2004, and before April
1, 2005, that the Secretary increase the payment amount that otherwise
would have been made under section 1895 of the Act for the services by
5 percent.
Section 5201 of the DRA amended section 421(a) of the MMA. The
amended section 421(a) of the MMA required, for HH services furnished
in a rural area (as defined in section 1886(d)(2)(D) of the Act), on or
after January 1, 2006 and before January 1, 2007, that the Secretary
increase the payment amount otherwise made under section 1895 of the
Act for those services by 5 percent.
Section 3131(c) of the Affordable Care Act amended section 421(a)
of the MMA to provide an increase of 3 percent of the payment amount
otherwise made under section 1895 of the Act for HH services furnished
in a rural area (as defined in section 1886(d)(2)(D) of the Act), for
episodes and visits ending on or after April 1, 2010, and before
January 1, 2016.
Section 210 of the Medicare Access and CHIP Reauthorization Act of
2015 (MACRA) (Public Law 114-10) amended section 421(a) of the MMA to
extend the rural add-on by providing an increase of 3 percent of the
payment amount otherwise made under section 1895 of the Act for HH
services provided in a rural area (as defined in section 1886(d)(2)(D)
of the Act), for episodes and visits ending before January 1, 2018.
Section 421 of the MMA, as amended, waives budget neutrality
related to this provision, as the statute specifically states that the
Secretary shall not reduce the standard prospective payment amount (or
amounts) under section 1895 of the Act applicable to HH services
furnished during a period to offset the increase in payments resulting
in the application of this section of the statute.
For CY 2017, home health payment rates for services provided to
beneficiaries in areas that are defined as rural under the OMB
delineations would be increased by 3 percent as mandated by section 210
of the MACRA. The 3 percent rural add-on is applied to the national,
standardized 60-day episode payment rate, national per visit rates, and
NRS conversion factor when HH services are provided in rural (non-CBSA)
areas. Refer to Tables 18 through 21 for these payment rates.
Table 18--Proposed CY 2017 Payment Amounts for 60-Day Episodes for Services Provided in a Rural Area
----------------------------------------------------------------------------------------------------------------
For HHAs that DO submit quality data For HHAs that DO NOT submit quality data
----------------------------------------------------------------------------------------------------------------
Proposed CY Proposed CY
2017 rural Proposed CY 2017 rural
Proposed CY 2017 national, Multiply by the national, 2017 national, Multiply by the national,
standardized 60-day episode 3 percent rural standardized standardized 3 percent rural standardized
payment rate add-on 60-day 60-day add-on 60-day
episode episode episode
payment rate payment rate payment rate
----------------------------------------------------------------------------------------------------------------
$2,936.68..................... x 1.03 $3,024.78 $2,879.27 x 1.03 $2,965.65
----------------------------------------------------------------------------------------------------------------
[[Page 43737]]
Table 19--Proposed CY 2017 Per-Visit Amounts for Services Provided in a Rural Area
--------------------------------------------------------------------------------------------------------------------------------------------------------
For HHAs that DO submit quality data For HHAs that DO NOT submit quality data
--------------------------------------------------------------------------------------------------------------------------------------------------------
Proposed CY Multiply by the Proposed CY Proposed CY Multiply by the Proposed CY
HH Discipline type 2017 per-visit 3 percent rural 2017 rural per- 2017 per-visit 3 percent rural 2017 rural per-
rate add-on visit rates rate add-on visit rates
--------------------------------------------------------------------------------------------------------------------------------------------------------
HH Aide............................................... $64.09 x 1.03 $66.01 $62.84 x 1.03 $64.73
MSS................................................... 226.87 x 1.03 233.68 222.43 x 1.03 229.10
OT.................................................... 155.77 x 1.03 160.44 152.73 x 1.03 157.31
PT.................................................... 154.72 x 1.03 159.36 151.69 x 1.03 156.24
SN.................................................... 141.54 x 1.03 145.79 138.77 x 1.03 142.93
SLP................................................... 168.16 x 1.03 173.20 164.87 x 1.03 169.82
--------------------------------------------------------------------------------------------------------------------------------------------------------
Table 20--Proposed CY 2017 NRS Conversion Factors for Services Provided in a Rural Area
----------------------------------------------------------------------------------------------------------------
For HHAs that DO submit quality data For HHAs that DO NOT submit quality
------------------------------------------------------------------------- data
---------------------------------------
Multiply by Proposed CY Multiply by Proposed CY
the 3 2017 rural Proposed CY the 3 2017 rural
Proposed CY 2017 conversion factor percent NRS 2017 percent NRS
rural add- conversion conversion rural add- conversion
on factor factor on factor
----------------------------------------------------------------------------------------------------------------
$52.40....................................... x 1.03 $53.97 $51.38 x 1.03 $52.92
----------------------------------------------------------------------------------------------------------------
Table 21--Proposed CY 2017 NRS Payment Amounts for Services Provided in a Rural Area
----------------------------------------------------------------------------------------------------------------
For HHAs that DO submit For HHAs that DO NOT submit
------------------------------------------------- quality data quality data
---------------------------------------------------------------
Proposed CY Proposed CY
2017 NRS 2017 NRS
Severity level Points (scoring) Relative payment Relative payment
weight amounts for weight amounts for
rural areas rural areas
----------------------------------------------------------------------------------------------------------------
1............................. 0............... 0.2698 $14.56 0.2698 $14.28
2............................. 1 to 14......... 0.9742 52.58 0.9742 51.55
3............................. 15 to 27........ 2.6712 144.16 2.6712 141.36
4............................. 28 to 48........ 3.9686 214.19 3.9686 210.02
5............................. 49 to 98........ 6.1198 330.29 6.1198 323.86
6............................. 99+............. 10.5254 568.06 10.5254 557.00
----------------------------------------------------------------------------------------------------------------
D. Payments for High-Cost Outliers Under the HH PPS
1. Background
Section 1895(b)(5) of the Act allows for the provision of an
addition or adjustment to the national, standardized 60-day case-mix
and wage-adjusted episode payment amounts in the case of episodes that
incur unusually high costs due to patient care needs. Prior to the
enactment of the Affordable Care Act, section 1895(b)(5) of the Act
stipulated that projected total outlier payments could not exceed 5
percent of total projected or estimated HH payments in a given year. In
the July 3, 2000 Medicare Program; Prospective Payment System for Home
Health Agencies final rule (65 FR 41188 through 41190), we described
the method for determining outlier payments. Under this system, outlier
payments are made for episodes whose estimated costs exceed a threshold
amount for each Home Health Resource Group (HHRG). The episode's
estimated cost is the sum of the national wage-adjusted per-visit
payment amounts for all visits delivered during the episode. The
outlier threshold for each case-mix group or Partial Episode Payment
(PEP) adjustment is defined as the 60-day episode payment or PEP
adjustment for that group plus a fixed-dollar loss (FDL) amount. The
outlier payment is defined to be a proportion of the wage-adjusted
estimated cost beyond the wage-adjusted threshold. The threshold amount
is the sum of the wage and case-mix adjusted PPS episode amount and
wage-adjusted FDL amount. The proportion of additional costs over the
outlier threshold amount paid as outlier payments is referred to as the
loss-sharing ratio.
In the CY 2010 HH PPS proposed rule (74 FR 40948), we stated that
outlier payments increased as a percentage of total payments from 4.1
percent in CY 2005, to 5.0 percent in CY 2006, to 6.4 percent in CY
2007 and that this excessive growth in outlier payments was primarily
the result of unusually high outlier payments in a few areas of the
country. In that discussion, we noted that despite program integrity
efforts associated with excessive outlier payments in targeted areas of
the country, we discovered that outlier expenditures still exceeded the
5 percent target in CY 2007 and, in the absence of corrective measures,
would continue do to so. Consequently, we assessed the appropriateness
of taking action to curb outlier abuse. As described in the HH PPS
final rule (74 FR 58080 through 58087), to mitigate possible billing
vulnerabilities associated with excessive outlier payments and adhere
to our statutory limit on outlier payments, we finalized an outlier
policy that included a 10 percent agency-level cap on outlier payments.
This cap was implemented in concert with a reduced FDL ratio of
[[Page 43738]]
0.67. These policies resulted in a projected target outlier pool of
approximately 2.5 percent. (The previous outlier pool was 5 percent of
total home health expenditures). For CY 2010, we first returned the 5
percent held for the previous target outlier pool to the national,
standardized 60-day episode rates, the national per-visit rates, the
LUPA add-on payment amount, and the NRS conversion factor. Then, we
reduced the CY 2010 rates by 2.5 percent to account for the new outlier
pool of 2.5 percent. This outlier policy was adopted for CY 2010 only.
As we noted in the CY 2011 HH PPS final rule (75 FR 70397 through
70399), section 3131(b)(1) of the Affordable Care Act amended section
1895(b)(3)(C) of the Act, and required the Secretary to reduce the HH
PPS payment rates such that aggregate HH PPS payments were reduced by 5
percent. In addition, section 3131(b)(2) of the Affordable Care Act
amended section 1895(b)(5) of the Act by re-designating the existing
language as section 1895(b)(5)(A) of the Act, and revising the language
to state that the total amount of the additional payments or payment
adjustments for outlier episodes may not exceed 2.5 percent of the
estimated total HH PPS payments for that year. Section 3131(b)(2)(C) of
the Affordable Care Act also added subparagraph (B) which capped
outlier payments as a percent of total payments for each HHA at 10
percent.
As such, beginning in CY 2011, our HH PPS outlier policy is that we
reduce payment rates by 5 percent and target up to 2.5 percent of total
estimated HH PPS payments to be paid as outliers. To do so, we first
returned the 2.5 percent held for the target CY 2010 outlier pool to
the national, standardized 60-day episode rates, the national per visit
rates, the LUPA add-on payment amount, and the NRS conversion factor
for CY 2010. We then reduced the rates by 5 percent as required by
section 1895(b)(3)(C) of the Act, as amended by section 3131(b)(1) of
the Affordable Care Act. For CY 2011 and subsequent calendar years we
target up to 2.5 percent of estimated total payments to be paid as
outlier payments, and apply a 10 percent agency-level outlier cap.
2. Proposed Changes to the Methodology Used To Estimate Episode Cost
As stated earlier, an episode's estimated cost is determined by
multiplying the national wage-adjusted per-visit payment amounts by
discipline by the number of visits by discipline reported on the home
health claim. An episode's estimated cost is then used to determine
whether an episode will receive an outlier payment and the amount of
the outlier payment. Analysis of CY 2015 home health claims data
indicates that there is significant variation in the visit length by
discipline for outlier episodes. Those agencies with 10 percent of
their total payments as outlier payments are providing shorter but more
frequent skilled nursing visits than agencies with less than 10 percent
of their total payments as outlier payments (see Table 22).
Table 22--Average Number and Length of Skilled Nursing Visits by the
Percentage of Outlier Payments to Total Payments at the Agency Level
(Current Outlier Methodology), CY 2015
------------------------------------------------------------------------
Avg.
Avg. # of minutes per
skilled skilled
nursing nursing
visits visit
------------------------------------------------------------------------
<1% Total Outlier Payments.................... 21.7 47.2
1% to <5% Total Outlier Payments.............. 26.7 44.0
5% to <10% Total Outlier Payments............. 26.7 44.3
10% Total Outlier Payments.................... 44.5 35.6
------------------------------------------------------------------------
Source: CY 2015 home health claims data from the standard analytic file
(as of December 31, 2015) for which we had a linked OASIS assessment.
Note(s): These results are based on simulations using CY 2015
utilization and the CY2017 payment parameters.
As shown in Table 23, the number of skilled nursing visits is
significantly higher than the number of visits for the five other
disciplines of care and therefore, outlier payments are predominately
driven by the provision of skilled nursing services.
Table 23--Average Number of Visits by Discipline for Outlier Episodes
------------------------------------------------------------------------
Average
Discipline number of
visits
------------------------------------------------------------------------
Home health aide........................................... 8.8
Medical social services.................................... 0.3
Occupational therapy....................................... 2.3
Physical therapy........................................... 5.1
Skilled nursing............................................ 34.0
Speech-language pathology.................................. 0.7
------------------------------------------------------------------------
Source: CY 2015 home health claims data from the standard analytic file
(as of December 31, 2015) for which we had a linked OASIS assessment.
Note(s): These results are based on simulations using CY 2015
utilization and the CY2017 payment parameters.
As a result of the analysis of CY 2015 home health claims data, we
are concerned the current methodology for calculating outlier payments
may create a financial disincentive for providers to treat medically
complex beneficiaries who require longer visits. The home health
environment differs from hospitals and other institutional
environments. In the home setting, the patient has a greater role in
determining how, when, and even if, certain interventions will be
implemented. Individual skill, cognitive and functional ability, and
financial resources affect the ability of home health patients to
safely manage their health care needs, interventions, and medication
regimens.\5\ Clinically complex patients generally use more health
services, have functional limitations, need more assistance to perform
activities of daily living (ADLs), require social support and community
resources, and require more complex medical interventions.\6\ For
example, patients using home total parenteral nutrition (TPN) must cope
with very high-tech needs at home and because of the complexity of TPN
therapy, a high level of knowledge and expertise is required in the
clinical management of these patients.\7\ In addition to the direct
patient care needs, patient education aims at instruction on the care
of the central venous access device, administration procedures and
monitoring for complications, overall well-being, parenteral nutrition
composition and frequency, test results, medications, practical and
psychosocial
[[Page 43739]]
issues.\8\ Visit frequency for home TPN patients varies and length of
nursing visits can range from 15 minutes for infusion site and catheter
assessment to 10 hours for direct patient care.\9\ For those patients
who require assistance with bathing, research has shown older persons
are more likely to have negative expectations regarding the
inevitability of further physical decline after they experience bathing
difficulties.\10\ As older home health patients decline, they may be
more likely to accept assistance with bathing and this may have the
unintended consequence of reliance on bathing assistance, which could
lead to further functional decline in the performance of other ADLs. To
mitigate further functional decline, home health nursing intensity and
visit time increases as home nursing interventions are targeted to work
with patients and caregivers on bathing sub-tasks, assistance in
modifying the home environment through the acquisition and use of
adaptive equipment and devising strategies to support patients in
dealing with pain and fatigue that could prevent independent
bathing.\11\
---------------------------------------------------------------------------
\5\ Ibid.
\6\ Rich, E., Lipson, D., Libersky, J., Parchman, M. (2012).
Coordinating Care for Adults with Complex Care Needs in the Patient-
Centered Medical Home: Challenges and Solutions. AHRQ Publication
No. 12-0010, https://pcmh.ahrq.gov/page/coordinating-care-adults-complex-care-needs-patient-centered-medical-home-challenges-and.
\7\ Huisman-deWaal, G. Achterberg, T., Jansen, J., Wanten, G.,
Schoonhoven, L. (2010). ``High-tech'' home care: Overview of
professional care in patients on home parenteral nutrition and
implications for nursing care. Journal of Clinical Nursing. (20),
2125-2134.
\8\ Ibid.
\9\ Piamjariyakul, U., Ross, V., Yadrich, D.M., Williams, A.,
Howard, L., Smith, C. (2010). Complex Home Care: Part I-Utilization
and Costs to Families for Health Care Services Each Year. Nursing
Economics. 28(4), 255-263
\10\ Friedman, B., Yanen, L., Liebel, D., Powers, B. (2014).
Effects of Home Visiting Nurse Intervention versus Care as Usual on
Individual Activities of Daily Living: A Secondary Analysis of a
Randomized Trial. BMC Geriatrics. 14(24), 1-13.
\11\ Ibid.
---------------------------------------------------------------------------
Higher nursing visit intensity and longer visits are a generally a
response to instability of the patient's condition, and/or inability to
effectively and safely manage their condition and self-care activities;
therefore, more clinically complex, frail, elderly patients will
require more intensive and frequent home health surveillance, increased
home health care utilization, and costs.12 13
---------------------------------------------------------------------------
\12\ Fried. L., Ferrucci, L., Darer, J., Williamson, J.,
Anderson, G. (2004). Untangling the Concepts of Disability, Frailty
and Comorbidity: Implications for Improved Targeting and Care.
Journal of Gerontology. 59(3), 255-263.
\13\ Riggs, J., Madigan, E., Fortinsky, R. (2011). Home Health
Care Nursing Visit Intensity and Heart Failure Patient Outcomes.
Home Health Care Managing Practice. 23(6), 412-420.
---------------------------------------------------------------------------
In addition to the clinical information described above,
Mathematica Policy Research published a report in 2010 titled ``Home
Health Independence Patients: High Use, but Not Financial Outliers.''
\14\ In this report, Mathematica described their analysis of the
relationships among the proxy demonstration target group for the Home
Health Independence Demonstration, patients who receive outlier
payments, and the agencies that serve them. As part of their research,
Mathematica examined the degree of overlap between the proxy
demonstration target group, who are ill, permanently disabled
beneficiaries, and those beneficiaries receiving outlier payments. The
study found that ``Only a small fraction of proxy demonstration
patients generate outlier payments and that differences between the
proxy demonstration and outlier patient groups examined in this study
suggest that outlier payments are not generally being used to serve the
types of severely, permanently disabled beneficiaries that were
addressed by the demonstration concept.''
---------------------------------------------------------------------------
\14\ Cheh, Valerie and Schurrer, John. Home Health Independence
Patients: High Use, but Not Financial Outliers, Report to Centers
for Medicare and Medicaid, Mathematical Policy Research. March 31,
2010.
---------------------------------------------------------------------------
Therefore, we are proposing to change the methodology used to
calculate outlier payments, using a cost-per-unit approach rather than
a cost-per-visit approach. Using this approach, we would convert the
national per-visit rates in section III.C.3. into per 15 minute unit
rates (see Table 24). The new per-unit rates by discipline would then
be used, along with the visit length data by discipline reported on the
home health claim in 15 minute increments (15 minutes = 1 unit), to
calculate the estimated cost of an episode to determine whether the
claim will receive an outlier payment and the amount of payment for an
episode of care. We note that this change in the methodology would be
budget neutral as we would still target to pay out 2.5 percent of total
payments as outlier payments in accordance with section 1895(b)(5)(A)
of the Act, which requires us to pay up to, but no more than, 2.5
percent of total HH PPS payments as outlier payments.
Table 24--Proposed Cost-per-Unit Payment Rates for the Calculation of Outlier Payments
----------------------------------------------------------------------------------------------------------------
Proposed CY
2017 national Average Cost-per-unit
Visit type per-visit minutes- per- (1 unit = 15
payment rates visit minutes)
----------------------------------------------------------------------------------------------------------------
Home health aide................................................ $64.09 62.2 $15.46
Medical social services......................................... 226.87 56.4 60.34
Occupational therapy............................................ 155.77 47.1 49.61
Physical therapy................................................ 154.72 46.6 49.80
Skilled nursing................................................. 141.54 44.7 47.50
Speech-language pathology....................................... 168.16 48.1 52.44
----------------------------------------------------------------------------------------------------------------
Source: CY 2015 home health claims data from the standard analytic file (as of December 31, 2015) for which we
had a linked OASIS assessment.
Note(s): Excludes LUPAs.
We believe that this proposed change to the outlier methodology
will result in more accurate outlier payments where the calculated cost
per episode accounts for not only the number of visits during an
episode of care, but also the length of the visits performed. This, in
turn, may address some of the findings from the home health study,
where margins were lower for patients with medically complex needs that
typically require longer visits, thus potentially creating an incentive
to treat less complex patients.
Table 25 shows the difference in the average number of visits and
the average minutes per visit for outlier episodes under the current
outlier methodology and the proposed outlier methodology by the
percentage of outlier payments to total payments at the agency level.
[[Page 43740]]
Table 25--Average Number of Visits and Minutes per Visit by the Percentage of Outlier Payments to Total Payments
at the Agency Level for Outlier Episodes for the Current and Proposed Outlier Methodologies, CY 2015
----------------------------------------------------------------------------------------------------------------
Current Outlier Proposed Outlier
Methodology (Cost per Methodology (Cost per
Visit) Unit)
---------------------------------------------------
Avg. Avg.
Avg. # of minutes per Avg. # of minutes per
visits visit visits visit
----------------------------------------------------------------------------------------------------------------
<1% Total Outlier Payments.................................. 39.7 48.9 38.5 52.6
1% to <5% Total Outlier Payments............................ 44.7 49.2 43.5 52.0
5% to <10% Total Outlier Payments........................... 44.7 49.6 54.8 55.2
10% Total Outlier Payments.................................. 60.7 44.0 56.4 65.6
----------------------------------------------------------------------------------------------------------------
Source: CY 2015 home health claims data from the standard analytic file (as of December 31, 2015) for which we
had a linked OASIS assessment.
Note(s): These results are based on simulations using CY 2015 utilization and the CY2017 payment parameters.
Analysis of the impact of the change from a cost-per-visit to a
cost-per-unit approach indicates that approximately two-thirds of
outlier episodes under the cost-per-unit approach would have still
received outlier payments under the current cost-per-visit approach,
while about one-third of outlier episodes under the current cost per
visit approach would not receive outlier payments under the cost-per-
unit approach. Table 26 shows the average number of visits and the
visit length for the episodes that would receive outlier payments under
the current cost-per-visit approach, but not under the proposed cost-
per-unit approach, as well as the average number of visits and the
visit length for the episodes that would receive outlier payments under
the proposed cost-per-unit approach, but not under the current cost-
per-visit approach. Those episodes that would only receive outlier
payments under the current cost-per-visit approach have less average
resource use (calculated by multiplying the number of visits with the
number of minutes) than those episodes that would only receive outlier
payments under the proposed cost-per-unit approach. These results
indicate that the change from the current cost-per-visit methodology to
the proposed cost-per-unit methodology would result in more accurate
outlier payments that better account for the intensity of the visits
performed rather than only visit volume.
Table 26--Average Number of Visits and Visit Length for Episodes That Receive Outlier Payments Only Under the
Current Outlier Methodology and for Episodes That Receive Outlier Payments Only Under the Proposed Outlier
Methodology, CY 2015
----------------------------------------------------------------------------------------------------------------
Episodes that only would Episodes that only would
receive outlier payments under receive outlier payments under
the current methodology the proposed methodology
---------------------------------------------------------------
Avg. # of Avg. minutes Avg. # of Avg. minutes
visits per visit visits per visit
----------------------------------------------------------------------------------------------------------------
<1% Total Outlier Payments...................... 36.8 39.9 29.8 63.4
1% to <5% Total Outlier Payments................ 37.6 38.5 30.6 65.6
5% to <10% Total Outlier Payments............... 43.8 36.4 30.2 85.9
10% Total Outlier Payments...................... 46.1 27.5 31.9 104.5
----------------------------------------------------------------------------------------------------------------
Source: CY 2015 home health claims data from the standard analytic file (as of December 31, 2015) for which we
had a linked OASIS assessment.
Note(s): These results are based on simulations using CY 2015 utilization and the CY2017 payment parameters.
In addition, we examined the impact of changing from the current
cost-per-visit methodology to the proposed cost-per-unit methodology on
a subset of the vulnerable patient populations identified in the home
health study. Our simulations indicate that certain subgroups
identified in the home health study may benefit from the change from
the current outlier methodology to the proposed outlier methodology.
Table 27 shows some of the vulnerable patient populations that may
benefit from the proposed changes to the outlier methodology. As shown
in Table 27, preliminary analysis indicates that a larger percentage of
episodes of care for patients with a fragile overall health status will
qualify for outlier payments under the proposed methodology than under
the current methodology (24.1 percent versus 20.1 percent). Similarly,
a larger percentage of episodes of care for patients who need
assistance with bathing will qualify for outlier payments under the
proposed methodology than under the current methodology (29.1 percent
versus 27.0 percent). In addition, a larger percentage of episodes of
care for patients who need caregiver assistance or who have surgical
wounds will qualify for outlier payments under the proposed methodology
versus under the current methodology (7.7 percent versus 6.7 percent
and 19.0 percent versus 18.1 percent, respectively). Furthermore, there
are small increases in the percentage of episodes of care that would
qualify for outlier payments for the patients who need parenteral
nutrition or have poorly controlled cardiac dysrhythmia or pulmonary
disorders. These results suggest that the proposed change to the
outlier methodology may address some of the findings from the home
health study and may alleviate potential financial
[[Page 43741]]
disincentives to treat patients with medically complex needs.
Table 27--Impact of the Proposed Outlier Methodology Change on Subgroups of Vulnerable Patient Populations
Identified in the Home Health Study
----------------------------------------------------------------------------------------------------------------
Overall percentage Percent of outliers Percent of outliers
Subgroups identified in the home health study for all non-LUPA based on cost-per- based on cost-per-
episodes (%) visit approach (%) unit approach (%)
----------------------------------------------------------------------------------------------------------------
Needs caregiver assistance.................... 6.8 6.7 7.7
Fragile-serious overall status................ 21.9 20.1 24.1
Needs assistance with bathing................. 20.1 27.0 29.1
Parenteral Nutrition.......................... 0.2 0.2 0.4
Poorly Controlled Cardiac Dysrhythmia......... 4.3 3.4 3.8
Poorly Controlled Pulmonary Disorder.......... 7.8 5.4 6.0
Surgical Wound................................ 17.6 18.1 19.0
----------------------------------------------------------------------------------------------------------------
Source: CY 2015 home health claims data from the standard analytic file (as of December 31, 2015) for which we
had a linked OASIS assessment.
Note(s): These results are based on simulations using CY 2015 utilization and the CY2017 payment parameters.
In concert with our proposal to change to a cost-per-unit approach
to estimate episode costs and determine whether an outlier episode
should receive outlier payments, we are proposing to implement a cap on
the amount of time per day that would be counted toward the estimation
of an episode's costs for outlier calculation purposes. Specifically,
we propose to limit the amount of time per day (summed across the six
disciplines of care) to 8 hours or 32 units per day when estimating the
cost of an episode for outlier calculation purposes. We note that this
proposal is consistent with the definition of ``part-time'' or
``intermittent'' set out in section 1861(m) of the Act, which limits
the amount of skilled nursing and home health aide minutes combined to
less than 8 hours each day and 28 or fewer hours each week (or, subject
to review on a case-by-case basis as to the need for care, less than 8
hours each day and 35 or fewer hours per week). We also note that we
are not limiting the amount of care that can be provided on any given
day. We are only limiting the time per day that can be credited towards
the estimated cost of an episode when determining if an episode should
receive outlier payments and calculating the amount of the outlier
payment. For instances when more than 8 hours of care is provided by
one discipline of care, the number of units for the line item will be
capped at 32 units for the day for outlier calculation purposes. For
rare instances when more than one discipline of care is provided and
there is more than 8 hours of care provided in one day, the episode
cost associated with the care provided during that day will be
calculated using a hierarchical method based on the cost per unit per
discipline shown in Table 24. The discipline of care with the lowest
associated cost per unit will be discounted in the calculation of
episode cost in order to cap the estimation of an episode's cost at 8
hours of care per day. For example, if an HHA provided 4.5 hours of
skilled nursing and 4.5 hours of home health aide services, all 4.5
hours of skilled nursing would be counted in the episode's estimated
cost and 3.5 hours of home health aide services would be counted in the
episode's estimated cost (8 hours - 4.5 hours = 3.5 hours) since home
health aide services has a lower cost-per-unit than skilled nursing
services.
We note that preliminary analysis suggests that this proposed cap
will have a limited impact on episodes overall. Out of approximately
5.4 million episodes in our preliminary analytic file for 2015, only
15,384 episodes or 0.28 percent of all home health episodes reported
instances where over 8 hours of care were provided in a single day
(which could have resulted from data entry errors as we currently do
not use visit length for payment). Of those 15,384 episodes, only 1,591
would be outlier episodes under the proposed outlier methodology.
Therefore, we estimate that only 1,600 episodes or so, out of 5.4
million episodes, would be impacted due to the proposed 8 hour cap.
3. Proposed Fixed Dollar Loss (FDL) Ratio
For a given level of outlier payments, there is a trade-off between
the values selected for the FDL ratio and the loss-sharing ratio. A
high FDL ratio reduces the number of episodes that can receive outlier
payments, but makes it possible to select a higher loss-sharing ratio,
and therefore, increase outlier payments for qualifying outlier
episodes. Alternatively, a lower FDL ratio means that more episodes can
qualify for outlier payments, but outlier payments per episode must
then be lower.
The FDL ratio and the loss-sharing ratio must be selected so that
the estimated total outlier payments do not exceed the 2.5 percent
aggregate level (as required by section 1895(b)(5)(A) of the Act).
Historically, we have used a value of 0.80 for the loss-sharing ratio
which, we believe, preserves incentives for agencies to attempt to
provide care efficiently for outlier cases. With a loss-sharing ratio
of 0.80, Medicare pays 80 percent of the additional estimated costs
above the outlier threshold amount.
In the CY 2011 HH PPS final rule (75 FR 70398), in targeting total
outlier payments as 2.5 percent of total HH PPS payments, we
implemented an FDL ratio of 0.67, and we maintained that ratio in CY
2012. Simulations based on CY 2010 claims data completed for the CY
2013 HH PPS final rule showed that outlier payments were estimated to
comprise approximately 2.18 percent of total HH PPS payments in CY
2013, and as such, we lowered the FDL ratio from 0.67 to 0.45. We
stated that lowering the FDL ratio to 0.45, while maintaining a loss-
sharing ratio of 0.80, struck an effective balance of compensating for
high-cost episodes while allowing more episodes to qualify as outlier
payments (77 FR 67080). The national, standardized 60-day episode
payment amount is multiplied by the FDL ratio. That amount is wage-
adjusted to derive the wage-adjusted FDL amount, which is added to the
case-mix and wage-adjusted 60-day episode payment amount to determine
the outlier threshold amount that costs have to exceed before Medicare
would pay 80 percent of the additional estimated costs.
[[Page 43742]]
For this proposed rule, simulating payments using preliminary CY
2015 claims data (as of December 31, 2015) and the CY 2016 payment
rates (80 FR 68649 through 68652), we estimate that outlier payments in
CY 2016 would comprise 2.23 percent of total payments. Based on
simulations using CY 2015 claims data and the CY 2017 payment rates in
section III.C.3 of this proposed rule, we estimate that outlier
payments would comprise approximately 2.58 percent of total HH PPS
payments in CY 2017 under the current outlier methodology, a percent
change of approximately 15.7 percent. This increase is attributable to
the increase in the national per-visit amounts through the rebasing
adjustments and the decrease in the national, standardized 60-day
episode payment amount as a result of the rebasing adjustment and the
nominal case-mix growth reduction.
Given the statutory requirement to target up to, but no more than,
2.5 percent of total payments as outlier payments, we are proposing a
change to the FDL ratio for CY 2017 as we believe that maintaining an
FDL ratio of 0.45 with a loss-sharing ratio of 0.80 is no longer
appropriate given the percentage of outlier payments projected for CY
2017. We note that we are not proposing a change to the loss-sharing
ratio (0.80) in order for the HH PPS to remain consistent with payment
for high-cost outliers in other Medicare payment systems (for example,
IRF PPS, IPPS, etc.) Under the current outlier methodology, the FDL
ratio would need to be changed from 0.45 to 0.48 to pay up to, but no
more than, 2.5 percent of total payments as outlier payments. Under the
proposed outlier methodology which would use a cost per unit rather
than a cost per visit when calculating episode costs, we estimate that
we will pay out 2.74 percent in outlier payments in CY 2017 using an
FDL ratio of 0.48 and that the FDL ratio will need to be changed to
0.56 to pay up to, but no more than, 2.5 percent of total payments as
outlier payments.
Therefore, in addition to the proposal to change the methodology
used to calculate outlier payments, we are proposing to change the FDL
ratio from 0.45 to 0.56 for CY 2017. We note that in the final rule, we
will update our estimate of outlier payments as a percent of total HH
PPS payments using the most current and complete year of HH PPS data
(CY 2015 claims data as of June 30, 2016) and therefore, we may adjust
the final FDL ratio accordingly. We invite public comments on the
proposed changes to the outlier payment calculation methodology and the
associated changes in the regulations text at Sec. 484.240 as well as
the proposed change to the FDL ratio.
E. Proposed Payment Policies for Negative Pressure Wound Therapy (NPWT)
Using a Disposable Device
1. Background
Negative pressure wound therapy (NPWT) is a medical procedure in
which a vacuum dressing is used to enhance and promote healing in
acute, chronic, and burn wounds. The therapy involves using a sealed
wound dressing attached to a pump to create a negative pressure
environment in the wound. Applying continued or intermittent vacuum
pressure helps to increase blood flow to the area and draw out excess
fluid from the wound. Moreover, the therapy promotes wound healing by
preparing the wound bed for closure, by reducing edema, by promoting
granulation tissue formation and perfusion, and by removing exudate and
infectious material. The wound type and/or the location of the wound
determine whether the vacuum can either be applied continuously or
intermittently. NPWT can be utilized for varying lengths of time, as
indicated by the severity of the wound, from a few days of use up to a
span of several months.
