Medicare and Medicaid Programs; CY 2016 Home Health Prospective Payment System Rate Update; Home Health Value-Based Purchasing Model; and Home Health Quality Reporting Requirements, 39839-39914 [2015-16790]
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Vol. 80
Friday,
No. 132
July 10, 2015
Part II
Department of Health and Human Services
asabaliauskas on DSK5VPTVN1PROD with PROPOSALS
Center for Medicare & Medicaid Services
42 CFR Parts 409, 424, and 484
Medicare and Medicaid Programs; CY 2016 Home Health Prospective
Payment System Rate Update; Home Health Value-Based Purchasing
Model; and Home Health Quality Reporting Requirements; Proposed Rules
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Federal Register / Vol. 80, No. 132 / Friday, July 10, 2015 / Proposed Rules
DEPARTMENT OF HEALTH AND
HUMAN SERVICES
Center for Medicare & Medicaid
Services
42 CFR Parts 409, 424, and 484
[CMS–1625–P]
RIN 0938–AS46
Medicare and Medicaid Programs; CY
2016 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 Home Health Prospective
Payment System (HH PPS) rates,
including the national, standardized 60day episode payment rates, the national
per-visit rates, and the non-routine
medical supply (NRS) conversion factor
under the Medicare prospective
payment system for home health
agencies (HHAs), effective for episodes
ending on or after January 1, 2016. As
required by the Affordable Care Act, this
proposed rule implements the third year
of the four-year phase-in of the rebasing
adjustments to the HH PPS payment
rates. This proposed rule provides
information on our efforts to monitor
the potential impacts of the rebasing
adjustments. This proposed rule also
proposes: reductions to the national,
standardized 60-day episode payment
rate in CY 2016 and CY 2017 of 1.72
percent in each year to account for
estimated case-mix growth unrelated to
increases in patient acuity (nominal
case-mix growth) between CY 2012 and
CY 2014; a HH value-based purchasing
(HHVBP) model to be implemented
beginning January 1, 2016 in which all
Medicare-certified HHAs in selected
states will be required to participate;
changes to the home health quality
reporting program requirements; and
minor technical regulations text
changes. Finally, this proposed rule
would update the HH PPS case-mix
weights using the most current,
complete data available at the time of
rulemaking and provide an update on
the Report to Congress regarding the
home health (HH) study.
DATES: To be assured consideration,
comments must be received at one of
the addresses provided below, no later
than 5 p.m. on September 4, 2015.
ADDRESSES: In commenting, please refer
to file code CMS–1625–P. Because of
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SUMMARY:
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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–1625–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–1625–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:
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Hillary Loeffler, (410) 786–0456, for
general information about the HH PPS.
Michelle Brazil, (410) 786–1648 for
information about the HH quality
reporting program.
Lori Teichman, (410) 786–6684, for
information about HHCAHPS.
Robert Flemming, (844) 280–5628, for
information about the HHVBP model.
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: 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
D. Advancing Health Information Exchange
III. Proposed Provisions of the Home Health
Prospective Payment System
A. Monitoring for Potential Impacts—
Affordable Care Act Rebasing
Adjustments
B. CY 2016 HH PPS Case-Mix Weights and
Proposed Reduction to the National,
Standardized 60-Day Episode Payment
Rate To Account for Nominal Case-Mix
Growth
1. CY 2016 HH PPS Case-Mix Weights
2. Reduction to the National, Standardized
60-Day Episode Payment Rate to
Account for Nominal Case-Mix Growth
C. CY 2016 Home Health Rate Update
1. CY 2016 Home Health Market Basket
Update
2. CY 2016 Home Health Wage Index
3. CY 2016 Annual Payment Update
a. Background
b. CY 2016 National, Standardized 60-Day
Episode Payment Rate
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c. CY 2016 National Per-Visit Rates
d. Low-Utilization Payment Adjustment
(LUPA) Add-On Factors
e. CY 2016 Nonroutine Medical Supply
Payment Rates
f. Rural Add-On
D. Payments for High-Cost Outliers Under
the HH PPS
E. Report to Congress on the Home Health
Study Required by Section 3131(d) of the
Affordable Care Act and an Update on
Subsequent Research and Analysis
F. Technical Regulations Text Changes
IV. Proposed Home Health Value-Based
Purchasing (HHVBP) Model
V. Proposed Provisions of 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. HH QRP Quality Measures and
Measures Under Consideration for
Future Years
D. Form, Manner, and Timing of OASIS
Data Submission and OASIS Data for
Annual Payment Update
1. Statutory Authority
2. Home Health Quality Reporting Program
Requirements for CY 2016 Payment and
Subsequent Years
3. Previously Established Pay-for-Reporting
Performance Requirement for
Submission of OASIS Quality Data
E. Home Health Care CAHPS Survey
(HHCAHPS)
1. Background and Description of
HHCAHPS
2. HHCAHPS Oversight Activities
3. HHCAHPS Requirements for the CY
2016 APU
4. HHCAHPS Requirements for the CY
2017 APU
5. HHCAHPS Requirements for the CY
2018 APU
6. HHCAHPS Reconsideration and Appeals
Process
7. Summary
F. Public Display of Home Health Quality
Data for the HH QRP
VI. Collection of Information Requirements
VII. Response to Comments
VII. Regulatory Impact Analysis
Regulations Text
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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
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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
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
(P.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
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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
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 HHAs for calendar
year (CY) 2016, as required under
section 1895(b) of the Social Security
Act (the Act). This would reflect the
third year of the four-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 also discusses our
efforts to monitor the potential impacts
of the rebasing adjustments mandated
by section 3131(a) of the Affordable
Care Act. This rule proposes:
Reductions to the national, standardized
60-day episode payment rate in CY 2016
and CY 2017 of 1.72 percent in each
year 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; a
HH Value-Based Purchasing (VBP)
model, in which certain Medicarecertified HHAs would be required to
participate beginning January 1, 2016,
under the authority of section 1115(A)
of the Act; changes to the home health
quality reporting program requirements
under section 1895(b)(3)(B)(v)(II) of the
Act; and minor technical regulations
text changes in 42 CFR parts 409, 424,
and 484 to better align the payment
requirements with recent statutory and
regulatory changes for home health
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services. Finally, this proposed rule
would update the case-mix weights
under section 1895(b)(4)(A)(i) and
(b)(4)(B) of the Act and provide an
update on the Report to Congress
regarding the HH study required by
section 3131(d) of the Affordable Care
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 final rule, ‘‘Medicare and
Medicaid Programs; Home Health
Prospective Payment System Rate
Update for 2014, Home Health Quality
Reporting Requirements, and Cost
Allocation of Home Health Survey
Expenses’’ (78 FR 77256, December 2,
2013), we are implementing the third
year of the four-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
2016 would 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.
This proposed rule also discusses our
efforts to monitor the potential impacts
of the rebasing adjustments in section
III.A. 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 addition, in section
III.B.2 of this rule, we propose to reduce
to the national, standardized 60-day
episode payment rate in CY 2016 and
CY 2017 by 1.72 percent in each year to
account for estimated case-mix growth
unrelated to increases in patient acuity
(nominal case-mix growth) between CY
2012 and CY 2014. 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 2.9 percent, minus 0.6
percentage point for productivity as
required by section 1895(b)(3)(B)(vi)(I)
of the Act. In the CY 2015 final rule (79
FR 66083 through 66087), we
incorporated new geographic area
designations, set out in a February 28,
2013 office of Management and Budget
(OMB) bulletin, into the home health
wage index. For CY 2015, we
implemented a wage index transition
policy consisting of a 50/50 blend of the
old geographic area delineations and the
new geographic area delineations. In
section III.C.2 of this proposed rule, we
propose to update the CY 2016 home
health wage index using solely the new
geographic area designations. In section
III.D of this proposed rule, we discuss
payments for high cost outliers. In
section III.E, we propose to make several
technical corrections in § 409, 424, and
§ 484 to better align the payment
requirements with recent statutory and
regulatory changes for home health
services. The sections include
§ 409.43(e), § 424.22(a), § 484.205(d),
§ 484.205(e), § 484.220, § 484.225,
§ 484.230, § 484.240(b), § 484.240(e),
§ 484.240(f), § 484.245. In section III.F,
we discuss the Report to Congress on
the home health study required by
section 3131(d) of the Affordable Care
Act and provide an update on
subsequent research and analysis.
In section IV of this proposed rule, we
propose a HHVBP model to be
implemented beginning January 1, 2016.
Medicare-certified HHAs selected for
inclusion in the HHVBP model would
be required to compete for payment
adjustments to their current PPS
reimbursements based on quality
performance. A competing Medicarecertified HHA is defined as an agency
having a current Medicare certification
and which is being reimbursed by CMS
for home health care delivered within
any of the nine states randomly selected
under CMS’ proposed selection
methodology.
This proposed rule also includes
changes to the home health quality
reporting program in section III.V,
including the proposal of one new
quality measure, the establishment of a
minimum threshold for submission of
Outcome and Assessment Information
Set (OASIS) assessments for purposes of
quality reporting compliance, and
submission dates for Home Health Care
Consumer Assessment of Healthcare
Providers and Systems Survey
(HHCAHPS) Survey through CY 2018.
C. Summary of Costs and Transfers
TABLE 1—SUMMARY OF COSTS AND TRANSFERS
Provision description
Costs
Transfers
CY 2016 HH PPS Payment Rate Update
........................
CY 2016 HHVBP Model ...........................
........................
The overall economic impact of the HH PPS payment rate update is an estimated
¥$350 million (¥1.8 percent) in payments to HHAs.
The overall economic impact of the HHVBP model provision for CY 2018 through
2022 is an estimated $380 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.
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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.
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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 Social
Security Act (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.
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Section 1895(b)(3)(A) of the Act
requires the following: (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
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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 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 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
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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
§ 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 in section 3131 of the
Affordable Care Act is the 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 two 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 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.
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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 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
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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
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 requires 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 must
phase in any adjustment over a fouryear 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 specifies that the
maximum rebasing adjustment is to 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 second
year of the four-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
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Skilled Nursing .................................................................................................................................................
Home Health Aide ...........................................................................................................................................
Physical Therapy .............................................................................................................................................
Occupational Therapy ......................................................................................................................................
Speech-Language Pathology ..........................................................................................................................
Medical Social Services ...................................................................................................................................
D. Advancing Health Information
Exchange
HHS has a number of initiatives
designed to encourage and support the
adoption of health information
technology and to promote nationwide
health information exchange to improve
health care. As discussed in the August
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2013 Statement ‘‘Principles and
Strategies for Accelerating Health
Information Exchange’’ (available at
https://www.healthit.gov/sites/default/
files/acceleratinghieprinciples_
strategy.pdf), HHS believes that all
individuals, their families, their
healthcare and social service providers,
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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
and payers should have consistent and
timely access to health information in a
standardized format that can be securely
exchanged between the patient,
providers, and others involved in the
individual’s care. Health IT that
facilitates the secure, efficient and
effective sharing and use of health-
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related information when and where it
is needed is an important tool for
settings across the continuum of care,
including home health. While home
health providers are not eligible for the
Medicare and Medicaid EHR Incentive
Programs, effective adoption and use of
health information exchange and health
IT tools will be essential as these
settings seek to improve quality and
lower costs through initiatives such as
value-based purchasing.
The Office of the National
Coordinator for Health Information
Technology (ONC) has released a
document entitled ‘‘Connecting Health
and Care for the Nation: A Shared
Nationwide Interoperability Roadmap
Draft Version 1.0 (draft Roadmap)
(available at https://www.healthit.gov/
sites/default/files/nationwideinteroperability-roadmap-draft-version1.0.pdf) which describes barriers to
interoperability across the current
health IT landscape, the desired future
state that the industry believes will be
necessary to enable a learning health
system, and a suggested path for moving
from the current state to the desired
future state. In the near term, the draft
Roadmap focuses on actions that will
enable a majority of individuals and
providers across the care continuum to
send, receive, find and use a common
set of electronic clinical information at
the nationwide level by the end of 2017.
The Roadmap’s goals also align with the
IMPACT Act of 2014 which requires
assessment data to be standardized and
interoperable to allow for exchange of
the data. Moreover, the vision described
in the draft Roadmap significantly
expands the types of electronic health
information, information sources and
information users well beyond clinical
information derived from electronic
health records (EHRs). This shared
strategy is intended to reflect important
actions that both public and private
sector stakeholders can take to enable
nationwide interoperability of electronic
health information such as: (1)
Establishing a coordinated governance
framework and process for nationwide
health IT interoperability; (2) improving
technical standards and implementation
guidance for sharing and using a
common clinical data set; (3) enhancing
incentives for sharing electronic health
information according to common
technical standards, starting with a
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common clinical data set; and (4)
clarifying privacy and security
requirements that enable
interoperability.
In addition, ONC has released the
draft version of the 2015 Interoperability
Standards Advisory (available at https://
www.healthit.gov/standards-advisory),
which provides a list of the best
available standards and implementation
specifications to enable priority health
information exchange functions.
Providers, payers, and vendors are
encouraged to take these ‘‘best available
standards’’ into account as they
implement interoperable health
information exchange across the
continuum of care, including care
settings such as behavioral health, longterm and post-acute care, and home and
community-based service providers.
We encourage stakeholders to utilize
health information exchange and
certified health IT to effectively and
efficiently help providers improve
internal care delivery practices, engage
patients in their care, support
management of care across the
continuum, enable the reporting of
electronically specified clinical quality
measures (eCQMs), and improve
efficiencies and reduce unnecessary
costs. As adoption of certified health IT
increases and interoperability standards
continue to mature, HHS will seek to
reinforce standards through relevant
policies and programs.
III. Proposed Provisions of the Home
Health Prospective Payment System
A. Monitoring for Potential Impacts—
Affordable Care Act Rebasing
Adjustments
1. Analysis of FY 2013 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 four
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39845
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 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.
For this proposed rule, we analyzed
2013 HHA cost report data and 2013
HHA claims data to determine whether
the average cost per episode was higher
using 2013 cost report data compared to
the 2011 cost report and 2012 claims
data used in calculating the rebasing
adjustments. To determine the 2013
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
2013 cost reports by size, facility type,
and urban/rural location so the costs per
visit were nationally representative
according to 2013 claims data. The 2013
average number of visits was taken from
2013 claims data. We estimate the cost
of a 60-day episode in CY 2013 to be
$2,402.11 using 2013 cost report data
(Table 3). Our latest analysis of 2013
cost report and 2013 claims data
suggests that an even larger reduction
(¥5.02 percent) than the reduction
described in the CY 2014 HH PPS final
rule (¥3.45 percent) or the reduction
described in the CY 2015 HH PPS final
rule (¥4.21) would have been needed in
order to align payments with costs.
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TABLE 3—2013 ESTIMATED COST PER EPISODE
2013 average
costs per visit
2013 average
number of
visits
2013 60-day
episode costs
Skilled Nursing .............................................................................................................................
Home Health Aide .......................................................................................................................
Physical Therapy .........................................................................................................................
Occupational Therapy ..................................................................................................................
Speech-Language Pathology ......................................................................................................
Medical Social Services ...............................................................................................................
$131.43
59.87
154.96
154.11
164.59
211.02
9.28
2.41
5.03
1.22
0.25
0.14
$1,219.67
144.29
779.45
188.01
41.15
29.54
Total ......................................................................................................................................
........................
18.33
2,402.11
Discipline
Source: FY 2013 Medicare cost report data and 2013 Medicare claims data from the standard analytic file (as of June 30, 2014) for episodes
(excluding low-utilization payment adjusted episodes and partial-episode-payment adjusted episodes) ending on or before December 31, 2013 for
which we could link an OASIS assessment.
2. MedPAC Report to the Congress:
Home Health Payment Rebasing
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Section 3131(a) of the Affordable Care
Act required the Medicare Payment
Advisory Commission (MedPAC) to
assess, by January 1, 2015, the impact of
the mandated rebasing adjustments on
quality of and beneficiary access to
home health care. As part of this
assessment, the statute required
MedPAC to consider the impact on care
delivered by rural, urban, nonprofit, and
for-profit home health agencies.
MedPAC’s Report to Congress noted that
the rebasing adjustments are partially
offset by the payment update each year
and across all four years of the phasein of the rebasing adjustments the
cumulative net reduction would equal
about 2 percent. MedPAC concluded
that, as a result of the payment update
offsets to the rebasing adjustments, HHA
margins are likely to remain high under
the current rebasing policy and quality
of care and beneficiary access to care are
unlikely to be negatively affected.1
As we noted in the CY 2014 HH PPS
final rule (78 FR 72291), MedPAC’s past
reviews of access to home health care
found that access generally remained
adequate during periods of substantial
decline in the number of agencies.
MedPAC stated that this is due in part
to the low capital requirements for
home health care services that allow the
industry to react rapidly when the
supply of agencies changes or contracts.
As described in section III.A.3, the
number of HHAs billing Medicare for
home health services in CY 2013 is 80
percent higher than the number of
HHAs billing Medicare for home health
services in 2001. Even if some HHAs
were to exit the program due to possible
reimbursement concerns, the home
health market would be expected to
remain robust.
3. Analysis of CY 2014 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 year of the four-year phase-in of
the rebasing adjustments (CY 2014), the
first calendar year of the HH PPS (CY
2001), and claims data for the three
years before implementation of the
rebasing adjustments (CY 2011–2013).
Preliminary analysis of CY 2014 home
health claims data indicates that the
number of episodes decreased by 3.8
percent between 2013 and 2014. In
addition, the number of home health
users decreased by approximately 3
percent between 2013 and 2014, while
the number of FFS beneficiaries has
remained the same. 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,
driven mostly by decreases TX and FL,
two of the six states with the highest
utilization of Medicare home health (see
Table 3 and Table 4). The HHAs that no
longer billed Medicare for home health
services in CY 2014 typically served
beneficiaries that were nearly twice as
likely to be dually-eligible for both
Medicare and Medicaid in CY 2013
compared to the national average for all
HHAs in CY 2013. We note that in CY
2014 there were 3.0 HHAs per 10,000
FFS beneficiaries, the same number of
HHAs per 10,000 FFS beneficiaries as
there was in 2011, but markedly higher
than the 1.9 HHAs per 10,000 FFS
beneficiaries in 2001. If we were to
exclude the six states with the highest
home health utilization (see Table 5),
the number of episodes amongst the
remaining states (including Guam,
Puerto Rico, and the Virgin Islands)
decreased by 2.6 percent between 2013
and 2014, the number of home health
users decreased by approximately 2.4
percent between 2013 and 2014, and the
number of HHAs billing Medicare for
home health services remained virtually
the same (a net decrease of only 1 HHA).
We would note that preliminary data
on hospital and skilled nursing facility
discharges and days indicates that there
was a decrease in hospital discharges of
approximately 3 percent and a decrease
in SNF days of approximately 2 percent
in CY 2014. 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 2014
2001
Number of episodes .............................................................
Beneficiaries receiving at least 1 episode (Home Health
Users) ...............................................................................
1 Medicare Payment Advisory Commission
(MedPAC), ‘‘Report to the Congress: Impact of
Home Health Payment Rebasing on Beneficiary
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2011
2012
2013
2014
3,896,502
6,821,459
6,727,875
6,708,923
6,451,283
2,412,318
3,449,231
3,446,122
3,484,579
3,381,635
Access to and Quality of Care’’. December 2014.
Washington, DC. Accessed on 5/05/15 at: https://
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TABLE 4—HOME HEALTH STATISTICS, CY 2001 AND CY 2011 THROUGH CY 2014—Continued
2001
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
2012
2013
2014
34,899,167
0.11
37,686,526
0.18
38,224,640
0.18
38,505,609
0.17
38,506,534
0.17
6.9%
6,511
1.9
9.2%
11,446
3.0
9.0%
11,746
3.1
9.0%
11,889
3.1
8.8%
11,693
3.0
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; and accessed on May 7, 2015 for CY 2001 and CY 2014 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.
For the six states (TX, LA, OK, MS,
FL, and IL) with the highest utilization
of Medicare home health (as measured
by the number of episodes per Part A
and/or Part B FFS beneficiaries), the
number of episodes decreased by 5.7
percent, the number of home health
users decreased by 4.3 percent, and the
number of HHAs billing Medicare
decreased by 3.7 percent (5,280–5,085)
between 2013 and 2014 (see Table 5). A
possible contributing factor to these
decreases may be the temporary
moratorium on the enrollment of new
HHAs, effective July 31, 2013, for
Miami, FL and Chicago, IL and the
temporary moratorium on enrollment of
new HHAs, effective February 4, 2014,
for Fort Lauderdale, FL; Detroit, MI;
Dallas, TX; and Houston, TX. The
temporary moratoria on enrollment of
new HHAs in Miami, FL; Chicago, IL;
Fort Lauderdale, FL; Detroit, MI; Dallas,
TX; and Houston, TX were extended for
6 months on August 1, 2014 and again
for 6 months effective January 29, 2015
(80 FR 5551).
TABLE 5—HOME HEALTH STATISTICS FOR THE STATES WITH THE HIGHEST NUMBER OF HOME HEALTH EPISODES PER
PART A AND/OR PART B FFS BENEFICIARIES, CY 2001 AND CY 2011 THROUGH CY 2014
Year
Number of Episodes ....................................
Beneficiaries Receiving at Least 1 Episode
(Home Health Users) ...............................
Part A and/or Part B FFS Beneficiaries ......
Episodes per Part A and/or Part B FFS
beneficiaries .............................................
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Home Health Users as a Percentage of
Part A and/or Part B FFS Beneficiaries ...
HHAs Providing at Least 1 Episode ............
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TX
FL
OK
MS
LA
IL
2001
2011
2012
2013
2014
285,710
1,107,605
1,054,244
995,555
941,815
284,579
701,426
691,255
689,269
651,940
77,149
203,112
196,887
196,713
189,421
73,353
153,983
148,516
143,428
141,293
124,789
249,479
230,115
215,590
196,495
162,686
433,117
423,462
421,309
389,850
2001
2011
2012
2013
2014
155,802
363,474
350,803
333,396
319,492
195,678
355,900
354,838
357,099
343,231
36,919
67,218
65,948
66,502
65,392
35,769
55,818
55,438
55,453
54,890
50,760
77,677
74,755
73,888
69,328
105,115
192,921
191,936
191,961
179,835
2001
2011
2012
2013
2014
2,132,310
2,597,406
2,604,458
2,535,611
2,564,292
2,246,313
2,454,124
2,451,790
2,454,216
2,464,748
480,556
549,687
558,500
568,815
580,267
436,751
476,497
480,218
483,439
491,482
528,287
561,531
568,483
574,654
575,832
1,543,158
1,785,278
1,812,241
1,836,862
1,674,935
2001
2011
2012
2013
2014
0.13
0.43
0.40
0.39
0.37
0.13
0.29
0.28
0.28
0.26
0.16
0.37
0.35
0.35
0.33
0.17
0.32
0.31
0.30
0.29
0.24
0.44
0.40
0.38
0.34
0.11
0.24
0.23
0.23
0.23
2001
2011
2012
2013
2014
7.3%
14.0%
13.5%
13.2%
12.5%
8.7%
14.5%
14.5%
14.6%
13.9%
7.7%
12.2%
11.8%
11.7%
11.3%
8.2%
11.7%
11.5%
11.5%
11.2%
9.6%
13.8%
13.2%
12.9%
12.0%
6.8%
10.8%
10.6%
10.5%
10.7%
2001
2011
2012
2013
2014
799
2,472
2,549
2,600
2,558
330
1,426
1,430
1,357
1,230
180
252
254
262
262
61
51
48
48
46
242
216
213
210
205
273
743
783
803
784
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TABLE 5—HOME HEALTH STATISTICS FOR THE STATES WITH THE HIGHEST NUMBER OF HOME HEALTH EPISODES PER
PART A AND/OR PART B FFS BENEFICIARIES, CY 2001 AND CY 2011 THROUGH CY 2014—Continued
Year
HHAs per 10,000 Part A and/or B FFS
beneficiaries .............................................
2001
2011
2012
2013
2014
TX
FL
3.7
9.5
9.8
10.3
10.0
OK
1.5
5.8
5.8
5.5
5.0
MS
3.7
4.6
4.5
4.6
4.5
LA
1.4
1.1
1.0
1.0
0.9
IL
4.6
3.8
3.7
3.7
3.6
1.8
4.2
4.3
4.4
4.7
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; and accessed on May 7, 2015 for CY 2001 and CY 2014 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.
asabaliauskas on DSK5VPTVN1PROD with PROPOSALS
In addition to examining home health
claims data from the first year of the
implementation of rebasing adjustments
required by the Affordable Care Act and
comparing utilization in that year (CY
2014) to the three years prior 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 2014. 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 $162
for CY 2014, the average total number of
visits per 60-day episode of care has
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declined, most notably between CY
2009 (21.7 visits per episode) and CY
2014 (18.0 visit per episode). As noted
in section II.C, we 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 2011and 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
slightly, the number of skilled nursing
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and home health aide visits have
decreased, between CY 2009 and CY
2014. 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 seems 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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39849
Figure 1: Average Total Number of Visits and Average Payment per Visit for a Medicare
Home Health 60-Da E isode of Care, CY 2001 throu h CY 2014
Source: National claims history (NCH) data obtained from Chronic Condition Warehouse (CCW)- Accessed on
May 21, 2014.
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asabaliauskas on DSK5VPTVN1PROD with PROPOSALS
Note(s):
These results exclude LUPA episodes, but 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.
Federal Register / Vol. 80, No. 132 / Friday, July 10, 2015 / Proposed Rules
asabaliauskas on DSK5VPTVN1PROD with PROPOSALS
We will continue to monitor for
potential impacts due to 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. CY 2016 HH PPS Case-Mix Weights
and Proposed Reduction to the
National, Standardized 60-Day Episode
Payment Rate To Account for Nominal
Case-Mix Growth
1. CY 2016 HH PPS Case-Mix Weights
For CY 2014, as part of the rebasing
effort mandated by the Affordable Care
Act, we reset the HH PPS case-mix
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weights, lowering the average case-mix
weight to 1.0000. To lower the HH PPS
case-mix weights to 1.0000, each HH
PPS case-mix weight was decreased by
the same factor (1.3464), thereby
maintaining the same relative values
between the weights. This ‘‘resetting’’ of
the HH PPS case-mix weights was done
in a budget neutral manner by inflating
the national, standardized 60-day
episode rate by the same factor (1.3464)
that was used to decrease the weights.
For CY 2015, 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 2016, we propose to use the same
methodology finalized in the CY 2008
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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 2016 HH
PPS case-mix weights, we used CY 2014
home health claims data (as of
December 31, 2014) with linked OASIS
data. These data are the most current
and complete data available at this time.
We will use CY 2014 home health
claims data (as of June 30, 2015) with
linked OASIS data to generate the CY
2016 HH PPS case-mix weights in the
CY 2016 HH PPS final rule. The process
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we used to calculate the HH PPS casemix 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 2013 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 2014 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.
TABLE 6—CASE-MIX ADJUSTMENT VARIABLES AND SCORES
Episode number within sequence of adjacent episodes .......................
Therapy visits .........................................................................................
EQUATION: ...........................................................................................
1 or 2
0–13
1
1 or 2
14+
2
3+
0–13
3
3+
14+
4
................
................
................
................
1
3
................
6
7
7
................
15
................
................
................
................
................
1
................
2
7
4
................
8
1
9
1
9
................
................
................
6
................
................
................
6
................
................
................
................
1
3
................
................
11
2
................
7
................
................
11
2
2
7
1
5
3
................
9
4
2
................
2
4
................
................
................
................
3
10
7
10
8
1
8
1
3
................
3
6
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
CLINICAL DIMENSION
1
2
3
4
5
6
..................................
..................................
..................................
..................................
..................................
..................................
7 ..................................
8 ..................................
9 ..................................
10 ................................
11 ................................
12 ................................
13 ................................
14 ................................
15 ................................
16 ................................
17 ................................
18 ................................
asabaliauskas on DSK5VPTVN1PROD with PROPOSALS
19 ................................
20 ................................
21 ................................
22 ................................
23 ................................
24 ................................
VerDate Sep<11>2014
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
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.
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TABLE 6—CASE-MIX ADJUSTMENT VARIABLES AND SCORES—Continued
25 ................................
26 ................................
27 ................................
28 ................................
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
................................
................................
................................
................................
................................
................................
................................
................................
................................
................................
................................
................................
................................
................................
................................
................................
................................
Primary Diagnosis = Skin 1—Traumatic wounds, burns, and post-operative complications.
Other Diagnosis = Skin 1—Traumatic wounds, burns, post-operative
complications.
Primary or Other Diagnosis = Skin 1—Traumatic wounds, burns, 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 ..................................................................
M1242 (Pain) = 3 or 4 ...........................................................................
M1308 = Two or more pressure ulcers at stage 3 or 4 ........................
M1324 (Most problematic pressure ulcer stage) = 1 or 2 .....................
M1324 (Most problematic pressure ulcer stage) = 3 or 4 .....................
M1334 (Stasis ulcer status) = 2 ............................................................
M1334 (Stasis ulcer status) = 3 ............................................................
M1342 (Surgical wound status) = 2 ......................................................
M1342 (Surgical wound status) = 3 ......................................................
M1400 (Dyspnea) = 2, 3, or 4 ...............................................................
M1620 (Bowel Incontinence) = 2 to 5 ...................................................
M1630 (Ostomy) = 1 or 2 ......................................................................
M2030 (Injectable Drug Use) = 0, 1, 2, or 3 .........................................
4
19
8
19
6
15
8
13
3
................
................
................
2
17
8
17
2
................
1
................
................
2
5
4
8
4
7
2
1
................
................
4
................
16
19
18
14
................
................
5
19
32
12
17
7
7
1
4
12
................
2
................
6
................
................
1
5
7
11
8
10
5
5
................
................
2
................
16
11
14
5
................
................
14
16
26
12
17
13
7
1
4
7
................
2
6
1
3
7
7
................
2
4
2
................
9
1
5
1
1
4
6
................
................
1
................
................
7
FUNCTIONAL DIMENSION
46
47
48
49
50
51
................................
................................
................................
................................
................................
................................
M1810
M1830
M1840
M1850
M1860
M1860
or M1820 (Dressing upper or lower body) = 1, 2, or 3 .............
(Bathing) = 2 or more ................................................................
(Toilet transferring) = 2 or more ................................................
(Transferring) = 2 or more .........................................................
(Ambulation) = 1, 2 or 3 ............................................................
(Ambulation) = 4 or more ..........................................................
asabaliauskas on DSK5VPTVN1PROD with PROPOSALS
Source: CY 2014 Medicare claims data for episodes ending on or before December 31, 2014 (as of December 31, 2014) for which we had a
linked OASIS assessment. LUPA episodes, outlier episodes, and episodes with SCIC or PEP adjustments were excluded.
Note(s): Points are additive; however, points may not be given for the same line item in the table more than once. Please see Medicare Home
Health Diagnosis Coding guidance at: https://www.cms.hhs.gov/HomeHealthPPS/03_coding&billing.asp for definitions of primary and secondary
diagnoses.
In updating the four-equation model
for CY 2016, using 2014 data (the last
update to the four-equation model for
CY 2015 used 2013 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 2013 and 2014. The CY 2016
four-equation model resulted in 130
point-giving variables being used in the
model (as compared to the 124 variables
for the 2015 recalibration). There were
nine variables that were added to the
model and three variables that were
dropped from the model due to the
absence of additional resources
associated with the variable. The points
for 18 variables increased in the CY
2016 four-equation model and the
points for 43 variables decreased in the
CY 2016 4-equation model. There were
58 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 2016 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
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 to guide where we placed our
thresholds. We tried to group scores
with similar average resource use within
the same level (even if it meant that
more or less than a third of episodes
2 For Step 1, 54% of episodes were in the medium
functional level (All with score 15).
For Step 2.1, 77.2% of episodes were in the low
functional level (Most with score 2 and 4).
For Step 2.2, 67.1% of episodes were in the low
functional level (All with score 0).
For Step 3, 60.9% of episodes were in the
medium functional level (Most with score 10).
For Step 4, 49.8% of episodes were in the low
functional level (Most with score 2).
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were placed within a level). The new
thresholds, based off of the CY 2016
four-equation model points are shown
in Table 7.
TABLE 7—CY 2016 CLINICAL AND FUNCTIONAL THRESHOLDS
1st and 2nd episodes
3rd+ episodes
All Episodes
20+
therapy
visits
0 to 13
therapy visits
14 to 19
therapy visits
0 to 13
therapy visits
14 to 19
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)
0 to 1 ...........
2 to 3 ...........
4+ ................
0 to 14 .........
15 ................
16+ ..............
0 ..................
1 to 7 ...........
8+ ................
0 to 6 ...........
7 to 13 .........
14+ ..............
0 ..................
1 ..................
2+ ................
0 to 6 ...........
7 to10 ..........
11+ ..............
0 to 3 ...........
4 to 12 .........
13+ ..............
0 ..................
1 to 7 ...........
8+ ................
0 to
4 to
17+
0 to
3 to
7+
Dimension:
Severity Level:
Clinical ...............................
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
3
16
2
6
variables in the payment regression
model updated with CY 2014 data. The
R-squared value for the payment
regression model is 0.4790 (an increase
from 0.4680 for the CY 2015
recalibration).
TABLE 8—PAYMENT REGRESSION MODEL
New payment
regression
coefficients
asabaliauskas on DSK5VPTVN1PROD with PROPOSALS
Variable Description
Step 1, Clinical Score Medium ........................................................................................................................................................
Step 1, Clinical Score High .............................................................................................................................................................
Step 1, Functional Score Medium ...................................................................................................................................................
Step 1, Functional Score High ........................................................................................................................................................
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 ..........................................................................................................................
Step 3, 3rd+ Episodes, 0–13 Therapy Visits ..................................................................................................................................
Step 4, All Episodes, 20+ Therapy Visits ........................................................................................................................................
Intercept ...........................................................................................................................................................................................
$23.43
57.50
73.18
110.39
42.51
163.27
34.24
88.01
58.37
210.67
10.64
65.24
9.87
89.22
53.47
83.07
70.04
231.22
14.07
63.20
444.92
485.03
¥73.86
889.81
378.68
Source: CY 2014 Medicare claims data for episodes ending on or before December 31, 2014 (as of December 31, 2014) 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
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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
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regression). This division constructs the
weight for each episode, which is
simply the ratio of the episode’s
predicted wage-weighted minutes of
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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 weights associated with 0
to 5 therapy visits are then 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 aligned 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
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 the 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 CY 2016 casemix weights shown in Table 9.
TABLE 9—CY 2016 CASE-MIX PAYMENT WEIGHTS
asabaliauskas on DSK5VPTVN1PROD with PROPOSALS
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
................
................
................
................
................
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................
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................
................
................
................
Step (episode and/or therapy visit ranges)
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
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,
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)
20:57 Jul 09, 2015
Jkt 235001
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 ....................................................................
4 When computing the average, we compute a
weighted average, assigning a value of one to each
PO 00000
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C1F1S3
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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
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............
............
............
............
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............
............
............
............
............
............
............
............
............
............
............
............
............
............
............
............
............
............
............
............
............
............
............
............
............
............
............
............
CY 2016
case-mix
weights
0.5969
0.7216
0.8462
0.9708
1.0954
1.2201
1.4237
1.6273
0.7123
0.8240
0.9357
1.0474
1.1591
1.2708
1.4643
1.6578
0.7709
0.8868
1.0027
1.1186
1.2345
1.3504
1.5410
1.7316
0.6339
0.7637
0.8935
1.0234
1.1532
1.2830
1.4994
1.7157
0.7492
0.8661
0.9830
1.0999
1.2169
1.3338
1.5400
1.7461
0.8079
0.9290
1.0501
normal episode and a value equal to the episode
length divided by 60 for PEPs.
E:\FR\FM\10JYP2.SGM
10JYP2
Federal Register / Vol. 80, No. 132 / Friday, July 10, 2015 / Proposed Rules
39855
TABLE 9—CY 2016 CASE-MIX PAYMENT WEIGHTS—Continued
asabaliauskas on DSK5VPTVN1PROD with PROPOSALS
Payment group
10334
10335
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
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
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................
................
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................
................
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................
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................
................
................
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................
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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)
Step (episode and/or therapy visit ranges)
1st and 2nd Episodes, 10 Therapy Visits .........................................................................
1st and 2nd Episodes, 11 to 13 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 ................................................................
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 .......................................................................................
20:57 Jul 09, 2015
Jkt 235001
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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
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10JYP2
............
............
............
............
............
............
............
............
............
............
............
............
............
............
............
............
............
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............
............
............
............
CY 2016
case-mix
weights
1.1712
1.2923
1.4134
1.6167
1.8200
0.6876
0.8424
0.9973
1.1522
1.3071
1.4619
1.6962
1.9304
0.8029
0.9449
1.0868
1.2288
1.3707
1.5127
1.7368
1.9609
0.8616
1.0077
1.1539
1.3000
1.4462
1.5923
1.8135
2.0347
0.4805
0.6403
0.8001
0.9599
1.1197
1.2795
1.4633
1.6471
1.8309
0.5648
0.7109
0.8570
1.0031
1.1492
1.2952
1.4806
1.6659
1.8512
0.6114
0.7644
0.9173
1.0703
1.2232
1.3761
1.5581
1.7401
1.9222
0.4961
0.6700
0.8440
1.0180
1.1920
1.3660
1.5546
1.7433
1.9320
0.5803
0.7406
0.9009
39856
Federal Register / Vol. 80, No. 132 / Friday, July 10, 2015 / Proposed Rules
TABLE 9—CY 2016 CASE-MIX PAYMENT WEIGHTS—Continued
Payment group
asabaliauskas on DSK5VPTVN1PROD with PROPOSALS
30133
30134
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
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
Step (episode and/or therapy visit ranges)
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 ............................................................................
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 would apply
a case-mix budget neutrality factor to
the CY 2016 national, standardized 60day episode payment rate (see section
III.B.1. of this proposed rule). The casemix budget neutrality factor is
calculated as the ratio of total payments
when the CY 2016 HH PPS case-mix
weights (developed using CY 2014
claims data) are applied to CY 2014
utilization (claims) data to total
payments when CY 2015 HH PPS casemix weights (developed using CY 2013
claims data) are applied to CY 2014
utilization data. This produces a casemix budget neutrality factor for CY 2016
of 1.0141, based on CY 2014 claims data
as of December 31, 2014.
VerDate Sep<11>2014
Clinical
and functional
levels
(1 = low;
2 = medium;
3= high)
20:57 Jul 09, 2015
Jkt 235001
2. Proposed Reduction to the National,
Standardized 60-Day Episode Payment
Rate To Account for Nominal Case-Mix
Growth
Section 1895(b)(3)(B)(iv) of the Act
gives the Secretary the authority to
implement payment reductions for
nominal case-mix growth (that is, casemix growth unrelated to changes in
patient acuity). Previously, we
accounted for nominal case-mix growth
through case-mix reductions
implemented from 2008 through 2013
(76 FR 68528–68543). As stated in the
2013 final rule, the goal of the
reductions for nominal case-mix growth
is to better align payment with real
changes in patient severity (77 FR
67077). Our analysis of data from CY
2000 through CY 2010 found that only
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............
............
............
............
............
............
............
............
............
............
............
............
............
............
............
............
............
............
............
............
............
............
............
............
............
............
............
............
............
............
............
............
............
............
............
............
............
............
............
............
............
............
CY 2016
case-mix
weights
1.0612
1.2214
1.3817
1.5719
1.7621
1.9523
0.6270
0.7941
0.9612
1.1284
1.2955
1.4626
1.6495
1.8364
2.0233
0.6211
0.8152
1.0093
1.2034
1.3975
1.5916
1.7826
1.9736
2.1647
0.7054
0.8858
1.0662
1.2466
1.4269
1.6073
1.7999
1.9924
2.1850
0.7521
0.9393
1.1265
1.3138
1.5010
1.6882
1.8774
2.0667
2.2559
15.97 percent of the total case-mix
change was real and 84.03 percent of
total case-mix change was nominal (77
FR 41553). In the CY 2015 HH PPS final
rule (79 FR 66032), we estimated that
total case-mix increased by 2.76 percent
between CY 2012 and CY 2013 and of
that amount, we estimated that 2.32
percent was a result of nominal casemix growth (2.76 ¥ (2.76 × 0.1597)).
However, for 2015, we did not
implement a reduction to the 2015
national, standardized 60-day episode
payment amount to account for nominal
case-mix growth, but stated that we
would continue to monitor case-mix
growth and may consider proposing
nominal case-mix reductions in the
future. Since the publication of the CY
2015 HH PPS final rule (79 FR 66032),
E:\FR\FM\10JYP2.SGM
10JYP2
asabaliauskas on DSK5VPTVN1PROD with PROPOSALS
Federal Register / Vol. 80, No. 132 / Friday, July 10, 2015 / Proposed Rules
MedPAC reported on their assessment
of the impact of the mandated rebasing
adjustments on quality of and
beneficiary access to home health care
as required by section 3131(a) of the
Affordable Care Act. As noted in section
III.A.2 of this proposed rule, MedPAC
concluded that quality of care and
beneficiary access to care are unlikely to
be negatively affected by the rebasing
adjustments. We further estimate that
case-mix increased by an additional
1.41 percent between CY 2013 and CY
2014 (as evidenced by the budget
neutrality factor of 1.0141 percent
described in section III.B.1 above). In
applying the 15.97 percent estimate of
real case-mix growth to the total
estimated case-mix growth from CY
2013 to CY 2014 (1.41 percent), we
estimate that case-mix increased by 1.18
percent (1.41 ¥ (1.41 × 0.1597)) as a
result of nominal case-mix growth (that
is, case-mix growth unrelated to changes
in patient acuity). Given the observed
nominal case-mix growth of 2.32
percent in 2013 and 1.18 percent in
2014, the reduction to offset the
nominal case-mix growth for these 2
years would be 3.41 percent (1 ¥ 1/
(1.0232 × 1.0118) = 0.0341).
We are proposing to implement this
3.41 percent reduction in equal
increments over 2 years. Specifically, in
addition to continuing our third year of
implementation of the rebasing
adjustments required under section
3131(a) of the Affordable Care Act, we
are proposing to apply a 1.72 percent (1
¥ 1/(1.0232 × 1.0118)1/2 = 1.72 percent)
reduction to the national, standardized
60-day episode payment rate each year
for 2 years, CY 2016 and CY 2017, under
the ongoing authority of section
1895(b)(3)(B)(iv) of the Act. These
reductions would adjust the national,
standardized 60-day episode payment
rate to account for nominal case-mix
growth between CY 2012 and CY 2014
built into the episode payment rate
through the 2015 and 2016 budget
neutrality factors. The reductions will
result in Medicare paying more
accurately for the delivery of home
health services and are separate from
the rebasing adjustments finalized in CY
2014 under section 1895(b)(3)(A)(iii) of
the Act, which were calculated using
CY 2012 claims and CY 2011 HHA cost
report data (which was the most current,
complete data at the time of the CY 2014
HH PPS proposed and final rules). We
will continue to monitor case-mix
growth and may consider whether to
propose additional nominal case-mix
reductions in future rulemaking.
We invite comments on the proposed
reduction to the national, standardized
60-day episode payment amount of 1.72
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percent in CY 2016 and 1.72 percent in
CY 2017 to account for nominal casemix growth from CY 2012 through CY
2014 and the associated changes in the
regulations text at § 484.220.
C. CY 2016 Home Health Rate Update
1. CY 2016 Home Health Market Basket
Update
Section 1895(b)(3)(B) of the Act
requires that the standard prospective
payment amounts for CY 2015 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 6708067090).
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. We note that the proposed
methodology for calculating and
applying the MFP adjustment to the
HHA payment update is similar to the
methodology used in other Medicare
provider payment systems as required
by section 3401 of the Affordable Care
Act.
Multifactor productivity is derived by
subtracting the contribution of labor and
capital input growth from output
growth. The projections of the
components of MFP are currently
produced by IGI, a nationally
recognized economic forecasting firm
with which CMS contracts to forecast
the components of the market basket
and MFP. As described in the CY 2015
HH PPS proposed rule (79 FR 38384
through 38386), in order to generate a
forecast of MFP, IGI replicated the MFP
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39857
measure calculated by the BLS using a
series of proxy variables derived from
IGI’s U.S. macroeconomic models. In
the CY 2015 HH PPS proposed rule, we
identified each of the major MFP
component series employed by the BLS
to measure MFP as well as provided the
corresponding concepts determined to
be the best available proxies for the BLS
series.
Beginning with the CY 2016
rulemaking cycle, the MFP adjustment
is calculated using a revised series
developed by IGI to proxy the aggregate
capital inputs. Specifically, IGI has
replaced the Real Effective Capital Stock
used for Full Employment GDP with a
forecast of BLS aggregate capital inputs
recently developed by IGI using a
regression model. This series provides a
better fit to the BLS capital inputs as
measured by the differences between
the actual BLS capital input growth
rates and the estimated model growth
rates over the historical time period.
Therefore, we are using IGI’s most
recent forecast of the BLS capital inputs
series in the MFP calculations beginning
with the CY 2016 rulemaking cycle. A
complete description of the MFP
projection methodology is available on
our Web site at https://www.cms.gov/
Research-Statistics-Data-and-Systems/
Statistics-Trends-and-Reports/
MedicareProgramRatesStats/
MarketBasketResearch.html. Although
we discuss the IGI changes to the MFP
proxy series in this proposed rule, in the
future, when IGI makes changes to the
MFP methodology, we will announce
them on our Web site rather than in the
annual rulemaking.
Using IGI’s first quarter 2015 forecast,
the MFP adjustment for CY 2016 (the
10-year moving average of MFP for the
period ending CY 2016) is projected to
be 0.6 percent. Thus, in accordance with
section 1895(b)(3)(B)(iii) of the Act, we
propose to base the CY 2016 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 2.9 percent based on
IGI’s first quarter 2015 forecast). We
propose to then reduce this percentage
increase by the current estimate of the
MFP adjustment for CY 2016 of 0.6
percentage point (the 10-year moving
average of MFP for the period ending
CY 2016 based on IGI’s first quarter
2015 forecast), in accordance with
1895(b)(3)(B)(vi). Therefore, the current
estimate of the CY 2016 HH update is
2.3 percent (2.9 percent market basket
update, less 0.6 percentage point MFP
adjustment). Furthermore, we note that
if more recent data are subsequently
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available (for example, a more recent
estimate of the market basket and MFP
adjustment), we would use such data to
determine the CY 2016 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 2016, the home
health update would be 0.3 percent (2.3
percent minus 2 percentage points).
2. CY 2016 Home Health Wage Index
asabaliauskas on DSK5VPTVN1PROD with PROPOSALS
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 2016, 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, prereclassified hospital wage index as the
wage adjustment to the labor portion of
the HH PPS rates. For CY 2016, the
updated wage data are for hospital cost
reporting periods beginning on or after
October 1, 2011 and before October 1,
2012 (FY 2012 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).
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. In adopting the CBSA
geographic designations, we provided a
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one-year transition in CY 2006 with a
blended wage index for all sites of
service. For CY 2006, the wage index for
each geographic area consisted of a
blend of 50 percent of the CY 2006
MSA-based wage index and 50 percent
of the CY 2006 CBSA-based wage index.
We referred to the blended wage index
as the CY 2006 HH PPS transition wage
index. As discussed in the CY 2006 HH
PPS final rule (70 FR 68132), since the
expiration of this one-year transition on
December 31, 2006, we have used the
full CBSA-based wage index values.
In this proposed rule, 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, and thus, no
hospital wage data on which to base the
calculation of the CY 2015 HH PPS
wage index. 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 2016, 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 2016, the only urban
area without inpatient hospital wage
data is Hinesville, GA (CBSA 25980).
b. Update
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.’’
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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 newest OMB delineations,
as described in OMB Bulletin No. 13–
01, beginning in CY 2015, including a
one-year transition with a blended wage
index for CY 2015. Because the one-year
transition period expires at the end of
CY 2015, the proposed HH PPS wage
index for CY 2016 is fully based on the
revised OMB delineations adopted in
CY 2015. The proposed CY 2016 wage
index is available on the CMS Web site
at https://www.cms.gov/Medicare/
Medicare-Fee-for-Service-Payment/
HomeHealthPPS/Home-HealthProspective-Payment-SystemRegulations-and-Notices.html.
3. CY 2016 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
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 2016 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:
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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 wageadjusted 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 2016 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 2016
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.1, a nominal case-mix
growth adjustment described in section
III.B.2, the rebasing adjustment
described in section II.C, and the MFPadjusted 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 2016 wage index and compared it to
39859
our simulation of total payments for
non-LUPA episodes using the 2015
wage index. By dividing the total
payments for non-LUPA episodes using
the 2016 wage index by the total
payments for non-LUPA episodes using
the 2015 wage index, we obtain a wage
index budget neutrality factor of 1.0006.
We would apply the wage index budget
neutrality factor of 1.0006 to the CY
2016 national, standardized 60-day
episode rate.
As discussed in section III.B.1 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 2016
national, standardized 60-day episode
payment rate. The case-mix weight
budget neutrality factor is calculated as
the ratio of total payments when CY
2016 case-mix weights are applied to CY
2014 utilization (claims) data to total
payments when CY 2015 case-mix
weights are applied to CY 2014
utilization data. The case-mix budget
neutrality factor for CY 2016 would be
1.0141 as described in section III.B.1 of
this proposed rule.
Next, as discussed in section III.B.2 of
this proposed rule, we would apply a
reduction of 1.72 percent to the
national, standardized 60-day episode
payment rate in CY 2016 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 payment rates by the CY 2016 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
CY 2016 national, standardized 60-day
episode payment rate is calculated in
Table 10.
TABLE 10—CY 2016 60-DAY NATIONAL, STANDARDIZED 60-DAY EPISODE PAYMENT AMOUNT
asabaliauskas on DSK5VPTVN1PROD with PROPOSALS
CY 2015 National,
standardized 60-day
episode payment
Wage index
budget
neutrality
factor
Case-mix
weights
budget
neutrality
factor
Nominal
case-mix
growth
adjustment
(1¥0.0172)
CY 2016
Rebasing
adjustment
CY 2016
HH Payment
update
percentage
CY 2016
National,
standardized
60-day
episode
payment
$2,961.38 .................................................
× 1.0006
× 1.0141
× 0.9828
¥$80.95
× 1.023
$2,938.37
The CY 2016 national, standardized
60-day episode payment rate for an
HHA that does not submit the required
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quality data is updated by the CY 2016
HH payment update (2.3 percent) minus
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2 percentage points and is shown in
Table 11.
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TABLE 11—FOR HHAS THAT DO NOT SUBMIT THE QUALITY DATA—CY 2015 NATIONAL, STANDARDIZED 60-DAY EPISODE
PAYMENT AMOUNT
CY 2015 National,
standardized 60-day
episode payment
Wage index
budget
neutrality
factor
Case-mix
weights
budget
neutrality
factor
Nominal casemix growth
adjustment
(1¥0.0172)
$2,961.38 .................................................
× 1.0006
× 1.0141
× 0.9828
c. CY 2016 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 CY 2016 national pervisit rates, we start with the CY 2015
national per-visit rates. We then apply
a wage index budget neutrality factor to
ensure budget neutrality for LUPA per-
visit payments and 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 2016 wage index and
comparing it to simulated total
payments for LUPA episodes using the
2015 wage index. By dividing the total
payments for LUPA episodes using the
2016 wage index by the total payments
for LUPA episodes using the 2015 wage
index, we obtain a wage index budget
neutrality factor of 1.0006. We would
apply the wage index budget neutrality
factor of 1.0006 to the CY 2016 national
per-visit rates.
CY 2016
Rebasing
adjustment
CY 2016
HH Payment
update
percentage
minus 2
percentage
points
CY 2016
National,
standardized
60-day
episode
payment
¥$80.95
× 1.003
$2,880.92
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 CY
2016 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 CY 2016 national
per-visit rates are shown in Tables 12
and 13.
TABLE 12—CY 2016 NATIONAL PER-VISIT PAYMENT AMOUNTS FOR HHAS THAT DO SUBMIT THE REQUIRED QUALITY
DATA
CY 2015 Per-visit
payment
HH Discipline type
Home Health Aide ..................................
Medical Social Services .........................
Occupational Therapy ............................
Physical Therapy ...................................
Skilled Nursing .......................................
Speech-Language Pathology ................
Wage index
budget neutrality
factor
×
×
×
×
×
×
$57.89
204.91
140.70
139.75
127.83
151.88
The CY 2016 per-visit payment rates
for an HHA that does not submit the
CY 2016
Rebasing
adjustment
1.0006
1.0006
1.0006
1.0006
1.0006
1.0006
CY 2016 HH
Payment update
percentage
×
×
×
×
×
×
+ $1.79
+ 6.34
+ 4.35
+ 4.32
+ 3.96
+ 4.70
required quality data are updated by the
CY 2016 HH payment update (2.3
1.023
1.023
1.023
1.023
1.023
1.023
CY 2016 Per-visit
payment
$61.09
216.23
148.47
147.47
134.90
160.27
percent) minus 2 percentage points and
is shown in Table 13.
TABLE 13—CY 2016 NATIONAL PER-VISIT PAYMENT AMOUNTS FOR HHAS THAT DO NOT SUBMIT THE REQUIRED
QUALITY DATA
CY 2015
Per-visit rates
asabaliauskas on DSK5VPTVN1PROD with PROPOSALS
HH Discipline type
Home Health Aide ..................................
Medical Social Services .........................
Occupational Therapy ............................
Physical Therapy ...................................
Skilled Nursing .......................................
Speech-Language Pathology ................
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Wage index
budget neutrality
factor
×
×
×
×
×
×
$57.89
204.91
140.70
139.75
127.83
151.88
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CY 2016
Rebasing
adjustment
1.0006
1.0006
1.0006
1.0006
1.0006
1.0006
E:\FR\FM\10JYP2.SGM
×
×
×
×
×
×
+ $1.79
+ 6.34
+ 4.35
+ 4.32
+ 3.96
+ 4.70
Sfmt 4702
CY 2016
HH Payment
update
percentage
minus 2
percentage points
10JYP2
1.003
1.003
1.003
1.003
1.003
1.003
CY 2016
Per-visit
rates
$59.89
212.01
145.57
144.59
132.26
157.14
Federal Register / Vol. 80, No. 132 / Friday, July 10, 2015 / Proposed Rules
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 $248.90 (1.8451
multiplied by $134.90), subject to area
wage adjustment.
e. CY 2016 Non-Routine Medical
Supply (NRS) Payment Rates
Payments for NRS are computed by
multiplying the relative weight for a
39861
particular severity level by the NRS
conversion factor. To determine the CY
2016 NRS conversion factor, we start
with the 2015 NRS conversion factor
($53.23) 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 CY 2016 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 NRS
conversion factor for CY 2016 is shown
in Table 14.
TABLE 14—CY 2016 NRS CONVERSION FACTOR FOR HHAS THAT DO SUBMIT THE REQUIRED QUALITY DATA
CY 2015
NRS conversion factor
CY 2016
Rebasing adjustment
CY 2016
HH Payment
update
percentage
CY 2016
NRS conversion
factor
$53.23 ........................................................................................................................
× 0.9718
× 1.023
$52.92
Using the CY 2015 NRS conversion
factor, the payment amounts for the six
severity levels are shown in Table 15.
TABLE 15—CY 2016 NRS PAYMENT AMOUNTS FOR HHAS THAT DO SUBMIT THE REQUIRED QUALITY DATA
Severity level
1
2
3
4
5
6
Points (scoring)
..............................................................................
..............................................................................
..............................................................................
..............................................................................
..............................................................................
..............................................................................
For HHAs that do not submit the
required quality data, we again begin
with the CY 2015 NRS conversion factor
($53.23) and apply the ¥2.82 percent
rebasing adjustment discussed in
Relative weight
0 .............................................................................
1 to 14 ....................................................................
15 to 27 ..................................................................
28 to 48 ..................................................................
49 to 98 ..................................................................
99+ .........................................................................
section II.C of this proposed rule
(1¥0.0282= 0.9718). We then update
the NRS conversion factor by the CY
2016 HH payment update percentage
(2.3 percent) minus 2 percentage points.
0.2698
0.9742
2.6712
3.9686
6.1198
10.5254
CY 2016 NRS
Payment amounts
$14.28
51.55
141.36
210.02
323.86
557.00
The CY 2016 NRS conversion factor for
HHAs that do not submit quality data is
shown in Table 16.
TABLE 16—CY 2016 NRS CONVERSION FACTOR FOR HHAS THAT DO NOT SUBMIT THE REQUIRED QUALITY DATA
CY 2016
HH Payment
update
percentage
minus 2
percentage points
CY 2016
NRS Conversion
factor
$53.23 ........................................................................................................................
asabaliauskas on DSK5VPTVN1PROD with PROPOSALS
CY 2015 NRS Conversion factor
CY 2016
Rebasing
adjustment
× 0.9718
× 1.003
$51.88
The payment amounts for the various
severity levels based on the updated
conversion factor for HHAs that do not
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submit quality data are calculated in
Table 17.
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TABLE 17—CY 2016 NRS PAYMENT AMOUNTS FOR HHAS THAT DO NOT SUBMIT THE REQUIRED QUALITY DATA
Severity level
1
2
3
4
5
6
Points (scoring)
..............................................................................
..............................................................................
..............................................................................
..............................................................................
..............................................................................
..............................................................................
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.
Relative weight
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) (Pub. L. 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
CY 2016 NRS
Payment amounts
0.2698
0.9742
2.6712
3.9686
6.1198
10.5254
$14.00
50.54
138.58
205.89
317.50
546.06
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 2016, 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—CY 2016 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
CY 2016 National, standardized
60-day episode payment rate
Multiply by the 3
percent rural
add-on
CY 2016 Rural
national, standardized 60-day
episode payment
rate
CY 2016 National, standardized
60-day episode payment rate
Multiply by the 3
percent rural
add-on
CY 2016 Rural
national, standardized 60-day
episode payment
rate
$2,938.37 ................................
× 1.03
$3,026.52
$2,880.92 ...................................
× 1.03
$2,967.35
TABLE 19—CY 2016 PER-VISIT AMOUNTS FOR SERVICES PROVIDED IN A RURAL AREA
For HHAs that DO submit quality data
asabaliauskas on DSK5VPTVN1PROD with PROPOSALS
HH Discipline type
HH Aide ...........................
MSS .................................
OT ....................................
PT ....................................
SN ....................................
SLP ..................................
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CY 2016
Per-visit rate
Multiply by the 3
percent rural
add-on
$61.09
216.23
148.47
147.47
134.90
160.27
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×
×
×
×
×
CY 2016 Rural
per-visit rates
1.03
1.03
1.03
1.03
1.03
1.03
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$62.92
222.72
152.92
151.89
138.95
165.08
Sfmt 4702
Multiply by the 3
percent rural
add-on
CY 2016
Per-visit rate
$59.89
212.01
145.57
144.59
132.26
157.14
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×
×
×
×
×
×
1.03
1.03
1.03
1.03
1.03
1.03
CY 2016 Rural
per-visit rates
$61.69
218.37
149.94
148.93
136.23
161.85
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TABLE 20—CY 2016 NRS CONVERSION FACTOR FOR SERVICES PROVIDED IN RURAL AREAS
For HHAs that DO submit quality data
For HHAs that DO NOT submit quality data
CY 2016 Conversion factor
Multiply by the 3
percent rural
add-on
CY 2016 Rural
NRS conversion
factor
CY 2016 Conversion factor
Multiply by the 3
percent rural
add-on
CY 2016 Rural
NRS conversion
factor
$52.92 .......................................
× 1.03
$54.51
$51.88 ......................................
× 1.03
$53.44
TABLE 21—CY 2016 NRS PAYMENT AMOUNTS FOR SERVICES PROVIDED IN RURAL AREAS
For HHAs that DO submit quality
data (CY 2016 NRS conversion factor = $54.51
Severity level
Points (scoring)
Relative weight
1
2
3
4
5
6
................................................
................................................
................................................
................................................
................................................
................................................
0 ...............................................
1 to 14 ......................................
15 to 27 ....................................
28 to 48 ....................................
49 to 98 ....................................
99+ ...........................................
asabaliauskas on DSK5VPTVN1PROD with PROPOSALS
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 HH Resource
Group (HHRG). The episode’s estimated
cost is the sum of the national wageadjusted 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 wageadjusted threshold. The threshold
amount is the sum of the wage and casemix adjusted PPS episode amount and
wage-adjusted FDL amount. The
proportion of additional costs over the
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CY 2016 NRS
Payment
amounts for rural
areas
0.2698
0.9742
2.6712
3.9686
6.1198
10.5254
outlier threshold amount paid as outlier
payments is referred to as the losssharing ratio.
In the CY 2010 HH PPS final rule (74
FR 58080 through 58087), we discussed
excessive growth in outlier payments,
primarily the result of unusually high
outlier payments in a few areas of the
country. 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 and, in the absence of
corrective measures, would continue do
to so. Consequently, we assessed the
appropriateness of taking action to curb
outlier abuse. To mitigate possible
billing vulnerabilities associated with
excessive outlier payments and adhere
to our statutory limit on outlier
payments, we adopted 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 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 HH expenditure). 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),
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For HHAs that DO NOT submit
quality data (CY 2016 NRS Conversion Factor = $53.44)
Relative weight
$14.71
53.10
145.61
216.33
333.59
573.74
0.2698
0.9742
2.6712
3.9686
6.1198
10.5254
CY 2016 NRS
Payment
amounts for rural
areas
$14.42
52.06
142.75
212.08
327.04
562.48
section 3131(b)(1) of the Affordable Care
Act amended section 1895(b)(3)(C) of
the Act, and requires the Secretary to
reduce the HH PPS payment rates such
that aggregate HH PPS payments are
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 it to state that the
Secretary may provide for an addition or
adjustment to the payment amount for
outlier episodes because of their
unusual variation in the type or amount
of medically necessary care. 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 and outlier payments as a
percent of total payments are capped 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
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be paid as outlier payments, and apply
a 10 percent agency-level outlier cap.
2. Fixed Dollar Loss (FDL) Ratio and
Loss-Sharing 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.
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.
For this proposed rule, simulating
payments using preliminary CY 2014
claims data (as of December 31, 2014)
and the CY 2015 payment rates (79 FR
66088 through 66092), we estimate that
outlier payments in CY 2015 would
comprise 2.02 percent of total payments.
Based on simulations using CY 2014
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claims data and the CY 2016 payments
rates in section III.C.3 of this proposed
rule, we estimate that outlier payments
would comprise approximately 2.34
percent of total HH PPS payments in CY
2016, a percent change of almost 16
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
similar rebasing adjustments and casemix growth reduction would also occur
for 2017, and hence a similar
anticipated increase in the outlier
payments, we estimate that for CY 2017
outlier payments as a percent of total
HH PPS payments would exceed 2.5
percent.
At this time, we are not proposing a
change to the FDL ratio or loss-sharing
ratio for CY 2016 as we believe that
maintaining an FDL of 0.45 and a losssharing ratio of 0.80 are appropriate
given the percentage of outlier payments
is estimated to increase as a result of 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 nominal casemix growth reduction. 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 2014
claims data as of June 30, 2015). We
would continue to monitor the percent
of total HH PPS payments paid as
outlier payments to determine if future
adjustments to either the FDL ratio or
loss-sharing ratio are warranted.
E. Report to Congress on the Home
Health Study Required by Section
3131(d) of the Affordable Care Act and
an Update on Subsequent Research and
Analysis
The current home health prospective
payment system (HH PPS) pays a
determined amount for a 60-day episode
of care adjusted for case mix using 153
home health resource groups (HHRGs).
The 153 HHRGs are determined based
on the amount of therapy provided, the
episode’s timing in a sequence of
episodes, and the patient’s clinical and
functional status determined from data
reported on the Outcome and
Assessment Information Set (OASIS).
There has been criticism that home
health providers have responded to
Medicare’s payment policy by altering
the level of service provided to
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patients.5 A review of the literature
increasingly indicates that the current
HH PPS payment model drives HHA
resource allocation and practice
decisions.6 Specifically, research has
highlighted the need to examine
whether there are vulnerabilities present
within the current HH PPS model that
provide disincentives for serving the
most clinically complex and vulnerable
beneficiaries who receive home health
care while incentivizing providers to
provide more therapy service than
needed to increase their
reimbursement.7 There is increasing
concern that the current home health
payment system encourages home
health providers to deliver the
maximum volume of therapy services
while restricting the number of skilled
nursing and home health aide services
because of the therapy payment
thresholds.8
This raises the question whether there
is a disparity in payment for those
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.9
Section 3131(d) of the Affordable Care
Act directed the Secretary to conduct a
study on HHA costs involved with
providing ongoing access to care to lowincome Medicare beneficiaries or
beneficiaries in medically underserved
areas, and in treating beneficiaries with
high levels of severity of illness.10 To
examine access to Medicare home
health services and payment, relative to
cost, for the vulnerable patient
populations, we awarded a contract to
L&M Policy Research to perform
extensive analysis of both survey and
administrative data. Specifically, the
L&M collected survey data from
physicians and HHAs to examine factors
associated with potential access to care
issues. The surveys provided
information on whether, and the reasons
5 Rosati, R., Russell, D., Peng, T., Brickner, C.,
Kurowski, D., Christopher, M.A., Sheehan, K.
(2014). Medicare Home Health Payment Reform
May Jeopardize Access for Clinically Complex and
Socially Vulnerable Patients. Health Affairs. 33(6),
946–956. Doi: 10.1377/hlthaff.2013.1159
6 Cabin, W. (2009). Evidence-based Research
Challenges Home Care PPS Patient Benefits, Costs,
and Payment Structure. Home Health Care
Management and Practice. 21(4), 240–245. Doi:
10.1177/10848223088328325
7 Ibid.
8 Rosati, R., Russell, D., Peng, T., Brickner, C.,
Kurowski, D., Christopher, M.A., Sheehan, K.