In addition to the conventional NPWT systems classified as durable
medical equipment (DME), NPWT can also be performed with a single-use
disposable system that consists of a non-manual vacuum pump, a
receptacle for collecting exudate, and dressings for the purposes of
wound therapy. These disposable systems consist of a small pump, which
eliminates the need for a bulky canister. Unlike conventional NPWT
systems classified as DME, disposable NPWT systems have a preset
continuous negative pressure, there is no intermittent setting, they
are pocket-sized and easily transportable, and they are generally
battery-operated with disposable batteries.\15\
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\15\ Single use negative pressure wound therapy. CME Online.
2013 www.pfiedler.com.
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Section 1895 of the Act requires that the HH PPS includes payment
for all covered home health services. Section 1861(m) of the Act
defines what items and services are considered to be ``home health
services'' when furnished to a Medicare beneficiary under a home health
plan of care when provided in the beneficiary's place of residence.
Those services include:
Part-time or intermittent nursing care
Physical or occupational therapy or speech-language
pathology services
Medical social services
Part-time or intermittent services of a home health aide
Medical supplies
A covered osteoporosis drug
Durable medical equipment (DME)
The unit of payment under the HH PPS is a national, standardized
60-day episode payment amount with applicable adjustments. The
national, standardized 60-day episode payment amount includes costs for
the home health services outlined above per section 1861(m) of the Act,
except for DME and the covered osteoporosis drug. Section 1814(k) of
the Act specifically excludes DME from the national, standardized 60-
day episode rate and consolidated billing requirements. DME continues
to be paid outside of the HH PPS. The cost of the covered osteoporosis
drug (injectable calcitonin), which is covered where a woman is
postmenopausal and has a bone fracture, is also not included in the
national, standardized 60-day episode payment amount, but must be
billed by the HHA while a patient is under a home health plan of care
since the law requires consolidated billing of osteoporosis drugs. The
osteoporosis drug itself continues to be paid on a reasonable cost
basis.
Medical supplies are included in the definition of ``home health
services'' and the cost of such supplies is included in the national,
standardized 60-day episode payment amount. Medical supplies are items
that, due to their therapeutic or diagnostic characteristics, are
essential in enabling HHA personnel to conduct home visits or to carry
out effectively the care the physician has ordered for the treatment or
diagnosis of the patient's illness or injury. Supplies are classified
into two categories, specifically:
Routine: Supplies used in small quantities for patients
during the usual course of most home visits; or
Non-routine: Supplies needed to treat a patient's specific
illness or injury in accordance with the physician's plan of care and
meet further conditions.
Both routine and non-routine medical supplies are included in the
national, standardized 60-day episode payment amount for every Medicare
home health patient regardless of whether or not the patient requires
medical supplies during the episode. The law requires that all medical
supplies (routine and non-routine) be provided by the HHA while the
patient is under a home health plan of care. A disposable NPWT system
would be considered a non-routine supply for home health.
As required under sections 1814(a)(2)(C) and 1835(a)(2)(A) of the
[[Page 43743]]
Act, for home health services to be covered, the patient must receive
such services under a plan of care established and periodically
reviewed by a physician. As described in Sec. 484.18 of the Medicare
Conditions of Participation (CoPs), the plan of care that is developed
in consultation with the agency staff, is to cover all pertinent
diagnoses, including the types of services and equipment required for
the treatment of those diagnoses as well as any other appropriate
items, including DME. Consolidated billing requirements ensure that
only the HHA can bill for home health services, with the exception of
DME and therapy services provided by physicians, when a patient is
under a home health plan of care. The types of service most affected by
the consolidated billing edits tend to be non-routine supplies and
outpatient therapies, since these services are routinely billed by
providers other than HHAs, or are delivered by HHAs to patients not
under home health plans of care.
As provided under section 1834(k)(5) of the Act, a therapy code
list was created based on a uniform coding system (that is, the HCPCS)
to identify and track these outpatient therapy services paid under the
Medicare Physician Fee Schedule (MPFS). The list of therapy codes,
along with their respective designation, can be found on the CMS Web
site, specifically at https://www.cms.hhs.gov/TherapyServices/05_Annual_Therapy_Update.asp#TopOfPage. Two of the designations that
are used for therapy services are: ``Always therapy'' and ``sometimes
therapy.'' An ``always therapy'' service must be performed by a
qualified therapist under a certified therapy plan of care, and a
``sometimes therapy'' service may be performed by physician or a non-
physician practitioner outside of a certified therapy plan of care. CPT
codes 97607 and 97608 are categorized as a ``sometimes'' therapy, which
may be performed by either a physician or a non-physician practitioner
outside of a certified therapy plan of care, as described in section
200.9 of Chapter 4 of the Medicare Claims Processing Manual.\16\
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\16\ https://www.cms.gov/Regulations-and-Guidance/Guidance/Manuals/Downloads/clm104c04.pdf.
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2. The Consolidated Appropriations Act of 2016
As mentioned in section III.A.1 above, for patients under a home
health plan of care, payment for part-time or intermittent skilled
nursing, physical therapy, speech-language pathology, occupational
therapy, medical social services, part-time or intermittent home health
aide visits, and routine and non-routine supplies are included in the
episode payment amount. A disposable NPWT system is currently
considered a non-routine supply and thus payment for the disposable
NPWT system is included in the episode payment amount. The Consolidated
Appropriations Act of 2016 (Pub. L 114-113) amends both section 1834 of
the Act (42 U.S.C. 1395m) and section 1861(m)(5) of the Act (42 U.S.C.
1395x(m)(5)), requiring a separate payment to a HHA for an applicable
disposable device when furnished on or after January 1, 2017, to an
individual who receives home health services for which payment is made
under the Medicare home health benefit. Section 1834(s)(2) of the Act
defines an applicable device as a disposable negative pressure wound
therapy device that is an integrated system comprised of a non-manual
vacuum pump, a receptacle for collecting exudate, and dressings for the
purposes of wound therapy used in lieu of a conventional NPWT DME
system.
As required by the Consolidated Appropriations Act of 2016 (Pub. L
114-113), the separate payment amount for NPWT using a disposable
system is to be set equal to the amount of the payment that would be
made under the Medicare Hospital Outpatient Prospective Payment System
(OPPS) using the Level I Healthcare Common Procedure Coding System
(HCPCS) code, otherwise referred to as Current Procedural Terminology
(CPT-4) codes, for which the description for a professional service
includes the furnishing of such a device.
Under the OPPS, CPT codes 97607 and 97608 (APC 5052--Level 2 Skin
Procedures), include furnishing the service as well as the disposable
NPWT device. The codes are defined as follows:
HCPCS 97607--Negative pressure wound therapy, (for
example, vacuum assisted drainage collection), utilizing disposable,
non-durable medical equipment including provision of exudate management
collection system, topical application(s), wound assessment, and
instructions for ongoing care, per session; total wound(s) surface area
less than or equal to 50 square centimeters.
HCPCS 97608--Negative pressure wound therapy, (for
example, vacuum assisted drainage collection), utilizing disposable,
non-durable medical equipment including provision of exudate management
collection system, topical application(s), wound assessment, and
instructions for ongoing care, per session; total wound(s) surface area
greater than 50 square centimeters.
3. Proposed Payment Policies for NPWT Using a Disposable Device
For the purposes of paying for NPWT using a disposable device for a
patient under a Medicare home health plan of care and for which payment
is otherwise made under section 1895(b) of the Act, CMS is proposing
that for instances where the sole purpose for an HHA visit is to
furnish NPWT using a disposable device, Medicare will not pay for the
visit under the HH PPS. Instead, we propose that since furnishing NPWT
using a disposable device for a patient under a home health plan of
care is to be paid separately, based on the OPPS amount, which includes
payment for both the device and furnishing the service, the HHA must
bill these visits separately under type of bill 34x (used for patients
not under a HH plan of care, Part B medical and other health services,
and osteoporosis injections) along with the appropriate HCPCS code
(97607 or 97608). Visits performed solely for the purposes of
furnishing NPWT using a disposable device are not to be reported on the
HH PPS claim (type of bill 32x).
If NPWT using a disposable device is performed during the course of
an otherwise covered HHA visit (for example, while also furnishing a
catheter change), we propose that the HHA must not include the time
spent furnishing NPWT in their visit charge or in the length of time
reported for the visit on the HH PPS claim (type of bill 32x).
Providing NPWT using a disposable device for a patient under a home
health plan of care will be separately paid based on the OPPS amount
relating to payment for covered OPD services. In this situation, the
HHA bills for NPWT performed using a disposable device under type of
bill 34x along with the appropriate HCPCS code (97607 or 97608).
Additionally, this same visit should also be reported on the HH PPS
claim (type of bill 32x), but only for the time spent furnishing the
services unrelated to the provision of NPWT.
As noted in section III.E.1, since these two CPT codes (97607 and
97608) are considered ``sometimes'' therapy codes, NPWT using a
disposable device for patients under a home health plan of care can be
performed, in accordance to State law, by a registered nurse, physical
therapist, or occupational therapist and the visits would be reported
on the type of bill 34x using revenue codes 0559, 042X, 043X. The
[[Page 43744]]
descriptions for CPT codes 97607 and 97608 include performing a wound
assessment, therefore we believe that it would only be appropriate for
these visits to be performed by a registered nurse, physical therapist,
or occupational therapist as defined in Sec. 484.4 of the Medicare
Conditions of Participation (CoPs).
The payment amount for both 97607and 97608 will be set equal to the
amount of the payment that would be made under the OPPS and subject to
the area wage adjustment policies in place under the OPPS, for CY 2017
and each subsequent year. Please see Medicare Hospital OPPS Web page
for Addenda A and B at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/HospitalOutpatientPPS/Addendum-A-and-Addendum-B-Updates.html. These addenda are a ``snapshot'' of HCPCS codes and their
status indicators, APC groups, and OPPS payment rates that are in
effect at the beginning of each quarter. Section 504(b)(1) of the
Consolidated Appropriations Act of 2016 (Pub. L 114-113) amends section
1833(a)(1) of the Act, which requires that furnishing the NPWT using a
disposable device be subject to beneficiary coinsurance in the amount
of 20 percent. The amount paid to the HHA by Medicare will be equal to
80 percent of the lesser of the actual charge or the payment amount as
determined by the OPPS for the year.
In order for a beneficiary to receive NPWT using a disposable
device under the home health benefit, the beneficiary must also qualify
for the home health benefit in accordance with the existing eligibility
requirements. To be eligible for Medicare home health services, as set
out in sections 1814(a) and 1835(a) of the Act, a physician must
certify that the Medicare beneficiary (patient) meets the following
criteria:
Is confined to the home
Needs skilled nursing care on an intermittent basis or
physical therapy or speech-language pathology; or have a continuing
need for occupational therapy
Is under the care of a physician
Receive services under a plan of care established and reviewed
by a physician; and
Has had a face-to-face encounter related to the primary reason
for home health care with a physician or allowed Non-Physician
Practitioner (NPP) within a required timeframe.
As set forth in Sec. Sec. 409.32 and 409.44, to be considered a
skilled service, the service must be so inherently complex that it can
be safely and effectively performed only by, or under the supervision
of, professional or technical personnel. Additionally, care is deemed
as ``reasonable and necessary'' based on information reflected in the
home health plan of care, the OASIS as required by Sec. 484.55, or a
medical record of the individual patient. Coverage for NPWT using a
disposable device will be determined based upon a doctor's order as
well as patient preference. Research has shown that patients prefer
wound dressing materials that afford the quickest wound healing, pain
reduction, maximum exudate absorption to minimize drainage and odor,
and they indicated some willingness to pay out of pocket costs.\17\
Treatment decisions as to whether to use a disposable NPWT system
versus a conventional NPWT DME system is determined by the
characteristics of the wound, as well as, patient goals and preferences
discussed with the ordering physician to best achieve wound healing and
reduction.
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\17\ Corbett, L., Ennis, W. (2014). What Do Patients Want?
Patient Preferences in Wound Care. 3(8), 537-543.
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We are soliciting public comment on all aspects of the proposed
payment policies for furnishing a disposable NPWT device as articulated
in this section as well as the corresponding proposed changes to the
regulations at Sec. 409.50 in section VII of this proposed rule.
F. Update on Subsequent Research and Analysis Related to Section
3131(d) of the Affordable Care Act
Section 3131(d) of the Patient Protection and Affordable Care Act
(Pub. L. 111-148), as amended by the Health Care and Education
Reconciliation Act of 2010 (Pub. L. 111-152), (collectively referred to
as ``The Affordable Care Act''), directed the Secretary of Health and
Human Services (the Secretary) to conduct a study on HHA costs involved
with providing ongoing access to care to low-income Medicare
beneficiaries or beneficiaries in medically underserved areas and in
treating beneficiaries with high levels of severity of illness and to
submit a Report to Congress on the study's findings and
recommendations. As part of the study, the Affordable Care Act stated
that we may also analyze methods to potentially revise the home health
prospective payment system (HH PPS). In the CY 2016 HH PPS proposed
rule (80 FR 39840), we summarized the Report to Congress on the home
health study, required by section 3131(d) of the Affordable Care Act,
and provided information on the initial research and analysis conducted
to potentially revise the HH PPS case-mix methodology to address the
home health study findings outlined in the Report to Congress. In this
proposed rule, we are providing an update on additional research and
analysis conducted on the Home Health Groupings Model (HHGM), one of
the model options referenced in the CY 2016 HH PPS proposed rule (80 FR
39866).
The premise of the HHGM starts with a clinical foundation where
home health episodes are grouped by primary diagnosis based on what
home health interventions would be required during the episode of care.
In addition to the clinical groupings, the HHGM incorporates other
information from the OASIS and claims data to further group home health
episodes for payment. Each home health episode is categorized into
different sub-groups within each of the five categories below:
Timing (early or late; that is, episode is placed into 1 of 2
groups)
Referral source (community, acute, or post-acute admission
source; that is, episode is placed into 1 of 3 groups)
Clinical grouping (musculoskeletal rehab, neuro/stroke rehab,
wounds, MMTA, behavioral, or complex; that is, episode is placed into 1
of 6 groups)
Functional/cognitive level (low, medium, or high; that is,
episode is placed into 1 of 3 groups)
Comorbidity adjustment (first, second, or third, tier based on
secondary diagnoses; that is, episode is placed into 1 of 3 groups)
In total there would be 324 possible payment groupings an episode
can be grouped into under the HHGM. Unlike the current payment model,
the HHGM does not rely on the number of therapy visits performed to
influence payment.
Similar to the current payment system, episodes under the HHGM are
first classified as ``early'' or ``late'' depending on when they occur
within a sequence of adjacent episodes, as outlined in our regulations
at Sec. 484.230. Currently, the first two 60-day episodes of care are
considered ``early'' and third or later 60-day episodes of care are
considered ``late''. However, recent analysis shows that there is a
substantial difference in the number of visits that occur during the
first 30 days of a 60-day episode of care compared to the second 30
days in a 60-day episode of care (see Figure 4, below).
[[Page 43745]]
[GRAPHIC] [TIFF OMITTED] TP05JY16.006
Given the differences in the number of visits occurring in the
first 30 days versus the second 30 days in a 60-day episode of care,
and to better account for the relationship between episode
characteristics and episode cost, we modeled all episodes as 30-day
episodes of care, instead of 60-day episodes of care as in the current
payment system. Under the HHGM, the first 30-day episode in a sequence
of adjacent episodes was classified as an early episode. All subsequent
episodes in a sequence (second or later) of adjacent episodes were
classified as late episodes if separated by no more than a 60-day gap
in care.
After taking into account whether the 30-day episode of care was
``early'' versus ``late'', each episode was then classified into one of
three referral source categories depending on whether the beneficiary
was admitted from an acute or post-acute care facility within 14 days
prior to being admitted to home health (community, acute, or post-
acute). Patients admitted to home health from the community, an acute
setting of care, or a post-acute setting of care had different
observable patterns of resource use and thus, under the HHGM, episodes
of care for those patients would be paid differently.
We then grouped episodes into one of six clinical groups based on
the primary diagnosis listed on the OASIS for each episode. We created
these groups to describe the most common types of care that HHAs
provide. We have reviewed all possible ICD-9-CM codes that could be
recorded on the OASIS and assigned each code into one of the following
clinical groups: Musculoskeletal Rehabilitation; Neuro/Stroke
Rehabilitation; Wound Care; Medication Management, Teaching and
Assessment (MMTA); Behavioral Health Care; and Complex Medical Care.
The HHGM designates a functional/cognitive level for each episode
based on items identified on the OASIS that impact resource use. Using
home health episodes from 2013, we estimated a regression model that
determines the relationship between the responses for certain OASIS
items and resource use.\18\ The coefficients from the regression show
how much more or less, on average, an episode's resource use is
depending on responses to these items which is then used to predict
resource use for each individual episodes. Ranking the episodes by
predicted resource use and then identifying thresholds that divides
episodes into three groups of roughly the same size allows us to assign
each episode to into a low, medium or high functional/cognitive level.
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\18\ ``Resource use'' is an estimate of the cost of an episode.
It is measured by multiplying the number of minutes of services that
occur during an episode by a wage rate for the disciplines providing
the care.
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Finally, our exploratory analyses have determined that secondary
diagnoses (comorbidities) provide additional information that can
predict resource use even after controlling for episode timing,
referral source, the clinical grouping (based in the patient's primary
diagnosis) and functional/cognitive level. Therefore, we further
differentiated episodes into based on the presence of certain secondary
diagnoses. We explored two options. For the first option we determined
the commonly occurring comorbidities (incidence of over 0.1 percent)
reported on the OASIS that were also associated with above average
resource use. We then divided the comorbidities into a low or high
group based on average resource use associated with the comorbidity. We
then placed episodes into three tiers: Episodes for beneficiaries with
no comorbidities reported on the OASIS in the low or high group (Tier
1); episodes for beneficiaries with comorbidities in the low, but not
high group as reported on the OASIS (Tier 2); and episodes for
beneficiaries with comorbidities in the high group reported on the
OASIS (Tier 3). For the second option, we used the major complication
or comorbidity (MCC) and complication and comorbidity (CC) list from
the Inpatient Prospective Payment System (IPPS).
[[Page 43746]]
Using the CC and MMC list we placed episodes into three tiers: Episodes
where beneficiaries had no MCC or CC diagnoses reported on either the
OASIS or any inpatient or professional claim within 90 days of the
start of home care (Tier 1); episodes where beneficiaries had CC but no
MCC diagnoses reported on either the OASIS or any inpatient or
professional claim within 90 days of the start of home care (Tier 2);
and episodes where beneficiaries had at least one MCC diagnosis
reported on either the OASIS or any inpatient or professional claim
within 90 days of the start of home care (Tier 3).
We determined the case-mix weight for each of the 324 different
HHGM payment groups by estimating a regression between episode resource
use and binary variables controlling for the five dimensions described
above (episode timing, admission source, HHGM clinical group,
functional/cognitive level, and comorbidities). After estimating this
model on home health episodes from 2013 (excluding LUPA and outlier
episodes), we then used the results of the model to predict the
expected average resource use of each episode based on these six
characteristics. We divide the predicted resource use of each episode
by the overall average resource use (of all 2013 episodes) to calculate
the average case-mix of all episodes within a particular payment group
(that is, each combination of the sub-groups within the five main
groups). That case-mix weight is then used to adjust the base payment
rate to then determine each episode's payment.
In many ways, the structure of the HHGM is similar to the current
payment system. However, by either adding to or removing certain
components of the current payment system, the HHGM could help to
strengthen the HH PPS by addressing the margin differences noted in the
home health study and by removing unintended financial incentives (for
example, the current therapy thresholds). As noted in the 3131(d)
study, margin differences exist across beneficiary characteristics such
as parenteral nutrition, traumatic wounds, whether bathing assistance
was needed, and admission source. These margin differences would be
addressed by moving to a HHGM approach where those characteristics are
better accounted for in the model. Additionally, the HHGM aligns with
how clinicians generally identify the types of patients they see in
home health, which, in turn, better defines the home health benefit in
a more transparent manner so that the payer understands the primary
reason for home care. We feel that the HHGM will address the findings
highlighted in the 3131(d) report, specifically improving the payment
accuracy for purchased home health services, promote fair compensation
to HHAs, and increase the quality of care for beneficiaries. We plan to
release a more detailed Technical Report in the future on this
additional research and analysis conducted on the HHGM. When we release
the technical report, we are also planning to release a list of the
ICD-9-CM and ICD-10-CM codes assigned to each of the clinical groups
within the HHGM to further assist the industry in analyzing the HHGM
model. While we are not soliciting comments on the HHGM in this
proposed rule, once the Technical Report is released, we will post a
link on our Home Health Agency (HHA) Center Web site (https://www.cms.gov/center/provider-Type/home-Health-Agency-HHA-Center.html) to
receive comments and feedback on the model.
FF. Update on Future Plans To Group HH PPS Claims Centrally During
Claims Processing
In the CY 2011 HH PPS proposed rule (75 FR 43236) we solicited
comments on potential plans to group HH PPS claims centrally during
claims processing and received many comments in support of this
initiative. In grouping HH PPS Claims centrally during processing, we
are describing a process whereby all of the information necessary to
group the claim and assign a Health Insurance Prospective Payment
System (HIPPS) score which determines payment is available and
processed within the Fiscal Intermediary Shared System (FISS). In that
rule, we discussed the potential use of the treatment authorization
field to group HH PPS claims within the claims processing system. In
conducting further analysis, we determined that the use of the
treatment authorization field was not a viable option. In our analysis,
we determined that the information we planned to report in this field
was not permitted by the Health Insurance Portability Accountability
Act (HIPAA). In this section, we are soliciting comments on another
process identified whereby all of the information necessary to group HH
PPS claims occurs centrally during claims processing.
As we outlined in the previous rule, Medicare makes payment under
the HH PPS on the basis of a national, standardized 60-day episode
payment amount that is adjusted for case-mix and geographic wage
variations. The national, standardized 60-day episode payment amount
includes services from the six HH disciplines (skilled nursing, HH
aide, physical therapy, speech-language pathology, occupational
therapy, and medical social services) and non-routine medical supplies.
Durable medical equipment covered under HH is paid for outside the HH
PPS payment. To adjust for case-mix, the HH PPS uses a 153-category
case-mix classification to assign patients to a home health resource
group (HHRG). Clinical needs, functional status, and service
utilization are computed from responses to selected data elements in
the Outcome & Assessment Information Set (OASIS) instrument. On
Medicare claims, the HHRGs are represented as HIPPS codes.
At a patient's start of care and before the start of each
subsequent 60-day episode, the HHA is required to perform a
comprehensive clinical assessment of the patient and complete the OASIS
assessment instrument. The OASIS instrument collects data concerning 3
dimensions of the patient's condition: (1) Clinical severity
(orthopedic, neurological or diabetic conditions, etc.); (2) Functional
status (comprised of 6 activities of daily living (ADLs)); and (3)
Service utilization (therapy visits provided during episode). HHAs
enter data collected from their patients' OASIS assessments into a data
collection software tool. For Medicare patients, the data collection
software invokes HH PPS Grouper software to assign a HIPPS code to the
patient's OASIS assessment. The HHA includes the HIPPS code assigned by
HH PPS Grouper software on the Medicare HH PPS bill, ultimately
enabling our claims processing system to reimburse the HHA for services
provided to patients receiving Medicare home health services.
The HHA is separately required to electronically submit OASIS
assessments for their Medicare and Medicaid patients to us. On the HH
PPS Web site at https://www.qtso.com/havendownload.html, we provide a
free OASIS assessment data collection tool (JHAVEN) which includes the
HH PPS grouper software, a separate HH PPS grouper program which can be
incorporated into an HHA's own data collection software, and HH PPS
data specifications for use by HHAs or software vendors desiring to
build their own HH PPS grouper. Most HHAs do not use the JHAVEN
freeware, instead preferring to employ software vendors to create and
maintain a customized assessment data collection tool which can be
integrated into the HHA's billing software. Likewise, many vendors
employed by HHAs do not utilize the
[[Page 43747]]
HH PPS grouper freeware, instead preferring to build their own HH PPS
grouper from the data specifications which we provide.
Prior to the CY 2008, we made infrequent, minor changes to the HH
PPS Grouper software. Since CY 2008, the HH PPS Grouper became more
complex and more sensitive to annual diagnosis coding changes. As a
result, in recent years, HHAs have been required to update their
grouper software twice a year. Most HHAs employ software vendors to
effectuate these updates. HHAs have expressed concerns to us that the
bi-annual grouper updates coupled with the additional complexity of the
grouper has increased provider and vendor burden.
We continue to identify OASIS assessments submitted with erroneous
HIPPS codes through a process of comparing the submitted HIPPS code to
the HIPPS code returned by our assessment system. These errors may
occur when HHAs or their software vendors inaccurately replicate the HH
PPS Grouper algorithm into the HHA's customized software. HHAs have
expressed concerns that the HH PPS Grouper complexities increase their
vulnerability to submit an inaccurate HIPPS code on the Medicare bill.
We believe that embedding the HH PPS Grouper within the claims
processing system would mitigate the provider's vulnerability and
improve payment accuracy.
We recently implemented a process where we match the claim and the
OASIS assessment in order to validate the HIPPS code on the Medicare
bill. In addition, we have conducted an analysis and prototype testing
of a java-based grouper with our FISS maintenance contractor. We
believe that making additional enhancements to the claim and OASIS
matching process would enable us to collect all of the other necessary
information to assign a HIPPS code within the claims processing system.
Adopting such a process would improve payment accuracy by improving the
accuracy for HIPPS codes on bills, decrease costs, and burden to HHAs.
We are soliciting public comments on this potential enhancement as
described above. If we implemented grouping HH PPS claims centrally
within the claims processing system, the HHA would no longer have to
maintain a separate process outside of our claims processing system,
thus reducing the costs and burden to HHAs associated with the updates
of the grouper software as well as the ongoing agency costs associated
with embedding the HH PPS Grouper within JHAVEN. Finally, this
enhancement would also address current payment vulnerabilities
associated with the reporting of incorrect HIPPS codes on the claim.
IV. Proposed Provisions of the Home Health Value-Based Purchasing
(HHVBP) Model
A. Background
As authorized by section 1115A of the Act and finalized in the CY
2016 HH PPS final rule, we implemented the HHVBP Model to begin on
January 1, 2016. The HHVBP Model has an overall purpose of improving
the quality and delivery of home health care services to Medicare
beneficiaries. The specific goals of the Model are to: (1) Provide
incentives for better quality care with greater efficiency; (2) study
new potential quality and efficiency measures for appropriateness in
the home health setting; and, (3) enhance the current public reporting
process.
Using the randomized selection methodology finalized in the CY 2016
HH PPS final rule, nine states were selected for inclusion in the HHVBP
Model, representing each geographic area across the nation. All
Medicare-certified HHAs that provide services in Arizona, Florida,
Iowa, Maryland, Massachusetts, Nebraska, North Carolina, Tennessee, and
Washington (competing HHAs), are required to compete in the Model.
Requiring all Medicare-certified HHAs in the selected states to
participate in the Model ensures that: (1) There is no selection bias;
(2) participating HHAs are representative of HHAs nationally; and, (3)
there is sufficient participation to generate meaningful results.
As finalized in the CY 2016 HH PPS final rule, the HHVBP Model will
utilize the waiver authority under section 1115A(d)(1) of the Act to
adjust Medicare payment rates under section 1895(b) of the Act
beginning in calendar year (CY) 2018 based on performance on applicable
measures. Payment adjustments will be increased incrementally over the
course of the HHVBP Model in the following manner: (1) A maximum
payment adjustment of 3 percent (upward or downward) in CY 2018; (2) a
maximum payment adjustment of 5 percent (upward or downward) in CY
2019; (3) a maximum payment adjustment of 6 percent (upward or
downward) in CY 2020; (4) a maximum payment adjustment of 7 percent
(upward or downward) in CY 2021; and, (5) a maximum payment adjustment
of 8 percent (upward or downward) in CY 2022. Payment adjustments will
be based on each HHA's Total Performance Score (TPS) in a given
performance year (PY) on (1) a set of measures already reported via
OASIS and HHCAHPS for all patients serviced by the HHA, or determined
by claims data and, (2) three New Measures where points are achieved
for reporting data.
B. Smaller- and Larger-Volume Cohorts Proposals
The HHVBP Model compares a competing HHA's performance on quality
measures against the performance of other competing HHAs within the
same state and size cohort. Within each of the nine selected states,
each competing HHA is grouped to either the smaller-volume cohort or
the larger-volume cohort, as defined in Sec. 484.305. The larger-
volume cohort is defined as the group of competing HHAs within the
boundaries of selected states that are participating in HHCAHPS in
accordance with Sec. 484.250 and the smaller-volume cohort is defined
as the group of competing HHAs within the boundaries of selected states
that are exempt from participation in HHCAHPS in accordance with Sec.
484.250 (80 FR 68664). An HHA can be exempt from the HHCAHPS reporting
requirements for a calendar year period if it has less than 60 eligible
unique HHCAHPS patients annually as specified in Sec. 484.250. In the
CY 2016 HH PPS final rule, we finalized that when there are too few
HHAs in the smaller-volume cohort in each state (such as when there are
only one or two HHAs competing within a smaller-volume cohort in a
given state) to compete in a fair manner, the HHAs would be included in
the larger-volume cohort for purposes of calculating the TPS and
payment adjustment percentage without being measured on HHCAHPS (80 FR
68664).
1. Proposal to Eliminate Smaller- and Larger-Volume Cohorts Solely for
Purposes of Setting Performance Benchmarks and Thresholds
In the CY 2016 HH PPS final rule (80 FR 68681-68682), we finalized
a scoring methodology for determining achievement points for each
measure under which HHAs will receive points along an achievement
range, which is a scale between the achievement threshold and a
benchmark. The achievement thresholds are calculated as the median of
all HHAs' performance on the specified quality measure during the
baseline period and the benchmark is calculated as the mean of the top
decile of all HHAs' performance on the specified quality measure during
the baseline period.
[[Page 43748]]
We previously finalized that under the HHVBP Model, we would
calculate both the achievement threshold and the benchmark separately
for each selected state and for HHA cohort size. Under this
methodology, benchmarks and achievement thresholds would be calculated
for both the larger-volume cohort and for the smaller-volume cohort of
HHAs in each state (which we defined in each state based on a baseline
period from January 1, 2015 through December 31, 2015). We also
finalized that, in determining improvement points for each measure,
HHAs would receive points along an improvement range, which we defined
as a scale indicating the change between an HHA's performance during
the performance period and the HHA's performance in the baseline period
divided by the difference between the benchmark and the HHAs
performance in the baseline period. We finalized that both the
benchmarks and the achievement thresholds would be calculated
separately for each state and for HHA cohort size.
We finalized the above policies based on extensive analyses of the
2013-2014 OASIS, claims, and HHCAHPS archived data. We believed that
these data were sufficient to predict the effect of using cohorts for
benchmarking and threshold purposes because they have been used for
several years in other CMS quality initiatives such as the Home Health
Quality Reporting Program.
Since the publication of the CY 2016 HH PPS final rule, we have
continued to evaluate the calculation of the benchmarks and achievement
thresholds using the most recent CY 2015 data that is now available. We
have calculated benchmarks and achievement thresholds for the OASIS
measures for the smaller- and larger-volume cohorts and state-wide for
each of the nine states using these data. Our review of the benchmarks
and achievement thresholds for each of the cohorts and states indicates
that the benchmark values for the smaller-volume cohorts varied
considerably more from state-to-state than the benchmark values for the
larger-volume cohorts. Some inter-state variation in the benchmarks and
achievement thresholds for each of the measures was expected due to
different state regulatory environments. However, the overall variation
in these values was more than we expected, given the previous analyses
we did. For example, with respect to the Improvement in Bed
Transferring measure, we discovered that variation in the benchmark
values between the smaller-volume cohorts was nearly three times
greater than the variation in the benchmark values for the larger-
volume cohorts or the statewide benchmarks. We also discovered that
this large variation affected most of the measures. We are concerned
that this high variation is not the result of expected differences like
state regulatory policy, but is instead the result of (1) the cohort is
so small that there are not enough HHAs in the cohort to calculate the
values using the finalized methodology (mean of the top decile); or (2)
the cohort is large enough to calculate the values using the finalized
methodology, but there are not enough HHAs in the cohort to generate
reliable values.
We have included three tables in this proposed rule to help
illustrate this issue. Each of the three tables include the 10
benchmarks for the OASIS measures that were calculated for the Model
using the 2015 QIES roll-up file data for each state. We did not
include the claims measures and the HHCAHPS measures in this example
because we do not have all of the 2015 data available. These three
tables demonstrate the relationship between the size of the cohort and
degree of variation of the different benchmark values among the states.
Table 28, Table 29 and Table 30 represent the benchmarks for the OASIS
measures for the smaller-volume cohorts, larger-volume cohorts and
state-wide (which includes HHAs from both smaller- and larger-volume
cohorts) respectively. For example, the difference in benchmark values
for Iowa and Nebraska (two of the four states that have smaller-volume
cohorts) for the Improvement in Bed Transfers measure is 13.1 (72.7 for
Iowa and 85.8 for Nebraska) for the smaller-volume cohort (Table 28),
4.1 (78.1 for Iowa to 82.2 for Nebraska) for the larger-volume cohort
(Table 29) and 5.5 (77.6 for Iowa to 83.1 for Nebraska) for the state
level cohort (Table 30). We believe that the higher range for the
smaller-volume cohorts is a result of there being a fewer number of
HHAs in these cohorts.
Table 28--Smaller-Volume Cohort Benchmarks
--------------------------------------------------------------------------------------------------------------------------------------------------------
State
-----------------------------------------------------------------------------------------
AZ FL IA MA MD NC NE TN WA
--------------------------------------------------------------------------------------------------------------------------------------------------------
Oasis-Based Measures:
Discharged to Community................................... 77.0 88.8 73.6 82.0 ........ 75.1 81.1 79.4
Drug Education on All Medications Provided to Patient/ 100.0 100.0 100.0 100.0 ........ 98.5 100.0 100.0
Caregiver during all Episodes of Care....................
Improvement in Ambulation- Locomotion..................... 90.6 90.5 72.7 75.6 ........ 60.1 84.0 85.2
Improvement in Bathing.................................... 82.0 91.2 79.5 71.8 ........ 72.1 77.4 81.5
Improvement in Bed Transferring........................... 68.8 80.4 72.7 74.1 ........ 55.1 85.8 79.0
Improvement in Dyspnea.................................... 84.2 90.4 81.3 62.6 ........ 62.5 80.3 93.7
Improvement in Management of Oral Medications............. 63.0 74.0 58.4 62.0 ........ 62.8 65.8 58.9
Improvement in Pain Interfering with Activity............. 83.2 97.3 82.6 82.3 ........ 58.5 78.2 69.0
Influenza Immunization Received for Current Flu Season.... 73.4 89.8 90.8 83.8 ........ 89.2 83.6 88.9
Pneumococcal Polysaccharide Vaccine Ever Received......... 95.8 91.5 95.8 95.3 ........ 83.6 97.0 100.0
--------------------------------------------------------------------------------------------------------------------------------------------------------
[[Page 43749]]
Table 29--Larger-Volume Cohort Benchmarks
--------------------------------------------------------------------------------------------------------------------------------------------------------
State
-----------------------------------------------------------------------------------------
AZ FL IA MA MD NC NE TN WA
--------------------------------------------------------------------------------------------------------------------------------------------------------
Oasis-Based Measures:
Discharged to Community................................... 82.1 85.6 78.3 81.2 81.1 78.2 80.3 81.0 83.1
Drug Education on All Medications Provided to Patient/ 99.8 100.0 99.9 100.0 99.9 99.7 99.9 99.8 99.7
Caregiver during all Episodes of Care....................
Improvement in Ambulation- Locomotion..................... 76.4 92.4 76.7 76.1 76.5 75.2 80.8 77.2 70.8
Improvement in Bathing.................................... 84.2 94.2 81.9 81.0 81.0 78.9 86.6 83.5 77.7
Improvement in Bed Transferring........................... 76.4 85.4 78.1 80.2 77.5 74.5 82.2 76.8 73.5
Improvement in Dyspnea.................................... 85.9 90.5 81.3 82.2 85.1 85.5 80.7 84.2 80.7
Improvement in Management of Oral Medications............. 69.4 80.5 68.1 73.2 71.7 63.9 68.1 72.2 64.0
Improvement in Pain Interfering with Activity............. 88.6 96.7 81.0 89.5 84.4 81.5 86.0 81.7 75.5
Influenza Immunization Received for Current Flu Season.... 88.0 93.3 88.1 90.1 87.9 88.0 95.2 88.2 87.0
Pneumococcal Polysaccharide Vaccine Ever Received......... 92.5 93.6 94.4 93.8 92.1 93.4 97.0 92.7 92.7
--------------------------------------------------------------------------------------------------------------------------------------------------------
Table 30--State Level Cohort Benchmarks
--------------------------------------------------------------------------------------------------------------------------------------------------------
State
-----------------------------------------------------------------------------------------
AZ FL IA MA MD NC NE TN WA
--------------------------------------------------------------------------------------------------------------------------------------------------------
Oasis-Based Measures:
Discharged to Community................................... 81.8 86.3 77.7 81.9 81.1 78.2 80.5 80.9 83.1
Drug Education on All Medications Provided to Patient/ 99.8 100.0 100.0 100.0 99.9 99.7 99.9 99.8 99.7
Caregiver during all Episodes of Care....................
Improvement in Ambulation- Locomotion..................... 77.5 92.1 76.2 76.3 76.5 75.2 82.9 77.9 70.8
Improvement in Bathing.................................... 84.1 93.8 81.8 80.3 81.0 78.9 84.6 83.5 77.7
Improvement in Bed Transferring........................... 75.9 84.8 77.6 80.1 77.5 74.5 83.1 77.3 73.5
Improvement in Dyspnea.................................... 85.8 90.5 81.9 81.7 85.1 85.5 81.3 85.8 80.7
Improvement in Management of Oral Medications............. 69.1 79.6 67.3 72.0 71.7 64.1 68.3 72.2 64.0
Improvement in Pain Interfering with Activity............. 88.1 96.8 81.5 88.4 84.4 81.5 84.3 81.7 75.5
Influenza Immunization Received for Current Flu Season.... 87.6 92.9 88.9 90.1 87.9 88.3 94.4 88.2 87.0
Pneumococcal Polysaccharide Vaccine Ever Received......... 92.9 93.3 94.8 94.2 92.1 93.4 97.0 93.3 92.7
--------------------------------------------------------------------------------------------------------------------------------------------------------
The three tables are based on the analysis using the most current
data available. The results highlight that there is a greater degree of
interstate variation in the benchmark values for the cohorts that have
fewer HHAs as compared to the variation in benchmark values for the
cohorts that have a greater number of HHAs.
We also performed a similar analysis with the achievement
thresholds and comparing how the individual benchmarks and achievement
thresholds would fluctuate from one year to the next for the smaller-
volume cohorts, larger-volume cohorts, and the state level cohorts. The
results of those analyses were similar.
Based on the analyses that we have described, we are concerned that
if we separate HHAs into smaller- and larger-volume cohorts by state
for purposes of calculating the benchmarks and achievement thresholds,
HHAs in the smaller-volume cohorts could be required to meet
performance standards that are greater than the level of performance
that HHAs in the larger-volume cohorts would be required to achieve.
For this reason, we are proposing to calculate the benchmarks and
achievement thresholds at the state level rather than at the smaller-
and larger-volume cohort level for all model years, beginning with CY
2016. This change will eliminate the increased variation caused by
having few HHAs in the cohort but still takes into account that there
will be some inter-state variation in the values due to state
regulatory differences.
We seek public comments on this proposal.
2. The Payment Adjustment Methodology
We finalized in the CY 2016 HH PPS final rule that we would use a
linear exchange function (LEF) to translate a competing HHA's TPS into
a value-based payment adjustment percentage under the HHVBP Model (80
FR 68686). We also finalized that we would calculate the LEF separately
for each smaller-volume cohort and larger-volume cohort. In addition,
we finalized that if an HHA does not have a minimum of 20 episodes of
care during a performance year to generate a performance score on at
least five measures, we would not include the HHA in the LEF and we
would not calculate a payment adjustment percentage for that HHA.
Since the publication of the CY 2016 HH PPS final rule, we have
continued
[[Page 43750]]
to evaluate the payment adjustment methodology using the most recent
data available. We updated our analysis of the 10 OASIS quality
measures and two claims-based measures using the newly available 2014
QIES Roll Up File data, which was not available prior to the issuance
of that final rule.\19\ We also determined the size of the cohorts
using the 2014 Quality Episode File based on OASIS assessments rather
than archived quality data sources that were used in the CY 2016 rule,
whereby the HHAs reported at least five measures with over 20 episodes
of care. Based on this data, we determined that with respect to
performance year 2016, there were only three states (AZ, FL, NE) that
have more than 10 HHAs in the smaller-volume cohort; one state (IA)
that has 8-10 HHAs in the smaller-volume cohort, three states (NC, MA,
TN) that have 1-3 HHAs in the smaller-volume cohort; and two states
(MD, WA) that have no HHAs in the smaller-volume cohort. In the CY 2016
HH PPS final rule (80 FR 68664), we finalized that when there are too
few HHAs in the smaller-volume cohort in each state to compete in a
fair manner, the HHAs in that cohort would be included in the larger-
volume cohort for purposes of calculating their payment adjustment
percentage. The CY 2016 rule further defines too few as when there is
only one or two HHAs competing within a smaller-volume cohort in a
given state.
---------------------------------------------------------------------------
\19\ We did not update our analysis of the HHCAHPS measures
because more recent data was not available.
---------------------------------------------------------------------------
We also used the more current data source mentioned above to
analyze the effects of outliers on the LEF. As indicated by the payment
distributions set forth in Table 23 of this rule, the LEF is designed
so that the majority of the payment adjustment values fall closer to
the median and only a small percentage of HHAs receive adjustments at
the higher and lower ends of the distribution. However, when we looked
at the more recent data, we discovered that if there are only three or
four HHAs in the cohort, one HHA outlier could skew the payment
adjustments and deviate the payment distribution from the intended
design of the LEF payment methodology where HHAs should fall close to
the median of the payment distribution. For example, if there are only
three HHAs in the cohort, we concluded that there is a high likelihood
that those HHAs would have payment adjustments of -2.5 percent, -2.0
percent and +4.5 percent when the maximum payment adjustment is 5
percent, none falling close to the mean, with the result that those
HHAs would receive payment adjustments at the higher or lower ends of
the distribution. As the size of the cohort increases, we determined
that this became less of an issue, and that the majority of the HHAs
would have payment adjustments that are close to the median. This is
illustrated in the payment distribution in Table 23 of this rule. Under
the payment distribution for the larger-volume cohorts, 80 percent of
the HHAs in AZ, IA, FL and NE would receive a payment adjustment
ranging from -2.2 percent to +2.2 percent when the maximum payment
adjustment is 5 percent (See state level cohort in Table 23). Arizona
is a state that has a smaller-volume cohort with only nine HHAs but its
payment distribution is comparable, ranging from -1 percent to +1
percent even with one outlier that is at 5 percent.
In order to determine the minimum number of HHAs that would have to
be in a smaller-volume cohort in order to insulate that cohort from the
effect of outliers, we analyzed performance results related to the
OASIS and claims-based measures, as well as HHCAHPS, using 2013 and
2014 data. We specifically simulated the impact that outliers would
have on cohort sizes ranging from four HHAs to twelve HHAs. We found
that the LEF was less susceptible to large variation from outlier
impacts once the cohort size reached a minimum of eight HHAs. We also
found that a minimum of eight HHAs would allow for four states with
smaller-volume cohorts to have 80 percent of their payment adjustments
fall between -2.3 percent and + 2.4 percent. As a result of this
analysis, we are proposing that a smaller-volume cohort have a minimum
eight HHAs in order for the HHAs in that cohort to be compared only
against each other, and not against the HHAs in the larger-volume
cohort. We believe this proposal would better mitigate the impact of
outliers as compared to our current policy, while also enabling us to
evaluate the impact of the Model on competition between smaller-volume
HHAs.
We are also proposing that if a smaller-volume cohort in a state
has fewer than eight HHAs, those HHAs would be included in the larger-
volume cohort for that state for purposes of calculating the LEF and
payment adjustment percentages. If finalized, this change would apply
to the CY 2018 payment adjustments and thereafter. We will continue to
analyze and review the most current cohort size data as it becomes
available. We seek public comments on this proposal.
C. Quality Measure Proposals
In the CY 2016 HH PPS final rule, we finalized a set of quality
measures in Figure 4a: Final PY1 Measures and Figure 4b: Final PY1 New
Measures (80 FR 68671-68673) for the HHVBP Model to be used in the
first performance year (PY1), referred to as the ``starter set''.
The measures were selected for the Model using the following
guiding principles: (1) Use a broad measure set that captures the
complexity of the services HHAs provide; (2) Incorporate the
flexibility for future inclusion of the Improving Medicare Post-Acute
Care Transformation (IMPACT) Act of 2014 measures that cut across post-
acute care settings; (3) Develop `second generation' (of the HHVBP
Model) measures of patient outcomes, health and functional status,
shared decision making, and patient activation; (4) Include a balance
of process, outcome and patient experience measures; (5) Advance the
ability to measure cost and value; (6) Add measures for appropriateness
or overuse; and (7) Promote infrastructure investments. This set of
quality measures encompasses the multiple National Quality Strategy
(NQS) domains \20\ (80 FR 68668). The NQS domains include six priority
areas identified in the CY 2016 HH PPS final rule (80 FR 68668) as the
CMS Framework for Quality Measurement Mapping. These areas are: (1)
Clinical quality of care, (2) Care coordination, (3) Population &
community health, (4) Person- and Caregiver-centered experience and
outcomes, (5) Safety, and (6) Efficiency and cost reduction. Figures 5
and 6 of the CY 2016 HH PPS final rule identified 15 outcome measures
(five from the HHCAHPS, eight from OASIS, and two from the Chronic Care
Warehouse (claims)), and nine process measures (six from OASIS, and
three New Measures, which were not previously reported in the home
health setting).
---------------------------------------------------------------------------
\20\ 2015 Annual Report to Congress, https://www.ahrq.gov/workingforquality/reports/annual-reports/nqs2015annlrpt.htm.
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During implementation of the Model, we determined that four of the
measures finalized for PY1 require further consideration before
inclusion in the HHVBP Model measure set as described below.
Specifically, we are proposing to remove the following measures, as
described in Figure 4a of the CY 2016 HH PPS final rule, from the set
of applicable measures: (1) Care Management: Types and Sources of
Assistance; (2) Prior Functioning ADL/IADL; (3) Influenza Vaccine Data
Collection Period: Does this episode of care include any dates on or
between
[[Page 43751]]
October 1 and March 31?; and (4) Reason Pneumococcal Vaccine Not
Received. We are proposing to remove these four measures, for the
reasons discussed below, beginning with the CY 2016 Performance Year
(PY1) calculations, and believe this will not cause substantial change
in the first annual payment adjustment that will occur in CY 2018, as
each measure is equally weighted and will not be represented in the
calculations. The proposed revisions to the measure set, as set forth
in Table 31 would be applicable to each performance year subject to any
changes made through future rulemaking.
We are proposing to remove the ``Care Management: Types and Sources
of Assistance'' measure because (1) a numerator and denominator for the
measure were not made available in the CY2016 HH PPS final rule; and
(2) the potential OASIS items that could be utilized in the development
of the measure were not fully specified in the CY 2016 HH PPS final
rule. We want to further consider the appropriate numerator and
denominator for the OASIS data source before proposing the inclusion of
this measure in the HHVBP Model.
We are proposing to remove the ``Prior Functioning ADL/IADL''
measure because (1) the NQF endorsed measure (NQF0430) included in the
2016 HH PPS final rule does not apply to home health agencies; and (2)
the NQF endorsed measure (NQF0430) refers to a measure that utilizes
the AM-PAC (Activity Measure for Post-Acute Care) tool that is not
currently (and has never been) collected by home health agencies.
We are proposing to remove the ``Influenza Vaccine Data Collection
Period: Does this episode of care include any dates on or between
October 1 and March 31?'' measure because this datum element (OASIS
item M1041) is used to calculate another HHVBP measure ``Influenza
Immunization Received for Current Flu Season'' and was not designed as
an additional and separate measure of performance.
We are proposing to remove the ``Reason Pneumococcal Vaccine Not
Received'' measure because (1) these data are reported as an element of
the record for clinical decision making and inform agency policy (that
is, so that the agency knows what proportion of its patients did not
receive the vaccine because it was contraindicated (harmful) for the
patient or that the patient chose to not receive the vaccine); and (2)
this measure itemizes the reason for the removal of individuals for
whom the vaccine is not appropriate, which is already included in the
numerator of the ``Pneumococcal Polysaccharide Vaccine Ever Received''
measure also included in the HHVBP Model.
Because the starter set is defined as the quality measures selected
for the first year of the Model only, we propose to revise Sec.
484.315 to refer to ``a set of quality measures'' rather than ``a
starter set of quality measures'' and to revise Sec. 484.320 (a), (b),
(c), and (d) to remove the phrase ``in the starter set''. We are also
proposing to delete the definition of ``Starter set'' in Sec. 484.305
because that definition would no longer be used in the HHVBP Model
regulations following the proposed revisions to Sec. Sec. 484.315 and
484.320.
The proposed revised set of applicable measures is presented in
Table 31, which excludes the four measures we propose to be removed. We
propose that this measure set will be applicable to PY1 and each
subsequent performance year until such time that another set of
applicable measures, or changes to this measure set, are proposed and
finalized in future rulemaking. Moving forward, we plan to utilize an
implementation contractor who will invite a group of measure experts to
provide advice on the adjustment of the current measure set.
---------------------------------------------------------------------------
\21\ For more detailed information on the proposed measures
utilizing OASIS refer to the OASIS-C1/ICD-9, Changed Items & Data
Collection Resources dated September 3, 2014 available at
www.oasisanswers.com/LiteratureRetrieve.aspx?ID=215074.
For NQF endorsed measures see The NQF Quality Positioning System
available at https://www.qualityforum.org/QPS. For non-NQF measures
using OASIS see links for data tables related to OASIS measures at
https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HomeHealthQualityInits/HHQIQualityMeasures.html. For
information on HHCAHPS measures see https://homehealthcahps.org/SurveyandProtocols/SurveyMaterials.aspx.
Table 31--Proposed Measure Set for the HHVBP Model \21\
--------------------------------------------------------------------------------------------------------------------------------------------------------
NQS domains Measure title Measure type Identifier Data source Numerator Denominator
--------------------------------------------------------------------------------------------------------------------------------------------------------
Clinical Quality of Care........ Improvement in Outcome........... NQF0167........... OASIS (M1860)..... Number of home Number of home
Ambulation- health episodes health episodes
Locomotion. of care where the of care ending
value recorded on with a discharge
the discharge during the
assessment reporting period,
indicates less other than those
impairment in covered by
ambulation/ generic or
locomotion at measure-specific
discharge than at exclusions.
the start (or
resumption) of
care.
Clinical Quality of Care........ Improvement in Bed Outcome........... NQF0175........... OASIS (M1850)..... Number of home Number of home
Transferring. health episodes health episodes
of care where the of care ending
value recorded on with a discharge
the discharge during the
assessment reporting period,
indicates less other than those
impairment in bed covered by
transferring at generic or
discharge than at measure-specific
the start (or exclusions.
resumption) of
care.
Clinical Quality of Care........ Improvement in Outcome........... NQF0174........... OASIS (M1830)..... Number of home Number of home
Bathing. health episodes health episodes
of care where the of care ending
value recorded on with a discharge
the discharge during the
assessment reporting period,
indicates less other than those
impairment in covered by
bathing at generic or
discharge than at measure-specific
the start (or exclusions.
resumption) of
care.
Clinical Quality of Care........ Improvement in Outcome........... NA................ OASIS (M1400)..... Number of home Number of home
Dyspnea. health episodes health episodes
of care where the of care ending
discharge with a discharge
assessment during the
indicates less reporting period,
dyspnea at other than those
discharge than at covered by
start (or generic or
resumption) of measure-specific
care. exclusions.
[[Page 43752]]
Communication & Care Discharged to Outcome........... NA................ OASIS (M2420)..... Number of home Number of home
Coordination. Community. health episodes health episodes
where the of care ending
assessment with discharge or
completed at the transfer to
discharge inpatient
indicates the facility during
patient remained the reporting
in the community period, other
after discharge. than those
covered by
generic or
measure-specific
exclusions.
Efficiency & Cost Reduction..... Acute Care Outcome........... NQF0171........... CCW (Claims)...... Number of home Number of home
Hospitalization: health stays for health stays that
Unplanned patients who have begin during the
Hospitalization a Medicare claim 12-month
during first 60 for an unplanned observation
days of Home admission to an period. A home
Health. acute care health stay is a
hospital in the sequence of home
60 days following health payment
the start of the episodes
home health stay. separated from
other home health
payment episodes
by at least 60
days.
Efficiency & Cost Reduction..... Emergency Outcome........... NQF0173........... CCW (Claims)...... Number of home Number of home
Department Use health stays for health stays that
without patients who have begin during the
Hospitalization. a Medicare claim 12-month
for outpatient observation
emergency period. A home
department use health stay is a
and no claims for sequence of home
acute care health payment
hospitalization episodes
in the 60 days separated from
following the other home health
start of the home payment episodes
health stay. by at least 60
days.
Patient Safety.................. Improvement in Outcome........... NQF0177........... OASIS (M1242)..... Number of home Number of home
Pain Interfering health episodes health episodes
with Activity. of care where the of care ending
value recorded on with a discharge
the discharge during the
assessment reporting period,
indicates less other than those
frequent pain at covered by
discharge than at generic or
the start (or measure-specific
resumption) of exclusions.
care.
Patient Safety.................. Improvement in Outcome........... NQF0176........... OASIS (M2020)..... Number of home Number of home
Management of health episodes health episodes
Oral Medications. of care where the of care ending
value recorded on with a discharge
the discharge during the
assessment reporting period,
indicates less other than those
impairment in covered by
taking oral generic or
medications measure-specific
correctly at exclusions.
discharge than at
start (or
resumption) of
care.
Population/Community Health..... Influenza Process........... NQF0522........... OASIS (M1046)..... Number of home Number of home
Immunization health episodes health episodes
Received for during which of care ending
Current Flu patients (a) with discharge,
Season. received or transfer to
vaccination from inpatient
the HHA or (b) facility during
had received the reporting
vaccination from period, other
HHA during than those
earlier episode covered by
of care, or (c) generic or
was determined to measure-specific
have received exclusions.
vaccination from
another provider.
Population/Community Health..... Pneumococcal Process........... NQF0525........... OASIS (M1051)..... Number of home Number of home
Polysaccharide health episodes health episodes
Vaccine Ever during which of care ending
Received. patients were with discharge or
determined to transfer to
have ever inpatient
received facility during
Pneumococcal the reporting
Polysaccharide period, other
Vaccine (PPV). than those
covered by
generic or
measure-specific
exclusions.
Clinical Quality of Care........ Drug Education on Process........... NA................ OASIS (M2015)..... Number of home Number of home
All Medications health episodes health episodes
Provided to of care during of care ending
Patient/Caregiver which patient/ with a discharge
during all caregiver was or transfer to
Episodes of Care. instructed on how inpatient
to monitor the facility during
effectiveness of the reporting
drug therapy, how period, other
to recognize than those
potential adverse covered by
effects, and how generic or
and when to measure-specific
report problems exclusions.
(since the
previous OASIS
assessment).
Patient & Caregiver-Centered Care of Patients.. Outcome........... CAHPS............. NA................ NA.
Experience.
Patient & Caregiver-Centered Communications Outcome........... CAHPS............. NA................ NA.
Experience. between Providers
and Patients.
Patient & Caregiver-Centered Specific Care Outcome........... CAHPS............. NA................ NA.
Experience. Issues.
Patient & Caregiver-Centered Overall rating of Outcome........... CAHPS............. NA................ NA.
Experience. home health care.
Patient & Caregiver-Centered Willingness to Outcome........... CAHPS............. NA................ NA.
Experience. recommend the
agency.
[[Page 43753]]
Population/Community Health..... Influenza Process........... NQF0431 (Used in Reported by HHAs Healthcare Number of
Vaccination other care through Web personnel in the healthcare
Coverage for Home settings, not Portal. denominator personnel who are
Health Care Home Health). population who working in the
Personnel. during the time healthcare
from October 1 facility for at
(or when the least 1 working
vaccine became day between
available) October 1 and
through March 31 March 31 of the
of the following following year,
year: (a) regardless of
received an clinical
influenza responsibility or
vaccination patient contact.
administered at
the healthcare
facility, or
reported in
writing or
provided
documentation
that influenza
vaccination was
received
elsewhere: or (b)
were determined
to have a medical
contraindication/
condition of
severe allergic
reaction to eggs
or to other
components of the
vaccine or
history of
Guillain-Barre
Syndrome within 6
weeks after a
previous
influenza
vaccination; or
(c) declined
influenza
vaccination; or
(d) persons with
unknown
vaccination
status or who do
not otherwise
meet any of the
definitions of
the above-
mentioned
numerator
categories.
Population/Community Health..... Herpes zoster Process........... NA................ Reported by HHAs Total number of Total number of
(Shingles) through Web Medicare Medicare
vaccination: Has Portal. beneficiaries beneficiaries
the patient ever aged 60 years and aged 60 years and
received the over who report over receiving
shingles having ever services from the
vaccination?. received zoster HHA.
vaccine (shingles
vaccine).
Communication & Care Advance Care Plan. Process........... NQF0326........... Reported by HHAs Patients who have All patients aged
Coordination. through Web an advance care 65 years and
Portal. plan or surrogate older.
decision maker
documented in the
medical record or
documentation in
the medical
record that an
advanced care
plan was
discussed but the
patient did not
wish or was not
able to name a
surrogate
decision maker or
provide an
advance care plan.
--------------------------------------------------------------------------------------------------------------------------------------------------------
In the CY 2016 HH PPS final rule, we finalized that HHAs will be
required to begin reporting data on each of the three New Measures no
later than October 7, 2016 for the period July 2016 through September
2016 and quarterly thereafter. We now propose to require annual, rather
than quarterly reporting for one of the three New Measures, ``Influenza
Vaccination Coverage for Home Health Personnel,'' with the first annual
submission in April 2017 for PY2. Specifically, we are proposing to
require an annual submission in April for the prior 6-month reporting
period of October 1-March 31 to coincide with the flu season. Under
this proposal, for PY1, the HHA would report on this measure in October
2016 and January 2017. HHAs would report on this measure in April 2017
for PY2 and annually in April thereafter. We believe that changing the
reporting and submission periods for this measure from quarterly to
annually would avoid the need for HHAs to have to report zeroes in
multiple data fields for the two quarters (July through September, and
April through June) that fall outside of the parameters of the
denominator (October through March).
We are not proposing to change the quarterly reporting and
submission requirements as set forth in the CY 2016 HH PPS final rule
(80 FR 68674-68678) for the other two New Measures, ``Advanced Care
Planning'', and ``Herpes zoster (Shingles) vaccination: Has the patient
ever received the shingles vaccination?''
We are also proposing to increase the timeframe for submitting New
Measures data from seven calendar days (80 FR 68675-68678) to fifteen
calendar days following the end of each reporting period to account for
weekends and holidays.
We invite public comment on our proposals.
D. Appeals Process Proposal
In the CY 2016 HH PPS final rule (80 FR 68689), we stated that we
intended to propose an appeals mechanism in future rulemaking prior to
the application of the first payment adjustments scheduled for CY 2018.
We are proposing an appeals process for the HHVBP Model which includes
the period to review and request recalculation of both the Interim
Performance Reports and the Annual TPS and Payment Adjustment Reports,
as finalized in the CY 2016 HH PPS final rule (80 FR 68688-68689) and
subject to the modifications we are proposing here, and reconsideration
request process for the Annual TPS and Payment Adjustment Report only,
as described later in this section, which may only occur after an HHA
has first submitted a recalculation request for the Annual TPS and
Payment Adjustment Report.
As finalized in the CY 2016 HH PPS final rule, HHAs have the
opportunity to review their Interim Performance Report following each
quarterly posting. The Interim Performance Reports are posted on the
HHVBP Secure Portal quarterly, setting forth the HHA's measure scores
based on available data to date. The first Interim Performance Report
will be provided to all competing HHAs in July 2016 and will include
performance scores for the OASIS-based measures for the first quarter
of CY 2016. See Table 32 for data provided in each report. The
quarterly Interim Performance Reports
[[Page 43754]]
will provide competing HHAs with the opportunity to identify and
correct calculation errors and resolve discrepancies, thereby
minimizing challenges to the annual performance scores linked to
payment adjustment.
Competing HHAs also have the opportunity to review their Annual TPS
and Payment Adjustment Report. We will inform each competing HHA of its
TPS and payment adjustment percentage in an Annual TPS and Payment
Adjustment Report provided prior to the calendar year for which the
payment adjustment will be applied. The annual TPS will be calculated
based on the calculation of performance measures contained in the
Interim Performance Reports that have already been received by the HHAs
for the performance year.
We are proposing specific timeframes for the submission of
recalculation and reconsideration requests to ensure that the final
payment adjustment percentage for each competing Medicare-certified HHA
can be submitted to the Fiscal Intermediary Shared Systems in time to
allow for application of the payment adjustments beginning in January
of the following calendar year. We believe HHVBP payment adjustments
should be timely and that the appeals process should be designed so
that determinations on recalculations and reconsiderations can be made
in advance of the applicable payment year to reduce burden and
uncertainty for competing HHAs.
In this proposed rule, we are proposing to add new Sec. 484.335,
titled ``Appeals Process for the Home Health Value-Based Purchasing
Model,'' which would codify the recalculation request process finalized
in the CY 2016 HH PPS final rule and also a proposed reconsideration
request process for the Annual TPS and Payment Adjustment Report. The
first level of this appeals process would be the recalculation request
process, as finalized in the CY 2016 HH PPS final rule and subject to
the proposed modifications described later in this section. We are
proposing that the reconsideration request process for the Annual TPS
and Payment Adjustment Report would complete the appeals process, and
would be available only when an HHA has first submitted a recalculation
request for the Annual TPS and Payment Adjustment Report under the
process finalized in the CY 2016 HH PPS final rule, subject to the
modifications we are proposing here. We believe that this proposed
appeals process will allow the HHAs to seek timely corrections for
errors that may be introduced during the Interim Performance Reports
that could affect an HHA's payments.
To inform our proposal for an appeals process under the HHVBP Model
we reviewed the appeals policies for two CMS programs that are similar
in their program goals to the HHVBP Model, the Medicare Shared Savings
Program \22\ and Hospital Value-Based Purchasing Program,\23\ as well
as the appeals policy for the Comprehensive Care for Joint Replacement
Model \24\ that is being tested by the Center for Medicare and Medicaid
Innovation (CMMI).
---------------------------------------------------------------------------
\22\ Title 42--Public Health, Chapter IV--Centers for Medicare &
Medicaid Services, Department of Health and Human Services,
Subchapter B, Part 425--Medicare Shared Savings Program, Subpart I--
Reconsideration Review Process. (https://www.ecfr.gov/cgi-bin/text-idx?SID=880f6bd181904fc648f0e9a885103dba&mc=true&node=sp42.3.425.i&rgn=div6)
\23\ Title 42--Public Health, Chapter IV--Centers for Medicare &
Medicaid Services, Department of Health and Human Services,
Subchapter B, Part 412--Prospective Payment System for Inpatient
Hospital Services, Subpart I--Adjustments to the Base Operating DRG
Payment Amounts Under the Prospective Payment Systems for Inpatient
Operating Costs (https://www.ecfr.gov/cgi-bin/text-idx?SID=dd15db0a13792035b9b42b342270fad6&mc=true&node=sg42.2.412_1155_6412_1159.sg4&rgn=div7)
\24\ Title 42--Public Health, Chapter IV--Centers for Medicare &
Medicaid Services, Department of Health and Human Services,
Subchapter H--Health Care Infrastructure and Model Programs, Part
510-- Comprehensive Care for Joint Replacement Model. (https://www.ecfr.gov/cgi-bin/text-idx?SID=a18d6f5665d1fbf2e1ae955e1bf1b97c&mc=true&node=pt42.5.510&rgn=div5)
---------------------------------------------------------------------------
Under section 1115A(d) of the Act, there is no administrative or
judicial review under sections 1869 or 1878 of the Act or otherwise for
the following:
The selection of models for testing or expansion under
section 1115A of the Act.
The selection of organizations, sites or participants to
test those models selected.
The elements, parameters, scope, and duration of such
models for testing or dissemination.
Determinations regarding budget neutrality under section
1115A(b)(3) of the Act.
The termination or modification of the design and
implementation of a model under section 1115A(b)(3)(B) of the Act.
Decisions about expansion of the duration and scope of a
model under section 1115A(c) of the Act, including the determination
that a model is not expected to meet criteria described in section
1115A(c)(1) or (2) of the Act.
Table 32--HHVBP Model Performance Report Data Schedule
----------------------------------------------------------------------------------------------------------------
OASIS-Based measures Claims- and HHCAHPS-
Report type Publication date and new measures based measures
----------------------------------------------------------------------------------------------------------------
Interim Performance Scores.......... January................. 3 quarters of previous 2 quarters of previous
PY (9 months); [Jan- PY (6 months); [Jan-
Sept]. Jun].