(2014). Medicare Home Health Payment Reform
May Jeopardize Access for Clinically Complex and
Socially Vulnerable Patients. Health Affairs. 33(6),
946–956. Doi: 10.1377/hlthaff.2013.1159
9 Ibid.
10 https://www.cms.gov/Center/Provider-Type/
Home-Health-Agency-HHA-Center.html
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as to why, patients were not placed or
admitted for home health services or
experienced delays in receiving home
health services, and information on the
characteristics of patients who may have
experienced access issues. L&M also
analyzed administrative data through
descriptive and regression analyses to
examine the relationship between
patient characteristics and estimated
financial margin (difference between
payment and estimated cost). The study
focused on margins because margin
differences, particularly those
associated with patient characteristics,
indicate that financial incentives may
exist in the HH PPS to provide home
health care for certain types of patients
over others. Lower margins, if
systematically associated with care for
vulnerable patient populations, may
indicate financial disincentives for
HHAs to admit these patients and may
create access to care issues for them.
The results of the survey revealed that
over 80 percent of HHAs and over 90
percent of physicians reported that
access to home health care for Medicare
fee-for-service beneficiaries in their
local area was excellent or good. When
survey respondents reported access
issues, specifically their inability to
place or admit Medicare fee-for-service
patients into home health, the most
common reason reported was that the
patients did not qualify for the Medicare
home health benefit. HHAs and
physicians also cited family or caregiver
issues as an important contributing
factor in the inability to admit or place
patients. About 17.2 percent of HHAs
and 16.7 percent of physicians reported
insufficient payment as an important
contributing factor in the inability to
admit or place patients. The survey
results suggest that much of the
variation in access to Medicare home
health services is associated with social
and personal conditions and therefore
CMS’ ability to improve access for
certain vulnerable patient populations
through payment policy may be limited.
Analysis of CY 2010 HHA payment
and cost data suggests that margins may
differ substantially across the HH PPS
case-mix groups. In addition, particular
beneficiary characteristics appear to be
strongly associated with margin, and
thus may create financial incentives to
select certain patients over others.
Margins were estimated to be lower in
CY 2010 for patients who required
parenteral nutrition, who had traumatic
wounds or ulcers, or required
substantial assistance in bathing. Given
that these variables are already included
in the HH PPS case-mix system, the
results indicate that modifications to the
case-mix system may be needed.
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Furthermore, in CY 2010, beneficiaries
admitted after acute or post-acute stays
or who had high Hierarchical Condition
Category scores or certain poorlycontrolled clinical conditions, such as
poorly-controlled pulmonary disorders,
were also associated with substantially
lower home health margins. In addition,
other characteristics, such as those
describing assistance by informal
caregivers for ADL needs and those
describing socio- economic status, such
as dual eligibility for Medicare and
Medicaid, were strongly associated with
lower margins. Exploration of potential
payment methodology changes
indicated that accounting for additional
variables in HH PPS payment may
decrease the difference in estimated
margin between individuals in specific
vulnerable subgroups and those not in
the subgroups, thereby potentially
decreasing financial incentives to select
certain types of patients over others.
CMS awarded a follow-on contract to
Abt Associates to further explore margin
differences across patient characteristics
and possible payment methodology
changes suggested by the results of the
home health study. Additionally, we
have heard from various stakeholders
that the current payment system
methodology is overly complex and
does not fully reflect the range of
services provided under the home
health benefit, and thus this follow-on
study would look at these aspects of the
current payment system as well.
Under the follow-on contract, Abt
Associates convened a Clinical
Workgroup meeting on June 25, 2014 to
gain clinical insight from industry
regarding the current HH PPS. Based
upon the feedback provided during the
Clinical Workgroup meeting, as well as
CMS concerns about the current model
given the findings from the Home
Health Study, Abt Associates was tasked
with developing model options for
consideration and discussion. In
September 2014, Abt Associates
presented several payment model
options for CMS consideration, which
were also presented to a Technical
Expert Panel meeting held on January 8,
2015.
• Diagnosis on Top Model:
The first model option, referred to as
the ‘‘Diagnosis on Top’’ (DOT) model,
combines diagnosis groups with a
regression model to create separate
weights for patients with different
diagnoses. For its ‘‘Studies in Home
Health Case Mix’’ project design report
(January 7, 2002), Abt had explored the
possibility of a DOT model for the home
health payment system. At that time,
there was a decision that the potential
gains in payment accuracy which would
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39865
result from implementing a DOT model
were offset by the added complexity and
burden to providers that a DOT model
could introduce by requiring providers
to classify their patients with a single
diagnosis that would be used to
determine payment. For present reform
efforts, Abt revisited the DOT model
with more current data and in the
context of other potential changes to the
payment system which a DOT model
might be able to complement. In this
analysis, we are removing the therapy
variable, allowing us to explore new
ideas and re-explore previously rejected
ideas to see how we can increase the
statistical power of the model without
the therapy variable. In this most recent
analysis, each episode is grouped into
the following diagnosis groups based on
the primary ICD–9–CM diagnosis code
reported on the OASIS: (1) Orthopedic;
(2) neurological; (3) diabetes; (4) cancer;
(5) skin wounds & lesions; (6)
cardiovascular; (7) pulmonary; (8)
gastrointestinal; (9) genito-urinary; (10)
mental/emotional disorders; (11) other
diagnoses; (12) case-mix V-codes; and
(13) non-case-mix V-codes. Unlike the
current HH PPS case-mix system, the
diagnosis on top model does not include
any therapy thresholds. Under the
diagnosis on top model, episodes are
first divided into different diagnosis
groups, prior to the determination of the
clinical and functional levels, and
payment model regressions would be
run separately for each diagnosis group.
This is intended to maximize the
statistical performance of the payment
system. The work conducted by Abt
Associates also included OASIS and
non-OASIS items (such as whether the
patient was admitted from an acute or
post-acute care setting and hierarchical
condition categories) not used in the
current payment system, but shown to
correlate with resource use. In many
ways, the regression component of the
diagnosis on top model is very similar
to the current 4-equation model except
that, in later versions of Abt’s work on
the diagnosis on top model, the clinical
and functional levels are replaced with
an overall severity level. This change
allows the diagnosis on top model to
account for a richer set of variables than
the clinical and functional levels in the
current payment system.
• Predicted Therapy Model:
The second model option is referred
to as the ‘‘Predicted Therapy Model.’’
The basic structure of this model is
similar to that of the current payment
model. In this model option, actual
therapy visits used in the current HH
PPS model are replaced with predicted
therapy visits to develop case mix
weights and payment amounts based on
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the predicted number of visits. The
weights are constructed via a two-part
model. The first part of the model uses
a logistic regression to estimate whether
or not the episode had any therapy
visits. The second part of this predicted
therapy model uses a truncated
binomial regression (truncated at zero)
to estimate the amount of therapy visits
conditional on having any therapy
visits. This ‘‘hurdle’’ model is
commonly used in health economics to
describe medical utilization or
expenditures where observing zero
health care use during the sample
period is common.11 We also looked at
estimating the two part model for each
of the diagnosis groups in the diagnosis
on top model referenced above. The
predicted therapy model still includes
the four-equation model, the payment
regression, and the 153 HHRGs as in the
current payment model.
• Home Health Groupings Model:
The third model is referred to as the
‘‘Home Health Groupings ’’ (HHG)
model. The premise of this type of
model is that it starts with a clinical
foundation. This groupings model
groups home health episodes by
diagnoses and the expected types of
home health interventions required.
Using expert clinical judgment, each
ICD–9 code is assigned to one of seven
groups based on the intervention
expected to be required. Those seven
groups include: (1) Musculoskeletal
Rehabilitation; (2) Neuro/Stroke
Rehabilitation; (3) Skin/Non-Surgical
Wound Care; (4) Post-Op Wound
Aftercare; (5) Behavioral Health Care; (6)
Complex Medical Care; and (7)
Medication Management, Teaching, and
Assessment. Unlike the current HH PPS
case-mix system, the home health
groupings model does not include any
therapy thresholds. Abt Associates is
currently in the process of further
delineating the seven groups listed
above using OASIS and non-OASIS
items (such as whether the patient was
admitted from an acute or post-acute
care setting and hierarchical condition
categories) not used in the current
payment system, but shown to correlate
with resource use. The HHG model
groups home health episodes in a way
that mirrors how clinicians would
differentiate between different types of
beneficiaries and would help explain
why the beneficiary is receiving home
health, something that the current HH
PPS case-mix may be lacking. MedPAC
noted that policy makers have faced
challenges in defining the role of home
health.12 We believe that the HHG
model may be one way to better define
the types of care that patients receive
under the home health benefit and thus
the role of home care.
To inform the model options
discussed above, Abt Associates also
reviewed other Medicare prospective
payment systems to identify alternative
methods used in classifying patients
and to better understand components of
each system. In the future, we plan to
issue a technical report under our
contract with Abt Associates that would
further describe and analyze the three
model options. We also plan to
reconvene the Clinical Workgroup and
the Technical Experts Panel in the near
future to help further inform CMS on
the various model options developed
and next steps.
11 ‘‘Modeling Health Care Costs and Counts,’’
ASHE conference course by Partha Deb, Willard
Manning and Edward Norton, https://
web.harrisschool.uchicago.edu/sites/default/files/
ASHE2012_Minicourse_Cost_Use_slides_
corrected.pdf
12 Medicare Payment Advisory Commission
(MedPAC), ‘‘Report to the Congress: Medicare
Payment Policy’’. March 2015. P. 219. Washington,
DC. Accessed on 5/5/2015 at: https://medpac.gov/
documents/reports/march-2015-report-to-thecongress-medicare-payment-policy.pdf?sfvrsn=0.
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F. Technical Regulations Text Changes
First, we propose to make several
technical corrections in part 484 to
better align the payment requirements
with recent statutory and regulatory
changes for home health services. We
propose to make changes to § 484.
205(e) to state that estimated total
outlier payments for a given calendar
year are limited to no more than 2.5
percent of total outlays under the HHA
PPS, rather than 5 percent of total
outlays, as required by section
1895(b)(5)(A) of the Act as amended by
section 3131(b)(2)(B) of the Affordable
Care Act. Similarly, we also propose to
specify in § 484.240(e) that the fixed
dollar loss and the loss sharing amounts
are chosen so that the estimated total
outlier payment is no more than 2.5
percent of total payments under the HH
PPS, rather than 5 percent of total
payments under the HH PPS as required
by section 1895(b)(5)(A) of the Act as
amended by section 3131(b)(2)(B) of the
Affordable Care Act. We also propose to
describe in § 484.240(f) that the
estimated total amount of outlier
payments to an HHA in a given year
may not exceed 10 percent of the
estimated total payments to the specific
agency under the HH PPS in a given
year. This update aligns the regulations
text at § 484.240(f) with the statutory
requirement in 1895(b)(5)(A) of the Act
as amended by section 3131(b)(2)(B) of
the Affordable Care Act. Finally, we
propose a minor editorial change in
§ 484.240(b) to specify that the outlier
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threshold for each case-mix group is the
episode payment amount for that group,
or the PEP adjustment amount for the
episode, plus a fixed dollar loss amount
that is the same for all case-mix groups.
Second, in addition to the proposed
changes to the regulations text
pertaining to outlier payments under the
HH PPS, we also propose to amend
§ 409.43(e)(iii) and to add language to
§ 484.205(d) to clarify the frequency of
review of the plan of care and the
provision of Partial Episode Payments
(PEP) under the HH PPS as a result of
a regulations text change in § 424.22(b)
that was finalized in the CY 2015 HH
PPS final rule (79 FR 66032).
Specifically, we propose to change the
definition of an intervening event to
include transfers and instances where a
patient is discharged and return to home
health during a 60-day episode, rather
than a discharge and return to the same
HHA during a 60-day episode. In
§ 484.220, we propose to update the
regulations text to reflect the downward
adjustments to the 60-day episode
payment rate due to changes in the
coding or classification of different units
of service that do not reflect real
changes in case-mix (nominal case-mix
growth) applied to calendar years 2012
and 2013, which were finalized in the
CY 2012 HH PPS final rule (76 FR
68532). This also includes updating the
CY 2011 adjustment to 3.79 percent as
finalized in the CY 2011 HH PPS final
rule (75 FR 70461). In § 484.225 we are
proposing to eliminate references to
outdated market basket index factors by
removing paragraphs (b), (c), (d), (e), (f)
and (g). In § 484.230 we propose to
delete the last sentence as a result of a
change from a separate LUPA add-on
amount to a LUPA add-on factor
finalized in the CY 2014 HH PPS final
rule (78 FR 72256). Finally, we are
deleting and reserving § 484.245 as we
believe that this language is no longer
applicable under the HH PPS, as it was
meant to facilitate the transition to the
original PPS established in CY 2000.
Lastly, we propose to make one
technical correction in § 424.22 to redesignate paragraph (a)(1)(v)(B)(1) as
(a)(2).
We invite comments on these
technical corrections and associated
changes in the regulations at § 409,
§ 424, and § 484.
IV. Proposed Home Health Value-Based
Purchasing (HHVBP) Model
A. Background
In the CY 2015 Home Health
Prospective Payment System (HH PPS)
final rule titled ‘‘Medicare and Medicaid
Programs; CY 2015 Home Health
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Prospective Payment System Rate
Update; Home Health Quality Reporting
Requirements; and Survey and
Enforcement Requirements for Home
Health Agencies (79 FR 66032–66118),
we indicated that we were considering
the development of a home health
value-based purchasing (HHVBP)
model. We sought comments on a future
HHVBP model, including elements of
the model; size of the payment
incentives and percentage of payments
that would need to be placed at risk in
order to spur home health agencies
(HHAs) to make the necessary
investments to improve the quality of
care for Medicare beneficiaries; the
timing of the payment adjustments; and,
how performance payments should be
distributed. We also sought comments
on the best approach for selecting states
for participation in this model. We
noted that if the decision was made to
move forward with the implementation
of a HHVBP model in CY 2016, we
would solicit additional comments on a
more detailed model proposal to be
included in future rulemaking.
In the CY 2015 HH PPS final rule,13
we indicated that we received a number
of comments related to the magnitude of
the percentage payment adjustments;
evaluation criteria; payment features; a
beneficiary risk adjustment strategy;
state selection methodology; and the
approach to selecting Medicare-certified
HHAs. A number of commenters
supported the development of a valuebased purchasing model in the home
health industry in whole or in part with
consideration of the design parameters
provided. No commenters provided
strong counterpoints or alternative
design options which dissuaded CMS
from moving forward with general
design and framework of the HHVBP
model as discussed in the CY 2015 HH
PPS proposed rule. All comments were
considered in our decision to develop
an HHVBP model for implementation
beginning January 1, 2016. Therefore, in
this proposed rule, we are proposing to
implement a HHVBP model, which
includes a randomized state selection
methodology; the reporting framework;
the payment adjustment methodology;
payment adjustment schedule by
performance year and payment
adjustment percentage; the quality
measures selection methodology,
classifications and weighting, measures
for performance year one, including the
reporting of New Measures, and the
framework for proposing to adopt
measures for subsequent performance
years; the performance scoring
methodology, which includes
performance based on achievement and
improvement; the review and
recalculation period; and the evaluation
framework.
The basis for developing this
proposed value-based purchasing (VBP)
model, as described in the proposed
regulations at § 484.300 et seq., stems
from several important areas of
consideration. First, we expect that
tying quality to payment through a
system of value-based purchasing will
improve the beneficiaries’ experience
and outcomes. In turn, we expect
payment adjustments that both reward
improved quality and penalize poor
performance will incentivize quality
improvement and encourage efficiency,
leading to a more sustainable payment
system.
Second, section 3006(b) of the
Affordable Care Act directed the
Secretary of the Department of Health
and Human Services (the Secretary) to
develop a plan to implement a VBP
program for payments under the
Medicare Program for HHAs and the
Secretary issued an associated Report to
Congress in March of 2012 (2012
Report).14 The 2012 Report included a
roadmap for implementation of an
HHVBP model and outlined the need to
develop an HHVBP program that aligns
with other Medicare programs and
coordinates incentives to improve
quality. The 2012 Report also indicated
that a HHVBP program should build on
and refine existing quality measurement
tools and processes. In addition, the
2012 Report indicated that one of the
ways that such a program could link
payment to quality would be to tie
payments to overall quality
performance.
Third, section 402(a)(1)(A) of the
Social Security Amendments of 1967 (as
amended) (42 U.S.C. 1395b–1(a)(1)(A)),
provided authority for us to conduct the
Home Health Pay-for-Performance
(HHPFP) Demonstration that ran from
2008 to 2010. The results of that
Demonstration found modest quality
improvement in certain measures after
comparing the quality of care furnished
by Demonstration participants to the
quality of care furnished by the control
group. One important lesson learned
from the HHPFP Demonstration was the
need to link the HHA’s quality
13 Medicare and Medicaid Programs; CY 2015
Home Health Prospective Payment System Rate
Update; Home Health Quality Reporting
Requirements; and Survey and Enforcement
Requirements for Home Health Agencies, 79 FR
66105–66106 (November 6, 2014).
14 CMS, ‘‘Report to Congress: Plan to Implement
a Medicare Home Health Agency Value-Based
Purchasing Program’’ (March 15, 2012) available at
https://www.cms.gov/Medicare/Medicare-Fee-forService-Payment/HomeHealthPPS/downloads/
stage-2-NPRM.PDF.
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improvement efforts and the incentives.
HHAs in three of the four regions
generated enough savings to have
incentive payments in the first year of
the Demonstration, but the size of
payments were unknown until after the
conclusion of the Demonstration. Also,
the time lag between quality
performance and payment incentives
was too long to provide a sufficient
motivation for HHAs to take necessary
steps to improve quality. The results of
the Demonstration published in a
comprehensive evaluation report 15
suggest that future models could benefit
from ensuring that incentives are
reliable enough, of sufficient magnitude,
and paid in a timely fashion to
encourage HHAs to be fully engaged in
the quality of care initiative.
Furthermore, the President’s FY 2015
and 2016 Budgets proposed that VBP
should be extended to additional
providers including skilled nursing
facilities, home health agencies,
ambulatory surgical centers, and
hospital outpatient departments. The FY
2015 Budget called for at least 2 percent
of payments to be tied to quality and
efficiency of care on a budget neutral
basis. The FY 2016 Budget outlines a
program which would tie at least 2
percent of Medicare payments to the
quality and efficiency of care in the first
2 years of implementation beginning in
2017, and at least 5 percent beginning
in 2019 without any impact to the
budget. We propose in this HHVBP
model to also follow a graduated
payment adjustment strategy within
certain selected states beginning January
1, 2016.
The Secretary has also set two overall
delivery system reform goals for CMS.
First, we seek to tie 30 percent of
traditional, or fee-for-service, Medicare
payments to quality or value-based
payments through alternative payment
models by the end of 2016, and to tie
50 percent of payments to these models
by the end of 2018. Second, we seek to
tie 85 percent of all traditional Medicare
payments to quality or value by 2016
and 90 percent by 2018.16 To support
these efforts the Health Care Payment
Learning and Action Network was
recently launched to help advance the
work being done across sectors to
increase the adoption of value-based
payments and alternative payment
15 ‘‘CMS Report on Home Health Agency ValueBased Purchasing Program’’ (February of 2012)
available at https://www.cms.gov/ResearchStatistics-Data-and-Systems/Statistics-Trends-andReports/Reports/Downloads/HHP4P_Demo_Eval_
Final_Vol1.pdf.
16 Content of this announcement can be found at
https://www.hhs.gov/news/press/2015pres/01/
20150126a.html.
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models. We believe that testing the
HHVBP model would support these
goals.
Finally, we have already successfully
implemented the Hospital Value-Based
Purchasing (HVBP) program, under
which value-based incentive payments
are made in a fiscal year to hospitals
that meet performance standards
established for a performance period
with respect to measures for that fiscal
year. The percentage of a participating
hospital’s base-operating DRG payment
amount for FY 2015 discharges that is
at risk, based on the hospital’s
performance under the program for that
fiscal year, is 1.5 percent. That
percentage will increase to 2.0 by FY
2017. We are proposing an HHVBP
model that builds on the lessons learned
and guidance from the HVBP program
and other applicable demonstrations as
discussed above, as well as from the
evaluation report discussed earlier.
The proposed HHVBP model presents
an opportunity to improve the quality of
care furnished to Medicare beneficiaries
and study what incentives are
sufficiently significant to encourage
HHAs to provide high quality care. The
HHVBP model being proposed would
offer both a greater potential reward for
high performing HHAs as well as a
greater potential downside risk for low
performing HHAs. If implemented, the
model would begin on January 1, 2016,
and include an array of measures that
would capture the multiple dimensions
of care that HHAs furnish.
The proposed model would be tested
by CMS’s Center for Medicare and
Medicaid Innovation (CMMI) under
section 1115A of the Act. Under section
1115A(d)(1) of the Act, the Secretary
may waive such requirements of Titles
XI and XVIII and of sections 1902(a)(1),
1902(a)(13), and 1903(m)(2)(A)(iii) as
may be necessary solely for purposes of
carrying out section 1115A with respect
to testing models described in section
1115A(b). The Secretary is not issuing
any waivers of the fraud and abuse
provisions in sections 1128A, 1128B,
and 1877 of the SSA or any other
Medicare or Medicaid fraud and abuse
laws for this model. Thus,
notwithstanding any other provisions of
this proposed rule, all providers and
suppliers participating in the HHVBP
model must comply with all applicable
fraud and abuse laws and regulations.
We are proposing to use the section
1115A(d)(1) waiver authority to apply a
reduction or increase of up to 8 percent
to current Medicare payments to
Medicare-certified HHAs delivering care
to beneficiaries within the boundaries of
certain states, depending on the HHA’s
performance on specified quality
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measures relative to its peers.
Specifically, the HHVBP model
proposes to utilize the waiver authority
to adjust Medicare payment rates under
section 1895(b) of the Act.17 In
accordance with the authority granted to
the Secretary in section 1115A(d)(1) of
the Act, we would waive section
1895(b)(4) of the Act only to the extent
necessary to adjust payment amounts to
reflect the value-based payment
adjustments under this proposed model
for Medicare-certified HHAs in
specified states selected in accordance
with CMS’s proposed selection
methodology. We are not proposing to
implement this model under the
authority granted by the Affordable Care
Act under section 3131 (‘‘Payment
Adjustments for Home Health Care’’).
The defined population would
include all Medicare beneficiaries being
provided care by any Medicare-certified
HHA delivering care within the selected
states. Medicare-certified HHAs that are
delivering care within the boundaries of
selected states are considered
‘Competing Medicare-certified Home
Health Agencies’ within the scope of
this HHVBP Model. If care is delivered
outside of boundaries of selected states,
or inside the boundaries of a nonselected state that does not have a
reciprocal agreement with a selected
state, payments for those beneficiaries
would not be considered within the
scope of the model because we are
basing participation in the model on
state specific CMS Certification
Numbers (CCNs). Payment adjustments
for each year of the model would be
calculated based on a comparison of
how well each competing Medicarecertified HHA performed during the
performance period for that year
(proposed below to be one year in
length, starting in CY 2016) with its
performance on the same measures in
2015 (proposed below to be the baseline
data year).
The first performance year would be
CY 2016, the second would be CY 2017,
the third would be CY 2018, the fourth
would be 2019, and the fifth would be
CY 2020. Greater details on performance
periods are outlined in further detail in
section D—Performance Assessment
and Payment Periods. This model
would test whether being subject to
significant payment adjustments to the
Medicare payment amounts that would
otherwise be made to competing
Medicare-certified HHAs would result
in statistically significant improvements
in the quality of care being delivered to
this specific population of Medicare
beneficiaries.
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U.S.C. 1395fff.
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We propose to identify Medicarecertified HHAs for participation in this
model using state borders as boundaries.
We do so under the authority granted in
section 1115A(a)(5) of the Act to elect to
limit testing of a model to certain
geographic areas. This decision is
influenced by the 2012 Report to
Congress mandated under section
3006(b) of the Affordable Care Act. This
Report stated that HHAs which
participated in previous value-based
purchasing demonstrations ‘‘uniformly
believed that all Medicare-certified
HHAs should be required to participate
in future VBP programs so all agencies
experience the potential burdens and
benefits of the program’’ and some
HHAs expressed concern that absent
mandatory participation, ‘‘lowperforming agencies in areas with
limited competition may not choose to
pursue quality improvement.’’ 18
Section 1115A(b)(2)(A) of the Act
requires that the Secretary select models
to be tested where the Secretary
determines that there is evidence that
the model addresses a defined
population for which there are deficits
in care leading to poor clinical
outcomes or potentially avoidable
expenditures. The HHVBP model was
developed to improve care for Medicare
patients receiving care from HHAs
based on evidence in the March 2014
MedPAC Report to Congress citing
quality and cost concerns in the home
health sector. According to MedPAC,
‘‘about 29 percent of post-hospital home
health stays result in readmission, and
there is tremendous variation in
performance among providers within
and across geographic regions.’’ 19 The
same report cited limited improvement
in quality based on existing measures,
and noted that the data on quality ‘‘are
collected only for beneficiaries who do
not have their home health care stays
terminated by a hospitalization,’’
skewing the results in favor of a
healthier segment of the Medicare
population.20 This model would test the
use of adjustments to Medicare HH PPS
rates by tying payment to quality
performance with the goal of achieving
the highest possible quality and
efficiency.
18 See the Recommendations section of the U.S.
Department of Health and Human Services. Report
to Congress: Plan to Implement a Medicare Home
Health Agency Value-Based Purchasing Program.’’
(March 2012) p. 28.
19 See full citation at note 11. MedPAC Report to
Congress (March 2014) p.215.
20 MedPAC Report to Congress (March 2014)
p.226.
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B. Overview
In § 484.305 we propose definitions
for ‘‘applicable percent’’, ‘‘applicable
measure’’, ‘‘benchmark’’, ‘‘home health
prospective payment system’’, ‘‘largervolume cohort’’, ‘‘linear exchange
function’’, ‘‘Medicare-certified home
health agency’’, ‘‘New Measures’’,
‘‘payment adjustment’’, ‘‘performance
period’’, ‘‘smaller-volume cohort’’,
‘‘selected states’’, ‘‘starter set’’, ‘‘Total
Performance Score’’, and ‘‘value-based
purchasing’’ as they pertain to this
subpart. The HHVBP model is being
proposed to encompass five
performance years and be implemented
beginning January 1, 2016 and conclude
on December 31, 2022. Payment and
service delivery models are developed
by CMMI in accordance with the
requirements of section 1115A of the
Act. During the development of new
models, CMMI builds on the ideas
received from internal and external
stakeholders and consults with clinical
and analytical experts.
In this proposed rule, we are outlining
an HHVBP model for public notice and
comment that has an overall purpose of
improving the quality of home health
care and delivering it to the Medicare
population in a more efficient manner.
The specific goals of the proposed
model are to:
1. Incentivize HHAs to provide better
quality care with greater efficiency;
2. Study new potential quality and
efficiency measures for appropriateness
in the home health setting; and,
3. Enhance current public reporting
processes.
We are proposing that the HHVBP
model would adjust Medicare HHA
payments over the course of the model
by up to 8 percent depending on the
applicable performance year and the
degree of quality performance
demonstrated by each competing
Medicare-certified HHA. The proposed
model would reduce the HH PPS final
claim payment amount to an HHA for
each episode in a calendar year by an
amount up to the applicable percentage
defined in proposed § 484.305. The
timeline of payment adjustments as they
apply to each performance year is
described in greater detail in the section
entitled ‘‘Payment Adjustment
Timeline.’’
The model would apply to all
Medicare-certified HHAs in each of the
selected states, which means that all
HHAs in the selected states would be
required to compete. We propose to
codify this policy at 42 CFR 484.310.
Furthermore, a competing Medicarecertified HHA would only be measured
on performance for care delivered to
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Medicare beneficiaries within selected
states (with rare exceptions given for
care delivered when a reciprocal
agreement exists between states). The
distribution of payment adjustments
would be based on quality performance,
as measured by both achievement and
improvement, across a proposed set of
quality measures rigorously constructed
to minimize burden as much as possible
and improve care. Competing Medicarecertified HHAs that demonstrate they
can deliver higher quality of care in
comparison to their peers (as defined by
the volume of services delivered within
the selected state), or their own past
performance, could have their payment
for each episode of care adjusted higher
than the amount that otherwise would
be paid under section 1895 of the Act.
Competing Medicare-certified HHAs
that do not perform as well as other
competing Medicare-certified HHAs of
the same size in the same state might
have their payments reduced and those
competing Medicare-certified HHAs that
perform similarly to others of similar
size in the same state might have no
payment adjustment made. This
operational concept is similar in
practice to what is used in the HVBP
program.
We expect that the risk of having
payments adjusted in this manner
would provide an incentive among all
competing Medicare-certified HHAs
delivering care within the boundaries of
selected states to provide significantly
better quality through improved
planning, coordination, and
management of care. The degree of the
payment adjustment would be
dependent on the level of quality
achieved or improved from the baseline
year, with the highest upward
performance adjustments going to
competing Medicare-certified HHAs
with the highest overall level of
performance based on either
achievement or improvement in quality.
The size of a Medicare-certified HHA’s
payment adjustment for each year under
the model would be dependent upon
that HHA’s performance with respect to
that calendar year relative to other
competing Medicare-certified HHAs of
similar size in the same state and
relative to its own performance during
the baseline year.
We are proposing that states would be
selected randomly from nine regional
groupings for model participation. A
competing Medicare-certified HHA is
only measured on performance for care
delivered to Medicare beneficiaries
within boundaries of selected states and
only payments for HHA services
provided to Medicare beneficiaries
within boundaries of selected states
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would be subject to adjustment under
the proposed model. Requiring all
Medicare-certified HHAs within the
boundaries of selected states to compete
in the model would ensure that: (1)
There is no self-selection bias, (2)
competing HHAs are representative of
HHAs nationally, and (3) there is
sufficient participation to generate
meaningful results. We believe it is
necessary to require all HHAs delivering
care within boundaries of selected states
to be included in the model because, in
our experience, Medicare-providers are
generally reluctant to participate
voluntarily in models in which their
Medicare payments could be subject to
possible reduction. This reluctance to
participate in voluntary models has
been shown to cause self-selection bias
in statistical assessments and thus, may
present challenges to our ability to
evaluate the model. In addition, state
boundaries represent a natural
demarcation in how quality is currently
being assessed through OASIS measures
on Home Health Compare (HHC).
C. Selection Methodology
1. Identifying a Geographic Demarcation
Area
We are proposing to adopt a
methodology that uses state borders as
boundaries for demarcating which
Medicare-certified HHAs will be
required to compete in the model. We
are proposing to select nine states from
nine geographically-defined groupings
of five or six states. Groupings were also
defined in order to ensure that the
successful implementation of the model
would produce robust and generalizable
results, as discussed later in this
section.
We took into account five key factors
when deciding to propose selection at
the state-level for this model. First, if we
required some, but not all, Medicarecertified HHAs that deliver care within
the boundaries of a selected state to
participate in the model, we believe the
HHA market for the state could be
disrupted because HHAs in the model
would be competing against HHAs not
in the model (herein referenced as either
‘non-model HHAs’ or ‘non-competing
HHAs’). Second, we wanted to ensure
that the distribution of payment
adjustments based on performance
under the model could be extrapolated
to the entire country. Statistically, the
larger the sample to which payment
adjustments are applied, the smaller the
variance of the sampling distribution
and the greater the likelihood that the
distribution accurately predicts what
would transpire if the methodology
were applied to the full population of
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HHAs. Third, we considered the need to
align with other HHA quality program
initiatives including HHC. The HHC
Web site presently provides the public
and HHAs a state- and national-level
comparison of quality. We expect that
aligning performance with the HHVBP
benchmark and the achievement score
would support how measures are
currently being reported on HHC.
Fourth, there is a need to align with
CMS regulations which require that
each HHA have a unique CMS
Certification Number (CCN) for each
state in which the HHA provides
service. Fifth, we wanted to ensure
sufficient sample size and the ability to
meet the rigorous evaluation
requirements for CMMI models. These
five factors are important for the
successful implementation and
evaluation of this model.
We expect that when there is a risk for
a downside payment adjustment based
on quality performance measures, the
use of a self-contained, mandatory
cohort of HHA participants will create
a stronger incentive to deliver greater
quality among competing Medicarecertified HHAs. Specifically, it is
possible the market would become
distorted if non-model HHAs are
delivering care within the same market
as competing Medicare-certified HHAs
because competition, on the whole,
becomes unfair when payment is
predicated on quality for one group and
volume for the other group. In addition,
we expect that evaluation efforts might
be negatively impacted because some
HHAs would be competing on quality
and others on volume within the same
market.
We are proposing the use of state
boundaries after careful consideration of
several alternative selection approaches,
including randomly selecting HHAs
from all HHAs across the country, and
requiring participation from smaller
geographic regions including the
county; the Combined Statistical Area
(CSA); the Core-Based Statistical Area
(CBSA); rural provider level; and the
Hospital Referral Region (HRR) level.
A methodology using a national
sample of HHAs that are randomly
selected from all HHAs across the
country could be designed to include
enough HHAs to ensure robust payment
adjustment distribution and a sufficient
sample size for the evaluation; however,
this approach may present significant
limitations when compared with the
state boundaries selection methodology
proposed in this model. Of primary
concern with randomly selecting at the
provider-level across the nation is the
issue with market distortions created by
having competing Medicare-certified
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HHAs operating in the same market as
non-model HHAs.
Using smaller geographic areas than
states, such as counties, CSAs, CBSAs,
rural, and HRRs, could also present
challenges for this model. These smaller
geographic areas were considered as
alternate selection options; however,
their use could result in too small of a
sample size of potential competing
HHAs. As a result, we expect the
distribution of payment adjustments
could become highly divergent among
fewer HHA competitors. In addition, the
ability to evaluate the model could
become more complex and may be less
generalizable to the full population of
Medicare-certified HHAs and the
beneficiaries they serve across the
nation. Further, the use of smaller
geographic areas than states could
increase the proportion of Medicarecertified HHAs that could fall into
groupings with too few agencies to
generate a stable distribution of
payment adjustments. Thus, if we were
to define geographic areas based on
CSAs, CBSAs, counties, or HRRs, we
would need to develop an approach for
consolidating smaller regions into larger
regions.
Home health care is a unique type of
health care service when compared to
other Medicare provider types. In
general, the HHA’s care delivery setting
is in the beneficiaries’ homes as
opposed to other provider types that
traditionally deliver care at a brick and
mortar institution within beneficiaries’
respective communities. As a result, the
HHVBP model needs to be designed to
account for the unique way that HHA
care is provided in order to ensure that
the results are generalizable to the
population. HHAs are limited to
providing care to beneficiaries in the
state that they have a CCN however;
HHAs are not restricted from providing
service in a county, CSA, CBSA or HRR
that they are not located in (as long as
the other county/CBSA/HRR is in the
same state in which the HHA is
certified). As a result, using smaller
geographic areas (than state boundaries)
could result in similar market distortion
and evaluation confounders as selecting
providers from a randomized national
sampling. The reason is that HHAs in
adjacent counties/CSAs/CBSAs/HRRs
may not be in the model but, would be
directly competing for services in the
same markets or geographic regions.
Competing HHAs delivering care in the
same market area as non-competing
HHAs could generate a spillover effect
where non-model HHAs would be vying
for the same beneficiaries as competing
HHAs. This spillover effect presents
several issues for evaluation as the
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dependent variable (quality) becomes
confounded by external influences
created by these non-competing HHAs.
These unintentional external influences
on competing HHAs may be made
apparent if non-competing HHAs
become incentivized to generate greater
volume at the expense of quality
delivered to the beneficiaries they serve
and at the expense of competing HHAs
that are paid on quality instead of
volume. Further, the ability to
extrapolate these results to the full
population of HHAs and the
beneficiaries they serve becomes
confounded by an artifact of the model
and inferences would be limited from
an inability to duplicate these results.
While these concerns would decrease in
some order of magnitude as larger
regions are considered, the only way to
eliminate these concerns entirely is to
define participation among Medicarecertified HHAs at the state level.
In addition, home health quality data
currently displayed on HHC allows
users to compare HHA services
furnished within a single state.
Selecting HHAs using other geographic
regions that are smaller and/or cross
state lines could require the model to
deviate from the established process for
reporting quality. For these reasons, we
believe a selection methodology based
on the use of Medicare-certified HHAs
delivering care within state boundaries
would be the most appropriate for the
successful implementation and
evaluation of this model.
While, for the reasons described
above, we are proposing that the
geographic basis of selection remain at
the state-level, we nevertheless seek
comment on potential alternatives that
might use smaller geographic areas.
With consideration of alternatives, the
public should reference the five
aforementioned key factors used to
consider selection at the state-level for
this model as they relate to the
evaluative framework and operational
feasibility of this model. In particular,
one potential alternative would be to
split states into sub-state regions using
a combination of CSAs and
metropolitan statistical areas (MSA), a
type of CBSA. For example, regions
might be defined using the following
process:
• Step 1: Define one sub-state region
corresponding to each CSA that
contains an MSA (but not for CSAs that
do not include an MSA) and one substate region corresponding to each MSA
that is not part of a CSA. In cases where
a CSA or MSA crossed state boundaries,
only the portion of the CSA or MSA that
falls inside the state boundaries would
be included in the sub-state region.
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• Step 2: Any portions of a state that
were not included in a sub-state region
based on a CSA or an MSA defined in
Step 1 would be consolidated in a single
‘‘remainder of state’’ sub-state region.
• Step 3: To ensure that all sub-state
regions have a sufficient number of
HHAs to permit stable distribution of
payment adjustments, sub-state regions
based on CSAs or MSAs that contained
fewer than 25 HHAs would be
consolidated into the ‘‘remainder of
state’’ sub-state region.
• Step 4: If a ‘‘remainder of state’’
sub-state region had fewer than 25
HHAs, that sub-state region would be
consolidated with the geographically
closest sub-state region based on a CSA
or MSA.
We note that algorithms like this one
may generate more than 100 total substate regions and over 200 unique
competing cohorts of Medicare-certified
HHAs.
We seek comment on advantages and
disadvantages of this approach relative
to defining regions based on state
boundaries. In particular, we note that
because this approach would generate a
larger number of regions, it could
increase the statistical power of the
model evaluation, and might improve
our ability to determine what effects the
model has on the quality of home health
care, as well as other outcomes of
interest. However, we note that because
regions would no longer line up with
full states in most cases, the regions
selected to participate in the model
would no longer align directly with
those displayed on HHC and therefore,
quality data would have to be
recalculated and displayed differently
from what is currently being reported on
HHC. In addition, using sub-state
regions could, as noted above, lead to
undesirable spillover effects between
participating and non-participating
HHAs. These spillover concerns would
be mitigated by the fact that none of the
sub-state regions defined under this
approach would cross state lines and
the fact that the sub-state regions would
be larger than under some approaches to
defining sub-state regions (for example,
at the county level). Nevertheless, it is
unclear how severe these evaluation and
operational concerns would be in
practice and how the extent of these
concerns would depend on the different
characteristics of the selected regions.
We welcome public comment on these
proposed state selection methodologies.
2. Overview of the Randomized
Selection Methodology for States
We are requesting comments on the
following proposed methodology for
selecting states. The selection
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methodology employed will need to
provide the strongest evidence of
producing meaningful results
representative of the national
population of Medicare-certified HHAs
and, in turn, meet the evaluation
requirements of section 1115A(b)(4) of
the Act.
The state selections listed in proposed
§ 484.310 are based on the described
proposed randomized selection
methodology and are subject to change
in the CY 2016 HH PPS final rule as a
result of any changes that may be made
to the proposed randomized
methodology in response to comments.
However, if the final methodology
differs from what we are proposing here,
we will apply the final methodology
and identify the states selected under
the final methodology in the final rule.
We propose to group states by each
state’s geographic proximity to one
another and by accounting for key
evaluation characteristics (that is,
proportionality of service utilization,
proportionality of organizations with
similar tax-exempt status and HHA size,
and proportionality of beneficiaries that
are dually-eligible for Medicare and
Medicaid).
Based on an analysis of OASIS quality
data and Medicare claims data, we
believe the use of nine geographic
groupings is necessary to ensure that the
model accounts for the diversity of
beneficiary demographics, rural and
urban status, cost and quality variations,
among other criteria. To provide for
comparable and equitable selection
probabilities, these separate geographic
groupings each include a comparable
number of states. We are not proposing
to adopt census-based geographic
groupings or the CMS Medicare
Administrative Contractor (MAC)
jurisdictions because those groupings
would not permit an equal opportunity
of selection of Medicare-certified HHAs
by state or an assurance that we would
be able test the model among a diversity
of agencies such as is found across the
nation. Following this logic, under our
proposed methodology, groupings are
based on states’ geographic proximity to
one another, having a comparable
number of states if randomized for an
equal opportunity of selection, and
similarities in key characteristics that
would be considered in the evaluation
study because the attributes represent
different types of HHAs, regulatory
oversight, and types of beneficiaries
served. This is necessary to ensure that
the evaluation study remains objective
and unbiased and that the results of this
study best represent the entire
population of Medicare-certified HHAs
across the nation.
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39871
Several of the key characteristics we
used for grouping state boundaries into
clusters for selection into the model are
also used in the impact analysis of our
annual HHA payment updates, a fact
that reinforces their relevance for
evaluation. The additional proposed
standards for grouping (level of
utilization and socioeconomic status of
patients) are also important to consider
when evaluating the program, because
of their current policy relevance. Large
variations in the level of utilization of
the home health benefit has received
attention from policymakers concerned
with achieving high-value health care
and curbing fraud and abuse.21
Policymakers’ concerns about the role of
beneficiary-level characteristics as
determinants of resource use and health
care quality were highlighted in the
Affordable Care Act, which mandated a
study 22 of access to home health care
for vulnerable populations 23 and, more
recently, Improving Medicare Post-acute
Care Transformation (IMPACT) Act of
2014 required the Secretary to study the
relationship between individuals’
socioeconomic status and resource use
or quality.24 The parameters used to
define each geographic grouping are
further described in the next three
sections.
a. Geographic Proximity
Under the proposed methodology, in
order to ensure that the Medicarecertified HHAs that would be required
to participate in the model are not all in
one region of the country, the states in
each grouping are adjacent to each other
whenever possible while creating
logical groupings of states based on
common characteristics as described
above. Specifically, analysis based on
quality data and claims data found that
HHAs in these neighboring states tend
to hold certain characteristics in
common. These include having similar;
patterns of utilization, proportionality of
non-profit agencies, and types of
beneficiaries served (for example,
severity and number, type of co21 See MedPAC Report to Congress: Medicare
Payment Policy (March 2014, Chapter 9) available
at https://medpac.gov/documents/reports/mar14_
entirereport.pdf. See also the Institute of Medicine
Interim Report of the Committee on Geographic
Variation in Health Care Spending and Promotion
of High-Value Health Care: Preliminary Committee
Observations (March 2013) available at https://
iom.edu/Reports/2013/Geographic-Variation-inHealth-Care-Spending-and-Promotion-of-HighCare-Value-Interim-Report.aspx.
22 This study can be accessed at https://
www.cms.gov/Center/Provider-Type/Home-HealthAgency-HHA-Center.html.
23 Section 3131(d) of the Affordable Care Act.
24 Improving Medicare Post-acute Care
Transformation (IMPACT) Act of 2014 (Public Law
113–185).
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morbidities, and socio-economic status).
Therefore, the proposed groupings of
states are delineated according to states’
geographic proximity to one another
and common characteristics as a means
of permitting greater comparability. In
addition, each of the groupings retains
similar types of characteristics when
compared to any other type of grouping
of states.
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b. Comparable Number of States in Each
Grouping
Under our proposed randomized
selection methodology, each geographic
region, or grouping, has a similar
number of states. As a result, all states
would have a 16.7 percent to 20 percent
chance of being selected under our
proposed methodology, and Medicarecertified HHAs would have a similar
likelihood of being required to compete
in the model by using this sampling
design. We assert that this sampling
design would ensure that no single
entity is singled out for selection, since
all states and Medicare-certified HHAs
would have approximately the same
chance of being selected. In addition,
this sampling approach would mitigate
the opportunity for HHAs to self-select
into the model and thereby bias any
results of the test.
c. Characteristics of State Groupings
Without sacrificing an equal
opportunity for selection, the proposed
state groupings are intended to ensure
that important characteristics of
Medicare-certified HHAs that deliver
care within state boundaries can be used
to evaluate the primary intervention
with greater generalizability and
representativeness of the entire
population of Medicare-certified HHAs
in the nation. Data analysis of these
characteristics employed the full data
set of Medicare claims and OASIS
quality data. Although some
characteristics, such as beneficiary age
and case-mix, yield some variations
from one state to another, other
important characteristics do vary
substantially and could influence how
HHAs respond to the incentives of the
model. Specifically, home health
services utilization rates, tax-exemption
status of the provider, the
socioeconomic status of beneficiaries (as
measured by the proportion of duallyeligible beneficiaries), and agency size
(as measured by average number of
episodes of care per HHA), are
important characteristics that could
influence outcomes of the model.
Subsequently, we intend to study the
impacts of these characteristics for
purposes of designing future valuebased purchasing models and programs.
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These characteristics and expected
variations must be considered in the
evaluation study to enable us to avoid
erroneous inferences about how
different types of HHAs will respond to
HHVBP incentives.
Under this proposed state selection
methodology, state groupings reflect
regional variations that enhance the
generalizability of the model. In line
with this methodology, each grouping
includes states that are similar in at
least one important aforementioned
characteristic while being
geographically located in close
proximity to one another. Using the
criteria described above, the following
geographic groupings were identified
using Medicare claims-based data from
calendar years 2013–2014. Each of the
50 states was assigned to one of the
following geographic groups:
• Group #1: (VT, MA, ME, CT, RI,
NH)
States in this group tend to have
larger HHAs and have average
utilization relative to other states.
• Group #2: (DE, NJ, MD, PA, NY)
States in this group tend to have
larger HHAs, have lower utilization, and
provide care to an average number of
dually-eligible beneficiaries relative to
other states.
• Group #3: (AL, GA, SC, NC, VA)
States in this group tend to have
larger HHAs, have average utilization
rates, and provide care to a high
proportion of minorities relative to other
states.
• Group #4: (TX, FL, OK, LA, MS)
States in this group have HHAs that
tend to be for-profit, have very high
utilization rates, and have a higher
proportion of dually-eligible
beneficiaries relative to other states.
• Group #5: (WA, OR, AK, HI, WY, ID)
States in this group tend to have
smaller HHAs, have average utilization
rates, and are more rural relative to
other states.
• Group #6: (NM, CA, NV, UT, CO,
AZ)
States in this group tend to have
smaller HHAs, have average utilization
rates, and provide care to a high
proportion of minorities relative to other
states.
• Group #7: (ND, SD, MT, WI, MN,
IA)
States in this group tend to have
smaller HHAs, have very low utilization
rates, and are more rural relative to
other states.
• Group #8: (OH, WV, IN, MO, NE.,
KS)
States in this group tend to have
HHAs that are of average size, have
average utilization rates, and provide
care to a higher proportion of dually-
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eligible beneficiaries relative to other
states.
• Group #9: (IL, KY, AR, MI, TN)
States in this group tend to have
HHAs with higher utilization rates
relative to other states.
d. Randomized Selection of States
Upon the careful consideration of the
aforementioned alternative selection
methodologies, including selecting
states on a non-random basis, we choose
to propose the use of a selection
methodology based on a randomized
sampling of states within each of the
nine regional groupings described
above. We examined data on the
evaluation elements listed in this
section to determine if specific states
could be identified in order to fulfill the
needs of the evaluation. After careful
review, we determined that each
evaluation element could be measured
by more than one state. As a result, we
determined that it was necessary to
apply a fair method of selection where
each state would have a comparable
opportunity of being selected and which
would fulfill the need for a robust
evaluation. The proposed nine
groupings of states as described in this
section permit the model to capture the
essential elements of the evaluation
including demographic, geographic, and
market factors.
The randomized sampling of states is
without bias to any characteristics of
any single state within any specific
regional grouping, where no states are
excluded, and no state appears more
than once across any of the groupings.
The randomized selection of states was
completed using a scientificallyaccepted computer algorithm designed
for randomized sampling. The
randomized selection of states was run
on each of the previously described
regional groupings using exactly the
same process and, therefore, reflects a
commonly accepted method of
randomized sampling. This computer
algorithm employs the aforementioned
sampling parameters necessary to define
randomized sampling and omits any
human interaction once it runs.
Based on this sampling methodology,
SAS Enterprise Guide (SAS EG) 5.1
software was used to run a computer
algorithm designed to randomly select
states from each grouping. SAS EG 5.1
and the computer algorithm were
employed to conduct the randomized
selection of states. SAS EG 5.1
represents an industry-standard for
generating advanced analytics and
provided a rigorous, standardized tool
by which to satisfy the requirements of
randomized selection. The key SAS
commands employed include a ‘‘PROC
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SURVEYSELECT’’ statement coupled
with the ‘‘METHOD=SRS’’ option used
to specify simple random sampling as
the sample selection method. A random
number seed was generated by using the
time of day from the computer’s clock.
The random number seed was used to
produce random number generation.
Note that no stratification was used
within any of the nine geographicallydiverse groupings to ensure there is an
equal probability of selection within
each grouping. For more information on
this procedure and the underlying
statistical methodology, please reference
SAS support documentation at: https://
support.sas.com/documentation/cdl/en/
statug/63033/HTML/default/
viewer.htm#statug_surveyselect_
sect003.htm/.
In § 484.310, we propose to codify the
names of the states selected utilizing
this proposed methodology, where one
state from each of the nine groupings
was selected. For each of these
groupings, we propose to use state
borders to demarcate which Medicare
certified HHAs would be required to
compete in this model: Massachusetts
was randomly selected from Group 1,
Maryland was randomly selected from
Group 2, North Carolina was randomly
selected from Group 3, Florida was
randomly selected from Group 4,
Washington was randomly selected
from Group 5, Arizona was randomly
selected from Group 6, Iowa was
randomly selected from Group 7,
Nebraska was randomly selected from
Group 8, and Tennessee was randomly
selected from Group 9. Thus, if our
methodology is finalized as proposed,
all Medicare-certified HHAs that
provide services in Massachusetts,
Maryland, North Carolina, Florida,
Washington, Arizona, Iowa, Nebraska,
and Tennessee will be required to
compete in this model.
However, should the methodology we
propose in this rule change as a result
of comments received during the
rulemaking process, it could result in
different states being selected for the
model. In such an event, we would
apply the final methodology and
announce the selected states in the final
rule. We therefore seek comment from
all interested parties in every state on
the randomized selection methodology
proposed above and codified at
§ 484.310.
Based on the comments received from
this proposed rule, the selection
methodology for participation in the
model may change from state
boundaries to an approach based on
sub-state regions built from CSAs/
MSAs, CBSAs, rural provider level or
HRRs. In that case, the goals of the
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model will remain the same, and
therefore, we would expect to take a
broadly similar approach to selecting
participating regions to the approach
that would be taken when regions are
defined based on state boundaries.
Specifically, as with the selection
methodology outlined above, we would
anticipate grouping sub-state regions
together based on geographic proximity
and other characteristics into groups of
approximately equal size and then
selecting some number of sub-state
regions to participate from each group.
The number of selected participants will
be dependent on the selection
methodology. We welcome public
comment on these proposed state
selection methodologies.
e. Use of CMS Certification Numbers
(CCNs)
We are proposing that Total
Performance Scores (TPS) and payment
adjustments would be calculated based
on an HHA’s CCN 25 and, therefore,
based only on services provided in the
selected states. The exception to this
methodology is where an HHA provides
service in a state that also has a
reciprocal agreement with another state.
Services being provided by the HHA to
beneficiaries who reside in another state
would be included in the TPS and
subject to payment adjustments.26 The
reciprocal agreement between states
allows for an HHA to provide services
to a beneficiary across state lines using
its original CCN number. Reciprocal
agreements are rare and, as identified
using the most recent Medicare claims
data from 2014, there was found to be
less than 0.1 percent of beneficiaries
that provided services that were being
served by CCNs with reciprocal
agreements across state lines. Due to the
very low number of beneficiaries served
across state borders as a result of these
agreements, we expect there to be an
inconsequential impact if we were to
include these beneficiaries in the model.
25 HHAs are required to report OASIS data and
any other quality measures by its own unique CMS
Certification Number (CCN) as defined under Title
42, Chapter IV, Subchapter G, Part § 484.20
Available at URL https://www.ecfr.gov/cgi-bin/textidx?tpl=/ecfrbrowse/Title42/42cfr484_main_02.tpl.
26 See Chapter 2 of the State Operations Manual
(SOM), Section 2184—Operation of HHAs Cross
State Lines, stating ‘‘When an HHA provides
services across State lines, it must be certified by
the State in which its CCN is based, and its
personnel must be qualified in all States in which
they provide services. The appropriate SA
completes the certification activities. The involved
States must have a written reciprocal agreement
permitting the HHA to provide services in this
manner.’’
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D. Performance Assessment and
Payment Periods
1. Performance Reports
We are proposing the use of quarterly
performance reports, annual payment
adjustment reports, and annual
publicly-available performance reports
as 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 would 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.
Competing HHAs would be scored for
the quality of care delivered under the
model based on their performance on
measures compared to both the
performance of their peers, defined by
the same size cohort (either smaller- or
larger-volume cohorts as defined in
§ 484.305), and their own past
performance on the measures. We
propose in § 484.305 to define largervolume cohort to mean the group of
Medicare-certified HHAs within the
boundaries of a selected state that are
participating in HHCAHPs in
accordance with § 484.250 and to define
smaller-volume cohort to mean the
group of HHAs within the boundaries of
a selected state that are exempt from
participation in HHCAHPs in
accordance with § 484.250. Where there
are too few HHAs in the smaller-volume
cohort in each state to compete in a fair
manner (that is, when there is only one
or two HHAs competing within a
specific cohort), these specific HHAs
would be included in the larger-volume
cohort [for purposes of calculating the
total performance score and payment
adjustment] without being measured on
HHCAHPS. We are requesting
comments on this proposed
methodology.
Quality performance scores and
relative peer rankings would be
determined through the use of a
baseline year (calendar year 2015) and
subsequent performance periods for
each competing HHA. Further, these
reports would provide competing HHAs
with an opportunity to track their
quality performance relative to their
peers and their own past performance.
Using these reports provides a
convenient and timely means for
competing HHAs to assess and track
their own respective performance as
capacity is developed to improve or
sustain quality over time.
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Beginning with the data collected
during the first quarter of CY 2016 (that
is, data for the period January 1, 2016
to March 31, 2016), and for every
quarter of the model thereafter, we are
proposing to provide each Medicare
certified HHA with a quarterly report
that contains information on their
performance during the quarter. We
expect to make the first quarterly report
available in July 2016, and to make
performance reports for subsequent
quarters available in October, January
and April. The final quarterly report
would be made available in April 2021.
The quarterly reports would include a
competing HHA’s model-specific
performance results with a comparison
to other competing HHAs within its
cohort (larger- or smaller-volume)
within the state boundary. These modelspecific performance results would
complement all quality data sources
already being provided through the
QIES system and any other quality
tracking system possibly being
employed by HHAs. We note that all
performance measures that Medicarecertified HHAs will report through the
QIES system are also already made
available in the CASPER Reporting
application. The primary difference
between the two reports (CASPER
reports and the model-specific
performance report) is that the modelspecific performance report we are
proposing here consolidates the
applicable performance measures used
in the HHVBP model and provides a
peer-ranking to other competing
Medicare-certified HHAs within the
same state and size-cohort. In addition,
CASPER reports would provide quality
data earlier than model-specific
performance reports because CASPER
reports are not limited by a quarterly
run-out of data and a calculation of
competing peer-rankings. For more
information on the accessibility and
functionality of the CASPER system,
please reference the CASPER Provider
Reporting Guide.27
The model-specific quarterly
performance report would be made
available to each HHA through a
dedicated CMMI model-specific
platform for data dissemination and
include each HHA’s relative ranking
amongst its peers along with
measurement scores and overall
performance rankings.
We are proposing that a separate
payment adjustment report would be
provided once a year to each of the
27 The Casper Reporting Guide is available at
https://www.cms.gov/Medicare/Quality-InitiativesPatient-Assessment-Instruments/
HomeHealthQualityInits/downloads/
HHQICASPER.pdf).
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competing HHAs. This report would
focus primarily on the payment
adjustment percentage and include an
explanation of when the adjustment
would be applied and how this
adjustment was determined relative to
performance scores. Each competing
HHA would receive its own payment
adjustment report viewable only to that
HHA.
We are also proposing a separate,
annual, publicly available quality report
that would provide home health
industry stakeholders, including
providers and suppliers that refer their
patients to HHAs, with an opportunity
to ensure that the beneficiaries they are
referring for home health services are
being provided the best possible quality
of care available. We seek public
comment on the proposed reporting
framework described above.
2. Payment Adjustment Timeline
We propose at § 484.325 that
Medicare-certified HHAs will be subject
to upward or downward payment
adjustments based on performance on
quality measures. We propose this
model would consist of 5 performance
years, where each performance year
would link performance to the
opportunity and risk for payment
adjustment up to an applicable percent
as defined in proposed 42 CFR 484.305.
The first performance year would
transpire from January 1, 2016 through
December 31, 2016, and subsequently,
all other performance years would be
assessed on an annual basis through
2020, unless modified through
rulemaking. The first payment
adjustment would begin January 1, 2018
applied to that calendar year based on
2016 performance data. Subsequently,
all other payment adjustments would be
made on an annual basis through the
conclusion of the model, unless
modified through rulemaking. We are
proposing that payment adjustments
will be increased incrementally over the
course of the model with a maximum
payment adjustment of (5 percent)
upward or downward in 2018 and 2019,
a maximum payment adjustment of 6
percent (upward or downward) in 2020,
and a maximum payment adjustment of
8 percent (upward or downward) in
2021 and 2022. We propose to
implement this model over a total of 7
years beginning on January 1, 2016, and
ending on December 31, 2022.
The baseline year would run from
January 1, 2015 through December 31,
2015 and provide a basis from which
each respective HHA’s performance
would be measured in each of the
performance years. Data related to
performance on quality measures would
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continue to be provided from the
baseline year through the model’s
tenure using a dedicated HHVBP webbased platform specifically designed to
disseminate data in this model (this
‘‘portal’’ would present and archive the
previously described quarterly and
annual quality reports). Further, HHAs
will provide performance data on the
four new quality measures through this
platform as well. Any new measures
employed through the model’s tenure,
subject to rulemaking, would use data
from the previous calendar year as the
baseline.
New market entries (specifically, new
Medicare-certified HHAs delivering care
in the boundaries of selected states)
would also be measured from their first
full calendar year of services in the
state, which would be treated as
baseline data for subsequent
performance years under this model.
The delivery of services would be
measured by the number of episodes of
care for Medicare beneficiaries and used
to determine whether an HHA falls into
the smaller- or larger- volume cohort.
Furthermore, these new market entries
would be competing under the HHVBP
model in the first full calendar year
following the full calendar year baseline
period.
HHAs would be notified in advance of
their first performance level and
payment adjustment being finalized,
based on the 2016 performance period
(January 1, 2016 to December 31, 2016),
with their first payment adjustment to
be applied January 1, 2018 through
December 31, 2018. Each HHA would be
notified of this first pending payment
adjustment on August 1, 2017 and a
preview period would run for 10 days
through August 11, 2017. This preview
period would provide each competing
HHA an opportunity to reconcile any
performance assessment issues relating
to the calculation of scores prior to the
payment adjustment taking effect, in
accordance with the process proposed
in section H—Preview and Period to
Request Recalculation. Once the
preview period ends, any changes
would be reconciled and a report
finalized no later than November 1,
2017 (or 60 days prior to the payment
adjustment taking affect).
Subsequent payment adjustments
would be calculated based on the
applicable full calendar year of
performance data from the quarterly
reports, with HHAs notified and
payments adjusted, respectively, every
year thereafter. As a sequential example,
the second payment adjustment would
occur January 1, 2019 based on a full 12
months of the CY 2017 performance
period. Notification of the adjustment
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would occur on August 1, 2018, along
with the preview period transpiring
through August 11, 2018 and followed
by reconciliation through September 10,
2018. Subsequent payment adjustments
would continue to follow a similar
timeline and process. We seek public
comment on this payment adjustment
schedule.
Beginning in CY 2019, we may
consider revising this payment
adjustment schedule and updating the
payment adjustment more frequently
than once each year if it is determined
that a more timely application of the
adjustment as it relates to performance
improvement efforts that have
transpired over the course of a calendar
year would generate increased
improvement in quality measures.
Specifically, we would expect that
having payment adjustments transpire
closer together through more frequent
performance periods would accelerate
improvement in quality measures
because HHAs would be able to justify
earlier investments in quality efforts and
be incentivized for improvements. In
effect, this concept may be
operationalized to create a smoothing
effect where payment adjustments are
based on overlapping 12-month
performance periods that occur every 6
months rather than annually. As an
example, the normal 12-month
performance period occurring from
January 1, 2020 to December 31, 2020
might have an overlapping 12-month
performance period occurring from July
1, 2020 to June 30, 2021. Following the
regularly scheduled January 1, 2022
payment adjustments, the next
adjustments could be applied to
payments beginning on July 1, 2022
through December 31, 2022. Depending
on if and when more frequent payment
adjustments would be applied,
performance would be calculated based
on the applicable 12-months of
performance data, HHAs notified, and
payments adjusted, respectively, every
six months thereafter, until the
conclusion of the model. As a result,
separate performance periods would
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have a 6-month overlap through the
conclusion of the model. HHAs would
be notified through rulemaking and be
given the opportunity to comment on
any proposed changes to the frequency
of payment adjustments. We seek public
comment on the proposed payment
adjustment schedule described above.
E. Quality Measures
1. Objectives
Initially, we propose the measures for
the HHVBP model would be
predominantly drawn from the current
Outcome and Assessment Information
Set (OASIS),28 which is familiar to the
home health industry and readily
available for utilization by the proposed
model. In addition, the HHVBP model
provides us with an opportunity to
examine a broad array of quality
measures that address critical gaps in
care. A recent comprehensive review of
the VBP experience over the past
decade, sponsored by the Office of the
Assistant Secretary for Planning and
Evaluation (ASPE), identified several
near- and long-term objectives for
HHVBP measures.29 The recommended
objectives emphasize measuring patient
outcomes and functional status;
appropriateness of care; and incentives
for providers to build infrastructure to
facilitate measurement within the
quality framework.30 The following
seven objectives derived from this study
served as guiding principles for the
selection of the proposed measures for
the HHVBP model:
28 For detailed information on OASIS see the
official CMS OASIS web resource available at
https://www.cms.gov/Medicare/Quality-InitiativesPatient-Assessment-Instruments/OASIS/
index.html?redirect=/oasis. See also industry
resource available at https://www.oasisanswers.com/
index.htm, specifically updated OASIS component
information available at www.oasisanswers.com/
LiteratureRetrieve.aspx?ID=215074).
25 U.S. Department of Health and Human
Services. Office of the Assistant Seretary for
Planning and Evaluation (ASPE) (2014) Measuring
Success in Health Care Value-Based Purchasing
Programs. Cheryl L. Damberg et. al. on behalf of
RAND Health.
30 Id.
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39875
1. Use a broad measure set that
captures the complexity of the HHA
service provided;
2. Incorporate the flexibility to
include Improving Medicare Post-Acute
Care Transformation (IMPACT) Act of
2014 proposed measures that are crosscutting amongst post-acute care settings;
3. Develop second-generation
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.
2. Proposed Methodology for Selection
of Quality Measures
a. Direct Alignment With National
Quality Strategy Priorities
A central driver of the proposed
measure selection process was
incorporating innovative thinking from
the field while simultaneously drawing
on the most current evidence-based
literature and documented best
practices. Broadly, we propose measures
that have a high impact on care delivery
and support the combined priorities of
HHS and CMS to improve health
outcomes, quality, safety, efficiency,
and experience of care for patients. To
frame the selection process, we utilized
the domains described in the CMS
Quality Strategy that maps to the six
National Quality Strategy (NQS) priority
areas (see Figure 3 for CMS domains).31
3131 The CMS Quality Strategy is discussed in
broad terms at URL https://www.cms.gov/Medicare/
Quality-Initiatives-Patient-Assessment-Instruments/
QualityInitiativesGenInfo/CMS-QualityStrategy.html. CMS Domains appear presentations
by CMS (xxxxx) and ONC (available at https://www.
cms.gov/eHealth/downloads/Webinar_eHealth_
March25_eCQM101.pdf) and a CMS discussion of
the NQS Domains can be found at URL https://www.
cms.gov/Regulations-and-Guidance/Legislation/
EHRIncentivePrograms/2014_
ClinicalQualityMeasures.html.
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b. Referenced Quality Measure
Authorities
We propose at § 484.315 that
Medicare-certified HHAs would be
evaluated using a starter set of quality
measures (‘‘starter set’’ refers to the
proposed quality measures for the first
year of this model) designed to
encompass multiple NQS domains, and
provide future flexibility to incorporate
and study newly developed measures
over time. New and evolving measures
would be considered for inclusion in
subsequent years of this model and
proposed through future rulemaking.
To create the proposed starter set we
began researching the current set of
OASIS measures that are being used
within the health home environment.32
Following that, we searched for
endorsed quality measures using the
National Quality Forum (NQF) Quality
Positioning System (QPS),33 selecting
measures that address all possible NQS
domains. We further examined
measures on the CMS-generated
Measures Under Consideration (MUC)
list,34 and reviewed other relevant
32 All data for the starter set measures, not
including New Measures, is currently collected
from HHAs under §§ 484.20 and 484.210.