Interim Performance Scores.......... April................... 12 months of previous 3 quarters of previous
PY [Jan-Dec]. PY (9 months); [Jan-
Sept].
Interim Performance Scores.......... July.................... 1st quarter of next PY 12 months of previous
(3 months); [Jan-Mar]. PY; [Jan-Dec].
Interim Performance Scores.......... October................. 2 quarters of next PY 1st quarter of next PY
(6 months); [Jan-Jun]. (3 months); [Jan-Mar].
-------------------------------------------------
Annual TPS and Payment Adjustment August.................. Entire 12 months of previous PY; [Jan-Dec].
Percentage.
-------------------------------------------------
Annual TPS and Payment Adjustment November................ Entire 12 months of previous PY [Jan-Dec] after
Percentage; (Final). all recalculations and reconsideration requests
processed.
----------------------------------------------------------------------------------------------------------------
[[Page 43755]]
1. Recalculation
HHAs may submit recalculation requests for both the Interim
Performance Reports and the Annual TPS and Payment Adjustment Report
via a form located on the HHVBP Secure Portal that is only accessible
to the competing HHAs. The request form would be entered by a person
who has legal authority to sign on behalf of the HHA and, as finalized
in the CY 2016 HH PPS final rule, must be submitted within 30 calendar
days of the posting of each performance report on the model-specific
Web site. For the reasons discussed later in this section, we are
proposing to change this policy to require that recalculation requests
for both the Interim Performance Report and the Annual TPS and Payment
Adjustment Report be submitted within 15 calendar days of the posting
of the Interim Performance Report and the Annual TPS and Payment
Adjustment Report on the HHVBP Secure Portal instead of 30 calendar
days.
For both the Interim Performance Reports and the Annual TPS and
Payment Adjustment Report, requests for recalculation must contain
specific information, as set forth in the CY 2016 HH PPS final rule (80
FR 68688). We are proposing that requests for reconsideration of the
Annual TPS and Payment Adjustment Report must also contain this same
information.
The provider's name, address associated with the services
delivered, and CMS Certification Number (CCN);
The basis for requesting recalculation to include the
specific quality measure data that the HHA believes is inaccurate or
the calculation the HHA believes is incorrect;
Contact information for a person at the HHA with whom CMS
or its agent can communicate about this request, including name, email
address, telephone number, and mailing address (must include physical
address, not just a post office box); and,
A copy of any supporting documentation the HHA wishes to
submit in electronic form via the model-specific Web page.
Following receipt of a request for recalculation of an Interim
Performance Report or the Annual TPS and Payment Adjustment Report, CMS
or its agent will:
Provide an email acknowledgement, using the contact
information provided in the recalculation request, to the HHA contact
notifying the HHA that the request has been received;
Review the request to determine validity, and determine
whether the recalculation request results in a score change, altering
performance measure scores or the HHA's TPS;
Conduct a review of quality data if recalculation results
in a performance score or TPS change, and recalculate the TPS using the
corrected performance data if an error is found; and,
Provide a formal response to the HHA contact, using the
contact information provided in the recalculation request, notifying
the HHA of the outcome of the review and recalculation process.
We anticipate providing this response as soon as administratively
feasible following the submission of the request.
We will not be responsible for providing HHAs with the underlying
source data utilized to generate performance measure scores because
HHAs have access to this data via the QIES system.
We are proposing that recalculation requests for the Interim
Performance Reports must be submitted within 15 calendar days of these
reports being posted on the HHVBP Secure Portal, rather than 30
calendar days as finalized in the CY 2016 HH PPS final rule. We believe
this would allow recalculations of the Interim Performance Reports
posted in July to be completed prior to the posting of the Annual TPS
and Payment Adjustment Report in August. We are proposing that
recalculation requests for the TPS or payment adjustment percentage
must be submitted within 15 calendar days of the Annual TPS and Payment
Adjustment Report being posted on the HHVBP Secure Portal, rather than
30 days as finalized in the CY 2016 HH PPS final rule. We are proposing
to shorten this timeframe to allow for a second level of appeals, the
proposed reconsideration request process, to be completed prior to the
generation of the final data files containing the payment adjustment
percentage for each competing Medicare-certified HHA and the submission
of those data files to the Fiscal Intermediary Share Systems. We
contemplated longer timeframes for the submission of both recalculation
and reconsideration requests for the Annual TPS and Payment Adjustment
Reports, but believe that this would result in appeals not being
resolved in advance of the payment adjustments being applied beginning
in January of the following calendar year. We invite comments on this
proposed timeframe for recalculation requests, as well as any
alternatives.
2. Reconsideration
We are proposing that if we determine that the calculation was
correct and deny the HHA request for recalculation of the Annual TPS
and Payment Adjustment Report, or if the HHA disagrees with the results
of a CMS recalculation of such report, the HHA may submit a
reconsideration request for the Annual TPS and Payment Adjustment
Report. The reconsideration request and supporting documentation would
be required to be submitted via the form on the HHVBP Secure Portal
within 15 calendar days of CMS' notification to the HHA contact of the
outcome of the recalculation request for the Annual TPS and Payment
Adjustment Report.
We propose that an HHA may request reconsideration of the outcome
of a recalculation request for its Annual TPS and Payment Adjustment
Report only. We believe that the ability to review the Interim
Performance Reports and submit recalculation requests on a quarterly
basis provides competing HHAs with a mechanism to address potential
errors in advance of receiving their annual TPS and payment adjustment
percentage. Therefore, we expect that in many cases, the
reconsideration request process proposed in this rule would result in a
mechanical review of the application of the formulas for the TPS and
the LEF, which could result in the determination that a formula was not
accurately applied. Reconsiderations would be conducted by a CMS
official who was not involved with the original recalculation request.
We are proposing that an HHA must submit the reconsideration
request and supporting documentation via the HHVBP Secure Portal within
15 calendar days of CMS' notification to the HHA contact of the outcome
of the recalculation process so that a decision on the reconsideration
can be made prior to the generation of the final data files containing
the payment adjustment percentage for each competing Medicare-certified
HHA and the submission of those data files to the Fiscal Intermediary
Share Systems. We believe that this would allow for finalization of the
interim performance scores, TPS, and annual payment adjustment
percentages in advance of the application of the payment adjustments
for the applicable performance year. As noted above, we contemplated
longer timeframes for the submission of both recalculation and
reconsideration requests, but believe this would result in appeals not
being resolved in advance of the payment adjustments being applied
beginning in January of the following calendar year. CMS invites
comments on its proposed timeframe for reconsideration requests, as
well as any alternatives.
[[Page 43756]]
We finalized in the CY 2016 HH PPS final rule (80 FR 68688) that
the final TPS and payment adjustment percentage would be provided to
competing HHAs in a final report no later than 60 calendar days in
advance of the payment adjustment taking effect. We are now proposing
that the final TPS and payment adjustment percentage be provided to
competing HHAs in a final report no later than 30 calendar days in
advance of the payment adjustment taking effect to account for
unforeseen delays that could occur between the time the Annual TPS and
Payment Adjustment Reports are posted and the appeals process is
completed.
We solicit comments on our proposals related to the appeals process
for the HHVBP Model described in this section and the associated
proposed regulation text at Sec. 484.335.
E. Public Display of Total Performance Scores for the HHVBP Model
In the CY 2016 HH PPS final rule (80 FR 68658), we stated that one
of the three goals of the HHVBP Model is to ``Enhance current public
reporting processes''. Annual publicly-available performance reports
would be a means of developing greater transparency of Medicare data on
quality and aligning the competitive forces within the market to
deliver care based on value over volume. The publicly-reported reports
will inform home health industry stakeholders (consumers, physicians,
hospitals) as well as all competing HHAs delivering care to Medicare
beneficiaries within selected state boundaries on their level of
quality relative to both their peers and their own past performance.
These public reports would provide home health industry stakeholders,
including providers and suppliers that refer their patients to HHAs, an
opportunity to confirm that the beneficiaries they are referring for
home health services are being provided the best possible quality of
care available.
We received support via public comments to publicly report the
HHVBP Model performance data because they would inform industry
stakeholders of quality improvements. These comments noted several
areas of value in performance data. Specifically, commenters suggested
that public reports would permit providers to direct patients to a
source of information about higher-performing HHAs based on quality
reports. Commenters offered that to the extent possible, accurate
comparable data will encourage HHAs to improve care delivery and
patient outcomes, while better predicting and managing quality
performance and payment updates. Although competing HHAs have direct
technical support and other tools to encourage best practices, we
believe public reporting of their Total Performance Score will
encourage providers and patients to utilize this information when
selecting a HHA to provide quality care.
We have employed a variety of means to ensure that we maintain
transparency while developing and implementing the HHVBP Model. This
same care is being taken as we plan public reporting in collaboration
with other CMS components that use many of the same quality measures.
We continue to engage and inform stakeholders about various aspects of
the HHVBP Model through CMS Open Door Forums and updates to the HHVBP
Model Innovation Center Web page (https://innovation.cms.gov/initiatives/home-health-value-based-purchasing-model). We have held
several webinars since December 2015 to educate competing HHAs. Topics
of the webinars ranged from an overview of the HHVBP Model to specific
content areas addressed in the CY 2016 HH PPS final rule. The primary
purpose of the focused attention provided to the competing HHAs through
the HHVBP learning systems and webinars is to facilitate direct
communication, sharing of information, and collaboration.
Section 1895(b)(3)(B)(v) of the Act requires HHAs to submit
patient-level quality of care data using the Outcome and Information
Assessment Set (OASIS) and the Home Health Consumer Assessment of
Health Care Providers and Systems (HHCAHPS). Section
1895(b)(3)(B)(v)(III) of the Act states that this quality data is to be
made available to the public. Thus, home health agencies have been
required to collect OASIS data since 1999 and report HHCAHPS data since
2012. Use of OASIS measures for the HHVBP Model logically follows, as
the validation through experience creates greater efficiency than
constructing an entirely new set of measures.
We are considering various public reporting platforms for the HHVBP
Model including Home Health Compare (HHC) and the Center for Medicare
and Medicaid Innovation (CMMI) Web page as a vehicle for maintaining
information in a centralized location and making information available
over the Internet. We believe the public reporting of competing HHAs'
performance scores under the HHVBP Model supports our continuing
efforts to empower consumers by providing more information to help them
make health care decisions, while also encouraging providers to strive
for higher levels of quality. As the public reporting mechanism for the
HHVBP Model is being developed, we are considering which data elements
reported will be meaningful to stakeholders and may inform the
selection of HHAs for care.
We are considering public reporting for the HHVBP Model, beginning
no earlier than CY 2019, to allow analysis of at least eight quarters
of performance data for the Model and the opportunity to compare how
those results align with other publicly reported quality data. We are
encouraged by the previous stakeholder comments and support for public
reporting that could assist patients, physicians, discharge planners,
and other referral sources to choose higher-performing HHAs.
V. Proposed Updates to the Home Health Care Quality Reporting Program
(HH QRP)
A. Background and Statutory Authority
Section 1895(b)(3)(B)(v)(II) of the Act requires that for 2007 and
subsequent years, each HHA submit to the Secretary in a form and
manner, and at a time, specified by the Secretary, such data that the
Secretary determines are appropriate for the measurement of health care
quality. To the extent that an HHA does not submit data in accordance
with this clause, the Secretary is directed to reduce the home health
market basket percentage increase applicable to the HHA for such year
by 2 percentage points. As provided at section 1895(b)(3)(B)(vi) of the
Act, depending on the market basket percentage for a particular year,
the 2 percentage point reduction under section 1895(b)(3)(B)(v)(I) of
the Act may result in this percentage increase, after application of
the productivity adjustment under section 1895(b)(3)(B)(vi)(I) of the
Act, being less than 0.0 percent for a year, and may result in payment
rates under the Home Health PPS for a year being less than payment
rates for the preceding year.
The Improving Medicare Post-Acute Care Transformation Act of 2014
(the IMPACT Act) imposed new data reporting requirements for certain
post-acute care (PAC) providers, including HHAs. For more information
on the statutory background of the IMPACT Act, please refer to the CY
2016 HH PPS final rule (80 FR 68690 through 68692).
In that final rule, we established our approach for identifying
cross-setting measures and processes for the adoption of measures,
including the application and purpose of the Measures Application
Partnership (MAP) and the notice and comment rulemaking process. More
information on the
[[Page 43757]]
IMPACT Act is also available at https://www.govtrack.us/congress/bills/113/hr4994.
In the CY 2016 HH PPS final rule (80 FR 68692), we also discussed
the reporting of OASIS data as it relates to the implementation of ICD-
10 on October 1, 2015. We submitted a new request for approval to OMB
for the OASIS-C1/ICD-10 version under the Paperwork Reduction Act (PRA)
process, including a new OMB control number (see 80 FR 15796). The new
information collection request for OASIS-C1/ICD-10 version was approved
under OMB control number 0938-1279 with a current expiration date of
May 31, 2018. To satisfy requirements in the IMPACT Act that HHAs
submit standardized patient assessment data in accordance with section
1899B(b) and to create consistency in the lookback period across
selected OASIS items, we have created a modified version of the OASIS,
OASIS-C2. We have submitted request for approval to OMB for the OASIS-
C2 version under the PRA process (81 FR 18855); also see https://www.cms.gov/Regulations-and-Guidance/Legislation/PaperworkReductionActof1995/PRA-Listing.html. The OASIS-C2 version will
replace the OASIS-C1/ICD-10 and will be effective for data collected
with an assessment completion date (M0090) on and after January 1,
2017. Information regarding the OASIS-C1/ICD-10 and C2 can be located
on the OASIS Data Sets Web page at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HomeHealthQualityInits/OASIS-Data-Sets.html.
B. General Considerations Used for the Selection of Quality Measures
for the HH QRP
We refer readers to the CY 2016 HH PPS final rule (80 FR 68695
through 68698) for a detailed discussion of the considerations we apply
in measure selection for the Home Health Quality Reporting Program (HH
QRP), such as alignment with the CMS Quality Strategy,\25\ which
incorporates the three broad aims of the National Quality Strategy.\26\
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 highest quality 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. Quality reporting programs (QRPs),
coupled with public reporting of quality information are critical to
the advancement of health care quality improvement efforts. Valid,
reliable, and 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.
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\25\ https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/QualityInitiativesGenInfo/CMS-Quality-Strategy.html.
\26\ https://www.ahrq.gov/workingforquality/nqs/nqs2011annlrpt.htm.
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In this proposed rule, we propose to adopt for the HH QRP one
measure that we are specifying under section 1899B(c)(1)(C) of the Act
to meet the Medication Reconciliation domain: (1) Drug Regimen Review
Conducted with Follow-Up for Identified Issues-Post-Acute Care Home
Health Quality Reporting Program (Drug Regimen Review Conducted with
Follow-Up for Identified Issues-PAC HH QRP). Further, we are proposing
to adopt for the HH QRP three measures to meet the ``Resource Use and
other Measures'' domains required by section 1899B(d)(1) of the Act:
(1) Total Estimated Medicare Spending per Beneficiary--Post Acute Care
Home Health Quality Reporting Program (MSPB-PAC HH QRP); (2) Discharge
to Community--Post Acute Care Home Health Quality Reporting Program
(Discharge to Community-PAC HH QRP); and (3) Potentially Preventable
30-Day Post-Discharge Readmission Measure for Post-Acute Care Home
Health Quality Reporting Program (Potentially Preventable 30-Day Post-
Discharge Readmission Measure for HH QRP).
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 pre-rulemaking
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 panels (TEPs) that included stakeholder experts and
patient representatives on July 29, 2015 for the Drug Regimen Review
Conducted with Follow-Up for Identified Issues-PAC HH QRP; on August
25, 2015, September 25, 2015, and October 5, 2015, for the Discharge to
Community-PAC HH QRP; on August 12-13, 2015, and October 14, 2015, for
the Potentially Preventable 30-Day Post-Discharge Readmission Measure
for HH QRP; and on October 29-30, 2015, for the MSPB-PAC HH QRP
measures. In addition, we released draft quality measure specifications
for public comment on the Drug Regimen Review Conducted with Follow-Up
for Identified Issues-PAC HH QRP from September 18, 2015 to October 6,
2015, for the Discharge to Community-PAC HH QRP from November 9, 2015
to December 8, 2015, for the Potentially Preventable 30-Day Post-
Discharge Readmission Measure for HH QRP from November 2, 2015 to
December 1, 2015, and for the MSPB-PAC HH QRP measures from January 13,
2016 to February 5, 2016. Further, we opened a public mailbox,
PACQualityInitiative@cms.hhs.gov, for the submission of public
comments. This PAC mailbox is accessible on our post-acute care quality
initiatives Web site, on the IMPACT Act of 2014 Data Standardization &
Cross Setting Measures Web page at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-of-2014-Data-Standardization-and-Cross-Setting-MeasuresMeasures.html.
Additionally, we sought public input from the MAP Post-Acute Care,
Long-Term Care Workgroup during the annual public meeting held December
14-15, 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 measure proposed in this rule for use in the HH QRP. For
more information on the MAP, we refer readers to the CY 2016 HH PPS
final rule (80 FR 68692 through 68694). Further, for more information
on the MAP's recommendations, we refer readers to the MAP 2015-2016
Considerations for Implementing Measures in Federal Programs public
report at https://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 HH QRP, we are proposing
measures for the HH QRP for the purposes of satisfying the measure
domains required under the IMPACT Act measures that most closely align
with the national priorities identified in the National Quality
Strategy (https://www.ahrq.gov/workingforquality/) and with respect to
which the MAP supports the measure concept. Further, we discuss below
the importance and high-priority status of
[[Page 43758]]
these proposed measures in the HH setting.
C. Process for Retaining, Removing, and Replacing Previously Adopted
Home Health Quality Reporting Program Measures for Subsequent Payment
Determinations
Consistent with the policies of other provider QRPs, including the
Hospital Inpatient Quality Reporting Program (Hospital IQR) (77 FR
53512 through 53513), the Hospital Outpatient Quality Reporting Program
(Hospital OQR) (77 FR 68471), the LTCH QRP (77 FR 53614 through 53615),
and the IRF QRP (77 FR 68500 through 68507), we are proposing that when
we initially adopt a measure for the HH QRP for a payment
determination, this measure will be automatically retained for all
subsequent payment determinations unless we propose to remove or
replace the measure, or unless the exception discussed below applies.
We are proposing to define the term ``remove'' to mean that the
measure is no longer a part of the HH QRP measure set, data on the
measure will no longer be collected for purposes of the HH QRP, and the
performance data for the measure will no longer be displayed on HH
Compare. We are also proposing to use the following criteria when
considering a quality measure for removal: (1) Measure performance
among HHAs is so high and unvarying that meaningful distinctions in
improvements in performance can no longer be made; (2) performance or
improvement on a measure does not result in better patient outcomes;
(3) a measure does not align with current clinical guidelines or
practice; (4) a more broadly applicable measure (across settings,
populations, or conditions) for the particular topic is available; (5)
a measure that is more proximal in time to desired patient outcomes for
the particular topic is available; and (6) a measure that is more
strongly associated with desired patient outcomes for the particular
topic is available. These items may still appear on OASIS for
previously established purposes that are non-related to our HH QRP.
HHAs will be able to access these reports using the Certification and
Survey Provider Enhanced Reports (CASPER) system and can use the
information for their own monitoring and quality improvement efforts.
Further, we are proposing to define ``replace'' to mean that we
would adopt a different quality measure in place of a currently used
quality measure, for one or more of the reasons described above.
Additionally, we are proposing that any such ``removal'' or
``replacement'' will take place through notice-and-comment rulemaking,
unless we determine that a measure is causing concern for patient
safety. Specifically, in the case of a HH QRP measure for which there
is a reason to believe that the continued collection raises possible
safety concerns or would cause other unintended consequences, we
propose to promptly remove the measure and publish the justification
for the removal in the Federal Register during the next rulemaking
cycle. In addition, we will immediately notify HHAs and the public
through the usual communication channels, including listening session,
memos, email notification, and Web postings. If we removed a measure
under these circumstances, we would also not continue to collect data
on that measure under our alternative authorities for purposes other
than the HH QRP.
We invite public comment on our proposed policy for retaining,
removing and replacing previously adopted quality measures, including
the criteria we propose to use when considering whether to remove a
quality measure from the HH QRP.
D. Quality Measures That Will Be Removed From the Home Health Quality
Initiative, and Quality Measures That Are Proposed for Removal From the
HH QRP Beginning With the CY 2018 Payment Determination
In 2015, we undertook a comprehensive reevaluation of all 81 HH
quality measures, some of which are used only in the Home Health
Quality Initiative (HHQI), and others which are also used in the HH
QRP. This review of all the measures was performed in accordance with
the guidelines from the CMS Measure Management System (MMS) (https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/MMS/MMS-Blueprint.html). The goal of this reevaluation was
to streamline the measure set, consistent with MMS guidance and in
response to stakeholder feedback. This reevaluation included a review
of the current scientific basis for each measure, clinical relevance,
usability for quality improvement, and evaluation of measure
properties, including reportability, and variability. Our measure
development and maintenance contractor convened a Technical Expert
Panel (TEP) on August 21, 2015, to review and advise on the
reevaluation results. The TEP provided feedback on which measures are
most useful for patients, caregivers, clinicians, and stakeholders, and
on analytics and an environmental scan conducted to inform measure set
revisions. Further information about the TEP feedback is available at
https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/MMS/Downloads/Health-Quality-Reporting-Program-HHQRP-TEP-.zip.
As a result of the comprehensive reevaluation described above, we
identified 28 HHQI measures that were either ``topped out'' and/or
determined to be of limited clinical and quality improvement value by
TEP members. Therefore, these measures will no longer be included in
the HHQI. A list of these measures, along with our reasons for no
longer including them in the HHQI, can be found at the following link
https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HomeHealthQualityInits/HHQIQualityMeasures.html.
In addition, based on the results of the comprehensive reevaluation
and the TEP input, we are proposing to remove 6 process measures from
the HH QRP, beginning with the CY 2018 payment determination, because
they are ``topped out'' and therefore no longer have sufficient
variability to distinguish between providers in public reporting. These
6 measures are different than the 28 measures that will no longer be
included within the HHQI. If this proposal is finalized, items used to
calculate one or more of these six measures may still appear on the
OASIS for previously established purposes that are not related to the
HH QRP.
The 6 process measures we are proposing to remove from the HH QRP
are:
Pain Assessment Conducted;
Pain Interventions Implemented During All Episodes of
Care;
Pressure Ulcer Risk Assessment Conducted;
Pressure Ulcer Prevention in Plan of Care;
Pressure Ulcer Prevention Implemented During All Episodes
of Care; and
Heart Failure Symptoms Addressed During All Episodes of
Care.
The technical analysis that supports our proposal to remove the six
process measures can be found at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HomeHealthQualityInits/HHQIQualityMeasures.html.
We invite public comment on our above proposal to remove 6 process
measures from the HH QRP.
E. Proposed Process for Adoption of Updates to HH QRP Measures
We believe that it is important to have in place a sub-regulatory
process to
[[Page 43759]]
incorporate non-substantive updates into the measure specifications so
that these measures remain up-to-date. We also recognize that some
changes are substantive in nature and might not be appropriate for
adoption using a sub-regulatory process.
Therefore, in the FY 2013 IPPS/LTCH PPS final rule (77 FR 53504
through 53505), we finalized a policy for the Hospital IQR Program
under which we use a subregulatory process to make nonsubstantive
updates to measures used for that program. For what constitutes
substantive versus nonsubstantive changes, we make this determination
on a case-by-case basis. Examples of nonsubstantive changes to measures
might include: Updated diagnosis or procedure codes, medication updates
for categories of medications, broadening of age ranges, and exclusions
for a measure. Nonsubstantive changes may also include updates to NQF-
endorsed measures based upon changes to guidelines upon which the
measures are based. Examples of changes that we might consider to be
substantive would be those in which: The changes are so significant
that the measure is no longer the same measure, or when a standard of
performance assessed by a measure becomes more stringent (for example,
changes in acceptable timing of medication, procedure/process, or test
administration). Another example of a substantive change might be where
the NQF has extended its endorsement of a previously endorsed measure
to a new setting, such as extending a measure from the inpatient
setting to hospice.
We are proposing to implement the same process for adopting updates
to measures in the HH QRP, and would apply this process, including our
policy for determining on a case-by-case basis whether an update is
substantive or nonsubstantive. We believe this process adequately
balances our need to incorporate updates to the HH QRP measures in the
most expeditious manner possible while preserving the public's ability
to comment on updates that do not fundamentally change a measure that
it is no longer the same measure that we originally adopted.
We invite public comment on this proposal.
F. Modifications to Guidance Regarding Assessment Data Reporting in the
OASIS
We are proposing modifications to our coding guidance modifications
related to certain pressure ulcer items on the OASIS. In the CY 2016 HH
PPS final rule (80 FR 68700), we adopted the NQF #0678 Percent of
Residents or Patients with Pressure Ulcers that are New or Worsened
(Short Stay) measure for use in the HH QRP for the CY 2018 HH QRP
payment determination and subsequent years. Concurrent with the
effective date for OASIS-C2 of January 1, 2017, we would use modified
guidance for the reporting of current pressure ulcers. The purpose of
this modification is to align with reporting guidance used in other
post-acute care settings and with the policies of relevant clinical
associations. Chapter 3 of the OASIS-C1/ICD-10 Guidance Manual
currently states ``Stage III and IV (full thickness) pressure ulcers
heal through a process of contraction, granulation, and
epithelialization. They can never be considered `fully healed' but they
can be considered closed when they are fully granulated and the wound
surface is covered with new epithelial tissue.'' We utilize
professional organizations, such as the National Pressure Ulcer
Advisory Panel (NPUAP) to provide clinical insight and expertise
related to the use and completion of relevant OASIS items. Based on the
currently published position statements and best practices available
from the NPUAP,\27\ effective January 1, 2017, full-thickness (Stage 3
or 4) pressure ulcers should not be reported on OASIS as unhealed
pressure ulcers once complete re-epithelialization has occurred. This
represents a change in past guidance, and will allow OASIS data
collection to conform to professional clinical guidelines, and align
with pressure ulcer reporting practices in other post-acute care
settings. In addition to revising guidance related to closed Stage 3
and 4 pressure ulcers, we are changing the reporting instructions when
a graft is applied to a pressure ulcer. Current guidance states that
when a graft is placed on a pressure ulcer, the wound remains a
pressure ulcer and is not concurrently reported as a surgical wound on
the OASIS. In order to align with reporting guidance in other post-
acute care settings, effective January 1, 2017, once a graft is applied
to a pressure ulcer, the wound will be reported on OASIS as a surgical
wound, and no longer be reported as a pressure ulcer.
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\27\ https://www.npuap.org/wp-content/uploads/2012/01/Reverse-Staging-Position-Statement.pdf.
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G. Proposed HH QRP Quality, Resource Use, and Other Measures for the CY
2018 Payment Determination and Subsequent Years
For the CY 2018 payment determination and subsequent years, in
addition to the quality measures we would retain if our proposed policy
on retaining measures is finalized, we are proposing to adopt four new
measures. These four measures were developed to meet the requirements
of the IMPACT Act. These proposed measures are:
MSPB-PAC HH QRP;
Discharge to Community-PAC HH QRP;
Potentially Preventable 30-Day Post-Discharge Readmission
Measure for HH QRP; and
Drug Regimen Review Conducted With Follow-Up for
Identified Issues-PAC HH QRP
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
agencies 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 agencies' results on our measures.
The NQF is currently undertaking a 2-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 2 years, NQF will conduct a trial of temporarily
allowing inclusion of sociodemographic factors in the risk-adjustment
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, 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.
[[Page 43760]]
1. Proposal To Address the IMPACT Act Domain of Resource Use and Other
Measures: MSPB-PAC HH QRP
Section 1899B(d)(1)(A) of the Act requires that no later than the
specified application date (which under section 1899B(a)(1)(E)(ii) is
October 1, 2016 for SNFs, IRFs and LTCHs and January 1, 2017 for HHAs),
the Secretary specify a measure to address the domain of resource use
measures, including total estimated Medicare spending per beneficiary.
We are proposing to adopt the measure, MSPB-PAC HH QRP, for which we
would begin to collect data on January 1, 2017 for the CY 2018 payment
determination and subsequent years as a Medicare fee-for-service (FFS)
claims-based measure to meet this requirement.
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 average 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.\28\ A study commissioned by the Institute of Medicine found
that variation in PAC spending explains 73 percent of variation in
total Medicare spending across the United States.\29\
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\28\ MedPAC, ``A Data Book: Health Care Spending and the
Medicare Program,'' (2015). 114.
\29\ Institute of Medicine, ``Variation in Health Care Spending:
Target Decision Making, Not Geography,'' (Washington, DC: National
Academies 2013). 2.
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We reviewed the NQF's consensus-endorsed measures and were unable
to identify any NQF-endorsed resource use measures for PAC settings.
Therefore, we are proposing to adopt this MSPB-PAC HH QRP measure under
section 1899B(e)(2)(B) of the Act, which allows us to specify a measure
under section 1899B that is not NQF-endorsed if the measure deals with
a specified area or medical topic the Secretary has determined to be
appropriate for which there is no feasible or practical NQF-endorsed
measure. We recognize that there are other measures that address
Medicare spending per beneficiary, but we are not aware of any such
measures that have been endorsed or adopted specifically for the home
health setting. Given the current lack of resource use measures for PAC
settings, our proposed MSPB-PAC HH QRP measure has the potential to
provide valuable information to HHAs on their relative Medicare
spending in delivering services to approximately 3.5 million Medicare
beneficiaries.\30\
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\30\ Figures for 2013. MedPAC, ``Medicare Payment Policy,''
Report to the Congress (2015). xvii-xviii.
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The proposed MSPB-PAC HH QRP episode-based measure would provide
actionable and transparent information to support HHAs' efforts to
promote care coordination and deliver high quality care at a lower cost
to Medicare. The MSPB-PAC HH QRP measure holds HHAs accountable for the
Medicare payments within an ``episode of care'' (episode), which
includes the period during which a patient is directly under the HHA's
care, as well as a defined period after the end of the HHA treatment,
which may be reflective of and influenced by the services furnished by
the HHA. MSPB-PAC HH QRP episodes, constructed according to the
methodology described below, have high levels of Medicare spending with
substantial variation. In FY 2014, Medicare FFS beneficiaries
experienced 5,379,410 MSPB-PAC HH QRP episodes triggered by admission
to a HHA. The mean payment-standardized, risk-adjusted episode spending
for these episodes was $10,348 during that fiscal year. There was
substantial variation in the Medicare payments for these MSPB-PAC HH
QRP episodes--ranging from approximately $2,480 at the 5th percentile
to approximately $31,964 at the 95th percentile. This variation was
partially driven by variation in payments occurring following HH
treatment.
Evaluating Medicare payments during an episode creates a continuum
of accountability between providers and has the potential to improve
post-treatment care planning and coordination. While some stakeholders
throughout the measure development process supported the MSPB-PAC
measures and believe that measuring Medicare spending is critical for
improving efficiency, others believe that resource use measures do not
reflect quality of care in that they do not take into account patient
outcomes or experience beyond those observable in claims data. However,
we believe that HHAs involved in the provision of high quality PAC care
as well as appropriate discharge planning and post-discharge care
coordination will perform well on this measure because beneficiaries
will 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 HHAs 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. In addition to this measure proposal, we proposed a
LTCH-specific MSPB-PAC measure in the FY 2017 IPPS/LTCH proposed rule
(81 FR 25216 through 25220), an IRF-specific MSPB-PAC measure in the FY
2017 IRF PPS proposed rule (81 FR 24197 through 24201), and a SNF-
specific MSPB-PAC measure in the FY 2017 SNF PPS proposed rule (81 FR
24258 through 24262). These 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, the MSPB-PAC HH QRP measure compares episodes triggered by
Partial Episode Payment (PEP) and Low-Utilization Payment Adjustment
(LUPA) claims only with episodes of the same type, as detailed below.
The MSPB-PAC measures mirror the general construction of the
inpatient prospective payment system (IPPS) hospital MSPB measure,
which was adopted for the Hospital IQR Program beginning with the FY
2014 program, and was implemented in the Hospital VBP Program beginning
with the FY 2015 program. The measure was endorsed by the NQF on
December 6, 2013 (NQF #2158).\31\ 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 hospital MSPB episode, which
comprises the periods immediately prior to, during, and following a
patient's hospital inpatient stay.32 33 Similarly, the MSPB-
PAC
[[Page 43761]]
measures assess all Medicare Part A and Part B payments for FFS claims
with a start date that begins at the episode trigger and continues for
the length of the episode window (which, as discussed in this section,
is the time period during which Medicare FFS Part A and Part B services
are counted towards the MSPB-PAC HH QRP episode). However, there are
differences between the MSPB-PAC measures, as proposed, and the
hospital MSPB measure that 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, for
clinically unrelated services) provided to a beneficiary during the
episode window while the hospital MSPB measure does not exclude any
services.\34\
---------------------------------------------------------------------------
\31\ QualityNet, ``Measure Methodology Reports: Medicare
Spending Per Beneficiary (MSPB) Measure,'' (2015). https://www.qualitynet.org/dcs/ContentServer?pagename=QnetPublic%2FPage%2FQnetTier3&cid=1228772053996.
\32\ QualityNet, ``Measure Methodology Reports: Medicare
Spending Per Beneficiary (MSPB) Measure,'' (2015). https://www.qualitynet.org/dcs/ContentServer?pagename=QnetPublic%2FPage%2FQnetTier3&cid=1228772053996.
\33\ FY 2012 IPPS/LTCH PPS final rule (76 FR 51619).
\34\ FY 2012 IPPS/LTCH PPS final rule (76 FR 51620).
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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. A home health episode beginning within 30 days of
discharge from an inpatient hospital will therefore be included: Once
in the hospital's MSPB measure, and once in the HHA'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/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/Downloads/Technical-Expert-Panel-on-Medicare-Spending-Per-Beneficiary.pdf. The measures were also presented to the MAP 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: Encourage continued development, do not encourage
further consideration, and insufficient information.\35\ The MAP PAC/
LTC Workgroup voted to ``encourage continued development'' for each of
the MSPB-PAC measures.\36\ The MAP PAC/LTC Workgroup's vote of
``encourage continued development'' was affirmed by the MAP
Coordinating Committee on January 26, 2016.\37\ The MAP's concerns
about the MSPB-PAC measures, as outlined in its final report, ``MAP
2016 Considerations for Implementing Measures in Federal Programs:
Post-Acute Care and Long-Term Care,'' and Spreadsheet of Final
Recommendations were taken into consideration during our measure
development process and are discussed as part of our responses to
public comments we received during the measure development process,
described below.38 39
---------------------------------------------------------------------------
\35\ National Quality Forum, Measure Applications Partnership,
``Process and Approach for MAP Pre-Rulemaking Deliberations, 2015-
2016'' (February 2016) https://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=81693.
\36\ National Quality Forum, Measure Applications Partnership
Post-Acute Care/Long-Term Care Workgroup, ``Meeting Transcript--Day
2 of 2'' (December 15, 2015) 104-106 https://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=81470.
\37\ National Quality Forum, Measure Applications Partnership,
``Meeting Transcript--Day 1 of 2'' (January 26, 2016) 231-232 https://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=81637.
\38\ National Quality Forum, Measure Applications Partnership,
``MAP 2016 Considerations for Implementing Measures in Federal
Programs: Post-Acute Care and Long-Term Care'' Final Report,
(February 2016) https://www.qualityforum.org/Publications/2016/02/MAP_2016_Considerations_for_Implementing_Measures_in_Federal_Programs_-_PAC-LTC.aspx.
\39\ National Quality Forum, Measure Applications Partnership,
``Spreadsheet of MAP 2016 Final Recommendations'' (February 1, 2016)
https://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=81593.
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Since the MAP's review and recommendation of continued development,
we have continued to refine the risk adjustment model and conduct
measure testing for the proposed MSPB-PAC measures. The proposed MSPB-
PAC 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. A total of 45 comments on
the MSPB-PAC measures were received during this 3.5 week period. The
comments received also covered each of the MAP's concerns as outlined
in their Final Recommendations.\40\ The MSPB-PAC Public Comment Summary
Report is available https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/Downloads/2016_03_24_mspb_pac_public_comment_summary_report.pdf and
contains the public comments. If finalized, the proposed MSPB-PAC HH
QRP measure, along with the other MSPB-PAC measures, as applicable,
will be submitted for NQF consideration of endorsement.
---------------------------------------------------------------------------
\40\ National Quality Forum, Measure Applications Partnership,
``Spreadsheet of MAP 2016 Final Recommendations'' (February 1, 2016)
https://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=81593.
---------------------------------------------------------------------------
To calculate the MSPB-PAC HH QRP measure for each HHA, we first
define the construction of the MSPB-PAC HH 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 in this section. More detailed
specifications for the proposed MSPB-PAC measures, including the MSPB-
PAC HH QRP measure in this proposed rule, are available at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/Downloads/2016_04_06_mspb_pac_measure_specifications_for_rulemaking.pdf.
a. Episode Construction
An MSPB-PAC HH QRP episode begins at the episode trigger, which is
defined as the patient's admission to a HHA. This admitting HHA is the
provider for whom the MSPB-PAC HH QRP measure is calculated (that is,
the attributed provider). The episode window is the time period during
which Medicare FFS Part A and Part B services are counted towards the
MSPB-PAC HH QRP episode. Because Medicare FFS claims are already
reported to the Medicare program for payment purposes, HHAs 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.
Our proposed MSPB-PAC HH QRP episode construction methodology
differentiates between episodes triggered by standard HH claims (for
which there is no PEP or LUPA adjustment) and claims for which PEP and
LUPA adjustments apply, reflecting the HHA PPS payment policy.
Standard, PEP, and LUPA episodes would be compared only with standard,
PEP and LUPA episodes, respectively. Differences in episode
construction
[[Page 43762]]
between these three episode types are noted below; they otherwise share
the same definition.
The episode window is comprised of a treatment period and an
associated services period. For MSPB-PAC HH Standard and LUPA QRP
episodes, the treatment period begins at the trigger (that is, on the
first day of the home health claim) and ends after 60 days. For MSPB-
PAC PEP QRP episodes, the treatment period begins at the trigger (that
is, on the first day of the home health claim) and ends at discharge.
The treatment period includes those services that are provided directly
or reasonably managed by the HHA 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 HH QRP episodes because they are clinically unrelated
to HHA care, and/or because HHAs may have limited influence over
certain Medicare services delivered by other providers during the
episode window. These limited service-level exclusions are not counted
towards a given HHA'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 a HHA 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 HH 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 HH QRP episode in the 30 days post-treatment. One
possible scenario occurs where a HHA discharges a beneficiary who is
then admitted to a SNF within 30 days. The SNF claim would be included
once as an associated service for the attributed provider of the first
MSPB-PAC HH QRP episode and once as a treatment service for the
attributed provider of the second MSPB-PAC SNF 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 HH setting, one MSPB-PAC HH QRP episode
may begin in the associated services period of another MSPB-PAC HH QRP
episode in the 30 days post-treatment. The second HH claim would be
included once as an associated service for the attributed HHA of the
first MSPB-PAC HH QRP episode and once as a treatment service for the
attributed HHA of the second MSPB-PAC HH QRP episode. Again, this
ensures that HHAs have the same incentives throughout both MSPB-PAC HH
QRP episodes to deliver quality care and engage in patient-focused care
planning and coordination. If the second MSPB-PAC HH QRP episode were
excluded from the second HHA's MSPB-PAC HH QRP measure, that HHA would
not share the same incentives as the first HHA of the first MSPB-PAC HH
QRP episode. The MSPB-PAC HH 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 HH QRP episodes, defined according to the
methodology previously discussed, are used to calculate the MSPB-PAC HH
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. The measure
calculation is performed separately for MSPB-PAC HH QRP standard, PEP,
and LUPA episodes to ensure that they are compared only to other
standard, PEP, and LUPA episodes, respectively. The final MSPB-PAC HH
QRP measure would combine the three ratios above to construct one HHA
score as described below.
(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 MSPB-PAC HH QRP measure to ensure that the MSPB-PAC HH QRP
measure accurately reflects resource use and facilitates fair and
meaningful comparisons between HHAs. The proposed episode-level
exclusions are as follows:
Any episode that is triggered by a HH claim outside the 50
states, DC, Puerto Rico, and U.S. territories.
Any episode where the claim(s) constituting the attributed
HHA 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
HHA 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 HH QRP measure are payment-standardized and risk-adjusted.
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
[[Page 43763]]
other add-on payments that support broader Medicare program goals
including indirect graduate medical education (IME) and hospitals
serving a disproportionate share of uninsured patients (DSH).\41\
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\41\ QualityNet, ``CMS Price (Payment) Standardization--Detailed
Methods'' (Revised May 2015) https://qualitynet.org/dcs/ContentServer?c=Page&pagename=QnetPublic%2FPage%2FQnetTier4&cid=1228772057350.
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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 HHA. To assist with risk adjustment for
MSPB-PAC HH 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 HH QRP episode. The
beneficiaries in these clinical case mix categories have a greater
degree of clinical similarity than the overall HHA patient population,
and allow us to more accurately estimate Medicare spending. Our
proposed MSPB-PAC HH QRP model, adapted for the HH 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. During
the public comment period that ran from January 13 to February 5, 2016
discussed above, we sought and considered public comment regarding the
treatment of hospice services occurring within the MSPB-PAC HH 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 HH QRP episodes with hospice are compared to a benchmark
reflecting other MSPB-PAC HH 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.
As noted previously, we understand the important role that
sociodemographic status, beyond age, 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 outcomes of
disadvantaged populations. We routinely monitor the impact of
sociodemographic status on providers' results on our measures.
The NQF is currently undertaking a 2-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 2 years, NQF will conduct a trial of temporarily
allowing inclusion of sociodemographic factors in the risk-adjustment
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 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 HH QRP risk-adjustment model, we are not
proposing to adjust the MSPB-PAC HH measure for socioeconomic and
demographic factors at this time. As this MSPB-PAC HH QRP measure will
be submitted to the NQF for consideration of 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 HH QRP measure.
(3) Measure Numerator and Denominator
The MPSB-PAC HH QRP measure is a payment-standardized, risk-
adjusted ratio that compares a given HHA's Medicare spending against
the Medicare spending of other HHAs 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 HH QRP measure is calculated as the ratio of the MSPB-
PAC Amount for each HHA divided by the episode-weighted median MSPB-PAC
Amount across all HHAs. To calculate the MSPB-PAC Amount for each HHA,
one calculates the average of the ratio of the standardized spending
for HHA standard episodes over the expected spending (as predicted in
risk adjustment) for HHA standard episodes, the average of the ratio of
the standardized spending for HHA PEP episodes over the expected
spending (as predicted in risk adjustment) for HHA PEP episodes, and
the average of the ratio of the standardized spending for HHA LUPA
episodes over the expected spending (as predicted in risk adjustment)
for HHA LUPA episodes. This quantity is then multiplied by the average
episode spending level across all HHAs nationally for standard, PEP,
and LUPA episodes. The denominator for a HHA's MSPB-PAC HH QRP measure
is the episode-weighted national median of the MSPB-PAC Amounts across
all HHAs. An MSPB-PAC HH QRP measure of less than 1 indicates that a
given HHA's Medicare spending is less than that of the national median
HHA during a performance period. Mathematically, this is represented in
equation (A) below:
[[Page 43764]]
[GRAPHIC] [TIFF OMITTED] TP05JY16.007
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[isin]{Ij{time} = all episodes i in the set of episodes
attributed to provider j.
a. Data Sources
The MSPB-PAC HH QRP resource use measure is an administrative
claims-based measure. It uses Medicare Part A and Part B claims from
FFS beneficiaries and Medicare eligibility files.
b. Cohort
The measure cohort includes Medicare FFS beneficiaries with a HHA
treatment period ending during the data collection period.
c. 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 2016.
We intend to publicly report this measure using claims data from
discharges in CY 2017. We are proposing a minimum of 20 episodes for
reporting and inclusion in the HH QRP. For the reliability calculation,
as described in the measure specifications provided above, we used data
from FY 2014. The reliability results support the 20 episode case
minimum, and 94.27 percent of HHAs had moderate or high reliability
(above 0.4).
We invite public comment on our proposal to adopt the MSPB-PAC HH
QRP measure for the HH QRP.
2. Proposal To Address the IMPACT Act Domain of Resource Use and Other
Measures: Discharge to Community-Post Acute Care Home Health Quality
Reporting Program
Section 1899B(d)(1)(B) of the Act requires that no later than the
specified application date (which under section 1899B(a)(1)(E)(ii) is
October 1, 2016 for SNFs, IRFs and LTCHs and January 1, 2017 for HHAs),
the Secretary specify a measure to address the domain of discharge to
community. We are proposing to adopt the measure, Discharge to
Community--PAC HH QRP for the HH QRP, beginning with the CY 2018
payment determination and subsequent years as a Medicare fee-for-
service (FFS) claims-based measure to meet this requirement.
This proposed measure assesses successful discharge to the
community from a HH setting, with successful discharge to the community
including no unplanned hospitalizations and no deaths in the 31 days
following discharge from the HH agency setting. Specifically, this
proposed measure reports a HHA's risk-standardized rate of Medicare FFS
patients who are discharged to the community following a HH episode, do
not have an unplanned admission to an acute care hospital or LTCH in
the 31 days following discharge to community, and remain alive during
the 31 days following discharge to community. The term ''community,''
for this measure, is defined as home/self-care, without home health
services, based on Patient Discharge Status Codes 01 and 81 on the
Medicare FFS claim.42 43 This measure is specified 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.
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\42\ 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.
\43\ 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.
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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 improvement during their HH episode and
for patients who may be expected to decline functionally due to their
medical condition. The discharge to community outcome offers a multi-
dimensional view of preparation for community life, including the
cognitive, physical, and psychosocial elements involved in a discharge
to the community.44 45
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\44\ El-Solh AA, Saltzman SK, Ramadan FH, Naughton BJ. Validity
of an artificial neural network in predicting discharge destination
from a post-acute geriatric rehabilitation unit. Archives of
physical medicine and rehabilitation. 2000;81(10):1388-1393.
\45\ 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.
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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 patients
discharged to institutional settings.46 47 Given the high
costs of care in institutional settings, encouraging post-acute
providers to prepare patients for discharge to community, when
clinically appropriate, may have cost-saving implications for the
Medicare program.\48\ Also, providers have discovered that successful
discharge to the community was a major driver of their ability to
achieve savings, where capitated payments for post-acute care were in
place.\49\ For patients who
[[Page 43765]]
require long-term care due to persistent disability, discharge to
community could result in lower long-term care costs for Medicaid and
for patients' out-of-pocket expenditures.\50\
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\46\ 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.
\47\ Gage B, Morley M, Spain P, Ingber M. Examining Post Acute
Care Relationships in an Integrated Hospital System Final Report.
RTI International;2009.
\48\ 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. Med Care.
2016 Mar;54(3):221-228.
\49\ 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.
\50\ 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. Med Care.
2016 Jan 12. Epub ahead of print.
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Analyses conducted for ASPE on PAC episodes, using a 5 percent
sample of 2006 Medicare claims, revealed that relatively high average,
unadjusted Medicare payments associated with discharge from IRFs, SNFs,
LTCHs, or HHAs to institutional settings, as compared with payments
associated with discharge from these PAC providers to community
settings.\51\ 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 non-community 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.\52\
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\51\ Gage B, Morley M, Spain P, Ingber M. Examining Post Acute
Care Relationships in an Integrated Hospital System. Final Report.
RTI International;2009.
\52\ Ibid.
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Measuring and comparing agency-level discharge to community rates
is expected to help differentiate among agencies 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), freestanding or hospital-based
units, and across patient-level characteristics such as race and
gender.53 54 55 56 57 58 In the HH Medicare FFS population,
using CY 2013 national claims data, we found that approximately 82
percent of episodes ended with a discharge to the community. A multi-
center study of 23 LTCHs demonstrated that 28.8 percent of 1,061
patients who were ventilator-dependent on admission were discharged to
home.\59\ A single-center study revealed that 31 percent of LTCH
hemodialysis patients were discharged to home.\60\ 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 \61\ and a second study noted
that between 58 percent and 63 percent of beneficiates were discharged
to home with rates varying by admission site.\62\ 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).\63\
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\53\ 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.
\54\ El-Solh AA, Saltzman SK, Ramadan FH, Naughton BJ. Validity
of an artificial neural network in predicting discharge destination
from a post-acute geriatric rehabilitation unit. Archives of
physical medicine and rehabilitation. 2000;81(10):1388-1393.
\55\ March 2015 Report to the Congress: Medicare Payment Policy.
Medicare Payment Advisory Commission;2015.
\56\ 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.
\57\ 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.
\58\ Berges IM, Kuo YF, Ostir GV, Granger CV, Graham JE,
Ottenbacher KJ. Gender and ethnic differences in rehabilitation
outcomes after hip-replacement surgery. American journal of physical
medicine & rehabilitation/Association of Academic Physiatrists.
2008;87(7):567-572.
\59\ 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.
\60\ 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.
\61\ 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.
\62\ Riggs JS, Madigan EA. Describing Variation in Home Health
Care Episodes for Patients with Heart Failure. Home Health Care
Management & Practice 2012; 24(3) 146-152.
\63\ Ibid.
---------------------------------------------------------------------------
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 post-acute
settings.64 65 66 67 68 Many of these interventions involve
discharge planning or specific rehabilitation strategies, such as
addressing discharge barriers and improving medical and functional
status.69 70 71 72 73 The 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.
---------------------------------------------------------------------------
\64\ 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.
\65\ 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.
\66\ 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.
\67\ 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.
\68\ Parker, E., Zimmerman, S., Rodriguez, S., & Lee, T.
Exploring best practices in home health care: a review of available
evidence on select innovations. Home Health Care Management and
Practice, 2014; 26(1): 17-33.
\69\ 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.
\70\ 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.
\71\ 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.
\72\ 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.
\73\ Parker, E., Zimmerman, S., Rodriguez, S., & Lee, T.
Exploring best practices in home health care: a review of available
evidence on select innovations. Home Health Care Management and
Practice, 2014; 26(1): 17-33.
---------------------------------------------------------------------------
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 HH QRP into the HH 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 page at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
[[Page 43766]]
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-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.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 HH QRP
measure in the HH QRP. The MAP encouraged continued development of the
proposed measure to meet the mandate of the IMPACT Act. 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 https://www.qualityforum.org/Publications/2016/02/MAP_2016_Considerations_for_Implementing_Measures_in_Federal_Programs_-_PAC-LTC.aspx.
Since the MAP review the measure and recommended continued
development, we have continued to refine the risk adjustment model and
conduct measure testing for this measure. This proposed measure is
consistent with the information submitted to the MAP and is
scientifically acceptable for current specification in the HH QRP.
We reviewed the NQF's consensus-endorsed measures and were unable
to identify any NQF-endorsed resource use or other measures for post-
acute care focused on discharge to the 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 HH QRP, under the Secretary's authority to specify non-
NQF-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 HH setting, using 2013 data, we found 97 percent
agreement in discharge to community codes when comparing ``Patient
Discharge Status Code'' from claims and Discharge Disposition (M2420)
and Inpatient Facility (M2410) on the OASIS C discharge assessment,
when the claims and OASIS assessment had the same discharge date. We
further examined the accuracy of ``Patient 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 found that
50 percent of HH claims with acute care discharge status codes were
followed by an acute care claim in the 31 days after HH discharge. We
believe these data support the use of the ``Patient Discharge Status
Code'' for determining discharge to a community setting for this
measure. In addition, the proposed measure has high feasibility because
all data used for measure calculation are derived from Medicare FFS
claims and eligibility files, which are already available to us.
Based on the evidence discussed above, we are proposing to adopt
the measure entitled, ``Discharge to Community-PAC HH QRP'', for the HH
QRP for the CY 2018 payment determination and subsequent years. This
proposed measure is calculated utilizing 2 years of data as defined
below. We are proposing a minimum of 20 eligible episodes in a given
HHA for public reporting of the proposed measure for that HHA. Since
Medicare FFS claims data are already reported to the Medicare program
for payment purposes, and Medicare eligibility files are also
available, HHAs 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 home health patients who are discharged to the community, do not
have an unplanned readmission to an acute care hospital or LTCH in the
31-day post-discharge observation window, and who remain alive during
the post-discharge observation window. The measure is risk-adjusted for
variables such as age and sex, principal diagnosis, comorbidities, and
ESRD status among other variables. For technical information about this
proposed measure, including information about the measure calculation,
risk adjustment, and denominator exclusions, we refer readers the
document titled Proposed Measure Specifications for Measures Proposed
in the CY 2017 HH QRP proposed rule, available at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HomeHealthQualityInits/HHQIQualityMeasures.html.
If this proposed measure is finalized, we intend to provide initial
confidential feedback to home health agencies, prior to the public
reporting of this measure, based on Medicare FFS claims data from
discharges in CYs 2015 and 2016. We intend to publicly report this
measure using claims data from discharges in CYs 2016 and 2017. We plan
to submit this proposed measure to the NQF for consideration for
endorsement.
We invite public comment on our proposal to adopt the measure,
Discharge to Community--PAC HH QRP for the HH QRP.
3. Proposal To Address the IMPACT Act Domain of Resource Use and Other
Measures: Potentially Preventable 30-Day Post-Discharge Readmission
Measure for Post-Acute Care Home Health Quality Reporting Program
Section 1899B(d)(1)(C) of the Act requires that no later than the
specified application date (which under section 1899B(a)(1)(E)(ii) is
October 1, 2016 for SNFs, IRFs and LTCHs and January 1, 2017 for HHAs),
the Secretary specify measures to address the domain of all-condition
risk-adjusted potentially preventable hospital readmission rates. We
are proposing the measure Potentially Preventable 30-Day Post-Discharge
Readmission Measure for HH QRP as a Medicare FFS claims-based measure
to meet this requirement beginning with the CY 2018 payment
determination.
The proposed measure assesses the facility-level risk-standardized
rate of unplanned, potentially preventable hospital readmissions for
Medicare FFS beneficiaries that take place within 30 days of a HH
discharge. The HH 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
[[Page 43767]]
readmissions include readmissions to a short-stay acute-care hospital
or a 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 HHAs. Because the
measure denominator is based on HH 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 HH 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 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.74 75 The MedPAC 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 30-day and
15-day readmissions and 84 percent of 7-day readmissions were
considered ``potentially preventable.'' \76\ 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 7-day readmissions.\77\ 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.\78\ 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.\79\ An analysis of data from a nationally representative
sample of Medicare FFS beneficiaries receiving home health services in
2004 show that home health patients receive significant amounts of
acute and post-acute services after discharge from home health care.
Within 30 days of discharge from home health, 29 percent of patients
were admitted to a hospital.\80\ Focusing on readmissions, Madigan and
colleagues studied 74,580 Medicare home health patients with a
rehospitalization within 30 days of the index hospital discharge. The
30-day rehospitalization rate was 26 percent with the largest
proportion related to a cardiac-related diagnosis (42 percent).\81\
Fewer studies have investigated potentially preventable readmission
rates from other post-acute care settings.
---------------------------------------------------------------------------
\74\ 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.
\75\ 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
\76\ MedPAC: Payment policy for inpatient readmissions, in
Report to the Congress: Promoting Greater Efficiency in Medicare.
Washington, DC, pp. 103-120, 2007. Available from https://www.medpac.gov/documents/reports/Jun07_EntireReport.pdf.
\77\ ibid.
\78\ ibid.
\79\ 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.
\80\ Wolff, J. L., Meadow, A., Weiss, C.O., Boyd, C.M., Leff, B.
Medicare Home Health Patients' Transitions Through Acute And Post-
Acute Care Settings.'' Medicare Care 11(46) 2008; 1188-1193.
\81\ Madigan, E. A., N. H. Gordon, et al. ``Rehospitalization in
a national population of home health care patients with heart
failure.'' Health Serv Res 47(6): 2013; 2316-2338.
---------------------------------------------------------------------------
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: Rehospitalization During the First 30 Days of Home
Health (NQF #2380), as well as similar measures for other PAC providers
(NQF #2502 for IRFs, NQF #2510 for SNFs NQF #2512 for LTCHs).\82\ These
measures are endorsed by the NQF, and the NQF-endorsed measure (NQF
#2380) was adopted into the HH QRP in the CY 2014 HH PPS final rule (80
FR 68691 through 68692). Note that these NQF-endorsed measures assess
all-cause unplanned readmissions.
---------------------------------------------------------------------------
\82\ National Quality Forum: All-Cause Admissions and
Readmissions Measures. pp. 1-319, April 2015. Available from https://www.qualityforum.org/Publications/2015/04/All-Cause_Admissions_and_Readmissions_Measures_-_Final_Report.aspx.
---------------------------------------------------------------------------
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 3M\TM\ algorithm for Potentially Preventable
Readmissions.83 84 85 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.86 87
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.88 89 90
---------------------------------------------------------------------------
\83\ 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 https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4195042/.
\84\ National Quality Forum: Prevention Quality Indicators
Overview. 2008.
\85\ MedPAC: Online Appendix C: Medicare Ambulatory Care
Indicators for the Elderly. pp. 1-12, prepared for Chapter 4, 2011.
Available from https://www.medpac.gov/documents/reports/Mar11_Ch04_APPENDIX.pdf?sfvrsn=0.
\86\ 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 https://www.medpac.gov/documents/contractor-reports/development-of-inpatient-rehabilitation-facility-quality-measures-potentially-avoidable-readmissions-community-discharge-and-functional-improvement.pdf?sfvrsn=0.
\87\ 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 https://www.medpac.gov/documents/contractor-reports/mar14_snfqualitymeasures_contractor.pdf?sfvrsn=0.
\88\ 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.
\89\ 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.
\90\ 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[hyphen]and
community[hyphen]based services waiver programs. J. Am. Geriatr.
Soc. 60(5):821-829, 2012. doi:10.1111/j.1532-5415.2012.03920.
---------------------------------------------------------------------------
Potentially Preventable Readmission Measure Definition: We
conducted a 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
[[Page 43768]]
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 CY 2017 HH QRP
proposed rule available at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HomeHealthQualityInits/HHQIQualityMeasures.html.
This proposed measure focuses on readmissions that are potentially
preventable and also unplanned. Similar to the Rehospitalization During
the First 30 Days of Home Health measure (NQF #2380), 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 https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/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 Measures Proposed in the CY
2017 HH QRP proposed rule available at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HomeHealthQualityInits/HHQIQualityMeasures.html.
The proposed measure, Potentially Preventable 30-Day Post-Discharge
Readmission Measure for HH 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 an agency-specific effect,
common to patients treated in each agency. This proposed measure is
calculated for each HHA based on the ratio of the predicted number of
risk-adjusted, unplanned, potentially preventable hospital readmissions
that occur within 30 days after an HH discharge, including the
estimated agency effect, to the estimated predicted number of risk-
adjusted, unplanned hospital readmissions for the same patients treated
at the average HHA. 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 HH episodes. The resulting rate is the risk-standardized
readmission rate (RSRR) of potentially preventable readmissions.
An eligible HH episode 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 risk-adjustment model for HHAs accounts for
demographic characteristics (age, sex, original reason for Medicare
entitlement), principal diagnosis during the prior proximal hospital
stay, body system specific surgical indicators, comorbidities, length
of stay during the patient's prior proximal hospital stay, intensive
care and coronary care unit (ICU and CCU) utilization, ESRD status, and
number of acute care hospitalizations in the preceding 365 days.
The proposed measure is calculated using 3 consecutive calendar
years of FFS data, in order to ensure the statistical reliability of
this measure for smaller agencies. In addition, we are proposing a
minimum of 20 eligible episodes for public reporting of the proposed
measure. For technical information about this proposed measure
including information about the measure calculation, risk adjustment,
and exclusions, we refer readers to our Proposed Measure Specifications
for Measures Proposed in the CY 2017 HH QRP proposed rule at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HomeHealthQualityInits/HHQIQualityMeasures.html.
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/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.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/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
The NQF-convened 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 https://www.qualityforum.org/Publications/2016/02/MAP_2016_Considerations_for_Implementing_Measures_in_Federal_Programs_-_PAC-LTC.aspx.
At the time of the MAP, 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 Rehospitalization
During the First 30 Days of Home Health Measure (NQF #2380) adopted
into the HH QRP.
We reviewed the NQF's consensus endorsed measures and were unable
to identify any NQF-endorsed measures focused on potentially
preventable
[[Page 43769]]
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 HH QRP under the
Secretary's authority to specify non-NQF-endorsed measures under
section 1899B(e)(2)(B) of the Act, for the HH QRP for the CY 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 3 calendar years of claims
data from discharges in CYs 2014, 2015 and 2016. We intend to publicly
report this proposed measure using claims data from CYs 2015, 2016 and
2017.
We are inviting public comment on our proposal to adopt the
measure, Potentially Preventable 30-Day Post-Discharge Readmission
Measure for HH QRP.
4. Proposal To Address the IMPACT Act Domain of Medication
Reconciliation: Drug Regimen Review Conducted With Follow-Up for
Identified Issues--Post-Acute Care Home Health Quality Reporting
Program
Section 1899B(c)(1)(C) of the Act requires that no later than the
specified application date (which under section 1899B(a)(1)(E)(i) is
October 1, 2018 for SNFs, IRFs and LTCHs and January 1, 2017 for HHAs),
the Secretary specify quality measures to address the domain of
medication reconciliation. We are proposing to adopt the quality
measure, Drug Regimen Review Conducted with Follow-Up for Identified
Issues--PAC HH QRP for the HH QRP as a patient-assessment based, cross-
setting quality measure to meet this requirement with data collection
beginning January 1, 2017, beginning with the CY 2018 payment
determination.
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 episodes in which a
drug regimen review was conducted at the start of care or resumption of
care and timely follow-up with a physician occurred each time potential
clinically significant medication issues were identified throughout
that episode. For this proposed quality measure, a drug regimen review
is defined as the review of all medications or drugs the patient is
taking in order to identify potential clinically significant medication
issues. This 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 agency identified and addressed each clinically
significant medication issue and if the agency 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.\91\ This measure is
applied uniformly across the PAC settings.
---------------------------------------------------------------------------
\91\ Institute of Medicine. Preventing Medication Errors.
Washington, DC: National Academies Press; 2006.
---------------------------------------------------------------------------
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). 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.\92\ The Joint Commission added medication reconciliation to its
list of National Patient Safety Goals (2005), suggesting that
medication reconciliation is an integral component of medication
safety.\93\ 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.\94\ There is universal
agreement that medication reconciliation directly addresses patient
safety issues that can result from medication miscommunication and
unavailable or incorrect information.95 96 97 98
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\92\ Leotsakos A., et al. Standardization in patient safety: The
WHO High 5s project. Int J Qual Health Care. 2014:26(2):109-116.
\93\ The Joint Commission. 2016 Long Term Care: National Patient
Safety Goals Medicare/Medicaid Certification-based Option.
(NPSG.03.06.01).
\94\ 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.
\95\ IHI. Medication Reconciliation to Prevent Adverse Drug
Events [Internet]. Cambridge, MA: Institute for Healthcare
Improvement; [cited 2016 Jan 11]. Available from: https://www.ihi.org/topics/adesmedicationreconciliation/Pages/default.aspx.
Leotsakos A., et al. Standardization in patient safety: The WHO High
5s project. Int J Qual Health Care. 2014:26(2):109-116.
\96\ The Joint Commission. 2016 Long Term Care: National Patient
Safety Goals Medicare/Medicaid Certification-based Option.
(NPSG.03.06.01).
\97\ 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.
\98\ The Joint Commission. 2016 Long Term Care: National Patient
Safety Goals Medicare/Medicaid Certification-based Option.
(NPSG.03.06.01).
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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,99 100 including
subsequent emergency room visits and re-hospitalizations. ADEs are
associated with an estimated $3.5 billion in annual health care costs
and 7,000 deaths annually.\101\
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\99\ 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.
\100\ 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.
\101\ Kohn L.T., Corrigan J.M., Donaldson M.S., ``To Err Is
Human: Building a Safer Health System,'' National Academies Press,
Washington, DC 1999
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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. 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.102 103 104 105 106 107
[[Page 43770]]
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.108 109
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\102\ Institute of Medicine. To err is human: Building a safer
health system. Washington, DC: National Academies Press; 2000.
\103\ Lesar T.S., Briceland L., Stein D.S. Factors related to
errors in medication prescribing. JAMA. 1997:277(4): 312-317.
\104\ 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.
\105\ 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.
\106\ 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.
\107\ 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.
\108\ Institute of Medicine. To err is human: Building a safer
health system. Washington, DC: National Academies Press; 2000
\109\ 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.
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There is strong evidence that medication discrepancies can occur
during transfers from acute care facilities to post-acute care
facilities. Discrepancies can occur when there is conflicting
information documented in the medical records. Almost one-third of
medication discrepancies have the potential to cause patient harm.\110\
Potential medication problems upon admission to HHAs have been reported
as occurring at a rate of 39 percent of reviewed charts \111\ and mean
medication discrepancies between 2.0 2.3 and 2.1 2.4.\112\ Similarly, medication discrepancies were noted as
patients transitioned from the hospital to home health settings.\113\
An estimated fifty percent of patients experienced a clinically
important medication error after hospital discharge in an analysis of
two tertiary care academic hospitals.\114\
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\110\ Wong, J.D.., et al. ``Medication reconciliation at
hospital discharge: Evaluating discrepancies.'' Annals of
Pharmacotherapy 42.10 (2008): 1373-1379.