33 The NQF Quality Positioning System is
available at https://www.qualityforum.org/QPS.
34 To review the MUC List see https://
www.qualityforum.org/Setting_Priorities/
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measures used within the health care
industry but not currently used in the
home health setting, as well as proposed
measures required by the IMPACT Act
of 2014. Finally, we searched the
National Quality Measures
Clearinghouse (NQMS) to identify
evidence-based measures and measure
sets.
c. Key Policy Considerations and Data
Sources
To ensure proposed measures for the
HHVBP model take a more holistic view
of the patient beyond a particular
disease state or care setting, we are
proposing measures, which include
outcome measures as well as process
measures, that have the potential to
follow patients across multiple settings,
reflect a multi-faceted approach, and
foster the intersection of health care
delivery and population health. A key
consideration behind this approach is to
use in performance year one (PY1) of
the model proven measures that are
readily available and meet a high impact
need, and in subsequent model years
augment this starter set with innovative
measures that have the potential to be
impactful and fill critical measure gap
areas. All substantive changes or
additions to the proposed starter set or
Partnership/Measures_Under_Consideration_List_
2014.aspx.
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new measures would be proposed for
inclusion in future rulemaking. This
approach to quality measure selection
aims to balance the burden of collecting
data with the inclusion of new and
important measures. We carefully
considered the potential burden on
HHAs to report the measure data when
developing the proposed starter set, and
prioritized proposed measures that
would draw both from claims data and
data already collected in OASIS.
The majority of the proposed
measures in this model would use
OASIS data currently being reported to
CMS and linked to state-specific CCNs
for selected states in order to promote
consistency and to reduce the data
collection burden for providers.
Utilizing primarily OASIS data would
allow the model to leverage reporting
structures already in place to evaluate
performance and identify weaknesses in
care delivery. This model would also
afford the opportunity to study
measures developed in other care
settings and new to the home health
industry (hereinafter referred to as
‘‘New Measures’’). Many of the
proposed New Measures have been used
in other health care settings and are
readily applicable to the home health
environment (for example, influenza
vaccination coverage for health care
personnel). Proposed New Measures for
PY1 are described in detail below. We
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propose in PY1 to collect data on these
New Measures which have already been
tested for validity, reliability, usability/
feasibility, and sensitivity in other
health care settings but have not yet
been validated within the home health
setting. HHVBP will study if their use in
the home health setting meets validity,
reliability, usability/feasibility, and
sensitivity to statistical variations
criteria. For PY1, we propose HHA’s
would earn points to be included in the
Total Performance Score (TPS) simply
for reporting data on New Measures (see
Section—Performance Scoring
Methodology). To the extent we
determine that one or more of the
proposed New Measures is valid and
reliable for the home health setting, we
will consider proposing in future
rulemaking to score Medicare-certified
HHAs on their actual performance on
the measure.
3. Proposed Measures
The initial set of measures proposed
for PY1 of the model utilizes data
collected via OASIS, Medicare claims,
HHCAHPS survey data, and data
reported directly from the HHAs to
CMS. In total there are 10 process
measures and 15 outcome measures (see
Figure 4a) plus the four New Measures
(see Figure 4b). Process measures
evaluate the rate of HHA use of specific
evidence-based processes of care based
on the evidence available. Outcomes
measures illustrate the end result of care
delivered to HHA patients. When
available, NQF endorsed measures
would be used. This set of measures
would be subject to change or
retirement during subsequent model
years and revised through the
rulemaking process. For example, we
may propose in future rulemaking to
remove one or more of these measures
if, based on the evidence, we conclude
that it is no longer appropriate for the
model because, for example,
performance on it has topped-out. We
would also consider proposing to
update the measure set if new measures
that address gaps within the NQS
domains became available. We would
also consider proposing adjustments to
the measure set based on lessons
learned during the course of the model.
For instance, in light of the passage of
the IMPACT Act of 2014, which
mandates the collection and use of
standardized post-acute care assessment
data, we would consider proposing in
future rulemaking to adopt measures
that meet the requirements of the
IMPACT Act as soon as they became
available.
We seek public comment on the
methodology for constructing the
proposed starter set of quality measures
and on the proposed selected measures.
FIGURE 4a—PY1 PROPOSED MEASURES 35
NQS domains
Measure
type
Measure title
Identifier
Data source
Improvement
in Ambulation-Locomotion.
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.
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Clinical Quality
of Care.
Improvement
in Dyspnea.
Outcome
NA ..................
OASIS
(M1400).
35 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
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Numerator
Denominator
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.
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.
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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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/HHQIQuality
Measures.html. For information on HHCAHPS
measures see https://homehealthcahps.org/Survey
andProtocols/SurveyMaterials.aspx.
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FIGURE 4a—PY1 PROPOSED MEASURES 35—Continued
Measure
type
Identifier
Process ..
NQF0526 .......
OASIS
(M0102;
M0030).
CommunicaDischarged to
tion & Care
Community.
Coordination.
Outcome
NA ..................
OASIS
(M2420).
CommunicaCare Managetion & Care
ment: Types
Coordination.
and Sources
of Assistance.
Efficiency &
Acute Care
Cost ReducHospitalization.
tion: Unplanned
Hospitalization during
first 60 days
of Home
Health; Hospitalization
during first
30 days of
Home
Health.
Efficiency &
Emergency
Cost ReducDepartment
tion.
Use without
Hospitalization.
Process ..
NA ..................
OASIS
(M2102).
Multiple data elements ...........
Outcome
NQF0171;
NQF2380
(Under review for
Home
Health).
CCW (Claims)
Number of home health stays
for patients who have a
Medicare claim for an admission to an acute care
hospital in the 60 days following the start of the home
health stay.
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.
Outcome
NQF0173 .......
CCW (Claims)
Patient Safety
Pressure Ulcer
Prevention
and Care.
Process ..
NQF0538 .......
OASIS
(M1300;
M2400).
Patient Safety
Improvement
in Pain Interfering with
Activity.
Outcome
NQF0177 .......
OASIS
(M1242).
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 during which interventions to prevent pressure ulcers were included
in the Physician-ordered
plan of care and implemented (since the previous
OASIS assessment).
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 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
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 during the reporting period, other than those
covered by generic or
measure-specific exclusions.
NQS domains
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Clinical Quality
of Care.
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Data source
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Numerator
Denominator
Number of home health episodes of care in which the
start or resumption of care
date was either on the Physician-specified date or
within 2 days of their referral date or inpatient discharge date whichever is
later. For resumption of
care, per the Medicare
Condition of Participation,
the patient must be seen
within 2 days of inpatient
discharge, even if the physician specifies a later date.
Number of home health episodes where the assessment completed at the discharge indicates the patient
remained in the community
after discharge.
Number of home health episodes of care ending with
discharge, death, or transfer to inpatient facility during the reporting period,
other than those covered
by generic or measure-specific exclusions.
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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.
Multiple data elements.
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FIGURE 4a—PY1 PROPOSED MEASURES 35—Continued
NQS domains
Measure title
Measure
type
Identifier
Patient Safety
Improvement
in Management of Oral
Medications.
Outcome
NQF0176 .......
OASIS
(M2020).
Patient Safety
Multifactor Fall
Risk Assessment
Conducted
for All Patients who
Can Ambulate.
Prior Functioning ADL/
IADL.
Process ..
NQF0537 .......
OASIS
(M1910).
Outcome
NQF0430 .......
OASIS
(M1900).
Care of Patients.
Outcome
........................
CAHPS ..........
Number of home health epiNumber of home health episodes of care where the
sodes of care ending with a
value recorded on the disdischarge during the reportcharge assessment indiing period, other than those
cates less impairment in
covered by generic or
taking oral medications cormeasure-specific exclusions
rectly at discharge than at
start (or resumption) of care.
Number of home health epiNumber of home health episodes in which patients had
sodes of care ending with
a multi-factor fall risk asdischarge, death, or transsessment at start/resumpfer to inpatient facility durtion of care.
ing the reporting period,
other than those covered
by generic or measure-specific exclusions.
The number (or proportion) of All patients in a risk adjusted
a clinician’s patients in a
diagnostic category with a
particular risk adjusted diDaily Activity goal for an
agnostic category who
episode of care Cases to
meet a target threshold of
be included in the denomiimprovement in Daily Activnator could be identified
ity (that is, ADL and IADL)
based on ICD–9 codes or
functioning.
alternatively, based on CPT
codes relevant to treatment
goals focused on Daily Activity function.
NA .......................................... NA.
Communications between Providers and
Patients.
Specific Care
Issues.
Outcome
........................
CAHPS ..........
NA ..........................................
NA.
Outcome
........................
CAHPS ..........
NA ..........................................
NA.
Overall rating
of home
health care
and.
Willingness to
recommend
the agency.
Outcome
........................
CAHPS ..........
NA ..........................................
NA.
Outcome
........................
CAHPS ..........
NA ..........................................
NA.
Depression
Assessment
Conducted.
Process ..
NQF0518 .......
OASIS
(M1730).
Number of home health episodes in which patients
were screened for depression (using a standardized
depression screening tool)
at start/resumption of care.
Influenza Vaccine Data
Collection
Period:
Does this
episode of
care include
any dates
on or between October 1 and
March 31?
Process ..
NA ..................
OASIS
(M1041).
NA ..........................................
Number of home health episodes of care ending with
discharge, death, or transfer to inpatient facility during the reporting period,
other than those covered
by generic or measure-specific exclusions.
NA.
Patient Safety
Patient &
CaregiverCentered
Experience.
Patient &
CaregiverCentered
Experience.
Patient &
CaregiverCentered
Experience.
Patient &
CaregiverCentered
Experience.
Patient &
CaregiverCentered
Experience.
Population/
Community
Health.
asabaliauskas on DSK5VPTVN1PROD with PROPOSALS
Population/
Community
Health.
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Numerator
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FIGURE 4a—PY1 PROPOSED MEASURES 35—Continued
Measure title
Measure
type
Identifier
Population/
Community
Health.
Influenza Immunization
Received for
Current Flu
Season.
Process ..
NQF0522 .......
OASIS
(M1046).
Population/
Community
Health.
Pneumococcal
Polysaccharide
Vaccine
Ever Received.
Process ..
NQF0525 .......
OASIS
(M1051).
Population/
Community
Health.
Reason Pneumococcal
vaccine not
received.
Drug Education on All
Medications
Provided to
Patient/
Caregiver
during all
Episodes of
Care.
Process ..
NA ..................
OASIS
(M1056).
NA ..........................................
Process ..
NA ..................
OASIS
(M2015).
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).
NQS domains
Clinical Quality
of Care.
Data source
Numerator
Denominator
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 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.
NA.
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.
FIGURE 4b—PY1 PROPOSED NEW MEASURES
Measure title
Measure
type
Identifier
Data source
Numerator
Denominator
Patient Safety
asabaliauskas on DSK5VPTVN1PROD with PROPOSALS
NQS domains
Adverse Event
for Improper
Medication
Administration and/or
Side Effects.
Outcome
NA ..................
Reported by
HHAs
through Web
Portal.
Number of home health episodes of care where the
discharge/transfer assessment indicated the patient
required emergency treatment from a hospital emergency department related
to improper administration
or medication side effects
(adverse drug reactions).
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.
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FIGURE 4b—PY1 PROPOSED NEW MEASURES—Continued
Measure title
Measure
type
Identifier
Data source
Numerator
Denominator
Population/
Community
Health.
Influenza Vaccination
Coverage
for Home
Health Care
Personnel.
Process ..
NQF0431
(Used in
other care
settings, not
Home
Health).
Reported by
HHAs
through Web
Portal.
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.
Population/
Community
Health.
Herpes zoster
(Shingles)
vaccination:
Has the patient ever received the
shingles
vaccination?.
Advanced
Care Plan.
Process ..
NA ..................
Reported by
HHAs
through Web
Portal.
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 abovementioned numerator categories.
Total number of Medicare
beneficiaries aged 60 years
and over who report having
ever received zoster vaccine (shingles vaccine).
Process ..
NQF0326 .......
Reported by
HHAs
through Web
Portal.
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.
All patients aged 65 years
and older.
NQS domains
asabaliauskas on DSK5VPTVN1PROD with PROPOSALS
Communication & Care
Coordination.
4. Additional Information on HHCAHPS
Figure 5 provides details on the
elements of the Home Health Care
Consumer Assessment of Healthcare
Providers and Systems Survey
(HHCAHPS) we propose to include in
the PY1 starter set. The HHVBP model
would not alter the HHCAHPS current
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scoring methodology or the
participation requirements in any way.
Details on participation requirements
for HHCAHPS can be found at 42 CFR
484.250 36 and details on HHCAHPS
36 76 FR 68606, Nov. 4, 2011, as amended at 77
FR 67164, Nov. 8, 2012; 79 FR 66118, Nov. 6, 2014.
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Total number of Medicare
beneficiaries aged 60 years
and over receiving services
from the HHA.
scoring methodology are available at
https://homehealthcahps.org/Surveyand
Protocols/SurveyMaterials.aspx.37
37 Detailed scoring information is contained in the
Protocols and Guidelines manual posted on the
HHCAHPS Web site and available at https://home
healthcahps.org/Portals/0/PandGManual_
NOAPPS.pdf.
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FIGURE 5—HOME HEALTH CARE CONSUMER ASSESSMENT OF HEALTHCARE PROVIDERS AND SYSTEMS SURVEY
(HHCAHPS) COMPOSITES
Response categories
Care of Patients:
Q9. In the last 2 months of care, how often did home health providers from this agency seem informed and up-to-date about all the care or treatment you got at home?.
Q16. In the last 2 months of care, how often did home health providers from this agency treat
you as gently as possible?.
Q19. In the last 2 months of care, how often did home health providers from this agency treat
you with courtesy and respect?.
Q24. In the last 2 months of care, did you have any problems with the care you got through this
agency?.
Communications Between Providers & Patients:
Q2. When you first started getting home health care from this agency, did someone from the
agency tell you what care and services you would get?.
Q15. In the past 2 months of care, how often did home health providers from this agency keep
you informed about when they would arrive at your home?.
Q17. In the past 2 months of care, how often did home health providers from this agency explain
things in a way that was easy to understand?.
Q18. In the past 2 months of care, how often did home health providers from this agency listen
carefully to you?.
Q22. In the past 2 months of care, when you contacted this agency’s office did you get the help
or advice you needed?.
Q23. When you contacted this agency’s office, how long did it take for you to get the help or advice you needed?.
Specific Care Issues:
Q3. When you first started getting home health care from this agency, did someone from the
agency talk with you about how to set up your home so you can move around safely?.
Q4. When you started getting home health care from this agency, did someone from the agency
talk with you about all the prescription medicines you are taking?.
Q5. When you started getting home health care from this agency, did someone from the agency
ask to see all the prescription medicines you were taking?.
Q10. In the past 2 months of care, did you and a home health provider from this agency talk
about pain?.
Q12. In the past 2 months of care, did home health providers from this agency talk with you
about the purpose for taking your new or changed prescription medicines?.
Q13. In the last 2 months of care, did home health providers from this agency talk with you about
when to take these medicines?.
Q14. In the last 2 months of care, did home health providers from this agency talk with you about
the important side effects of these medicines?.
Global Type Measures:
What is your overall rating of your home health care? ......................................................................
Would you be willing to recommend this home health agency to family and friends? ......................
asabaliauskas on DSK5VPTVN1PROD with PROPOSALS
5. New Measures
As discussed in the previous section,
the New Measures we propose are not
currently reported by Medicare-certified
HHAs to CMS, but we believe fill gaps
in the NQS Domains not completely
covered by existing measures in the
home health setting. All Medicarecertified HHAs in selected states,
regardless of cohort size or number of
episodes, will be required to submit
data on the New Measures for all
Medicare beneficiaries to whom they
provide home health services within the
state (unless an exception applies). We
propose at § 484.315 that HHAs will be
required to report data on these New
Measures. Competing Medicare-certified
HHAs would submit data through a
dedicated HHVBP web-based platform.
This web-based platform would
function as a means to collect and
distribute information from and to
competing Medicare-certified HHAs.
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Also, for those HHAs with a sufficient
number of episodes of care to be subject
to a payment adjustment, New Measures
scores included in the final TPS for PY1
are only based on whether the HHA has
submitted data to the HHVBP web-based
platform or not. We are proposing the
following New Measures for competing
Medicare-certified HHAs:
• Advance Care Planning;
• Adverse Event for Improper
Medication Administration and/or Side
Effects;
• Influenza Vaccination Coverage for
Home Health Care Personnel; and,
• Herpes Zoster (Shingles)
Vaccination received by HHA patients.
a. Advance Care Planning
Advance Care Planning is an NQFendorsed process measure in the NQS
domain of Person- and Caregivercentered experience and outcomes (see
Figure 3). This measure is currently
endorsed at the group practice/
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Never, Sometimes, Usually, Always.
Never, Sometimes, Usually, Always.
Never, Sometimes, Usually, Always.
Yes, No.
Yes, No.
Never, Sometimes, Usually, Always.
Never, Sometimes, Usually, Always.
Never, Sometimes, Usually, Always.
Yes, No.
Same day; 1 to 5 days; 6 to 14 days;
More than 14 days.
Yes, No.
Yes, No.
Yes, No.
Yes, No.
Yes, No.
Yes, No.
Yes, No.
Use a rating scale (1–10).
Never, Sometimes, Usually, Always.
individual clinician level of analysis.
We believe its adoption under the
HHVBP model represents an
opportunity to study this measure in the
home health setting. This is an
especially pertinent measure for home
health care to ensure that the wishes of
the patient regarding their medical,
emotional, or social needs are met
across care settings. The Advance Care
Planning measure would focus on
Medicare beneficiaries, including
dually-eligible beneficiaries.
The measure would be numerically
expressed by a ratio whose numerator
and denominator are as follows:
Numerator: The measure would
calculate the percentage of patients age
18 years and older served by the HHA
that have an advance care plan or
surrogate decision maker 38 documented
38 A surrogate decision maker, also known as a
health care proxy or agent, advocates for patients
who are unable to make decisions or speak for
themselves about personal health care such that
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mishap ‘‘that occur[s] during
prescribing, transcribing, dispensing,
administering, adherence, or monitoring
a drug’’ and should be distinguished
from an adverse drug reaction, which is
harm directly caused by the drug at
normal doses, during normal use.42 The
National Quality Forum has included
ADEs as a Serious Reportable Event
(SRE) in the category of Care
Management, defining said event as a
‘‘patient death or serious injury
associated with a medication error (for
example, errors involving the wrong
drug, wrong dose, wrong patient, wrong
time, wrong rate, wrong preparation, or
wrong route of administration)’’, noting
that ‘‘. . . the high rate of medication
errors resulting in injury and death
makes this event important to endorse
again.’’ 43
The annual incidence of ADEs in
health care in the United States is high;
authoritative estimates indicate that
each year 400,000 preventable ADEs
occur in hospitals, 800,000 in long term
care settings and in excess of 500,000
among Medicare patients in outpatient
settings.44 The cost of ADEs occurring in
hospitals alone has been estimated at
$5.6 billion.45 Older patients are
b. Adverse Event for Improper
Medication Administration and/or Side
Effects
Adverse Event for Improper
Medication Administration and/or Side
Effects is a measure that aligns with the
NQS domain of Safety (specifically
‘‘medication safety’’—see Figure 3) with
the goal of making care safer by
reducing harm caused in the delivery of
care.
An adverse drug event (ADE) is an
injury related to medication use.40 More
specifically, it is ‘‘an injury resulting
from medical intervention related to a
drug’’ and ‘‘encompasses harms that
occur during medical care that are
directly caused by the drug including
but not limited to medication errors,
adverse drug reactions and
overdoses.’’ 41 A medication error is a
asabaliauskas on DSK5VPTVN1PROD with PROPOSALS
in the clinical record or documentation
in the clinical record that an advance
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.
Denominator: All patients aged 65
years and older admitted to the HHA.
Information on this numerator and
denominator would be reported by
HHAs through the HHVBP web-based
platform, in addition to other
information related to this measure as
the Secretary deems appropriate.
Advance care planning ensures that
the health care plan is consistent with
the patient’s wishes and preferences.
Therefore, studying this measure within
the HHA environment allows for further
analysis of planning for the ‘‘what ifs’’
that may occur during the patient’s
lifetime. In addition, the use of this
measure is expected to result in an
increase in the number of patients with
advance care plans. Increased advance
care planning among the elderly is
expected to result in enhanced patient
autonomy and reduced hospitalizations
and in-hospital deaths.39
We welcome public comments on this
measure’s proposed adoption under the
HHVBP model.
pdfs/ADE-Action-Plan-Executive-Summary.pdf,
citing VA Center for Medication Safety And VHA
Pharmacy Benefits Management Strategic
Healthcare Group and the Medical Advisory Panel
Adverse Drug Events, Adverse Drug Reactions and
Medication Errors Frequently Asked Questions
(November 2006), available at: https://www.va.gov/
ms/professionals/medications/adverse_drug_
reaction_faq.pdfhttps://www.va.gov/ms/
professionals/medications/adverse_drug_reaction_
faq.pdf.
42 VA Center for Medication Safety And VHA
Pharmacy Benefits Management Strategic
Healthcare Group and the Medical Advisory Panel
Adverse Drug Events, Adverse Drug Reactions and
Medication Errors Frequently Asked Questions
(November 2006), available at: https://www.va.gov/
ms/professionals/medications/adverse_drug_
reaction_faq.pdf.https://www.va.gov/ms/
professionals/medications/adverse_drug_reaction_
faq.pdf. Note that this VA document urges that the
term Adverse Drug Reaction should generally be
used rather than the term ‘‘side effect’’ because the
latter ’’ tends to normalize the concept of injury
from drugs. This approach has been adopted in the
National Action Plan for ADE Prevention, in which
the term ‘‘side effects’’ does not appear. See: The
Office of Disease Prevention and Health Promotion
(ODPHP), National Action Plan for ADE Prevention,
available at: https://www.health.gov/hai/pdfs/ADEAction-Plan-Executive-Summary.pdf.
43 National Quality Forum, Serious Reportable
Events in Healthcare-2011, at 9. (2011), available at:
https://www.qualityforum.org/Publications/2011/12/
Serious_Reportable_Events_in_Healthcare_
2011.aspxhttps://www.qualityforum.org/
Publications/2011/12/Serious_Reportable_Events_
in_Healthcare_2011.aspx.
44 The Institute of Medicine, Preventing
Medication Errors (2006), at 5.). Available at:
https://books.nap.edu/openbook.php?record_
id=11623&page=5.
45 National Quality Forum, NQF-Endorsed
Measures for Patient Safety DRAFT REPORT FOR
COMMENT (May 28, 2014), at 6. Available at:
someone else must provide direction in decisionmaking, as the surrogate decision-maker.
39 Lauren Hersch Nicholas, Ph.D., MPP et al.
Regional Variation in the Association Between
Advance Directives and End-of-Life Medicare
Expenditures. JAMA. 2011; 306(13): 1447–1453.
doi:10.1001/jama.2011.1410.
40 Reporting of Adverse Drug Events: Examination
of a Hospital Incident Reporting System. Radhika
Desikan, Melissa J. Krauss, W. Claiborne Dunagan,
Erin Christensen Rachmiel, Thomas Bailey, Victoria
J. Fraser https://www.ahrq.gov/professionals/qualitypatient-safety/patient-safety-resources/resources/
advances-in-patient-safety/vol1/Desikan.pdf.
41 The Office of Disease Prevention and Health
Promotion (ODPHP), National Action Plan for ADE
Prevention, available at: https://www.health.gov/hai/
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39883
particularly vulnerable to adverse drug
reactions and are seven times as likely
as younger persons to experience an
adverse drug event requiring
hospitalization.46 Further, we are
specifically concerned that ‘‘Analyses of
cost data indicate that Medicare patients
experience significantly higher rates of
ADEs than both privately insured and
Medicaid-covered patients.’’ 47
Prevention of ADEs is a national Patient
Safety Priority pursuant to the ADE
National Action Plan, which focuses on
vulnerable population groups, one of
which is the elderly. Most work on
ADEs has taken place in the hospital
setting. There is little available data
regarding the incidence and types of
ADEs occurring in home health care for
the elderly under Medicare. We believe
there is a critical need for such
information with regard to patient
safety, and we are proposing this
measure to address that need.
The measure would be numerically
expressed by a ratio whose numerator
and denominator are as follows:
Numerator: Number of home health
episodes of care where the discharge/
transfer assessment indicated the
patient required emergency treatment
from a hospital emergency department
related to improper administration or
medication side effects (adverse drug
reactions).
Denominator: Number of home health
episodes of care ending with a discharge
during the performance period.
Numbers to be specifically excluded
from the ratio as a measure-specific
exclusion are those relating to home
health episodes of care for which
emergency department use or the reason
for emergency department use is
unknown at transfer or discharge. Stated
otherwise, the measure would be
expressed by a ratio indicating the
relationship between (i) the number of
emergency treatments transferring or
discharged patients sought or received
for OASIS C M2310, ‘‘1-Improper
medication administration, adverse drug
reactions, medication side effects,
toxicity, anaphylaxis’’ and (ii) the
number of emergency treatments sought
or received for one of the other reasons
identified by OASIS–C M2310. Neither
www.qualityforum.org/WorkArea/
linkit.aspx?LinkIdentifier=id.
46 Emergency Hospitalizations for Adverse Drug
Events in Older Americans Daniel S. Budnitz, M.D.,
M.P.H., Maribeth C. Lovegrove, M.P.H., Nadine
Shehab, Pharm.D., M.P.H., and Chesley L. Richards,
M.D., M.P.H.,N Engl J Med 2011; 365: 2002–2012
available at: https://www.nejm.org/doi/full/10.1056/
NEJMsa1103053.
47 The Office of Disease Prevention and Health
Promotion (ODPHP), National Action Plan for ADE
Prevention, available at: https://www.health.gov/hai/
pdfs/ADE-Action-Plan-Executive-Summary.pdf.
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number would include (a) incidents
where the reason checked on M2310 is
‘‘UK-Reason unknown’’ or (b) incidents
where use of emergency department was
unknown at transfer or discharge. Data
for this measure would be reported by
HHAs through the dedicated HHVBP
web-based platform based on OASIS C/
ICD 9/10 Items M2300 Emergent Care
and M2310 Reasons for Emergent Care,
in addition to other information related
to this measure as the Secretary deems
appropriate.
We welcome public comments on this
measure’s proposed adoption under the
HHVBP model.
asabaliauskas on DSK5VPTVN1PROD with PROPOSALS
c. Influenza Vaccination Coverage for
Home Health Care Personnel
Staff Immunizations (Influenza
Vaccination Coverage among Health
Care Personnel) (NQF #0431) is an NQFendorsed measure that addresses the
NQS domain of Population Health (see
Figure 3). The measure is currently
endorsed in Ambulatory Care;
Ambulatory Surgery Center (ASC),
Ambulatory Care; Clinician Office/
Clinic, Dialysis Facility, Hospital/Acute
Care Facility, Post-Acute/Long Term
Care Facility; Inpatient Rehabilitation
Facility, Post-Acute/Long Term Care
Facility; Long Term Acute Care
Hospital, and Post-Acute/Long Term
Care Facility: Nursing Home/Skilled
Nursing Facility. Home health care is
among the only remaining settings for
which the measure has not been
endorsed. We believe the proposed
HHVBP model presents an opportunity
to study this measure in the home
health setting. This measure is currently
reported in multiple CMS quality
reporting programs, including
Ambulatory Surgical Center Quality
Reporting, Hospital Inpatient Quality
Reporting, and Long-Term Care Hospital
Quality Reporting; we believe its
adoption under the proposed HHVBP
model presents an opportunity for
alignment in our quality programs. The
documentation of staff immunizations is
also a standard required by many HHA
accrediting organizations. We believe
that this measure would be appropriate
for HHVBP because it addresses total
population health across settings of care
by reducing the exposure of individuals
to a potentially avoidable virus.
The measure would be numerically
expressed by a ratio whose numerator
and denominator are as follows:
Numerator: The measure would
calculate the percentage of home health
care personnel who receive the
influenza vaccine, and document those
who do not receive the vaccine in the
articulated categories below:
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(1) Received an influenza vaccination
administered at the health care agency,
or reported in writing (paper or
electronic) or provided documentation
that influenza vaccination was received
elsewhere; or
(2) Were determined to have a
medical contraindication/condition of
severe allergic reaction to eggs or to
other component(s) of the vaccine, or
´
history of Guillain-Barre Syndrome
within 6 weeks after a previous
influenza vaccination; or
(3) Declined influenza vaccination; or
(4) Persons with unknown
vaccination status or who do not
otherwise meet any of the definitions of
the above-mentioned numerator
categories.
Each of the above groups would be
divided by the number of health care
personnel who are working in the HHA
for at least one working day between
October 1 and March 31 of the following
year, regardless of clinical responsibility
or patient contact.
Denominator: This measure collects
the number of home health care
personnel who, during the flu season: 48
Denominators are to be calculated
separately for the following three
groups:
1. Employees: All persons who
receive a direct paycheck from the
reporting HHA (that is, on the agency’s
payroll);
2. Licensed independent
practitioners: Include physicians (MD,
DO), advanced practice nurses, and
physician assistants only who are
affiliated with the reporting agency who
do not receive a direct paycheck from
the reporting HHA; and
3. Adult students/trainees and
volunteers: Include all adult students/
trainees and volunteers who do not
receive a direct paycheck from the
reporting HHA.
This proposed measure for the
HHVBP model is expected to result in
increased influenza vaccination among
home health professionals. Reporting
health care personnel influenza
vaccination status would allow HHAs to
better identify and target unvaccinated
personnel. Increased influenza
vaccination coverage among HHA
personnel would be expected to result
in reduced morbidity and mortality
related to influenza virus infection
among patients, especially elderly and
vulnerable populations.49
48 Flu season is generally October 1 (or when the
vaccine became available) through March 31 of the
following year. See URL https://www.cdc.gov/flu/
about/season/flu-season.htm for detailed
information.
49 Carman W.F., Elder A.G., Wallace L.A., et al.
Effects of influenza vaccination of health-care
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Information on the above numerator
and denominator would be reported by
HHAs through the HHVBP web-based
platform, in addition to other
information related to this measure as
the Secretary deems appropriate. We
welcome public comments on this
measure’s proposed adoption under the
HHVBP model.
d. Herpes Zoster Vaccine (Shingles
Vaccine) for Patients
We are proposing to adopt this
measure for the HHVBP model because
it aligns with the NQS Quality Strategy
Goal to Promote Effective Prevention &
Treatment of Chronic Disease. Currently
this proposed measure is not endorsed
by NQF or collected in OASIS.
However, due to the severe physical
consequences of symptoms associated
with shingles,50 we view its adoption
under the HHVBP model as an
opportunity to perform further study on
this measure. The results of this analysis
could provide the necessary data to
meet NQF endorsement criteria. The
measure would calculate the percentage
of home health patients who receive the
Shingles vaccine, and collect the
number of patients who did not receive
the vaccine.
Numerator: Equals the total number of
Medicare beneficiaries aged 60 years
and over who report having ever
received herpes zoster vaccine (shingles
vaccine) during the home health
episode of care.
Denominator: Equals the total number
of Medicare beneficiaries aged 60 years
and over receiving services from the
HHA.
The Food and Drug Administration
(FDA) has approved the use of herpes
zoster vaccine in adults age 50 and
older. In addition, the Advisory
Committee on Immunization Practices
(ACIP) currently recommends that
herpes zoster vaccine be routinely
administered to adults, age 60 years and
older.51 In 2013, 24.2 percent of adults
60 years and older reported receiving
herpes zoster vaccine to prevent
shingles, an increase from the 20.1
percent in 2012,52 yet below the targets
workers on mortality of elderly people in long-term
care: A randomized controlled trial. Lancet 2000;
355:93–97.
50 For detailed information on Shingles
incidences and known complications associated
with this condition see CDC information available
at https://www.cdc.gov/shingles/about/
overview.html.
51 CDC. Morbidity and Mortality Weekly Report
2011; 60(44):1528.
52 CDC. Morbidity and Mortality Weekly Report
2015; 64(04):95–102.
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recommended in the HHS Healthy
People 2020 initiative.53
The incidence of herpes zoster
outbreak increases as people age, with a
significant increase after age 50. Older
people are more likely to experience the
severe nerve pain known as postherpetic neuralgia (PHN),54 the primary
acute symptom of shingles infection, as
well as non-pain complications,
hospitalizations,55 and interference with
activities of daily living.56 Studies have
shown for adults aged 60 years or older
the vaccine’s efficacy rate for the
prevention of herpes zoster is 51.3
percent and 66.5 percent for the
prevention of PHN for up to 4.9 years
after vaccination.57 The Short-Term
Persistence Sub study (STPS) followed
patients 4 to 7 years after vaccination
and found a vaccine efficacy of 39.6
percent for the prevention of herpes
zoster and 60.1 percent for the
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51 CDC. Morbidity and Mortality Weekly Report
2011; 60(44):1528.
52 CDC. Morbidity and Mortality Weekly Report
2015; 64(04):95–102.
53 Healthy People 2020: Objectives and targets for
immunization and infectious diseases. Available at
https://www.healthypeople.gov/2020/topicsobjectives/topic/immunization-and-infectiousdiseases/objectives.
54 Yawn B.P., Saddier P., Wollen P.C., St Sauvier
J.L., Kurland M.J., Sy L.S. A population-based study
of the incidence and complication rate of herpes
zoster before zoster vaccine introduction. Mayo
Clinic Proc 2007; 82:1341–9.
55 Lin F., Hadler J.L. Epidemiology of primary
varicella and herpes zoster hospitalizations: The
pre-varicella vaccine era. J Infect Dis 2000;
181:1897–905.
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prevention of PHN.58 The majority of
patients reporting PHN are over age 70;
vaccination of this older population
would prevent most cases, followed by
vaccination at age 60 and then age 50.
Studying this measure in the home
health setting presents an ideal
opportunity to address a population at
risk which would benefit greatly from
this vaccination strategy. For example,
receiving the vaccine will often reduce
the course and severity of the disease
and reduce the risk of post herpetic
neuralgia.
Information on the above numerator
and denominator would be reported by
HHAs through the HHVBP web-based
platform, in addition to other
information related to this measure as
the Secretary deems appropriate. We
welcome public comments on this
measure’s proposed adoption under the
HHVBP model.
6. HHVBP Model’s Four Classifications
As previously stated, the quality
measures that we are proposing to use
in the performance years are aligned
with the six NQS domains: Patient and
Caregiver-centered experience and
outcomes; Clinical quality of care; Care
coordination; Population Health;
Efficiency and cost reduction; and,
Safety (see Figure 6).
56 Schmader K.E., Johnson G.R., Saddier P., et al.
Effect of a zoster vaccine on herpes zoster-related
interference with functional status and healthrelated quality-of-life measures in older adults. J
Am Geriatr Soc 2010; 58:1634–41.
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We propose to filter these NQS
domains and the proposed HHVBP
quality measures into four
classifications to align directly with the
measure weighting utilized in
calculating payment adjustments. The
four HHVBP classifications we are
proposing are: Clinical Quality of Care,
Outcome and Efficiency, Person- and
Caregiver-Centered Experience, and
New Measures reported by the HHAs.
These four classifications capture the
multi-dimensional nature of health care
provided by the HHA. These
classifications are further defined as:
• Classification I—Clinical Quality of
Care: Measures the quality of health care
services provided by eligible
professionals and paraprofessionals
within the home health environment.
• Classification II—Outcome and
Efficiency: Outcomes measure the end
result of care provided to the
beneficiary. Efficiencies measure
maximizing quality and minimizing use
of resources.
• Classification III—Person- and
Caregiver-Centered Experience:
Measures the beneficiary and their
caregivers’ experience of care.
• Classification IV—New Measures:
Measures not currently reported by
Medicare-certified HHAs to CMS, but
that may fill gaps in the NQS Domains
not completely covered by existing
measures in the home health setting.
We seek public comment on our
proposed measure classifications for the
HHVBP model.
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7. Weighting
We propose that measures within
each classification will be weighted the
same for the purposes of payment
adjustment. We are weighting at the
individual measure level and not the
classification level. Classifications are
for organizational purposes only. We
selected this approach since we did not
want any one measure within a
classification to be more important than
another measure. This approach ensures
that a measure’s weight will remain the
same even if some of the measures
within a classification group have no
available data. Weighting will be reexamined in subsequent years of the
model and be subject to the rulemaking
process.
We welcome public comments on this
proposed weighting methodology under
the HHVBP model.
F. Performance Scoring Methodology
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1. Performance Calculation Parameters
The methodology we are proposing
for assessing each HHA’s total annual
performance is based on a score
calculated using the proposed starter set
of quality measures that apply to the
HHA (based on a minimum number of
cases, as discussed herein). The
methodology we propose would provide
an assessment on a quarterly basis for
each HHA and would result in an
annual distribution of value-based
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payment adjustments among HHAs so
that HHAs achieving the highest
performance scores would receive the
largest upward payment adjustment.
The methodology we are proposing
includes three primary features:
• The HHA’s Total Performance Score
(TPS) would be determined using the
higher of an HHA’s achievement or
improvement score for each measure;
• All measures in the Clinical Quality
of Care, Outcome and Efficiency, and
Person and Caregiver-Centered
Experience classifications will have
equal weight and will account for 90
percent of the TPS (see section 2 below)
regardless of the number of measures in
the three classifications. Points for New
Measures are awarded for submission of
data on the New Measures via the
HHVBP web-based platform, and
withheld if data is not submitted. Data
reporting for each New Measure will
have equal weight and will account for
10 percent of the TPS for the first
performance year; and,
• The HHA performance score would
reflect all of the measures that apply to
the HHA based on a minimum number
of cases defined below.
2. Considerations for Calculating the
Total Performance Score
In § 484.320 we propose to calculate
the TPS by adding together points
awarded to Medicare-certified HHAs on
the starter set of measures, including the
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New Measures. We considered several
factors when developing the proposed
performance scoring methodology for
the HHVBP model. First, we believe it
is important that the performance
scoring methodology be straightforward
and transparent to HHAs, patients, and
other stakeholders. HHAs must be able
to clearly understand performance
scoring methods and performance
expectations to maximize quality
improvement efforts. The public must
understand performance score methods
to utilize publicly-reported information
when choosing HHAs.
Second, we believe the proposed
performance scoring methodology for
the HHVBP model should be aligned
appropriately with the quality
measurements adopted for other
Medicare value-based purchasing
programs including those introduced in
the hospital and skilled nursing home
settings. This alignment would facilitate
the public’s understanding of quality
measurement information disseminated
in these programs and foster more
informed consumer decision-making
about their health care choices.
Third, we believe that differences in
performance scores must reflect true
differences in quality performance. To
ensure that this point is addressed in
the proposed performance scoring
methodology for the HHVBP model, we
assessed quantitative characteristics of
the measures, including the current
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state of measure development, number
of measures, and the number and
grouping of measure classifications.
Fourth, we believe that both quality
achievement and improvement must be
measured appropriately in the
performance scoring methodology for
the HHVBP model. The proposed
methodology specifies that performance
scores under the HHVBP model are
calculated utilizing the higher of
achievement or improvement scores for
each measure. The impact of
performance scores utilizing
achievement and improvement on
HHAs’ behavior and the resulting
payment implications was also
considered. Using the higher of
achievement or improvement scores
allows the model to recognize HHAs
that have made great improvements,
though their measured performance
score may still be relatively lower in
comparison to other HHAs.
Fifth, through careful measure
selection we intend to eliminate, or at
least control for, unintended
consequences such as undermining
better outcomes to patients or rewarding
inappropriate care. As discussed above,
when available, NQF endorsed
measures would be used. In addition we
propose to adopt measures that we
believe are closely associated with
better outcomes in the HHA setting in
order to incentivize genuine
improvements and sustain positive
achievement while retaining the
integrity of the model.
Sixth, we intend to ensure the model
utilizes the most currently available
data to assess HHA performance. We
recognize that these data would not be
available instantaneously due to the
time required to process quality
measurement information accurately;
however, we intend to make every effort
to process data in the timeliest fashion.
Using more current data would result in
a more accurate performance score
while recognizing that HHAs need time
to report measure data.
3. Additional Considerations for the
Proposed HHVBP Total Performance
Scores
Many of the key elements of the
proposed HHVBP model performance
scoring methodology would be aligned
with the scoring methodology of the
Hospital Value-Based Purchasing
Program (HVBP) in order to leverage the
rigorous analysis and review
underpinning that Program’s approach
to value-based purchasing in the
hospital sector. The HVBP Program
includes as one of its core elements the
scoring methodology included in the
2007 Report to Congress ‘‘Plan to
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Implement a Medicare Hospital ValueBased Purchasing Program’’ (hereinafter
referred to as ‘‘The 2007 HVBP
Report’’).59 The 2007 HVBP Report
describes a Performance Assessment
Model with core elements that can
easily be replicated for other valuebased purchasing programs or models,
including the HHVBP.
In the HVBP Program, the
Performance Assessment Model
aggregates points on the individual
quality measures across different quality
measurement domains to calculate a
hospital’s TPS. Similarly, the proposed
HHVBP model would aggregate points
on individual measures across four
measure classifications derived from the
6 CMS/NQS domains as described
above (see Figure 3) to calculate the
HHA’s TPS. In addition, the proposed
HHVBP payment methodology is also
aligned with the HVBP Program with
respect to evaluating an HHA’s
performance on each quality measure
based on the higher of an achievement
or improvement score in the
performance period. The proposed
model is not only designed to provide
incentives for HHAs to provide the
highest level of quality, but also to
provide incentives for HHAs to improve
the care they provide to Medicare
beneficiaries. By rewarding HHAs that
provide high quality and/or high
improvement, we believe the proposed
HHVBP model would ensure that all
HHAs would be incentivized to commit
the resources necessary to make the
organizational changes that would result
in better quality.
Under the proposed model an HHA
would be awarded points only for
‘‘applicable measures.’’ An ‘‘applicable
measure’’ is one for which the HHA has
provided 20 home health episodes of
care per year. Points awarded for each
applicable measure would be aggregated
to generate a TPS. As described in the
benchmark section below, HHAs would
have the opportunity to receive 0 to 10
points for each measure in the Clinical
Quality of Care, Outcome and
Efficiency, and Person and CaregiverCentered Experience classifications.
Each measure would have equal weight
regardless of the total number of
measures in each of the first three
classifications. In contrast, we propose
to score the New Measures in a different
way. For each New Measure, HHAs
would receive 10 points if they report
the New Measure or 0 points if they do
not report the measure during the
57 Schmader K.E., Johnson G.R., Saddier P., et al.
Effect of a zoster vaccine on herpes zoster0-related
interference with functional status and healthrelated quality-of-life measures in older adults. J
Am Geriatr Soc 2010; 58:1634–41.
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performance year. In total, the New
Measures would account for 10 percent
of the TPS regardless of the number of
measures applied to an HHA in the
other three classifications.
We propose to calculate the TPS for
the HHVBP methodology similarly to
the TPS calculation that has been
finalized under the HVBP program. The
performance scoring methodology for
the HHVBP model would include
determining performance standards
(benchmarks and thresholds) using the
2015 baseline period performance year’s
quality measure data, scoring HHAs
based on their achievement and/or
improvement with respect to those
performance standards, and weighting
each of the classifications by the
number of measures employed, as
presented in further detail in Section G
below.
4. Setting Performance Benchmarks and
Thresholds
For scoring HHAs’ performance on
measures in the proposed Clinical
Quality of Care, Outcome and
Efficiency, and Person and CaregiverCentered Experience classifications, we
propose that the HHVBP model would
adopt an approach using several key
elements from the scoring methodology
set forth in the 2007 HVBP Report and
the successfully implemented HVBP
Program 60 including allocating points
based on achievement or improvement,
and calculating those points based on
industry benchmarks and thresholds.
In determining the achievement
points for each measure, HHAs would
receive points along an achievement
range, which is a scale between the
achievement threshold and a
benchmark. We propose to calculate the
achievement threshold as the median of
all HHAs’ performance on the specified
quality measure during the baseline
period and to calculate the benchmark
as the mean of the top decile of all
HHAs’ performance on the specified
quality measure during the baseline
period. Unlike the HVBP Program that
uses a national sample, this model
would calculate both the achievement
threshold and the benchmark separately
for each selected state and for HHA
cohort size. Under this proposed
methodology, we would have
benchmarks and achievement
58 Schmader K.E., Oxman M.N., Levin M.J.,
Johnson G., Zhang J.H., Betts R., Morrison V.A.,
Gelb L., Guatelli J.C., Harbecke R., Pachucki C.,
Keay S., Menzies B., Griffin M.R., Kauffman C.,
Marques A., Toney J., Keller P.M., LI,X, Chan L.S.F.,
Annumziato P. Persistence of the Efficacy of Zoster
Vaccine in the Shingles Prevention Study and the
Short Term Persistence Substudy. Clinical
Infectious Disease 2012; 55:1320–8.
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between an HHA’s performance during
the performance period and the baseline
period. In addition, as in the
achievement calculation, the benchmark
and threshold would be calculated
separately for each state and for HHA
cohort size to ensure that HHAs would
only be competing with those HHAs in
their state and their size cohort.
Grouping HHAs by state and size is
another way that the HHVBP payment
methodology differs from the HVBP.
All achievement points would be
rounded up or down to the nearest point
(for example, an achievement score of
4.555 would be rounded to 5). HHAs
would receive an achievement score as
follows:
• An HHA with performance equal to
or higher than the benchmark would
receive the maximum of 10 points for
achievement.
• An HHA with performance equal to
or greater than the achievement
threshold (but below the benchmark)
would receive 1–9 points for
achievement, by applying the formula
above.
• An HHA with performance less
than the achievement threshold would
receive 0 points for achievement.
We welcome public comment on this
proposed methodology for scoring
HHAs on achievement under the
proposed HHVBP model.
All improvement points would be
rounded to the nearest point. If an
HHA’s performance on the measure
during the performance period was:
• Equal to or higher than the
benchmark score, the HHA would
receive an improvement score of 10
points;
• Greater than its baseline period
score but below the benchmark (within
the improvement range), the HHA
would receive an improvement score of
0–10, based on the formula above; or
• Equal to or lower than its baseline
period score on the measure, the HHA
would receive 0 points for
improvement.
We welcome public comments on this
proposed methodology for scoring
HHAs on improvement under the
proposed HHVBP model.
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5. Calculating Achievement and
Improvement Points
be based on the Performance
Assessment Model set forth in the 2007
HVBP Report and as implemented
under the HVBP Program. An HHA
would earn 0–10 points for achievement
for each measure in the Clinical Quality
of Care, Outcome and Efficiency, and
Person and Caregiver-Centered
Experience classifications based on
where its performance during the
performance period falls relative to the
achievement threshold and the
benchmark, according to the following
formula:
a. Achievement Scoring
We are proposing that achievement
scoring under the HHVBP model would
b. Improvement Scoring
In keeping with the approach used by
the HVBP program, we propose that an
HHA would earn 0–10 points based on
how much its performance during the
c. Examples of Calculating Achievement
and Improvement Scores
For illustrative purposes we present
the following examples of how the
proposed performance scoring
methodology would be applied in the
context of the proposed measures in the
proposed Clinical Quality of Care,
Outcome and Efficiency, and Person
and Caregiver-Centered Experience
classifications. These HHA examples
were selected from an empirical
database created from 2013/2014 data
from the Home Health Compare
archived data, claims data and
enrollment data to support the
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performance period improved from its
performance on each measure in the
proposed Clinical Quality of Care,
Outcome and Efficiency, and Person
and Caregiver-Centered Experience
classifications during the baseline
period. A unique improvement range for
each measure would be established for
each HHA that defines the difference
between the HHA’s baseline period
score and the same state and size level
benchmark for the measure used in the
achievement scoring calculation
described previously, according to the
following formula:
development of the HHVBP permutation
of the Performance Assessment Model,
and all performance scores are
calculated for the pneumonia measure,
with respect to the number of
individuals assessed and administered
the pneumococcal vaccine.
Figure 7 shows the scoring for HHA
‘A’, as an example. The benchmark
calculated for the pneumonia measure
in this case was 0.87 (the mean value of
the top decile in 2013), and the
achievement threshold was 0.47 (the
performance of the median or the 50th
percentile among HHAs in 2013). HHA
A’s 2014 performance rate of 0.91
during the performance period for this
measure exceeds the benchmark, so
HHA A would earn 10 (the maximum)
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thresholds for both the larger-volume
cohort and for the smaller-volume
cohort of HHAs (defined in each state
based on a baseline period and
proposed to run from January 1, 2015
through December 31, 2015). Another
way HHVBP differs from the Hospital
VBP is this model only uses 2015 as the
baseline year for the measures included
in the proposed starter set. For the
starter set used in the model, 2015 will
consistently be used as the baseline
period in order to evaluate the degree of
change that may occur over the multiple
years of the model. In determining
improvement points for each measure,
we propose that HHAs would receive
points along an improvement range,
which is a scale indicating change
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39889
Checking HHA B’s improvement score
yields the following result: Based on
HHA B’s period-to-period improvement,
from 0.21 in the baseline year to 0.70 in
the performance year, HHA B would
earn 7 points, calculated as follows: [10
* ((0.70 ¥ 0.21)/(0.87 ¥ 0.21))] ¥ 0.5
= 6.92, rounded to 7 points. Because the
higher of the achievement and
improvement scores is used, HHA B
would receive 7 points for this measure.
period is lower than the achievement
threshold of 0.47 and, as a result,
receives 0 points based on achievement.
It also receives 0 points for
improvement, because its performance
during the performance period is lower
than its performance during the baseline
period.
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Figure 7 also shows the scoring for
HHA ‘B’. As referenced below, HHA B’s
performance on this measure went from
0.21 (which was below the achievement
threshold) in the baseline period to 0.70
(which is above the achievement
threshold) in the performance period.
Applying the achievement scale, HHA B
would earn 6 points for achievement,
calculated as follows: [9 * ((0.70 ¥
0.47)/(0.87 ¥ 0.47))] + 0.5 = 5.675, and
then rounded to 6 points.
In Figure 8, HHA ‘C’ yielded a decline
in performance on the pneumonia
measure, falling from 0.57 to 0.46 (a
decline of 0.11 points). HHA C’s
performance during the performance
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points for its achievement score. The
HHA’s performance rate on a measure is
expressed as a decimal. In the
illustration, HHA A’s performance rate
of 0.91 means that 91 percent of the
applicable patients that were assessed
were given the pneumococcal vaccine.
In this case, HHA A has earned the
maximum number of 10 possible
achievement points for this measure and
thus, its improvement score is irrelevant
in the calculation.
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6. Proposed Scoring Methodology for
New Measures
The HHVBP model provides us with
the opportunity to study new quality
measures. The four New Measures that
we have proposed to adopt for the
model for PY1 would be reported
directly by the HHA and would account
for 10 percent of the TPS regardless of
the number of measures in the other
three classifications. We are proposing
that HHAs that report on these measures
would receive 10 points out of a
maximum of 10 points for each of the
4 measures in the New Measure
classification. Hence a HHA that reports
on all four measures would receive 40
points out of a maximum of 40. An HHA
would receive 0 points for each measure
that it fails to report on. If an HHA
reports on all four measures, it would
receive 40 points for the classification
and 10 points (40/40 * 10 points) would
be added to its TPS because the New
Measure classification has a maximum
weight of 10 percent. If an HHA reports
on 3 of 4 measures, it would receive 30
points of 40 points available for the
classification and 7.5 points (30/40 * 10
points) added to its TPS. If an HHA
reports on 2 of 4 measures, they would
receive 20 points of 40 points available
for the classification and 5.0 points (20/
40 * 10 points) added to their TPS. If an
HHA reports on 0 of 4 measures, they
would receive 0 points and have no
points added to their TPS. We intend to
update these measures through future
rulemaking to allow us to study newer,
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leading-edge measures as well as retire
measures that no longer require such
analysis. We request comment on this
proposed scoring methodology for new
measures.
7. Minimum Number of Cases for
Outcome and Clinical Quality Measures
While no HHA in a selected state
would be exempt from the HHVBP
model, there may be periods when an
HHA does not receive a payment
adjustment because there are not an
adequate number of episodes of care to
generate sufficient quality measure data.
The minimum threshold for an HHA to
receive a score on a given measure is 20
home health episodes of care per year
for HHAs that have been certified for at
least 6-months. If an HHA does not meet
this threshold to generate scores on five
or more of the Clinical Quality of Care,
Outcome and Efficiency, and Person
and Caregiver-Centered Experience
measures, no payment adjustment will
be made, and the Medicare-certified
HHA would be paid for HHA services in
an amount equivalent to the amount it
would have been paid under section
1895 of the Act.61
HHAs with very low volumes will
either increase their volume in later
performance years and be subject to
future payment adjustment, or the
61 HHVBP would follow the Home Health
Compare Web site policy not to report measures on
HHAs that have less than 20 observations for
statistical reasons concerning the power to detect
reliable differences in the quality of care.
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HHAs’ volume will remain very low and
the HHAs would continue to not have
their payment adjusted in future years.
Based on the most recent data available
at this time, a very small number of
HHAs are reporting on less than five of
the total number of measures included
in the Clinical Quality of Care, Outcome
and Efficiency, and Person and
Caregiver-Centered Experience
classifications and account for less than
0.5 percent of the claims made over
1,900 HHAs delivering care within the
nine proposed selected states. We
expect very little impact of very low
service volume HHAs on the model due
to the low number of low volume HHAs
and because it is unlikely that a HHA
will reduce the amount of service to
such a low level to avoid a payment
adjustment. Although these HHAs
would not be subject to payment
adjustments, they would remain in the
model and have access to the same
technical assistance as all other HHAs
in the model, and would receive quality
reports on any measures for which they
do have 20 episodes of care, and a
future opportunity to compete for
payment adjustments.
We propose the HHA’s TPS would be
based on all the Clinical Quality of Care,
Outcome and Efficiency, Person and
Caregiver-Centered Experience
measures and the New Measures that
apply to the HHA. As described above,
each measure in the Clinical Quality of
Care, Outcome and Efficiency and
Person and Caregiver-Centered
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Experience classifications would be
weighted equally. Each measure would
have an equal weight relative to the total
score of the three classifications
regardless of the number of measures
that are applicable.
As an example, HHA ‘‘A’’ has at least
20 episodes of care in a 12-month
period for only 9 quality measures out
of a possible 25 measures from three of
the four classifications (except the New
Measures). Under the proposed scoring
methodology outlined above, HHA A
would be awarded 0, 0, 3, 4, 5, 7, 7, 9,
and 10 points, respectively, for these
measures. HHA A’s total earned points
for the three classifications would be
calculated by adding together all the
points awarded to HHA A, resulting in
a total of 45 points. HHA A’s total
possible points would be calculated by
multiplying the total number of
measures for which the HHA reported
on least 20 episodes (nine) by the
maximum number of points for those
measures (10), yielding a total of 90
possible points. HHA A’s score for the
three classifications would be the total
earned points (45) divided by the total
possible points (90) multiplied by 90
because as mentioned in section E7, the
Clinical Quality of Care, Outcome and
Efficiency, and Person and CaregiverCentered Experience classifications
account for 90 percent of the TPS and
the New Measures classification
accounts for 10 percent of the TPS,
which yields a result of 45. In this
example, HHAs also reported all four
numbers and would receive the full 10
points for the new measure. As a result,
the TPS for HHA A would be 55 (45
plus 10). In addition, as specified in
Section E:7—Weighting, all measures
have equal weights regardless of their
classification (except for New Measures)
and the total earned points for the three
classifications can be calculated by
adding the points awarded for each such
measure together. We seek public
comment on our proposal of the
minimum number of cases for outcome
and clinical quality measures.
asabaliauskas on DSK5VPTVN1PROD with PROPOSALS
G. The Payment Adjustment
Methodology
We propose to codify at 42 CFR
484.330 a methodology for applying
value-based payment adjustments to
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home health services under the HHVBP
model. Payment adjustments would be
made to the HH PPS final claim
payment amount as calculated in
accordance with § 484.205 using a linear
exchange function (LEF) similar to the
methodology utilized by the HVBP
Program. The LEF is used to translate an
HHA’s TPS into a percentage of the
value-based payment adjustment earned
by each HHA under the HHVBP model.
The LEF was identified by the HVBP
Program as the simplest and most
straightforward option to provide the
same marginal incentives to all
hospitals, and we believe the same to be
true for HHAs. We propose the
function’s intercept at zero percent,
meaning those HHAs that have a TPS
that is average in relationship to other
HHAs in their cohort (a zero percent),
would not receive any payment
adjustment. Payment adjustments for
each HHA with a score above zero
percent would be determined by the
slope of the LEF. In addition we propose
to set the slope of the LEF for the first
performance year, CY 2016, so that the
estimated aggregate value-based
payment adjustments for CY 2016 are
equal to 5 percent of the estimated
aggregate base operating episode
payment amount for CY 2018. The
estimated aggregate base operating
episode payment amount is the total
amount of episode payments made to all
the HHAs by Medicare in each
individual state in the larger- and
smaller-volume cohorts respectively (we
are proposing nine states, which would
create 18 separate aggregate base
operating episode payment amounts).
Figure 9 provides an example of how
the LEF is calculated and how it is
applied to calculate the percentage
payment adjustment to a HHA’s TPS.
For this example, we applied the 8
percent payment adjustment level that
is proposed for the final two years of the
HHVBP model. The proposed rate for
the payment adjustments for other years
would be proportionally less.
Step #1 involves the calculation of the
‘Prior Year Aggregate HHA Payment
Amount’ (See C2 in Figure 9) that each
HHA was paid in the prior year. From
claims data, all payments are summed
together for each HHA for CY 2015, the
year prior to the HHVBP Model.
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Step #2 involves the calculation of the
‘8 percent Payment Reduction Amount’
(C3 of Figure 9) for each HHA. The
‘Prior Year Aggregate HHA Payment
Amount’ is multiplied by the ‘8 percent
Payment Reduction Rate’. The aggregate
of the ‘8-percent Payment Reduction
Amount’ is the numerator of the LEF.
Step #3 involves the calculation of the
‘Final TPS Adjusted Reduction Amount’
(C4 of Figure 9) by multiplying the ‘8percent Payment Reduction Amount’
from Step #2 by the TPS (C1) divided
by 100. The aggregate of the ‘TPS
Adjusted Reduction Amount’ is the
denominator of the LEF.
Step #4 involves calculating the LEF
(C5 of Figure 9) by dividing the
aggregate ‘8 percent Payment Reduction
Amount’ by the aggregate ‘TPS Adjusted
Reduction Amount’.
Step #5 involves the calculation of the
‘Final TPS Adjusted Payment Amount’
(C6 of Figure 9) by multiplying the ‘TPS
Adjusted Reduction Amount’ (C4) by
the LEF (C5). This is an intermediary
value used to calculate ‘Quality
Adjusted Payment Rate’.
Step #6 involves the calculation of the
‘Quality Adjusted Payment Rate’ (C7 of
Figure 9) that the HHA would receive
instead of the 8 percent reduction in
payment. This is an intermediary step to
determining the payment adjustment
rate. For CYs 2021 and 2022, the
payment adjustment in this column
would range from 0 percent to 16
percent depending on the quality of care
provided.
Step #7 involves the calculation of the
‘Final Percent Payment Adjustment’ (C8
of Figure 9) that would be applied to the
HHA payments after the performance
period. It simply involves the CY
payment adjustment percent (in 2018, 5
percent; in 2019, 5 percent; in 2020, 6
percent; in 2021, 8 percent; and in 2022,
8 percent). In this example, we use the
maximum eight-percent (8 percent)
subtraction to the ‘Quality Adjusted
Payment Rate’. Note that the payment
adjustment percentage is capped at no
more than plus or minus 8 percent for
each respective performance period and
the payment adjustment would occur on
the final claim payment amount.
We invite public comments on this
proposed payment adjustment
methodology.
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FIGURE 9—8-PERCENT REDUCTION SAMPLE
Step 1
Step 3
Step 4
Step 5
Step 6
Step 7
TPS
Prior year
aggregate
HHA
payment *
8-Percent payment
reduction
amount
(C2*8%)
TPS adjusted
reduction
amount
(C1/100)*C3
Linear
exchange
function
(LEF)
(Sum of C3/
Sum of C4)
Final TPS
adjusted
payment
amount
(C4*C5)
Quality
adjusted
payment rate
(C6/C2)
*100
%
Final percent
payment
adjustment
+/¥
(C7–8%)
%
(C1)
HHA
Step 2
(C2)
(C3)
(C4)
(C5)
(C6)
(C7)
(C8)
............
............
............
............
............
............
............
............
38
55
22
85
50
63
74
25
$ 100,000
145,000
800,000
653,222
190,000
340,000
660,000
564,000
$ 8,000
11,600
64,000
52,258
15,200
27,200
52,800
45,120
$ 3,040
6,380
14,080
44,419
7,600
17,136
39,072
11,280
1.93
1.93
1.93
1.93
1.93
1.93
1.93
1.93
$ 5,867
12,313
27,174
85,729
14,668
33,072
75,409
21,770
5.9
8.5
3.4
13.1
7.7
9.7
11.4
3.9
¥2.1
0.5
¥4.6
5.1
¥0.3
1.7
3.4
¥4.1
Sum .......
............
........................
276,178
143,007
........................
276,002
........................
........................
HHA1
HHA2
HHA3
HHA4
HHA5
HHA6
HHA7
HHA8
asabaliauskas on DSK5VPTVN1PROD with PROPOSALS
* Example cases.
H. Preview and Period To Request
Recalculation
We are proposing to provide HHAs
two separate opportunities to review
scoring information under the HHVBP
model. First, HHAs will have the
opportunity to review their quarterly
quality reports following each quarterly
posting; second, Medicare-certified
HHAs will have the opportunity to
review their TPS and payment
adjustment calculations, and request a
recalculation if a discrepancy is
identified due to a CMS error as
described in this section. These
processes would also help educate and
inform each competing Medicarecertified HHA on the direct relation
between the payment adjustment and
performance measure scores.
The proposed model design calls for
us to inform HHA quarterly of their
performance on each of the individual
quality measures used to calculate the
TPS. We propose that HHAs will have
10 days after the quarterly reports are
provided to request a recalculation of a
measure scores if it believes there is
evidence of a discrepancy. We would
adjust the score if it is determined that
the discrepancy in the calculated
measure scores was the result of our
failure to follow measurement
calculation protocols.
In addition, the proposed model
design also calls for us to inform each
Medicare-certified HHA of the TPS and
payment adjustment amount in an
annual report. We propose that these
annual reports be provided to Medicarecertified HHAs each August prior to the
calendar year for which the payment
adjustment would be applied. Similar to
quarterly reports, HHAs will have 10
days to request a recalculation of their
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TPS and payment adjustment amount
from the date information is made
available. For both the quarterly reports
and the annual report containing the
TPS and payment adjustments,
Medicare-certified HHAs will only be
permitted to request scoring
recalculations, and must include a
specific basis for the requested
recalculation. We will not be
responsible for providing HHAs with
the underlying source data utilized to
generate performance measure scores.
Each HHA has access to this data via the
QIES system. The final TPS and
payment adjustment would then be
provided to competing Medicarecertified HHAs in a final report no later
than 60 days in advance of the payment
adjustment taking effect.
The TPS from the annual performance
report would be calculated based on the
calculation of performance measures
contained in the quarterly reports that
have already been provided and
reviewed by the HHAs. As a result, we
believe that quarterly reviews would
provide substantial opportunity to
identify and correct errors and resolve
discrepancies, thereby minimizing the
challenges to the annual performance
scores linked to payment adjustment.
As described above, a quarterly
performance report would be provided
to all Medicare-certified HHAs within
the selected states beginning with the
first quarter of CY 2016 being reported
in July 2016. We propose that HHAs
would submit recalculation requests for
both quarterly quality performance
measure reports and for the TPS and
payment adjustment reports via an
email link provided on the modelspecific Web page. The request form
would be entered by a person who has
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authority to sign on behalf of the HHA
and be submitted within 10 days of
receiving the quarterly data report or the
annual TPS and payment adjustment
report.
Requests for both quarterly report
measure score recalculations or TPS and
payment adjustment recalculations
would contain the following
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 modelspecific Web page.
Following receipt of a request for
quarterly report measure score
recalculations or a request for TPS and
payment adjustment recalculation, CMS
or its agent would:
+ 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
requested recalculation would result in
a score change altering performance
measure scores or the HHA’s TPS;
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+ If recalculation would result in a
performance measure score or TPS
change, conduct a review of quality data
and if an error is found, recalculate the
TPS using the corrected performance
data; 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.
Recalculation and subsequent
communication of the results of these
determinations would occur as soon as
administratively feasible following the
submission of requests. We request
comment on our proposed quarterly
quality report measure review, TPS
preview period, and our proposed
process for requesting recalculation of
the quarterly performance measure
scores, and the TPS and payment
adjustment. We intend to codify these
processes in regulation text in future
rulemaking.
Additionally, we will develop and
adopt an appeals mechanism under the
model through future rulemaking in
advance of the application of any
payment adjustments.
I. Evaluation
We propose to codify at 484.315(c)
that HHAs in selected states would be
required to collect and report
information to CMS necessary for the
purposes of monitoring and evaluating
this model as required by statute.62 We
plan to conduct an evaluation of the
proposed HHVBP model in accordance
with section 1115A(b)(4) of the Act,
which requires the Secretary to evaluate
each model tested by CMMI. We
consider an independent evaluation of
the model to be necessary to understand
its impacts on care quality in the home
health setting. The evaluation would be
focused primarily on understanding
how successful the model is in
achieving quality improvement as
evidenced by HHAs’ performance on
clinical care process measures, clinical
outcome measures (for example,
functional status), utilization/outcome
measures (for example, hospital
readmission rates, emergency room
visits), access to care, and patient’s
experience of care, and Medicare costs.
We also intend to examine the
likelihood of unintended consequences.
We intend to select an independent
evaluation contractor to perform this
evaluation. However, because the
procurement for the selection of the
evaluation contractor is in progress and
is subject to the finalization of the
62 See
proposed model, we cannot provide a
detailed description of the evaluation
methodology here.
We intend to use a multilevel
approach to evaluation. Here, we intend
to conduct analyses at the state, HHA,
and patient levels. Based on the state
groupings discussed in the section on
selection of Medicare certified HHAs,
we believe there are several ways in
which we can draw comparison groups
and remain open to scientifically-sound,
rigorous methods for evaluating the
effect of the model intervention.
The evaluation effort may require of
HHAs participating in the Model
additional data specifically for
evaluation purposes. Such requirements
for additional data to carry out model
evaluation would be in compliance with
42 CFR 403.1105 which, as of January
1, 2015, requires entities participating in
the testing of a model under section
1115A to collect and report such
information, including protected health
information (as defined at 45 CFR
160.103), as the Secretary determines is
necessary to monitor and evaluate the
model. We would consider all
Medicare-certified HHAs providing
services within a state selected for the
Model to be participating in the testing
of this model because the competing
HHAs would be receiving payment from
CMS under the model.63
We invite public comments on this
proposed evaluation plan.
V. Proposed Provisions of 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
1115A(b)(4) of the Act (42 U.S.C. 1315a).
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FR 67751 through 67755.
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result in payment rates under the Home
Health PPS for a year being less than
payment rates for the preceding year.
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. New section 1899B of the Act is
titled, ‘‘Standardized Post-Acute Care
(PAC) Assessment Data for Quality,
Payment, and Discharge Planning’’.
Under section 1899B(a)(1) of the Act,
certain post-acute care (PAC) providers
(defined in section 1899B(a)(2)(A) of the
Act to include 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 sets out specified
application dates for each of the
measures. The Secretary must specify
the quality, resource use, and other
measures no later than the applicable
specified application date defined in
section 1899B(a)(2)(E) of the Act.
Section 1899B(b) of the Act describes
the standardized patient assessment
data that PAC providers are required to
submit in accordance with section
1899B(b)(1) of the Act; requires the
Secretary, to the extent practicable, to
match claims data with standardized
patient assessment data in accordance
with section 1899B(b)(2) of the Act; and
requires the Secretary, as soon as
practicable, to revise or replace existing
patient assessment data to the extent
that such data duplicate or overlap with
standardized patient assessment data, in
accordance with section 1899B(b)(3) of
the Act.
Sections 1899B(c)(1) and (d)(1) of the
Act direct the Secretary to specify
measures that relate to at least five
stated quality domains and three stated
resource use and other measure
domains. Section 1899B(c)(1) of the Act
provides that the quality measures on
which PAC providers, including HHAs,
are required to submit standardized
patient assessment data and other
necessary data specified by the
Secretary must be in accordance with, at
least, the following domains:
• Functional status, cognitive
function, and changes in function and
cognitive function;
• Skin integrity and changes in skin
integrity;
• Medication reconciliation;
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• Incidence of major falls; and
• 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 (1) from a hospital or Critical
Access Hospital (CAH) to another
applicable setting, including a PAC
provider or the home of the individual,
or (2) from a PAC provider to another
applicable setting, including a different
PAC provider, hospital, CAH, or the
home of the individual.
Section 1899B(c)(2)(A) provides that,
to the extent possible, the Secretary
must require such reporting through the
use of a PAC assessment instrument and
modify the instrument as necessary to
enable such use.
Section 1899B(d)(1) of the Act
provides that the resource use and other
measures on which PAC providers,
including HHAs, are required to submit
any necessary data specified by the
Secretary, which may include
standardized assessment data in
addition to claims data, must be in
accordance with, at least, the following
domains:
• Resource use measures, including
total estimated Medicare spending per
beneficiary;
• Discharge to community; and
• Measures to reflect all-condition
risk-adjusted potentially preventable
hospital readmission rates.
Sections 1899B(c) and (d) of the Act
indicate that data satisfying the eight
measure domains in the IMPACT Act is
the minimum data reporting
requirement. Therefore, the Secretary
may specify additional measures and
additional domains.
Section 1899B(e)(1) of the Act
requires that the Secretary implement
the quality, resource use, and other
measures required under sections
1899B(c)(1) and (d)(1) of the Act in
phases consisting of measure
specification, data collection, and data
analysis; the provision of feedback
reports to PAC providers in accordance
with section 1899B(f) of the Act; and
public reporting of PAC providers’
performance on such measures in
accordance with section 1899B(g) of the
Act. Section 1899B(e)(2) of the Act
generally requires that each measure
specified by the Secretary under section
1899B of the Act be NQF-endorsed, but
authorizes an exception under which
the Secretary may select non-NQFendorsed quality measures in the case of
specified areas or medical topics
determined appropriate by the Secretary
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for which a feasible or practical measure
has not been endorsed by the NQF, as
long as due consideration is given to
measures that have been endorsed or
adopted by a consensus organization
identified by the Secretary. Section
1899B(e)(3) of the Act provides that the
pre-rulemaking process required by
section 1890A of the Act applies to
quality, resource use, and other
measures specified under sections
1899B(c)(1) and (d)(1) of the Act, but
authorizes exceptions under which the
Secretary may (1) use expedited
procedures, such as ad hoc reviews, as
necessary in the case of a measure
required with respect to data
submissions during the 1-year period
before the applicable specified
application date, or (2) alternatively,
waive section 1890A of the Act in the
case of such a measure if applying
section 1890A of the Act (including
through the use of expedited
procedures) would result in the inability
of the Secretary to satisfy any deadline
specified under section 1899B of the Act
with respect to the measure.
Section 1899B(f)(1) of the Act requires
the Secretary to provide confidential
feedback reports to PAC providers on
the performance of such PAC providers
with respect to quality, resource use,
and other measures required under
sections 1899B(c)(1) and (d)(1) of the
Act beginning 1 year after the applicable
specified application date.
Section 1899B(g) of the Act requires
the Secretary to establish procedures for
making available to the public
information regarding the performance
of individual PAC providers with
respect to quality, resource use, and
other measures required under sections
1899B(c)(1) and (d)(1) beginning not
later than 2 years after the applicable
specified application date. The
procedures must ensure, including
through a process consistent with the
process applied under section
1886(b)(3)(B)(viii)(VII) for similar
purposes, that each PAC provider has
the opportunity to review and submit
corrections to the data and information
that are to be made public with respect
to the PAC provider prior to such data
being made public.
Section 1899B(h) of the Act sets out
requirements for removing, suspending,
or adding quality, resource use, and
other measures required under sections
1899B(c)(1) and (d)(1) of the Act. In
addition, section 1899B(j) of the Act
requires the Secretary to allow for
stakeholder input, such as through town
halls, open door forums, and mailbox
submissions, before the initial
rulemaking process to implement
section 1899B of the Act.
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Section 2(c)(1) of the IMPACT Act
amended section 1895 of the Act to
address the payment consequences for
HHAs with respect to the additional
data which HHAs are required to submit
under section 1899B of the Act. These
changes include the addition of a new
section 1895(3)(B)(v)(IV), which
requires HHAs to submit the following
additional data: (1) For the year
beginning on the applicable specified
application date and subsequent years,
data on the quality, resource use, and
other measures required under sections
1899B(c)(1) and (d)(1) of the Act; and (2)
for 2019 and subsequent years, the
standardized patient assessment data
required under section 1899B(b)(1) of
the Act. Such data must be submitted in
the form and manner, and at the time,
specified by the Secretary.
As stated above, the IMPACT Act
adds a new section 1899B that imposes
new data reporting requirements for
certain post-acute care (PAC) providers,
including HHAs. Sections 1899B(c)(1)
and 1899B(d)(1) collectively require that
the Secretary specify quality measures
and resource use and other measures
with respect to certain domains not later
than the specified application date that
applies to each measure domain and
PAC provider setting. Section
1899B(a)(2)(E) delineates the specified
application dates for each measure
domain and PAC provider. The IMPACT
Act also amends other sections of the
Act, including section 1895(b)(3)(B)(v),
to require the Secretary to reduce the
otherwise applicable PPS payment to a
PAC provider that does not report the
new data in a form and manner, and at
a time, specified by the Secretary. For
HHAs, amended section 1895(b)(3)(B)(v)
would require the Secretary to reduce
the payment update for any HHA that
does not satisfactorily submit the new
required data.
Under the current HH QRP, the
general timeline and sequencing of
measure implementation occurs as
follows: Specification of measures;
proposal and finalization of measures
through notice-and-comment
rulemaking; HHA submission of data on
the adopted measures; analysis and
processing of the submitted data;
notification to HHAs regarding their
quality reporting compliance with
respect to a particular year;
consideration of any reconsideration
requests; and imposition of a payment
reduction in a particular year for failure
to satisfactorily submit data with respect
to that year. Any payment reductions
that are taken with respect to a year
begin approximately 1 year after the end
of the data submission period for that
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year and approximately 2 years after we
first adopt the measure.
To the extent that the IMPACT Act
could be interpreted to shorten this
timeline, so as to require us to reduce
HH PPS payment for failure to
satisfactorily submit data on a measure
specified under section 1899B(c)(1) or
(d)(1) of the IMPACT Act beginning
with the same year as the specified
application date for that measure, such
a timeline would not be feasible. The
current timeline discussed above
reflects operational and other practical
constraints, including the time needed
to specify and adopt valid and reliable
measures, collect the data, and
determine whether a HHA has complied
with our quality reporting requirements.
It also takes into consideration our
desire to give HHAs enough notice of
new data reporting obligations so that
they are prepared to timely start
reporting data. Therefore, we intend to
follow the same timing and sequence of
events for measures specified under
sections 1899B(c)(1) and (d)(1) of the
Act that we currently follow for other
measures specified under the HH QRP.
We intend to specify each of these
measures no later than the specified
application dates set forth in section
1899B(a)(2)(E) of the Act and propose to
adopt them consistent with the
requirements in the Act and
Administrative Procedure Act. To the
extent that we finalize a proposal to
adopt a measure for the HH QRP that
satisfies an IMPACT Act measure
domain, we intend to require HHAs to
report data on the measure for the year
that begins 2 years after the specified
application date for that measure.
Likewise, we intend to require HHAs to
begin reporting any other data
specifically required under the IMPACT
Act for the year that begins 2 years after
we adopt requirements that would
govern the submission of that data.
Lastly, on April 1, 2014, the Congress
passed the Protecting Access to
Medicare Act of 2014 (PAMA) (Pub. L.
113–93), which stated the Secretary may
not adopt ICD–10 prior to October 1,
2015. On August 4, 2014, HHS
published a final rule titled
‘‘Administrative Simplification: Change
to the Compliance Date for the
International Classification of Diseases,
10th Revision (ICD–10–CM and ICD–
10–PCS Medical Data Code Sets’’ (79 FR
45128), which announced October 1,
2015 as the new compliance date. 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. We
intended to use the OASIS–C1 to
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coincide with the original
implementation date of the ICD–10. The
approved OASIS–C1 included changes
to accommodate coding of diagnoses
using the ICD–10–CM coding set and
other important stakeholder concerns
such as updating clinical concepts, and
revised item wording and response
categories to improve item clarity. This
version included five (5) data items that
required the use of ICD–10 codes.
Since OASIS–C1 was revised to
incorporate ICD–10 coding, it is not
feasible to implement the OASIS–C1/
ICD–10 version prior to October 1, 2015,
when ICD–10 is scheduled to be
implemented. Due to this delay, we had
to ensure the collection and submission
of OASIS data continued, until ICD–10
could be implemented. Therefore, we
have made interim changes to the
OASIS–C1 data item set to allow use
with ICD–9 until ICD–10 is adopted.
The OASIS–C1/ICD–9 version was
submitted to OMB for approval until the
OASIS–C1/ICD–10 version could be
implemented. A 6-month emergency
approval was granted on October 7,
2014 and CMS subsequently applied for
an extension. The extension of the
OASIS–C1/ICD–9 version was
reapproved under OMB control number
0938–0760 with a current expiration
date of March 31, 2018. It is important
to note, that 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 planned 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. We are 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.
Information regarding the OASIS–C1
can be located at https://www.cms.gov/
Medicare/Quality-Initiatives-PatientAssessment-Instruments/
HomeHealthQualityInits/OASISC1.html. Additional information
regarding the adoption of ICD–10 can be
located at https://www.cms.gov/
Medicare/Coding/ICD10/
index.html?redirect=/icd10.
B. General Considerations Used for the
Selection of Quality Measures for the
HH QRP
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
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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, coupled with public reporting
of quality information, are critical to the
advancement of health care quality
improvement efforts.
We seek to adopt measures for the HH
QRP that promotes better, safer, and
more efficient care. Valid, reliable,
relevant quality measures are
fundamental to the effectiveness of our
quality reporting programs. Therefore,
selection of quality measures is a
priority for CMS in all of its quality
reporting programs.
The measures selected would address
the measure domains as specified in the
IMPACT Act and would be in alignment
with the CMS Quality Strategy, which is
framed using the three broad aims of the
National Quality Strategy:
• Better Care: Improve the overall
quality of care by making healthcare
more patient-centered, reliable,
accessible, and safe.
• Healthy People, Healthy
Communities: Improve the health of the
U.S. population by supporting proven
interventions to address behavioral,
social, and environmental determinants
of health in addition to delivering
higher-quality care.
• Affordable Care: Reduce the cost of
quality healthcare for individuals,
families, employers, and government.
In addition, our measure selection
activities for the HH QRP take into
consideration input we receive from the
Measure Applications Partnership
(MAP), convened by the NQF, as part of
the established CMS pre-rulemaking
process required under section 1890A of
the Act. The MAP is a public-private
partnership comprised of multistakeholder groups convened for the
primary purpose of providing input to
us on the selection of certain categories
of quality and efficiency measures, as
required by section 1890A(a)(3) of the
Social Security Act (the Act). By
February 1st of each year, the NQF must
provide that input to us. Input from the
MAP is located at https://
www.qualityforum.org/Setting_
Priorities/Partnership/Measure_
Applications_Partnership.aspx. In
addition, we take into account national
priorities, such as those established by
the National Priorities Partnership at
https://www.qualityforum.org/npp/, and
the HHS Strategic Plan at https://
www.hhs.gov/secretary/about/priorities/
priorities.html.
We initiated an Ad Hoc MAP process
for the review of the measures under
consideration for implementation in
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preparation of the measures for
adoption into the HH QRP that we must
propose through this fiscal year’s rule,
in order to begin implementing such
measures by 2017. We included under
the List of Measures under
Consideration (MUC List) a list of
measures that the Secretary must make
available to the public, as part of the
pre-rulemaking process, as described in
section 1890A(a)(2) of the Act. The MAP
Off-Cycle Measures under Consideration
for PAC–LTC Settings can be accessed
on the National Quality Forum Web site
at: https://www.qualityforum.org/map/.
The NQF MAP met in February 2015
and provided input to us as required
under section 1890A(a)(3) of the Act.
The MAP issued a pre-rulemaking
report on March 6, 2015 entitled MAP
Off-Cycle Deliberations 2015: Measures
under Consideration to Implement
Provisions of the IMPACT Act—Final
Report, which is available for download
at: https://www.qualityforum.org/
Publications/2015/03/MAP_Off-Cycle_
Deliberations_2015_-_Final_
Report.aspx. The MAP’s input for the
proposed measure is discussed in this
section.
To meet the first specified application
date applicable to HHAs under section
1899B(a)(2)(E) of the Act, which is
October 1, 2017, we have focused on
measures that:
• Correspond to a measure domain in
sections 1899B(c)(1) or (d)(1) of the Act
and are setting-agnostic: For example
falls with major injury and the
incidence of pressure ulcers;
• Are currently adopted for 1 or more
of our PAC quality reporting programs,
are already either NQF-endorsed and in
use or finalized for use, or already
previewed by the Measure Applications
Partnership (MAP) with support;
• Minimize added burden on HHAs;
• Minimize or avoid, to the extent
feasible, revisions to the existing items
in assessment tools currently in use (for
example, the OASIS); and
• Where possible, the avoidance
duplication of existing assessment
items.
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.
This process is based on a private public
partnership, and it occurs via the MAP.
The MAP is composed of
multistakeholder groups convened by
the NQF, our current contractor under
section 1890 of the Act, to provide input
on the selection of quality and
efficiency measures described in section
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1890(b)(7)(B). The NQF must convene
these stakeholders and provide us with
the stakeholders’ input on the selection
of such measures. We, in turn, must take
this input into consideration in
selecting such measures. In addition,
the Secretary must make available to the
public by December 1 of each year a list
of such measures that the Secretary is
considering under Title XVIII of the Act.
As discussed in section V.A. of this
proposed rule 1899B(e)(3) provides that
the pre-rulemaking process required by
section 1890A of the Act applies to the
measures required under section 1899B,
subject to certain exceptions for
expedited procedures or, alternatively,
waiver of section 1890A. We initiated
an ad hoc MAP process for the review
of the quality measures under
consideration for proposal, in
preparation for adoption of those quality
measures into the HH QRP that are
required by the IMPACT Act, and that
must be implemented by January 1,
2017. The List of Measures under
Consideration (MUC List) under the
IMPACT Act was made public on
February 5, 2015. Under the IMPACT
Act, these measures must be
standardized so they can be applied
across PAC settings and must
correspond to measure domains
specified in sections 1899B(c)(1) and
(d)(1) of the IMPACT Act. The MAP
reviewed each IMPACT Act-related
quality measure proposed in this
proposed rule for the HH QRP, in light
of its intended cross-setting use. We
refer to sections V.A. and V.C. of this
proposed rule for more information on
the MAP’s recommendations. The
MAP’s final report, MAP Off-Cycle
Deliberations 2015: Measures under
Consideration to Implement Provisions
of the IMPACT Act: Final Report, is
available at https://
www.qualityforum.org/Setting_
Priorities/Partnership/MAP_
Reports.aspx. As discussed in section
V.A. of this proposed rule, section
1899B(j) of the Act, requires that we
allow for stakeholder input, such as
through town halls, open door forums,
and mailbox submissions, before the
initial rulemaking process to implement
section 1899B. To meet this
requirement, we provided the following
opportunities for stakeholder input: (a)
We convened a technical expert panel
(TEP) that included stakeholder experts
and patient representatives on February
3, 2015; (b) we provided two separate
listening sessions on February 10th and
March 24, 2015; (c) we sought public
input during the February 2015 ad hoc
MAP process regarding the measures
under consideration with respect to
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IMPACT Act domains; (d) we sought
public comment as part of our measure
maintenance work; and (e) we
implemented a public mail box for the
submission of comments in January,
2015 located at PACQualityInitiative@
cms.hhs.gov. The CMS public mailbox
can be accessed on our post-acute care
quality initiatives Web site: https://
www.cms.gov/Medicare/QualityInitiatives-Patient-AssessmentInstruments/Post-Acute-Care-QualityInitiatives/IMPACT-Act-of-2014-andCross-Setting-Measures.html. Lastly, we
held a National Stakeholder Special
Open Door Forum to seek input on the
measures on February 25, 2015.
In the absence of NQF endorsement
on measures for the home health setting,
or measures that are not fully supported
by the MAP for the HH QRP, we intend
to propose for adoption measures that
most closely align with the national
priorities discussed above and for which
the MAP supports the measure concept.
Further discussion as to the importance
and high-priority status of these
measures in the HH setting is included
under each quality measure proposal in
this proposed rule. In addition, for
measures not endorsed by the NQF, we
have sought, to the extent practicable, to
adopt measures that have been endorsed
or adopted by a national consensus
organization, recommended by multistakeholder organizations, and/or
developed with the input of providers,
purchasers/payers, and other
stakeholders.
C. HH QRP Quality Measures and
Measures Under Consideration for
Future Years
In the CY 2014 HH PPS final rule, (78
FR 72256–72320), we finalized a
proposal to add two claims-based
measures to the HH QRP, and stated that
we would begin reporting the data from
these measures to HHAs beginning in
CY 2014. These claims based measures
are: (1) Rehospitalization during the first
30 days of HH; and (2) Emergency
Department Use without Hospital
Readmission during the first 30 days of
HH. In an effort to align with other
updates to Home Health Compare,
including the transition to quarterly
provider preview reports, we have made
the decision to delay the reporting of
data from these measures until July
2015 (https://www.cms.gov/Medicare/
Quality-Initiatives-Patient-AssessmentInstruments/HomeHealthQualityInits/
HHQISpotlight.html). Also in that rule,
we finalized our proposal to reduce the
number of process measures reported on
the Certification and Survey Provider
Enhanced Reporting (CASPER) reports
by eliminating the stratification by
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episode length for nine (9) process
measures. The removal of these
measures from the CASPER folders
occurred in October 2014. The CMS
Home Health Quality Initiative Web site
identifies the current HH QRP measures
located at https://www.cms.gov/
Medicare/Quality-Initiatives-PatientAssessment-Instruments/
HomeHealthQualityInits/
HHQIQualityMeasures.html. In
addition, as stated in the CY 2012 and
CY 2013 HH PPS final rules (76 FR
68575 and 77 FR 67093, respectively),
we finalized that we will also use
measures derived from Medicare claims
data to measure home health quality.
This effort ensures that providers do not
have an additional burden of reporting
quality of care measures through a
separate mechanism, and that the costs
associated with the development and
testing of a new reporting mechanism
are avoided.
(a) We are proposing one standardized
cross-setting new measure for CY 2016
to meet the requirements of the IMPACT
Act. The proposed quality measure that
addresses the domain of skin integrity
and changes in skin integrity is the
National Quality Forum (NQF)-endorsed
measure: Percent of Residents or
Patients with Pressure Ulcers That Are
New or Worsened (Short Stay) (NQF
#0678) (https://www.qualityforum.org/
QPS/0678).
The IMPACT Act requires the
specification of a quality measure to
address skin integrity and changes in
skin integrity in the home health setting
by January 1, 2017. We are proposing
the implementation of the quality
measure NQF #0678, Percent of
Residents or Patients with Pressure
Ulcers that are New or Worsened (Short
Stay) in the HH QRP as a cross-setting
quality measure to meet the
requirements of the IMPACT Act for the
CY 2018 payment determination and
subsequent years. This measure reports
the percent of patients with Stage 2
through 4 pressure ulcers that are new
or worsened since the beginning of the
episode of care.
Pressure ulcers are high-volume in
post-acute care settings and high-cost
adverse events. According to the 2014
Prevention and Treatment Guidelines
published by the National Pressure
Ulcer Advisory Panel, European
Pressure Ulcer Advisory Panel, and Pan
Pacific Pressure Injury Alliance,
pressure ulcer care is estimated to cost
approximately $11 billion annually, and
between $500 and $70,000 per
individual pressure ulcer.64 Pressure
64 National Pressure Ulcer Advisory Panel,
European Pressure Ulcer Advisory Panel and Pan
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ulcers are a serious medical condition
that result in pain, decreased quality of
life, and increased mortality in aging
populations.65 66 67 68 Pressure ulcers
typically are the result of prolonged
periods of uninterrupted pressure on the
skin, soft tissue, muscle, and bone.69 70 71
Elderly individuals are prone to a wide
range of medical conditions that
increase their risk of developing
pressure ulcers. These include impaired
mobility or sensation, malnutrition or
undernutrition, obesity, stroke, diabetes,
dementia, cognitive impairments,
circulatory diseases, dehydration, bowel
or bladder incontinence, the use of
wheelchairs, the use of medical devices,
polypharmacy, and a history of pressure
ulcers or a pressure ulcer at
admission.72 73 74 75 76 77 78 79 80 81 82
Pacific Pressure Injury Alliance. Prevention and
Treatment of Pressure Ulcers: Clinical Practice
Guideline. Emily Haesler (Ed.) Cambridge Media;
Osborne Park, Western Australia; 2014.
65 Casey, G. (2013). ‘‘Pressure ulcers reflect
quality of nursing care.’’ Nurs N Z 19(10): 20–24.
66 Gorzoni, M. L., and S. L. Pires (2011). ‘‘Deaths
in nursing homes.’’ Rev Assoc Med Bras 57(3): 327–
331.
67 Thomas, J. M., et al. (2013). ‘‘Systematic
review: health-related characteristics of elderly
hospitalized adults and nursing home residents
associated with short-term mortality.’’ J Am Geriatr
Soc 61(6): 902–911.
68 White-Chu, E. F., et al. (2011). ‘‘Pressure ulcers
in long-term care.’’ Clin Geriatr Med 27(2): 241–258.
69 Bates-Jensen BM. Quality indicators for
prevention and management of pressure ulcers in
vulnerable elders. Ann Int Med. 2001;135 (8 Part 2),
744–51.
70 Institute for Healthcare Improvement (IHI).
Relieve the pressure and reduce harm. May 21,
2007. Available from https://www.ihi.org/IHI/
Topics/PatientSafety/SafetyGeneral/
ImprovementStories/
FSRelievethePressureandReduceHarm.htm.
71 Russo CA, Steiner C, Spector W.
Hospitalizations related to pressure ulcers among
adults 18 years and older, 2006 (Healthcare Cost
and Utilization Project Statistical Brief No. 64).
December 2008. Available from https://
www.hcupus.ahrq.gov/reports/statbriefs/sb64.pdf.
72 Agency for Healthcare Research and Quality
(AHRQ). Agency news and notes: pressure ulcers
are increasing among hospital patients. January
2009. Available from https://www.ahrq.gov/
research/jan09/0109RA22.htm.=.
73 Bates-Jensen BM. Quality indicators for
prevention and management of pressure ulcers in
vulnerable elders. Ann Int Med. 2001;135 (8 Part 2),
744–51.
74 Cai, S., et al. (2013). ‘‘Obesity and pressure
ulcers among nursing home residents.’’ Med Care
51(6): 478–486.
75 Casey, G. (2013). ‘‘Pressure ulcers reflect
quality of nursing care.’’ Nurs N Z 19(10): 20–24.
76 Hurd D, Moore T, Radley D, Williams C.
Pressure ulcer prevalence and incidence across
post-acute care settings. Home Health Quality
Measures & Data Analysis Project, Report of
Findings, prepared for CMS/OCSQ, Baltimore, MD,
under Contract No. 500–2005–000181 TO 0002.
2010.
77 MacLean DS. Preventing & managing pressure
sores. Caring for the Ages. March 2003;4(3):34–7.
Available from https://www.amda.com/publications/
caring/march2003/policies.cfm.
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The IMPACT Act requires the
specification of quality measures that
are harmonized across PAC settings.
This requirement is consistent with the
NQF Steering Committee report, which
stated that to understand the impact of
pressure ulcers across settings, quality
measures addressing prevention,
incidence, and prevalence of pressure
ulcers must be harmonized and
aligned.83 NQF #0678, Percent of
Residents or Patients with Pressure
Ulcers That Are New or Worsened
(Short Stay) is NQF-endorsed and has
been successfully implemented using a
harmonized set of data elements in IRF,
LTCH, and SNF settings. A new item,
M1309 was added to the OASIS–C1/
ICD–9 version to collect data on new
and worsened pressure ulcers in home
health patients to support
harmonization with NQF #0678; data
collection for this item began January 1,
2015. A new measure, based on this
item, was included in the 2014 MUC list
and received conditional endorsement
from the National Quality Forum. That
measure was harmonized with NQF
#0678, but differed in the consideration
of unstageable pressure ulcers. In this
rule, we are proposing a HH measure
that is fully-standardized with NQF
#0678.
A TEP convened by our measure
development contractor provided input
on the technical specifications of this
quality measure, including the
feasibility of implementing the measure
across PAC settings. The TEP was
supportive of the implementation of this
measure across PAC settings and
applauded CMS’s efforts to standardize
this measure for cross-setting
development. Additionally, the NQF
MAP met on February 9, 2015 and
78 Michel, J. M., et al. (2012). ‘‘As of 2012, what
are the key predictive risk factors for pressure
ulcers? Developing French guidelines for clinical
practice.’’ Ann Phys Rehabil Med 55(7): 454–465.
79 National Pressure Ulcer Advisory Panel
(NPUAP) Board of Directors; Cuddigan J, Berlowitz
DR, Ayello EA (Eds). Pressure ulcers in America:
prevalence, incidence, and implications for the
future. An executive summary of the National
Pressure Ulcer Advisory Panel Monograph. Adv
Skin Wound Care. 2001;14(4):208–15.
80 Park-Lee E, Caffrey C. Pressure ulcers among
nursing home residents: United States, 2004 (NCHS
Data Brief No. 14). Hyattsville, MD: National Center
for Health Statistics, 2009. Available from https://
www.cdc.gov/nchs/data/databriefs/db14.htm.
81 Reddy, M. (2011). ‘‘Pressure ulcers.’’ Clin Evid
(Online) 2011.
82 Teno, J. M., et al. (2012). ‘‘Feeding tubes and
the prevention or healing of pressure ulcers.’’ Arch
Intern Med 172(9): 697–701.
83 National Quality Forum. National voluntary
consensus standards for developing a framework for
measuring quality for prevention and management
of pressure ulcers. April 2008. Available from
https://www.qualityforum.org/Projects/Pressure_
Ulcers.aspx.
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February 27, 2015 and provided input to
CMS. The MAP supported the use of
NQF #0678, Percent of Residents or
Patients with Pressure Ulcers that are
New or Worsened (Short Stay) in the
HH QRP as a cross-setting quality
measure implemented under the
IMPACT Act. More information about
the MAPs recommendations for this
measure is available at https://
www.qualityforum.org/map/.
We propose that data for the
standardized quality measure would be
collected using the OASIS–C1 with
submission through the Quality
Improvement and Evaluation System
(QIES) Assessment Submission and
Processing (ASAP) system. HHAs began
submitting data in January 2015 for the
OASIS items used to calculate NQF
#0678, the Percent of Residents, or
Patients with Pressure Ulcers That Are
New or Worsened (Short Stay), as part
of the Home Health Quality Initiative to
assess the number of new or worsened
pressure ulcers in January 2015. By
building on the existing reporting and
submission infrastructure for HHAs, we
intend to minimize the administrative
burden related to data collection and
submission for this measure under the
HH QRP. For more information on HH
reporting using the QIES ASAP system,
refer to: https://www.cms.gov/Medicare/
Quality-Initiatives-Patient-AssessmentInstruments/HomeHealthQualityInits/
HHQIOASISUserManual.html and
https://www.cms.gov/Medicare/QualityInitiatives-Patient-AssessmentInstruments/OASIS/
index.html?redirect=/oasis/.
Data collected through the OASIS–C1
would be used to calculate this quality
measure. Data items in the OASIS–C1
include M1308 (Current Number of
Unhealed Pressure Ulcers at Each Stage
or Unstageable) and M1309 (Worsening
in Pressure Ulcer Status Since SOC/
ROC). Data collected through the
OASIS–C1 would be used for risk
adjustment of this measure. We
anticipate risk adjustment items would
include, but is not limited to M1850
(Activities of Daily Living Assistance,
Transferring), and M1620 (Bowel
Incontinence Frequency). OASIS C1
items M1016 (Diagnoses Requiring
Medical or Treatment Change Within
past 14 Days), M1020 (Primary
Diagnoses) and M1022 (Other
Diagnoses) would be used to identify
patients with a diagnosis of peripheral
vascular disease, diabetes, or
malnutrition. More information about
the OASIS items is available in the
OASIS Manual https://www.cms.gov/
Medicare/Quality-Initiatives-PatientAssessment-Instruments/
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HomeHealthQualityInits/
HHQIOASISUserManual.html.
The calculation of the proposed
measure would be based on the items
M1308 (Current Number of Unhealed
Pressure Ulcers at Each Stage or
Unstageable) and M1309 (Worsening in
Pressure Ulcer Status Since SOC/ROC).
The specifications and data items for
NQF #0678, the Percent of Residents or
Patients with Pressure Ulcers that are
New or Worsened (Short Stay), are
available at https://www.cms.gov/
Medicare/Quality-Initiatives-PatientAssessment-Instruments/Post-AcuteCare-Quality-Initiatives/PAC-QualityInitiatives.html.
We invite public comment on our
proposal to adopt NQF #0678 Percent of
Residents or Patients with Pressure
Ulcers that are New or Worsened (Short
Stay) for the HH QRP to fulfill the
timeline requirements for
implementation under the IMPACT Act,
for CY2018 HH payment determination
and subsequent years.
As part of our ongoing measure
development efforts, we are considering
a future update to the numerator of the
quality measure NQF #0678, Percent of
Residents or Patients with Pressure
Ulcers that are New or Worsened (Short
Stay). This update would hold providers
accountable for the development of
unstageable pressure ulcers and
suspected deep tissue injuries (sDTIs).
Under this proposed change the
numerator of the quality measure would
be updated to include unstageable
pressure ulcers, including sDTIs that are
new/developed while the patient is
receiving home health care, as well as
Stage 1 or 2 pressure ulcers that become
unstageable due to slough or eschar
(indicating progression to a full
thickness [that is, stage 3 or 4] pressure
ulcer) after admission. This would be
consistent with the specifications of the
‘‘New and Worsened Pressure Ulcer’’
measure for HH patients presented to
the MAP on the 2014 MUC list. At this
time, we are not proposing the
implementation of this change (that is,
including sDTIs and unstageable
pressure ulcers in the numerator) in the
HH QRP, but are soliciting public
feedback on this potential area of
measure development.
Our measure development contractor
convened a cross-setting pressure ulcer
TEP that strongly recommended that
CMS hold providers accountable for the
development of new unstageable
pressure ulcers and sDTIs by including
these pressure ulcers in the numerator
of the quality measure. Although the
TEP acknowledged that unstageable
pressure ulcers and sDTIs cannot and
should not be assigned a numeric stage,
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panel members recommended that these
be included in the numerator of NQF
#0678, the Percent of Residents, or
Patients with Pressure Ulcers That Are
New or Worsened (Short Stay), as a new
pressure ulcer if developed during a
home health episode. The TEP also
recommended that a Stage 1 or 2
pressure ulcer that becomes unstageable
due to slough or eschar should be
considered worsened because the
presence of slough or eschar indicates a
full thickness (equivalent to Stage 3 or
4) wound.84 85 These recommendations
were supported by technical and
clinical advisors and the National
Pressure Ulcer Advisory Panel.86
Additionally, exploratory data analysis
conducted by our measure development
contractor suggests that the addition of
unstageable pressure ulcers, including
sDTIs, would increase the observed
incidence of new or worsened pressure
ulcers at the agency level and may
improve the ability of the quality
measure to discriminate between poorand high-performing facilities.
In addition, we are also considering
whether body mass index (BMI) should
be used as a covariate for risk-adjusting
NQF #0678 in the home health setting,
as is done in other post-acute care
settings. We invite public feedback to
inform our direction to include
unstageable pressure ulcers and sDTIs
in the numerator of the quality measure
NQF #0678 Percent of Residents or
Patients with Pressure Ulcers that are
New or Worsened (Short Stay), as well
as on the possible collection of height
84 Schwartz, M., Nguyen, K.H., Swinson Evans,
T.M., Ignaczak, M.K., Thaker, S., and Bernard, S.L.:
Development of a Cross-Setting Quality Measure for
Pressure Ulcers: OY2 Information Gathering, Final
Report. Centers for Medicare & Medicaid Services,
November 2013. Available: https://www.cms.gov/
Medicare/Quality-Initiatives-Patient-AssessmentInstruments/Post-Acute-Care-Quality-Initiatives/
Downloads/Development-of-a-Cross-SettingQuality-Measure-for-Pressure-Ulcers-InformationGathering-Final-Report.pdf
85 Schwartz, M., Ignaczak, M.K., Swinson Evans,
T.M., Thaker, S., and Smith, L.: The Development
of a Cross-Setting Pressure Ulcer Quality Measure:
Summary Report on November 15, 2013, Technical
Expert Panel Follow-Up Webinar. Centers for
Medicare & Medicaid Services, January 2014.
Available: https://www.cms.gov/Medicare/QualityInitiatives-Patient-Assessment-Instruments/PostAcute-Care-Quality-Initiatives/Downloads/
Development-of-a-Cross-Setting-Pressure-UlcerQuality-Measure-Summary-Report-on-November15-2013-Technical-Expert-Pa.pdf
86 Schwartz, M., Nguyen, K.H., Swinson Evans,
T.M., Ignaczak, M.K., Thaker, S., and Bernard, S.L.:
Development of a Cross-Setting Quality Measure for
Pressure Ulcers: OY2 Information Gathering, Final
Report. Centers for Medicare & Medicaid Services,
November 2013. Available: https://www.cms.gov/
Medicare/Quality-Initiatives-Patient-AssessmentInstruments/Post-Acute-Care-Quality-Initiatives/
Downloads/Development-of-a-Cross-SettingQuality-Measure-for-Pressure-Ulcers-InformationGathering-Final-Report.pdf
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and weight data for risk-adjustment, as
part of our future measure development
efforts.
(b) We have also identified four
future, cross-setting measure constructs
to potentially meet requirements of the
IMPACT Act domains of: (1) All-
condition risk-adjusted potentially
preventable hospital readmission rates;
(2) resource use, including total
estimated Medicare spending per
beneficiary; (3) discharge to community;
and (4) medication reconciliation. These
39899
are shown in Table 22; we would like
to solicit public feedback to inform
future measure development of these
constructs as it relates to meeting the
IMPACT Act requirements in these
areas.
TABLE 22—FUTURE CROSS-SETTING MEASURE CONSTRUCTS UNDER CONSIDERATION TO MEET IMPACT ACT
REQUIREMENTS
[Home Health Timeline for Implementation—January 1, 2017]
IMPACT Act domain
Measures to reflect all-condition risk-adjusted potentially preventable hospital readmission rates
Measures ...................................................
Application of (NQF #2510): Skilled Nursing Facility 30-Day All-Cause Readmission Measure
(SNFRM) CMS is the steward.
Application of the LTCH/IRF All-Cause Unplanned Readmission Measure for 30 Days Post Discharge from LTCHs/IRFs.
Resource Use, including total estimated Medicare spending per beneficiary.
Payment Standardized Medicare Spending Per Beneficiary (MSPB).
Discharge to community.
Percentage residents/patients at discharge assessment, who discharged to a higher level of care
versus to the community.
Medication Reconciliation.
Percent of patients for whom any needed medication review actions were completed.
IMPACT Act Domain .................................
Measure .....................................................
IMPACT Act Domain .................................
Measure .....................................................
IMPACT Act Domain .................................
Measure .....................................................
(c) We are working with our measure
development and maintenance
contractor to identify setting-specific
measure concepts for future
implementation in the HH QRP that
align with or complement current
measures and new measures to meet
domains specified in the IMPACT Act.
In identifying priority areas for future
measure enhancement and
development, we take into
consideration results of environmental
scans and resulting gaps analysis for
relevant home health quality measure
constructs, along with input from
numerous stakeholders, including the
Measures Application Partnership
(MAP), the Medicare Payment Advisory
Commission (MedPAC), Technical
Expert Panels, and national priorities,
such as those established by the
National Priorities Partnership, the HHS
Strategic Plan, the National Strategy for
Quality Improvement in Healthcare, and
the CMS Quality Strategy. Based on
input from stakeholders, CMS has
identified several high priority concept
areas for future measure development in
Table 23.
TABLE 23—FUTURE SETTING-SPECIFIC MEASURE CONSTRUCTS UNDER CONSIDERATION
National quality strategy domain
Measure construct
Safety .....................................................................
Falls risk composite process measure: Percentage of home health patients who were assessed for falls risk and whose care plan reflects the assessment, and which was implemented appropriately.
Nutrition assessment composite measure: Percentage of home health patients who were assessed for nutrition risk with a validated tool and whose care plan reflects the assessment,
and which was implemented appropriately.
Improvement in Dyspnea in Patients with a Primary Diagnosis of Congestive Heart Failure
(CHF), Chronic Obstructive Pulmonary Disease (COPD), and/or Asthma: Percentage of
home health episodes of care during which a patient with a primary diagnosis of CHF,
asthma and/or COPD became less short of breath or dyspneic.
Improvement in Patient-Reported Interference due to Pain: Percent of home health patients
whose self-reported level of pain interference on the Patient-Reported Objective Measurement Information System (PROMIS) tool improved.
Improvement in Patient-Reported Pain Intensity: Percent of home health patients whose selfreported level of pain severity on the PROMIS tool improved.
Improvement in Patient-Reported Fatigue: Percent of home health patients whose self-reported level of fatigue on the PROMIS tool improved.
Stabilization in 3 or more Activities of Daily Living (ADLs): Percent of home health patients
whose functional scores remain the same between admission and discharge for at least 3
ADLs.
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Effective Prevention and Treatment ......................
These measure concepts are under
development, and details regarding
measure definitions, data sources, data
collection approaches, and timeline for
implementation would be
communicated in future rulemaking. We
invite feedback about these seven high
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priority concept areas for future
measure development.
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D. 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 must 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 do not need to submit OASIS
data for those patients who are excluded
from the OASIS submission
requirements. As described in the
December 23, 2005 Medicare and
Medicaid Programs: Reporting Outcome
and Assessment Information Set Data as
Part of the Conditions of Participation
for Home Health Agencies final rule (70
FR 76202), we defined the exclusion as
those patients:
• Receiving only non-skilled services;
• For whom neither Medicare nor
Medicaid is paying for HH care (patient
receiving care under a Medicare or
Medicaid Managed Care Plan are not
excluded from the OASIS reporting
requirement);
• Receiving pre- or post-partum
services; or
• Under the age of 18 years.
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 do not affect the HHAs’ reporting
responsibilities as announced 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).
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2. Home Health Quality Reporting
Program Requirements for CY 2016
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 1st of the
calendar year 2 years prior to the
calendar year of the Annual Payment
Update (APU) effective date and ending
June 30th 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
data to the Secretary in accordance with
subclause (II) with respect to such a
year. This pay-for-reporting requirement
was implemented on January 1, 2007. In
the CY 2015 HH PPS Final rule (79 FR
38387), we finalized a proposal to
define the quantity of OASIS
assessments each HHA must submit to
meet the pay-for-reporting requirement.
We believe that defining a more
explicit performance requirement for
the submission of OASIS data by HHAs
would better meet section 5201(c)(2) of
the Deficit Reduction Act of 2005
(DRA), which requires that each home
health agency shall submit to the
Secretary such data that the Secretary
determines are appropriate for the
measurement of health care quality.
Such data shall be submitted in a form
and manner, and at a time, specified by
the Secretary for purposes of this clause.
In the CY 2015 HH PPS Final rule (79
FR 38387), we reported information on
a study performed by the Department of
Health & Human Services, Office of the
Inspector General (OIG) in February
2012 to: (1) Determine the extent to
which HHAs met federal reporting
requirements for the OASIS data; (2) to
determine the extent to which states met
federal reporting requirements for
OASIS data; and (3) to determine the
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extent to which CMS was overseeing the
accuracy and completeness of OASIS
data submitted by HHAs. Based on the
OIG report we proposed a performance
requirement for submission of OASIS
quality data, which would be responsive
to the recommendations of the OIG.
In response to these requirements and
the OIG report, we designed a pay-forreporting 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. However, it was
determined that there are several
scenarios that could meet this matching
assessment requirement of the new payfor-reporting performance requirement.
These scenarios or quality assessments
are defined as assessments that create a
quality episode of care during the
reporting period or could create a
quality episode if the reporting period
were expanded to an earlier reporting
period or into the next reporting period.
Seven types of assessments submitted
by an HHA fit this definition of a quality
assessment. These are:
1. A Start of Care (SOC; M0100 = ‘01’)
or Resumption of Care (ROC; M0100 =
‘03’) assessment that can be matched to
an End of Care (EOC; M0100 = ‘06’, ‘07’,
‘08’, or ‘09’) assessment. These SOC/
ROC assessments are the first
assessment in the pair of assessments
that create a standard quality of care
episode describe in the previous
paragraph.
2. An End of Care (EOC) assessment
that can be matched to a Start of Care
(SOC) or Resumption of Care (ROC)
assessment. These EOC assessments are
the second assessment in the pair of
assessments that create a standard
quality of care episode describe in the
previous paragraph.
3. A SOC/ROC assessment that could
begin an episode of care, but the
assessment occurs in the last 60 days of
the performance period. This is labeled
as a Late SOC/ROC quality assessment.
The assumption is that the EOC
assessment will occur in the next
reporting period.
4. An EOC assessment that could end
an episode of care that began in the
previous reporting period, (that is, an
EOC that occurs in the first 60 days of
the performance period). This is labeled
as an Early EOC quality assessment. The
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7. A SOC/ROC assessment that is part
of a known one-visit episode. This is
labeled as a One-Visit episode quality
assessment. This determination is made
by consulting HH claims data.
SOC, ROC, and EOC assessments that
do not meet any of these definitions are
labeled as Non-Quality assessments.
Follow-up assessments (that is, where
the M0100 Reason for Assessment = ‘04’
or ‘05’) are considered Neutral
assessments and do not count toward or
against the pay-for-reporting
performance requirement.
Compliance with this performance
requirement can be measured through
the use of an uncomplicated
mathematical formula. This pay-forreporting performance requirement
metric has been titled as the ‘‘Quality
Assessments Only’’ (QAO) formula
because only those OASIS assessments
that contribute, or could contribute, to
creating a quality episode of care are
included in the computation.
The formula based on this definition
is as follows:
Our ultimate goal is to require all
HHAs to achieve a pay-for-reporting
performance requirement compliance
rate of 90 percent or more, as calculated
using the QAO metric illustrated above.
In the CY 2015 HH PPS final rule (79
FR 66074), we proposed implementing
a pay-for-reporting performance
requirement over a three-year period.
After consideration of the public
comments received, we adopted as final
our proposal to establish a pay-forreporting performance requirement for
assessments submitted on or after July 1,
2015 and before June 30, 2016 with
appropriate start of care dates, HHAs
must score at least 70 percent on the
QAO metric of pay-for-reporting
performance requirement or be subject
to a 2 percentage point reduction to
their market basket update for CY 2017.
HHAs have been statutorily required
to report OASIS for a number of years
and therefore should have many years of
experience with the collection of OASIS
data and transmission of this data to
CMS. Given the length of time that
HHAs have been mandated to report
OASIS data and based on preliminary
analyses that indicate that the majority
of HHAs are already achieving the target
goal of 90 percent on the QAO metric,
we believe that HHAs would adapt
quickly to the implementation of the
pay-for-reporting performance
requirement, if phased in over a threeyear period.
In the CY2015 rule, we did not
finalize a proposal to increase the
reporting requirement in 10 percent
increments over a two-year period until
the maximum rate of 90 percent is
reached, but instead proposed to
analyze historical data to set the
reporting requirements. To set the
threshold for the 2nd year, we analyzed
the most recently available data, from
2013 and 2014, to make a determination
about what the pay-for-reporting
performance requirement should be.
Specifically, we reviewed OASIS data
from this time period simulating the
pay-for-reporting performance 70
percent submission requirement to
determine the hypothetical performance
of each HHA as if the pay-for-reporting
performance requirement were in effect
during the reporting period preceding
its implementation. This analysis
indicated a nominal increase of 10
percent each year would provide the
greatest opportunity for successful
implementation versus an increase of 20
percent from year 1 to year 2.
Based on this analysis, we propose to
set the performance threshold at 80
percent for the reporting period from
July 1, 2016 through June 30, 2017. For
the reporting period from July 1, 2017
through June 30, 2018 and thereafter, we
propose the performance threshold
would be 90 percent.
We provided a report to each HHA of
their hypothetical performance under
the pay-for-reporting performance
requirement during the 2014–2015 preimplementation reporting period in June
2015. On January 1, 2015, the data
submission process for OASIS
converted from the current state-based
OASIS submission system to a new
national OASIS submission system
known as the Assessment Submission
and Processing (ASAP) System. On July
1, 2015, when the pay-for-reporting
performance requirement of 70 percent
goes into effect, providers would be
required to submit their OASIS
assessment data into the ASAP system.
Successful submission of an OASIS
assessment would consist of the
submission of the data into the ASAP
system with a receipt of no fatal error
messages. Error messages received
during submission can be an indication
of a problem that occurred during the
submission process and could also be an
indication that the OASIS assessment
was rejected. Successful submission can
be verified by ascertaining that the
submitted assessment data resides in the
national database after the assessment
has met all of the quality standards for
completeness and accuracy during the
submission process. Should one or more
OASIS assessments submitted by a HHA
be rejected due to an IT/servers issue
caused by CMS, we may, at our
discretion, excuse the non-submission
of OASIS data. We anticipate that such
a scenario would rarely, if ever, occur.
In the event that a HHA believes, they
were unable to submit OASIS
assessments due to an IT/server issue on
the part of CMS, the HHA should be
prepared to provide any documentation
or proof available, which demonstrates
that no fault on their part contributed to
the failure of the OASIS records to
transmit to CMS.
The initial performance period for the
pay-for-reporting performance
requirement would be July 1, 2015
through June 30, 2016. Prior to and
during this performance period, we
have scheduled Open Door Forums and
webinars to educate HHA personnel as
needed about the pay-for-reporting
performance requirement program and
the pay-for- reporting performance QAO
metric, and distributed individual
provider preview reports. Additionally,
OASIS Education Coordinators (OECs)
would be trained to provide state-level
instruction on this program and metric.
We have already posted a report, which
provides a detailed explanation of the
methodology for this pay-for-reporting
QAO methodology. To view this report,
go to: https://www.cms.gov/Medicare/
Quality-Initiatives-Patient-Assessment-
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assumption is that the matching SOC/
ROC assessment occurred in the
previous reporting period.
5. A SOC/ROC assessment that is
followed by one or more follow-up
assessments, the last of which occurs in
the last 60 days of the performance
period. This is labeled as an SOC/ROC
Pseudo Episode quality assessment.
6. An EOC assessment is preceded by
one or more follow-up assessments, the
first of which occurs in the first 60 days
of the performance period. This is
labeled an EOC Pseudo Episode quality
assessment.
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Instruments/HomeHealthQualityInits/
Home-Health-Quality-ReportingRequirements.html. Training
announcements and additional
educational information related to the
pay-for-reporting performance
requirement would be provided on the
HH Quality Initiatives Web page. We
invite public comment on our proposal
to implement an 80 percent Pay-forReporting Performance Requirement for
Submission of OASIS Quality Data for
Year 2 reporting period July 1, 2016 to
June 30, 2017 as described previously,
for the HH QRP.
E. Home Health Care CAHPS Survey
(HHCAHPS)
In the CY 2015 HH PPS final rule (79
FR 66031), we stated that the home
health quality measures reporting
requirements for Medicare-certified
agencies include the Home Health Care
CAHPS® (HHCAHPS) Survey for the CY
2015 Annual Payment Update (APU).
We maintained the stated HHCAHPS
data requirements for CY 2015 set out in
previous rules, for the continuous
monthly data collection and quarterly
data submission of HHCAHPS data.
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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 originally
endorsed by the NQF in March 2009
(NQF Number 0517) and recently NQF
re-endorsed in 2015. 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 HHCAHPS Survey is approved
under OMB Control Number 0938–1066
through May 31, 2017. 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 the HHCAHPS 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,
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which is downloadable from https://
homehealthcahps.org.
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. HHCAHPS data was first
publicly reported in April 2012 on
Home Health Compare. 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. If
you need additional language
translations of the HHCAHPS Survey,
please contact us at HHCAHPS@rti.org.
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. We
update the HHCAHPS Protocols and
Guidelines Manual annually, and the
current version is 7.0. 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
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information for a specific condition or
illness that the patient has; or
• 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 all their surveyeligible home health care 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.
Update training is required annually for
all approved HHCAHPS survey vendors.
We have approximately 30 approved
HHCAHPS survey vendors. The most
current 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. As
stated previously in the six prior final
rules to this proposed rule, all
HHCAHPS approved survey vendors
must develop a Quality Assurance Plan
(QAP) for survey administration in
accordance with the HHCAHPS
Protocols and Guidelines Manual. An
HHCAHPS survey vendor’s first QAP
must be submitted within 6 weeks of the
data submission deadline date after the
vendor’s first quarterly data submission.
The QAP must be updated and
submitted annually thereafter and at any
time that changes occur in staff or
vendor capabilities or systems. A model
QAP is included in the HHCAHPS
Protocols and Guidelines Manual. The
QAP must include the following:
• Organizational Background and
Staff Experience;
• Work Plan;
• Sampling Plan;
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• Survey Implementation Plan;
• Data Security, Confidentiality and
Privacy Plan; and
• Questionnaire Attachments.
As part of the oversight activities, the
HHCAHPS Survey Coordination Team
conducts on-site visits to all approved
HHCAHPS survey vendors. The purpose
of the site visits is to allow the
HHCAHPS Coordination Team to
observe the entire HHCAHPS Survey
implementation process, from the
sampling stage through file preparation
and submission, as well as to assess data
security and storage. The HHCAHPS
Survey Coordination Team reviews the
HHCAHPS survey vendor’s survey
systems, and assesses administration
protocols based on the HHCAHPS
Protocols and Guidelines Manual posted
at https://homehealthcahps.org. The
systems and program site visit review
includes, but is not limited to the
following:
• Survey management and data
systems;
• Printing and mailing materials and
facilities;
• Telephone call center facilities;
• Data receipt, entry and storage
facilities; and
• Written documentation of survey
processes.
After the site visits, HHCAHPS survey
vendors are given a defined time period
in which to correct any identified issues
and provide follow-up documentation
of corrections for review. HHCAHPS
survey vendors are subject to follow-up
site visits on an as-needed basis.
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
2016 APU
In the CY 2015 HH PPS final rule (79
FR 66031), we stated that for the CY
2016 APU, we would require continued
monthly HHCAHPS data collection and
reporting for four quarters. The data
collection period for CY 2016, APU
includes the second quarter 2014
through the first quarter 2015 (the
months of April 2014 through March
2015). Although these dates are past, we
wished to state them in this proposed
rule so that HHAs are again reminded of
what months constituted the
requirements for the CY 2016 APU.
HHAs are required to submit their
HHCAHPS data files to the HHCAHPS
Data Center for the HHCAHPS data from
the first quarter of 2015 data by 11:59
p.m., EST on July 16, 2015. This
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deadline is firm; no exceptions are
permitted.
For the CY 2016 APU, we required
that all HHAs that had fewer than 60
HHCAHPS-eligible unduplicated or
unique patients in the period of April 1,
2013 through March 31, 2014 are
exempted from the HHCAHPS data
collection and submission requirements
for the CY 2016 APU, upon completion
of the CY 2016 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,
2013, through March 31, 2014, were
required to submit their patient counts
on the HHCAHPS Participation
Exemption Request form for the CY
2016 APU posted on https://
homehealthcahps.org by 11:59 p.m.,
EST on March 31, 2015. This deadline
was 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
counts. HHAs receiving Medicare
certification on or after April 1, 2014 are
exempt from the HHCAHPS reporting
requirement for the CY 2016 APU.
These newly-certified HHAs did not
need to complete a HHCAHPS
Participation Exemption Request form
for the CY 2016 APU.
4. HHCAHPS Requirements for the CY
2017 APU
For the CY 2017 APU, we require
continued 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 would be 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 will be firm; no exceptions
will be permitted.
For the CY 2017 APU, we require that
all HHAs that have fewer than 60
HHCAHPS-eligible unduplicated or
unique patients in the period of April 1,
2014 through March 31, 2015 are
exempted 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
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39903
CMS verification of the HHA patient
counts. Agencies with fewer than 60
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 HHCAHPS Participation
Exemption Request form for the CY
2017 APU posted on https://
homehealthcahps.org by 11:59 p.m.,
EST on 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
counts. 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 did not
need to complete a HHCAHPS
Participation Exemption Request form
for the CY 2017 APU.
5. HHCAHPS Requirements for the CY
2018 APU
For the CY 2018 APU, we require
continued 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 would 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 will be firm; no exceptions
will be permitted.
For the CY 2018 APU, we require that
all HHAs that have fewer than 60
HHCAHPS-eligible unduplicated or
unique patients in the period of April 1,
2015 through March 31, 2016 are
exempted 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 HHCAHPS Participation
Exemption Request form for the CY
2018 APU posted on https://
homehealthcahps.org by 11:59 p.m.,
EST on March 31, 2017. This deadline
is firm, as are all of the quarterly data
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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
counts. 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 did
not need to complete a HHCAHPS
Participation Exemption Request form
for the CY 2018 APU.
the 2 percent reduction via the Provider
Reimbursement Review Board (PRRB)
appeals process. The PRRB contact
information is provided to the HHAs
receiving letters in December about the
CMS reconsideration decisions.
Providers who wish to submit a
reconsideration request should continue
to follow the reconsideration and
appeals process as finalized in the CY
2012, CY 2013, CY 2014, and CY 2015
Home Health Prospective Payment
System Rate Update Final Rules.
6. 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
would help HHAs ensure that their data
are submitted in the proper format for
data processing to the HHCAHPS Data
Center.
We will continue HHCAHPS
oversight activities as finalized in the
CY 2014 rule. In the CY 2013 HH PPS
final rule (77 FR 6704, 67164), we
codified the current guideline that all
approved HHCAHPS survey vendors
must fully comply with all HHCAHPS
oversight activities. We included this
survey requirement at § 484.250(c)(3).
We propose to continue the OASIS
and HHCAHPS reconsiderations and
appeals process that we have finalized
and that we have used for prior periods
for the CY 2012, CY 2013, CY 2014, and
CY 2015 APU determinations. We have
described the reconsiderations process
requirements in the CMS Technical
Direction Letter that we sent to the
affected HHAs, on or in late September.
HHAs have 30 days from their receipt of
the Technical Direction Letter informing
them that they did not meet the OASIS
and HHCAHPS requirements for the CY
period, to send all documentation that
supports their requests for
reconsideration to CMS. It is important
that the affected HHAs send in
comprehensive information in their
reconsideration letter/package because
we would 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,
the 2 percent reduction in the APU
would be upheld. If clear evidence of
compliance is present, the 2 percent
reduction for the APU would be
reversed. We notify affected HHAs by
December 31st annually for the APU
period that begins on January 1st. If we
determine to uphold the 2 percent
reduction, the HHA may further appeal
7. Summary
We are not proposing 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 in the 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 telephone toll-free (1–866–
354–0985) for more information about
HHCAHPS.
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F. Public Display of Home Health
Quality Data for the HH QRP
Section 1895(b)(3)(B)(v)(III) of the Act
and section 1899B(f) of the IMPACT Act
states the Secretary shall establish
procedures for making data submitted
under subclause (II) available to the
public. Such procedures shall ensure
that a home health agency has the
opportunity to review the data that is to
be made public with respect to the
agency prior to such data being made
public. 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 be meaningful and that
comparing performance across home
health agencies requires that measures
be constructed from data collected in a
standardized and uniform manner. We
also recognize the need to ensure that
each home health agency has the
opportunity to review the data before
publication. Medicare home health
regulations, as codified at § 484.250(a),
requires 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.
In addition, beginning April 1, 2015
HHAs began to receive Provider Preview
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Reports (for all Process Measures and
Outcome Measures) on a quarterly,
rather than annual, basis. The
opportunity for providers to review
their data and to submit corrections
prior to public reporting aligns with the
other quality reporting programs and the
requirement for provider review under
the IMPACT Act. We provide quality
measure data to HHAs via the
Certification and Survey Provider
Enhanced Reports (CASPER reports),
which are available through the CMS
Health Care Quality Improvement and
Evaluation System (QIES).
As part of our ongoing efforts to make
healthcare more transparent, affordable,
and accountable, the HH QRP has
developed a CMS Compare Web site for
home health agencies, which identifies
home health providers based on the
areas they serve. Consumers can search
for all Medicare-certified home health
providers that serve their city or ZIP
code and then find the agencies offering
the types of services they need. A subset
of the HH quality measures has been
publicly reported on the Home Health
Compare (HH Compare) Web site since
2003. The selected measures that are
made available to the public can be
viewed on the HH Compare Web site
located at https://www.medicare.gov/
HHCompare/Home.asp.
The Affordable Care Act calls for
transparent, easily understood
information on provider quality to be
publicly reported and made widely
available. To provide home health care
consumers with a summary of existing
quality measures in an accessible
format, we plan to publish a star rating
based on the quality of care measures
for home health agencies on Home
Health Compare starting in July 2015.
This is part of our plan to adopt star
ratings across all Medicare.gov Compare
Web sites. Star ratings are currently
publicly displayed on Nursing Home
Compare, Physician Compare, the
Medicare Advantage Plan Finder, and
Dialysis Facility Compare, and they are
scheduled to be displayed on Hospital
Compare in 2015.
The Quality of Patient Care star rating
methodology assigns each home health
agency a rating between one (1) and five
(5) stars, using half stars for adjustment
and reporting. All Medicare-certified
home health agencies are eligible to
receive a Quality of Patient Care star
rating providing that they have quality
data reported on at least 5 out of the 9
quality measures that are included in
the calculation.
Home health agencies would continue
to have prepublication access to their
agency’s quality data, which enables
each agency to know how it is
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performing before public posting of the
data on the Compare Web site. Starting
in April 2015, HHAs are receiving
quarterly preview reports showing their
Quality of Patient Care star rating and
how it was derived well before public
posting, and they have several weeks to
review and provide feedback.
The Quality of Patient Care star
ratings methodology was developed
through a transparent process the
included multiple opportunities for
stakeholder input, which was
subsequently the basis for refinements
to the methodology. An initial proposed
methodology for calculating the Quality
of Patient Care star ratings was posted
on the CMS.gov Web site in December
2014. CMS then held two Special Open
Door Forums (SODFs) on December 17,
2014 and February 5, 2015 to present
the proposed methodology and solicit
input. At each SODF, stakeholders
provided immediate input, and were
invited to submit additional comments
via the Quality of Patient Care star
ratings Help Desk mailbox: HHC_Star_
Ratings_Helpdesk@cms.hhs.gov. CMS
refined the methodology, based on
comments received and additional
analysis. The final methodology report
is posted on the new star ratings Web
page: https://www.cms.gov/Medicare/
Quality-Initiatives-Patient-AssessmentInstruments/HomeHealthQualityInits/
HHQIHomeHealthStarRatings.html. A
Frequently-Asked-Questions (FAQ)
document is also posted on the same
Web page, addressing the issues raised
in the comments that were received. We
tested the Web site language used to
present the Quality of Patient Care star
ratings with Medicare beneficiaries to
assure that it allowed them to accurately
understand the significance of the
various star ratings.
Additional information regarding the
Quality of Patient Care star rating would
be posted on the star ratings Web page
at https://www.cms.gov/Medicare/
Quality-Initiatives-Patient-AssessmentInstruments/HomeHealthQualityInits/
HHQIHomeHealthStarRatings.html.
Additional communications regarding
the Quality of Patient Care star ratings
would be announced via regular HH
QRP communication channels.
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
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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 casemix adjustment factors for significant
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39905
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
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 proposed HHVBP model would
apply a payment adjustment based on
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an HHA’s performance on quality
measures to test the effects on quality
and costs of care. This proposed HHVBP
model was developed based on the
experiences we gained from the
implementation of the Home Health
Pay-for-Performance (HHPP)
demonstration as well as the successful
implementation of the HVBP program.
The model design was also developed
from the public comments received on
the discussion of a HHVBP model being
considered in the CY 2015 HH PPS
proposed and final rules. Value-based
purchasing programs have also been
included in the President’s budget for
most providers types, including Home
Health.
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). 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 proposed
changes in payments under the HH PPS
for CY 2016 are estimated to be ¥$350
million. The savings impacts related to
the proposed HHVBP model are
estimated at a total projected 5-year
gross savings of $380 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. In
accordance with the provisions of
Executive Order 12866, this regulation
was reviewed by the Office of
Management and Budget.
1. HH PPS
The update set forth in this rule
applies to Medicare payments under HH
PPS in CY 2016. Accordingly, the
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following analysis describes the impact
in CY 2016 only. We estimate that the
net impact of the proposals in this rule
is approximately $350 million in
decreased payments to HHAs in CY
2016. 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 2016 wage index proposed
in section III.C.3 of this proposed rule
and the recalibration of the case-mix
weights for 2016 proposed in section
III.B. of this proposed rule is zero. The
¥$350 million impact reflects the
distributional effects of the 2.3 percent
HH payment update percentage ($420
million increase), the effects of the third
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 ¥2.5 percent ($470 million
decrease), and the effects of the ¥1.72
percent adjustment for nominal casemix growth ($300 million decrease). The
$350 million in decreased payments is
reflected in the last column of the first
row in Table 24 as a 0.1 percent
decrease in expenditures when
comparing CY 2015 payments to
estimated CY 2016 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
conclude that the policies proposed in
this rule will result in an estimated total
impact of 3 to 5 percent or more on
Medicare revenue for greater than 5
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percent of HHAs. Therefore, the
Secretary has determined that this HH
PPS proposed rule will have a
significant economic impact on a
substantial number of small entities.
Further detail is presented in Table 24,
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 2016. For the
proposed reduction to the national,
standardized 60-day episode payment
amount of 1.72 percent for CY 2016
described in section III.B.2 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 below,
we note that we considered proposing
the full 3.41 percent reduction to the 60day episode rate in CY 2016 to account
for nominal case-mix growth between
CY 2012 and CY 2014. However, we
instead proposed to reduce the 60-day
episode rate by 1.72 percent in CY 2016
and 1.72 percent in CY 2017 to account
for estimated nominal case-mix growth
between CY 2012 and CY 2014.
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
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beyond CY 2016. 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.
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 applies to HHAs.
Therefore, the Secretary has determined
that the HH PPS proposed rule will not
have a significant economic impact on
the operations of small rural hospitals.