\111\ Vink J., Morton D., Ferreri S. Medication-Related Problems
in the Home Care Setting. The Consultant Pharmacist. Vol 26 No 7
2011 478-484
\112\ Setter S.M., Corbett C.F., Neumiller J.J., Gates B.J., et
al. Effectiveness of a pharmacist-nurse intervention on resolving
medication discrepancies for patients transitioning from hospital to
home health care, Am J Health-Syst Pharm, vol. 66, pp. 2027-2031,
2009
\113\ Zillich A.J., Snyder M.E., Frail C.K., Lewis J.L., et al.
A Randomized, Controlled Pragmatic Trial of Telephonic Medication
Therapy Management to Reduce Hospitalization in Home Health Patient,
Health Services Research, vol. 49, no. 5, pp. 1537-1554, 2014.
\114\ Kripalani, Sunil, et al. ``Effect of a pharmacist
intervention on clinically important medication errors after
hospital discharge: A randomized trial. ``Annals of internal
medicine 157.1 (2012): 1-10.
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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.115 116 Hospital discharge has been
identified as a particularly high risk time point, with evidence that
medication reconciliation identifies high levels of
discrepancy.117 118 119 120 121 122 Also, there is evidence
that medication reconciliation discrepancies occur throughout the
patient stay.123 124 With respect to older patients who may
have multiple comorbid conditions and thus multiple medications,
transitions between acute and post-acute care settings can be further
complicated,\125\ and medication reconciliation and patient knowledge
(medication literacy) can be inadequate post-discharge.\126\ The
proposed quality measure, Drug Regimen Review Conducted with Follow-Up
for Identified Issues-PAC HH 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
settings each year. For example, in 2013, 3.2 million Medicare FFS
beneficiaries had a home health episode.
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\115\ 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.
\116\ Gandara, Esteban, et al. ``Deficits in discharge
documentation in patients transferred to rehabilitation facilities
on anticoagulation: Results of a system wide evaluation.'' Joint
Commission Journal on Quality and Patient Safety 34.8 (2008): 460-
463.
\117\ 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.
\118\ 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.
\119\ 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.
\120\ 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.
\121\ 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.
\122\ 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.
\123\ 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.
\124\ 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.
\125\ 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.
\126\ Hume K., Tomsik E. Enhancing Patient Education and
Medication Reconciliation Strategies to Reduce Readmission Rates.
Hosp Pharm; 2014; 49(2):112-114.
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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 HH
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 cross-setting 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-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.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/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
The NQF-convened MAP met on December 14 and 15, 2015, and provided
input on the use of this proposed quality measure, Drug Regimen Review
Conducted with Follow-Up for Identified Issues-PAC HH QRP. The MAP
encouraged continued development of the proposed quality measure for
the HH QRP to meet the mandate of 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 https://www.qualityforum.org/Setting_Priorities/Partnership/MAP_Final_Reports.aspx.
Since the MAP's review, we have continued to refine this proposed
[[Page 43771]]
measure in compliance with the MAP's recommendations. The proposed
measure is both consistent with the information submitted to the MAP
and supports its scientific acceptability for use in the HH QRP.
Therefore, we are proposing this measure for implementation in the HH
QRP as required by the IMPACT Act.
We reviewed the NQF's endorsed measures and identified one NQF-
endorsed cross-setting and quality measure related to medication
reconciliation, which applies to the SNF, LTCH, IRF, and HH 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 HH QRP, which reports the percentage of patient episodes in
which a drug regimen review was conducted at the time of admission and
that timely follow-up with a physician or physician-designee occurred
each time one or more potential clinically significant medication
issues were identified throughout that episode.
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 HH 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 HH
QRP, employs three standardized patient-assessment 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 HH QRP, requires the
identification of clinically potential medication issues at the
beginning, during and at the end of the patient's episode to capture
data on each patient's complete HH episode; 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 HH 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 time frame (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
time frame in which the follow-up would need to occur;
The proposed quality measure, Drug Regimen Review
Conducted with Follow-Up for Identified Issues-PAC HH 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; and
The proposed quality measure, Drug Regimen Review
Conducted with Follow-Up for Identified Issues-PAC HH QRP, would be
reported to HHAs 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 HH QRP, for the HH QRP for CY
2018 payment determination and subsequent years. We plan to submit the
quality measure to the NQF for consideration of endorsement.
The calculation of the proposed quality measure would be based on
the data collection of three standardized items that would be added to
the OASIS. The collection of data by means of the standardized items
would be obtained at start or resumption of care and end of care. For
more information about the data submission required for this proposed
measure, we refer readers to Section I. Form, Manner, and Timing of
OASIS Data Submission and OASIS Data for Annual Payment Update.
The standardized items used to calculate this proposed quality
measure will replace existing items currently used for data collection
within the OASIS. The proposed measure denominator is the number of
patient episodes with an end of care assessment during the reporting
period. The proposed measure numerator is the number of episodes in the
denominator where the medical record contains documentation of a drug
regimen review conducted at: (1) Start or resumption of care; and (2)
end of care with a look back through the home health patient episode
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 CY 2017 HH QRP proposed rule available at
https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HomeHealthQualityInits/HHQIQualityMeasures.html.
Data for the proposed quality measure, Drug Regimen Review
Conducted with Follow-Up for Identified Issues--PAC HH QRP, would be
collected using the OASIS with submission through the QIES 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 HH QRP for CY 2018 APU determination and subsequent years.
H. HH QRP Quality Measures and Measure Concepts Under Consideration for
Future Years
We invite public comment on the importance, relevance,
appropriateness, and applicability of each of the quality measures
listed in Table 33 for use in future years in the HH QRP.
[[Page 43772]]
[GRAPHIC] [TIFF OMITTED] TP05JY16.008
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 also considering application of two
IMPACT Act measures to the HH QRP, to assess the incidence of falls
with major injury and functional assessment and goals setting. We are
additionally considering application of four standardized functional
measures to the HH QRP; two that would assess change in function across
the HH episode and two that would assess actual function at discharge
relative to expected function. Finally, we are considering a measure
related to health and well-being, Percent of Residents or Patients Who
Were Assessed and Appropriately Given the Seasonal Influenza Vaccine
(Short Stay).
Based on input from stakeholders, we have identified additional
concept areas for potential future measure development for the HH QRP.
These include ``efficacy'' measures that pair processes, such as
assessment and care planning, with outcomes, such as emergency
treatment for injuries or increase in pain. The prevalence of mental
health and behavioral problems was identified as an option to address
outcomes for special populations. In addition, CMS is considering
development of measures that assess if functional abilities were
maintained during a care episode and composite measures that combine
multiple evidence-based processes. CMS invites feedback on the
importance, relevance, appropriateness, and applicability of these
measure constructs.
I. Form Manner and Timing of OASIS Data Submission and OASIS Data for
Annual Payment Update
1. Regulatory Authority
The HH conditions of participation (CoPs) at Sec. 484.55(d)
require that the
[[Page 43773]]
comprehensive assessment be updated and revised (including the
administration of the OASIS) no less frequently than: (1) The last 5
days of every 60 days beginning with the start of care date, unless
there is a beneficiary-elected transfer, significant change in
condition, or discharge and return to the same HHA during the 60-day
episode; (2) within 48 hours of the patient's return to the home from a
hospital admission of 24-hours or more for any reason other than
diagnostic tests; and (3) at discharge.
It is important to note that to calculate quality measures from
OASIS data, there must be a complete quality episode, which requires
both a Start of Care (initial assessment) or Resumption of Care OASIS
assessment and a Transfer or Discharge OASIS assessment. Failure to
submit sufficient OASIS assessments to allow calculation of quality
measures, including transfer and discharge assessments, is a failure to
comply with the CoPs.
HHAs are not required to submit OASIS data for patients who are
excluded from the OASIS submission requirements as described in the
December 23, 2005, final rule ``Medicare and Medicaid Programs:
Reporting Outcome and Assessment Information Set Data as Part of the
Conditions of Participation for Home Health Agencies'' (70 FR 76202).
As set forth in the CY 2008 HH PPS final rule (72 FR 49863), HHAs
that become Medicare certified on or after May 31 of the preceding year
are not subject to the OASIS quality reporting requirement nor any
payment penalty for quality reporting purposes for the following year.
For example, HHAs certified on or after May 31, 2014, are not subject
to the 2 percentage point reduction to their market basket update for
CY 2015. These exclusions only affect quality reporting requirements
and payment reductions, and do not affect the HHA's reporting
responsibilities as announced in the December 23, 2005 OASIS final
rules (70 FR 76202).
2. Home Health Quality Reporting Program Requirements for CY 2017
Payment and Subsequent Years
In the CY 2014 HH PPS final rule (78 FR 72297), we finalized a
proposal to consider OASIS assessments submitted by HHAs to CMS in
compliance with HH CoPs and Conditions for Payment for episodes
beginning on or after July 1, 2012, and before July 1, 2013, as
fulfilling one portion of the quality reporting requirement for CY
2014.
In addition, we finalized a proposal to continue this pattern for
each subsequent year beyond CY 2014. OASIS assessments submitted for
episodes beginning on July 1 of the calendar year 2 years prior to the
calendar year of the Annual Payment Update (APU) effective date and
ending June 30 of the calendar year one year prior to the calendar year
of the APU effective date; fulfill the OASIS portion of the HH QRP
requirement.
3. Previously Established Pay-for-Reporting Performance Requirement for
Submission of OASIS Quality Data
Section 1895(b)(3)(B)(v)(I) of the Act states that for 2007 and
each subsequent year, the home health market basket percentage increase
applicable under such clause for such year shall be reduced by 2
percentage points if a home health agency does not submit quality data
to the Secretary in accordance with subclause (II) for such a year.
This pay-for-reporting requirement was implemented on January 1, 2007.
In the CY 2016 HH PPS final rule (80 FR 68703 through 68705), we
finalized a proposal to define the quantity of OASIS assessments each
HHA must submit to meet the pay-for-reporting requirement. We designed
a pay-for-reporting performance system model that could accurately
measure the level of an HHA's submission of OASIS data. The performance
system is based on the principle that each HHA is expected to submit a
minimum set of two matching assessments for each patient admitted to
their agency. These matching assessments together create what is
considered a quality episode of care, consisting ideally of a Start of
Care (SOC) or Resumption of Care (ROC) assessment and a matching End of
Care (EOC) assessment.
Section 80 of Chapter 10 of the Medicare Claims Processing Manual
states, ``If a Medicare beneficiary is covered under an MA Organization
during a period of home care, and subsequently decides to change to
Medicare FFS coverage, a new start of care OASIS assessment must be
completed that reflects the date of the beneficiary's change to this
pay source.'' We wish to clarify that the SOC OASIS assessment
submitted when this change in coverage occurs will not be used in our
determination of a quality assessment for the purpose of determining
compliance with data submission requirements. In such a circumstance,
the original SOC or ROC assessment submitted while the Medicare
beneficiary is covered under an MA Organization would be considered a
quality assessment within the pay-for-reporting, APU, Quality
Assessments Only methodology. For further information on successful
submission of OASIS assessments, types of assessments submitted by an
HHA that fit the definition of a quality assessment, defining the
``Quality Assessments Only'' (QAO) formula, and implementing a pay-for-
reporting performance requirement over a 3-year period, please see the
CY 2016 HH PPS final rule (80 FR 68704 to 68705). HHAs must score at
least 70 percent on the QAO metric of pay-for-reporting performance
requirement for CY 2017 (reporting period July 1, 2015 to June 30,
2016), 80 percent for CY 2018 (reporting period July 1, 2016 to June
30, 2017) and 90 percent for CY 2019 (reporting period July 1, 2017 to
June 30, 2018) or be subject to a 2 percentage point reduction to their
market basket update for that reporting period.
In this proposed rule we are not proposing any additional policies
related to the pay-for-reporting performance requirement.
4. Proposed Timeline and Data Submission Mechanisms for Measures
Proposed for the CY 2018 Payment Determination and Subsequent Years
a. Claims Based Measures
The MSPB-PAC HH QRP, Discharge to Community--PAC HH QRP, and
Potentially Preventable 30-Day Post-Discharge Readmission Measure for
HH QRP, which we have proposed in this proposed rule, are Medicare FFS
claims-based 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 HHAs. As previously discussed in V.G., for the Discharge to
Community--PAC HH QRP measure we propose to use 2 years of claims data,
beginning with CYs 2015 and 2016 claims data to inform confidential
feedback and CYs 2016 and 2017 claims data for public reporting. For
the Potentially Preventable 30-Day Post-Discharge Readmission Measure
for HH QRP we propose to use 3 years of claims data, beginning with CY
2014, 2015 and 2016 claims data to inform confidential feedback reports
for HHAs, and CY 2015, 2016 and 2017 claims data for public reporting.
For the MSPB-PAC HH QRP measure, we propose to use one year of claims
data beginning with CY 2016 claims data to inform confidential feedback
reports for HHAs, and CY 2017 claims data for public reporting for the
HH QRP.
[[Page 43774]]
b. Assessment-Based Measures Using OASIS Data Collection
As discussed in section V.G of this proposed rule, for the proposed
measure, Drug Regimen Review Conducted with Follow-Up for Identified
Issues--PAC HH QRP, affecting CY 2018 payment determination and
subsequent years, we are proposing that HHAs would submit data by
completing data elements on the OASIS and then submitting the OASIS to
CMS through the QIES ASAP system beginning January 1, 2017. For more
information on HH QRP reporting through the QIES ASAP system, refer to
CMS Web site at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HomeHealthQualityInits/HHQIOASISUserManual.html.
We propose to use standardized data elements in OASIS C2 to
calculate the proposed measure: Drug Regimen Review Conducted with
Follow-Up for Identified Issues--PAC HH QRP. The data elements
necessary to calculate this measure using the OASIS are available on
our Web site at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HomeHealthQualityInits/HHQIQualityMeasures.html.
We invite public comments on the proposed HH QRP data collection
requirements for the proposed measure affecting CY 2018 payment
determination and subsequent years.
5. Proposed Timeline and Data Submission Mechanisms for the CY 2018
Payment Determination and Subsequent Years for New HH QRP Assessment-
Based Quality Measure
In the CY 2016 HH PPS final rule (80 FR 68695 through 68698) for
the FY 2018 payment determination, we finalized that HHAs must submit
data on the quality measure NQF #0678 Percent of Residents or Patients
with Pressure Ulcers that are New or Worsened (Short Stay) using CY
2017 data, for example, patients who are admitted to the HHA on and
after January 1, 2017, and discharged from the HHA up to and including
December 31, 2017. However, for CY 2018 APU purposes this timeframe
would be impossible to achieve, given the processes we have established
associated with APU determinations, such as the opportunity for
providers to seek reconsideration for determinations of non-compliance.
Therefore, for both the measure NQF #0678 Percent of Residents or
Patients with Pressure Ulcers that are New or Worsened (Short Stay)
that we finalized in the CY 2016 HH PPS rule, and the CY 2017 HH PPS
proposed measure, Drug Regimen Review Conducted with Follow-Up for
Identified Issues--PAC HH QRP, we propose that we would collect two
quarters of data for CY 2018 APU determination to remain consistent
with the January release schedule for the OASIS and to give HHAs
sufficient time to update their systems so that they can comply with
the new data reporting requirements, and to give us a sufficient amount
of time to determine compliance for the CY 2018 program. The proposed
use of two quarters of data for the initial year of quality reporting
is consistent with the approach we have used to implement new measures
in a number of other QRPs, including the LTCH, IRF, and Hospice QRPs in
which only one quarter of data was used.
We invite public comments on our proposal to adopt a calendar year
data collection time frame, using an initial 6-month reporting period
from January 1, 2017, to June 30, 2017 for CY 2018 payment
determinations, for the application of measure NQF #0678 Percent of
Residents or Patients with Pressure Ulcers that are New or Worsened
(Short Stay) that we finalized in the CY 2016 HH PPS rule, and the CY
2017 HH PPS proposed measure, Drug Regimen Review Conducted with
Follow-Up for Identified Issues--PAC HH QRP.
6. Data Collection Timelines and Requirements for the CY 2019 Payment
Determinations and Subsequent Years
In CY 2014 HH PPS final rule (78 FR 72297), we finalized our use of
a July 1-June 30 time frame for APU determinations. In alignment with
the previously established timeframe data collection for a given
calendar year APU determination time period, beginning with the CY 2019
payment determination, we propose for both the finalized measure, NQF
#0678 Percent of Residents or Patients with Pressure Ulcers that are
New or Worsened (Short Stay), and the proposed measure, Drug Regimen
Review Conducted with Follow-Up for Identified Issues--PAC HH QRP, to
use 12 months of data collection, specifically assessments submitted
July 1, 2017 through June 30, 2018, for the CY 2019 payment
determination. We further propose to continue to use the same 12-month
timeframe of July 1-June 30 for these measures for subsequent years for
APU determinations.
We invite comment on these proposals for the data collection
timelines and requirements.
7. Proposed Data Review and Correction Timeframes for Data Submitted
Using the OASIS Instrument
In addition, to remain consistent with the SNF, LTCH and IRF QRPs,
as well as to comply with the requirements of section of section
1899B(g) of the Act, we are also proposing to implement calendar year
provider review and correction periods for the OASIS assessment-based
quality measures implemented into the HH QRP in satisfaction of the
IMPACT Act, that is, finalized NQF #0678 Percent of Residents or
Patients with Pressure Ulcers that are New or Worsened (Short Stay) and
the proposed Drug Regimen Review Conducted with Follow-Up for
Identified Issues--PAC HH QRP. More specifically, we are proposing that
HHAs 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 Quality Measure reports) to calculate the measures.
During the time of data submission for a given quarterly reporting
period and up until the quarterly submission deadline, HHAs could
review and perform corrections to errors in the assessment data used to
calculate the measures and could request correction of measure
calculations. However, once the quarterly submission deadline occurs,
the data is ``frozen'' and calculated for public reporting and
providers can no longer submit any corrections. As laid out in Table
34, the first calendar year reporting quarter is January 1, 2017
through March 31, 2017. The final deadline for submitting corrected
data would be August 15, 2017 for CY Quarter 1, and subsequently and
sequentially, November 15, 2017 for CY 2017 Quarter 2, February 15,
2018 for CY 2017 Quarter 3 and May 15, 2018 for CY 2017 Quarter 4. We
note that this proposal to review and correct data does not replace
other requirements associated with timely data submission. We would
encourage HHAs 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.
[[Page 43775]]
[GRAPHIC] [TIFF OMITTED] TP05JY16.009
We invite public comments on our proposal to adopt a calendar year
data collection time frame, with a 4.5 month period of time for review
and correction beginning with CY 2017 for the measure NQF #0678 Percent
of Residents or Patients with Pressure Ulcers that are New or Worsened
(Short Stay) that we finalized in the CY 2016 HH PPS rule, and the CY
2017 HH PPS proposed measure, Drug Regimen Review Conducted with
Follow-Up for Identified Issues-PAC HH QRP for the HH QRP.
Further, we propose that the OASIS assessment-based measures
already finalized for adoption into the HH QRP follow a similar CY
schedule of data reporting using quarterly data collection/submission
reporting periods followed by 4.5 months during which providers will
have an opportunity to review and correct their data up until the
quarterly data submission deadlines as provided in Table 35 for all
reporting years unless otherwise specified. This policy would apply to
all proposed and finalized assessment-based measures in the HH QRP.
Table 35--Proposed CY Data Collection Submission Quarterly Reporting Periods, Quarterly Review and Correction
Periods and Data Submission Deadlines for Measures Specified in Satisfaction of the IMPACT Act in Subsequent
Years
----------------------------------------------------------------------------------------------------------------
Proposed quarterly
Proposed data review and correction
Proposed CY data collection quarter collection/submission periods and data Proposed correction
quarterly reporting submission quarterly deadlines *
period deadlines *
----------------------------------------------------------------------------------------------------------------
Quarter 1........................... January 1-March 31..... April 1-August 15..... August 15.
Quarter 2........................... April 1-June 30........ July 1-November 15.... November 15.
Quarter 3........................... July 1-September 30.... October 1-February 15. February 15.
Quarter 4........................... October 1-December 31.. January 1-May 15...... May 15.
----------------------------------------------------------------------------------------------------------------
*We note that the submission deadlines provided pertain to the correction of data and that the submission of
OASIS data must continue to adhere to all submission deadline requirements as imposed under the Conditions of
Participation.
We invite public comment on our use of CY quarterly data
collection/submission reporting periods with quarterly data submission
deadlines that follow a period of approximately 4.5 months of time to
enable the review and correction of such data for OASIS assessment-
based measures.
J. Public Display of Quality Measure Data for the HH QRP and Procedures
for the Opportunity To Review and Correct Data and Information
Medicare home health regulations, as codified at Sec. 484.250(a),
require HHAs to submit OASIS assessments and Home Health Care Consumer
Assessment of Healthcare Providers and Systems Survey[supreg] (HHCAHPS)
data to meet the quality reporting requirements of section
1895(b)(3)(B)(v) of the Act. Section 1899B(g) of the Act requires that
data and information of provider performance on quality measures and
resource use and other measures be made publicly available beginning
not later than 2 years after the applicable specified application date.
In future rulemaking, we intend to propose a policy to publicly display
performance information for individual HHAs on IMPACT Act measures, as
required under the Act. In addition, sections 1895(b)(3)(B)(v)(III) and
1899B(g) of the Act require the Secretary to establish procedures for
making data submitted under subclause (II) available to the
[[Page 43776]]
public. Under section 1899B(g)(2), such 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 a
home health agency has the opportunity to review and submit corrections
to its data and information that are to be made public for the agency
prior to such data being made public through a process consistent with
the Hospital Inpatient Quality Reporting Program (Hospital IQR). We
recognize that public reporting of quality data is a vital component of
a robust quality reporting program and are fully committed to ensuring
that the data made available to the public are meaningful. Further, we
agree that measures for comparing performance across home health
agencies requires should be constructed from data collected in a
standardized and uniform manner. In this proposed rule, we are
proposing procedures that would allow individual HHAs to review and
correct their data and information on IMPACT Act measures that are to
be made public before those measure data are made public.
1. Proposals for the Review and Correction of Data Used To Calculate
the Assessment-Based Measures Prior to Public Display
As provided in section V.I.7., and in Table 34, for assessment-
based measures, we are proposing to provide confidential feedback
reports to HHAs that contain performance information that the HHAs can
review, during the review and correction period, and correct the data
used to calculate the measures for the HH QRP that the HHA submitted
via the QIES ASAP system. In addition, during the review period, the
HHA 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 HHA using the Certification and Survey Provider
Enhanced Reporting (CASPER) System. We refer to these reports as the HH
Quality Measure (QM) Reports. We intend to provide monthly updates to
the data contained in these reports that pertain to assessment-based
data, as data become available. The reports will contain both agency-
and patient-level data used to calculate the assessment-based quality
measures. The CASPER facility level QM reporting would include the
numerator, denominator, agency rate, and national rate. The CASPER
patient-level QM Reports would also contain individual patient
information that HHAs can use to identify patients that were included
in the quality measures so as to identify any potential errors. In
addition, we would make other reports available to HHAs through the
CASPER System, including OASIS data submission reports and provider
validation reports, which would contain information on each HHA's data
submission status, including details on all items the HHA submitted in
relation to individual assessments and the status of the HHA's
assessment (OASIS) records that they submitted. When available,
additional information regarding the content and availability of these
confidential feedback reports would be provided on the HH QRP Web site
https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HomeHealthQualityInits/.
As previously proposed in section V.I.7., for those measures that
use assessment-based data, HHAs would have 4.5 months after the
conclusion of each reporting quarter to review and update their
reported measure data for the quarter, including correcting any errors
that they find on the CASPER-generated Review and Correct, QM reports
pertaining to their assessment-based data used to calculate the
assessment-based measures. However, at the conclusion of this 4.5 month
review and correction period, the data reported for that quarter would
be ``frozen'' and used to calculate measure rates for public reporting.
We would encourage HHAs to submit timely assessment data during each
quarterly reporting period and to review their data and information
early during the 4.5 month review and correction period so they can
identify errors and resubmit data before the data submission deadline.
We believe that the proposed data submission period along with a
review and correction period, consisting of the reporting quarter plus
approximately 4.5 months, is sufficient time for HHAs to submit, review
and, where necessary, correct their data and information. We also
propose that, in addition to the data submission/correction and review
period, HHAs will have a 30-day preview period prior to public display
during which they can preview the performance information on their
measures that will be made public. We also propose to provide this
preview report using the Certification and Survey Provider Enhanced
Reporting (CASPER) System because HHAs are familiar with this system.
The CASPER preview reports for the reporting quarter would be available
after the 4.5 month review and correction period ends, and would be
refreshed quarterly or annually for each measure, depending on the
length of the reporting period for that measure. We propose to give
HHAs 30 days to review this information, beginning from the date on
which they can access the preview report. Corrections to the underlying
data would not be permitted during this time; however, HHAs would be
able to ask for a correction to their measure calculations during the
30-day preview period. If we determine that the measure, as it is
displayed in the preview report, contains a calculation error, we would
suppress the data on the public reporting Web site, recalculate the
measure and publish the corrected rate at the time of the next
scheduled public display date. This process is consistent with informal
processes used in the Hospital IQR program. If finalized, we intend to
utilize a subregulatory mechanism, such as our HH QRP Web site, to
explain the technical details for how and when providers may contest
their measure calculations. We further propose to increase the current
preview period of 15 days to 30 days beginning with the public display
of the measures finalized for the CY 2018 payment determination. This
preview period would include all measures that are to be publicly
displayed under the current quarterly refresh schedule used for posting
quality measure data on the Medicare.gov Home Health Compare site.
We invite public comment on these proposals.
2. Proposals for Review and Correction of Data Used To Calculate
Claims-Based Measures Prior To Public Display
In addition to assessment-based measures, we have also proposed
claims-based measures for the HH QRP. As noted previously, 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 procedures, for
claims-based measures, we give hospitals 30 days to preview their
claims-based measures and data in a preview report containing aggregate
hospital-level data. We propose to adopt a similar process for the HH
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
[[Page 43777]]
to their claims-based measure rate calculations, including agency and
national rates. 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 rates.
We propose to create data extracts using claims data for these
claims based measures, at least 90 days after the last discharge date
in the applicable period (12 calendar months preceding), 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, 2017, 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 the 2017
reporting period. We propose that beginning with data for measures that
will be publicly displayed by January 1, 2019, and for which will need
to coincide with the quarterly refresh schedule on Home Health Compare,
the claims-based measures will be calculated at least 90 days after the
last discharge date using claims data from the applicable reporting
period. This timeframe allows us to balance the need to provide timely
program information to HHAs with the need to calculate the claims-based
measures using as complete a data set as possible. Since HHAs would not
be able to submit corrections to the underlying claims snapshot or add
claims (for those measures that use HH claims) to this data set, at the
conclusion of the 90-day period following the last date of discharge
used in the applicable period, we would consider the HH claims data to
be complete for purposes of calculating the claims-based measures. We
wish to convey the importance that HHAs ensure the completeness and
correctness of their claims prior to the claims ``snapshot''. We seek
to have as complete a data set as possible. We recognize that the
proposed approximately 90 day ``run-out'' period 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 approximately 90 day run-out period is appropriate to
calculate the claims-based 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, and/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 HHAs sooner than 18 to 24 months
after the last discharge. We believe this would create an unacceptably
long delay, both for HHAs and for us to deliver timely calculations to
HHAs for quality improvement.
As noted, under this proposed procedure, during the 30-day preview
period, HHAs would not be able to submit corrections to the underlying
claims data or add new claims to the data extract. This is for two
reasons. First, for certain measures, some of the claims data used to
calculate the measure are derived not from the HHA's claims, but from
the claims of another provider. For example, the proposed measure
Potentially Preventable 30-Day Post-Discharge Readmission Measure for
HH QRP uses claims data submitted by the hospital to which the patient
was readmitted. HHAs are not able to make corrections to these hospital
claims, although the agency could request that the hospital reconfirm
that its submissions are correct. Second, even where HHA claims are
used to calculate the measures, it would 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.
As noted previously, we propose to provide HHAs a 30-day preview
period to review their confidential preview reports. HHAs would have 30
days from the date the preview report is made available to review this
information. The 30-day preview period would be the only time when HHAs
would be able to see their claims-based measure rates before they are
publicly displayed. HHAs could request that we correct our measure
calculation during the 30-day preview period if the HHA believes the
measure rate is incorrect. If we agree that the measure rate, as it is
displayed in the preview report, contains a calculation error, we would
suppress the data on the public reporting Web site, recalculate the
measure, and publish the corrected measure rate at the time of the next
scheduled public display date. If finalized, we intend to utilize a
subregulatory mechanism, such as our HH QRP Web site, to explain the
technical details regarding how and when providers may contest their
measure calculations. We refer readers to the discussion inV.I.2 for
additional information on these preview reports.
In addition, because the claims-based measures used for the HH QRP
are re-calculated on an annual basis, these confidential CASPER QM
preview reports for claims-based measures would be refreshed annually.
An annual refresh is being utilized to ensure consistency in our
display of claims based measures, and it will include both claims-based
measures that satisfy the IMPACT Act, as well as all other HH QRP
claims-based measures.
We invite public comment on these proposals for the public display
of quality measure data.
K. Mechanism for Providing Feedback Reports to HHAs
Section 1899B(f) of the Act requires the Secretary to provide
confidential feedback measure reports to post-acute care providers on
their performance on the measures specified under paragraphs (c)(1) and
(d)(1), beginning 1 year after the specified application date that
applies to such measures and PAC providers. We propose to build upon
the current confidential quality measure reports we already generate
for HHAs so as to also provide data and information on the measures
implemented in satisfaction of the IMPACT Act. As a result, HHAs could
review their performance on these measures, as well as those already
adopted in the HH QRP. We propose that these additional confidential
feedback reports would be made available to each HHA through the CASPER
System. Data contained within these CASPER reports would be updated, as
previously described, on a monthly basis as the data become available
except for claims-based measures, which will only be updated on an
annual basis.
We intend to provide detailed procedures to HHAs on how to obtain
their new confidential feedback reports in CASPER on the HH QRP Web
site at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HomeHealthQualityInits/Home-Health-Quality-Reporting-Requirements.html. We also propose to use the QIES ASAP
system to provide these new confidential quality measure reports in a
manner consistent with how HHAs have obtained such reports to date. The
QIES ASAP system is a confidential and secure system with access
granted to providers, or their designees.
We invite public comment on this proposal to satisfy the
requirement to provide confidential feedback reports to
[[Page 43778]]
HHAs specific to the requirements of the Act.
L. Home Health Care CAHPS[supreg] Survey (HHCAHPS)
In the CY 2016 HH PPS final rule (80 FR 68623), we stated that the
home health quality measures reporting requirements for Medicare-
certified agencies includes the Home Health Care CAHPS[supreg]
(HHCAHPS) Survey for the CY 2017 and 2018 Annual Payment Update (APU)
periods. We are continuing to maintain the stated HHCAHPS data
requirements for CY 2017 and CY 2018 that were stated in CY 2016 and in
previous HH PPS rules, for the continuous monthly data collection and
quarterly data submission of HHCAHPS data.
1. Background and Description of HHCAHPS
As part of the HHS Transparency Initiative, we implemented a
process to measure and publicly report patient experiences with home
health care, using a survey developed by the Agency for Healthcare
Research and Quality's (AHRQ's) Consumer Assessment of Healthcare
Providers and Systems (CAHPS[supreg]) program and endorsed by the
National Quality Forum (NQF) in March 2009 (NQF Number 0517) and NQF
re-endorsed in 2015. The HHCAHPS Survey is approved under OMB Control
Number 0938-1066. The HHCAHPS survey is part of a family of
CAHPS[supreg] surveys that asks patients to report on and rate their
experiences with health care. The Home Health Care CAHPS[supreg]
(HHCAHPS) survey presents home health patients with a set of
standardized questions about their home health care providers and about
the quality of their home health care.
Prior to this survey, there was no national standard for collecting
information about patient experiences that enabled valid comparisons
across all HHAs. The history and development process for HHCAHPS has
been described in previous rules and is also available on the official
HHCAHPS Web site at https://homehealthcahps.org and in the annually-
updated HHCAHPS Protocols and Guidelines Manual, which is downloadable
from https://homehealthcahps.org.
Since April 2012, for public reporting purposes, we report five
measures from the HHCAHPS Survey--three composite measures and two
global ratings of care that are derived from the questions on the
HHCAHPS survey. The publicly reported data are adjusted for differences
in patient mix across HHAs. We update the HHCAHPS data on Home Health
Compare on www.medicare.gov quarterly. Each HHCAHPS composite measure
consists of four or more individual survey items regarding one of the
following related topics:
Patient care (Q9, Q16, Q19, and Q24);
Communications between providers and patients (Q2, Q15,
Q17, Q18, Q22, and Q23); and
Specific care issues on medications, home safety, and pain
(Q3, Q4, Q5, Q10, Q12, Q13, and Q14).