2. Proposed HHVBP Model
To test the impact of upside and
downside value-based payment
adjustments, beginning in calendar year
2018 and in each succeeding calendar
year through calendar year 2022, the
proposed model would adjust the final
claim payment amount for a home
health agency for each episode in a
calendar year by an amount equal to the
applicable percent. For purposes of this
proposed rule, we have limited our
analysis of the economic impacts to the
value-based incentive payment
adjustments. Under the proposed model
design, the incentive payment
adjustments would be limited to the
total payment reductions to home health
agencies included in the model and
would be no less than the total amount
available for value-based incentive
payment adjustment. Overall, the
distributive impact of this proposed rule
is estimated at $380 million for CY
2018–2022. Therefore, this proposed
rule is economically significant and
thus a major rule under the
Congressional Review Act. The
proposed model would test the effect on
quality and costs of care by applying
payment adjustments based on HHAs’
performance on quality measures. This
proposed rule was developed based on
extensive research and experience with
value-based purchasing models.
Guidance issued by the Department of
Health and Human Services interpreting
the Regulatory Flexibility Act considers
the effects economically ‘significant’
only if greater than 5 percent of
providers reach a threshold of 3 to 5
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percent or more of total revenue or total
costs. Among the over 1900 HHAs in the
selected states that would be expected
to be included in the proposed HHVBP
model, we estimate that the maximum
percent payment adjustment resulting
from this proposed rule will only be
greater than ¥5 percent for 10 percent
of the HHAs included in the model
(using the 8 percent maximum payment
adjustment threshold applied in CY2021
and CY2022). As a result, only 2 percent
of all HHA providers nationally would
be significantly impacted, falling well
below the RFA threshold. In addition,
only HHAs that are impacted with lower
payments are those providers that
provide the poorest quality which is the
main tenet of the model. This falls well
below the threshold for economic
significance established by HHS for
requiring a more detailed impact
assessment under the RFA. Thus, we are
not preparing an analysis under the RFA
because the Secretary has determined
that this proposed rule would not have
a significant economic impact on a
substantial number of small entities.
In addition, section 1102(b) of the Act
requires us to prepare a regulatory
impact analysis if a rule may have a
significant impact on the operations of
a substantial number of small rural
HHAs. This analysis must conform to
the provisions of section 603 of the
RFA. For purposes of section 1102(b) of
the Act, we have identified less than 5
percent of HHAs included in the
proposed selected states that primarily
serve beneficiaries that reside in rural
areas (greater than 50 percent of
beneficiaries served). We are not
preparing an analysis under section
1102(b) of the Act because the Secretary
has determined that the proposed
HHVBP model would not have a
significant impact on the operations of
a substantial number of small rural
HHAs.
Section 202 of the Unfunded
Mandates Reform Act of 1995 also
requires that agencies assess anticipated
costs and benefits before issuing any
rule whose mandates require spending
in any 1 year of $100 million in 1995
dollars, updated annually for inflation.
In 2015, that threshold is approximately
$144 million. This rule will have no
consequential effect on state, local, or
tribal governments or on the private
sector.
Executive Order 13132 establishes
certain requirements that an agency
must meet when it promulgates a
proposed rule (and subsequent final
rule) that imposes substantial direct
requirement costs on State and local
governments, preempts state law, or
otherwise has Federalism implications.
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Since this regulation does not impose
any costs on state or local governments,
the requirements of Executive Order
13132 are not applicable.
In accordance with the provisions of
Executive Order 12866, this regulation
was reviewed by the Office of
Management and Budget.
C. Detailed Economic Analysis
1. HH PPS
This proposed rule sets forth updates
for CY 2016 to the HH PPS rates
contained in the CY 2015 HH PPS final
rule (79 FR 66032 through 66118). 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 preliminary
Medicare claims data from 2014. 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 24 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 2014 HH claims data
(as of December 31, 2014) for dates of
service that ended on or before
December 31, 2014, and OASIS
assessments. The first column of Table
24 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
proposed CY 2016 wage index. The
fourth column shows the payment
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effects of the proposed CY 2016 casemix weights. The fifth column shows
the effects the proposed reduction of
1.72 percent 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 2016, the average impact
for all HHAs due to the effects of
rebasing is an estimated 2.5 percent
decrease in payments. The seventh
column shows the effects of the CY 2016
home health payment update percentage
(the home health market basket update
adjusted for multifactor productivity as
discussed in section III.C.1. of this
proposed rule).
The last column shows the combined
effects of all the proposed policies for
HH PPS. Overall, it is projected that
aggregate payments in CY 2016 will
decrease by 1.8 percent. As illustrated
in Table 24, 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
group may experience different impacts
on payments than others due to the
distributional impact of the CY 2016
wage index, the extent to which HHAs
had episodes in case-mix groups where
the case-mix weight decreased for CY
2016 relative to CY 2015, 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 24—ESTIMATED HOME HEALTH AGENCY IMPACTS BY FACILITY TYPE AND AREA OF THE COUNTRY, CY 2016
Number of
agencies
All Agencies .....................
11,432
60-day
episode rate
nominal casemix reduction
(percent)
CY 2016
case-mix
weights 2
(percent)
CY 2016 wage
index 1
(percent)
0.0
Rebasing 3
(percent)
HH payment
update
percentage 4
(percent)
Total (percent)
¥1.6
0.0
¥2.5
2.3
¥1.8
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 ......
1,054
0.2
¥0.2
¥1.6
¥2.5
2.3
¥1.8
8,917
0.0
0.0
¥1.6
¥2.5
2.3
¥1.8
379
741
116
¥0.2
0.1
¥0.3
¥0.1
¥0.2
¥0.1
¥1.6
¥1.6
¥1.6
¥2.5
¥2.5
¥2.5
2.3
2.3
2.3
¥2.1
¥1.9
¥2.2
225
10,350
1,082
1,795
9,033
604
¥0.2
0.0
0.0
0.1
0.0
¥0.2
¥0.2
0.0
¥0.2
¥0.2
0.0
¥0.1
¥1.6
¥1.6
¥1.6
¥1.6
¥1.6
¥1.6
¥2.5
¥2.5
¥2.5
¥2.5
¥2.5
¥2.5
2.3
2.3
2.3
2.3
2.3
2.3
¥2.2
¥1.8
¥2.0
¥1.9
¥1.8
¥2.1
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 ..............................
188
¥0.8
¥0.2
¥1.6
¥2.4
2.3
¥2.7
143
¥0.2
¥0.1
¥1.6
¥2.5
2.3
¥2.1
448
231
25
¥0.5
¥0.6
0.0
¥0.1
¥0.2
¥0.2
¥1.6
¥1.6
¥1.6
¥2.5
¥2.5
¥2.5
2.3
2.3
2.3
¥2.4
¥2.6
¥2.0
136
¥0.4
¥0.1
¥1.6
¥2.5
2.3
¥2.3
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Facility Type and Control: Urban
Free-Standing/Other Vol/
NP .................................
Free-Standing/Other Proprietary ..........................
Free-Standing/Other Government ........................
Facility-Based Vol/NP ......
Facility-Based Proprietary
Facility-Based Government ..............................
912
0.2
¥0.2
¥1.6
¥2.5
2.3
¥1.8
8,604
0.0
0.0
¥1.6
¥2.5
2.3
¥1.8
152
510
91
¥0.4
0.2
¥0.3
¥0.1
¥0.2
¥0.1
¥1.6
¥1.6
¥1.6
¥2.5
¥2.5
¥2.4
2.3
2.3
2.3
¥2.3
¥1.8
¥2.1
89
¥0.1
¥0.2
¥1.6
¥2.5
2.3
¥2.1
¥2.5
¥2.5
2.3
2.3
¥2.4
¥1.7
Facility Location: Urban or Rural
Rural .................................
Urban ...............................
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0.1
1,074
10,358
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0.0
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¥1.6
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TABLE 24—ESTIMATED HOME HEALTH AGENCY IMPACTS BY FACILITY TYPE AND AREA OF THE COUNTRY, CY 2016—
Continued
Number of
agencies
CY 2016 wage
index 1
(percent)
60-day
episode rate
nominal casemix reduction
(percent)
CY 2016
case-mix
weights 2
(percent)
Rebasing 3
(percent)
HH payment
update
percentage 4
(percent)
Total (percent)
Facility Location: Region of the Country
Northeast ..........................
Midwest ............................
South ................................
West .................................
Other ................................
837
3,044
5,623
1,837
91
0.2
¥0.1
¥0.1
0.4
0.4
¥0.1
0.0
0.0
¥0.1
0.1
¥1.6
¥1.6
¥1.6
¥1.6
¥1.6
¥2.4
¥2.5
¥2.5
¥2.5
¥2.5
2.3
2.3
2.3
2.3
2.3
2.3
¥1.9
¥1.9
¥1.5
¥1.3
¥2.4
¥2.5
¥2.6
¥2.5
¥2.5
¥2.6
¥2.5
¥2.5
¥2.5
2.3
2.3
2.3
2.3
2.3
2.3
2.3
2.3
2.3
2.3
¥1.6
¥2.0
¥1.8
¥1.5
¥2.3
¥2.1
¥1.6
¥1.5
¥2.5
¥2.5
¥2.5
¥2.5
¥2.5
2.3
2.3
2.3
2.3
2.3
2.3
¥1.7
¥1.7
¥1.8
¥1.9
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 ...............................
296
541
2,407
637
1,826
444
3,353
602
1,235
0.2
0.3
¥0.1
0.0
0.2
¥0.4
¥0.2
0.2
0.5
¥0.1
¥0.1
0.0
0.0
0.1
0.0
¥0.1
0.0
¥0.2
¥1.6
¥1.6
¥1.6
¥1.6
¥1.6
¥1.6
¥1.6
¥1.6
¥1.6
Facility Size (Number of 1st Episodes)
< 100 episodes ................
100 to 249 ........................
250 to 499 ........................
500 to 999 ........................
1,000 or More ..................
3,171
2,861
2,425
1,679
1,296
0.1
0.1
0.1
0.0
0.0
¥0.1
0.0
0.0
0.0
¥0.1
¥1.6
¥1.6
¥1.6
¥1.6
¥1.6
Source: CY 2014 Medicare claims data for episodes ending on or before December 31, 2014 (as of December 31, 2014) for which we had a
linked OASIS assessment.
1 The impact of the proposed CY 2016 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 proposed CY 2016 home health case-mix weights reflects the recalibration of the case-mix weights as outlined in section
III.B.1 of this proposed rule offset by the case-mix weights budget neutrality factor described in section III.C.3 of this proposed rule.
3 The impact of rebasing includes the rebasing adjustments to the national, standardized 60-day episode payment rate (-2.74 percent after the
CY 2016 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 2016 home health payment update percentage reflects the home health market basket update of 2.9 percent, reduced by a 0.6 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
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2. Proposed HHVBP Model
Table 25 displays our analysis of the
distribution of possible payment
adjustments at the 5 percent, 6 percent
and 8 percent rates that are being
proposed in the model based on 2013–
2014 data, providing information on the
estimated impact of this proposed rule.
We note that this impact analysis is
based on the aggregate value of all 9
states identified in section IV.C.2. of this
proposed rule by applying the proposed
state selection methodology.
Table 26 displays our analysis of the
distribution of possible payment
adjustments based on 2013–2014 data,
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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 states
(identified in section IV.C.2. of this
proposed rule) by applying the
proposed state selection methodology.
If our methodology is finalized as
proposed, all Medicare-certified HHAs
that provide services in Massachusetts,
Maryland, North Carolina, Florida,
Washington, Arizona, Iowa, Nebraska,
and Tennessee will be required to
compete in this model. However, should
the methodology we propose in this rule
change as a result of comments received
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during the rulemaking process, it could
result in different states being selected
for the model. In such an event, we
would apply the final methodology and
announce the selected states in the final
rule. The estimates presented here may
also change accordingly.
Value-based incentive payment
adjustments for the estimated 1,900 plus
HHAs in the proposed selected states
that would compete in the HHVBP
model are stratified by the size as
defined in section F. For example,
Arizona has 31 HHAs that do not
provide services to enough beneficiaries
to be required to complete CAHPS
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surveys and therefore are considered
lower-volume under the proposed
model. Using 2013–2014 data and the
highest payment adjustment of 5
percent (which we propose to be
applied in CYs 2021 and 2022), based
on 10 process and outcome measures
currently available on home health
compare, the small HHAs in Arizona
would have a mean payment adjustment
of positive 0.64 percent. Only 10
percent of home health agencies would
be subject to downward payment
adjustments of more than ¥3.3 percent.
The next columns provide the
distribution of scores by percentile; we
see that the value-based incentive
percentage payments for home health
agencies in Arizona range from ¥3.3
percent at the 10th percentile to +5.0
percent at the 90th percentile, while the
value-based incentive payment at the
50th percentile is 0.56 percent.
The smaller-volume HHA cohorts
table identifies that some consideration
will have to be made for MD, WA and
TN where there are too few HHAs in the
smaller-volume cohort and would be
included in the larger-volume cohort
without being measured on HHCAHPS.
Table 27 provides the payment
adjustment distribution based on
proportion of dual-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 TPS score and the payment
methodology at the state and size level
were calculated so that each home
health agency’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 1,931 HHAs in the nine
selected states out of 1,991 HHAs that
were found in the HHA data sources
which yielded the sufficient measures to
be included 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.
TABLE 25—ADJUSTMENT DISTRIBUTION BY PERCENTILE LEVEL OF QUALITY TOTAL PERFORMANCE SCORE AT DIFFERENT
MODEL PAYMENT ADJUSTMENT RATES
Lowest quality providers
Payment adjustment
distribution
Range
5% Payment Adjustment for Year 1
and Year 2 of
Model ....................
6% Payment Adjustment for Year 3 of
Model ....................
8% Payment Adjustment for Year 4
and Year 5 of
Model ....................
Lowest
10th
pctile*
20th
pctile*
30th
pctile*
Highest quality providers
40th
pctile*
50th
pctile*
60th
pctile*
70th
pctile*
80th
pctile*
Highest
10th
pctile*
7.69
¥2.98
¥2.04
¥1.23
¥0.54
0.15
0.83
1.74
3.08
4.71
9.24
¥3.60
¥2.46
¥1.50
¥0.66
0.18
1.02
2.10
3.72
5.64
12.31
¥4.77
¥3.27
¥1.97
¥0.86
0.25
1.33
2.78
4.92
7.54
*pctile = percentile
TABLE 26—HHA COHORT PAYMENT ADJUSTMENT DISTRIBUTIONS BY STATE
[Based on a 5 percent payment adjustment]
State
Number of
HHAs
Average
payment
adjustment
(%)
10%
20%
30%
40%
50%
60%
70%
80%
90%
0.56
0.21
¥0.97
0.39
¥0.47
¥0.68
¥1.13
2.48
0.00
1.31
0.94
0.31
0.79
1.78
0.34
¥0.44
5.00
0.00
3.36
1.84
2.74
1.33
1.78
3.67
0.40
5.00
0.00
4.75
3.04
3.25
2.46
1.78
5.00
0.42
5.00
0.00
5.00
4.38
5.00
4.68
1.78
5.00
1.46
5.00
0.00
0.56
0.19
¥0.56
0.63
0.00
0.38
¥0.19
1.31
0.94
0.13
1.25
0.81
0.94
0.50
3.38
1.81
0.56
2.06
2.38
1.88
1.31
4.75
3.06
1.19
3.81
2.94
3.06
2.31
5.00
4.38
3.50
4.88
4.13
4.88
5.00
asabaliauskas on DSK5VPTVN1PROD with PROPOSALS
Smaller-Volume HHA Cohort by State
AZ .................
FL .................
IA ..................
MA ................
MD ................
NC ................
NE ................
TN .................
WA ................
31
353
23
29
2
9
16
2
1
0.64
0.44
0.17
0.39
¥0.47
0.72
¥0.51
2.48
0.00
¥3.33
¥3.01
¥3.14
¥3.68
¥2.71
¥2.38
¥2.26
¥0.05
0.00
¥2.72
¥1.76
¥2.53
¥1.75
¥2.71
¥1.84
¥1.80
¥0.05
0.00
¥2.17
¥1.00
¥2.01
¥0.70
¥2.71
¥1.41
¥1.64
¥0.05
0.00
¥0.82
¥0.39
¥1.41
¥0.10
¥2.71
¥1.23
¥1.43
¥0.05
0.00
Larger-volume HHA Cohort by State
AZ .................
FL .................
IA ..................
MA ................
MD ................
NC ................
NE ................
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82
672
129
101
50
163
48
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0.39
0.41
¥0.31
0.64
0.41
0.65
0.37
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¥3.31
¥3.00
¥3.13
¥2.88
¥2.75
¥2.75
¥2.63
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¥2.75
¥1.75
¥2.31
¥2.19
¥2.06
¥1.56
¥2.19
Frm 00072
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¥2.19
¥1.60
¥2.70
¥1.50
¥2.30
¥1.30
¥1.40
Sfmt 4702
¥0.81
¥0.38
¥1.13
¥0.38
¥0.88
¥0.06
¥0.56
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TABLE 26—HHA COHORT PAYMENT ADJUSTMENT DISTRIBUTIONS BY STATE—Continued
[Based on a 5 percent payment adjustment]
State
TN .................
WA ................
Average
payment
adjustment
(%)
Number of
HHAs
134
55
0.39
0.39
10%
20%
30%
40%
50%
¥2.56
¥2.75
¥1.81
¥1.63
¥2.00
¥2.00
¥0.63
¥0.94
¥0.06
¥0.19
60%
0.81
0.69
70%
1.44
1.94
80%
2.50
3.31
90%
4.69
4.06
TABLE 27—PAYMENT ADJUSTMENT DISTRIBUTIONS BY CHARACTERISTICS
[based on a 5 percent payment adjustment]
Percentage Dually-eligible
asabaliauskas on DSK5VPTVN1PROD with PROPOSALS
Low % Dually-eligible ...............
Medium % Dually-eligible .........
High % Dually-eligible ..............
Acuity (HCC):
Low Acuity .........................
Middle acuity .....................
High Acuity ........................
% Rural Beneficiaries:
All non-rural .......................
Up to 35% rural .................
over 35% rural ..................
Organizational Type:
Church ...............................
Private Not-For-Profit ........
Other .................................
Private For-Profit ...............
Federal ..............................
State ..................................
Local ..................................
Number of
HHAs
10%
20%
30%
40%
50%
498
995
498
¥3.21
¥2.91
¥2.46
¥2.57
¥2.10
¥1.04
¥1.86
¥1.33
¥0.24
¥1.29
¥0.63
0.59
¥0.60
0.01
1.29
0.12
0.67
2.34
0.78
1.39
3.38
2.13
2.47
4.53
3.97
4.12
5.00
499
993
499
¥2.83
¥3.05
¥3.04
¥1.76
¥2.08
¥2.04
¥0.94
¥1.24
¥1.29
¥0.23
¥0.50
¥0.51
0.46
0.19
0.26
1.16
0.90
1.06
2.03
1.71
2.00
3.40
2.81
3.16
5.00
4.51
4.91
800
925
250
¥2.81
¥3.12
¥2.91
¥1.51
¥2.37
¥2.01
¥0.66
¥1.71
¥1.17
0.08
¥1.01
¥0.62
0.78
¥0.42
¥0.11
1.54
0.32
0.56
2.64
1.18
1.32
3.94
2.24
2.86
5.00
3.97
4.58
62
194
93
1538
83
5
61
¥2.92
¥2.78
¥2.62
¥3.09
¥2.44
¥3.03
¥2.30
¥2.04
¥1.74
¥1.68
¥2.08
¥1.61
¥1.11
¥1.28
¥1.33
¥0.97
¥0.95
¥1.27
¥0.67
¥.37
¥0.48
¥0.46
¥0.42
¥0.38
¥0.53
0.01
¥0.01
0.16
0.12
0.27
0.36
0.24
0.53
0.24
0.98
0.64
0.85
1.08
1.02
1.13
0.42
1.91
1.30
1.77
1.86
1.88
1.80
1.66
2.88
2.58
2.89
3.09
3.02
3.09
2.96
4.11
4.22
4.55
4.63
4.83
4.58
3.24
5.00
D. Alternatives Considered
As described in section III.B.2 of this
proposed rule, we considered proposing
to reduce the national, standardized 60day 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 estimate that the aggregate impact
would be a net decrease of $650 million
in payments to HHAs, resulting from a
$470 million decrease (¥2.5 percent)
due to the third year of the Affordable
Care Act mandated rebasing
adjustments, a $420 million increase
(2.3 percent) due to the home health
payment update percentage, and a $600
million decrease due to reducing the
national, standardized 60-day episode
payment rate by 3.41 percent. However,
instead of proposing 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 proposed to
reduce the national, standardized 60day episode payment rate by 1.72
percent in CY 2016 and 1.72 percent in
CY 2017 to account for nominal case-
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mix growth from CY 2012 through CY
2014 as outlined in section III.B.2 of this
proposed rule.
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
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60%
70%
80%
90%
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 ¥0.6 percentage
point productivity adjustment to the
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proposed CY 2016 home health market
basket update (2.9 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).
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 27, 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 27 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.
($300 million decrease), and the third
year of the 4-year phase-in of the
rebasing adjustments required by
section 3131(a) of the Affordable Care
Act of ¥2.5 percent ($470 million
decrease). This analysis, together with
the remainder of this preamble,
provides an initial Regulatory
Flexibility Analysis.
2. Proposed HHVBP Model
In conclusion, we estimate there will
be no net impact of the proposals in this
rule in Medicare payments to HHAs for
CY 2016. However, the overall
economic impact of the HHVBP model
provision is an estimated $380 million
in total savings from a reduction in
unnecessary hospitalizations and SNF
usage as a result of greater quality
improvements in the HH industry over
the life of the proposed model.
IX. Federalism Analysis
TABLE 27—ACCOUNTING STATEMENT:
Executive Order 13132 on Federalism
HH PPS CLASSIFICATION OF ESTI(August 4, 1999) establishes certain
MATED TRANSFERS AND COSTS,
requirements that an agency must meet
FROM THE CYS 2015 TO 2016 *
when it promulgates a final rule that
Category
Annualized Monetized
Transfers.
From Whom to
Whom?.
Transfers
¥$350 million.
Federal Government
to HHAs.
* The estimates reflect 2016 dollars.
Table 28 provides our best estimate of
the decrease in Medicare payments
under the proposed HHVBP model.
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.
Annualized Monetized
Transfers.
From Whom to
Whom?.
¥$380 million.
Federal Government
to Hospitals and
SNFs.
asabaliauskas on DSK5VPTVN1PROD with PROPOSALS
F. Conclusion
1. HH PPS
In conclusion, we estimate that the
net impact of the HH PPS proposals in
this rule is a decrease in Medicare
payments to HHAs of $350 million for
CY 2016. The $350 million decrease in
estimated payments to HHAs for CY
2016 reflects the distributional effects of
the 2.3 percent CY 2016 HH payment
update percentage ($420 million
increase), the proposed reduction to the
national, standardized 60-day episode
payment rate in CY 2016 of 1.72 percent
to account for nominal case-mix growth
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Emergency medical services, Health
facilities, Health professions, Medicare,
and Reporting and recordkeeping
requirements.
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 proposes to amend
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
Social Security Act (42 U.S.C. 1302 and
1395hh).
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Plan of care requirements.
*
*
*
*
*
(e) * * *
(1) * * *
(iii) Discharge with goals met and/or
no expectation of a return to home
health care and the patient returns to
home health care during the 60 day
episode.
*
*
*
*
*
PART 424—CONDITIONS FOR
MEDICARE PAYMENT
3. The authority citation for part 424
continues to read as follows:
■
Authority: Secs. 1102 and 1871 of the
Social Security Act (42 U.S.C. 1302 and
1395hh).
§ 424.22
[Amended]
4. Section 424.22 is amended by
redesignating paragraph (a)(1)(v)(B)(1)
as paragraph (a)(2) and by removing
reserved paragraph (a)(1)(v)(B)(2).
■
PART 484—HOME HEALTH SERVICES
5. The authority citation for part 484
continues to read as follows:
■
Authority: Secs 1102 and 1871 of the
Social Security Act (42 U.S.C. 1302 and
1395(hh)) unless otherwise indicated.
6. Section 484.205 is amended by
revising paragraphs (d) and (e) to read
as follows:
■
Basis of payment.
*
42 CFR Part 424
Transfers
§ 409.43
§ 484.205
TABLE 28—ACCOUNTING STATEMENT: List of Subjects
HHVBP MODEL CLASSIFICATION OF 42 CFR Part 409
ESTIMATED TRANSFERS AND COSTS
Health facilities, Medicare
FOR CY 2018–2022
Category
2. Section 409.43 is amended by
revising paragraph (e)(1)(iii) to read as
follows:
■
*
*
*
*
(d) Partial episode payment
adjustment. (1) An HHA receives a
national 60-day episode payment of a
predetermined rate for home health
services unless CMS determines an
intervening event, defined as a
beneficiary elected transfer or discharge
with goals met or no expectation of
return to home health and the
beneficiary returned to home health
during the 60-day episode, warrants a
new 60-day episode for purposes of
payment. A start of care OASIS
assessment and physician certification
of the new plan of care are required.
(2) The PEP adjustment will not apply
in situations of transfers among HHAs of
common ownership. Those situations
will be considered services provided
under arrangement on behalf of the
originating HHA by the receiving HHA
with the common ownership interest for
the balance of the 60-day episode. The
common ownership exception to the
transfer PEP adjustment does not apply
if the beneficiary moves to a different
MSA or Non-MSA during the 60-day
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episode before the transfer to the
receiving HHA. The transferring HHA in
situations of common ownership not
only serves as a billing agent, but must
also exercise professional responsibility
over the arranged-for services in order
for services provided under
arrangements to be paid.
(3) If the intervening event warrants a
new 60-day episode payment and a new
physician certification and a new plan
of care, the initial HHA receives a
partial episode payment adjustment
reflecting the length of time the patient
remained under its care. A partial
episode payment adjustment is
determined in accordance with
§ 484.235.
(e) Outlier payment. An HHA receives
a national 60-day episode payment of a
predetermined rate for a home health
service, unless the imputed cost of the
60-day episode exceeds a threshold
amount. The outlier payment is defined
to be a proportion of the imputed costs
beyond the threshold. An outlier
payment is a payment in addition to the
national 60-day episode payment. The
total of all outlier payments is limited
to no more than 2.5 percent of total
outlays under the HHA PPS. An outlier
payment is determined in accordance
with § 484.240.
■ 7. Section 484.220 is amended by
revising paragraph (a)(3) and adding
paragraphs (a)(4) through (6) to read as
follows:
§ 484.220 Calculation of the adjusted
national prospective 60-day episode
payment rate for case-mix and area wage
levels.
*
*
*
*
*
(a) * * *
(3) For CY 2011, the adjustment is
3.79 percent.
(4) For CY 2012, the adjustment is
3.79 percent.
(5) For CY 2013, the adjustment is
1.32 percent.
(6) For CY 2016 and CY 2017, the
adjustment is 1.72 percent in each year.
*
*
*
*
*
■ 8. Section 484.225 is revised to read
as follows:
asabaliauskas on DSK5VPTVN1PROD with PROPOSALS
§ 484.225 Annual update of the unadjusted
national prospective 60-day episode
payment rate.
(a) CMS updates the unadjusted
national 60-day episode payment rate
on a fiscal year basis (as defined in
section 1895(b)(1)(B) of the Act).
(b) For 2007 and subsequent calendar
years, in accordance with section
1895(b)(3)(B)(v) of the Act, in the case
of a home health agency that submits
home health quality data, as specified
by the Secretary, the unadjusted
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39913
national prospective 60-day episode rate
is equal to the rate for the previous
calendar year increased by the
applicable home health market basket
index amount.
(c) For 2007 and subsequent calendar
years, in accordance with section
1895(b)(3)(B)(v) of the Act, in the case
of a home health agency that does not
submit home health 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 home health market basket
index amount minus 2 percentage
points. Any reduction of the percentage
change will apply only to the calendar
year involved and will not be taken into
account in computing the prospective
payment amount for a subsequent
calendar year.
484.305 Definitions.
484.310 Applicability of the Home Health
Value-Based Purchasing (HHVBP)
model.
484.315 Data reporting for measures and
evaluation under the Home Health
Value-Based Purchasing (HHVBP)
model.
484.320 Calculation of the Total
Performance Score.
484.325 Payments for home health services
under Home Health Value-Based
Purchasing (HHVBP) model.
484.330 Process for determining and
applying the value-based payment
adjustment under the Home Health
Value-Based Purchasing (HHVBP)
model.
§ 484.230
§ 484.300
[Amended]
9. Section 484.230 is amended by
removing the last sentence.
■ 10. Section 484.240 is amended by
revising paragraphs (b) and (e) and
adding paragraph (f) to read as follows:
■
§ 484.240 Methodology used for the
calculation of the outlier payment.
*
*
*
*
*
(b) The outlier threshold for each
case-mix group is the episode payment
amount for that group, or the PEP
adjustment amount for the episode, plus
a fixed dollar loss amount that is the
same for all case-mix groups
*
*
*
*
*
(e) The fixed dollar loss amount and
the loss sharing proportion are chosen
so that the estimated total outlier
payment is no more than 2.5 percent of
total payment under home health PPS.
(f) The total amount of outlier
payments to a specific home health
agency for a year may not exceed an
amount equal to 10 percent of the total
payments to the specific agency under
home health PPS for the year.
§ 484.245
[Removed and Reserved]
11. Section 484.245 is removed and
reserved.
■
§ 484.250
[Amended]
12. Section § 484.250(a)(2) is amended
by removing the reference ‘‘§ 484.225(i)’’
and adding in its place the reference
‘‘§ 484.225(c)’’.
■ 13. Subpart F is added to read as
follows:
■
Subpart F—Home Health Value-Based
Purchasing (HHVBP) Model Components
for Medicare-Certified Home Health
Agencies Within State Boundaries
Sec.
484.300 Basis and scope of subpart.
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Subpart F—Home Health Value-Based
Purchasing (HHVBP) Model
Components for Medicare-Certified
Home Health Agencies Within State
Boundaries
Basis and scope of subpart.
This subpart is established under
section 1115A(a)(1) of the Act (42 U.S.C.
1315a), which authorizes the Secretary
to test innovative payment and service
delivery models to improve
coordination, quality, and efficiency of
health care services furnished under
Title XVIII.
§ 484.305
Definitions.
As used in this subpart—
Applicable measure means a measure
for which the Medicare-certified HHA
has provided 20 home health episodes
of care per year.
Applicable percent means a
maximum upward or downward
adjustment for a given performance
year, not to exceed the following:
(1) For CY 2018 and 2019, 5 percent.
(2) For CY 2020, 6 percent.
(3) For CY 2021 and 2022, 8 percent.
Benchmark refers to the mean of the
top decile of Medicare-certified HHA
performance on the specified quality
measure during the baseline period,
calculated separately for the largervolume and smaller-volume cohorts
within each state.
Home health prospective payment
system (HH PPS) refers to the basis of
payment for home health agencies as set
forth in §§ 484.200 through 484.245.
Larger-volume cohort means the
group of Medicare-certified home health
agencies within the boundaries of
selected states that are participating in
HHCAHPs in accordance with
§ 484.250.
Linear exchange function is the means
to translate a Medicare-certified HHA’s
Total Performance Score into a valuebased payment adjustment percentage.
Medicare-certified home health
agency means an agency:
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(1) That has a current Medicare
certification; and,
(2) Is being reimbursed by CMS for
home health care delivered within any
of the states specified in accordance
with CMS’s selection methodology.
New measures means those measures
to be reported by Medicare-certified
HHAs under the HHVBP model that are
not otherwise reported by Medicarecertified HHAs to CMS and were
identified to fill gaps to cover National
Quality Strategy Domains not
completely covered by existing
measures in the home health setting.
Payment adjustment means the
amount by which a Medicare-certified
HHA’s final claim payment amount
under the HH PPS is changed in
accordance with the methodology
described in § 484.325.
Performance period means the time
period during which data are collected
for the purpose of calculating a
Medicare-certified HHA’s performance
on measures.
Selected state(s) means those nine
states that were randomly selected to
compete/participate in the HHVBP
model via a computer algorithm
designed for random selection.
Smaller-volume cohort means the
group of Medicare-certified home health
agencies within the boundaries of
selected states that are exempt from
participation in HHCAHPs in
accordance with § 484.250.
Starter set means the quality measures
selected for the first year of this model.
Total Performance Score means the
numeric score ranging from 0 to 100
awarded to each Medicare-certified
HHA based on its performance under
the HHVBP model.
Value-based purchasing means
measuring, reporting, and rewarding
excellence in health care delivery that
takes into consideration quality,
efficiency, and alignment of incentives.
Effective health care services and high
performing health care providers may be
rewarded with improved reputations
through public reporting, enhanced
payments through differential
reimbursements, and increased market
share through purchaser, payer, and/or
consumer selection.
asabaliauskas on DSK5VPTVN1PROD with PROPOSALS
§ 484.310 Applicability of the Home Health
Value-Based Purchasing (HHVBP) model.
(a) General rule. The HHVBP model
applies to all Medicare-certified home
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health agencies (HHAs) in selected
states.
(b) Nine states are selected in
accordance with CMS’s selection
methodology. All Medicare-certified
HHAs that provide services in
Massachusetts, Maryland, North
Carolina, Florida, Washington, Arizona,
Iowa, Nebraska, and Tennessee will be
required to compete in this model.
§ 484.315 Data reporting for measures and
evaluation under the Home Health ValueBased Purchasing (HHVBP) model.
(a) Medicare-certified home health
agencies will be evaluated using a
starter set of quality measures.
(b) Medicare-certified home health
agencies in selected states will be
required to report information on New
Measures, as determined appropriate by
the Secretary, to CMS in the form,
manner, and at a time specified by the
Secretary.
(c) Medicare-certified home health
agencies in selected states will be
required to collect and report such
information as the Secretary determines
is necessary for purposes of monitoring
and evaluating the HHVBP model under
section 1115A(b)(4) of the Act (42 U.S.C.
1315a).
§ 484.320 Calculation of the Total
Performance Score.
A Medicare-certified home health
agency’s Total Performance Score for a
model year is calculated as follows:
(a) CMS will award points to the
Medicare-certified home health agency
for performance on each of the
applicable measures in the starter set,
other than New Measures.
(b) CMS will award points to the
Medicare-certified home health agency
for reporting on each of the New
Measures in the starter set, worth up to
ten percent of the Total Performance
Score.
(c) CMS will sum all points awarded
for each applicable measure in the
starter set, weighted equally at the
individual measure level, to calculate a
value worth up to 90 percent of the
Total Performance Score.
(d) The sum of the points awarded to
a Medicare-certified HHA for each
applicable measure in the starter set and
the points awarded to a Medicarecertified HHA for reporting data on each
New Measure is the Medicare-certified
PO 00000
Frm 00076
Fmt 4701
Sfmt 9990
HHA’s Total Performance Score for the
calendar year.
§ 484.325 Payments for home health
services under Home Health Value-Based
Purchasing (HHVBP) model.
CMS will determine a payment
adjustment up to the maximum
applicable percentage, upward or
downward, under the HHVBP model for
each Medicare-certified home health
agency based on the agency’s Total
Performance Score using a linear
exchange function. Payment
adjustments made under the HHVBP
model will be calculated as a percentage
of otherwise-applicable payments for
home health services provided under
section 1895 of the Act (42 U.S.C.
1395fff).
§ 484.330 Process for determining and
applying the payment adjustment under the
Home Health Value-Based Purchasing
(HHVBP) model.
(a) General. Medicare-certified home
health agencies will be ranked within
the larger-volume and smaller-volume
cohorts in selected states based on the
performance standards that apply to the
HHVBP model for the baseline year, and
CMS will make value-based payment
adjustments to the Medicare-certified
HHAs as specified in this section.
(b) Calculation of the value-based
payment adjustment amount. The
value-based payment adjustment
amount is calculated by multiplying the
Home Health Prospective Payment final
claim payment amount as calculated in
accordance with § 484.205 by the
payment adjustment percentage.
(c) Calculation of the payment
adjustment percentage. The payment
adjustment percentage is calculated as
the product of: The applicable percent
as defined in § 484.320, the Medicarecertified HHA’s Total Performance
Score divided by 100, and the linear
exchange function slope.
Dated: June 25, 2015.
Andrew M. Slavitt,
Administrator, Centers for Medicare &
Medicaid Services.
Dated: June 26, 2015.
Sylvia M. Burwell,
Secretary.
[FR Doc. 2015–16790 Filed 7–6–15; 4:15 pm]
BILLING CODE 4120–01–P
E:\FR\FM\10JYP2.SGM
10JYP2
Agencies
[Federal Register Volume 80, Number 132 (Friday, July 10, 2015)]
[Proposed Rules]
[Pages 39839-39914]
From the Federal Register Online via the Government Publishing Office [www.gpo.gov]
[FR Doc No: 2015-16790]
[[Page 39839]]
Vol. 80
Friday,
No. 132
July 10, 2015
Part II
Department of Health and Human Services
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Center for Medicare & Medicaid Services
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42 CFR Parts 409, 424, and 484
Medicare and Medicaid Programs; CY 2016 Home Health Prospective Payment
System Rate Update; Home Health Value-Based Purchasing Model; and Home
Health Quality Reporting Requirements; Proposed Rules
Federal Register / Vol. 80 , No. 132 / Friday, July 10, 2015 /
Proposed Rules
[[Page 39840]]
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DEPARTMENT OF HEALTH AND HUMAN SERVICES
Center for Medicare & Medicaid Services
42 CFR Parts 409, 424, and 484
[CMS-1625-P]
RIN 0938-AS46
Medicare and Medicaid Programs; CY 2016 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.
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SUMMARY: This proposed rule would update Home Health Prospective
Payment System (HH PPS) rates, including the national, standardized 60-
day episode payment rates, the national per-visit rates, and the non-
routine medical supply (NRS) conversion factor under the Medicare
prospective payment system for home health agencies (HHAs), effective
for episodes ending on or after January 1, 2016. As required by the
Affordable Care Act, this proposed rule implements the third year of
the four-year phase-in of the rebasing adjustments to the HH PPS
payment rates. This proposed rule provides information on our efforts
to monitor the potential impacts of the rebasing adjustments. This
proposed rule also proposes: reductions to the national, standardized
60-day episode payment rate in CY 2016 and CY 2017 of 1.72 percent in
each year to account for estimated case-mix growth unrelated to
increases in patient acuity (nominal case-mix growth) between CY 2012
and CY 2014; a HH value-based purchasing (HHVBP) model to be
implemented beginning January 1, 2016 in which all Medicare-certified
HHAs in selected states will be required to participate; changes to the
home health quality reporting program requirements; and minor technical
regulations text changes. Finally, this proposed rule would update the
HH PPS case-mix weights using the most current, complete data available
at the time of rulemaking and provide an update on the Report to
Congress regarding the home health (HH) study.
DATES: To be assured consideration, comments must be received at one of
the addresses provided below, no later than 5 p.m. on September 4,
2015.
ADDRESSES: In commenting, please refer to file code CMS-1625-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-1625-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-1625-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:
Hillary Loeffler, (410) 786-0456, for general information about the
HH PPS.
Michelle Brazil, (410) 786-1648 for information about the HH
quality reporting program.
Lori Teichman, (410) 786-6684, for information about HHCAHPS.
Robert Flemming, (844) 280-5628, for information about the HHVBP
model.
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: 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
D. Advancing Health Information Exchange
III. Proposed Provisions of the Home Health Prospective Payment
System
A. Monitoring for Potential Impacts--Affordable Care Act
Rebasing Adjustments
B. CY 2016 HH PPS Case-Mix Weights and Proposed Reduction to the
National, Standardized 60-Day Episode Payment Rate To Account for
Nominal Case-Mix Growth
1. CY 2016 HH PPS Case-Mix Weights
2. Reduction to the National, Standardized 60-Day Episode
Payment Rate to Account for Nominal Case-Mix Growth
C. CY 2016 Home Health Rate Update
1. CY 2016 Home Health Market Basket Update
2. CY 2016 Home Health Wage Index
3. CY 2016 Annual Payment Update
a. Background
b. CY 2016 National, Standardized 60-Day Episode Payment Rate
[[Page 39841]]
c. CY 2016 National Per-Visit Rates
d. Low-Utilization Payment Adjustment (LUPA) Add-On Factors
e. CY 2016 Nonroutine Medical Supply Payment Rates
f. Rural Add-On
D. Payments for High-Cost Outliers Under the HH PPS
E. Report to Congress on the Home Health Study Required by
Section 3131(d) of the Affordable Care Act and an Update on
Subsequent Research and Analysis
F. Technical Regulations Text Changes
IV. Proposed Home Health Value-Based Purchasing (HHVBP) Model
V. Proposed Provisions of 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. HH QRP Quality Measures and Measures Under Consideration for
Future Years
D. Form, Manner, and Timing of OASIS Data Submission and OASIS
Data for Annual Payment Update
1. Statutory Authority
2. Home Health Quality Reporting Program Requirements for CY
2016 Payment and Subsequent Years
3. Previously Established Pay-for-Reporting Performance
Requirement for Submission of OASIS Quality Data
E. Home Health Care CAHPS Survey (HHCAHPS)
1. Background and Description of HHCAHPS
2. HHCAHPS Oversight Activities
3. HHCAHPS Requirements for the CY 2016 APU
4. HHCAHPS Requirements for the CY 2017 APU
5. HHCAHPS Requirements for the CY 2018 APU
6. HHCAHPS Reconsideration and Appeals Process
7. Summary
F. Public Display of Home Health Quality Data for the HH QRP
VI. Collection of Information Requirements
VII. Response to Comments
VII. Regulatory Impact 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
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 (P.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
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 HHAs for
calendar year (CY) 2016, as required under section 1895(b) of the
Social Security Act (the Act). This would reflect the third year of the
four-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 also discusses our efforts to monitor the
potential impacts of the rebasing adjustments mandated by section
3131(a) of the Affordable Care Act. This rule proposes: Reductions to
the national, standardized 60-day episode payment rate in CY 2016 and
CY 2017 of 1.72 percent in each year 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; a HH Value-Based Purchasing (VBP) model,
in which certain Medicare-certified HHAs would be required to
participate beginning January 1, 2016, under the authority of section
1115(A) of the Act; changes to the home health quality reporting
program requirements under section 1895(b)(3)(B)(v)(II) of the Act; and
minor technical regulations text changes in 42 CFR parts 409, 424, and
484 to better align the payment requirements with recent statutory and
regulatory changes for home health
[[Page 39842]]
services. Finally, this proposed rule would update the case-mix weights
under section 1895(b)(4)(A)(i) and (b)(4)(B) of the Act and provide an
update on the Report to Congress regarding the HH study required by
section 3131(d) of the Affordable Care 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 final rule, ``Medicare and Medicaid
Programs; Home Health Prospective Payment System Rate Update for 2014,
Home Health Quality Reporting Requirements, and Cost Allocation of Home
Health Survey Expenses'' (78 FR 77256, December 2, 2013), we are
implementing the third year of the four-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 2016 would 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.
This proposed rule also discusses our efforts to monitor the
potential impacts of the rebasing adjustments in section III.A. 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 addition, in section III.B.2 of this rule,
we propose to reduce to the national, standardized 60-day episode
payment rate in CY 2016 and CY 2017 by 1.72 percent in each year to
account for estimated case-mix growth unrelated to increases in patient
acuity (nominal case-mix growth) between CY 2012 and CY 2014. 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 2.9 percent, minus 0.6 percentage point for productivity as
required by section 1895(b)(3)(B)(vi)(I) of the Act. In the CY 2015
final rule (79 FR 66083 through 66087), we incorporated new geographic
area designations, set out in a February 28, 2013 office of Management
and Budget (OMB) bulletin, into the home health wage index. For CY
2015, we implemented a wage index transition policy consisting of a 50/
50 blend of the old geographic area delineations and the new geographic
area delineations. In section III.C.2 of this proposed rule, we propose
to update the CY 2016 home health wage index using solely the new
geographic area designations. In section III.D of this proposed rule,
we discuss payments for high cost outliers. In section III.E, we
propose to make several technical corrections in Sec. 409, 424, and
Sec. 484 to better align the payment requirements with recent
statutory and regulatory changes for home health services. The sections
include Sec. 409.43(e), Sec. 424.22(a), Sec. 484.205(d), Sec.
484.205(e), Sec. 484.220, Sec. 484.225, Sec. 484.230, Sec.
484.240(b), Sec. 484.240(e), Sec. 484.240(f), Sec. 484.245. In
section III.F, we discuss the Report to Congress on the home health
study required by section 3131(d) of the Affordable Care Act and
provide an update on subsequent research and analysis.
In section IV of this proposed rule, we propose a HHVBP model to be
implemented beginning January 1, 2016. Medicare-certified HHAs selected
for inclusion in the HHVBP model would be required to compete for
payment adjustments to their current PPS reimbursements based on
quality performance. A competing Medicare-certified HHA is defined as
an agency having a current Medicare certification and which is being
reimbursed by CMS for home health care delivered within any of the nine
states randomly selected under CMS' proposed selection methodology.
This proposed rule also includes changes to the home health quality
reporting program in section III.V, including the proposal of one new
quality measure, the establishment of a minimum threshold for
submission of Outcome and Assessment Information Set (OASIS)
assessments for purposes of quality reporting compliance, and
submission dates for Home Health Care Consumer Assessment of Healthcare
Providers and Systems Survey (HHCAHPS) Survey through CY 2018.
C. Summary of Costs and Transfers
Table 1--Summary of Costs and Transfers
------------------------------------------------------------------------
Provision description Costs Transfers
------------------------------------------------------------------------
CY 2016 HH PPS Payment Rate .............. The overall economic
Update. impact of the HH PPS
payment rate update is
an estimated -$350
million (-1.8 percent)
in payments to HHAs.
CY 2016 HHVBP Model............ .............. The overall economic
impact of the HHVBP
model provision for CY
2018 through 2022 is
an estimated $380
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
Social Security Act (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 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
[[Page 39843]]
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 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 in section 3131 of the Affordable Care Act is the
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 two
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 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.
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
[[Page 39844]]
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 requires 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 must phase in any adjustment over a four-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 specifies that the
maximum rebasing adjustment is to 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 second year of the
four-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 adjustments per
per-visit year (CY 2014
payment 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
------------------------------------------------------------------------
D. Advancing Health Information Exchange
HHS has a number of initiatives designed to encourage and support
the adoption of health information technology and to promote nationwide
health information exchange to improve health care. As discussed in the
August 2013 Statement ``Principles and Strategies for Accelerating
Health Information Exchange'' (available at https://www.healthit.gov/sites/default/files/acceleratinghieprinciples_strategy.pdf), HHS
believes that all individuals, their families, their healthcare and
social service providers, and payers should have consistent and timely
access to health information in a standardized format that can be
securely exchanged between the patient, providers, and others involved
in the individual's care. Health IT that facilitates the secure,
efficient and effective sharing and use of health-
[[Page 39845]]
related information when and where it is needed is an important tool
for settings across the continuum of care, including home health. While
home health providers are not eligible for the Medicare and Medicaid
EHR Incentive Programs, effective adoption and use of health
information exchange and health IT tools will be essential as these
settings seek to improve quality and lower costs through initiatives
such as value-based purchasing.
The Office of the National Coordinator for Health Information
Technology (ONC) has released a document entitled ``Connecting Health
and Care for the Nation: A Shared Nationwide Interoperability Roadmap
Draft Version 1.0 (draft Roadmap) (available at https://www.healthit.gov/sites/default/files/nationwide-interoperability-roadmap-draft-version-1.0.pdf) which describes barriers to
interoperability across the current health IT landscape, the desired
future state that the industry believes will be necessary to enable a
learning health system, and a suggested path for moving from the
current state to the desired future state. In the near term, the draft
Roadmap focuses on actions that will enable a majority of individuals
and providers across the care continuum to send, receive, find and use
a common set of electronic clinical information at the nationwide level
by the end of 2017. The Roadmap's goals also align with the IMPACT Act
of 2014 which requires assessment data to be standardized and
interoperable to allow for exchange of the data. Moreover, the vision
described in the draft Roadmap significantly expands the types of
electronic health information, information sources and information
users well beyond clinical information derived from electronic health
records (EHRs). This shared strategy is intended to reflect important
actions that both public and private sector stakeholders can take to
enable nationwide interoperability of electronic health information
such as: (1) Establishing a coordinated governance framework and
process for nationwide health IT interoperability; (2) improving
technical standards and implementation guidance for sharing and using a
common clinical data set; (3) enhancing incentives for sharing
electronic health information according to common technical standards,
starting with a common clinical data set; and (4) clarifying privacy
and security requirements that enable interoperability.
In addition, ONC has released the draft version of the 2015
Interoperability Standards Advisory (available at https://www.healthit.gov/standards-advisory), which provides a list of the best
available standards and implementation specifications to enable
priority health information exchange functions. Providers, payers, and
vendors are encouraged to take these ``best available standards'' into
account as they implement interoperable health information exchange
across the continuum of care, including care settings such as
behavioral health, long-term and post-acute care, and home and
community-based service providers.
We encourage stakeholders to utilize health information exchange
and certified health IT to effectively and efficiently help providers
improve internal care delivery practices, engage patients in their
care, support management of care across the continuum, enable the
reporting of electronically specified clinical quality measures
(eCQMs), and improve efficiencies and reduce unnecessary costs. As
adoption of certified health IT increases and interoperability
standards continue to mature, HHS will seek to reinforce standards
through relevant policies and programs.
III. Proposed Provisions of the Home Health Prospective Payment System
A. Monitoring for Potential Impacts--Affordable Care Act Rebasing
Adjustments
1. Analysis of FY 2013 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 four 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 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.
For this proposed rule, we analyzed 2013 HHA cost report data and
2013 HHA claims data to determine whether the average cost per episode
was higher using 2013 cost report data compared to the 2011 cost report
and 2012 claims data used in calculating the rebasing adjustments. To
determine the 2013 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 2013 cost
reports by size, facility type, and urban/rural location so the costs
per visit were nationally representative according to 2013 claims data.
The 2013 average number of visits was taken from 2013 claims data. We
estimate the cost of a 60-day episode in CY 2013 to be $2,402.11 using
2013 cost report data (Table 3). Our latest analysis of 2013 cost
report and 2013 claims data suggests that an even larger reduction (-
5.02 percent) than the reduction described in the CY 2014 HH PPS final
rule (-3.45 percent) or the reduction described in the CY 2015 HH PPS
final rule (-4.21) would have been needed in order to align payments
with costs.
[[Page 39846]]
Table 3--2013 Estimated Cost per Episode
----------------------------------------------------------------------------------------------------------------
2013 average 2013 average
Discipline costs per number of 2013 60-day
visit visits episode costs
----------------------------------------------------------------------------------------------------------------
Skilled Nursing................................................. $131.43 9.28 $1,219.67
Home Health Aide................................................ 59.87 2.41 144.29
Physical Therapy................................................ 154.96 5.03 779.45
Occupational Therapy............................................ 154.11 1.22 188.01
Speech-Language Pathology....................................... 164.59 0.25 41.15
Medical Social Services......................................... 211.02 0.14 29.54
-----------------------------------------------
Total....................................................... .............. 18.33 2,402.11
----------------------------------------------------------------------------------------------------------------
Source: FY 2013 Medicare cost report data and 2013 Medicare claims data from the standard analytic file (as of
June 30, 2014) for episodes (excluding low-utilization payment adjusted episodes and partial-episode-payment
adjusted episodes) ending on or before December 31, 2013 for which we could link an OASIS assessment.
2. MedPAC Report to the Congress: Home Health Payment Rebasing
Section 3131(a) of the Affordable Care Act required the Medicare
Payment Advisory Commission (MedPAC) to assess, by January 1, 2015, the
impact of the mandated rebasing adjustments on quality of and
beneficiary access to home health care. As part of this assessment, the
statute required MedPAC to consider the impact on care delivered by
rural, urban, nonprofit, and for-profit home health agencies. MedPAC's
Report to Congress noted that the rebasing adjustments are partially
offset by the payment update each year and across all four years of the
phase-in of the rebasing adjustments the cumulative net reduction would
equal about 2 percent. MedPAC concluded that, as a result of the
payment update offsets to the rebasing adjustments, HHA margins are
likely to remain high under the current rebasing policy and quality of
care and beneficiary access to care are unlikely to be negatively
affected.\1\
---------------------------------------------------------------------------
\1\ Medicare Payment Advisory Commission (MedPAC), ``Report to
the Congress: Impact of Home Health Payment Rebasing on Beneficiary
Access to and Quality of Care''. December 2014. Washington, DC.
Accessed on 5/05/15 at: https://www.medpac.gov/documents/reports/dec14_homehealth_rebasing_report.pdf?sfvrsn=0.
---------------------------------------------------------------------------
As we noted in the CY 2014 HH PPS final rule (78 FR 72291),
MedPAC's past reviews of access to home health care found that access
generally remained adequate during periods of substantial decline in
the number of agencies. MedPAC stated that this is due in part to the
low capital requirements for home health care services that allow the
industry to react rapidly when the supply of agencies changes or
contracts. As described in section III.A.3, the number of HHAs billing
Medicare for home health services in CY 2013 is 80 percent higher than
the number of HHAs billing Medicare for home health services in 2001.
Even if some HHAs were to exit the program due to possible
reimbursement concerns, the home health market would be expected to
remain robust.
3. Analysis of CY 2014 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 year of the four-year phase-in of the rebasing adjustments (CY
2014), the first calendar year of the HH PPS (CY 2001), and claims data
for the three years before implementation of the rebasing adjustments
(CY 2011-2013). Preliminary analysis of CY 2014 home health claims data
indicates that the number of episodes decreased by 3.8 percent between
2013 and 2014. In addition, the number of home health users decreased
by approximately 3 percent between 2013 and 2014, while the number of
FFS beneficiaries has remained the same. 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, driven mostly by decreases TX and
FL, two of the six states with the highest utilization of Medicare home
health (see Table 3 and Table 4). The HHAs that no longer billed
Medicare for home health services in CY 2014 typically served
beneficiaries that were nearly twice as likely to be dually-eligible
for both Medicare and Medicaid in CY 2013 compared to the national
average for all HHAs in CY 2013. We note that in CY 2014 there were 3.0
HHAs per 10,000 FFS beneficiaries, the same number of HHAs per 10,000
FFS beneficiaries as there was in 2011, but markedly higher than the
1.9 HHAs per 10,000 FFS beneficiaries in 2001. If we were to exclude
the six states with the highest home health utilization (see Table 5),
the number of episodes amongst the remaining states (including Guam,
Puerto Rico, and the Virgin Islands) decreased by 2.6 percent between
2013 and 2014, the number of home health users decreased by
approximately 2.4 percent between 2013 and 2014, and the number of HHAs
billing Medicare for home health services remained virtually the same
(a net decrease of only 1 HHA).
We would note that preliminary data on hospital and skilled nursing
facility discharges and days indicates that there was a decrease in
hospital discharges of approximately 3 percent and a decrease in SNF
days of approximately 2 percent in CY 2014. 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 2014
----------------------------------------------------------------------------------------------------------------
2001 2011 2012 2013 2014
----------------------------------------------------------------------------------------------------------------
Number of episodes.............. 3,896,502 6,821,459 6,727,875 6,708,923 6,451,283
Beneficiaries receiving at least 2,412,318 3,449,231 3,446,122 3,484,579 3,381,635
1 episode (Home Health Users)..
[[Page 39847]]
Part A and/or B FFS 34,899,167 37,686,526 38,224,640 38,505,609 38,506,534
beneficiaries..................
Episodes per Part A and/or B FFS 0.11 0.18 0.18 0.17 0.17
beneficiaries..................
Home health users as a 6.9% 9.2% 9.0% 9.0% 8.8%
percentage of Part A and/or B
FFS beneficiaries..............
HHAs providing at least 1 6,511 11,446 11,746 11,889 11,693
episode........................
HHAs per 10,000 Part A and/or B 1.9 3.0 3.1 3.1 3.0
FFS beneficiaries..............
----------------------------------------------------------------------------------------------------------------
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; and accessed on May 7, 2015 for CY 2001 and
CY 2014 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.
For the six states (TX, LA, OK, MS, FL, and IL) with the highest
utilization of Medicare home health (as measured by the number of
episodes per Part A and/or Part B FFS beneficiaries), the number of
episodes decreased by 5.7 percent, the number of home health users
decreased by 4.3 percent, and the number of HHAs billing Medicare
decreased by 3.7 percent (5,280-5,085) between 2013 and 2014 (see Table
5). A possible contributing factor to these decreases may be the
temporary moratorium on the enrollment of new HHAs, effective July 31,
2013, for Miami, FL and Chicago, IL and the temporary moratorium on
enrollment of new HHAs, effective February 4, 2014, for Fort
Lauderdale, FL; Detroit, MI; Dallas, TX; and Houston, TX. The temporary
moratoria on enrollment of new HHAs in Miami, FL; Chicago, IL; Fort
Lauderdale, FL; Detroit, MI; Dallas, TX; and Houston, TX were extended
for 6 months on August 1, 2014 and again for 6 months effective January
29, 2015 (80 FR 5551).
Table 5--Home Health Statistics for the States with the Highest Number of Home Health Episodes per Part A and/or Part B FFS Beneficiaries, CY 2001 and
CY 2011 Through CY 2014
--------------------------------------------------------------------------------------------------------------------------------------------------------
Year TX FL OK MS LA IL
--------------------------------------------------------------------------------------------------------------------------------------------------------
Number of Episodes............................................. 2001 285,710 284,579 77,149 73,353 124,789 162,686
2011 1,107,605 701,426 203,112 153,983 249,479 433,117
2012 1,054,244 691,255 196,887 148,516 230,115 423,462
2013 995,555 689,269 196,713 143,428 215,590 421,309
2014 941,815 651,940 189,421 141,293 196,495 389,850
--------------------------------------------------------------------------------------------------------------------------------------------------------
Beneficiaries Receiving at Least 1 Episode (Home Health Users). 2001 155,802 195,678 36,919 35,769 50,760 105,115
2011 363,474 355,900 67,218 55,818 77,677 192,921
2012 350,803 354,838 65,948 55,438 74,755 191,936
2013 333,396 357,099 66,502 55,453 73,888 191,961
2014 319,492 343,231 65,392 54,890 69,328 179,835
--------------------------------------------------------------------------------------------------------------------------------------------------------
Part A and/or Part B FFS Beneficiaries......................... 2001 2,132,310 2,246,313 480,556 436,751 528,287 1,543,158
2011 2,597,406 2,454,124 549,687 476,497 561,531 1,785,278
2012 2,604,458 2,451,790 558,500 480,218 568,483 1,812,241
2013 2,535,611 2,454,216 568,815 483,439 574,654 1,836,862
2014 2,564,292 2,464,748 580,267 491,482 575,832 1,674,935
--------------------------------------------------------------------------------------------------------------------------------------------------------
Episodes per Part A and/or Part B FFS beneficiaries............ 2001 0.13 0.13 0.16 0.17 0.24 0.11
2011 0.43 0.29 0.37 0.32 0.44 0.24
2012 0.40 0.28 0.35 0.31 0.40 0.23
2013 0.39 0.28 0.35 0.30 0.38 0.23
2014 0.37 0.26 0.33 0.29 0.34 0.23
--------------------------------------------------------------------------------------------------------------------------------------------------------
Home Health Users as a Percentage of Part A and/or Part B FFS 2001 7.3% 8.7% 7.7% 8.2% 9.6% 6.8%
Beneficiaries.................................................
2011 14.0% 14.5% 12.2% 11.7% 13.8% 10.8%
2012 13.5% 14.5% 11.8% 11.5% 13.2% 10.6%
2013 13.2% 14.6% 11.7% 11.5% 12.9% 10.5%
2014 12.5% 13.9% 11.3% 11.2% 12.0% 10.7%
--------------------------------------------------------------------------------------------------------------------------------------------------------
HHAs Providing at Least 1 Episode.............................. 2001 799 330 180 61 242 273
2011 2,472 1,426 252 51 216 743
2012 2,549 1,430 254 48 213 783
2013 2,600 1,357 262 48 210 803
2014 2,558 1,230 262 46 205 784
--------------------------------------------------------------------------------------------------------------------------------------------------------
[[Page 39848]]
HHAs per 10,000 Part A and/or B FFS beneficiaries.............. 2001 3.7 1.5 3.7 1.4 4.6 1.8
2011 9.5 5.8 4.6 1.1 3.8 4.2
2012 9.8 5.8 4.5 1.0 3.7 4.3
2013 10.3 5.5 4.6 1.0 3.7 4.4
2014 10.0 5.0 4.5 0.9 3.6 4.7
--------------------------------------------------------------------------------------------------------------------------------------------------------
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; and accessed on May 7, 2015 for CY 2001 and CY 2014 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
year of the implementation of rebasing adjustments required by the
Affordable Care Act and comparing utilization in that year (CY 2014) to
the three years prior 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 2014. 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 $162 for CY 2014, 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 2014 (18.0 visit per episode). As
noted in section II.C, we 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 2011and 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 slightly, the number of skilled nursing and home
health aide visits have decreased, between CY 2009 and CY 2014. 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 seems 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.
[[Page 39849]]
[GRAPHIC] [TIFF OMITTED] TP10JY15.000
[[Page 39850]]
[GRAPHIC] [TIFF OMITTED] TP10JY15.001
We will continue to monitor for potential impacts due to 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. CY 2016 HH PPS Case-Mix Weights and Proposed Reduction to the
National, Standardized 60-Day Episode Payment Rate To Account for
Nominal Case-Mix Growth
1. CY 2016 HH PPS Case-Mix Weights
For CY 2014, as part of the rebasing effort mandated by the
Affordable Care Act, we reset the HH PPS case-mix weights, lowering the
average case-mix weight to 1.0000. To lower the HH PPS case-mix weights
to 1.0000, each HH PPS case-mix weight was decreased by the same factor
(1.3464), thereby maintaining the same relative values between the
weights. This ``resetting'' of the HH PPS case-mix weights was done in
a budget neutral manner by inflating the national, standardized 60-day
episode rate by the same factor (1.3464) that was used to decrease the
weights. For CY 2015, 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 2016, we propose to 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 2016 HH PPS case-mix weights, we used
CY 2014 home health claims data (as of December 31, 2014) with linked
OASIS data. These data are the most current and complete data available
at this time. We will use CY 2014 home health claims data (as of June
30, 2015) with linked OASIS data to generate the CY 2016 HH PPS case-
mix weights in the CY 2016 HH PPS final rule. The process
[[Page 39851]]
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 2013 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 2014 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.
TABLE 6--Case-Mix Adjustment Variables and Scores
----------------------------------------------------------------------------------------------------------------
----------------------------------------------------------------------------------------------------------------
Episode number within 1 or 2 1 or 2 3+ 3+
sequence of adjacent
episodes.
Therapy visits............ 0-13 14+ 0-13 14+
EQUATION:................. 1 2 3 4
----------------------------------------------------------------------------------------------------------------
CLINICAL DIMENSION
----------------------------------------------------------------------------------------------------------------
1....................................... Primary or Other Diagnosis ......... ......... ......... .........
= Blindness/Low Vision.
2....................................... Primary or Other Diagnosis ......... 6 ......... 2
= Blood disorders.
3....................................... Primary or Other Diagnosis ......... 7 ......... 7
= Cancer, selected benign
neoplasms.
4....................................... Primary Diagnosis = ......... 7 ......... 4
Diabetes.
5....................................... Other Diagnosis = Diabetes 1 ......... ......... .........
6....................................... Primary or Other Diagnosis 3 15 1 8
= Dysphagia.
AND
Primary or Other Diagnosis
= Neuro 3--Stroke
7....................................... Primary or Other Diagnosis 1 9 1 9
= Dysphagia.
AND
M1030 (Therapy at home) =
3 (Enteral)
8....................................... Primary or Other Diagnosis ......... ......... ......... .........
= Gastrointestinal
disorders.
9....................................... Primary or Other Diagnosis ......... 6 ......... 6
= Gastrointestinal
disorders.
AND
M1630 (ostomy) = 1 or 2
10...................................... 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.
11...................................... Primary or Other Diagnosis 1 ......... ......... .........
= Heart Disease OR
Hypertension.
12...................................... Primary Diagnosis = Neuro 3 11 7 11
1--Brain disorders and
paralysis.
13...................................... Primary or Other Diagnosis ......... 2 ......... 2
= Neuro 1--Brain
disorders and paralysis.
AND
M1840 (Toilet transfer) =
2 or more
14...................................... Primary or Other Diagnosis 2 7 1 5
= 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
15...................................... Primary or Other Diagnosis 3 9 2 2
= Neuro 3--Stroke.
16...................................... Primary or Other Diagnosis ......... 4 ......... 4
= Neuro 3--Stroke AND.
M1810 or M1820 (Dressing
upper or lower body) = 1,
2, or 3
17...................................... Primary or Other Diagnosis ......... ......... ......... .........
= Neuro 3--Stroke.
AND
M1860 (Ambulation) = 4 or
more
18...................................... Primary or Other Diagnosis 3 10 7 10
= 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
19...................................... Primary or Other Diagnosis 8 1 8 1
= Ortho 1--Leg Disorders
or Gait Disorders.
AND
M1324 (most problematic
pressure ulcer stage) =
1, 2, 3 or 4
20...................................... Primary or Other Diagnosis 3 ......... 3 6
= Ortho 1--Leg OR Ortho
2--Other orthopedic
disorders.
AND
M1030 (Therapy at home) =
1 (IV/Infusion) or 2
(Parenteral)
21...................................... Primary or Other Diagnosis ......... ......... ......... .........
= Psych 1--Affective and
other psychoses,
depression.
22...................................... Primary or Other Diagnosis ......... ......... ......... .........
= Psych 2--Degenerative
and other organic
psychiatric disorders.
23...................................... Primary or Other Diagnosis ......... ......... ......... .........
= Pulmonary disorders.
24...................................... Primary or Other Diagnosis ......... ......... ......... .........
= Pulmonary disorders AND
M1860 (Ambulation) = 1 or
more.
[[Page 39852]]
25...................................... Primary Diagnosis = Skin 4 19 8 19
1--Traumatic wounds,
burns, and post-operative
complications.
26...................................... Other Diagnosis = Skin 1-- 6 15 8 13
Traumatic wounds, burns,
post-operative
complications.
27...................................... Primary or Other Diagnosis 3 ......... ......... .........
= Skin 1--Traumatic
wounds, burns, and post-
operative complications
OR Skin 2--Ulcers and
other skin conditions.
AND
M1030 (Therapy at home) =
1 (IV/Infusion) or 2
(Parenteral)
28...................................... Primary or Other Diagnosis 2 17 8 17
= Skin 2--Ulcers and
other skin conditions.
29...................................... Primary or Other Diagnosis 2 16 2 16
= Tracheostomy.
30...................................... Primary or Other Diagnosis ......... 19 ......... 11
= Urostomy/Cystostomy.
31...................................... M1030 (Therapy at home) = 1 18 6 14
1 (IV/Infusion) or 2
(Parenteral).
32...................................... M1030 (Therapy at home) = ......... 14 ......... 5
3 (Enteral).
33...................................... M1200 (Vision) = 1 or more ......... ......... ......... .........
34...................................... M1242 (Pain) = 3 or 4..... 2 ......... 1 .........
35...................................... M1308 = Two or more 5 5 5 14
pressure ulcers at stage
3 or 4.
36...................................... M1324 (Most problematic 4 19 7 16
pressure ulcer stage) = 1
or 2.
37...................................... M1324 (Most problematic 8 32 11 26
pressure ulcer stage) = 3
or 4.
38...................................... M1334 (Stasis ulcer 4 12 8 12
status) = 2.
39...................................... M1334 (Stasis ulcer 7 17 10 17
status) = 3.
40...................................... M1342 (Surgical wound 2 7 5 13
status) = 2.
41...................................... M1342 (Surgical wound 1 7 5 7
status) = 3.
42...................................... M1400 (Dyspnea) = 2, 3, or ......... 1 ......... 1
4.
43...................................... M1620 (Bowel Incontinence) ......... 4 ......... 4
= 2 to 5.
44...................................... M1630 (Ostomy) = 1 or 2... 4 12 2 7
45...................................... M2030 (Injectable Drug ......... ......... ......... .........
Use) = 0, 1, 2, or 3.
----------------------------------------------------------------------------------------------------------------
FUNCTIONAL DIMENSION
----------------------------------------------------------------------------------------------------------------
46...................................... M1810 or M1820 (Dressing 2 ......... 1 .........
upper or lower body) = 1,
2, or 3.
47...................................... M1830 (Bathing) = 2 or 6 2 5 .........
more.
48...................................... M1840 (Toilet 1 4 1 1
transferring) = 2 or more.
49...................................... M1850 (Transferring) = 2 3 2 1 .........
or more.
50...................................... M1860 (Ambulation) = 1, 2 7 ......... 4 .........
or 3.
51...................................... M1860 (Ambulation) = 4 or 7 9 6 7
more.
----------------------------------------------------------------------------------------------------------------
Source: CY 2014 Medicare claims data for episodes ending on or before December 31, 2014 (as of December 31,
2014) for which we had a linked OASIS assessment. LUPA episodes, outlier episodes, and episodes with SCIC or
PEP adjustments were excluded.
Note(s): Points are additive; however, points may not be given for the same line item in the table more than
once. Please see Medicare Home Health Diagnosis Coding guidance at: https://www.cms.hhs.gov/HomeHealthPPS/03_coding&billing.asp for definitions of primary and secondary diagnoses.
In updating the four-equation model for CY 2016, using 2014 data
(the last update to the four-equation model for CY 2015 used 2013
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 2013 and 2014. The CY 2016 four-equation model resulted in
130 point-giving variables being used in the model (as compared to the
124 variables for the 2015 recalibration). There were nine variables
that were added to the model and three variables that were dropped from
the model due to the absence of additional resources associated with
the variable. The points for 18 variables increased in the CY 2016
four-equation model and the points for 43 variables decreased in the CY
2016 4-equation model. There were 58 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 2016 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 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 to guide where we
placed our thresholds. We tried to group scores with similar average
resource use within the same level (even if it meant that more or less
than a third of episodes
[[Page 39853]]
were placed within a level). The new thresholds, based off of the CY
2016 four-equation model points are shown in Table 7.
---------------------------------------------------------------------------
\2\ For Step 1, 54% of episodes were in the medium functional
level (All with score 15).
For Step 2.1, 77.2% of episodes were in the low functional level
(Most with score 2 and 4).
For Step 2.2, 67.1% of episodes were in the low functional level
(All with score 0).
For Step 3, 60.9% of episodes were in the medium functional
level (Most with score 10).
For Step 4, 49.8% of episodes were in the low functional level
(Most with score 2).
Table 7--CY 2016 Clinical and Functional Thresholds
--------------------------------------------------------------------------------------------------------------------------------------------------------
1st and 2nd episodes 3rd+ episodes All Episodes
----------------------------------------------------------------------------------------------------
0 to 13 therapy 14 to 19 therapy 0 to 13 therapy 14 to 19 therapy
visits visits visits 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:
--------------------------------------------------------------------------------------------------------------------------------------------------------
Clinical................... C1............. 0 to 1............. 0................. 0................. 0 to 3............ 0 to 3
C2............. 2 to 3............. 1 to 7............ 1................. 4 to 12........... 4 to 16
C3............. 4+................. 8+................ 2+................ 13+............... 17+
Functional................. F1............. 0 to 14............ 0 to 6............ 0 to 6............ 0................. 0 to 2
F2............. 15................. 7 to 13........... 7 to10............ 1 to 7............ 3 to 6
F3............. 16+................ 14+............... 11+............... 8+................ 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 2014 data. The R-squared value
for the payment regression model is 0.4790 (an increase from 0.4680 for
the CY 2015 recalibration).
TABLE 8--Payment Regression Model
------------------------------------------------------------------------
New payment
Variable Description regression
coefficients
------------------------------------------------------------------------
Step 1, Clinical Score Medium......................... $23.43
Step 1, Clinical Score High........................... 57.50
Step 1, Functional Score Medium....................... 73.18
Step 1, Functional Score High......................... 110.39
Step 2.1, Clinical Score Medium....................... 42.51
Step 2.1, Clinical Score High......................... 163.27
Step 2.1, Functional Score Medium..................... 34.24
Step 2.1, Functional Score High....................... 88.01
Step 2.2, Clinical Score Medium....................... 58.37
Step 2.2, Clinical Score High......................... 210.67
Step 2.2, Functional Score Medium..................... 10.64
Step 2.2, Functional Score High....................... 65.24
Step 3, Clinical Score Medium......................... 9.87
Step 3, Clinical Score High........................... 89.22
Step 3, Functional Score Medium....................... 53.47
Step 3, Functional Score High......................... 83.07
Step 4, Clinical Score Medium......................... 70.04
Step 4, Clinical Score High........................... 231.22
Step 4, Functional Score Medium....................... 14.07
Step 4, Functional Score High......................... 63.20
Step 2.1, 1st and 2nd Episodes, 14 to 19 Therapy 444.92
Visits...............................................
Step 2.2, 3rd+ Episodes, 14 to 19 Therapy Visits...... 485.03
Step 3, 3rd+ Episodes, 0-13 Therapy Visits............ -73.86
Step 4, All Episodes, 20+ Therapy Visits.............. 889.81
Intercept............................................. 378.68
------------------------------------------------------------------------
Source: CY 2014 Medicare claims data for episodes ending on or before
December 31, 2014 (as of December 31, 2014) 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
[[Page 39854]]
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 weights associated with 0 to 5 therapy visits are then
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 aligned 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 the 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 CY 2016 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--CY 2016 Case-Mix Payment Weights
----------------------------------------------------------------------------------------------------------------
Clinical and functional levels
Payment group Step (episode and/or (1 = low; 2 = medium; 3= CY 2016 case-mix
therapy visit ranges) high) weights
----------------------------------------------------------------------------------------------------------------
10111........................... 1st and 2nd Episodes, 0 to C1F1S1......................... 0.5969
5 Therapy Visits.
10112........................... 1st and 2nd Episodes, 6 C1F1S2......................... 0.7216
Therapy Visits.
10113........................... 1st and 2nd Episodes, 7 to C1F1S3......................... 0.8462
9 Therapy Visits.
10114........................... 1st and 2nd Episodes, 10 C1F1S4......................... 0.9708
Therapy Visits.
10115........................... 1st and 2nd Episodes, 11 to C1F1S5......................... 1.0954
13 Therapy Visits.
10121........................... 1st and 2nd Episodes, 0 to C1F2S1......................... 1.2201
5 Therapy Visits.
10122........................... 1st and 2nd Episodes, 6 C1F2S2......................... 1.4237
Therapy Visits.
10123........................... 1st and 2nd Episodes, 7 to C1F2S3......................... 1.6273
9 Therapy Visits.
10124........................... 1st and 2nd Episodes, 10 C1F2S4......................... 0.7123
Therapy Visits.
10125........................... 1st and 2nd Episodes, 11 to C1F2S5......................... 0.8240
13 Therapy Visits.
10131........................... 1st and 2nd Episodes, 0 to C1F3S1......................... 0.9357
5 Therapy Visits.
10132........................... 1st and 2nd Episodes, 6 C1F3S2......................... 1.0474
Therapy Visits.
10133........................... 1st and 2nd Episodes, 7 to C1F3S3......................... 1.1591
9 Therapy Visits.
10134........................... 1st and 2nd Episodes, 10 C1F3S4......................... 1.2708
Therapy Visits.
10135........................... 1st and 2nd Episodes, 11 to C1F3S5......................... 1.4643
13 Therapy Visits.
10211........................... 1st and 2nd Episodes, 0 to C2F1S1......................... 1.6578
5 Therapy Visits.
10212........................... 1st and 2nd Episodes, 6 C2F1S2......................... 0.7709
Therapy Visits.
10213........................... 1st and 2nd Episodes, 7 to C2F1S3......................... 0.8868
9 Therapy Visits.
10214........................... 1st and 2nd Episodes, 10 C2F1S4......................... 1.0027
Therapy Visits.
10215........................... 1st and 2nd Episodes, 11 to C2F1S5......................... 1.1186
13 Therapy Visits.
10221........................... 1st and 2nd Episodes, 0 to C2F2S1......................... 1.2345
5 Therapy Visits.
10222........................... 1st and 2nd Episodes, 6 C2F2S2......................... 1.3504
Therapy Visits.
10223........................... 1st and 2nd Episodes, 7 to C2F2S3......................... 1.5410
9 Therapy Visits.
10224........................... 1st and 2nd Episodes, 10 C2F2S4......................... 1.7316
Therapy Visits.
10225........................... 1st and 2nd Episodes, 11 to C2F2S5......................... 0.6339
13 Therapy Visits.
10231........................... 1st and 2nd Episodes, 0 to C2F3S1......................... 0.7637
5 Therapy Visits.
10232........................... 1st and 2nd Episodes, 6 C2F3S2......................... 0.8935
Therapy Visits.
10233........................... 1st and 2nd Episodes, 7 to C2F3S3......................... 1.0234
9 Therapy Visits.
10234........................... 1st and 2nd Episodes, 10 C2F3S4......................... 1.1532
Therapy Visits.
10235........................... 1st and 2nd Episodes, 11 to C2F3S5......................... 1.2830
13 Therapy Visits.
10311........................... 1st and 2nd Episodes, 0 to C3F1S1......................... 1.4994
5 Therapy Visits.
10312........................... 1st and 2nd Episodes, 6 C3F1S2......................... 1.7157
Therapy Visits.
10313........................... 1st and 2nd Episodes, 7 to C3F1S3......................... 0.7492
9 Therapy Visits.
10314........................... 1st and 2nd Episodes, 10 C3F1S4......................... 0.8661
Therapy Visits.
10315........................... 1st and 2nd Episodes, 11 to C3F1S5......................... 0.9830
13 Therapy Visits.
10321........................... 1st and 2nd Episodes, 0 to C3F2S1......................... 1.0999
5 Therapy Visits.
10322........................... 1st and 2nd Episodes, 6 C3F2S2......................... 1.2169
Therapy Visits.
10323........................... 1st and 2nd Episodes, 7 to C3F2S3......................... 1.3338
9 Therapy Visits.
10324........................... 1st and 2nd Episodes, 10 C3F2S4......................... 1.5400
Therapy Visits.
10325........................... 1st and 2nd Episodes, 11 to C3F2S5......................... 1.7461
13 Therapy Visits.
10331........................... 1st and 2nd Episodes, 0 to C3F3S1......................... 0.8079
5 Therapy Visits.
10332........................... 1st and 2nd Episodes, 6 C3F3S2......................... 0.9290
Therapy Visits.
10333........................... 1st and 2nd Episodes, 7 to C3F3S3......................... 1.0501
9 Therapy Visits.
[[Page 39855]]
10334........................... 1st and 2nd Episodes, 10 C3F3S4......................... 1.1712
Therapy Visits.
10335........................... 1st and 2nd Episodes, 11 to C3F3S5......................... 1.2923
13 Therapy Visits.
21111........................... 1st and 2nd Episodes, 14 to C1F1S1......................... 1.4134
15 Therapy Visits.
21112........................... 1st and 2nd Episodes, 16 to C1F1S2......................... 1.6167
17 Therapy Visits.
21113........................... 1st and 2nd Episodes, 18 to C1F1S3......................... 1.8200
19 Therapy Visits.
21121........................... 1st and 2nd Episodes, 14 to C1F2S1......................... 0.6876
15 Therapy Visits.
21122........................... 1st and 2nd Episodes, 16 to C1F2S2......................... 0.8424
17 Therapy Visits.
21123........................... 1st and 2nd Episodes, 18 to C1F2S3......................... 0.9973
19 Therapy Visits.
21131........................... 1st and 2nd Episodes, 14 to C1F3S1......................... 1.1522
15 Therapy Visits.
21132........................... 1st and 2nd Episodes, 16 to C1F3S2......................... 1.3071
17 Therapy Visits.
21133........................... 1st and 2nd Episodes, 18 to C1F3S3......................... 1.4619
19 Therapy Visits.
21211........................... 1st and 2nd Episodes, 14 to C2F1S1......................... 1.6962
15 Therapy Visits.
21212........................... 1st and 2nd Episodes, 16 to C2F1S2......................... 1.9304
17 Therapy Visits.
21213........................... 1st and 2nd Episodes, 18 to C2F1S3......................... 0.8029
19 Therapy Visits.
21221........................... 1st and 2nd Episodes, 14 to C2F2S1......................... 0.9449
15 Therapy Visits.
21222........................... 1st and 2nd Episodes, 16 to C2F2S2......................... 1.0868
17 Therapy Visits.
21223........................... 1st and 2nd Episodes, 18 to C2F2S3......................... 1.2288
19 Therapy Visits.
21231........................... 1st and 2nd Episodes, 14 to C2F3S1......................... 1.3707
15 Therapy Visits.
21232........................... 1st and 2nd Episodes, 16 to C2F3S2......................... 1.5127
17 Therapy Visits.
21233........................... 1st and 2nd Episodes, 18 to C2F3S3......................... 1.7368
19 Therapy Visits.
21311........................... 1st and 2nd Episodes, 14 to C3F1S1......................... 1.9609
15 Therapy Visits.
21312........................... 1st and 2nd Episodes, 16 to C3F1S2......................... 0.8616
17 Therapy Visits.
21313........................... 1st and 2nd Episodes, 18 to C3F1S3......................... 1.0077
19 Therapy Visits.
21321........................... 1st and 2nd Episodes, 14 to C3F2S1......................... 1.1539
15 Therapy Visits.
21322........................... 1st and 2nd Episodes, 16 to C3F2S2......................... 1.3000
17 Therapy Visits.
21323........................... 1st and 2nd Episodes, 18 to C3F2S3......................... 1.4462
19 Therapy Visits.
21331........................... 1st and 2nd Episodes, 14 to C3F3S1......................... 1.5923
15 Therapy Visits.
21332........................... 1st and 2nd Episodes, 16 to C3F3S2......................... 1.8135
17 Therapy Visits.
21333........................... 1st and 2nd Episodes, 18 to C3F3S3......................... 2.0347
19 Therapy Visits.
22111........................... 3rd+ Episodes, 14 to 15 C1F1S1......................... 0.4805
Therapy Visits.
22112........................... 3rd+ Episodes, 16 to 17 C1F1S2......................... 0.6403
Therapy Visits.
22113........................... 3rd+ Episodes, 18 to 19 C1F1S3......................... 0.8001
Therapy Visits.
22121........................... 3rd+ Episodes, 14 to 15 C1F2S1......................... 0.9599
Therapy Visits.
22122........................... 3rd+ Episodes, 16 to 17 C1F2S2......................... 1.1197
Therapy Visits.
22123........................... 3rd+ Episodes, 18 to 19 C1F2S3......................... 1.2795
Therapy Visits.
22131........................... 3rd+ Episodes, 14 to 15 C1F3S1......................... 1.4633
Therapy Visits.
22132........................... 3rd+ Episodes, 16 to 17 C1F3S2......................... 1.6471
Therapy Visits.
22133........................... 3rd+ Episodes, 18 to 19 C1F3S3......................... 1.8309
Therapy Visits.
22211........................... 3rd+ Episodes, 14 to 15 C2F1S1......................... 0.5648
Therapy Visits.
22212........................... 3rd+ Episodes, 16 to 17 C2F1S2......................... 0.7109
Therapy Visits.
22213........................... 3rd+ Episodes, 18 to 19 C2F1S3......................... 0.8570
Therapy Visits.
22221........................... 3rd+ Episodes, 14 to 15 C2F2S1......................... 1.0031
Therapy Visits.
22222........................... 3rd+ Episodes, 16 to 17 C2F2S2......................... 1.1492
Therapy Visits.
22223........................... 3rd+ Episodes, 18 to 19 C2F2S3......................... 1.2952
Therapy Visits.
22231........................... 3rd+ Episodes, 14 to 15 C2F3S1......................... 1.4806
Therapy Visits.
22232........................... 3rd+ Episodes, 16 to 17 C2F3S2......................... 1.6659
Therapy Visits.
22233........................... 3rd+ Episodes, 18 to 19 C2F3S3......................... 1.8512
Therapy Visits.
22311........................... 3rd+ Episodes, 14 to 15 C3F1S1......................... 0.6114
Therapy Visits.
22312........................... 3rd+ Episodes, 16 to 17 C3F1S2......................... 0.7644
Therapy Visits.
22313........................... 3rd+ Episodes, 18 to 19 C3F1S3......................... 0.9173
Therapy Visits.
22321........................... 3rd+ Episodes, 14 to 15 C3F2S1......................... 1.0703
Therapy Visits.
22322........................... 3rd+ Episodes, 16 to 17 C3F2S2......................... 1.2232
Therapy Visits.
22323........................... 3rd+ Episodes, 18 to 19 C3F2S3......................... 1.3761
Therapy Visits.
22331........................... 3rd+ Episodes, 14 to 15 C3F3S1......................... 1.5581
Therapy Visits.
22332........................... 3rd+ Episodes, 16 to 17 C3F3S2......................... 1.7401
Therapy Visits.
22333........................... 3rd+ Episodes, 18 to 19 C3F3S3......................... 1.9222
Therapy Visits.
30111........................... 3rd+ Episodes, 0 to 5 C1F1S1......................... 0.4961
Therapy Visits.
30112........................... 3rd+ Episodes, 6 Therapy C1F1S2......................... 0.6700
Visits.
30113........................... 3rd+ Episodes, 7 to 9 C1F1S3......................... 0.8440
Therapy Visits.
30114........................... 3rd+ Episodes, 10 Therapy C1F1S4......................... 1.0180
Visits.
30115........................... 3rd+ Episodes, 11 to 13 C1F1S5......................... 1.1920
Therapy Visits.
30121........................... 3rd+ Episodes, 0 to 5 C1F2S1......................... 1.3660
Therapy Visits.
30122........................... 3rd+ Episodes, 6 Therapy C1F2S2......................... 1.5546
Visits.
30123........................... 3rd+ Episodes, 7 to 9 C1F2S3......................... 1.7433
Therapy Visits.
30124........................... 3rd+ Episodes, 10 Therapy C1F2S4......................... 1.9320
Visits.
30125........................... 3rd+ Episodes, 11 to 13 C1F2S5......................... 0.5803
Therapy Visits.
30131........................... 3rd+ Episodes, 0 to 5 C1F3S1......................... 0.7406
Therapy Visits.
30132........................... 3rd+ Episodes, 6 Therapy C1F3S2......................... 0.9009
Visits.
[[Page 39856]]
30133........................... 3rd+ Episodes, 7 to 9 C1F3S3......................... 1.0612
Therapy Visits.
30134........................... 3rd+ Episodes, 10 Therapy C1F3S4......................... 1.2214
Visits.
30135........................... 3rd+ Episodes, 11 to 13 C1F3S5......................... 1.3817
Therapy Visits.
30211........................... 3rd+ Episodes, 0 to 5 C2F1S1......................... 1.5719
Therapy Visits.
30212........................... 3rd+ Episodes, 6 Therapy C2F1S2......................... 1.7621
Visits.
30213........................... 3rd+ Episodes, 7 to 9 C2F1S3......................... 1.9523
Therapy Visits.
30214........................... 3rd+ Episodes, 10 Therapy C2F1S4......................... 0.6270
Visits.
30215........................... 3rd+ Episodes, 11 to 13 C2F1S5......................... 0.7941
Therapy Visits.
30221........................... 3rd+ Episodes, 0 to 5 C2F2S1......................... 0.9612
Therapy Visits.
30222........................... 3rd+ Episodes, 6 Therapy C2F2S2......................... 1.1284
Visits.
30223........................... 3rd+ Episodes, 7 to 9 C2F2S3......................... 1.2955
Therapy Visits.
30224........................... 3rd+ Episodes, 10 Therapy C2F2S4......................... 1.4626
Visits.
30225........................... 3rd+ Episodes, 11 to 13 C2F2S5......................... 1.6495
Therapy Visits.
30231........................... 3rd+ Episodes, 0 to 5 C2F3S1......................... 1.8364
Therapy Visits.
30232........................... 3rd+ Episodes, 6 Therapy C2F3S2......................... 2.0233
Visits.
30233........................... 3rd+ Episodes, 7 to 9 C2F3S3......................... 0.6211
Therapy Visits.
30234........................... 3rd+ Episodes, 10 Therapy C2F3S4......................... 0.8152
Visits.
30235........................... 3rd+ Episodes, 11 to 13 C2F3S5......................... 1.0093
Therapy Visits.
30311........................... 3rd+ Episodes, 0 to 5 C3F1S1......................... 1.2034
Therapy Visits.
30312........................... 3rd+ Episodes, 6 Therapy C3F1S2......................... 1.3975
Visits.
30313........................... 3rd+ Episodes, 7 to 9 C3F1S3......................... 1.5916
Therapy Visits.
30314........................... 3rd+ Episodes, 10 Therapy C3F1S4......................... 1.7826
Visits.
30315........................... 3rd+ Episodes, 11 to 13 C3F1S5......................... 1.9736
Therapy Visits.
30321........................... 3rd+ Episodes, 0 to 5 C3F2S1......................... 2.1647
Therapy Visits.
30322........................... 3rd+ Episodes, 6 Therapy C3F2S2......................... 0.7054
Visits.
30323........................... 3rd+ Episodes, 7 to 9 C3F2S3......................... 0.8858
Therapy Visits.
30324........................... 3rd+ Episodes, 10 Therapy C3F2S4......................... 1.0662
Visits.
30325........................... 3rd+ Episodes, 11 to 13 C3F2S5......................... 1.2466
Therapy Visits.
30331........................... 3rd+ Episodes, 0 to 5 C3F3S1......................... 1.4269
Therapy Visits.
30332........................... 3rd+ Episodes, 6 Therapy C3F3S2......................... 1.6073
Visits.
30333........................... 3rd+ Episodes, 7 to 9 C3F3S3......................... 1.7999
Therapy Visits.
30334........................... 3rd+ Episodes, 10 Therapy C3F3S4......................... 1.9924
Visits.
30335........................... 3rd+ Episodes, 11 to 13 C3F3S5......................... 2.1850
Therapy Visits.
40111........................... All Episodes, 20+ Therapy C1F1S1......................... 0.7521
Visits.
40121........................... All Episodes, 20+ Therapy C1F2S1......................... 0.9393
Visits.
40131........................... All Episodes, 20+ Therapy C1F3S1......................... 1.1265
Visits.
40211........................... All Episodes, 20+ Therapy C2F1S1......................... 1.3138
Visits.
40221........................... All Episodes, 20+ Therapy C2F2S1......................... 1.5010
Visits.
40231........................... All Episodes, 20+ Therapy C2F3S1......................... 1.6882
Visits.
40311........................... All Episodes, 20+ Therapy C3F1S1......................... 1.8774
Visits.
40321........................... All Episodes, 20+ Therapy C3F2S1......................... 2.0667
Visits.
40331........................... All Episodes, 20+ Therapy C3F3S1......................... 2.2559
Visits.
----------------------------------------------------------------------------------------------------------------
To ensure the changes to the HH PPS case-mix weights are
implemented in a budget neutral manner, we would apply a case-mix
budget neutrality factor to the CY 2016 national, standardized 60-day
episode payment rate (see section III.B.1. of this proposed rule). The
case-mix budget neutrality factor is calculated as the ratio of total
payments when the CY 2016 HH PPS case-mix weights (developed using CY
2014 claims data) are applied to CY 2014 utilization (claims) data to
total payments when CY 2015 HH PPS case-mix weights (developed using CY
2013 claims data) are applied to CY 2014 utilization data. This
produces a case-mix budget neutrality factor for CY 2016 of 1.0141,
based on CY 2014 claims data as of December 31, 2014.
2. Proposed Reduction to the National, Standardized 60-Day Episode
Payment Rate To Account for Nominal Case-Mix Growth
Section 1895(b)(3)(B)(iv) of the Act gives the Secretary the
authority to implement payment reductions for nominal case-mix growth
(that is, case-mix growth unrelated to changes in patient acuity).
Previously, we accounted for nominal case-mix growth through case-mix
reductions implemented from 2008 through 2013 (76 FR 68528-68543). As
stated in the 2013 final rule, the goal of the reductions for nominal
case-mix growth is to better align payment with real changes in patient
severity (77 FR 67077). Our analysis of data from CY 2000 through CY
2010 found that only 15.97 percent of the total case-mix change was
real and 84.03 percent of total case-mix change was nominal (77 FR
41553). In the CY 2015 HH PPS final rule (79 FR 66032), we estimated
that total case-mix increased by 2.76 percent between CY 2012 and CY
2013 and of that amount, we estimated that 2.32 percent was a result of
nominal case-mix growth (2.76 - (2.76 x 0.1597)). However, for 2015, we
did not implement a reduction to the 2015 national, standardized 60-day
episode payment amount to account for nominal case-mix growth, but
stated that we would continue to monitor case-mix growth and may
consider proposing nominal case-mix reductions in the future. Since the
publication of the CY 2015 HH PPS final rule (79 FR 66032),
[[Page 39857]]
MedPAC reported on their assessment of the impact of the mandated
rebasing adjustments on quality of and beneficiary access to home
health care as required by section 3131(a) of the Affordable Care Act.
As noted in section III.A.2 of this proposed rule, MedPAC concluded
that quality of care and beneficiary access to care are unlikely to be
negatively affected by the rebasing adjustments. We further estimate
that case-mix increased by an additional 1.41 percent between CY 2013
and CY 2014 (as evidenced by the budget neutrality factor of 1.0141
percent described in section III.B.1 above). In applying the 15.97
percent estimate of real case-mix growth to the total estimated case-
mix growth from CY 2013 to CY 2014 (1.41 percent), we estimate that
case-mix increased by 1.18 percent (1.41 - (1.41 x 0.1597)) as a result
of nominal case-mix growth (that is, case-mix growth unrelated to
changes in patient acuity). Given the observed nominal case-mix growth
of 2.32 percent in 2013 and 1.18 percent in 2014, the reduction to
offset the nominal case-mix growth for these 2 years would be 3.41
percent (1 - 1/(1.0232 x 1.0118) = 0.0341).
We are proposing to implement this 3.41 percent reduction in equal
increments over 2 years. Specifically, in addition to continuing our
third year of implementation of the rebasing adjustments required under
section 3131(a) of the Affordable Care Act, we are proposing to apply a
1.72 percent (1 - 1/(1.0232 x 1.0118)1/2 = 1.72 percent)
reduction to the national, standardized 60-day episode payment rate
each year for 2 years, CY 2016 and CY 2017, under the ongoing authority
of section 1895(b)(3)(B)(iv) of the Act. These reductions would adjust
the national, standardized 60-day episode payment rate to account for
nominal case-mix growth between CY 2012 and CY 2014 built into the
episode payment rate through the 2015 and 2016 budget neutrality
factors. The reductions will result in Medicare paying more accurately
for the delivery of home health services and are separate from the
rebasing adjustments finalized in CY 2014 under section
1895(b)(3)(A)(iii) of the Act, which were calculated using CY 2012
claims and CY 2011 HHA cost report data (which was the most current,
complete data at the time of the CY 2014 HH PPS proposed and final
rules). We will continue to monitor case-mix growth and may consider
whether to propose additional nominal case-mix reductions in future
rulemaking.
We invite comments on the proposed reduction to the national,
standardized 60-day episode payment amount of 1.72 percent in CY 2016
and 1.72 percent in CY 2017 to account for nominal case-mix growth from
CY 2012 through CY 2014 and the associated changes in the regulations
text at Sec. 484.220.
C. CY 2016 Home Health Rate Update
1. CY 2016 Home Health Market Basket Update
Section 1895(b)(3)(B) of the Act requires that the standard
prospective payment amounts for CY 2015 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. We note that the proposed methodology for calculating and
applying the MFP adjustment to the HHA payment update is similar to the
methodology used in other Medicare provider payment systems as required
by section 3401 of the Affordable Care Act.
Multifactor productivity is derived by subtracting the contribution
of labor and capital input growth from output growth. The projections
of the components of MFP are currently produced by IGI, a nationally
recognized economic forecasting firm with which CMS contracts to
forecast the components of the market basket and MFP. As described in
the CY 2015 HH PPS proposed rule (79 FR 38384 through 38386), in order
to generate a forecast of MFP, IGI replicated the MFP measure
calculated by the BLS using a series of proxy variables derived from
IGI's U.S. macroeconomic models. In the CY 2015 HH PPS proposed rule,
we identified each of the major MFP component series employed by the
BLS to measure MFP as well as provided the corresponding concepts
determined to be the best available proxies for the BLS series.
Beginning with the CY 2016 rulemaking cycle, the MFP adjustment is
calculated using a revised series developed by IGI to proxy the
aggregate capital inputs. Specifically, IGI has replaced the Real
Effective Capital Stock used for Full Employment GDP with a forecast of
BLS aggregate capital inputs recently developed by IGI using a
regression model. This series provides a better fit to the BLS capital
inputs as measured by the differences between the actual BLS capital
input growth rates and the estimated model growth rates over the
historical time period. Therefore, we are using IGI's most recent
forecast of the BLS capital inputs series in the MFP calculations
beginning with the CY 2016 rulemaking cycle. A complete description of
the MFP projection methodology is available on our Web site at https://www.cms.gov/Research-Statistics-Data-and-Systems/Statistics-Trends-and-Reports/MedicareProgramRatesStats/MarketBasketResearch.html. Although
we discuss the IGI changes to the MFP proxy series in this proposed
rule, in the future, when IGI makes changes to the MFP methodology, we
will announce them on our Web site rather than in the annual
rulemaking.
Using IGI's first quarter 2015 forecast, the MFP adjustment for CY
2016 (the 10-year moving average of MFP for the period ending CY 2016)
is projected to be 0.6 percent. Thus, in accordance with section
1895(b)(3)(B)(iii) of the Act, we propose to base the CY 2016 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 2.9
percent based on IGI's first quarter 2015 forecast). We propose to then
reduce this percentage increase by the current estimate of the MFP
adjustment for CY 2016 of 0.6 percentage point (the 10-year moving
average of MFP for the period ending CY 2016 based on IGI's first
quarter 2015 forecast), in accordance with 1895(b)(3)(B)(vi).
Therefore, the current estimate of the CY 2016 HH update is 2.3 percent
(2.9 percent market basket update, less 0.6 percentage point MFP
adjustment). Furthermore, we note that if more recent data are
subsequently
[[Page 39858]]
available (for example, a more recent estimate of the market basket and
MFP adjustment), we would use such data to determine the CY 2016 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 2016, the home health update
would be 0.3 percent (2.3 percent minus 2 percentage points).
2. CY 2016 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 2016, 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 2016, the updated wage data are for hospital cost
reporting periods beginning on or after October 1, 2011 and before
October 1, 2012 (FY 2012 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). 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. In adopting the CBSA geographic designations, we
provided a one-year transition in CY 2006 with a blended wage index for
all sites of service. For CY 2006, the wage index for each geographic
area consisted of a blend of 50 percent of the CY 2006 MSA-based wage
index and 50 percent of the CY 2006 CBSA-based wage index. We referred
to the blended wage index as the CY 2006 HH PPS transition wage index.
As discussed in the CY 2006 HH PPS final rule (70 FR 68132), since the
expiration of this one-year transition on December 31, 2006, we have
used the full CBSA-based wage index values.
In this proposed rule, 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, and thus, no hospital wage data on which to base the
calculation of the CY 2015 HH PPS wage index. 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 2016, 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 2016, the only urban area without inpatient
hospital wage data is Hinesville, GA (CBSA 25980).
b. Update
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 newest OMB
delineations, as described in OMB Bulletin No. 13-01, beginning in CY
2015, including a one-year transition with a blended wage index for CY
2015. Because the one-year transition period expires at the end of CY
2015, the proposed HH PPS wage index for CY 2016 is fully based on the
revised OMB delineations adopted in CY 2015. The proposed CY 2016 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. CY 2016 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
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 2016 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:
[[Page 39859]]
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 2016 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 2016 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.1, a
nominal case-mix growth adjustment described in section III.B.2, 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 2016 wage index and
compared it to our simulation of total payments for non-LUPA episodes
using the 2015 wage index. By dividing the total payments for non-LUPA
episodes using the 2016 wage index by the total payments for non-LUPA
episodes using the 2015 wage index, we obtain a wage index budget
neutrality factor of 1.0006. We would apply the wage index budget
neutrality factor of 1.0006 to the CY 2016 national, standardized 60-
day episode rate.
As discussed in section III.B.1 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 2016 national, standardized 60-day episode payment rate. The
case-mix weight budget neutrality factor is calculated as the ratio of
total payments when CY 2016 case-mix weights are applied to CY 2014
utilization (claims) data to total payments when CY 2015 case-mix
weights are applied to CY 2014 utilization data. The case-mix budget
neutrality factor for CY 2016 would be 1.0141 as described in section
III.B.1 of this proposed rule.
Next, as discussed in section III.B.2 of this proposed rule, we
would apply a reduction of 1.72 percent to the national, standardized
60-day episode payment rate in CY 2016 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
payment rates by the CY 2016 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 CY 2016 national,
standardized 60-day episode payment rate is calculated in Table 10.
Table 10--CY 2016 60-Day National, Standardized 60-Day Episode Payment Amount
--------------------------------------------------------------------------------------------------------------------------------------------------------
CY 2016
Wage index Case-mix Nominal case- CY 2016 CY 2016 HH National,
CY 2015 National, standardized 60-day episode budget weights budget mix growth Rebasing Payment update standardized
payment neutrality neutrality adjustment (1- adjustment percentage 60-day episode
factor factor 0.0172) payment
--------------------------------------------------------------------------------------------------------------------------------------------------------
$2,961.38......................................... x 1.0006 x 1.0141 x 0.9828 -$80.95 x 1.023 $2,938.37
--------------------------------------------------------------------------------------------------------------------------------------------------------
The CY 2016 national, standardized 60-day episode payment rate for
an HHA that does not submit the required quality data is updated by the
CY 2016 HH payment update (2.3 percent) minus 2 percentage points and
is shown in Table 11.
[[Page 39860]]
Table 11--For HHAs That Do Not Submit the Quality Data--CY 2015 National, Standardized 60-Day Episode Payment Amount
--------------------------------------------------------------------------------------------------------------------------------------------------------
CY 2016 HH
Wage index Case-mix Nominal case- Payment update CY 2016
CY 2015 National, standardized 60-day episode budget weights budget mix growth CY 2016 percentage National,
payment neutrality neutrality adjustment (1- Rebasing minus 2 standardized
factor factor 0.0172) adjustment percentage 60-day episode
points payment
--------------------------------------------------------------------------------------------------------------------------------------------------------
$2,961.38......................................... x 1.0006 x 1.0141 x 0.9828 -$80.95 x 1.003 $2,880.92
--------------------------------------------------------------------------------------------------------------------------------------------------------
c. CY 2016 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 CY 2016 national per-visit rates, we start with
the CY 2015 national per-visit rates. We then apply a wage index budget
neutrality factor to ensure budget neutrality for LUPA per-visit
payments and 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 2016 wage index and comparing it
to simulated total payments for LUPA episodes using the 2015 wage
index. By dividing the total payments for LUPA episodes using the 2016
wage index by the total payments for LUPA episodes using the 2015 wage
index, we obtain a wage index budget neutrality factor of 1.0006. We
would apply the wage index budget neutrality factor of 1.0006 to the CY
2016 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 CY 2016 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 CY 2016
national per-visit rates are shown in Tables 12 and 13.
Table 12--CY 2016 National Per-Visit Payment Amounts for HHAs That DO Submit the Required Quality Data
--------------------------------------------------------------------------------------------------------------------------------------------------------
CY 2016 HH
HH Discipline type CY 2015 Per-visit Wage index budget CY 2016 Rebasing Payment update CY 2016 Per-visit
payment neutrality factor adjustment percentage payment
--------------------------------------------------------------------------------------------------------------------------------------------------------
Home Health Aide......................................... $57.89 x 1.0006 + $1.79 x 1.023 $61.09
Medical Social Services.................................. 204.91 x 1.0006 + 6.34 x 1.023 216.23
Occupational Therapy..................................... 140.70 x 1.0006 + 4.35 x 1.023 148.47
Physical Therapy......................................... 139.75 x 1.0006 + 4.32 x 1.023 147.47
Skilled Nursing.......................................... 127.83 x 1.0006 + 3.96 x 1.023 134.90
Speech-Language Pathology................................ 151.88 x 1.0006 + 4.70 x 1.023 160.27
--------------------------------------------------------------------------------------------------------------------------------------------------------
The CY 2016 per-visit payment rates for an HHA that does not submit
the required quality data are updated by the CY 2016 HH payment update
(2.3 percent) minus 2 percentage points and is shown in Table 13.
Table 13--CY 2016 National Per-Visit Payment Amounts for HHAs That DO NOT Submit the Required Quality Data
--------------------------------------------------------------------------------------------------------------------------------------------------------
CY 2016 HH
Payment update
HH Discipline type CY 2015 Per- Wage index budget CY 2016 Rebasing percentage minus CY 2016 Per-
visit rates neutrality factor adjustment 2 percentage visit rates
points
--------------------------------------------------------------------------------------------------------------------------------------------------------
Home Health Aide......................................... $57.89 x 1.0006 + $1.79 x 1.003 $59.89
Medical Social Services.................................. 204.91 x 1.0006 + 6.34 x 1.003 212.01
Occupational Therapy..................................... 140.70 x 1.0006 + 4.35 x 1.003 145.57
Physical Therapy......................................... 139.75 x 1.0006 + 4.32 x 1.003 144.59
Skilled Nursing.......................................... 127.83 x 1.0006 + 3.96 x 1.003 132.26
Speech-Language Pathology................................ 151.88 x 1.0006 + 4.70 x 1.003 157.14
--------------------------------------------------------------------------------------------------------------------------------------------------------
[[Page 39861]]
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 $248.90
(1.8451 multiplied by $134.90), subject to area wage adjustment.
e. CY 2016 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 CY 2016 NRS conversion factor, we start with the 2015 NRS
conversion factor ($53.23) 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 CY 2016 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 NRS conversion factor for CY 2016 is shown in Table 14.
Table 14--CY 2016 NRS Conversion Factor for HHAs That DO Submit the Required Quality Data
----------------------------------------------------------------------------------------------------------------
CY 2016 HH
CY 2015 NRS conversion factor CY 2016 Rebasing Payment update CY 2016 NRS
adjustment percentage conversion factor
----------------------------------------------------------------------------------------------------------------
$53.23.............................................. x 0.9718 x 1.023 $52.92
----------------------------------------------------------------------------------------------------------------
Using the CY 2015 NRS conversion factor, the payment amounts for
the six severity levels are shown in Table 15.
Table 15--CY 2016 NRS Payment Amounts for HHAs That DO Submit the Required Quality Data
----------------------------------------------------------------------------------------------------------------
CY 2016 NRS
Severity level Points (scoring) Relative weight Payment amounts
----------------------------------------------------------------------------------------------------------------
1.......................................... 0............................ 0.2698 $14.28
2.......................................... 1 to 14...................... 0.9742 51.55
3.......................................... 15 to 27..................... 2.6712 141.36
4.......................................... 28 to 48..................... 3.9686 210.02
5.......................................... 49 to 98..................... 6.1198 323.86
6.......................................... 99+.......................... 10.5254 557.00
----------------------------------------------------------------------------------------------------------------
For HHAs that do not submit the required quality data, we again
begin with the CY 2015 NRS conversion factor ($53.23) 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 CY 2016 HH payment update percentage (2.3 percent) minus
2 percentage points. The CY 2016 NRS conversion factor for HHAs that do
not submit quality data is shown in Table 16.
Table 16--CY 2016 NRS Conversion Factor for HHAs That DO NOT Submit the Required Quality Data
----------------------------------------------------------------------------------------------------------------
CY 2016 HH
CY 2016 Rebasing Payment update CY 2016 NRS
CY 2015 NRS Conversion factor adjustment percentage minus 2 Conversion factor
percentage points
----------------------------------------------------------------------------------------------------------------
$53.23.............................................. x 0.9718 x 1.003 $51.88
----------------------------------------------------------------------------------------------------------------
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.
[[Page 39862]]
Table 17--CY 2016 NRS Payment Amounts for HHAs That DO NOT Submit the Required Quality Data
----------------------------------------------------------------------------------------------------------------
CY 2016 NRS
Severity level Points (scoring) Relative weight Payment amounts
----------------------------------------------------------------------------------------------------------------
1.......................................... 0............................ 0.2698 $14.00
2.......................................... 1 to 14...................... 0.9742 50.54
3.......................................... 15 to 27..................... 2.6712 138.58
4.......................................... 28 to 48..................... 3.9686 205.89
5.......................................... 49 to 98..................... 6.1198 317.50
6.......................................... 99+.......................... 10.5254 546.06
----------------------------------------------------------------------------------------------------------------
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) (Pub. L. 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 2016, 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--CY 2016 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
--------------------------------------------------------------------------------------------------------------------------------------------------------
CY 2016
Rural CY 2016 Rural
Multiply by the 3 national, Multiply by the 3 national,
CY 2016 National, standardized 60-day episode percent rural add- standardized CY 2016 National, standardized 60- percent rural add- standardized 60-
payment rate on 60-day day episode payment rate on day episode
episode payment rate
payment rate
--------------------------------------------------------------------------------------------------------------------------------------------------------
$2,938.37..................................... x 1.03 $3,026.52 $2,880.92........................ x 1.03 $2,967.35
--------------------------------------------------------------------------------------------------------------------------------------------------------
Table 19--CY 2016 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
------------------------------------------------------------------------------------------------------------
HH Discipline type Multiply by the Multiply by the
CY 2016 Per- 3 percent rural CY 2016 Rural per- CY 2016 Per- 3 percent rural CY 2016 Rural
visit rate add-on visit rates visit rate add-on per-visit rates
--------------------------------------------------------------------------------------------------------------------------------------------------------
HH Aide.................................... $61.09 x 1.03 $62.92 $59.89 x 1.03 $61.69
MSS........................................ 216.23 x 1.03 222.72 212.01 x 1.03 218.37
OT......................................... 148.47 x 1.03 152.92 145.57 x 1.03 149.94
PT......................................... 147.47 x 1.03 151.89 144.59 x 1.03 148.93
SN......................................... 134.90 x 1.03 138.95 132.26 x 1.03 136.23
SLP........................................ 160.27 x 1.03 165.08 157.14 x 1.03 161.85
--------------------------------------------------------------------------------------------------------------------------------------------------------
[[Page 39863]]
Table 20--CY 2016 NRS Conversion Factor for Services Provided in Rural Areas
--------------------------------------------------------------------------------------------------------------------------------------------------------
For HHAs that DO submit quality data For HHAs that DO NOT submit quality data
--------------------------------------------------------------------------------------------------------------------------------------------------------
CY 2016
Multiply by the 3 Rural NRS Multiply by the 3 CY 2016 Rural NRS
CY 2016 Conversion factor percent rural add- conversion CY 2016 Conversion factor percent rural add- conversion factor
on factor on
--------------------------------------------------------------------------------------------------------------------------------------------------------
$52.92......................................... x 1.03 $54.51 $51.88............................ x 1.03 $53.44
--------------------------------------------------------------------------------------------------------------------------------------------------------
Table 21--CY 2016 NRS Payment Amounts for Services Provided in Rural Areas
--------------------------------------------------------------------------------------------------------------------------------------------------------
For HHAs that DO submit quality For HHAs that DO NOT submit
data (CY 2016 NRS conversion factor quality data (CY 2016 NRS
= $54.51 Conversion Factor = $53.44)
Severity level Points (scoring) ------------------------------------------------------------------------
CY 2016 NRS CY 2016 NRS
Relative weight Payment amounts Relative weight Payment amounts
for rural areas for rural areas
--------------------------------------------------------------------------------------------------------------------------------------------------------
1............................................ 0............................... 0.2698 $14.71 0.2698 $14.42
2............................................ 1 to 14......................... 0.9742 53.10 0.9742 52.06
3............................................ 15 to 27........................ 2.6712 145.61 2.6712 142.75
4............................................ 28 to 48........................ 3.9686 216.33 3.9686 212.08
5............................................ 49 to 98........................ 6.1198 333.59 6.1198 327.04
6............................................ 99+............................. 10.5254 573.74 10.5254 562.48
--------------------------------------------------------------------------------------------------------------------------------------------------------
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 HH 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 final rule (74 FR 58080 through 58087), we
discussed excessive growth in outlier payments, primarily the result of
unusually high outlier payments in a few areas of the country. 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 and, in the absence of corrective
measures, would continue do to so. Consequently, we assessed the
appropriateness of taking action to curb outlier abuse. To mitigate
possible billing vulnerabilities associated with excessive outlier
payments and adhere to our statutory limit on outlier payments, we
adopted 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 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 HH expenditure). 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 requires the Secretary to reduce the HH
PPS payment rates such that aggregate HH PPS payments are 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 it to state
that the Secretary may provide for an addition or adjustment to the
payment amount for outlier episodes because of their unusual variation
in the type or amount of medically necessary care. 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 and outlier payments as a percent of total payments are capped 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
[[Page 39864]]
be paid as outlier payments, and apply a 10 percent agency-level
outlier cap.
2. Fixed Dollar Loss (FDL) Ratio and Loss-Sharing 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.
For this proposed rule, simulating payments using preliminary CY
2014 claims data (as of December 31, 2014) and the CY 2015 payment
rates (79 FR 66088 through 66092), we estimate that outlier payments in
CY 2015 would comprise 2.02 percent of total payments. Based on
simulations using CY 2014 claims data and the CY 2016 payments rates in
section III.C.3 of this proposed rule, we estimate that outlier
payments would comprise approximately 2.34 percent of total HH PPS
payments in CY 2016, a percent change of almost 16 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
similar rebasing adjustments and case-mix growth reduction would also
occur for 2017, and hence a similar anticipated increase in the outlier
payments, we estimate that for CY 2017 outlier payments as a percent of
total HH PPS payments would exceed 2.5 percent.
At this time, we are not proposing a change to the FDL ratio or
loss-sharing ratio for CY 2016 as we believe that maintaining an FDL of
0.45 and a loss-sharing ratio of 0.80 are appropriate given the
percentage of outlier payments is estimated to increase as a result of
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
nominal case-mix growth reduction. 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 2014 claims
data as of June 30, 2015). We would continue to monitor the percent of
total HH PPS payments paid as outlier payments to determine if future
adjustments to either the FDL ratio or loss-sharing ratio are
warranted.
E. Report to Congress on the Home Health Study Required by Section
3131(d) of the Affordable Care Act and an Update on Subsequent Research
and Analysis
The current home health prospective payment system (HH PPS) pays a
determined amount for a 60-day episode of care adjusted for case mix
using 153 home health resource groups (HHRGs). The 153 HHRGs are
determined based on the amount of therapy provided, the episode's
timing in a sequence of episodes, and the patient's clinical and
functional status determined from data reported on the Outcome and
Assessment Information Set (OASIS). There has been criticism that home
health providers have responded to Medicare's payment policy by
altering the level of service provided to patients.\5\ A review of the
literature increasingly indicates that the current HH PPS payment model
drives HHA resource allocation and practice decisions.\6\ Specifically,
research has highlighted the need to examine whether there are
vulnerabilities present within the current HH PPS model that provide
disincentives for serving the most clinically complex and vulnerable
beneficiaries who receive home health care while incentivizing
providers to provide more therapy service than needed to increase their
reimbursement.\7\ There is increasing concern that the current home
health payment system encourages home health providers to deliver the
maximum volume of therapy services while restricting the number of
skilled nursing and home health aide services because of the therapy
payment thresholds.\8\
---------------------------------------------------------------------------
\5\ Rosati, R., Russell, D., Peng, T., Brickner, C., Kurowski,
D., Christopher, M.A., Sheehan, K. (2014). Medicare Home Health
Payment Reform May Jeopardize Access for Clinically Complex and
Socially Vulnerable Patients. Health Affairs. 33(6), 946-956. Doi:
10.1377/hlthaff.2013.1159
\6\ Cabin, W. (2009). Evidence-based Research Challenges Home
Care PPS Patient Benefits, Costs, and Payment Structure. Home Health
Care Management and Practice. 21(4), 240-245. Doi: 10.1177/
10848223088328325
\7\ Ibid.
\8\ Rosati, R., Russell, D., Peng, T., Brickner, C., Kurowski,
D., Christopher, M.A., Sheehan, K. (2014). Medicare Home Health
Payment Reform May Jeopardize Access for Clinically Complex and
Socially Vulnerable Patients. Health Affairs. 33(6), 946-956. Doi:
10.1377/hlthaff.2013.1159
---------------------------------------------------------------------------
This raises the question whether there is a disparity in payment
for those 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.\9\
---------------------------------------------------------------------------
\9\ Ibid.
---------------------------------------------------------------------------
Section 3131(d) of the Affordable Care Act directed 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.\10\ To examine access to Medicare home
health services and payment, relative to cost, for the vulnerable
patient populations, we awarded a contract to L&M Policy Research to
perform extensive analysis of both survey and administrative data.
Specifically, the L&M collected survey data from physicians and HHAs to
examine factors associated with potential access to care issues. The
surveys provided information on whether, and the reasons
[[Page 39865]]
as to why, patients were not placed or admitted for home health
services or experienced delays in receiving home health services, and
information on the characteristics of patients who may have experienced
access issues. L&M also analyzed administrative data through
descriptive and regression analyses to examine the relationship between
patient characteristics and estimated financial margin (difference
between payment and estimated cost). The study focused on margins
because margin differences, particularly those associated with patient
characteristics, indicate that financial incentives may exist in the HH
PPS to provide home health care for certain types of patients over
others. Lower margins, if systematically associated with care for
vulnerable patient populations, may indicate financial disincentives
for HHAs to admit these patients and may create access to care issues
for them.
---------------------------------------------------------------------------
\10\ https://www.cms.gov/Center/Provider-Type/Home-Health-Agency-HHA-Center.html
---------------------------------------------------------------------------
The results of the survey revealed that over 80 percent of HHAs and
over 90 percent of physicians reported that access to home health care
for Medicare fee-for-service beneficiaries in their local area was
excellent or good. When survey respondents reported access issues,
specifically their inability to place or admit Medicare fee-for-service
patients into home health, the most common reason reported was that the
patients did not qualify for the Medicare home health benefit. HHAs and
physicians also cited family or caregiver issues as an important
contributing factor in the inability to admit or place patients. About
17.2 percent of HHAs and 16.7 percent of physicians reported
insufficient payment as an important contributing factor in the
inability to admit or place patients. The survey results suggest that
much of the variation in access to Medicare home health services is
associated with social and personal conditions and therefore CMS'
ability to improve access for certain vulnerable patient populations
through payment policy may be limited.
Analysis of CY 2010 HHA payment and cost data suggests that margins
may differ substantially across the HH PPS case-mix groups. In
addition, particular beneficiary characteristics appear to be strongly
associated with margin, and thus may create financial incentives to
select certain patients over others. Margins were estimated to be lower
in CY 2010 for patients who required parenteral nutrition, who had
traumatic wounds or ulcers, or required substantial assistance in
bathing. Given that these variables are already included in the HH PPS
case-mix system, the results indicate that modifications to the case-
mix system may be needed. Furthermore, in CY 2010, beneficiaries
admitted after acute or post-acute stays or who had high Hierarchical
Condition Category scores or certain poorly-controlled clinical
conditions, such as poorly-controlled pulmonary disorders, were also
associated with substantially lower home health margins. In addition,
other characteristics, such as those describing assistance by informal
caregivers for ADL needs and those describing socio- economic status,
such as dual eligibility for Medicare and Medicaid, were strongly
associated with lower margins. Exploration of potential payment
methodology changes indicated that accounting for additional variables
in HH PPS payment may decrease the difference in estimated margin
between individuals in specific vulnerable subgroups and those not in
the subgroups, thereby potentially decreasing financial incentives to
select certain types of patients over others.
CMS awarded a follow-on contract to Abt Associates to further
explore margin differences across patient characteristics and possible
payment methodology changes suggested by the results of the home health
study. Additionally, we have heard from various stakeholders that the
current payment system methodology is overly complex and does not fully
reflect the range of services provided under the home health benefit,
and thus this follow-on study would look at these aspects of the
current payment system as well.
Under the follow-on contract, Abt Associates convened a Clinical
Workgroup meeting on June 25, 2014 to gain clinical insight from
industry regarding the current HH PPS. Based upon the feedback provided
during the Clinical Workgroup meeting, as well as CMS concerns about
the current model given the findings from the Home Health Study, Abt
Associates was tasked with developing model options for consideration
and discussion. In September 2014, Abt Associates presented several
payment model options for CMS consideration, which were also presented
to a Technical Expert Panel meeting held on January 8, 2015.
Diagnosis on Top Model:
The first model option, referred to as the ``Diagnosis on Top''
(DOT) model, combines diagnosis groups with a regression model to
create separate weights for patients with different diagnoses. For its
``Studies in Home Health Case Mix'' project design report (January 7,
2002), Abt had explored the possibility of a DOT model for the home
health payment system. At that time, there was a decision that the
potential gains in payment accuracy which would result from
implementing a DOT model were offset by the added complexity and burden
to providers that a DOT model could introduce by requiring providers to
classify their patients with a single diagnosis that would be used to
determine payment. For present reform efforts, Abt revisited the DOT
model with more current data and in the context of other potential
changes to the payment system which a DOT model might be able to
complement. In this analysis, we are removing the therapy variable,
allowing us to explore new ideas and re-explore previously rejected
ideas to see how we can increase the statistical power of the model
without the therapy variable. In this most recent analysis, each
episode is grouped into the following diagnosis groups based on the
primary ICD-9-CM diagnosis code reported on the OASIS: (1) Orthopedic;
(2) neurological; (3) diabetes; (4) cancer; (5) skin wounds & lesions;
(6) cardiovascular; (7) pulmonary; (8) gastrointestinal; (9) genito-
urinary; (10) mental/emotional disorders; (11) other diagnoses; (12)
case-mix V-codes; and (13) non-case-mix V-codes. Unlike the current HH
PPS case-mix system, the diagnosis on top model does not include any
therapy thresholds. Under the diagnosis on top model, episodes are
first divided into different diagnosis groups, prior to the
determination of the clinical and functional levels, and payment model
regressions would be run separately for each diagnosis group. This is
intended to maximize the statistical performance of the payment system.
The work conducted by Abt Associates also included OASIS and non-OASIS
items (such as whether the patient was admitted from an acute or post-
acute care setting and hierarchical condition categories) not used in
the current payment system, but shown to correlate with resource use.
In many ways, the regression component of the diagnosis on top model is
very similar to the current 4-equation model except that, in later
versions of Abt's work on the diagnosis on top model, the clinical and
functional levels are replaced with an overall severity level. This
change allows the diagnosis on top model to account for a richer set of
variables than the clinical and functional levels in the current
payment system.
Predicted Therapy Model:
The second model option is referred to as the ``Predicted Therapy
Model.'' The basic structure of this model is similar to that of the
current payment model. In this model option, actual therapy visits used
in the current HH PPS model are replaced with predicted therapy visits
to develop case mix weights and payment amounts based on
[[Page 39866]]
the predicted number of visits. The weights are constructed via a two-
part model. The first part of the model uses a logistic regression to
estimate whether or not the episode had any therapy visits. The second
part of this predicted therapy model uses a truncated binomial
regression (truncated at zero) to estimate the amount of therapy visits
conditional on having any therapy visits. This ``hurdle'' model is
commonly used in health economics to describe medical utilization or
expenditures where observing zero health care use during the sample
period is common.\11\ We also looked at estimating the two part model
for each of the diagnosis groups in the diagnosis on top model
referenced above. The predicted therapy model still includes the four-
equation model, the payment regression, and the 153 HHRGs as in the
current payment model.
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\11\ ``Modeling Health Care Costs and Counts,'' ASHE conference
course by Partha Deb, Willard Manning and Edward Norton, https://web.harrisschool.uchicago.edu/sites/default/files/ASHE2012_Minicourse_Cost_Use_slides_corrected.pdf
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Home Health Groupings Model:
The third model is referred to as the ``Home Health Groupings ''
(HHG) model. The premise of this type of model is that it starts with a
clinical foundation. This groupings model groups home health episodes
by diagnoses and the expected types of home health interventions
required. Using expert clinical judgment, each ICD-9 code is assigned
to one of seven groups based on the intervention expected to be
required. Those seven groups include: (1) Musculoskeletal
Rehabilitation; (2) Neuro/Stroke Rehabilitation; (3) Skin/Non-Surgical
Wound Care; (4) Post-Op Wound Aftercare; (5) Behavioral Health Care;
(6) Complex Medical Care; and (7) Medication Management, Teaching, and
Assessment. Unlike the current HH PPS case-mix system, the home health
groupings model does not include any therapy thresholds. Abt Associates
is currently in the process of further delineating the seven groups
listed above using OASIS and non-OASIS items (such as whether the
patient was admitted from an acute or post-acute care setting and
hierarchical condition categories) not used in the current payment
system, but shown to correlate with resource use. The HHG model groups
home health episodes in a way that mirrors how clinicians would
differentiate between different types of beneficiaries and would help
explain why the beneficiary is receiving home health, something that
the current HH PPS case-mix may be lacking. MedPAC noted that policy
makers have faced challenges in defining the role of home health.\12\
We believe that the HHG model may be one way to better define the types
of care that patients receive under the home health benefit and thus
the role of home care.
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\12\ Medicare Payment Advisory Commission (MedPAC), ``Report to
the Congress: Medicare Payment Policy''. March 2015. P. 219.
Washington, DC. Accessed on 5/5/2015 at: https://medpac.gov/documents/reports/march-2015-report-to-the-congress-medicare-payment-policy.pdf?sfvrsn=0.
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To inform the model options discussed above, Abt Associates also
reviewed other Medicare prospective payment systems to identify
alternative methods used in classifying patients and to better
understand components of each system. In the future, we plan to issue a
technical report under our contract with Abt Associates that would
further describe and analyze the three model options. We also plan to
reconvene the Clinical Workgroup and the Technical Experts Panel in the
near future to help further inform CMS on the various model options
developed and next steps.
F. Technical Regulations Text Changes
First, we propose to make several technical corrections in part 484
to better align the payment requirements with recent statutory and
regulatory changes for home health services. We propose to make changes
to Sec. 484. 205(e) to state that estimated total outlier payments for
a given calendar year are limited to no more than 2.5 percent of total
outlays under the HHA PPS, rather than 5 percent of total outlays, as
required by section 1895(b)(5)(A) of the Act as amended by section
3131(b)(2)(B) of the Affordable Care Act. Similarly, we also propose to
specify in Sec. 484.240(e) that the fixed dollar loss and the loss
sharing amounts are chosen so that the estimated total outlier payment
is no more than 2.5 percent of total payments under the HH PPS, rather
than 5 percent of total payments under the HH PPS as required by
section 1895(b)(5)(A) of the Act as amended by section 3131(b)(2)(B) of
the Affordable Care Act. We also propose to describe in Sec.
484.240(f) that the estimated total amount of outlier payments to an
HHA in a given year may not exceed 10 percent of the estimated total
payments to the specific agency under the HH PPS in a given year. This
update aligns the regulations text at Sec. 484.240(f) with the
statutory requirement in 1895(b)(5)(A) of the Act as amended by section
3131(b)(2)(B) of the Affordable Care Act. Finally, we propose a minor
editorial change in Sec. 484.240(b) to specify that the outlier
threshold for each case-mix group is the episode payment amount for
that group, or the PEP adjustment amount for the episode, plus a fixed
dollar loss amount that is the same for all case-mix groups.
Second, in addition to the proposed changes to the regulations text
pertaining to outlier payments under the HH PPS, we also propose to
amend Sec. 409.43(e)(iii) and to add language to Sec. 484.205(d) to
clarify the frequency of review of the plan of care and the provision
of Partial Episode Payments (PEP) under the HH PPS as a result of a
regulations text change in Sec. 424.22(b) that was finalized in the CY
2015 HH PPS final rule (79 FR 66032). Specifically, we propose to
change the definition of an intervening event to include transfers and
instances where a patient is discharged and return to home health
during a 60-day episode, rather than a discharge and return to the same
HHA during a 60-day episode. In Sec. 484.220, we propose to update the
regulations text to reflect the downward adjustments to the 60-day
episode payment rate due to changes in the coding or classification of
different units of service that do not reflect real changes in case-mix
(nominal case-mix growth) applied to calendar years 2012 and 2013,
which were finalized in the CY 2012 HH PPS final rule (76 FR 68532).
This also includes updating the CY 2011 adjustment to 3.79 percent as
finalized in the CY 2011 HH PPS final rule (75 FR 70461). In Sec.
484.225 we are proposing to eliminate references to outdated market
basket index factors by removing paragraphs (b), (c), (d), (e), (f) and
(g). In Sec. 484.230 we propose to delete the last sentence as a
result of a change from a separate LUPA add-on amount to a LUPA add-on
factor finalized in the CY 2014 HH PPS final rule (78 FR 72256).
Finally, we are deleting and reserving Sec. 484.245 as we believe that
this language is no longer applicable under the HH PPS, as it was meant
to facilitate the transition to the original PPS established in CY
2000.
Lastly, we propose to make one technical correction in Sec. 424.22
to re-designate paragraph (a)(1)(v)(B)(1) as (a)(2).
We invite comments on these technical corrections and associated
changes in the regulations at Sec. 409, Sec. 424, and Sec. 484.
IV. Proposed Home Health Value-Based Purchasing (HHVBP) Model
A. Background
In the CY 2015 Home Health Prospective Payment System (HH PPS)
final rule titled ``Medicare and Medicaid Programs; CY 2015 Home Health
[[Page 39867]]
Prospective Payment System Rate Update; Home Health Quality Reporting
Requirements; and Survey and Enforcement Requirements for Home Health
Agencies (79 FR 66032-66118), we indicated that we were considering the
development of a home health value-based purchasing (HHVBP) model. We
sought comments on a future HHVBP model, including elements of the
model; size of the payment incentives and percentage of payments that
would need to be placed at risk in order to spur home health agencies
(HHAs) to make the necessary investments to improve the quality of care
for Medicare beneficiaries; the timing of the payment adjustments; and,
how performance payments should be distributed. We also sought comments
on the best approach for selecting states for participation in this
model. We noted that if the decision was made to move forward with the
implementation of a HHVBP model in CY 2016, we would solicit additional
comments on a more detailed model proposal to be included in future
rulemaking.
In the CY 2015 HH PPS final rule,\13\ we indicated that we received
a number of comments related to the magnitude of the percentage payment
adjustments; evaluation criteria; payment features; a beneficiary risk
adjustment strategy; state selection methodology; and the approach to
selecting Medicare-certified HHAs. A number of commenters supported the
development of a value-based purchasing model in the home health
industry in whole or in part with consideration of the design
parameters provided. No commenters provided strong counterpoints or
alternative design options which dissuaded CMS from moving forward with
general design and framework of the HHVBP model as discussed in the CY
2015 HH PPS proposed rule. All comments were considered in our decision
to develop an HHVBP model for implementation beginning January 1, 2016.
Therefore, in this proposed rule, we are proposing to implement a HHVBP
model, which includes a randomized state selection methodology; the
reporting framework; the payment adjustment methodology; payment
adjustment schedule by performance year and payment adjustment
percentage; the quality measures selection methodology, classifications
and weighting, measures for performance year one, including the
reporting of New Measures, and the framework for proposing to adopt
measures for subsequent performance years; the performance scoring
methodology, which includes performance based on achievement and
improvement; the review and recalculation period; and the evaluation
framework.