The two global ratings are the overall rating of care given by the
HHA's care providers (Q20), and the patient's willingness to recommend
the HHA to family and friends (Q25).
The HHCAHPS survey is currently available in English, Spanish,
Chinese, Russian, and Vietnamese. The OMB number on these surveys is
the same (0938-1066). All of these surveys are on the Home Health Care
CAHPS[supreg] Web site, https://homehealthcahps.org. We continue to
consider additional language translations of the HHCAHPS in response to
the needs of the home health patient population.
All of the requirements about home health patient eligibility for
the HHCAHPS survey and conversely, which home health patients are
ineligible for the HHCAHPS survey are delineated and detailed in the
HHCAHPS Protocols and Guidelines Manual, which is downloadable at
https://homehealthcahps.org. Home health patients are eligible for
HHCAHPS if they received at least two skilled home health visits in the
past 2 months, which are paid for by Medicare or Medicaid.
Home health patients are ineligible for inclusion in HHCAHPS
surveys if one of these conditions pertains to them:
Are under the age of 18;
Are deceased prior to the date the sample is pulled;
Receive hospice care;
Receive routine maternity care only;
Are not considered survey eligible because the state in
which the patient lives restricts release of patient information for a
specific condition or illness that the patient has; or
Are ``No Publicity'' patients, defined as patients who on
their own initiative at their first encounter with the HHAs make it
very clear that no one outside of the agencies can be advised of their
patient status, and no one outside of the HHAs can contact them for any
reason.
We stated in previous rules that Medicare-certified HHAs are
required to contract with an approved HHCAHPS survey vendor. This
requirement continues, and Medicare-certified agencies also must
provide on a monthly basis a list of their patients served to their
respective HHCAHPS survey vendors. Agencies are not allowed to
influence at all how their patients respond to the HHCAHPS survey.
As previously required, HHCAHPS survey vendors are required to
attend introductory and all update trainings conducted by CMS and the
HHCAHPS Survey Coordination Team, as well as to pass a post-training
certification test. We have approximately 30 approved HHCAHPS survey
vendors. The list of approved HHCAHPS survey vendors is available at
https://homehealthcahps.org.
2. HHCAHPS Oversight Activities
We stated in prior final rules that all approved HHCAHPS survey
vendors are required to participate in HHCAHPS oversight activities to
ensure compliance with HHCAHPS protocols, guidelines, and survey
requirements. The purpose of the oversight activities is to ensure that
approved HHCAHPS survey vendors follow the HHCAHPS Protocols and
Guidelines Manual.
In the CY 2013 HH PPS final rule (77 FR 67094, 67164), we codified
the current guideline that all approved HHCAHPS survey vendors fully
comply with all HHCAHPS oversight activities. We included this survey
requirement at Sec. 484.250(c)(3).
3. HHCAHPS Requirements for the CY 2017 APU
For the CY 2017 APU, we require continuous monthly HHCAHPS data
collection and reporting for four quarters. The data collection period
for the CY 2017, APU includes the second quarter 2015 through the first
quarter 2016 (the months of April 2015 through March 2016). HHAs are
required to submit their HHCAHPS data files to the HHCAHPS Data Center
for the second quarter 2015 by 11:59 p.m., EST on October 15, 2015; for
the third quarter 2015 by 11:59 p.m., EST on January 21, 2016; for the
fourth quarter 2015 by 11:59 p.m., EST on April 21, 2016; and for the
first quarter 2016 by 11:59 p.m., EST on July 21, 2016. These deadlines
are firm; no exceptions are permitted.
For the CY 2017 APU, we require that all HHAs with fewer than 60
HHCAHPS-eligible unduplicated or unique patients in the period of April
1, 2014, through March 31, 2015, are exempt from the HHCAHPS data
collection and submission requirements for the CY 2017 APU, upon
completion of the CY 2017 HHCAHPS Participation Exemption Request form,
and upon CMS verification of the HHA patient counts. Agencies with
fewer than 60
[[Page 43779]]
HHCAHPS-eligible, unduplicated or unique patients in the period of
April 1, 2014, through March 31, 2015, are required to submit their
patient counts on the CY 2017 HHCAHPS Participation Exemption Request
form posted on https://homehealthcahps.org from April 1, 2015, to 11:59
p.m., EST to March 31, 2016. This deadline is firm, as are all of the
quarterly data submission deadlines for the HHAs that participate in
HHCAHPS.
We automatically exempt HHAs receiving Medicare certification after
the period in which HHAs do their patient count. HHAs receiving
Medicare-certification on or after April 1, 2015, are exempt from the
HHCAHPS reporting requirement for the CY 2017 APU. These newly-
certified HHAs do not need to complete the HHCAHPS Participation
Exemption Request Form for the CY 2017 APU.
4. HHCAHPS Requirements for the CY 2018 APU
For the CY 2018 APU, we require continuous monthly HHCAHPS data
collection and reporting for four quarters. The data collection period
for the CY 2018, APU includes the second quarter 2016 through the first
quarter 2017 (the months of April 2016 through March 2017). HHAs will
be required to submit their HHCAHPS data files to the HHCAHPS Data
Center for the second quarter 2016 by 11:59 p.m., EST on October 20,
2016; for the third quarter 2016 by 11:59 p.m., EST on January 19,
2017; for the fourth quarter 2016 by 11:59 p.m., EST on April 20, 2017;
and for the first quarter 2017 by 11:59 p.m., EST on July 20, 2017.
These deadlines are firm; no exceptions will be permitted.
For the CY 2018 APU, we require that all HHAs with fewer than 60
HHCAHPS-eligible unduplicated or unique patients in the period of April
1, 2015 through March 31, 2016, are exempt from the HHCAHPS data
collection and submission requirements for the CY 2018 APU, upon
completion of the CY 2018 HHCAHPS Participation Exemption Request form,
and upon CMS verification of the HHA patient counts. Agencies with
fewer than 60 HHCAHPS-eligible, unduplicated or unique patients in the
period of April 1, 2015, through March 31, 2016, are required to submit
their patient counts on the CY 2018 HHCAHPS Participation Exemption
Request form posted on https://homehealthcahps.org from April 1, 2016,
to 11:59 p.m., EST to March 31, 2017. This deadline is firm, as are all
of the quarterly data submission deadlines for the HHAs that
participate in HHCAHPS.
We automatically exempt HHAs receiving Medicare certification after
the period in which HHAs do their patient count. HHAs receiving
Medicare-certification on or after April 1, 2016, are exempt from the
HHCAHPS reporting requirement for the CY 2018 APU. These newly-
certified HHAs do not need to complete the HHCAHPS Participation
Exemption Request Form for the CY 2018 APU.
5. HHCAHPS Requirements for the CY 2019 APU
For the CY 2019 APU, we require continuous monthly HHCAHPS data
collection and reporting for four quarters. The data collection period
for the CY 2018, APU includes the second quarter 2017 through the first
quarter 2018 (the months of April 2017 through March 2018). HHAs will
be required to submit their HHCAHPS data files to the HHCAHPS Data
Center for the second quarter 2017 by 11:59 p.m., EST on October 19,
2017; for the third quarter 2017 by 11:59 p.m., EST on January 18,
2018; for the fourth quarter 2017 by 11:59 p.m., EST on April 19, 2018;
and for the first quarter 2018 by 11:59 p.m., EST on July 19, 2018.
These deadlines are firm; no exceptions will be permitted.
For the CY 2019 APU, we require that all HHAs with fewer than 60
HHCAHPS-eligible unduplicated or unique patients in the period of April
1, 2016 through March 31, 2017, are exempt from the HHCAHPS data
collection and submission requirements for the CY 2019 APU, upon
completion of the CY 2019 HHCAHPS Participation Exemption Request form,
and upon CMS verification of the HHA patient counts. Agencies with
fewer than 60 HHCAHPS-eligible, unduplicated or unique patients in the
period of April 1, 2016, through March 31, 2017, are required to submit
their patient counts on the CY 2019 HHCAHPS Participation Exemption
Request form posted on https://homehealthcahps.org from April 1, 2017,
to 11:59 p.m., EST to March 31, 2018. This deadline is firm, as are all
of the quarterly data submission deadlines for the HHAs that
participate in HHCAHPS.
We automatically exempt HHAs receiving Medicare certification after
the period in which HHAs do their patient count. HHAs receiving
Medicare-certification on or after April 1, 2017, are exempt from the
HHCAHPS reporting requirement for the CY 2019 APU. These newly-
certified HHAs do not need to complete the HHCAHPS Participation
Exemption Request Form for the CY 2019 APU.
6. HHCAHPS Requirements for the CY 2020 APU
For the CY 2020 APU, we require continued monthly HHCAHPS data
collection and reporting for four quarters. The data collection period
for the CY 2020, APU includes the second quarter 2018 through the first
quarter 2019 (the months of April 2018 through March 2019). HHAs will
be required to submit their HHCAHPS data files to the HHCAHPS Data
Center for the second quarter 2018 by 11:59 p.m., EST on October 18,
2018; for the third quarter 2018 by 11:59 p.m., EST on January 17,
2019; for the fourth quarter 2018 by 11:59 p.m., EST on April 18, 2019;
and for the first quarter 2019 by 11:59 p.m., EST on July 19, 2019.
These deadlines are firm; no exceptions will be permitted.
For the CY 2020 APU, we require that all HHAs with fewer than 60
HHCAHPS-eligible unduplicated or unique patients in the period of April
1, 2017, through March 31, 2018, are exempt from the HHCAHPS data
collection and submission requirements for the CY 2020 APU, upon
completion of the CY 2020 HHCAHPS Participation Exemption Request form,
and upon CMS verification of the HHA patient counts. Agencies with
fewer than 60 HHCAHPS-eligible, unduplicated or unique patients in the
period of April 1, 2017, through March 31, 2018, are required to submit
their patient counts on the CY 2020 HHCAHPS Participation Exemption
Request form posted on https://homehealthcahps.org from April 1, 2018,
to 11:59 p.m., EST to March 31, 2019. This deadline is firm, as are all
of the quarterly data submission deadlines for the HHAs that
participate in HHCAHPS.
We automatically exempt HHAs receiving Medicare certification after
the period in which HHAs do their patient count. HHAs receiving
Medicare-certification on or after April 1, 2018 are exempt from the
HHCAHPS reporting requirement for the CY 2020 APU. These newly-
certified HHAs do not need to complete the HHCAHPS Participation
Exemption Request Form for the CY 2020 APU.
7. HHCAHPS Reconsiderations and Appeals Process
HHAs should monitor their respective HHCAHPS survey vendors to
ensure that vendors submit their HHCAHPS data on time, by accessing
their HHCAHPS Data Submission Reports on https://homehealthcahps.org.
This helps HHAs ensure that their data are submitted in the proper
format for data
[[Page 43780]]
processing to the HHCAHPS Data Center.
We continue the OASIS and HHCAHPS reconsiderations and appeals
process that we have finalized and that we have used for prior all
periods cited in the previous rules, and utilized in the CY 2012 to CY
2016 APU determinations. We have described the HHCAHPS reconsiderations
and appeals process requirements in the APU Notification Letter that we
send to the affected HHAs annually in September. HHAs have 30 days from
their receipt of the letter informing them that they did not meet the
HHCAHPS requirements to reply to us with documentation that supports
their requests for reconsideration of the annual payment update to us.
It is important that the affected HHAs send in comprehensive
information in their reconsideration letter/package because we will not
contact the affected HHAs to request additional information or to
clarify incomplete or inconclusive information. If clear evidence to
support a finding of compliance is not present, then the 2 percent
reduction in the annual payment update will be upheld. If clear
evidence of compliance is present, then the 2 percent reduction for the
APU will be reversed. We notify affected HHAs by December 31 of the
decisions that affects payments in the annual year beginning on January
1. If we determine to uphold the 2 percent reduction for the annual
payment update, the affected HHA may further appeal the 2 percent
reduction via the Provider Reimbursement Review Board (PRRB) appeals
process, which is described in the December letter.
8. Summary
We did not propose any changes to the participation requirements,
or to the requirements pertaining to the implementation of the Home
Health CAHPS[supreg] Survey (HHCAHPS). We only updated the information
to reflect the dates for future APU years. We again strongly encourage
HHAs to keep up-to-date about the HHCAHPS by regularly viewing the
official Web site for the HHCAHPS at https://homehealthcahps.org. HHAs
can also send an email to the HHCAHPS Survey Coordination Team at
hhcahps@rti.org or to CMS at homehealthcahps@cms.hhs.gov, or telephone
toll-free (1-866-354-0985) for more information about the HHCAHPS
Survey.
VI. Collection of Information Requirements
While this proposed rule contains information collection
requirements, this rule does not add new, nor revise any of the
existing information collection requirements, or burden estimate. The
information collection requirements discussed in this rule for the
OASIS-C1 data item set had been previously approved by the Office of
Management and Budget (OMB) on February 6, 2014 and scheduled for
implementation on October 1, 2014. The extension of OASIS-C1/ICD-9
version was reapproved under OMB control number 0938-0760 with a
current expiration date of March 31, 2018. This version of the OASIS
will be discontinued once the OASIS-C1/ICD-10 version is approved and
implemented. In addition, to facilitate the reporting of OASIS data as
it relates to the implementation of ICD-10 on October 1, 2015, CMS
submitted a new request for approval to OMB for the OASIS-C1/ICD-10
version under the Paperwork Reduction Act (PRA) process. CMS is
requesting a new OMB control number for the proposed revised OASIS item
as announced in the 30-day Federal Register notice (80 FR 15797). The
new information collection request is currently pending OMB approval.
VII. Response to Comments
Because of the large number of public comments we normally receive
on Federal Register documents, we are not able to acknowledge or
respond to them individually. We will consider all comments we receive
by the date and time specified in the DATES section of this preamble,
and, when we proceed with a subsequent document, we will respond to the
comments in the preamble to that document.
VIII. Regulatory Impact Analysis
A. Statement of Need
Section 1895(b)(1) of the Act requires the Secretary to establish a
HH PPS for all costs of HH services paid under Medicare. In addition,
section 1895(b)(3)(A) of the Act requires (1) the computation of a
standard prospective payment amount include all costs for HH services
covered and paid for on a reasonable cost basis and that such amounts
be initially based on the most recent audited cost report data
available to the Secretary, and (2) the standardized prospective
payment amount be adjusted to account for the effects of case-mix and
wage levels among HHAs. Section 1895(b)(3)(B) of the Act addresses the
annual update to the standard prospective payment amounts by the HH
applicable percentage increase. Section 1895(b)(4) of the Act governs
the payment computation. Sections 1895(b)(4)(A)(i) and (b)(4)(A)(ii) of
the Act require the standard prospective payment amount to be adjusted
for case-mix and geographic differences in wage levels. Section
1895(b)(4)(B) of the Act requires the establishment of appropriate
case-mix adjustment factors for significant variation in costs among
different units of services. Lastly, section 1895(b)(4)(C) of the Act
requires the establishment of wage adjustment factors that reflect the
relative level of wages, and wage-related costs applicable to HH
services furnished in a geographic area compared to the applicable
national average level.
Section 1895(b)(3)(B)(iv) of the Act provides the Secretary with
the authority to implement adjustments to the standard prospective
payment amount (or amounts) for subsequent years to eliminate the
effect of changes in aggregate payments during a previous year or years
that was the result of changes in the coding or classification of
different units of services that do not reflect real changes in case-
mix. Section 1895(b)(5) of the Act provides the Secretary with the
option to make changes to the payment amount otherwise paid in the case
of outliers because of unusual variations in the type or amount of
medically necessary care. Section 1895(b)(3)(B)(v) of the Act requires
HHAs to submit data for purposes of measuring health care quality, and
links the quality data submission to the annual applicable percentage
increase.
Section 421(a) of the MMA requires that HH services furnished in a
rural area, for episodes and visits ending on or after April 1, 2010,
and before January 1, 2016, receive an increase of 3 percent of the
payment amount otherwise made under section 1895 of the Act. Section
210 of the MACRA amended section 421(a) of the MMA to extend the 3
percent increase to the payment amounts for serviced furnished in rural
areas for episodes and visits ending before January 1, 2018.
Section 3131(a) of the Affordable Care Act mandates that starting
in CY 2014, the Secretary must apply an adjustment to the national,
standardized 60-day episode payment rate and other amounts applicable
under section 1895(b)(3)(A)(i)(III) of the Act to reflect factors such
as changes in the number of visits in an episode, the mix of services
in an episode, the level of intensity of services in an episode, the
average cost of providing care per episode, and other relevant factors.
In addition, section 3131(a) of the Affordable Care Act mandates that
rebasing must be phased-in over a 4-year period in equal increments,
not to exceed 3.5 percent of the amount (or
[[Page 43781]]
amounts) as of the date of enactment (2010) under section
1895(b)(3)(A)(i)(III) of the Act, and be fully implemented in CY 2017.
The HHVBP Model will apply a payment adjustment based on an HHA's
performance on quality measures to test the effects on quality and
costs of care. The HHVBP Model was implemented in January 2016 as
described in the CY 2016 HH PPS final rule.
B. Overall Impact
We have examined the impacts of this rule as required by Executive
Order 12866 on Regulatory Planning and Review (September 30, 1993),
Executive Order 13563 on Improving Regulation and Regulatory Review
(January 18, 2011), the Regulatory Flexibility Act (RFA) (September 19,
1980, Pub. L. 96-354), section 1102(b) of the Act, section 202 of the
Unfunded Mandates Reform Act of 1995 (UMRA, March 22, 1995; Pub. L.
104-4), Executive Order 13132 on Federalism (August 4, 1999), and the
Congressional Review Act (5 U.S.C. 804(2)).
Executive Orders 12866 and 13563 direct agencies to assess all
costs and benefits of available regulatory alternatives and, if
regulation is necessary, to select regulatory approaches that maximize
net benefits (including potential economic, environmental, public
health and safety effects, distributive impacts, and equity).
Section 3(f) of Executive Order 12866 defines a ``significant
regulatory action'' as an action that is likely to result in a rule:
(1) Having an annual effect on the economy of $100 million or more in
any 1 year, or adversely and materially affecting a sector of the
economy, productivity, competition, jobs, the environment, public
health or safety, or state, local or tribal governments or communities
(also referred to as ``economically significant''); (2) creating a
serious inconsistency or otherwise interfering with an action taken or
planned by another agency; (3) materially altering the budgetary
impacts of entitlement grants, user fees, or loan programs or the
rights and obligations of recipients thereof; or (4) raising novel
legal or policy issues arising out of legal mandates, the President's
priorities, or the principles set forth in the Executive Order.
A regulatory impact analysis (RIA) must be prepared for major rules
with economically significant effects ($100 million or more in any 1
year).The net transfer impacts related to the changes in payments under
the HH PPS for CY 2017 are estimated to be -$180 million. The savings
impacts related to the HHVBP model are estimated at a total projected
5-year gross savings of $378 million assuming a very conservative
savings estimate of a 6 percent annual reduction in hospitalizations
and a 1.0 percent annual reduction in SNF admissions. Therefore, we
estimate that this rulemaking is ``economically significant'' as
measured by the $100 million threshold, and hence also a major rule
under the Congressional Review Act. Accordingly, we have prepared a
Regulatory Impact Analysis that to the best of our ability presents the
costs and benefits of the rulemaking. In accordance with the provisions
of Executive Order 12866, this regulation was reviewed by the Office of
Management and Budget.
In addition, section 1102(b) of the Act requires us to prepare a
RIA if a rule may have a significant impact on the operations of a
substantial number of small rural hospitals. This analysis must conform
to the provisions of section 603 of 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. This proposed rule is applicable exclusively to HHAs.
Therefore, the Secretary has determined this rule would not have a
significant economic impact on the operations of small rural hospitals.
Executive Order 13563 emphasizes the importance of quantifying both
costs and benefits, of reducing costs, of harmonizing rules, and of
promoting flexibility. The net transfer impacts related to the changes
in payments under the HH PPS for CY 2017 are estimated to be -$180
million. The savings impacts related to the HHVBP Model are estimated
at a total projected 6-year gross savings of $378 million assuming a
very conservative savings estimate of a 6 percent annual reduction in
hospitalizations and a 1.0 percent annual reduction in SNF admissions.
Section 202 of the Unfunded Mandates Reform Act of 1995 (UMRA) also
requires that agencies assess anticipated costs and benefits before
issuing any rule whose mandates require spending in any 1 year of $100
million in 1995 dollars, updated annually for inflation. In 2016, that
threshold is approximately $146 million. This proposed rule is not
anticipated to have an effect on State, local, or tribal governments,
in the aggregate, or on the private sector of $146 million or more.
1. HH PPS
The update set forth in this rule applies to Medicare payments
under HH PPS in CY 2017. Accordingly, the following analysis describes
the impact in CY 2017 only. We estimate that the net impact of the
policies in this rule is approximately $180 million in decreased
payments to HHAs in CY 2017. We applied a wage index budget neutrality
factor and a case-mix weights budget neutrality factor to the rates as
discussed in section III.C.3 of this proposed rule. Therefore, the
estimated impact of the 2017 wage index and the recalibration of the
case-mix weights for 2017 is zero. The -$180 million impact reflects
the distributional effects of the 2.3 percent HH payment update
percentage ($420 million increase), the effects of the fourth year of
the four-year phase-in of the rebasing adjustments to the national,
standardized 60-day episode payment amount, the national per-visit
payment rates, and the NRS conversion factor for an impact of -2.3
percent ($420 million decrease), the effects of the -0.97 percent
adjustment to the national, standardized 60-day episode payment rate to
account for nominal case-mix growth for an impact of -0.9 percent ($160
million decrease), and the effects of the proposed change to the FDL
ratio of 0.45 to 0.56 for an impact of -0.1 percent ($20 million
decrease). The $180 million in decreased payments is reflected in the
last column of the first row in Table 36 as a 1.0 percent decrease in
expenditures when comparing CY 2016 payments to estimated CY 2017
payments.
The RFA requires agencies to analyze options for regulatory relief
of small entities, if a rule has a significant impact on a substantial
number of small entities. For purposes of the RFA, small entities
include small businesses, nonprofit organizations, and small
governmental jurisdictions. Most hospitals and most other providers and
suppliers are small entities, either by nonprofit status or by having
revenues of less than $7.5 million to $38.5 million in any one year.
For the purposes of the RFA, we estimate that almost all HHAs are small
entities as that term is used in the RFA. Individuals and states are
not included in the definition of a small entity. The economic impact
assessment is based on estimated Medicare payments (revenues) and HHS's
practice in interpreting the RFA is to consider effects economically
``significant'' only if greater than 5 percent of providers reach a
threshold of 3 to 5 percent or more of total revenue or total costs.
The majority of HHAs' visits are Medicare-paid visits and therefore the
majority of HHAs' revenue consists of Medicare payments. Based on our
analysis, we
[[Page 43782]]
conclude that the policies proposed in this rule would result in an
estimated total impact of 3 to 5 percent or more on Medicare revenue
for greater than 5 percent of HHAs. Therefore, the Secretary has
determined that this HH PPS proposed rule would have a significant
economic impact on a substantial number of small entities. Further
detail is presented in Table 39, by HHA type and location.
With regards to options for regulatory relief, we note that in the
CY 2014 HH PPS final rule we finalized rebasing adjustments to the
national, standardized 60-day episode rate, non-routine supplies (NRS)
conversion factor, and the national per-visit payment rates for each
year, 2014 through 2017 as described in section II.C and III.C.3 of
this proposed rule. Since the rebasing adjustments are mandated by
section 3131(a) of the Affordable Care Act, we cannot offer HHAs relief
from the rebasing adjustments for CY 2017. For the 0.97 percent
reduction to the national, standardized 60-day episode payment amount
for CY 2017 described in section III.C.3 of this proposed rule, we
believe it is appropriate to reduce the national, standardized 60-day
episode payment amount to account for the estimated increase in nominal
case-mix in order to move towards more accurate payment for the
delivery of home health services where payments better align with the
costs of providing such services. In the alternatives considered
section for the CY 2016 HH PPS proposed rule (80 FR 39839), we note
that we considered reducing the 60-day episode rate in CY 2016 only to
account for nominal case-mix growth between CY 2012 and CY 2014.
However, we instead finalized a reduction to the 60-day episode rate
over a three-year period (CY 2016, CY 2017, and CY 2018) to account for
estimated nominal case-mix growth between CY 2012 and CY 2014 in order
to lessen the impact on HHAs in a given year (80 FR 68646).
Executive Order 13563 specifies, to the extent practicable,
agencies should assess the costs of cumulative regulations. However,
given potential utilization pattern changes, wage index changes,
changes to the market basket forecasts, and unknowns regarding future
policy changes, we believe it is neither practicable nor appropriate to
forecast the cumulative impact of the rebasing adjustments on Medicare
payments to HHAs for future years at this time. Changes to the Medicare
program may continue to be made as a result of the Affordable Care Act,
or new statutory provisions. Although these changes may not be specific
to the HH PPS, the nature of the Medicare program is such that the
changes may interact, and the complexity of the interaction of these
changes would make it difficult to predict accurately the full scope of
the impact upon HHAs for future years beyond CY 2017. We note that the
rebasing adjustments to the national, standardized 60-day episode
payment rate and the national per-visit rates are capped at the
statutory limit of 3.5 percent of the CY 2010 amounts (as described in
the preamble in section II.C. of this proposed rule) for each year,
2014 through 2017. The NRS rebasing adjustment will be -2.82 percent in
each year, 2014 through 2017.
2. HHVBP Model
Under the HHVBP Model, the first payment adjustment will apply in
CY 2018 based on PY1 (CY 2016) data and the final payment adjustment
will apply in CY 2022 based on PY5 (CY 2020) data. In the CY 2016 HH
PPS final rule, the overall impact of HHVBP Model from CY 2018-CY 2022
was approximately a reduction of $380 million. That estimate was based
on the five performance years of the Model and only two payment
adjustment years. We now estimate that this will be approximately a
decrease of $378 million. This estimate represents the five performance
years (CY 2016-CY 2020) and applying the payment adjustments from CY
2018 through CY 2021. We assume that the behavior changes and savings
will continue into 2021 because HHAs will continue to receive quality
reports until July 2021. Although behavior changes and savings could
persist into CY 2022, HHAs would not be receiving quality reports so we
did not include it in our savings assumptions.
C. Detailed Economic Analysis
1. HH PPS
This rule proposes updates for CY 2017 to the HH PPS rates
contained in the CY 2016 HH PPS final rule (80 FR 68624 through 68719).
The impact analysis of this proposed rule presents the estimated
expenditure effects of policy changes proposed in this rule. We use the
latest data and best analysis available, but we do not make adjustments
for future changes in such variables as number of visits or case-mix.
This analysis incorporates the latest estimates of growth in
service use and payments under the Medicare HH benefit, based primarily
on Medicare claims data from 2015. 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 errors
resulting from other changes in the impact time period assessed. Some
examples of such possible events are newly-legislated general Medicare
program funding changes made by the Congress, or changes specifically
related to HHAs. In addition, changes to the Medicare program may
continue to be made as a result of the Affordable Care Act, or new
statutory provisions. Although these changes may not be specific to the
HH 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 HHAs.
Table 36 represents how HHA revenues are likely to be affected by
the policy changes proposed in this rule. For this analysis, we used an
analytic file with linked CY 2015 OASIS assessments and HH claims data
for dates of service that ended on or before December 31, 2015 (as of
March 31, 2016). The first column of Table 36 classifies HHAs according
to a number of characteristics including provider type, geographic
region, and urban and rural locations. The second column shows the
number of facilities in the impact analysis. The third column shows the
payment effects of the CY 2017 wage index. The fourth column shows the
payment effects of the CY 2016 case-mix weights. The fifth column shows
the effects the 0.97 percent reduction to the national, standardized
60-day episode payment amount to account for nominal case-mix growth.
The sixth column shows the effects of the rebasing adjustments to the
national, standardized 60-day episode payment rate, the national per-
visit payment rates, and NRS conversion factor. For CY 2017, the
average impact for all HHAs due to the effects of rebasing is an
estimated 2.3 percent decrease in payments. The seventh column shows
the effects of revising the FDL ratio used to compute outlier payments
from 0.45 to 0.56. The eighth column shows the effects of the change to
the outlier methodology. The ninth column shows the effects of the CY
2017 home health payment update percentage.
The last column shows the combined effects of all the policies
proposed in this rule. Overall, it is projected that aggregate payments
in CY 2017 would decrease by 1.0 percent. As illustrated in Table 36,
the combined effects of all of the changes vary by specific types of
providers and by location. We note that some individual HHAs within the
same
[[Page 43783]]
group may experience different impacts on payments than others due to
the distributional impact of the CY 2017 wage index, the extent to
which HHAs had episodes in case-mix groups where the case-mix weight
decreased for CY 2017 relative to CY 2016, the percentage of total HH
PPS payments that were subject to the low-utilization payment
adjustment (LUPA) or paid as outlier payments, and the degree of
Medicare utilization.
Table 36-- Estimated Home Health Agency Impacts by Facility Type and Area of the Country, CY 2017
--------------------------------------------------------------------------------------------------------------------------------------------------------
60-day
episode HH
CY 2017 CY 2017 rate Revised Revised payment
Number of wage index case-mix nominal Rebas-ing outlier outlier update Total %
Agencies \1\ % weights case-mix \4\ % FDL % method- percentage
\2\ % reduct-ion ology % \5\ %
\3\ %
--------------------------------------------------------------------------------------------------------------------------------------------------------
All Agencies................................ 11,167 0.0 0.0 -0.9 -2.3 -0.1 0.0 2.3 -1.0
--------------------------------------------------------------------------------------------------------------------------------------------------------
Facility Type and Control
--------------------------------------------------------------------------------------------------------------------------------------------------------
Free-Standing/Other Vol/NP.................. 1,087 -0.2 -0.1 -0.9 -2.2 -0.1 0.9 2.3 -0.3
Free-Standing/Other Proprietary............. 8,715 0.1 0.0 -0.9 -2.3 -0.1 -0.3 2.3 -1.2
Free-Standing/Other Government.............. 362 0.1 0.1 -0.9 -2.2 -0.1 0.3 2.3 -0.4
Facility-Based Vol/NP....................... 690 -0.1 -0.1 -0.9 -2.2 -0.1 0.8 2.3 -0.3
Facility-Based Proprietary.................. 109 0.0 0.0 -0.9 -2.2 -0.1 0.4 2.3 -0.5
Facility-Based Government................... 204 -0.3 0.0 -0.9 -2.3 -0.1 0.8 2.3 -0.5
Subtotal: Freestanding.................. 10,164 0.0 0.0 -0.9 -2.3 -0.1 -0.1 2.3 -1.1
Subtotal: Facility-based................ 1,003 -0.1 0.0 -0.9 -2.2 -0.1 0.8 2.3 -0.2
Subtotal: Vol/NP........................ 1,777 -0.2 -0.1 -0.9 -2.2 -0.1 0.9 2.3 -0.3
Subtotal: Proprietary................... 8,824 0.1 0.0 -0.9 -2.3 -0.1 -0.3 2.3 -1.2
Subtotal: Government.................... 566 -0.1 0.1 -0.9 -2.3 -0.1 0.5 2.3 -0.5
--------------------------------------------------------------------------------------------------------------------------------------------------------
Facility Type and Control: Rural
--------------------------------------------------------------------------------------------------------------------------------------------------------
Free-Standing/Other Vol/NP.................. 279 0.1 0.1 -0.9 -2.2 -0.1 0.8 2.3 0.1
Free-Standing/Other Proprietary............. 873 0.0 -0.1 -0.9 -2.3 -0.1 0.2 2.3 -0.9
Free-Standing/Other Government.............. 261 0.2 0.0 -0.9 -2.4 -0.1 -0.2 2.3 -1.1
Facility-Based Vol/NP....................... 333 0.3 0.1 -0.9 -2.2 -0.1 0.5 2.3 0.0
Facility-Based Proprietary.................. 54 -0.1 0.1 -0.9 -2.3 -0.1 0.5 2.3 -0.5
Facility-Based Government................... 152 0.1 0.2 -0.9 -2.2 -0.1 0.4 2.3 -0.2
--------------------------------------------------------------------------------------------------------------------------------------------------------
Facility Type and Control: Urban
--------------------------------------------------------------------------------------------------------------------------------------------------------
Free-Standing/Other Vol/NP.................. 807 -0.3 -0.2 -0.9 -2.2 -0.1 0.9 2.3 -0.5
Free-Standing/Other Proprietary............. 7,837 0.1 0.0 -0.9 -2.3 -0.1 -0.4 2.3 -1.3
Free-Standing/Other Government.............. 101 0.0 0.0 -0.9 -2.3 -0.1 0.2 2.3 -0.8
Facility-Based Vol/NP....................... 357 -0.2 -0.1 -0.9 -2.2 -0.1 0.9 2.3 -0.3
Facility-Based Proprietary.................. 55 0.1 -0.1 -0.9 -2.2 -0.1 0.3 2.3 -0.6
Facility-Based Government................... 52 -0.6 -0.1 -0.9 -2.3 -0.1 1.1 2.3 -0.6
--------------------------------------------------------------------------------------------------------------------------------------------------------
Facility Location: Urban or Rural
--------------------------------------------------------------------------------------------------------------------------------------------------------
Rural....................................... 1,952 0.2 0.0 -0.9 -2.3 -0.1 0.0 2.3 -0.8
Urban....................................... 9,209 0.0 0.0 -0.9 -2.3 -0.1 0.0 2.3 -1.0
--------------------------------------------------------------------------------------------------------------------------------------------------------
Facility Location: Region of the Country
--------------------------------------------------------------------------------------------------------------------------------------------------------
Northeast................................... 848 -0.4 0.0 -0.9 -2.1 -0.1 0.8 2.3 -0.4
Midwest..................................... 2,992 0.0 0.0 -0.9 -2.4 -0.1 0.4 2.3 -0.7
South....................................... 5,310 -0.1 0.0 -0.9 -2.3 -0.1 -0.6 2.3 -1.7
West........................................ 1,968 0.6 0.0 -0.9 -2.3 -0.1 0.3 2.3 -0.1
Other....................................... 49 -0.3 0.1 -0.9 -2.2 -0.1 0.9 2.3 -0.2
Puerto Rico................................. 41 -0.5 0.1 -0.8 -2.2 -0.1 0.5 2.3 -0.7
--------------------------------------------------------------------------------------------------------------------------------------------------------
Facility Location: Region of the Country (Census Region)
--------------------------------------------------------------------------------------------------------------------------------------------------------
New England................................. 347 -0.7 0.1 -0.9 -2.1 -0.1 0.3 2.3 -1.1
Mid Atlantic................................ 501 -0.3 -0.1 -0.9 -2.1 -0.1 1.1 2.3 -0.1
East North Central.......................... 2,271 0.0 0.1 -0.9 -2.4 -0.1 0.4 2.3 -0.6
West North Central.......................... 721 0.0 -0.1 -0.9 -2.3 -0.1 0.6 2.3 -0.5
South Atlantic.............................. 1,791 -0.3 -0.1 -0.9 -2.3 -0.1 -0.6 2.3 -2.0
East South Central.......................... 426 -0.1 0.0 -0.9 -2.4 -0.1 0.0 2.3 -1.1
West South Central.......................... 3,093 0.3 0.0 -0.9 -2.3 -0.1 -0.8 2.3 -1.5
Mountain.................................... 672 0.2 0.1 -0.9 -2.3 -0.1 -0.2 2.3 -0.9
Pacific..................................... 1,296 0.7 0.0 -0.9 -2.3 -0.1 0.6 2.3 0.3
--------------------------------------------------------------------------------------------------------------------------------------------------------
Facility Size (Number of 1st Episodes)
--------------------------------------------------------------------------------------------------------------------------------------------------------
<100 episodes............................... 3,177 0.0 0.3 -0.9 -2.3 -0.1 0.4 2.3 -0.3
100 to 249.................................. 2,733 0.1 0.2 -0.9 -2.4 -0.1 0.1 2.3 -0.7
250 to 499.................................. 2,342 0.1 0.0 -0.9 -2.3 -0.1 0.0 2.3 -0.9
500 to 999.................................. 1,597 0.0 0.0 -0.9 -2.3 -0.1 -0.1 2.3 -1.1
1,000 or More............................... 1,318 0.0 -0.1 -0.9 -2.3 -0.1 0.0 2.3 -1.1
--------------------------------------------------------------------------------------------------------------------------------------------------------
Source: CY 2015 Medicare claims data for episodes ending on or before December 31, 2015 (as of December 31, 2015) for which we had a linked OASIS
assessment.