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\13\ Medicare and Medicaid Programs; CY 2015 Home Health
Prospective Payment System Rate Update; Home Health Quality
Reporting Requirements; and Survey and Enforcement Requirements for
Home Health Agencies, 79 FR 66105-66106 (November 6, 2014).
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The basis for developing this proposed value-based purchasing (VBP)
model, as described in the proposed regulations at Sec. 484.300 et
seq., stems from several important areas of consideration. First, we
expect that tying quality to payment through a system of value-based
purchasing will improve the beneficiaries' experience and outcomes. In
turn, we expect payment adjustments that both reward improved quality
and penalize poor performance will incentivize quality improvement and
encourage efficiency, leading to a more sustainable payment system.
Second, section 3006(b) of the Affordable Care Act directed the
Secretary of the Department of Health and Human Services (the
Secretary) to develop a plan to implement a VBP program for payments
under the Medicare Program for HHAs and the Secretary issued an
associated Report to Congress in March of 2012 (2012 Report).\14\ The
2012 Report included a roadmap for implementation of an HHVBP model and
outlined the need to develop an HHVBP program that aligns with other
Medicare programs and coordinates incentives to improve quality. The
2012 Report also indicated that a HHVBP program should build on and
refine existing quality measurement tools and processes. In addition,
the 2012 Report indicated that one of the ways that such a program
could link payment to quality would be to tie payments to overall
quality performance.
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\14\ CMS, ``Report to Congress: Plan to Implement a Medicare
Home Health Agency Value-Based Purchasing Program'' (March 15, 2012)
available at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/HomeHealthPPS/downloads/stage-2-NPRM.PDF.
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Third, section 402(a)(1)(A) of the Social Security Amendments of
1967 (as amended) (42 U.S.C. 1395b-1(a)(1)(A)), provided authority for
us to conduct the Home Health Pay-for-Performance (HHPFP) Demonstration
that ran from 2008 to 2010. The results of that Demonstration found
modest quality improvement in certain measures after comparing the
quality of care furnished by Demonstration participants to the quality
of care furnished by the control group. One important lesson learned
from the HHPFP Demonstration was the need to link the HHA's quality
improvement efforts and the incentives. HHAs in three of the four
regions generated enough savings to have incentive payments in the
first year of the Demonstration, but the size of payments were unknown
until after the conclusion of the Demonstration. Also, the time lag
between quality performance and payment incentives was too long to
provide a sufficient motivation for HHAs to take necessary steps to
improve quality. The results of the Demonstration published in a
comprehensive evaluation report \15\ suggest that future models could
benefit from ensuring that incentives are reliable enough, of
sufficient magnitude, and paid in a timely fashion to encourage HHAs to
be fully engaged in the quality of care initiative.
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\15\ ``CMS Report on Home Health Agency Value-Based Purchasing
Program'' (February of 2012) available at https://www.cms.gov/Research-Statistics-Data-and-Systems/Statistics-Trends-and-Reports/Reports/Downloads/HHP4P_Demo_Eval_Final_Vol1.pdf.
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Furthermore, the President's FY 2015 and 2016 Budgets proposed that
VBP should be extended to additional providers including skilled
nursing facilities, home health agencies, ambulatory surgical centers,
and hospital outpatient departments. The FY 2015 Budget called for at
least 2 percent of payments to be tied to quality and efficiency of
care on a budget neutral basis. The FY 2016 Budget outlines a program
which would tie at least 2 percent of Medicare payments to the quality
and efficiency of care in the first 2 years of implementation beginning
in 2017, and at least 5 percent beginning in 2019 without any impact to
the budget. We propose in this HHVBP model to also follow a graduated
payment adjustment strategy within certain selected states beginning
January 1, 2016.
The Secretary has also set two overall delivery system reform goals
for CMS. First, we seek to tie 30 percent of traditional, or fee-for-
service, Medicare payments to quality or value-based payments through
alternative payment models by the end of 2016, and to tie 50 percent of
payments to these models by the end of 2018. Second, we seek to tie 85
percent of all traditional Medicare payments to quality or value by
2016 and 90 percent by 2018.\16\ To support these efforts the Health
Care Payment Learning and Action Network was recently launched to help
advance the work being done across sectors to increase the adoption of
value-based payments and alternative payment
[[Page 39868]]
models. We believe that testing the HHVBP model would support these
goals.
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\16\ Content of this announcement can be found at https://www.hhs.gov/news/press/2015pres/01/20150126a.html.
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Finally, we have already successfully implemented the Hospital
Value-Based Purchasing (HVBP) program, under which value-based
incentive payments are made in a fiscal year to hospitals that meet
performance standards established for a performance period with respect
to measures for that fiscal year. The percentage of a participating
hospital's base-operating DRG payment amount for FY 2015 discharges
that is at risk, based on the hospital's performance under the program
for that fiscal year, is 1.5 percent. That percentage will increase to
2.0 by FY 2017. We are proposing an HHVBP model that builds on the
lessons learned and guidance from the HVBP program and other applicable
demonstrations as discussed above, as well as from the evaluation
report discussed earlier.
The proposed HHVBP model presents an opportunity to improve the
quality of care furnished to Medicare beneficiaries and study what
incentives are sufficiently significant to encourage HHAs to provide
high quality care. The HHVBP model being proposed would offer both a
greater potential reward for high performing HHAs as well as a greater
potential downside risk for low performing HHAs. If implemented, the
model would begin on January 1, 2016, and include an array of measures
that would capture the multiple dimensions of care that HHAs furnish.
The proposed model would be tested by CMS's Center for Medicare and
Medicaid Innovation (CMMI) under section 1115A of the Act. Under
section 1115A(d)(1) of the Act, the Secretary may waive such
requirements of Titles XI and XVIII and of sections 1902(a)(1),
1902(a)(13), and 1903(m)(2)(A)(iii) as may be necessary solely for
purposes of carrying out section 1115A with respect to testing models
described in section 1115A(b). The Secretary is not issuing any waivers
of the fraud and abuse provisions in sections 1128A, 1128B, and 1877 of
the SSA or any other Medicare or Medicaid fraud and abuse laws for this
model. Thus, notwithstanding any other provisions of this proposed
rule, all providers and suppliers participating in the HHVBP model must
comply with all applicable fraud and abuse laws and regulations.
We are proposing to use the section 1115A(d)(1) waiver authority to
apply a reduction or increase of up to 8 percent to current Medicare
payments to Medicare-certified HHAs delivering care to beneficiaries
within the boundaries of certain states, depending on the HHA's
performance on specified quality measures relative to its peers.
Specifically, the HHVBP model proposes to utilize the waiver authority
to adjust Medicare payment rates under section 1895(b) of the Act.\17\
In accordance with the authority granted to the Secretary in section
1115A(d)(1) of the Act, we would waive section 1895(b)(4) of the Act
only to the extent necessary to adjust payment amounts to reflect the
value-based payment adjustments under this proposed model for Medicare-
certified HHAs in specified states selected in accordance with CMS's
proposed selection methodology. We are not proposing to implement this
model under the authority granted by the Affordable Care Act under
section 3131 (``Payment Adjustments for Home Health Care'').
---------------------------------------------------------------------------
\17\ 42 U.S.C. 1395fff.
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The defined population would include all Medicare beneficiaries
being provided care by any Medicare-certified HHA delivering care
within the selected states. Medicare-certified HHAs that are delivering
care within the boundaries of selected states are considered `Competing
Medicare-certified Home Health Agencies' within the scope of this HHVBP
Model. If care is delivered outside of boundaries of selected states,
or inside the boundaries of a non-selected state that does not have a
reciprocal agreement with a selected state, payments for those
beneficiaries would not be considered within the scope of the model
because we are basing participation in the model on state specific CMS
Certification Numbers (CCNs). Payment adjustments for each year of the
model would be calculated based on a comparison of how well each
competing Medicare-certified HHA performed during the performance
period for that year (proposed below to be one year in length, starting
in CY 2016) with its performance on the same measures in 2015 (proposed
below to be the baseline data year).
The first performance year would be CY 2016, the second would be CY
2017, the third would be CY 2018, the fourth would be 2019, and the
fifth would be CY 2020. Greater details on performance periods are
outlined in further detail in section D--Performance Assessment and
Payment Periods. This model would test whether being subject to
significant payment adjustments to the Medicare payment amounts that
would otherwise be made to competing Medicare-certified HHAs would
result in statistically significant improvements in the quality of care
being delivered to this specific population of Medicare beneficiaries.
We propose to identify Medicare-certified HHAs for participation in
this model using state borders as boundaries. We do so under the
authority granted in section 1115A(a)(5) of the Act to elect to limit
testing of a model to certain geographic areas. This decision is
influenced by the 2012 Report to Congress mandated under section
3006(b) of the Affordable Care Act. This Report stated that HHAs which
participated in previous value-based purchasing demonstrations
``uniformly believed that all Medicare-certified HHAs should be
required to participate in future VBP programs so all agencies
experience the potential burdens and benefits of the program'' and some
HHAs expressed concern that absent mandatory participation, ``low-
performing agencies in areas with limited competition may not choose to
pursue quality improvement.'' \18\
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\18\ See the Recommendations section of the U.S. Department of
Health and Human Services. Report to Congress: Plan to Implement a
Medicare Home Health Agency Value-Based Purchasing Program.'' (March
2012) p. 28.
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Section 1115A(b)(2)(A) of the Act requires that the Secretary
select models to be tested where the Secretary determines that there is
evidence that the model addresses a defined population for which there
are deficits in care leading to poor clinical outcomes or potentially
avoidable expenditures. The HHVBP model was developed to improve care
for Medicare patients receiving care from HHAs based on evidence in the
March 2014 MedPAC Report to Congress citing quality and cost concerns
in the home health sector. According to MedPAC, ``about 29 percent of
post-hospital home health stays result in readmission, and there is
tremendous variation in performance among providers within and across
geographic regions.'' \19\ The same report cited limited improvement in
quality based on existing measures, and noted that the data on quality
``are collected only for beneficiaries who do not have their home
health care stays terminated by a hospitalization,'' skewing the
results in favor of a healthier segment of the Medicare population.\20\
This model would test the use of adjustments to Medicare HH PPS rates
by tying payment to quality performance with the goal of achieving the
highest possible quality and efficiency.
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\19\ See full citation at note 11. MedPAC Report to Congress
(March 2014) p.215.
\20\ MedPAC Report to Congress (March 2014) p.226.
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[[Page 39869]]
B. Overview
In Sec. 484.305 we propose definitions for ``applicable percent'',
``applicable measure'', ``benchmark'', ``home health prospective
payment system'', ``larger-volume cohort'', ``linear exchange
function'', ``Medicare-certified home health agency'', ``New
Measures'', ``payment adjustment'', ``performance period'', ``smaller-
volume cohort'', ``selected states'', ``starter set'', ``Total
Performance Score'', and ``value-based purchasing'' as they pertain to
this subpart. The HHVBP model is being proposed to encompass five
performance years and be implemented beginning January 1, 2016 and
conclude on December 31, 2022. Payment and service delivery models are
developed by CMMI in accordance with the requirements of section 1115A
of the Act. During the development of new models, CMMI builds on the
ideas received from internal and external stakeholders and consults
with clinical and analytical experts.
In this proposed rule, we are outlining an HHVBP model for public
notice and comment that has an overall purpose of improving the quality
of home health care and delivering it to the Medicare population in a
more efficient manner. The specific goals of the proposed model are to:
1. Incentivize HHAs to provide better quality care with greater
efficiency;
2. Study new potential quality and efficiency measures for
appropriateness in the home health setting; and,
3. Enhance current public reporting processes.
We are proposing that the HHVBP model would adjust Medicare HHA
payments over the course of the model by up to 8 percent depending on
the applicable performance year and the degree of quality performance
demonstrated by each competing Medicare-certified HHA. The proposed
model would reduce the HH PPS final claim payment amount to an HHA for
each episode in a calendar year by an amount up to the applicable
percentage defined in proposed Sec. 484.305. The timeline of payment
adjustments as they apply to each performance year is described in
greater detail in the section entitled ``Payment Adjustment Timeline.''
The model would apply to all Medicare-certified HHAs in each of the
selected states, which means that all HHAs in the selected states would
be required to compete. We propose to codify this policy at 42 CFR
484.310. Furthermore, a competing Medicare-certified HHA would only be
measured on performance for care delivered to Medicare beneficiaries
within selected states (with rare exceptions given for care delivered
when a reciprocal agreement exists between states). The distribution of
payment adjustments would be based on quality performance, as measured
by both achievement and improvement, across a proposed set of quality
measures rigorously constructed to minimize burden as much as possible
and improve care. Competing Medicare-certified HHAs that demonstrate
they can deliver higher quality of care in comparison to their peers
(as defined by the volume of services delivered within the selected
state), or their own past performance, could have their payment for
each episode of care adjusted higher than the amount that otherwise
would be paid under section 1895 of the Act. Competing Medicare-
certified HHAs that do not perform as well as other competing Medicare-
certified HHAs of the same size in the same state might have their
payments reduced and those competing Medicare-certified HHAs that
perform similarly to others of similar size in the same state might
have no payment adjustment made. This operational concept is similar in
practice to what is used in the HVBP program.
We expect that the risk of having payments adjusted in this manner
would provide an incentive among all competing Medicare-certified HHAs
delivering care within the boundaries of selected states to provide
significantly better quality through improved planning, coordination,
and management of care. The degree of the payment adjustment would be
dependent on the level of quality achieved or improved from the
baseline year, with the highest upward performance adjustments going to
competing Medicare-certified HHAs with the highest overall level of
performance based on either achievement or improvement in quality. The
size of a Medicare-certified HHA's payment adjustment for each year
under the model would be dependent upon that HHA's performance with
respect to that calendar year relative to other competing Medicare-
certified HHAs of similar size in the same state and relative to its
own performance during the baseline year.
We are proposing that states would be selected randomly from nine
regional groupings for model participation. A competing Medicare-
certified HHA is only measured on performance for care delivered to
Medicare beneficiaries within boundaries of selected states and only
payments for HHA services provided to Medicare beneficiaries within
boundaries of selected states would be subject to adjustment under the
proposed model. Requiring all Medicare-certified HHAs within the
boundaries of selected states to compete in the model would ensure
that: (1) There is no self-selection bias, (2) competing HHAs are
representative of HHAs nationally, and (3) there is sufficient
participation to generate meaningful results. We believe it is
necessary to require all HHAs delivering care within boundaries of
selected states to be included in the model because, in our experience,
Medicare-providers are generally reluctant to participate voluntarily
in models in which their Medicare payments could be subject to possible
reduction. This reluctance to participate in voluntary models has been
shown to cause self-selection bias in statistical assessments and thus,
may present challenges to our ability to evaluate the model. In
addition, state boundaries represent a natural demarcation in how
quality is currently being assessed through OASIS measures on Home
Health Compare (HHC).
C. Selection Methodology
1. Identifying a Geographic Demarcation Area
We are proposing to adopt a methodology that uses state borders as
boundaries for demarcating which Medicare-certified HHAs will be
required to compete in the model. We are proposing to select nine
states from nine geographically-defined groupings of five or six
states. Groupings were also defined in order to ensure that the
successful implementation of the model would produce robust and
generalizable results, as discussed later in this section.
We took into account five key factors when deciding to propose
selection at the state-level for this model. First, if we required
some, but not all, Medicare-certified HHAs that deliver care within the
boundaries of a selected state to participate in the model, we believe
the HHA market for the state could be disrupted because HHAs in the
model would be competing against HHAs not in the model (herein
referenced as either `non-model HHAs' or `non-competing HHAs'). Second,
we wanted to ensure that the distribution of payment adjustments based
on performance under the model could be extrapolated to the entire
country. Statistically, the larger the sample to which payment
adjustments are applied, the smaller the variance of the sampling
distribution and the greater the likelihood that the distribution
accurately predicts what would transpire if the methodology were
applied to the full population of
[[Page 39870]]
HHAs. Third, we considered the need to align with other HHA quality
program initiatives including HHC. The HHC Web site presently provides
the public and HHAs a state- and national-level comparison of quality.
We expect that aligning performance with the HHVBP benchmark and the
achievement score would support how measures are currently being
reported on HHC. Fourth, there is a need to align with CMS regulations
which require that each HHA have a unique CMS Certification Number
(CCN) for each state in which the HHA provides service. Fifth, we
wanted to ensure sufficient sample size and the ability to meet the
rigorous evaluation requirements for CMMI models. These five factors
are important for the successful implementation and evaluation of this
model.
We expect that when there is a risk for a downside payment
adjustment based on quality performance measures, the use of a self-
contained, mandatory cohort of HHA participants will create a stronger
incentive to deliver greater quality among competing Medicare-certified
HHAs. Specifically, it is possible the market would become distorted if
non-model HHAs are delivering care within the same market as competing
Medicare-certified HHAs because competition, on the whole, becomes
unfair when payment is predicated on quality for one group and volume
for the other group. In addition, we expect that evaluation efforts
might be negatively impacted because some HHAs would be competing on
quality and others on volume within the same market.
We are proposing the use of state boundaries after careful
consideration of several alternative selection approaches, including
randomly selecting HHAs from all HHAs across the country, and requiring
participation from smaller geographic regions including the county; the
Combined Statistical Area (CSA); the Core-Based Statistical Area
(CBSA); rural provider level; and the Hospital Referral Region (HRR)
level.
A methodology using a national sample of HHAs that are randomly
selected from all HHAs across the country could be designed to include
enough HHAs to ensure robust payment adjustment distribution and a
sufficient sample size for the evaluation; however, this approach may
present significant limitations when compared with the state boundaries
selection methodology proposed in this model. Of primary concern with
randomly selecting at the provider-level across the nation is the issue
with market distortions created by having competing Medicare-certified
HHAs operating in the same market as non-model HHAs.
Using smaller geographic areas than states, such as counties, CSAs,
CBSAs, rural, and HRRs, could also present challenges for this model.
These smaller geographic areas were considered as alternate selection
options; however, their use could result in too small of a sample size
of potential competing HHAs. As a result, we expect the distribution of
payment adjustments could become highly divergent among fewer HHA
competitors. In addition, the ability to evaluate the model could
become more complex and may be less generalizable to the full
population of Medicare-certified HHAs and the beneficiaries they serve
across the nation. Further, the use of smaller geographic areas than
states could increase the proportion of Medicare-certified HHAs that
could fall into groupings with too few agencies to generate a stable
distribution of payment adjustments. Thus, if we were to define
geographic areas based on CSAs, CBSAs, counties, or HRRs, we would need
to develop an approach for consolidating smaller regions into larger
regions.
Home health care is a unique type of health care service when
compared to other Medicare provider types. In general, the HHA's care
delivery setting is in the beneficiaries' homes as opposed to other
provider types that traditionally deliver care at a brick and mortar
institution within beneficiaries' respective communities. As a result,
the HHVBP model needs to be designed to account for the unique way that
HHA care is provided in order to ensure that the results are
generalizable to the population. HHAs are limited to providing care to
beneficiaries in the state that they have a CCN however; HHAs are not
restricted from providing service in a county, CSA, CBSA or HRR that
they are not located in (as long as the other county/CBSA/HRR is in the
same state in which the HHA is certified). As a result, using smaller
geographic areas (than state boundaries) could result in similar market
distortion and evaluation confounders as selecting providers from a
randomized national sampling. The reason is that HHAs in adjacent
counties/CSAs/CBSAs/HRRs may not be in the model but, would be directly
competing for services in the same markets or geographic regions.
Competing HHAs delivering care in the same market area as non-competing
HHAs could generate a spillover effect where non-model HHAs would be
vying for the same beneficiaries as competing HHAs. This spillover
effect presents several issues for evaluation as the dependent variable
(quality) becomes confounded by external influences created by these
non-competing HHAs. These unintentional external influences on
competing HHAs may be made apparent if non-competing HHAs become
incentivized to generate greater volume at the expense of quality
delivered to the beneficiaries they serve and at the expense of
competing HHAs that are paid on quality instead of volume. Further, the
ability to extrapolate these results to the full population of HHAs and
the beneficiaries they serve becomes confounded by an artifact of the
model and inferences would be limited from an inability to duplicate
these results. While these concerns would decrease in some order of
magnitude as larger regions are considered, the only way to eliminate
these concerns entirely is to define participation among Medicare-
certified HHAs at the state level.
In addition, home health quality data currently displayed on HHC
allows users to compare HHA services furnished within a single state.
Selecting HHAs using other geographic regions that are smaller and/or
cross state lines could require the model to deviate from the
established process for reporting quality. For these reasons, we
believe a selection methodology based on the use of Medicare-certified
HHAs delivering care within state boundaries would be the most
appropriate for the successful implementation and evaluation of this
model.
While, for the reasons described above, we are proposing that the
geographic basis of selection remain at the state-level, we
nevertheless seek comment on potential alternatives that might use
smaller geographic areas. With consideration of alternatives, the
public should reference the five aforementioned key factors used to
consider selection at the state-level for this model as they relate to
the evaluative framework and operational feasibility of this model. In
particular, one potential alternative would be to split states into
sub-state regions using a combination of CSAs and metropolitan
statistical areas (MSA), a type of CBSA. For example, regions might be
defined using the following process:
Step 1: Define one sub-state region corresponding to each
CSA that contains an MSA (but not for CSAs that do not include an MSA)
and one sub-state region corresponding to each MSA that is not part of
a CSA. In cases where a CSA or MSA crossed state boundaries, only the
portion of the CSA or MSA that falls inside the state boundaries would
be included in the sub-state region.
[[Page 39871]]
Step 2: Any portions of a state that were not included in
a sub-state region based on a CSA or an MSA defined in Step 1 would be
consolidated in a single ``remainder of state'' sub-state region.
Step 3: To ensure that all sub-state regions have a
sufficient number of HHAs to permit stable distribution of payment
adjustments, sub-state regions based on CSAs or MSAs that contained
fewer than 25 HHAs would be consolidated into the ``remainder of
state'' sub-state region.
Step 4: If a ``remainder of state'' sub-state region had
fewer than 25 HHAs, that sub-state region would be consolidated with
the geographically closest sub-state region based on a CSA or MSA.
We note that algorithms like this one may generate more than 100 total
sub-state regions and over 200 unique competing cohorts of Medicare-
certified HHAs.
We seek comment on advantages and disadvantages of this approach
relative to defining regions based on state boundaries. In particular,
we note that because this approach would generate a larger number of
regions, it could increase the statistical power of the model
evaluation, and might improve our ability to determine what effects the
model has on the quality of home health care, as well as other outcomes
of interest. However, we note that because regions would no longer line
up with full states in most cases, the regions selected to participate
in the model would no longer align directly with those displayed on HHC
and therefore, quality data would have to be recalculated and displayed
differently from what is currently being reported on HHC. In addition,
using sub-state regions could, as noted above, lead to undesirable
spillover effects between participating and non-participating HHAs.
These spillover concerns would be mitigated by the fact that none of
the sub-state regions defined under this approach would cross state
lines and the fact that the sub-state regions would be larger than
under some approaches to defining sub-state regions (for example, at
the county level). Nevertheless, it is unclear how severe these
evaluation and operational concerns would be in practice and how the
extent of these concerns would depend on the different characteristics
of the selected regions. We welcome public comment on these proposed
state selection methodologies.
2. Overview of the Randomized Selection Methodology for States
We are requesting comments on the following proposed methodology
for selecting states. The selection methodology employed will need to
provide the strongest evidence of producing meaningful results
representative of the national population of Medicare-certified HHAs
and, in turn, meet the evaluation requirements of section 1115A(b)(4)
of the Act.
The state selections listed in proposed Sec. 484.310 are based on
the described proposed randomized selection methodology and are subject
to change in the CY 2016 HH PPS final rule as a result of any changes
that may be made to the proposed randomized methodology in response to
comments. However, if the final methodology differs from what we are
proposing here, we will apply the final methodology and identify the
states selected under the final methodology in the final rule. We
propose to group states by each state's geographic proximity to one
another and by accounting for key evaluation characteristics (that is,
proportionality of service utilization, proportionality of
organizations with similar tax-exempt status and HHA size, and
proportionality of beneficiaries that are dually-eligible for Medicare
and Medicaid).
Based on an analysis of OASIS quality data and Medicare claims
data, we believe the use of nine geographic groupings is necessary to
ensure that the model accounts for the diversity of beneficiary
demographics, rural and urban status, cost and quality variations,
among other criteria. To provide for comparable and equitable selection
probabilities, these separate geographic groupings each include a
comparable number of states. We are not proposing to adopt census-based
geographic groupings or the CMS Medicare Administrative Contractor
(MAC) jurisdictions because those groupings would not permit an equal
opportunity of selection of Medicare-certified HHAs by state or an
assurance that we would be able test the model among a diversity of
agencies such as is found across the nation. Following this logic,
under our proposed methodology, groupings are based on states'
geographic proximity to one another, having a comparable number of
states if randomized for an equal opportunity of selection, and
similarities in key characteristics that would be considered in the
evaluation study because the attributes represent different types of
HHAs, regulatory oversight, and types of beneficiaries served. This is
necessary to ensure that the evaluation study remains objective and
unbiased and that the results of this study best represent the entire
population of Medicare-certified HHAs across the nation.
Several of the key characteristics we used for grouping state
boundaries into clusters for selection into the model are also used in
the impact analysis of our annual HHA payment updates, a fact that
reinforces their relevance for evaluation. The additional proposed
standards for grouping (level of utilization and socioeconomic status
of patients) are also important to consider when evaluating the
program, because of their current policy relevance. Large variations in
the level of utilization of the home health benefit has received
attention from policymakers concerned with achieving high-value health
care and curbing fraud and abuse.\21\ Policymakers' concerns about the
role of beneficiary-level characteristics as determinants of resource
use and health care quality were highlighted in the Affordable Care
Act, which mandated a study \22\ of access to home health care for
vulnerable populations \23\ and, more recently, Improving Medicare
Post-acute Care Transformation (IMPACT) Act of 2014 required the
Secretary to study the relationship between individuals' socioeconomic
status and resource use or quality.\24\ The parameters used to define
each geographic grouping are further described in the next three
sections.
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\21\ See MedPAC Report to Congress: Medicare Payment Policy
(March 2014, Chapter 9) available at https://medpac.gov/documents/reports/mar14_entirereport.pdf. See also the Institute of Medicine
Interim Report of the Committee on Geographic Variation in Health
Care Spending and Promotion of High-Value Health Care: Preliminary
Committee Observations (March 2013) available at https://iom.edu/Reports/2013/Geographic-Variation-in-Health-Care-Spending-and-Promotion-of-High-Care-Value-Interim-Report.aspx.
\22\ This study can be accessed at https://www.cms.gov/Center/Provider-Type/Home-Health-Agency-HHA-Center.html.
\23\ Section 3131(d) of the Affordable Care Act.
\24\ Improving Medicare Post-acute Care Transformation (IMPACT)
Act of 2014 (Public Law 113-185).
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a. Geographic Proximity
Under the proposed methodology, in order to ensure that the
Medicare-certified HHAs that would be required to participate in the
model are not all in one region of the country, the states in each
grouping are adjacent to each other whenever possible while creating
logical groupings of states based on common characteristics as
described above. Specifically, analysis based on quality data and
claims data found that HHAs in these neighboring states tend to hold
certain characteristics in common. These include having similar;
patterns of utilization, proportionality of non-profit agencies, and
types of beneficiaries served (for example, severity and number, type
of co-
[[Page 39872]]
morbidities, and socio-economic status). Therefore, the proposed
groupings of states are delineated according to states' geographic
proximity to one another and common characteristics as a means of
permitting greater comparability. In addition, each of the groupings
retains similar types of characteristics when compared to any other
type of grouping of states.
b. Comparable Number of States in Each Grouping
Under our proposed randomized selection methodology, each
geographic region, or grouping, has a similar number of states. As a
result, all states would have a 16.7 percent to 20 percent chance of
being selected under our proposed methodology, and Medicare-certified
HHAs would have a similar likelihood of being required to compete in
the model by using this sampling design. We assert that this sampling
design would ensure that no single entity is singled out for selection,
since all states and Medicare-certified HHAs would have approximately
the same chance of being selected. In addition, this sampling approach
would mitigate the opportunity for HHAs to self-select into the model
and thereby bias any results of the test.
c. Characteristics of State Groupings
Without sacrificing an equal opportunity for selection, the
proposed state groupings are intended to ensure that important
characteristics of Medicare-certified HHAs that deliver care within
state boundaries can be used to evaluate the primary intervention with
greater generalizability and representativeness of the entire
population of Medicare-certified HHAs in the nation. Data analysis of
these characteristics employed the full data set of Medicare claims and
OASIS quality data. Although some characteristics, such as beneficiary
age and case-mix, yield some variations from one state to another,
other important characteristics do vary substantially and could
influence how HHAs respond to the incentives of the model.
Specifically, home health services utilization rates, tax-exemption
status of the provider, the socioeconomic status of beneficiaries (as
measured by the proportion of dually-eligible beneficiaries), and
agency size (as measured by average number of episodes of care per
HHA), are important characteristics that could influence outcomes of
the model. Subsequently, we intend to study the impacts of these
characteristics for purposes of designing future value-based purchasing
models and programs. These characteristics and expected variations must
be considered in the evaluation study to enable us to avoid erroneous
inferences about how different types of HHAs will respond to HHVBP
incentives.
Under this proposed state selection methodology, state groupings
reflect regional variations that enhance the generalizability of the
model. In line with this methodology, each grouping includes states
that are similar in at least one important aforementioned
characteristic while being geographically located in close proximity to
one another. Using the criteria described above, the following
geographic groupings were identified using Medicare claims-based data
from calendar years 2013-2014. Each of the 50 states was assigned to
one of the following geographic groups:
Group #1: (VT, MA, ME, CT, RI, NH)
States in this group tend to have larger HHAs and have average
utilization relative to other states.
Group #2: (DE, NJ, MD, PA, NY)
States in this group tend to have larger HHAs, have lower
utilization, and provide care to an average number of dually-eligible
beneficiaries relative to other states.
Group #3: (AL, GA, SC, NC, VA)
States in this group tend to have larger HHAs, have average
utilization rates, and provide care to a high proportion of minorities
relative to other states.
Group #4: (TX, FL, OK, LA, MS)
States in this group have HHAs that tend to be for-profit, have
very high utilization rates, and have a higher proportion of dually-
eligible beneficiaries relative to other states.
Group #5: (WA, OR, AK, HI, WY, ID)
States in this group tend to have smaller HHAs, have average
utilization rates, and are more rural relative to other states.
Group #6: (NM, CA, NV, UT, CO, AZ)
States in this group tend to have smaller HHAs, have average
utilization rates, and provide care to a high proportion of minorities
relative to other states.
Group #7: (ND, SD, MT, WI, MN, IA)
States in this group tend to have smaller HHAs, have very low
utilization rates, and are more rural relative to other states.
Group #8: (OH, WV, IN, MO, NE., KS)
States in this group tend to have HHAs that are of average size,
have average utilization rates, and provide care to a higher proportion
of dually-eligible beneficiaries relative to other states.
Group #9: (IL, KY, AR, MI, TN)
States in this group tend to have HHAs with higher utilization
rates relative to other states.
d. Randomized Selection of States
Upon the careful consideration of the aforementioned alternative
selection methodologies, including selecting states on a non-random
basis, we choose to propose the use of a selection methodology based on
a randomized sampling of states within each of the nine regional
groupings described above. We examined data on the evaluation elements
listed in this section to determine if specific states could be
identified in order to fulfill the needs of the evaluation. After
careful review, we determined that each evaluation element could be
measured by more than one state. As a result, we determined that it was
necessary to apply a fair method of selection where each state would
have a comparable opportunity of being selected and which would fulfill
the need for a robust evaluation. The proposed nine groupings of states
as described in this section permit the model to capture the essential
elements of the evaluation including demographic, geographic, and
market factors.
The randomized sampling of states is without bias to any
characteristics of any single state within any specific regional
grouping, where no states are excluded, and no state appears more than
once across any of the groupings. The randomized selection of states
was completed using a scientifically-accepted computer algorithm
designed for randomized sampling. The randomized selection of states
was run on each of the previously described regional groupings using
exactly the same process and, therefore, reflects a commonly accepted
method of randomized sampling. This computer algorithm employs the
aforementioned sampling parameters necessary to define randomized
sampling and omits any human interaction once it runs.
Based on this sampling methodology, SAS Enterprise Guide (SAS EG)
5.1 software was used to run a computer algorithm designed to randomly
select states from each grouping. SAS EG 5.1 and the computer algorithm
were employed to conduct the randomized selection of states. SAS EG 5.1
represents an industry-standard for generating advanced analytics and
provided a rigorous, standardized tool by which to satisfy the
requirements of randomized selection. The key SAS commands employed
include a ``PROC
[[Page 39873]]
SURVEYSELECT'' statement coupled with the ``METHOD=SRS'' option used to
specify simple random sampling as the sample selection method. A random
number seed was generated by using the time of day from the computer's
clock. The random number seed was used to produce random number
generation. Note that no stratification was used within any of the nine
geographically-diverse groupings to ensure there is an equal
probability of selection within each grouping. For more information on
this procedure and the underlying statistical methodology, please
reference SAS support documentation at: https://support.sas.com/documentation/cdl/en/statug/63033/HTML/default/viewer.htm#statug_surveyselect_sect003.htm/.
In Sec. 484.310, we propose to codify the names of the states
selected utilizing this proposed methodology, where one state from each
of the nine groupings was selected. For each of these groupings, we
propose to use state borders to demarcate which Medicare certified HHAs
would be required to compete in this model: Massachusetts was randomly
selected from Group 1, Maryland was randomly selected from Group 2,
North Carolina was randomly selected from Group 3, Florida was randomly
selected from Group 4, Washington was randomly selected from Group 5,
Arizona was randomly selected from Group 6, Iowa was randomly selected
from Group 7, Nebraska was randomly selected from Group 8, and
Tennessee was randomly selected from Group 9. Thus, if our methodology
is finalized as proposed, all Medicare-certified HHAs that provide
services in Massachusetts, Maryland, North Carolina, Florida,
Washington, Arizona, Iowa, Nebraska, and Tennessee will be required to
compete in this model.
However, should the methodology we propose in this rule change as a
result of comments received during the rulemaking process, it could
result in different states being selected for the model. In such an
event, we would apply the final methodology and announce the selected
states in the final rule. We therefore seek comment from all interested
parties in every state on the randomized selection methodology proposed
above and codified at Sec. 484.310.
Based on the comments received from this proposed rule, the
selection methodology for participation in the model may change from
state boundaries to an approach based on sub-state regions built from
CSAs/MSAs, CBSAs, rural provider level or HRRs. In that case, the goals
of the model will remain the same, and therefore, we would expect to
take a broadly similar approach to selecting participating regions to
the approach that would be taken when regions are defined based on
state boundaries. Specifically, as with the selection methodology
outlined above, we would anticipate grouping sub-state regions together
based on geographic proximity and other characteristics into groups of
approximately equal size and then selecting some number of sub-state
regions to participate from each group. The number of selected
participants will be dependent on the selection methodology. We welcome
public comment on these proposed state selection methodologies.
e. Use of CMS Certification Numbers (CCNs)
We are proposing that Total Performance Scores (TPS) and payment
adjustments would be calculated based on an HHA's CCN \25\ and,
therefore, based only on services provided in the selected states. The
exception to this methodology is where an HHA provides service in a
state that also has a reciprocal agreement with another state. Services
being provided by the HHA to beneficiaries who reside in another state
would be included in the TPS and subject to payment adjustments.\26\
The reciprocal agreement between states allows for an HHA to provide
services to a beneficiary across state lines using its original CCN
number. Reciprocal agreements are rare and, as identified using the
most recent Medicare claims data from 2014, there was found to be less
than 0.1 percent of beneficiaries that provided services that were
being served by CCNs with reciprocal agreements across state lines. Due
to the very low number of beneficiaries served across state borders as
a result of these agreements, we expect there to be an inconsequential
impact if we were to include these beneficiaries in the model.
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\25\ HHAs are required to report OASIS data and any other
quality measures by its own unique CMS Certification Number (CCN) as
defined under Title 42, Chapter IV, Subchapter G, Part Sec. 484.20
Available at URL https://www.ecfr.gov/cgi-bin/text-idx?tpl=/ecfrbrowse/Title42/42cfr484_main_02.tpl.
\26\ See Chapter 2 of the State Operations Manual (SOM), Section
2184--Operation of HHAs Cross State Lines, stating ``When an HHA
provides services across State lines, it must be certified by the
State in which its CCN is based, and its personnel must be qualified
in all States in which they provide services. The appropriate SA
completes the certification activities. The involved States must
have a written reciprocal agreement permitting the HHA to provide
services in this manner.''
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D. Performance Assessment and Payment Periods
1. Performance Reports
We are proposing the use of quarterly performance reports, annual
payment adjustment reports, and annual publicly-available performance
reports as 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
would 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.
Competing HHAs would be scored for the quality of care delivered
under the model based on their performance on measures compared to both
the performance of their peers, defined by the same size cohort (either
smaller- or larger-volume cohorts as defined in Sec. 484.305), and
their own past performance on the measures. We propose in Sec. 484.305
to define larger-volume cohort to mean the group of Medicare-certified
HHAs within the boundaries of a selected state that are participating
in HHCAHPs in accordance with Sec. 484.250 and to define smaller-
volume cohort to mean the group of HHAs within the boundaries of a
selected state that are exempt from participation in HHCAHPs in
accordance with Sec. 484.250. Where there are too few HHAs in the
smaller-volume cohort in each state to compete in a fair manner (that
is, when there is only one or two HHAs competing within a specific
cohort), these specific HHAs would be included in the larger-volume
cohort [for purposes of calculating the total performance score and
payment adjustment] without being measured on HHCAHPS. We are
requesting comments on this proposed methodology.
Quality performance scores and relative peer rankings would be
determined through the use of a baseline year (calendar year 2015) and
subsequent performance periods for each competing HHA. Further, these
reports would provide competing HHAs with an opportunity to track their
quality performance relative to their peers and their own past
performance. Using these reports provides a convenient and timely means
for competing HHAs to assess and track their own respective performance
as capacity is developed to improve or sustain quality over time.
[[Page 39874]]
Beginning with the data collected during the first quarter of CY
2016 (that is, data for the period January 1, 2016 to March 31, 2016),
and for every quarter of the model thereafter, we are proposing to
provide each Medicare certified HHA with a quarterly report that
contains information on their performance during the quarter. We expect
to make the first quarterly report available in July 2016, and to make
performance reports for subsequent quarters available in October,
January and April. The final quarterly report would be made available
in April 2021. The quarterly reports would include a competing HHA's
model-specific performance results with a comparison to other competing
HHAs within its cohort (larger- or smaller-volume) within the state
boundary. These model-specific performance results would complement all
quality data sources already being provided through the QIES system and
any other quality tracking system possibly being employed by HHAs. We
note that all performance measures that Medicare-certified HHAs will
report through the QIES system are also already made available in the
CASPER Reporting application. The primary difference between the two
reports (CASPER reports and the model-specific performance report) is
that the model-specific performance report we are proposing here
consolidates the applicable performance measures used in the HHVBP
model and provides a peer-ranking to other competing Medicare-certified
HHAs within the same state and size-cohort. In addition, CASPER reports
would provide quality data earlier than model-specific performance
reports because CASPER reports are not limited by a quarterly run-out
of data and a calculation of competing peer-rankings. For more
information on the accessibility and functionality of the CASPER
system, please reference the CASPER Provider Reporting Guide.\27\
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\27\ The Casper Reporting Guide is available at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HomeHealthQualityInits/downloads/HHQICASPER.pdf).
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The model-specific quarterly performance report would be made
available to each HHA through a dedicated CMMI model-specific platform
for data dissemination and include each HHA's relative ranking amongst
its peers along with measurement scores and overall performance
rankings.
We are proposing that a separate payment adjustment report would be
provided once a year to each of the competing HHAs. This report would
focus primarily on the payment adjustment percentage and include an
explanation of when the adjustment would be applied and how this
adjustment was determined relative to performance scores. Each
competing HHA would receive its own payment adjustment report viewable
only to that HHA.
We are also proposing a separate, annual, publicly available
quality report that would provide home health industry stakeholders,
including providers and suppliers that refer their patients to HHAs,
with an opportunity to ensure that the beneficiaries they are referring
for home health services are being provided the best possible quality
of care available. We seek public comment on the proposed reporting
framework described above.
2. Payment Adjustment Timeline
We propose at Sec. 484.325 that Medicare-certified HHAs will be
subject to upward or downward payment adjustments based on performance
on quality measures. We propose this model would consist of 5
performance years, where each performance year would link performance
to the opportunity and risk for payment adjustment up to an applicable
percent as defined in proposed 42 CFR 484.305. The first performance
year would transpire from January 1, 2016 through December 31, 2016,
and subsequently, all other performance years would be assessed on an
annual basis through 2020, unless modified through rulemaking. The
first payment adjustment would begin January 1, 2018 applied to that
calendar year based on 2016 performance data. Subsequently, all other
payment adjustments would be made on an annual basis through the
conclusion of the model, unless modified through rulemaking. We are
proposing that payment adjustments will be increased incrementally over
the course of the model with a maximum payment adjustment of (5
percent) upward or downward in 2018 and 2019, a maximum payment
adjustment of 6 percent (upward or downward) in 2020, and a maximum
payment adjustment of 8 percent (upward or downward) in 2021 and 2022.
We propose to implement this model over a total of 7 years beginning on
January 1, 2016, and ending on December 31, 2022.
The baseline year would run from January 1, 2015 through December
31, 2015 and provide a basis from which each respective HHA's
performance would be measured in each of the performance years. Data
related to performance on quality measures would continue to be
provided from the baseline year through the model's tenure using a
dedicated HHVBP web-based platform specifically designed to disseminate
data in this model (this ``portal'' would present and archive the
previously described quarterly and annual quality reports). Further,
HHAs will provide performance data on the four new quality measures
through this platform as well. Any new measures employed through the
model's tenure, subject to rulemaking, would use data from the previous
calendar year as the baseline.
New market entries (specifically, new Medicare-certified HHAs
delivering care in the boundaries of selected states) would also be
measured from their first full calendar year of services in the state,
which would be treated as baseline data for subsequent performance
years under this model. The delivery of services would be measured by
the number of episodes of care for Medicare beneficiaries and used to
determine whether an HHA falls into the smaller- or larger- volume
cohort. Furthermore, these new market entries would be competing under
the HHVBP model in the first full calendar year following the full
calendar year baseline period.
HHAs would be notified in advance of their first performance level
and payment adjustment being finalized, based on the 2016 performance
period (January 1, 2016 to December 31, 2016), with their first payment
adjustment to be applied January 1, 2018 through December 31, 2018.
Each HHA would be notified of this first pending payment adjustment on
August 1, 2017 and a preview period would run for 10 days through
August 11, 2017. This preview period would provide each competing HHA
an opportunity to reconcile any performance assessment issues relating
to the calculation of scores prior to the payment adjustment taking
effect, in accordance with the process proposed in section H--Preview
and Period to Request Recalculation. Once the preview period ends, any
changes would be reconciled and a report finalized no later than
November 1, 2017 (or 60 days prior to the payment adjustment taking
affect).
Subsequent payment adjustments would be calculated based on the
applicable full calendar year of performance data from the quarterly
reports, with HHAs notified and payments adjusted, respectively, every
year thereafter. As a sequential example, the second payment adjustment
would occur January 1, 2019 based on a full 12 months of the CY 2017
performance period. Notification of the adjustment
[[Page 39875]]
would occur on August 1, 2018, along with the preview period
transpiring through August 11, 2018 and followed by reconciliation
through September 10, 2018. Subsequent payment adjustments would
continue to follow a similar timeline and process. We seek public
comment on this payment adjustment schedule.
Beginning in CY 2019, we may consider revising this payment
adjustment schedule and updating the payment adjustment more frequently
than once each year if it is determined that a more timely application
of the adjustment as it relates to performance improvement efforts that
have transpired over the course of a calendar year would generate
increased improvement in quality measures. Specifically, we would
expect that having payment adjustments transpire closer together
through more frequent performance periods would accelerate improvement
in quality measures because HHAs would be able to justify earlier
investments in quality efforts and be incentivized for improvements. In
effect, this concept may be operationalized to create a smoothing
effect where payment adjustments are based on overlapping 12-month
performance periods that occur every 6 months rather than annually. As
an example, the normal 12-month performance period occurring from
January 1, 2020 to December 31, 2020 might have an overlapping 12-month
performance period occurring from July 1, 2020 to June 30, 2021.
Following the regularly scheduled January 1, 2022 payment adjustments,
the next adjustments could be applied to payments beginning on July 1,
2022 through December 31, 2022. Depending on if and when more frequent
payment adjustments would be applied, performance would be calculated
based on the applicable 12-months of performance data, HHAs notified,
and payments adjusted, respectively, every six months thereafter, until
the conclusion of the model. As a result, separate performance periods
would have a 6-month overlap through the conclusion of the model. HHAs
would be notified through rulemaking and be given the opportunity to
comment on any proposed changes to the frequency of payment
adjustments. We seek public comment on the proposed payment adjustment
schedule described above.
E. Quality Measures
1. Objectives
Initially, we propose the measures for the HHVBP model would be
predominantly drawn from the current Outcome and Assessment Information
Set (OASIS),\28\ which is familiar to the home health industry and
readily available for utilization by the proposed model. In addition,
the HHVBP model provides us with an opportunity to examine a broad
array of quality measures that address critical gaps in care. A recent
comprehensive review of the VBP experience over the past decade,
sponsored by the Office of the Assistant Secretary for Planning and
Evaluation (ASPE), identified several near- and long-term objectives
for HHVBP measures.\29\ The recommended objectives emphasize measuring
patient outcomes and functional status; appropriateness of care; and
incentives for providers to build infrastructure to facilitate
measurement within the quality framework.\30\ The following seven
objectives derived from this study served as guiding principles for the
selection of the proposed measures for the HHVBP model:
---------------------------------------------------------------------------
\28\ For detailed information on OASIS see the official CMS
OASIS web resource available at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/OASIS/?redirect=/oasis. See also industry resource available at
https://www.oasisanswers.com/index.htm, specifically updated OASIS
component information available at www.oasisanswers.com/LiteratureRetrieve.aspx?ID=215074).
\25\ U.S. Department of Health and Human Services. Office of the
Assistant Seretary for Planning and Evaluation (ASPE) (2014)
Measuring Success in Health Care Value-Based Purchasing Programs.
Cheryl L. Damberg et. al. on behalf of RAND Health.
\30\ Id.
---------------------------------------------------------------------------
1. Use a broad measure set that captures the complexity of the HHA
service provided;
2. Incorporate the flexibility to include Improving Medicare Post-
Acute Care Transformation (IMPACT) Act of 2014 proposed measures that
are cross-cutting amongst post-acute care settings;
3. Develop second-generation 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.
2. Proposed Methodology for Selection of Quality Measures
a. Direct Alignment With National Quality Strategy Priorities
A central driver of the proposed measure selection process was
incorporating innovative thinking from the field while simultaneously
drawing on the most current evidence-based literature and documented
best practices. Broadly, we propose measures that have a high impact on
care delivery and support the combined priorities of HHS and CMS to
improve health outcomes, quality, safety, efficiency, and experience of
care for patients. To frame the selection process, we utilized the
domains described in the CMS Quality Strategy that maps to the six
National Quality Strategy (NQS) priority areas (see Figure 3 for CMS
domains).\31\
---------------------------------------------------------------------------
\3131\ The CMS Quality Strategy is discussed in broad terms at
URL https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/QualityInitiativesGenInfo/CMS-Quality-Strategy.html. CMS Domains appear presentations by CMS (xxxxx) and
ONC (available at https://www.cms.gov/eHealth/downloads/Webinar_eHealth_March25_eCQM101.pdf) and a CMS discussion of the NQS
Domains can be found at URL https://www.cms.gov/Regulations-and-Guidance/Legislation/EHRIncentivePrograms/2014_ClinicalQualityMeasures.html.
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[[Page 39876]]
[GRAPHIC] [TIFF OMITTED] TP10JY15.002
b. Referenced Quality Measure Authorities
We propose at Sec. 484.315 that Medicare-certified HHAs would be
evaluated using a starter set of quality measures (``starter set''
refers to the proposed quality measures for the first year of this
model) designed to encompass multiple NQS domains, and provide future
flexibility to incorporate and study newly developed measures over
time. New and evolving measures would be considered for inclusion in
subsequent years of this model and proposed through future rulemaking.
To create the proposed starter set we began researching the current
set of OASIS measures that are being used within the health home
environment.\32\ Following that, we searched for endorsed quality
measures using the National Quality Forum (NQF) Quality Positioning
System (QPS),\33\ selecting measures that address all possible NQS
domains. We further examined measures on the CMS-generated Measures
Under Consideration (MUC) list,\34\ and reviewed other relevant
measures used within the health care industry but not currently used in
the home health setting, as well as proposed measures required by the
IMPACT Act of 2014. Finally, we searched the National Quality Measures
Clearinghouse (NQMS) to identify evidence-based measures and measure
sets.
---------------------------------------------------------------------------
\32\ All data for the starter set measures, not including New
Measures, is currently collected from HHAs under Sec. Sec. 484.20
and 484.210.
\33\ The NQF Quality Positioning System is available at https://www.qualityforum.org/QPS.
\34\ To review the MUC List see https://www.qualityforum.org/Setting_Priorities/Partnership/Measures_Under_Consideration_List_2014.aspx.
---------------------------------------------------------------------------
c. Key Policy Considerations and Data Sources
To ensure proposed measures for the HHVBP model take a more
holistic view of the patient beyond a particular disease state or care
setting, we are proposing measures, which include outcome measures as
well as process measures, that have the potential to follow patients
across multiple settings, reflect a multi-faceted approach, and foster
the intersection of health care delivery and population health. A key
consideration behind this approach is to use in performance year one
(PY1) of the model proven measures that are readily available and meet
a high impact need, and in subsequent model years augment this starter
set with innovative measures that have the potential to be impactful
and fill critical measure gap areas. All substantive changes or
additions to the proposed starter set or new measures would be proposed
for inclusion in future rulemaking. This approach to quality measure
selection aims to balance the burden of collecting data with the
inclusion of new and important measures. We carefully considered the
potential burden on HHAs to report the measure data when developing the
proposed starter set, and prioritized proposed measures that would draw
both from claims data and data already collected in OASIS.
The majority of the proposed measures in this model would use OASIS
data currently being reported to CMS and linked to state-specific CCNs
for selected states in order to promote consistency and to reduce the
data collection burden for providers. Utilizing primarily OASIS data
would allow the model to leverage reporting structures already in place
to evaluate performance and identify weaknesses in care delivery. This
model would also afford the opportunity to study measures developed in
other care settings and new to the home health industry (hereinafter
referred to as ``New Measures''). Many of the proposed New Measures
have been used in other health care settings and are readily applicable
to the home health environment (for example, influenza vaccination
coverage for health care personnel). Proposed New Measures for PY1 are
described in detail below. We
[[Page 39877]]
propose in PY1 to collect data on these New Measures which have already
been tested for validity, reliability, usability/feasibility, and
sensitivity in other health care settings but have not yet been
validated within the home health setting. HHVBP will study if their use
in the home health setting meets validity, reliability, usability/
feasibility, and sensitivity to statistical variations criteria. For
PY1, we propose HHA's would earn points to be included in the Total
Performance Score (TPS) simply for reporting data on New Measures (see
Section--Performance Scoring Methodology). To the extent we determine
that one or more of the proposed New Measures is valid and reliable for
the home health setting, we will consider proposing in future
rulemaking to score Medicare-certified HHAs on their actual performance
on the measure.
3. Proposed Measures
The initial set of measures proposed for PY1 of the model utilizes
data collected via OASIS, Medicare claims, HHCAHPS survey data, and
data reported directly from the HHAs to CMS. In total there are 10
process measures and 15 outcome measures (see Figure 4a) plus the four
New Measures (see Figure 4b). Process measures evaluate the rate of HHA
use of specific evidence-based processes of care based on the evidence
available. Outcomes measures illustrate the end result of care
delivered to HHA patients. When available, NQF endorsed measures would
be used. This set of measures would be subject to change or retirement
during subsequent model years and revised through the rulemaking
process. For example, we may propose in future rulemaking to remove one
or more of these measures if, based on the evidence, we conclude that
it is no longer appropriate for the model because, for example,
performance on it has topped-out. We would also consider proposing to
update the measure set if new measures that address gaps within the NQS
domains became available. We would also consider proposing adjustments
to the measure set based on lessons learned during the course of the
model. For instance, in light of the passage of the IMPACT Act of 2014,
which mandates the collection and use of standardized post-acute care
assessment data, we would consider proposing in future rulemaking to
adopt measures that meet the requirements of the IMPACT Act as soon as
they became available.
We seek public comment on the methodology for constructing the
proposed starter set of quality measures and on the proposed selected
measures.
---------------------------------------------------------------------------
\35\ 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.
Figure 4a--PY1 Proposed Measures \35\
--------------------------------------------------------------------------------------------------------------------------------------------------------
NQS domains Measure title Measure type Identifier Data source Numerator Denominator
--------------------------------------------------------------------------------------------------------------------------------------------------------
Clinical Quality of Care....... Improvement in Outcome....... NQF0167.......... OASIS (M1860).... Number of home health Number of home health
Ambulation- episodes of care episodes of care
Locomotion. where the value ending with a
recorded on the discharge during the
discharge assessment reporting period,
indicates less other than those
impairment in covered by generic or
ambulation/locomotion measure-specific
at discharge than at exclusions.
the start (or
resumption) of care.
Clinical Quality of Care....... Improvement in Outcome....... NQF0175.......... OASIS (M1850).... Number of home health Number of home health
Bed Transferring. episodes of care episodes of care
where the value ending with a
recorded on the discharge during the
discharge assessment reporting period,
indicates less other than those
impairment in bed covered by generic or
transferring at measure-specific
discharge than at the exclusions.
start (or resumption)
of care.
Clinical Quality of Care....... Improvement in Outcome....... NQF0174.......... OASIS (M1830).... Number of home health Number of home health
Bathing. episodes of care episodes of care
where the value ending with a
recorded on the discharge during the
discharge assessment reporting period,
indicates less other than those
impairment in bathing covered by generic or
at 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 health Number of home health
Dyspnea. episodes of care episodes of care
where the discharge ending with a
assessment indicates discharge during the
less dyspnea at reporting period,
discharge than at other than those
start (or resumption) covered by generic or
of care. measure-specific
exclusions.
[[Page 39878]]
Clinical Quality of Care....... Timely Initiation Process....... NQF0526.......... OASIS (M0102; Number of home health Number of home health
of Care. M0030). episodes of care in episodes of care
which the start or ending with
resumption of care discharge, death, or
date was either on transfer to inpatient
the Physician- facility during the
specified date or reporting period,
within 2 days of other than those
their referral date covered by generic or
or inpatient measure-specific
discharge date exclusions.
whichever is later.
For resumption of
care, per the
Medicare Condition of
Participation, the
patient must be seen
within 2 days of
inpatient discharge,
even if the physician
specifies a later
date.
Communication & Care Discharged to Outcome....... NA............... OASIS (M2420).... Number of home health Number of home health
Coordination. Community. episodes where the episodes of care
assessment completed ending with discharge
at the discharge or transfer to
indicates the patient inpatient facility
remained in the during the reporting
community after period, other than
discharge. those covered by
generic or measure-
specific exclusions.
Communication & Care Care Management: Process....... NA............... OASIS (M2102).... Multiple data elements Multiple data
Coordination. Types and elements.
Sources of
Assistance.
Efficiency & Cost Reduction.... Acute Care Outcome....... NQF0171; NQF2380 CCW (Claims)..... Number of home health Number of home health
Hospitalization: (Under review stays for patients stays that begin
Unplanned for Home Health). who have a Medicare during the 12-month
Hospitalization claim for an observation period.
during first 60 admission to an acute A home health stay is
days of Home care hospital in the a sequence of home
Health; 60 days following the health payment
Hospitalization start of the home episodes separated
during first 30 health stay. from other home
days of Home health payment
Health. episodes by at least
60 days.
Efficiency & Cost Reduction.... Emergency Outcome....... NQF0173.......... CCW (Claims)..... Number of home health Number of home health
Department Use stays for patients stays that begin
without who have a Medicare during the 12-month
Hospitalization. claim for outpatient observation period.
emergency department A home health stay is
use and no claims for a sequence of home
acute care health payment
hospitalization in episodes separated
the 60 days following from other home
the start of the home health payment
health stay. episodes by at least
60 days.
Patient Safety................. Pressure Ulcer Process....... NQF0538.......... OASIS (M1300; Number of home health Number of home health
Prevention and M2400). episodes during which episodes of care
Care. interventions to ending with
prevent pressure discharge, or
ulcers were included transfer to inpatient
in the Physician- facility during the
ordered plan of care reporting period,
and implemented other than those
(since the previous covered by generic or
OASIS assessment). measure-specific
exclusions.
Patient Safety................. Improvement in Outcome....... NQF0177.......... OASIS (M1242).... Number of home health Number of home health
Pain Interfering episodes of care episodes of care
with Activity. where the value ending with a
recorded on the discharge during the
discharge assessment reporting period,
indicates less other than those
frequent pain at covered by generic or
discharge than at the measure-specific
start (or resumption) exclusions.
of care.
[[Page 39879]]
Patient Safety................. Improvement in Outcome....... NQF0176.......... OASIS (M2020).... Number of home health Number of home health
Management of episodes of care episodes of care
Oral Medications. where the value ending with a
recorded on the discharge during the
discharge assessment reporting period,
indicates less other than those
impairment in taking covered by generic or
oral medications measure-specific
correctly at exclusions
discharge than at
start (or resumption)
of care.
Patient Safety................. Multifactor Fall Process....... NQF0537.......... OASIS (M1910).... Number of home health Number of home health
Risk Assessment episodes in which episodes of care
Conducted for patients had a multi- ending with
All Patients who factor fall risk discharge, death, or
Can Ambulate. assessment at start/ transfer to inpatient
resumption of care. facility during the
reporting period,
other than those
covered by generic or
measure-specific
exclusions.
Patient Safety................. Prior Functioning Outcome....... NQF0430.......... OASIS (M1900).... The number (or All patients in a risk
ADL/IADL. proportion) of a adjusted diagnostic
clinician's patients category with a Daily
in a particular risk Activity goal for an
adjusted diagnostic episode of care Cases
category who meet a to be included in the
target threshold of denominator could be
improvement in Daily identified based on
Activity (that is, ICD-9 codes or
ADL and IADL) alternatively, based
functioning. on CPT codes relevant
to treatment goals
focused on Daily
Activity function.
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
and.
Patient & Caregiver-Centered Willingness to Outcome....... ................. CAHPS............ NA.................... NA.
Experience. recommend the
agency.
Population/Community Health.... Depression Process....... NQF0518.......... OASIS (M1730).... Number of home health Number of home health
Assessment episodes in which episodes of care
Conducted. patients were ending with
screened for discharge, death, or
depression (using a transfer to inpatient
standardized facility during the
depression screening reporting period,
tool) at start/ other than those
resumption of care. covered by generic or
measure-specific
exclusions.
Population/Community Health.... Influenza Vaccine Process....... NA............... OASIS (M1041).... NA.................... NA.
Data Collection
Period: Does
this episode of
care include any
dates on or
between October
1 and March 31?
[[Page 39880]]
Population/Community Health.... Influenza Process....... NQF0522.......... OASIS (M1046).... Number of home health Number of home health
Immunization episodes during which episodes of care
Received for patients (a) received ending with
Current Flu vaccination from the discharge, or
Season. HHA or (b) had transfer to inpatient
received vaccination facility during the
from HHA during reporting period,
earlier episode of other than those
care, or (c) was covered by generic or
determined to have measure-specific
received vaccination exclusions.
from another provider.
Population/Community Health.... Pneumococcal Process....... NQF0525.......... OASIS (M1051).... Number of home health Number of home health
Polysaccharide episodes during which episodes of care
Vaccine Ever patients were ending with discharge
Received. determined to have or transfer to
ever received inpatient facility
Pneumococcal during the reporting
Polysaccharide period, other than
Vaccine (PPV). those covered by
generic or measure-
specific exclusions.
Population/Community Health.... Reason Process....... NA............... OASIS (M1056).... NA.................... NA.
Pneumococcal
vaccine not
received.
Clinical Quality of Care....... Drug Education on Process....... NA............... OASIS (M2015).... Number of home health Number of home health
All Medications episodes of care episodes of care
Provided to during which patient/ ending with a
Patient/ caregiver was discharge or transfer
Caregiver during instructed on how to to inpatient facility
all Episodes of monitor the during the reporting
Care. effectiveness of drug period, other than
therapy, how to those covered by
recognize potential generic or measure-
adverse effects, and specific exclusions.
how and when to
report problems
(since the previous
OASIS assessment).
--------------------------------------------------------------------------------------------------------------------------------------------------------
Figure 4b--PY1 Proposed New Measures
--------------------------------------------------------------------------------------------------------------------------------------------------------
NQS domains Measure title Measure type Identifier Data source Numerator Denominator
--------------------------------------------------------------------------------------------------------------------------------------------------------
Patient Safety................. Adverse Event for Outcome....... NA............... Reported by HHAs Number of home health Number of home health
Improper through Web episodes of care episodes of care
Medication Portal. where the discharge/ ending with a
Administration transfer assessment discharge during the
and/or Side indicated the patient reporting period,
Effects. required emergency other than those
treatment from a covered by generic or
hospital emergency measure-specific
department related to exclusions.
improper
administration or
medication side
effects (adverse drug
reactions).
[[Page 39881]]
Population/Community Health.... Influenza Process....... NQF0431 (Used in Reported by HHAs Healthcare personnel Number of healthcare
Vaccination other care through Web in the denominator personnel who are
Coverage for settings, not Portal. population who during working in the
Home Health Care Home Health). the time from October healthcare facility
Personnel. 1 (or when the for at least 1
vaccine became working day between
available) through October 1 and March
March 31 of the 31 of the following
following year: (a) year, regardless of
Received an influenza clinical
vaccination responsibility or
administered at the patient contact.
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 aged 60 beneficiaries aged 60
the patient ever years and over who years and over
received the report having ever receiving services
shingles received zoster from the HHA.
vaccination?. vaccine (shingles
vaccine).
Communication & Care Advanced Care Process....... NQF0326.......... Reported by HHAs Patients who have an All patients aged 65
Coordination. Plan. through Web advance care plan or years and older.
Portal. 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.
--------------------------------------------------------------------------------------------------------------------------------------------------------
4. Additional Information on HHCAHPS
Figure 5 provides details on the elements of the Home Health Care
Consumer Assessment of Healthcare Providers and Systems Survey
(HHCAHPS) we propose to include in the PY1 starter set. The HHVBP model
would not alter the HHCAHPS current scoring methodology or the
participation requirements in any way. Details on participation
requirements for HHCAHPS can be found at 42 CFR 484.250 \36\ and
details on HHCAHPS scoring methodology are available at https://homehealthcahps.org/SurveyandProtocols/SurveyMaterials.aspx.\37\
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\36\ 76 FR 68606, Nov. 4, 2011, as amended at 77 FR 67164, Nov.
8, 2012; 79 FR 66118, Nov. 6, 2014.
\37\ Detailed scoring information is contained in the Protocols
and Guidelines manual posted on the HHCAHPS Web site and available
at https://homehealthcahps.org/Portals/0/PandGManual_NOAPPS.pdf.
[[Page 39882]]
Figure 5--Home Health Care Consumer Assessment of Healthcare Providers
and Systems Survey (HHCAHPS) Composites
------------------------------------------------------------------------
Response categories
------------------------------------------------------------------------
Care of Patients:
Q9. In the last 2 months of care, how Never, Sometimes, Usually,
often did home health providers from Always.
this agency seem informed and up-to-
date about all the care or treatment
you got at home?.
Q16. In the last 2 months of care, how Never, Sometimes, Usually,
often did home health providers from Always.
this agency treat you as gently as
possible?.
Q19. In the last 2 months of care, how Never, Sometimes, Usually,
often did home health providers from Always.
this agency treat you with courtesy
and respect?.
Q24. In the last 2 months of care, did Yes, No.
you have any problems with the care
you got through this agency?.
Communications Between Providers &
Patients:
Q2. When you first started getting Yes, No.
home health care from this agency,
did someone from the agency tell you
what care and services you would get?.
Q15. In the past 2 months of care, how Never, Sometimes, Usually,
often did home health providers from Always.
this agency keep you informed about
when they would arrive at your home?.
Q17. In the past 2 months of care, how Never, Sometimes, Usually,
often did home health providers from Always.
this agency explain things in a way
that was easy to understand?.
Q18. In the past 2 months of care, how Never, Sometimes, Usually,
often did home health providers from Always.
this agency listen carefully to you?.
Q22. In the past 2 months of care, Yes, No.
when you contacted this agency's
office did you get the help or advice
you needed?.
Q23. When you contacted this agency's Same day; 1 to 5 days; 6 to
office, how long did it take for you 14 days; More than 14 days.
to get the help or advice you needed?.
Specific Care Issues:
Q3. When you first started getting Yes, No.
home health care from this agency,
did someone from the agency talk with
you about how to set up your home so
you can move around safely?.
Q4. When you started getting home Yes, No.
health care from this agency, did
someone from the agency talk with you
about all the prescription medicines
you are taking?.
Q5. When you started getting home Yes, No.
health care from this agency, did
someone from the agency ask to see
all the prescription medicines you
were taking?.
Q10. In the past 2 months of care, did Yes, No.
you and a home health provider from
this agency talk about pain?.