\1\ The impact of the CY 2017 home health wage index is offset by the wage index budget neutrality factor described in section III.C.3 of this proposed
rule.
\2\ The impact of the CY 2017 home health case-mix weights reflects the recalibration of the case-mix weights as outlined in section III.B of this
proposed rule offset by the case-mix weights budget neutrality factor described in section III.C.3 of this proposed rule.
[[Page 43784]]
\3\ The 0.97 percent reduction to the national, standardized 60-day episode payment amount in CY 2017 is estimated to have a 0.9 percent impact on
overall HH PPS expenditures.
\4\ The impact of rebasing includes the rebasing adjustments to the national, standardized 60-day episode payment rate (-2.74 percent after the CY 2017
payment rate was adjusted for the wage index and case-mix weight budget neutrality factors and the nominal case-mix reduction), the national per-visit
rates (+2.9 percent), and the NRS conversion factor (-2.82 percent). The estimated impact of the NRS conversion factor rebasing adjustment is an
overall -0.01 percent decrease in estimated payments to HHAs
\4\ The CY 2017 home health payment update percentage reflects the home health market basket update of 2.8 percent, reduced by a 0.5 percentage point
multifactor productivity (MFP) adjustment as required under section 1895(b)(3)(B)(vi)(I) of the Act, as described in section III.C.1 of this proposed
rule.
Region Key:
New England = Connecticut, Maine, Massachusetts, New Hampshire, Rhode Island, Vermont;
Middle Atlantic = Pennsylvania, New Jersey, New York;
South Atlantic = Delaware, District of Columbia, Florida, Georgia, Maryland, North Carolina, South Carolina, Virginia, West Virginia;
East North Central = Illinois, Indiana, Michigan, Ohio, Wisconsin;
East South Central = Alabama, Kentucky, Mississippi, Tennessee;
West North Central = Iowa, Kansas, Minnesota, Missouri, Nebraska, North Dakota, South Dakota;
West South Central = Arkansas, Louisiana, Oklahoma, Texas;
Mountain = Arizona, Colorado, Idaho, Montana, Nevada, New Mexico, Utah, Wyoming;
Pacific = Alaska, California, Hawaii, Oregon, Washington;
Other = Guam, Puerto Rico, Virgin Islands
2. HHVBP Model
Table 37 displays our analysis of the distribution of possible
payment adjustments at the 3-percent, 5-percent, 6-percent, 7-percent,
and 8-percent rates that are being used in the Model using the 2013 and
2014 OASIS measures, hospitalization measure and Emergency Department
(ED) measure from QIES, and Home Health CAHPS data. The impacts below
also account for the proposals to change the smaller-volume cohort size
determination, calculate achievement threshold and benchmark proposals
at the state level, and revise the applicable measures. We determined
the distribution of possible payment adjustments based on ten (10)
OASIS quality measures, two (2) claims-based measures in QIES, the
three (3)New Measures (with the assumption that all HHAs reported on
all New Measures and received full points), and QIES Roll Up File data
in the same manner as they would be in the Model. The five (5) HHCAHPS
measures are based on archived data. The size of the cohorts were
determined using the 2014 Quality Episode File based on OASIS
assessments (the Model will use the year before each performance year),
whereby the HHAs reported at least five measures with over 20
observations. The basis of the payment adjustment was derived from
complete 2014 claims data. We note that this impact analysis is based
on the aggregate value of all nine (9) selected states.
Table 38 displays our analysis of the distribution of possible
payment adjustments based on the same 2013-2014 data used to calculate
Table 37, providing information on the estimated impact of this
proposed rule. We note that this impact analysis is based on the
aggregate value of all nine (9) selected states. All Medicare-certified
HHAs that provide services in Massachusetts, Maryland, North Carolina,
Florida, Washington, Arizona, Iowa, Nebraska, and Tennessee are
required to compete in this Model. Value-based incentive payment
adjustments for the estimated 1,900 plus HHAs in the selected states
that compete in the HHVBP Model are stratified by size as described in
this proposed rule. Under the proposal described, there must be a
minimum of eight (8) HHAs in any cohort.
Those HHAs that are in states that do not have at least eight small
HHAs would not have a smaller-volume cohort and thus there would only
be one cohort that would include all the HHAS in that state. As
indicated in Table 38, under this proposal, Massachusetts, Maryland,
North Carolina, Tennessee and Washington would only have one cohort and
Florida, Arizona, Iowa, Nebraska would have a smaller-volume cohort and
a larger-volume cohort. For example, Iowa has 29 HHAs eligible to be
exempt from being required to have their beneficiaries complete HHCAHPS
surveys because they provided HHA services to less than 60
beneficiaries in 2013. Therefore, those 29 HHAs would be competing in
Iowa's smaller-volume cohort if the performance year was 2014.
Using 2013-2014 data and the payment adjustment of 5-percent (as
applied in CY 2019), based on the ten (10) OASIS quality measures, two
(2) claims-based measures in QIES, the five (5) HHCAHPS measures (based
on the archived data), and the three (3) New Measures (with the
assumption that all HHAs submitted data), Table 38 illustrates that
smaller-volume HHAs in Iowa would have a mean payment adjustment of
positive 0.62 percent and the payment adjustment ranges from -2.3
percent at the 10th percentile to +3.8 percent at the 90th percentile.
As a result of using the OASIS quality and claims-based measures, the
same source data (from QIES rather than archived data) that the Model
will use for implementation, and adding the assumption that all HHAs
will submit data for each of the New Measures when calculating the
payment adjustments, the range of payment adjustments for all cohorts
in this proposed rule is lower than that was included in HH PPS 2016
rule. This difference is largely due to the lowered variation in TPS
caused by the assumption that all HHAs will submit data for each of the
New Measures.
Table 39 provides the payment adjustment distribution based on
proportion of dually-eligible beneficiaries, average case mix (using
HCC scores), proportion that reside in rural areas, as well as HHA
organizational status. Besides the observation that higher proportion
of dually-eligible beneficiaries serviced is related to better
performance, the payment adjustment distribution is consistent with
respect to these four categories.
The payment adjustment percentages were calculated at the state and
size level so that each HHA's payment adjustment was calculated as it
would be in the Model. Hence, the values of each separate analysis in
the tables are representative of what they would be if the baseline
year was 2013 and the performance year was 2014. There were 1,839 HHAs
in the nine selected states out of 1,991 HHAs that were found in the
HHA data sources that yielded a sufficient number of measures to
receive a payment adjustment in the Model. It is expected that a
certain number of HHAs will not be subject to the payment adjustment
because they may be servicing too small of a population to report on an
adequate number of measures to calculate a TPS.
[[Page 43785]]
Table 37--HHVBP Model: Adjustment Distribution by Percentile Level of Quality Total Performance Score at Different Model Payment Adjustment Rates
[Percentage]
--------------------------------------------------------------------------------------------------------------------------------------------------------
Payment adjustment distribution Range 10% 20% 30% 40% Median 60% 70% 80% 90%
--------------------------------------------------------------------------------------------------------------------------------------------------------
3% Payment Adjustment For Performance year 1 of the Model..... 3.08 -1.23 -0.87 -0.56 -0.30 -0.02 0.27 0.61 1.11 1.85
5% Payment Adjustment For Performance year 2 of the Model..... 5.12 -2.04 -1.45 -0.94 -0.50 -0.03 0.46 1.01 1.85 3.08
6% Payment Adjustment For Performance year 3 of the Model..... 6.15 -2.45 -1.74 -1.13 -0.61 -0.04 0.55 1.21 2.22 3.70
7% Payment Adjustment For Performance year 4 of the Model..... 7.18 -2.86 -2.03 -1.32 -0.71 -0.04 0.64 1.42 2.59 4.32
8% Payment Adjustment For Performance year 5 of the Model..... 8.25 -3.27 -2.32 -1.50 -0.81 -0.05 0.73 1.62 2.96 4.93
--------------------------------------------------------------------------------------------------------------------------------------------------------
Table 38--HHVBP Model: HHA Cohort Payment Adjustment Distributions by State/Cohort
[Based on a 5-percent payment adjustment]
--------------------------------------------------------------------------------------------------------------------------------------------------------
Average
COHORT # of payment 10% 20% 30% 40% Median 60% 70% 80% 90%
HHA adj. (%)
--------------------------------------------------------------------------------------------------------------------------------------------------------
HHA Cohort in States with no small cohorts (percent)
--------------------------------------------------------------------------------------------------------------------------------------------------------
MA................................................. 127 0.00 -2.20 -1.50 -1.10 -0.70 -0.30 0.00 0.80 1.40 2.70
MD................................................. 53 0.56 -1.50 -1.10 -0.80 -0.10 0.20 0.50 1.40 2.00 3.60
NC................................................. 172 0.16 -1.90 -1.50 -1.00 -0.50 0.10 0.50 0.90 1.70 2.40
TN................................................. 135 0.36 -2.00 -1.30 -0.80 -0.40 -0.10 0.30 0.90 2.00 3.10
WA................................................. 59 0.71 -1.70 -0.70 -0.30 0.20 0.50 0.80 1.70 2.30 2.90
--------------------------------------------------------------------------------------------------------------------------------------------------------
Smaller-volume HHA Cohort in states with small cohort (percent)
--------------------------------------------------------------------------------------------------------------------------------------------------------
AZ small........................................... 9 0.53 -1.20 -0.70 -0.70 -0.50 -0.30 -0.10 0.60 0.90 5.00
FL small........................................... 130 -0.14 -2.20 -1.70 -1.20 -0.60 -0.20 0.10 0.40 1.20 1.80
IA small........................................... 29 0.62 -2.30 -1.10 -0.80 0.00 0.30 0.90 1.70 2.30 3.80
NE small........................................... 16 0.48 -1.70 -1.60 -1.20 -0.60 -0.40 1.30 2.20 2.40 4.00
--------------------------------------------------------------------------------------------------------------------------------------------------------
Larger-volume HHA Cohort in states with small cohorts (percent)
--------------------------------------------------------------------------------------------------------------------------------------------------------
AZ large........................................... 112 -0.06 -2.20 -1.50 -1.10 -0.70 -0.30 0.10 0.50 1.30 2.30
FL large........................................... 889 0.37 -2.10 -1.50 -0.90 -0.40 0.00 0.60 1.30 2.20 3.30
IA large........................................... 107 -0.21 -2.30 -1.60 -1.30 -0.70 -0.20 0.10 0.50 1.00 1.80
NE large........................................... 49 0.31 -1.80 -1.20 -0.90 -0.60 -0.10 0.30 0.70 1.80 3.70
--------------------------------------------------------------------------------------------------------------------------------------------------------
Table 39--PAYMENT ADJUSTMENT DISTRIBUTIONS BY CHARACTERISTICS
[Based on a 5-percent payment adjustment]
--------------------------------------------------------------------------------------------------------------------------------------------------------
Average
COHORT # of payment 10% 20% 30% 40% Median 60% 70% 80% 90%
HHA adj. (%)
--------------------------------------------------------------------------------------------------------------------------------------------------------
Low % Dually-eligible.............................. 621 0.18 -1.80 -1.30 -0.90 -0.50 0.00 0.40 0.90 1.50 2.50
Medium % Dually-eligible........................... 841 -0.15 -2.20 -1.70 -1.20 -0.80 -0.40 0.00 0.50 1.20 2.20
High % Dually-eligible............................. 416 1.21 -1.80 -0.80 -0.20 0.50 1.10 1.80 2.60 3.30 4.20
Low acuity......................................... 459 0.97 -1.70 -1.00 -0.40 0.10 0.70 1.30 2.10 2.90 4.00
Mid acuity......................................... 1089 0.83 -2.10 -1.50 -1.00 -0.60 -0.10 0.30 0.80 1.50 2.60
High acuity........................................ 338 -0.16 -2.10 -1.60 -1.30 -0.90 -0.50 -0.10 0.50 1.30 2.40
All non-rural...................................... 989 0.57 -2.10 -1.50 -0.90 -0.40 0.10 1.00 1.80 2.70 3.80
Up to 35% rural.................................... 141 0.01 -2.10 -1.50 -1.10 -0.60 -0.20 0.20 0.70 1.40 2.30
Over 35% rural..................................... 172 0.54 -1.80 -1.30 -0.90 -0.50 0.00 0.50 1.10 1.70 2.90
Church............................................. 62 0.80 -1.70 -0.90 -0.80 0.10 0.40 1.10 1.70 2.60 3.70
Private NP......................................... 168 0.22 -1.90 -1.30 -0.90 -0.30 0.10 0.50 0.90 1.70 2.50
Other.............................................. 84 0.40 -1.60 -1.10 -0.70 -0.40 0.20 0.60 1.00 1.80 2.60
Private FP......................................... 1315 0.20 -2.10 -1.50 -1.00 -0.60 -0.10 0.30 1.00 1.90 3.10
Federal............................................ 72 0.37 -2.20 -1.60 -1.10 -0.40 0.20 0.60 1.40 2.10 2.80
State.............................................. 5 -0.39 -2.50 -1.90 -1.40 -0.50 0.30 0.50 0.60 0.80 1.00
Local.............................................. 57 0.50 -1.50 -1.10 -0.70 0.00 0.30 0.60 0.90 1.40 2.40
--------------------------------------------------------------------------------------------------------------------------------------------------------
D. Alternatives Considered
As described in the CY 2016 HH PPS proposed rule (80 FR 39911), we
considered proposing to reduce the national, standardized 60-day
episode payment rate by 3.41 percent in CY 2016 to account for nominal
case-mix growth between CY 2012 and CY 2014. If we were to reduce the
national, standardized 60-day episode payment rate by 3.41 percent, we
estimated that the aggregate impact would have been a decrease of $600
million in payments to HHAs. However, instead of implementing a one-
time reduction in the national, standardized 60-day episode payment
rate of 3.41 percent in CY 2016 to account for nominal case-mix growth
from CY 2012 through CY 2014, we finalized a reduction to the national,
standardized 60-day episode payment rate of 0.97 percent in CY 2016, CY
2017, and CY 2018 to account for nominal case-mix growth from CY 2012
through CY 2014 (80 FR 68646). Since the 0.97 percent reduction to the
national, standardized 60-day episode payment rate to account for
nominal case-mix growth from 2012 to 2014 was finalized in the CY 2016
HH PPS final
[[Page 43786]]
rule, we did not consider alternatives to implementing this reduction
for CY 2017.
Section 3131(a) of the Affordable Care Act mandates that starting
in CY 2014, the Secretary must apply an adjustment to the national,
standardized 60-day episode payment rate and other amounts applicable
under section 1895(b)(3)(A)(i)(III) of the Act to reflect factors such
as changes in the number of visits in an episode, the mix of services
in an episode, the level of intensity of services in an episode, the
average cost of providing care per episode, and other relevant factors.
In addition, section 3131(a) of the Affordable Care Act mandates that
rebasing must be phased-in over a 4-year period in equal increments,
not to exceed 3.5 percent of the amount (or amounts) as of the date of
enactment (2010) under section 1895(b)(3)(A)(i)(III) of the Act, and be
fully implemented in CY 2017. Therefore, in the CY 2014 HH PPS final
rule (78 FR 77256), we finalized rebasing adjustments to the national,
standardized 60-day episode payment amount, the national per-visit
rates and the NRS conversion factor. As we noted in the CY 2014 HH PPS
final rule, because section 3131(a) of the Affordable Care Act requires
a four year phase-in of rebasing, in equal increments, to start in CY
2014 and be fully implemented in CY 2017, we do not have the discretion
to delay, change, or eliminate the rebasing adjustments once we have
determined that rebasing is necessary (78 FR 72283).
Section 1895(b)(3)(B) of the Act requires that the standard
prospective payment amounts for CY 2016 be increased by a factor equal
to the applicable HH market basket update for those HHAs that submit
quality data as required by the Secretary. For CY 2016, section 3401(e)
of the Affordable Care Act, requires that, in CY 2015 (and in
subsequent calendar years), the market basket update under the HHA
prospective payment system, as described in section 1895(b)(3)(B) of
the Act, be annually adjusted by changes in economy-wide productivity.
Beginning in CY 2015, section 1895(b)(3)(B)(vi)(I) of the Act, as
amended by section 3401(e) of the Affordable Care Act, requires the
application of the productivity adjustment described in section
1886(b)(3)(B)(xi)(II) of the Act to the HHA PPS for CY 2015 and each
subsequent CY. The -0.5 percentage point productivity adjustment to the
proposed CY 2017 home health market basket update (2.8 percent), is
discussed in the preamble of this rule and is not discretionary as it
is a requirement in section 1895(b)(3)(B)(vi)(I) of the Act (as amended
by the Affordable Care Act).
With regards to payments made under the HH PPS for high-cost
``outlier'' episodes of care (that is, episodes of care with unusual
variations in the type or amount of medically necessary care), we did
not consider maintaining the fixed-dollar loss (FDL) ratio at 0.45 in
section III.D.3 of this proposed rule because simulations using CY 2015
utilization data (that is, home health claims data) the proposed CY
2017 HH PPS payment rates resulted in an estimated 2.58 percent of
total HH PPS payments being paid as outlier payments using the existing
methodology (cost-per-visit) for calculating the cost of an episode of
care. Likewise, simulations using CY 2015 utilization data (that is,
home health claims data) the proposed CY 2017 HH PPS payment rates
resulted in an estimated 3.10 percent of total HH PPS payments being
paid as outlier payments using the proposed methodology (cost-per-unit)
for calculating the cost of an episode of care. The FDL ratio and the
loss-sharing ratio must be selected so that the estimated outlier
payments do not exceed the 2.5 percent of total HH PPS payments (as
required by section 1895(b)(5)(A) of the Act). We did not consider
proposing a change to the loss-sharing ratio (0.80) in order for the HH
PPS to remain consistent with payment for high-cost outliers in other
Medicare payment systems (for example, IRF PPS, IPPS, etc.)
With regards to the methodology used to calculate the cost of an
episode of care in order to determine the payment amount under the HH
PPS for high-cost ``outliers'' (that is, episodes of care with unusual
variations in the type or amount of medically necessary care), in
section III.D.2, we considered maintaining the current methodology used
to calculate the cost of an episode of care (cost-per-visit). However,
due to the findings from the home health study required as a result of
section 3131(d) of the Affordable Care Act (as discussed in section
III.D.2 of this proposed rule and in the CY 2016 HH PPS proposed rule
(80 FR 39864), we believe that the proposed methodology change (cost-
per-unit) helps to alleviate financial disincentives for providers to
treat medically complex beneficiaries who require longer visits. Since
the projection of the percentage of outlier dollars is the same as
before the change, the impact of this proposal is budget neutral.
As described in Section III.E of this proposed rule, the
Consolidated Appropriations Act of 2016 (Pub. L 114-113) amends both
Section 1834 of the Act (42 U.S.C. 1395m) and Section 1861(m)(5) of the
Act (42 U.S.C. 1395x(m)(5)), requiring a separate payment to a HHA for
an applicable disposable device when furnished on or after January 1,
2017, to an individual who receives home health services for which
payment is made under the Medicare home health benefit. Therefore, we
do not have the discretion to delay or eliminate the implementation of
a separate payment amount for NPWT performed using a disposable device
and thus we did not consider any alternatives regarding this proposal.
We invite comments on the alternatives discussed in this analysis.
E. Accounting Statement and Table
As required by OMB Circular A-4 (available at https://www.whitehouse.gov/omb/circulars_a004_a-4), in Table 40, we have
prepared an accounting statement showing the classification of the
transfers and costs associated with the HH PPS provisions of this
proposed rule. Table 40 provides our best estimate of the decrease in
Medicare payments under the HH PPS as a result of the changes presented
in this proposed rule for the HH PPS provisions.
Table 40--Accounting Statement: HH PPS Classification of Estimated
Transfers and Costs, From the CYs 2016 to 2017 *
------------------------------------------------------------------------
Category Transfers
------------------------------------------------------------------------
Annualized Monetized Transfers............ -$180 million.
From Whom to Whom? Federal Government to HHAs.
------------------------------------------------------------------------
Table 41 provides our best estimate of the decrease in Medicare
payments under the HHVBP Model as a result of the proposed changes
presented in this proposed rule for the HHVBP Model.
Table 41--Accounting Statement: HHVBP Model Classification of Estimated
Cost Savings for CY 2016-2021
------------------------------------------------------------------------
Category Savings
------------------------------------------------------------------------
6-Year Gross Savings...................... -$378 million.
Medicare Payments......................... Hospitals and SNFs.
------------------------------------------------------------------------
F. Conclusion
1. HH PPS
In conclusion, we estimate that the net impact of the HH PPS
policies in this rule is a decrease of 1.0 percent, or $180 million, in
Medicare payments to
[[Page 43787]]
HHAs for CY 2017. The -$180 million impact reflects the effects of the
2.3 percent CY 2017 HH payment update percentage ($420 million
increase), a 0.9 percent decrease in payments due to the 0.97 percent
reduction to the national, standardized 60-day episode payment rate in
CY 2016 to account for nominal case-mix growth from 2012 through 2014
($160 million decrease), the 0.1 percent decrease in payments due to
the change to the FDL ratio ($20 million decrease), and a 2.3 percent
decrease in in payments due to the third year of the 4-year phase-in of
the rebasing adjustments required by section 3131(a) of the Affordable
Care Act ($420 million decrease).
This analysis, together with the remainder of this preamble,
provides an initial Regulatory Flexibility Analysis.
2. HHVBP Model
In conclusion, we estimate there would be no net impact (to include
either a net increase or reduction in payments) in this proposed rule
in Medicare payments to HHAs competing in the HHVBP Model for CY 2017.
However, the overall economic impact of the HHVBP Model provision is an
estimated $378 million in total savings from a reduction in unnecessary
hospitalizations and SNF usage as a result of greater quality
improvements in the home health industry over the life of the HHVBP
Model. The financial estimates were based on the analysis of hospital,
home health and skilled nursing facility claims data from nine states
using the most recent 2014 Medicare claims data. A study published in
2002 by the Journal of the American Geriatric Society (JAGS),
``Improving patient outcomes of home health care: findings from two
demonstration trials of outcome-based quality improvement,'' formed the
basis for CMMI's projections.\127\ That study observed a
hospitalization relative rate of decline of 22-percent to 26-percent
over the 3-year and 4-year demonstration periods (the 1st year of each
being the base year) for the national and New York trials. CMMI assumed
a conservative savings estimate of up to a 6-percent ultimate annual
reduction in hospitalizations and up to a 1.0-percent ultimate annual
reduction in SNF admissions and took into account costs incurred from
the beneficiary remaining in the HHA if the hospitalization did not
occur; resulting in total projected six performance year gross savings
of $378 million. Based on the JAGS study, which observed
hospitalization reductions of over 20-percent, the 6-percent ultimate
annual hospitalization reduction assumptions are considered reasonable.
---------------------------------------------------------------------------
\127\ Shaughnessy, et al. ``Improving patient outcomes of home
health care: findings from two demonstration trials of outcome-based
quality improvement,'' available at https://www.ncbi.nlm.nih.gov/pubmed/12164991.
---------------------------------------------------------------------------
IX. Federalism Analysis
Executive Order 13132 on Federalism (August 4, 1999) 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. We have reviewed this proposed rule under the threshold
criteria of Executive Order 13132, Federalism, and have determined that
it will not have substantial direct effects on the rights, roles, and
responsibilities of states, local or tribal governments.
List of Subjects
42 CFR part 409
Health facilities, Medicare
42 CFR Part 484
Health facilities, Health professions, Medicare, and Reporting and
recordkeeping requirements.
For the reasons set forth in the preamble, the Centers for Medicare
& Medicaid Services amends 42 CFR chapter IV as set forth below:
PART 409--HOSPITAL INSURANCE BENEFITS
0
1. The authority citation for part 409 continues to read as follows:
Authority: Secs. 1102 and 1871 of the Act (42 U.S.C. 1302 and
1395hh).
0
2. Section 409.50 is revised to read as follows:
Sec. 409.50 Coinsurance for durable medical equipment (DME) and
applicable disposable devices furnished as a home health service.
The coinsurance liability of the beneficiary or other person for
DME or applicable disposable devices (as defined in section 1834(s)(2))
furnished as a home health service is 20 percent of the customary
(insofar as reasonable) charge for the services.
PART 484--HOME HEALTH SERVICES
0
3. The authority citation for part 484 continues to read as follows:
Authority: Secs 1102 and 1871 of the Act (42 U.S.C. 1302 and
1395(hh)) unless otherwise indicated.
0
4. Section 484.240 is amended by revising paragraph (d) to read as
follows:
Sec. 484.240 Methodology used for the calculation of the outlier
payment.
* * * * *
(d) CMS imputes the cost for each episode by multiplying the
national per-15 minute unit amount of each discipline by the number of
15 minute units in the discipline and computing the total imputed cost
for all disciplines.
* * * * *
0
5. Section 484.305 is amended by revising the definition of
``Benchmark'' and removing the definition of ``Starter Set'' and to
read as follows:
Sec. 484.305 Definitions.
* * * * *
Benchmark refers to the mean of the top decile of Medicare-
certified HHA performance on the specified quality measure during the
baseline period, calculated for each state.
* * * * *
0
6. Section 484.315 is amended by revising paragraph (a) to read as
follows:
Sec. 484.315 Data reporting for measures and evaluation under the
Home Health Value-Based Purchasing (HHVBP) Model.
(a) Competing home health agencies will be evaluated using a set of
quality measures.
* * * * *
Sec. 484.320 [Amended]
0
7. Section 484.320 is amended by:
0
a. Amending paragraphs (a), (b), and (c) by removing the phrase ``in
the starter set,''.
0
b. Amending paragraph (d) by removing the phrase ``in the starter
set''.
0
8. Section 484.335 is added to read as follows:
Sec. 484.335 Appeals Process for the Home Health Value-Based
Purchasing (HHVBP) Model.
(a) Requests for recalculation--(1) Matters for recalculation.
Subject to the limitations on review under section 1115A of the Act, a
HHA may submit a request for recalculation under this section if it
wishes to dispute the calculation of the following:
(i) Interim performance scores.
(ii) Annual total performance scores.
(iii) Application of the formula to calculate annual payment
adjustment percentages.
(2) Time for filing a request for recalculation. A recalculation
request must be submitted in writing within 15 calendar days after CMS
posts the HHA-specific information on the HHVBP Secure Portal, in a
time and manner specified by CMS.
(3) Content of request. (i) The provider's name, address associated
with the services delivered, and CMS Certification Number (CCN).
[[Page 43788]]
(ii) The basis for requesting recalculation to include the specific
quality measure data that the HHA believes is inaccurate or the
calculation the HHA believes is incorrect.
(iii) Contact information for a person at the HHA with whom CMS or
its agent can communicate about this request, including name, email
address, telephone number, and mailing address (must include physical
address, not just a post office box).
(iv) The HHA may include in the request for reconsideration
additional documentary evidence that CMS should consider. Such
documents may not include data that was to have been filed by the
applicable data submission deadline, but may include evidence of timely
submission.
(4) Scope of review for recalculation. In conducting the
recalculation, CMS will review the applicable measures and performance
scores, the evidence and findings upon which the determination was
based, and any additional documentary evidence submitted by the home
health agency. CMS may also review any other evidence it believes to be
relevant to the recalculation.
(5) Recalculation decision. CMS will issue a written notification
of findings. A recalculation decision is subject to the request for
reconsideration process in accordance with paragraph (b) of this
section.
(b) Requests for reconsideration--(1) Matters for reconsideration.
A home health agency may request reconsideration of the recalculation
of the annual total performance score and payment adjustment percentage
following a recalculation request submitted under Sec. 484.335(a) or
the decision to deny a HHA's recalculation request submitted under
paragraph (a) of this section.
(2) Time for filing a request for reconsideration. The request for
reconsideration must be submitted via the HHVBP Secure Portal within 15
calendar days from CMS' notification to the HHA contact of the outcome
of the recalculation process.
(3) Content of request. (i) The name of the HHA, address associated
with the services delivered, and CMS Certification Number (CCN).
(ii) The basis for requesting reconsideration to include the
specific quality measure data that the HHA believes is inaccurate or
the calculation the HHA believes is incorrect.
(iii) Contact information for a person at the HHA with whom CMS or
its agent can communicate about this request, including name, email
address, telephone number, and mailing address (must include physical
address, not just a post office box).
(iv) The HHA may include in the request for reconsideration
additional documentary evidence that CMS should consider. Such
documents may not include data that was to have been filed by the
applicable data submission deadline, but may include evidence of timely
submission.
(4) Scope of review for reconsideration. In conducting the
reconsideration review, CMS will review the applicable measures and
performance scores, the evidence and findings upon which the
determination was based, and any additional documentary evidence
submitted by the HHA. CMS may also review any other evidence it
believes to be relevant to the reconsideration. The HHA must prove its
case by a preponderance of the evidence with respect to issues of fact
(5) Reconsideration decision. CMS reconsideration officials will
issue a written determination.
Dated: June 2, 2016.
Andrew M. Slavitt,
Acting Administrator, Centers for Medicare & Medicaid Services.
Dated: June 23, 2016.
Sylvia M. Burwell,
Secretary, Department of Health and Human Services.
[FR Doc. 2016-15448 Filed 6-27-16; 4:15 pm]
BILLING CODE 4120-01-P