Q12. In the past 2 months of care, did Yes, No.
home health providers from this
agency talk with you about the
purpose for taking your new or
changed prescription medicines?.
Q13. In the last 2 months of care, did Yes, No.
home health providers from this
agency talk with you about when to
take these medicines?.
Q14. In the last 2 months of care, did Yes, No.
home health providers from this
agency talk with you about the
important side effects of these
medicines?.
Global Type Measures:
What is your overall rating of your Use a rating scale (1-10).
home health care?.
Would you be willing to recommend this Never, Sometimes, Usually,
home health agency to family and Always.
friends?.
------------------------------------------------------------------------
5. New Measures
As discussed in the previous section, the New Measures we propose
are not currently reported by Medicare-certified HHAs to CMS, but we
believe fill gaps in the NQS Domains not completely covered by existing
measures in the home health setting. All Medicare-certified HHAs in
selected states, regardless of cohort size or number of episodes, will
be required to submit data on the New Measures for all Medicare
beneficiaries to whom they provide home health services within the
state (unless an exception applies). We propose at Sec. 484.315 that
HHAs will be required to report data on these New Measures. Competing
Medicare-certified HHAs would submit data through a dedicated HHVBP
web-based platform. This web-based platform would function as a means
to collect and distribute information from and to competing Medicare-
certified HHAs. Also, for those HHAs with a sufficient number of
episodes of care to be subject to a payment adjustment, New Measures
scores included in the final TPS for PY1 are only based on whether the
HHA has submitted data to the HHVBP web-based platform or not. We are
proposing the following New Measures for competing Medicare-certified
HHAs:
Advance Care Planning;
Adverse Event for Improper Medication Administration and/
or Side Effects;
Influenza Vaccination Coverage for Home Health Care
Personnel; and,
Herpes Zoster (Shingles) Vaccination received by HHA
patients.
a. Advance Care Planning
Advance Care Planning is an NQF-endorsed process measure in the NQS
domain of Person- and Caregiver-centered experience and outcomes (see
Figure 3). This measure is currently endorsed at the group practice/
individual clinician level of analysis. We believe its adoption under
the HHVBP model represents an opportunity to study this measure in the
home health setting. This is an especially pertinent measure for home
health care to ensure that the wishes of the patient regarding their
medical, emotional, or social needs are met across care settings. The
Advance Care Planning measure would focus on Medicare beneficiaries,
including dually-eligible beneficiaries.
The measure would be numerically expressed by a ratio whose
numerator and denominator are as follows:
Numerator: The measure would calculate the percentage of patients
age 18 years and older served by the HHA that have an advance care plan
or surrogate decision maker \38\ documented
[[Page 39883]]
in the clinical record or documentation in the clinical record that an
advance 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.
---------------------------------------------------------------------------
\38\ A surrogate decision maker, also known as a health care
proxy or agent, advocates for patients who are unable to make
decisions or speak for themselves about personal health care such
that someone else must provide direction in decision-making, as the
surrogate decision-maker.
---------------------------------------------------------------------------
Denominator: All patients aged 65 years and older admitted to the
HHA.
Information on this numerator and denominator would be reported by
HHAs through the HHVBP web-based platform, in addition to other
information related to this measure as the Secretary deems appropriate.
Advance care planning ensures that the health care plan is
consistent with the patient's wishes and preferences. Therefore,
studying this measure within the HHA environment allows for further
analysis of planning for the ``what ifs'' that may occur during the
patient's lifetime. In addition, the use of this measure is expected to
result in an increase in the number of patients with advance care
plans. Increased advance care planning among the elderly is expected to
result in enhanced patient autonomy and reduced hospitalizations and
in-hospital deaths.\39\
---------------------------------------------------------------------------
\39\ Lauren Hersch Nicholas, Ph.D., MPP et al. Regional
Variation in the Association Between Advance Directives and End-of-
Life Medicare Expenditures. JAMA. 2011; 306(13): 1447-1453.
doi:10.1001/jama.2011.1410.
---------------------------------------------------------------------------
We welcome public comments on this measure's proposed adoption
under the HHVBP model.
b. Adverse Event for Improper Medication Administration and/or Side
Effects
Adverse Event for Improper Medication Administration and/or Side
Effects is a measure that aligns with the NQS domain of Safety
(specifically ``medication safety''--see Figure 3) with the goal of
making care safer by reducing harm caused in the delivery of care.
An adverse drug event (ADE) is an injury related to medication
use.\40\ More specifically, it is ``an injury resulting from medical
intervention related to a drug'' and ``encompasses harms that occur
during medical care that are directly caused by the drug including but
not limited to medication errors, adverse drug reactions and
overdoses.'' \41\ A medication error is a mishap ``that occur[s] during
prescribing, transcribing, dispensing, administering, adherence, or
monitoring a drug'' and should be distinguished from an adverse drug
reaction, which is harm directly caused by the drug at normal doses,
during normal use.\42\ The National Quality Forum has included ADEs as
a Serious Reportable Event (SRE) in the category of Care Management,
defining said event as a ``patient death or serious injury associated
with a medication error (for example, errors involving the wrong drug,
wrong dose, wrong patient, wrong time, wrong rate, wrong preparation,
or wrong route of administration)'', noting that ``. . . the high rate
of medication errors resulting in injury and death makes this event
important to endorse again.'' \43\
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\40\ Reporting of Adverse Drug Events: Examination of a Hospital
Incident Reporting System. Radhika Desikan, Melissa J. Krauss, W.
Claiborne Dunagan, Erin Christensen Rachmiel, Thomas Bailey,
Victoria J. Fraser https://www.ahrq.gov/professionals/quality-patient-safety/patient-safety-resources/resources/advances-in-patient-safety/vol1/Desikan.pdf.
\41\ The Office of Disease Prevention and Health Promotion
(ODPHP), National Action Plan for ADE Prevention, available at:
https://www.health.gov/hai/pdfs/ADE-Action-Plan-Executive-Summary.pdf, citing VA Center for Medication Safety And VHA Pharmacy
Benefits Management Strategic Healthcare Group and the Medical
Advisory Panel Adverse Drug Events, Adverse Drug Reactions and
Medication Errors Frequently Asked Questions (November 2006),
available at: https://www.va.gov/ms/professionals/medications/adverse_drug_reaction_faq.pdfhttps://www.va.gov/ms/professionals/medications/adverse_drug_reaction_faq.pdf.
\42\ VA Center for Medication Safety And VHA Pharmacy Benefits
Management Strategic Healthcare Group and the Medical Advisory Panel
Adverse Drug Events, Adverse Drug Reactions and Medication Errors
Frequently Asked Questions (November 2006), available at: https://www.va.gov/ms/professionals/medications/adverse_drug_reaction_faq.pdf.https://www.va.gov/ms/professionals/medications/adverse_drug_reaction_faq.pdf. Note that this VA
document urges that the term Adverse Drug Reaction should generally
be used rather than the term ``side effect'' because the latter ''
tends to normalize the concept of injury from drugs. This approach
has been adopted in the National Action Plan for ADE Prevention, in
which the term ``side effects'' does not appear. See: The Office of
Disease Prevention and Health Promotion (ODPHP), National Action
Plan for ADE Prevention, available at: https://www.health.gov/hai/pdfs/ADE-Action-Plan-Executive-Summary.pdf.
\43\ National Quality Forum, Serious Reportable Events in
Healthcare-2011, at 9. (2011), available at: https://www.qualityforum.org/Publications/2011/12/Serious_Reportable_Events_in_Healthcare_2011.aspxhttps://www.qualityforum.org/Publications/2011/12/Serious_Reportable_Events_in_Healthcare_2011.aspx.
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The annual incidence of ADEs in health care in the United States is
high; authoritative estimates indicate that each year 400,000
preventable ADEs occur in hospitals, 800,000 in long term care settings
and in excess of 500,000 among Medicare patients in outpatient
settings.\44\ The cost of ADEs occurring in hospitals alone has been
estimated at $5.6 billion.\45\ Older patients are particularly
vulnerable to adverse drug reactions and are seven times as likely as
younger persons to experience an adverse drug event requiring
hospitalization.\46\ Further, we are specifically concerned that
``Analyses of cost data indicate that Medicare patients experience
significantly higher rates of ADEs than both privately insured and
Medicaid-covered patients.'' \47\ Prevention of ADEs is a national
Patient Safety Priority pursuant to the ADE National Action Plan, which
focuses on vulnerable population groups, one of which is the elderly.
Most work on ADEs has taken place in the hospital setting. There is
little available data regarding the incidence and types of ADEs
occurring in home health care for the elderly under Medicare. We
believe there is a critical need for such information with regard to
patient safety, and we are proposing this measure to address that need.
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\44\ The Institute of Medicine, Preventing Medication Errors
(2006), at 5.). Available at: https://books.nap.edu/openbook.php?record_id=11623&page=5.
\45\ National Quality Forum, NQF-Endorsed Measures for Patient
Safety DRAFT REPORT FOR COMMENT (May 28, 2014), at 6. Available at:
www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id.
\46\ Emergency Hospitalizations for Adverse Drug Events in Older
Americans Daniel S. Budnitz, M.D., M.P.H., Maribeth C. Lovegrove,
M.P.H., Nadine Shehab, Pharm.D., M.P.H., and Chesley L. Richards,
M.D., M.P.H.,N Engl J Med 2011; 365: 2002-2012 available at: https://www.nejm.org/doi/full/10.1056/NEJMsa1103053.
\47\ The Office of Disease Prevention and Health Promotion
(ODPHP), National Action Plan for ADE Prevention, available at:
https://www.health.gov/hai/pdfs/ADE-Action-Plan-Executive-Summary.pdf.
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The measure would be numerically expressed by a ratio whose
numerator and denominator are as follows:
Numerator: Number of home health episodes of care where the
discharge/transfer assessment indicated the patient required emergency
treatment from a hospital emergency department related to improper
administration or medication side effects (adverse drug reactions).
Denominator: Number of home health episodes of care ending with a
discharge during the performance period. Numbers to be specifically
excluded from the ratio as a measure-specific exclusion are those
relating to home health episodes of care for which emergency department
use or the reason for emergency department use is unknown at transfer
or discharge. Stated otherwise, the measure would be expressed by a
ratio indicating the relationship between (i) the number of emergency
treatments transferring or discharged patients sought or received for
OASIS C M2310, ``1-Improper medication administration, adverse drug
reactions, medication side effects, toxicity, anaphylaxis'' and (ii)
the number of emergency treatments sought or received for one of the
other reasons identified by OASIS-C M2310. Neither
[[Page 39884]]
number would include (a) incidents where the reason checked on M2310 is
``UK-Reason unknown'' or (b) incidents where use of emergency
department was unknown at transfer or discharge. Data for this measure
would be reported by HHAs through the dedicated HHVBP web-based
platform based on OASIS C/ICD 9/10 Items M2300 Emergent Care and M2310
Reasons for Emergent Care, in addition to other information related to
this measure as the Secretary deems appropriate.
We welcome public comments on this measure's proposed adoption
under the HHVBP model.
c. Influenza Vaccination Coverage for Home Health Care Personnel
Staff Immunizations (Influenza Vaccination Coverage among Health
Care Personnel) (NQF #0431) is an NQF-endorsed measure that addresses
the NQS domain of Population Health (see Figure 3). The measure is
currently endorsed in Ambulatory Care; Ambulatory Surgery Center (ASC),
Ambulatory Care; Clinician Office/Clinic, Dialysis Facility, Hospital/
Acute Care Facility, Post-Acute/Long Term Care Facility; Inpatient
Rehabilitation Facility, Post-Acute/Long Term Care Facility; Long Term
Acute Care Hospital, and Post-Acute/Long Term Care Facility: Nursing
Home/Skilled Nursing Facility. Home health care is among the only
remaining settings for which the measure has not been endorsed. We
believe the proposed HHVBP model presents an opportunity to study this
measure in the home health setting. This measure is currently reported
in multiple CMS quality reporting programs, including Ambulatory
Surgical Center Quality Reporting, Hospital Inpatient Quality
Reporting, and Long-Term Care Hospital Quality Reporting; we believe
its adoption under the proposed HHVBP model presents an opportunity for
alignment in our quality programs. The documentation of staff
immunizations is also a standard required by many HHA accrediting
organizations. We believe that this measure would be appropriate for
HHVBP because it addresses total population health across settings of
care by reducing the exposure of individuals to a potentially avoidable
virus.
The measure would be numerically expressed by a ratio whose
numerator and denominator are as follows:
Numerator: The measure would calculate the percentage of home
health care personnel who receive the influenza vaccine, and document
those who do not receive the vaccine in the articulated categories
below:
(1) Received an influenza vaccination administered at the health
care agency, or reported in writing (paper or electronic) or provided
documentation that influenza vaccination was received elsewhere; or
(2) Were determined to have a medical contraindication/condition of
severe allergic reaction to eggs or to other component(s) of the
vaccine, or history of Guillain-Barr[eacute] Syndrome within 6 weeks
after a previous influenza vaccination; or
(3) Declined influenza vaccination; or
(4) Persons with unknown vaccination status or who do not otherwise
meet any of the definitions of the above-mentioned numerator
categories.
Each of the above groups would be divided by the number of health
care personnel who are working in the HHA for at least one working day
between October 1 and March 31 of the following year, regardless of
clinical responsibility or patient contact.
Denominator: This measure collects the number of home health care
personnel who, during the flu season: \48\ Denominators are to be
calculated separately for the following three groups:
---------------------------------------------------------------------------
\48\ Flu season is generally October 1 (or when the vaccine
became available) through March 31 of the following year. See URL
https://www.cdc.gov/flu/about/season/flu-season.htm for detailed
information.
---------------------------------------------------------------------------
1. Employees: All persons who receive a direct paycheck from the
reporting HHA (that is, on the agency's payroll);
2. Licensed independent practitioners: Include physicians (MD, DO),
advanced practice nurses, and physician assistants only who are
affiliated with the reporting agency who do not receive a direct
paycheck from the reporting HHA; and
3. Adult students/trainees and volunteers: Include all adult
students/trainees and volunteers who do not receive a direct paycheck
from the reporting HHA.
This proposed measure for the HHVBP model is expected to result in
increased influenza vaccination among home health professionals.
Reporting health care personnel influenza vaccination status would
allow HHAs to better identify and target unvaccinated personnel.
Increased influenza vaccination coverage among HHA personnel would be
expected to result in reduced morbidity and mortality related to
influenza virus infection among patients, especially elderly and
vulnerable populations.\49\
---------------------------------------------------------------------------
\49\ Carman W.F., Elder A.G., Wallace L.A., et al. Effects of
influenza vaccination of health-care workers on mortality of elderly
people in long-term care: A randomized controlled trial. Lancet
2000; 355:93-97.
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Information on the above numerator and denominator would be
reported by HHAs through the HHVBP web-based platform, in addition to
other information related to this measure as the Secretary deems
appropriate. We welcome public comments on this measure's proposed
adoption under the HHVBP model.
d. Herpes Zoster Vaccine (Shingles Vaccine) for Patients
We are proposing to adopt this measure for the HHVBP model because
it aligns with the NQS Quality Strategy Goal to Promote Effective
Prevention & Treatment of Chronic Disease. Currently this proposed
measure is not endorsed by NQF or collected in OASIS. However, due to
the severe physical consequences of symptoms associated with
shingles,\50\ we view its adoption under the HHVBP model as an
opportunity to perform further study on this measure. The results of
this analysis could provide the necessary data to meet NQF endorsement
criteria. The measure would calculate the percentage of home health
patients who receive the Shingles vaccine, and collect the number of
patients who did not receive the vaccine.
---------------------------------------------------------------------------
\50\ For detailed information on Shingles incidences and known
complications associated with this condition see CDC information
available at https://www.cdc.gov/shingles/about/overview.html.
---------------------------------------------------------------------------
Numerator: Equals the total number of Medicare beneficiaries aged
60 years and over who report having ever received herpes zoster vaccine
(shingles vaccine) during the home health episode of care.
Denominator: Equals the total number of Medicare beneficiaries aged
60 years and over receiving services from the HHA.
The Food and Drug Administration (FDA) has approved the use of
herpes zoster vaccine in adults age 50 and older. In addition, the
Advisory Committee on Immunization Practices (ACIP) currently
recommends that herpes zoster vaccine be routinely administered to
adults, age 60 years and older.\51\ In 2013, 24.2 percent of adults 60
years and older reported receiving herpes zoster vaccine to prevent
shingles, an increase from the 20.1 percent in 2012,\52\ yet below the
targets
[[Page 39885]]
recommended in the HHS Healthy People 2020 initiative.\53\
---------------------------------------------------------------------------
\51\ CDC. Morbidity and Mortality Weekly Report 2011;
60(44):1528.
\52\ CDC. Morbidity and Mortality Weekly Report 2015; 64(04):95-
102.
\53\ Healthy People 2020: Objectives and targets for
immunization and infectious diseases. Available at https://www.healthypeople.gov/2020/topics-objectives/topic/immunization-and-infectious-diseases/objectives.
---------------------------------------------------------------------------
The incidence of herpes zoster outbreak increases as people age,
with a significant increase after age 50. Older people are more likely
to experience the severe nerve pain known as post-herpetic neuralgia
(PHN),\54\ the primary acute symptom of shingles infection, as well as
non-pain complications, hospitalizations,\55\ and interference with
activities of daily living.\56\ Studies have shown for adults aged 60
years or older the vaccine's efficacy rate for the prevention of herpes
zoster is 51.3 percent and 66.5 percent for the prevention of PHN for
up to 4.9 years after vaccination.\57\ The Short-Term Persistence Sub
study (STPS) followed patients 4 to 7 years after vaccination and found
a vaccine efficacy of 39.6 percent for the prevention of herpes zoster
and 60.1 percent for the prevention of PHN.\58\ The majority of
patients reporting PHN are over age 70; vaccination of this older
population would prevent most cases, followed by vaccination at age 60
and then age 50.
---------------------------------------------------------------------------
\54\ Yawn B.P., Saddier P., Wollen P.C., St Sauvier J.L.,
Kurland M.J., Sy L.S. A population-based study of the incidence and
complication rate of herpes zoster before zoster vaccine
introduction. Mayo Clinic Proc 2007; 82:1341-9.
\55\ Lin F., Hadler J.L. Epidemiology of primary varicella and
herpes zoster hospitalizations: The pre-varicella vaccine era. J
Infect Dis 2000; 181:1897-905.
\56\ Schmader K.E., Johnson G.R., Saddier P., et al. Effect of a
zoster vaccine on herpes zoster-related interference with functional
status and health-related quality-of-life measures in older adults.
J Am Geriatr Soc 2010; 58:1634-41.
\57\ Schmader K.E., Johnson G.R., Saddier P., et al. Effect of a
zoster vaccine on herpes zoster0-related interference with
functional status and health-related quality-of-life measures in
older adults. J Am Geriatr Soc 2010; 58:1634-41.
\58\ Schmader K.E., Oxman M.N., Levin M.J., Johnson G., Zhang
J.H., Betts R., Morrison V.A., Gelb L., Guatelli J.C., Harbecke R.,
Pachucki C., Keay S., Menzies B., Griffin M.R., Kauffman C., Marques
A., Toney J., Keller P.M., LI,X, Chan L.S.F., Annumziato P.
Persistence of the Efficacy of Zoster Vaccine in the Shingles
Prevention Study and the Short Term Persistence Substudy. Clinical
Infectious Disease 2012; 55:1320-8.
---------------------------------------------------------------------------
Studying this measure in the home health setting presents an ideal
opportunity to address a population at risk which would benefit greatly
from this vaccination strategy. For example, receiving the vaccine will
often reduce the course and severity of the disease and reduce the risk
of post herpetic neuralgia.
Information on the above numerator and denominator would be
reported by HHAs through the HHVBP web-based platform, in addition to
other information related to this measure as the Secretary deems
appropriate. We welcome public comments on this measure's proposed
adoption under the HHVBP model.
6. HHVBP Model's Four Classifications
As previously stated, the quality measures that we are proposing to
use in the performance years are aligned with the six NQS domains:
Patient and Caregiver-centered experience and outcomes; Clinical
quality of care; Care coordination; Population Health; Efficiency and
cost reduction; and, Safety (see Figure 6).
We propose to filter these NQS domains and the proposed HHVBP
quality measures into four classifications to align directly with the
measure weighting utilized in calculating payment adjustments. The four
HHVBP classifications we are proposing are: Clinical Quality of Care,
Outcome and Efficiency, Person- and Caregiver-Centered Experience, and
New Measures reported by the HHAs.
These four classifications capture the multi-dimensional nature of
health care provided by the HHA. These classifications are further
defined as:
Classification I--Clinical Quality of Care: Measures the
quality of health care services provided by eligible professionals and
paraprofessionals within the home health environment.
Classification II--Outcome and Efficiency: Outcomes
measure the end result of care provided to the beneficiary.
Efficiencies measure maximizing quality and minimizing use of
resources.
Classification III--Person- and Caregiver-Centered
Experience: Measures the beneficiary and their caregivers' experience
of care.
Classification IV--New Measures: Measures not currently
reported by Medicare-certified HHAs to CMS, but that may fill gaps in
the NQS Domains not completely covered by existing measures in the home
health setting.
We seek public comment on our proposed measure classifications for
the HHVBP model.
[[Page 39886]]
[GRAPHIC] [TIFF OMITTED] TP10JY15.003
7. Weighting
We propose that measures within each classification will be
weighted the same for the purposes of payment adjustment. We are
weighting at the individual measure level and not the classification
level. Classifications are for organizational purposes only. We
selected this approach since we did not want any one measure within a
classification to be more important than another measure. This approach
ensures that a measure's weight will remain the same even if some of
the measures within a classification group have no available data.
Weighting will be re-examined in subsequent years of the model and be
subject to the rulemaking process.
We welcome public comments on this proposed weighting methodology
under the HHVBP model.
F. Performance Scoring Methodology
1. Performance Calculation Parameters
The methodology we are proposing for assessing each HHA's total
annual performance is based on a score calculated using the proposed
starter set of quality measures that apply to the HHA (based on a
minimum number of cases, as discussed herein). The methodology we
propose would provide an assessment on a quarterly basis for each HHA
and would result in an annual distribution of value-based payment
adjustments among HHAs so that HHAs achieving the highest performance
scores would receive the largest upward payment adjustment. The
methodology we are proposing includes three primary features:
The HHA's Total Performance Score (TPS) would be
determined using the higher of an HHA's achievement or improvement
score for each measure;
All measures in the Clinical Quality of Care, Outcome and
Efficiency, and Person and Caregiver-Centered Experience
classifications will have equal weight and will account for 90 percent
of the TPS (see section 2 below) regardless of the number of measures
in the three classifications. Points for New Measures are awarded for
submission of data on the New Measures via the HHVBP web-based
platform, and withheld if data is not submitted. Data reporting for
each New Measure will have equal weight and will account for 10 percent
of the TPS for the first performance year; and,
The HHA performance score would reflect all of the
measures that apply to the HHA based on a minimum number of cases
defined below.
2. Considerations for Calculating the Total Performance Score
In Sec. 484.320 we propose to calculate the TPS by adding together
points awarded to Medicare-certified HHAs on the starter set of
measures, including the New Measures. We considered several factors
when developing the proposed performance scoring methodology for the
HHVBP model. First, we believe it is important that the performance
scoring methodology be straightforward and transparent to HHAs,
patients, and other stakeholders. HHAs must be able to clearly
understand performance scoring methods and performance expectations to
maximize quality improvement efforts. The public must understand
performance score methods to utilize publicly-reported information when
choosing HHAs.
Second, we believe the proposed performance scoring methodology for
the HHVBP model should be aligned appropriately with the quality
measurements adopted for other Medicare value-based purchasing programs
including those introduced in the hospital and skilled nursing home
settings. This alignment would facilitate the public's understanding of
quality measurement information disseminated in these programs and
foster more informed consumer decision-making about their health care
choices.
Third, we believe that differences in performance scores must
reflect true differences in quality performance. To ensure that this
point is addressed in the proposed performance scoring methodology for
the HHVBP model, we assessed quantitative characteristics of the
measures, including the current
[[Page 39887]]
state of measure development, number of measures, and the number and
grouping of measure classifications.
Fourth, we believe that both quality achievement and improvement
must be measured appropriately in the performance scoring methodology
for the HHVBP model. The proposed methodology specifies that
performance scores under the HHVBP model are calculated utilizing the
higher of achievement or improvement scores for each measure. The
impact of performance scores utilizing achievement and improvement on
HHAs' behavior and the resulting payment implications was also
considered. Using the higher of achievement or improvement scores
allows the model to recognize HHAs that have made great improvements,
though their measured performance score may still be relatively lower
in comparison to other HHAs.
Fifth, through careful measure selection we intend to eliminate, or
at least control for, unintended consequences such as undermining
better outcomes to patients or rewarding inappropriate care. As
discussed above, when available, NQF endorsed measures would be used.
In addition we propose to adopt measures that we believe are closely
associated with better outcomes in the HHA setting in order to
incentivize genuine improvements and sustain positive achievement while
retaining the integrity of the model.
Sixth, we intend to ensure the model utilizes the most currently
available data to assess HHA performance. We recognize that these data
would not be available instantaneously due to the time required to
process quality measurement information accurately; however, we intend
to make every effort to process data in the timeliest fashion. Using
more current data would result in a more accurate performance score
while recognizing that HHAs need time to report measure data.
3. Additional Considerations for the Proposed HHVBP Total Performance
Scores
Many of the key elements of the proposed HHVBP model performance
scoring methodology would be aligned with the scoring methodology of
the Hospital Value-Based Purchasing Program (HVBP) in order to leverage
the rigorous analysis and review underpinning that Program's approach
to value-based purchasing in the hospital sector. The HVBP Program
includes as one of its core elements the scoring methodology included
in the 2007 Report to Congress ``Plan to Implement a Medicare Hospital
Value-Based Purchasing Program'' (hereinafter referred to as ``The 2007
HVBP Report'').\59\ The 2007 HVBP Report describes a Performance
Assessment Model with core elements that can easily be replicated for
other value-based purchasing programs or models, including the HHVBP.
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\59\ The 2007 HVBP Report is available at the CMS Web site at
https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/downloads/HospitalVBPPlanRTCFINALSUBMITTED2007.pdf.
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In the HVBP Program, the Performance Assessment Model aggregates
points on the individual quality measures across different quality
measurement domains to calculate a hospital's TPS. Similarly, the
proposed HHVBP model would aggregate points on individual measures
across four measure classifications derived from the 6 CMS/NQS domains
as described above (see Figure 3) to calculate the HHA's TPS. In
addition, the proposed HHVBP payment methodology is also aligned with
the HVBP Program with respect to evaluating an HHA's performance on
each quality measure based on the higher of an achievement or
improvement score in the performance period. The proposed model is not
only designed to provide incentives for HHAs to provide the highest
level of quality, but also to provide incentives for HHAs to improve
the care they provide to Medicare beneficiaries. By rewarding HHAs that
provide high quality and/or high improvement, we believe the proposed
HHVBP model would ensure that all HHAs would be incentivized to commit
the resources necessary to make the organizational changes that would
result in better quality.
Under the proposed model an HHA would be awarded points only for
``applicable measures.'' An ``applicable measure'' is one for which the
HHA has provided 20 home health episodes of care per year. Points
awarded for each applicable measure would be aggregated to generate a
TPS. As described in the benchmark section below, HHAs would have the
opportunity to receive 0 to 10 points for each measure in the Clinical
Quality of Care, Outcome and Efficiency, and Person and Caregiver-
Centered Experience classifications. Each measure would have equal
weight regardless of the total number of measures in each of the first
three classifications. In contrast, we propose to score the New
Measures in a different way. For each New Measure, HHAs would receive
10 points if they report the New Measure or 0 points if they do not
report the measure during the performance year. In total, the New
Measures would account for 10 percent of the TPS regardless of the
number of measures applied to an HHA in the other three
classifications.
We propose to calculate the TPS for the HHVBP methodology similarly
to the TPS calculation that has been finalized under the HVBP program.
The performance scoring methodology for the HHVBP model would include
determining performance standards (benchmarks and thresholds) using the
2015 baseline period performance year's quality measure data, scoring
HHAs based on their achievement and/or improvement with respect to
those performance standards, and weighting each of the classifications
by the number of measures employed, as presented in further detail in
Section G below.
4. Setting Performance Benchmarks and Thresholds
For scoring HHAs' performance on measures in the proposed Clinical
Quality of Care, Outcome and Efficiency, and Person and Caregiver-
Centered Experience classifications, we propose that the HHVBP model
would adopt an approach using several key elements from the scoring
methodology set forth in the 2007 HVBP Report and the successfully
implemented HVBP Program \60\ including allocating points based on
achievement or improvement, and calculating those points based on
industry benchmarks and thresholds.
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\60\ For detailed information on HVBP scoring see https://www.medicare.gov/hospitalcompare/data/hospital-vbp.html.
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In determining the achievement points for each measure, HHAs would
receive points along an achievement range, which is a scale between the
achievement threshold and a benchmark. We propose to calculate the
achievement threshold as the median of all HHAs' performance on the
specified quality measure during the baseline period and to calculate
the benchmark as the mean of the top decile of all HHAs' performance on
the specified quality measure during the baseline period. Unlike the
HVBP Program that uses a national sample, this model would calculate
both the achievement threshold and the benchmark separately for each
selected state and for HHA cohort size. Under this proposed
methodology, we would have benchmarks and achievement
[[Page 39888]]
thresholds for both the larger-volume cohort and for the smaller-volume
cohort of HHAs (defined in each state based on a baseline period and
proposed to run from January 1, 2015 through December 31, 2015).
Another way HHVBP differs from the Hospital VBP is this model only uses
2015 as the baseline year for the measures included in the proposed
starter set. For the starter set used in the model, 2015 will
consistently be used as the baseline period in order to evaluate the
degree of change that may occur over the multiple years of the model.
In determining improvement points for each measure, we propose that
HHAs would receive points along an improvement range, which is a scale
indicating change between an HHA's performance during the performance
period and the baseline period. In addition, as in the achievement
calculation, the benchmark and threshold would be calculated separately
for each state and for HHA cohort size to ensure that HHAs would only
be competing with those HHAs in their state and their size cohort.
Grouping HHAs by state and size is another way that the HHVBP payment
methodology differs from the HVBP.
5. Calculating Achievement and Improvement Points
a. Achievement Scoring
We are proposing that achievement scoring under the HHVBP model
would be based on the Performance Assessment Model set forth in the
2007 HVBP Report and as implemented under the HVBP Program. An HHA
would earn 0-10 points for achievement for each measure in the Clinical
Quality of Care, Outcome and Efficiency, and Person and Caregiver-
Centered Experience classifications based on where its performance
during the performance period falls relative to the achievement
threshold and the benchmark, according to the following formula:
[GRAPHIC] [TIFF OMITTED] TP10JY15.004
All achievement points would be rounded up or down to the nearest
point (for example, an achievement score of 4.555 would be rounded to
5). HHAs would receive an achievement score as follows:
An HHA with performance equal to or higher than the
benchmark would receive the maximum of 10 points for achievement.
An HHA with performance equal to or greater than the
achievement threshold (but below the benchmark) would receive 1-9
points for achievement, by applying the formula above.
An HHA with performance less than the achievement
threshold would receive 0 points for achievement.
We welcome public comment on this proposed methodology for scoring
HHAs on achievement under the proposed HHVBP model.
b. Improvement Scoring
In keeping with the approach used by the HVBP program, we propose
that an HHA would earn 0-10 points based on how much its performance
during the performance period improved from its performance on each
measure in the proposed Clinical Quality of Care, Outcome and
Efficiency, and Person and Caregiver-Centered Experience
classifications during the baseline period. A unique improvement range
for each measure would be established for each HHA that defines the
difference between the HHA's baseline period score and the same state
and size level benchmark for the measure used in the achievement
scoring calculation described previously, according to the following
formula:
[GRAPHIC] [TIFF OMITTED] TP10JY15.005
All improvement points would be rounded to the nearest point. If an
HHA's performance on the measure during the performance period was:
Equal to or higher than the benchmark score, the HHA would
receive an improvement score of 10 points;
Greater than its baseline period score but below the
benchmark (within the improvement range), the HHA would receive an
improvement score of 0-10, based on the formula above; or
Equal to or lower than its baseline period score on the
measure, the HHA would receive 0 points for improvement.
We welcome public comments on this proposed methodology for scoring
HHAs on improvement under the proposed HHVBP model.
c. Examples of Calculating Achievement and Improvement Scores
For illustrative purposes we present the following examples of how
the proposed performance scoring methodology would be applied in the
context of the proposed measures in the proposed Clinical Quality of
Care, Outcome and Efficiency, and Person and Caregiver-Centered
Experience classifications. These HHA examples were selected from an
empirical database created from 2013/2014 data from the Home Health
Compare archived data, claims data and enrollment data to support the
development of the HHVBP permutation of the Performance Assessment
Model, and all performance scores are calculated for the pneumonia
measure, with respect to the number of individuals assessed and
administered the pneumococcal vaccine.
Figure 7 shows the scoring for HHA `A', as an example. The
benchmark calculated for the pneumonia measure in this case was 0.87
(the mean value of the top decile in 2013), and the achievement
threshold was 0.47 (the performance of the median or the 50th
percentile among HHAs in 2013). HHA A's 2014 performance rate of 0.91
during the performance period for this measure exceeds the benchmark,
so HHA A would earn 10 (the maximum)
[[Page 39889]]
points for its achievement score. The HHA's performance rate on a
measure is expressed as a decimal. In the illustration, HHA A's
performance rate of 0.91 means that 91 percent of the applicable
patients that were assessed were given the pneumococcal vaccine. In
this case, HHA A has earned the maximum number of 10 possible
achievement points for this measure and thus, its improvement score is
irrelevant in the calculation.
Figure 7 also shows the scoring for HHA `B'. As referenced below,
HHA B's performance on this measure went from 0.21 (which was below the
achievement threshold) in the baseline period to 0.70 (which is above
the achievement threshold) in the performance period. Applying the
achievement scale, HHA B would earn 6 points for achievement,
calculated as follows: [9 * ((0.70 - 0.47)/(0.87 - 0.47))] + 0.5 =
5.675, and then rounded to 6 points.
Checking HHA B's improvement score yields the following result:
Based on HHA B's period-to-period improvement, from 0.21 in the
baseline year to 0.70 in the performance year, HHA B would earn 7
points, calculated as follows: [10 * ((0.70 - 0.21)/(0.87 - 0.21))] -
0.5 = 6.92, rounded to 7 points. Because the higher of the achievement
and improvement scores is used, HHA B would receive 7 points for this
measure.
[GRAPHIC] [TIFF OMITTED] TP10JY15.006
In Figure 8, HHA `C' yielded a decline in performance on the
pneumonia measure, falling from 0.57 to 0.46 (a decline of 0.11
points). HHA C's performance during the performance period is lower
than the achievement threshold of 0.47 and, as a result, receives 0
points based on achievement. It also receives 0 points for improvement,
because its performance during the performance period is lower than its
performance during the baseline period.
[[Page 39890]]
[GRAPHIC] [TIFF OMITTED] TP10JY15.007
6. Proposed Scoring Methodology for New Measures
The HHVBP model provides us with the opportunity to study new
quality measures. The four New Measures that we have proposed to adopt
for the model for PY1 would be reported directly by the HHA and would
account for 10 percent of the TPS regardless of the number of measures
in the other three classifications. We are proposing that HHAs that
report on these measures would receive 10 points out of a maximum of 10
points for each of the 4 measures in the New Measure classification.
Hence a HHA that reports on all four measures would receive 40 points
out of a maximum of 40. An HHA would receive 0 points for each measure
that it fails to report on. If an HHA reports on all four measures, it
would receive 40 points for the classification and 10 points (40/40 *
10 points) would be added to its TPS because the New Measure
classification has a maximum weight of 10 percent. If an HHA reports on
3 of 4 measures, it would receive 30 points of 40 points available for
the classification and 7.5 points (30/40 * 10 points) added to its TPS.
If an HHA reports on 2 of 4 measures, they would receive 20 points of
40 points available for the classification and 5.0 points (20/40 * 10
points) added to their TPS. If an HHA reports on 0 of 4 measures, they
would receive 0 points and have no points added to their TPS. We intend
to update these measures through future rulemaking to allow us to study
newer, leading-edge measures as well as retire measures that no longer
require such analysis. We request comment on this proposed scoring
methodology for new measures.
7. Minimum Number of Cases for Outcome and Clinical Quality Measures
While no HHA in a selected state would be exempt from the HHVBP
model, there may be periods when an HHA does not receive a payment
adjustment because there are not an adequate number of episodes of care
to generate sufficient quality measure data. The minimum threshold for
an HHA to receive a score on a given measure is 20 home health episodes
of care per year for HHAs that have been certified for at least 6-
months. If an HHA does not meet this threshold to generate scores on
five or more of the Clinical Quality of Care, Outcome and Efficiency,
and Person and Caregiver-Centered Experience measures, no payment
adjustment will be made, and the Medicare-certified HHA would be paid
for HHA services in an amount equivalent to the amount it would have
been paid under section 1895 of the Act.\61\
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\61\ HHVBP would follow the Home Health Compare Web site policy
not to report measures on HHAs that have less than 20 observations
for statistical reasons concerning the power to detect reliable
differences in the quality of care.
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HHAs with very low volumes will either increase their volume in
later performance years and be subject to future payment adjustment, or
the HHAs' volume will remain very low and the HHAs would continue to
not have their payment adjusted in future years. Based on the most
recent data available at this time, a very small number of HHAs are
reporting on less than five of the total number of measures included in
the Clinical Quality of Care, Outcome and Efficiency, and Person and
Caregiver-Centered Experience classifications and account for less than
0.5 percent of the claims made over 1,900 HHAs delivering care within
the nine proposed selected states. We expect very little impact of very
low service volume HHAs on the model due to the low number of low
volume HHAs and because it is unlikely that a HHA will reduce the
amount of service to such a low level to avoid a payment adjustment.
Although these HHAs would not be subject to payment adjustments, they
would remain in the model and have access to the same technical
assistance as all other HHAs in the model, and would receive quality
reports on any measures for which they do have 20 episodes of care, and
a future opportunity to compete for payment adjustments.
We propose the HHA's TPS would be based on all the Clinical Quality
of Care, Outcome and Efficiency, Person and Caregiver-Centered
Experience measures and the New Measures that apply to the HHA. As
described above, each measure in the Clinical Quality of Care, Outcome
and Efficiency and Person and Caregiver-Centered
[[Page 39891]]
Experience classifications would be weighted equally. Each measure
would have an equal weight relative to the total score of the three
classifications regardless of the number of measures that are
applicable.
As an example, HHA ``A'' has at least 20 episodes of care in a 12-
month period for only 9 quality measures out of a possible 25 measures
from three of the four classifications (except the New Measures). Under
the proposed scoring methodology outlined above, HHA A would be awarded
0, 0, 3, 4, 5, 7, 7, 9, and 10 points, respectively, for these
measures. HHA A's total earned points for the three classifications
would be calculated by adding together all the points awarded to HHA A,
resulting in a total of 45 points. HHA A's total possible points would
be calculated by multiplying the total number of measures for which the
HHA reported on least 20 episodes (nine) by the maximum number of
points for those measures (10), yielding a total of 90 possible points.
HHA A's score for the three classifications would be the total earned
points (45) divided by the total possible points (90) multiplied by 90
because as mentioned in section E7, the Clinical Quality of Care,
Outcome and Efficiency, and Person and Caregiver-Centered Experience
classifications account for 90 percent of the TPS and the New Measures
classification accounts for 10 percent of the TPS, which yields a
result of 45. In this example, HHAs also reported all four numbers and
would receive the full 10 points for the new measure. As a result, the
TPS for HHA A would be 55 (45 plus 10). In addition, as specified in
Section E:7--Weighting, all measures have equal weights regardless of
their classification (except for New Measures) and the total earned
points for the three classifications can be calculated by adding the
points awarded for each such measure together. We seek public comment
on our proposal of the minimum number of cases for outcome and clinical
quality measures.
G. The Payment Adjustment Methodology
We propose to codify at 42 CFR 484.330 a methodology for applying
value-based payment adjustments to home health services under the HHVBP
model. Payment adjustments would be made to the HH PPS final claim
payment amount as calculated in accordance with Sec. 484.205 using a
linear exchange function (LEF) similar to the methodology utilized by
the HVBP Program. The LEF is used to translate an HHA's TPS into a
percentage of the value-based payment adjustment earned by each HHA
under the HHVBP model. The LEF was identified by the HVBP Program as
the simplest and most straightforward option to provide the same
marginal incentives to all hospitals, and we believe the same to be
true for HHAs. We propose the function's intercept at zero percent,
meaning those HHAs that have a TPS that is average in relationship to
other HHAs in their cohort (a zero percent), would not receive any
payment adjustment. Payment adjustments for each HHA with a score above
zero percent would be determined by the slope of the LEF. In addition
we propose to set the slope of the LEF for the first performance year,
CY 2016, so that the estimated aggregate value-based payment
adjustments for CY 2016 are equal to 5 percent of the estimated
aggregate base operating episode payment amount for CY 2018. The
estimated aggregate base operating episode payment amount is the total
amount of episode payments made to all the HHAs by Medicare in each
individual state in the larger- and smaller-volume cohorts respectively
(we are proposing nine states, which would create 18 separate aggregate
base operating episode payment amounts).
Figure 9 provides an example of how the LEF is calculated and how
it is applied to calculate the percentage payment adjustment to a HHA's
TPS. For this example, we applied the 8 percent payment adjustment
level that is proposed for the final two years of the HHVBP model. The
proposed rate for the payment adjustments for other years would be
proportionally less.
Step #1 involves the calculation of the `Prior Year Aggregate HHA
Payment Amount' (See C2 in Figure 9) that each HHA was paid in the
prior year. From claims data, all payments are summed together for each
HHA for CY 2015, the year prior to the HHVBP Model.
Step #2 involves the calculation of the `8 percent Payment
Reduction Amount' (C3 of Figure 9) for each HHA. The `Prior Year
Aggregate HHA Payment Amount' is multiplied by the `8 percent Payment
Reduction Rate'. The aggregate of the `8-percent Payment Reduction
Amount' is the numerator of the LEF.
Step #3 involves the calculation of the `Final TPS Adjusted
Reduction Amount' (C4 of Figure 9) by multiplying the `8-percent
Payment Reduction Amount' from Step #2 by the TPS (C1) divided by 100.
The aggregate of the `TPS Adjusted Reduction Amount' is the denominator
of the LEF.
Step #4 involves calculating the LEF (C5 of Figure 9) by dividing
the aggregate `8 percent Payment Reduction Amount' by the aggregate
`TPS Adjusted Reduction Amount'.
Step #5 involves the calculation of the `Final TPS Adjusted Payment
Amount' (C6 of Figure 9) by multiplying the `TPS Adjusted Reduction
Amount' (C4) by the LEF (C5). This is an intermediary value used to
calculate `Quality Adjusted Payment Rate'.
Step #6 involves the calculation of the `Quality Adjusted Payment
Rate' (C7 of Figure 9) that the HHA would receive instead of the 8
percent reduction in payment. This is an intermediary step to
determining the payment adjustment rate. For CYs 2021 and 2022, the
payment adjustment in this column would range from 0 percent to 16
percent depending on the quality of care provided.
Step #7 involves the calculation of the `Final Percent Payment
Adjustment' (C8 of Figure 9) that would be applied to the HHA payments
after the performance period. It simply involves the CY payment
adjustment percent (in 2018, 5 percent; in 2019, 5 percent; in 2020, 6
percent; in 2021, 8 percent; and in 2022, 8 percent). In this example,
we use the maximum eight-percent (8 percent) subtraction to the
`Quality Adjusted Payment Rate'. Note that the payment adjustment
percentage is capped at no more than plus or minus 8 percent for each
respective performance period and the payment adjustment would occur on
the final claim payment amount.
We invite public comments on this proposed payment adjustment
methodology.
[[Page 39892]]
Figure 9--8-Percent Reduction Sample
--------------------------------------------------------------------------------------------------------------------------------------------------------
Step 1 Step 2 Step 3 Step 4 Step 5 Step 6 Step 7
---------------------------------------------------------------------------------------------------------------
Linear
HHA TPS Prior year 8-Percent TPS adjusted exchange Final TPS Quality Final percent
aggregate HHA payment reduction function (LEF) adjusted adjusted payment
payment * reduction amount (C1/ (Sum of C3/Sum payment payment rate adjustment +/-
amount (C2*8%) 100)*C3 of C4) amount (C4*C5) (C6/C2) *100 % (C7-8%) %
--------------------------------------------------------------------------------------------------------------------------------------------------------
(C1) (C2) (C3) (C4) (C5) (C6) (C7) (C8)
--------------------------------------------------------------------------------------------------------------------------------------------------------
HHA1........................... 38 $ 100,000 $ 8,000 $ 3,040 1.93 $ 5,867 5.9 -2.1
HHA2........................... 55 145,000 11,600 6,380 1.93 12,313 8.5 0.5
HHA3........................... 22 800,000 64,000 14,080 1.93 27,174 3.4 -4.6
HHA4........................... 85 653,222 52,258 44,419 1.93 85,729 13.1 5.1
HHA5........................... 50 190,000 15,200 7,600 1.93 14,668 7.7 -0.3
HHA6........................... 63 340,000 27,200 17,136 1.93 33,072 9.7 1.7
HHA7........................... 74 660,000 52,800 39,072 1.93 75,409 11.4 3.4
HHA8........................... 25 564,000 45,120 11,280 1.93 21,770 3.9 -4.1
------------------------------------------------------------------------------------------------------------------------
Sum........................ ....... .............. 276,178 143,007 .............. 276,002 .............. ..............
--------------------------------------------------------------------------------------------------------------------------------------------------------
* Example cases.
H. Preview and Period To Request Recalculation
We are proposing to provide HHAs two separate opportunities to
review scoring information under the HHVBP model. First, HHAs will have
the opportunity to review their quarterly quality reports following
each quarterly posting; second, Medicare-certified HHAs will have the
opportunity to review their TPS and payment adjustment calculations,
and request a recalculation if a discrepancy is identified due to a CMS
error as described in this section. These processes would also help
educate and inform each competing Medicare-certified HHA on the direct
relation between the payment adjustment and performance measure scores.
The proposed model design calls for us to inform HHA quarterly of
their performance on each of the individual quality measures used to
calculate the TPS. We propose that HHAs will have 10 days after the
quarterly reports are provided to request a recalculation of a measure
scores if it believes there is evidence of a discrepancy. We would
adjust the score if it is determined that the discrepancy in the
calculated measure scores was the result of our failure to follow
measurement calculation protocols.
In addition, the proposed model design also calls for us to inform
each Medicare-certified HHA of the TPS and payment adjustment amount in
an annual report. We propose that these annual reports be provided to
Medicare-certified HHAs each August prior to the calendar year for
which the payment adjustment would be applied. Similar to quarterly
reports, HHAs will have 10 days to request a recalculation of their TPS
and payment adjustment amount from the date information is made
available. For both the quarterly reports and the annual report
containing the TPS and payment adjustments, Medicare-certified HHAs
will only be permitted to request scoring recalculations, and must
include a specific basis for the requested recalculation. We will not
be responsible for providing HHAs with the underlying source data
utilized to generate performance measure scores. Each HHA has access to
this data via the QIES system. The final TPS and payment adjustment
would then be provided to competing Medicare-certified HHAs in a final
report no later than 60 days in advance of the payment adjustment
taking effect.
The TPS from the annual performance report would be calculated
based on the calculation of performance measures contained in the
quarterly reports that have already been provided and reviewed by the
HHAs. As a result, we believe that quarterly reviews would provide
substantial opportunity to identify and correct errors and resolve
discrepancies, thereby minimizing the challenges to the annual
performance scores linked to payment adjustment.
As described above, a quarterly performance report would be
provided to all Medicare-certified HHAs within the selected states
beginning with the first quarter of CY 2016 being reported in July
2016. We propose that HHAs would submit recalculation requests for both
quarterly quality performance measure reports and for the TPS and
payment adjustment reports via an email link provided on the model-
specific Web page. The request form would be entered by a person who
has authority to sign on behalf of the HHA and be submitted within 10
days of receiving the quarterly data report or the annual TPS and
payment adjustment report.
Requests for both quarterly report measure score recalculations or
TPS and payment adjustment recalculations would contain the following
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 quarterly report measure score
recalculations or a request for TPS and payment adjustment
recalculation, CMS or its agent would:
+ 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 requested recalculation would result in a score change altering
performance measure scores or the HHA's TPS;
[[Page 39893]]
+ If recalculation would result in a performance measure score or
TPS change, conduct a review of quality data and if an error is found,
recalculate the TPS using the corrected performance data; 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.
Recalculation and subsequent communication of the results of these
determinations would occur as soon as administratively feasible
following the submission of requests. We request comment on our
proposed quarterly quality report measure review, TPS preview period,
and our proposed process for requesting recalculation of the quarterly
performance measure scores, and the TPS and payment adjustment. We
intend to codify these processes in regulation text in future
rulemaking.
Additionally, we will develop and adopt an appeals mechanism under
the model through future rulemaking in advance of the application of
any payment adjustments.
I. Evaluation
We propose to codify at 484.315(c) that HHAs in selected states
would be required to collect and report information to CMS necessary
for the purposes of monitoring and evaluating this model as required by
statute.\62\ We plan to conduct an evaluation of the proposed HHVBP
model in accordance with section 1115A(b)(4) of the Act, which requires
the Secretary to evaluate each model tested by CMMI. We consider an
independent evaluation of the model to be necessary to understand its
impacts on care quality in the home health setting. The evaluation
would be focused primarily on understanding how successful the model is
in achieving quality improvement as evidenced by HHAs' performance on
clinical care process measures, clinical outcome measures (for example,
functional status), utilization/outcome measures (for example, hospital
readmission rates, emergency room visits), access to care, and
patient's experience of care, and Medicare costs. We also intend to
examine the likelihood of unintended consequences. We intend to select
an independent evaluation contractor to perform this evaluation.
However, because the procurement for the selection of the evaluation
contractor is in progress and is subject to the finalization of the
proposed model, we cannot provide a detailed description of the
evaluation methodology here.
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\62\ See 1115A(b)(4) of the Act (42 U.S.C. 1315a).
---------------------------------------------------------------------------
We intend to use a multilevel approach to evaluation. Here, we
intend to conduct analyses at the state, HHA, and patient levels. Based
on the state groupings discussed in the section on selection of
Medicare certified HHAs, we believe there are several ways in which we
can draw comparison groups and remain open to scientifically-sound,
rigorous methods for evaluating the effect of the model intervention.
The evaluation effort may require of HHAs participating in the
Model additional data specifically for evaluation purposes. Such
requirements for additional data to carry out model evaluation would be
in compliance with 42 CFR 403.1105 which, as of January 1, 2015,
requires entities participating in the testing of a model under section
1115A to collect and report such information, including protected
health information (as defined at 45 CFR 160.103), as the Secretary
determines is necessary to monitor and evaluate the model. We would
consider all Medicare-certified HHAs providing services within a state
selected for the Model to be participating in the testing of this model
because the competing HHAs would be receiving payment from CMS under
the model.\63\
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\63\ 79 FR 67751 through 67755.
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We invite public comments on this proposed evaluation plan.
V. Proposed Provisions of 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.
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. New section
1899B of the Act is titled, ``Standardized Post-Acute Care (PAC)
Assessment Data for Quality, Payment, and Discharge Planning''. Under
section 1899B(a)(1) of the Act, certain post-acute care (PAC) providers
(defined in section 1899B(a)(2)(A) of the Act to include 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 sets out specified application dates for each of the
measures. The Secretary must specify the quality, resource use, and
other measures no later than the applicable specified application date
defined in section 1899B(a)(2)(E) of the Act.
Section 1899B(b) of the Act describes the standardized patient
assessment data that PAC providers are required to submit in accordance
with section 1899B(b)(1) of the Act; requires the Secretary, to the
extent practicable, to match claims data with standardized patient
assessment data in accordance with section 1899B(b)(2) of the Act; and
requires the Secretary, as soon as practicable, to revise or replace
existing patient assessment data to the extent that such data duplicate
or overlap with standardized patient assessment data, in accordance
with section 1899B(b)(3) of the Act.
Sections 1899B(c)(1) and (d)(1) of the Act direct the Secretary to
specify measures that relate to at least five stated quality domains
and three stated resource use and other measure domains. Section
1899B(c)(1) of the Act provides that the quality measures on which PAC
providers, including HHAs, are required to submit standardized patient
assessment data and other necessary data specified by the Secretary
must be in accordance with, at least, the following domains:
Functional status, cognitive function, and changes in
function and cognitive function;
Skin integrity and changes in skin integrity;
Medication reconciliation;
[[Page 39894]]
Incidence of major falls; and
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 (1) from a hospital or Critical Access
Hospital (CAH) to another applicable setting, including a PAC provider
or the home of the individual, or (2) from a PAC provider to another
applicable setting, including a different PAC provider, hospital, CAH,
or the home of the individual.
Section 1899B(c)(2)(A) provides that, to the extent possible, the
Secretary must require such reporting through the use of a PAC
assessment instrument and modify the instrument as necessary to enable
such use.
Section 1899B(d)(1) of the Act provides that the resource use and
other measures on which PAC providers, including HHAs, are required to
submit any necessary data specified by the Secretary, which may include
standardized assessment data in addition to claims data, must be in
accordance with, at least, the following domains:
Resource use measures, including total estimated Medicare
spending per beneficiary;
Discharge to community; and
Measures to reflect all-condition risk-adjusted
potentially preventable hospital readmission rates.
Sections 1899B(c) and (d) of the Act indicate that data satisfying
the eight measure domains in the IMPACT Act is the minimum data
reporting requirement. Therefore, the Secretary may specify additional
measures and additional domains.
Section 1899B(e)(1) of the Act requires that the Secretary
implement the quality, resource use, and other measures required under
sections 1899B(c)(1) and (d)(1) of the Act in phases consisting of
measure specification, data collection, and data analysis; the
provision of feedback reports to PAC providers in accordance with
section 1899B(f) of the Act; and public reporting of PAC providers'
performance on such measures in accordance with section 1899B(g) of the
Act. Section 1899B(e)(2) of the Act generally requires that each
measure specified by the Secretary under section 1899B of the Act be
NQF-endorsed, but authorizes an exception under which the Secretary may
select non-NQF-endorsed quality measures in the case of specified areas
or medical topics determined appropriate by the Secretary for which a
feasible or practical measure has not been endorsed by the NQF, as long
as due consideration is given to measures that have been endorsed or
adopted by a consensus organization identified by the Secretary.
Section 1899B(e)(3) of the Act provides that the pre-rulemaking process
required by section 1890A of the Act applies to quality, resource use,
and other measures specified under sections 1899B(c)(1) and (d)(1) of
the Act, but authorizes exceptions under which the Secretary may (1)
use expedited procedures, such as ad hoc reviews, as necessary in the
case of a measure required with respect to data submissions during the
1-year period before the applicable specified application date, or (2)
alternatively, waive section 1890A of the Act in the case of such a
measure if applying section 1890A of the Act (including through the use
of expedited procedures) would result in the inability of the Secretary
to satisfy any deadline specified under section 1899B of the Act with
respect to the measure.
Section 1899B(f)(1) of the Act requires the Secretary to provide
confidential feedback reports to PAC providers on the performance of
such PAC providers with respect to quality, resource use, and other
measures required under sections 1899B(c)(1) and (d)(1) of the Act
beginning 1 year after the applicable specified application date.
Section 1899B(g) of the Act requires the Secretary to establish
procedures for making available to the public information regarding the
performance of individual PAC providers with respect to quality,
resource use, and other measures required under sections 1899B(c)(1)
and (d)(1) beginning not later than 2 years after the applicable
specified application date. The procedures must ensure, including
through a process consistent with the process applied under section
1886(b)(3)(B)(viii)(VII) for similar purposes, that each PAC provider
has the opportunity to review and submit corrections to the data and
information that are to be made public with respect to the PAC provider
prior to such data being made public.
Section 1899B(h) of the Act sets out requirements for removing,
suspending, or adding quality, resource use, and other measures
required under sections 1899B(c)(1) and (d)(1) of the Act. In addition,
section 1899B(j) of the Act requires the Secretary to allow for
stakeholder input, such as through town halls, open door forums, and
mailbox submissions, before the initial rulemaking process to implement
section 1899B of the Act.
Section 2(c)(1) of the IMPACT Act amended section 1895 of the Act
to address the payment consequences for HHAs with respect to the
additional data which HHAs are required to submit under section 1899B
of the Act. These changes include the addition of a new section
1895(3)(B)(v)(IV), which requires HHAs to submit the following
additional data: (1) For the year beginning on the applicable specified
application date and subsequent years, data on the quality, resource
use, and other measures required under sections 1899B(c)(1) and (d)(1)
of the Act; and (2) for 2019 and subsequent years, the standardized
patient assessment data required under section 1899B(b)(1) of the Act.
Such data must be submitted in the form and manner, and at the time,
specified by the Secretary.
As stated above, the IMPACT Act adds a new section 1899B that
imposes new data reporting requirements for certain post-acute care
(PAC) providers, including HHAs. Sections 1899B(c)(1) and 1899B(d)(1)
collectively require that the Secretary specify quality measures and
resource use and other measures with respect to certain domains not
later than the specified application date that applies to each measure
domain and PAC provider setting. Section 1899B(a)(2)(E) delineates the
specified application dates for each measure domain and PAC provider.
The IMPACT Act also amends other sections of the Act, including section
1895(b)(3)(B)(v), to require the Secretary to reduce the otherwise
applicable PPS payment to a PAC provider that does not report the new
data in a form and manner, and at a time, specified by the Secretary.
For HHAs, amended section 1895(b)(3)(B)(v) would require the Secretary
to reduce the payment update for any HHA that does not satisfactorily
submit the new required data.
Under the current HH QRP, the general timeline and sequencing of
measure implementation occurs as follows: Specification of measures;
proposal and finalization of measures through notice-and-comment
rulemaking; HHA submission of data on the adopted measures; analysis
and processing of the submitted data; notification to HHAs regarding
their quality reporting compliance with respect to a particular year;
consideration of any reconsideration requests; and imposition of a
payment reduction in a particular year for failure to satisfactorily
submit data with respect to that year. Any payment reductions that are
taken with respect to a year begin approximately 1 year after the end
of the data submission period for that
[[Page 39895]]
year and approximately 2 years after we first adopt the measure.
To the extent that the IMPACT Act could be interpreted to shorten
this timeline, so as to require us to reduce HH PPS payment for failure
to satisfactorily submit data on a measure specified under section
1899B(c)(1) or (d)(1) of the IMPACT Act beginning with the same year as
the specified application date for that measure, such a timeline would
not be feasible. The current timeline discussed above reflects
operational and other practical constraints, including the time needed
to specify and adopt valid and reliable measures, collect the data, and
determine whether a HHA has complied with our quality reporting
requirements. It also takes into consideration our desire to give HHAs
enough notice of new data reporting obligations so that they are
prepared to timely start reporting data. Therefore, we intend to follow
the same timing and sequence of events for measures specified under
sections 1899B(c)(1) and (d)(1) of the Act that we currently follow for
other measures specified under the HH QRP. We intend to specify each of
these measures no later than the specified application dates set forth
in section 1899B(a)(2)(E) of the Act and propose to adopt them
consistent with the requirements in the Act and Administrative
Procedure Act. To the extent that we finalize a proposal to adopt a
measure for the HH QRP that satisfies an IMPACT Act measure domain, we
intend to require HHAs to report data on the measure for the year that
begins 2 years after the specified application date for that measure.
Likewise, we intend to require HHAs to begin reporting any other data
specifically required under the IMPACT Act for the year that begins 2
years after we adopt requirements that would govern the submission of
that data.
Lastly, on April 1, 2014, the Congress passed the Protecting Access
to Medicare Act of 2014 (PAMA) (Pub. L. 113-93), which stated the
Secretary may not adopt ICD-10 prior to October 1, 2015. On August 4,
2014, HHS published a final rule titled ``Administrative
Simplification: Change to the Compliance Date for the International
Classification of Diseases, 10th Revision (ICD-10-CM and ICD-10-PCS
Medical Data Code Sets'' (79 FR 45128), which announced October 1, 2015
as the new compliance date. 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.
We intended to use the OASIS-C1 to coincide with the original
implementation date of the ICD-10. The approved OASIS-C1 included
changes to accommodate coding of diagnoses using the ICD-10-CM coding
set and other important stakeholder concerns such as updating clinical
concepts, and revised item wording and response categories to improve
item clarity. This version included five (5) data items that required
the use of ICD-10 codes.
Since OASIS-C1 was revised to incorporate ICD-10 coding, it is not
feasible to implement the OASIS-C1/ICD-10 version prior to October 1,
2015, when ICD-10 is scheduled to be implemented. Due to this delay, we
had to ensure the collection and submission of OASIS data continued,
until ICD-10 could be implemented. Therefore, we have made interim
changes to the OASIS-C1 data item set to allow use with ICD-9 until
ICD-10 is adopted. The OASIS-C1/ICD-9 version was submitted to OMB for
approval until the OASIS-C1/ICD-10 version could be implemented. A 6-
month emergency approval was granted on October 7, 2014 and CMS
subsequently applied for an extension. The extension of the OASIS-C1/
ICD-9 version was reapproved under OMB control number 0938-0760 with a
current expiration date of March 31, 2018. It is important to note,
that 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 planned 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. We are 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. Information regarding the OASIS-C1 can
be located at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HomeHealthQualityInits/OASIS-C1.html. Additional
information regarding the adoption of ICD-10 can be located at https://www.cms.gov/Medicare/Coding/ICD10/?redirect=/icd10.
B. General Considerations Used for the Selection of Quality Measures
for the HH QRP
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, coupled with public
reporting of quality information, are critical to the advancement of
health care quality improvement efforts.
We seek to adopt measures for the HH QRP that promotes better,
safer, and more efficient care. Valid, reliable, relevant quality
measures are fundamental to the effectiveness of our quality reporting
programs. Therefore, selection of quality measures is a priority for
CMS in all of its quality reporting programs.
The measures selected would address the measure domains as
specified in the IMPACT Act and would be in alignment with the CMS
Quality Strategy, which is framed using the three broad aims of the
National Quality Strategy:
Better Care: Improve the overall quality of care by making
healthcare more patient-centered, reliable, accessible, and safe.
Healthy People, Healthy Communities: Improve the health of
the U.S. population by supporting proven interventions to address
behavioral, social, and environmental determinants of health in
addition to delivering higher-quality care.
Affordable Care: Reduce the cost of quality healthcare for
individuals, families, employers, and government.
In addition, our measure selection activities for the HH QRP take
into consideration input we receive from the Measure Applications
Partnership (MAP), convened by the NQF, as part of the established CMS
pre-rulemaking process required under section 1890A of the Act. The MAP
is a public-private partnership comprised of multi-stakeholder groups
convened for the primary purpose of providing input to us on the
selection of certain categories of quality and efficiency measures, as
required by section 1890A(a)(3) of the Social Security Act (the Act).
By February 1st of each year, the NQF must provide that input to us.
Input from the MAP is located at https://www.qualityforum.org/Setting_Priorities/Partnership/Measure_Applications_Partnership.aspx.
In addition, we take into account national priorities, such as those
established by the National Priorities Partnership at https://www.qualityforum.org/npp/, and the HHS Strategic Plan at https://www.hhs.gov/secretary/about/priorities/priorities.html.
We initiated an Ad Hoc MAP process for the review of the measures
under consideration for implementation in
[[Page 39896]]
preparation of the measures for adoption into the HH QRP that we must
propose through this fiscal year's rule, in order to begin implementing
such measures by 2017. We included under the List of Measures under
Consideration (MUC List) a list of measures that the Secretary must
make available to the public, as part of the pre-rulemaking process, as
described in section 1890A(a)(2) of the Act. The MAP Off-Cycle Measures
under Consideration for PAC-LTC Settings can be accessed on the
National Quality Forum Web site at: https://www.qualityforum.org/map/.
The NQF MAP met in February 2015 and provided input to us as required
under section 1890A(a)(3) of the Act. The MAP issued a pre-rulemaking
report on March 6, 2015 entitled MAP Off-Cycle Deliberations 2015:
Measures under Consideration to Implement Provisions of the IMPACT
Act--Final Report, which is available for download at: https://www.qualityforum.org/Publications/2015/03/MAP_Off-Cycle_Deliberations_2015_-_Final_Report.aspx. The MAP's input for the
proposed measure is discussed in this section.
To meet the first specified application date applicable to HHAs
under section 1899B(a)(2)(E) of the Act, which is October 1, 2017, we
have focused on measures that:
Correspond to a measure domain in sections 1899B(c)(1) or
(d)(1) of the Act and are setting-agnostic: For example falls with
major injury and the incidence of pressure ulcers;
Are currently adopted for 1 or more of our PAC quality
reporting programs, are already either NQF-endorsed and in use or
finalized for use, or already previewed by the Measure Applications
Partnership (MAP) with support;
Minimize added burden on HHAs;
Minimize or avoid, to the extent feasible, revisions to
the existing items in assessment tools currently in use (for example,
the OASIS); and
Where possible, the avoidance duplication of existing
assessment items.
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. This
process is based on a private public partnership, and it occurs via the
MAP. The MAP is composed of multistakeholder groups convened by the
NQF, our current contractor under section 1890 of the Act, to provide
input on the selection of quality and efficiency measures described in
section 1890(b)(7)(B). The NQF must convene these stakeholders and
provide us with the stakeholders' input on the selection of such
measures. We, in turn, must take this input into consideration in
selecting such measures. In addition, the Secretary must make available
to the public by December 1 of each year a list of such measures that
the Secretary is considering under Title XVIII of the Act. As discussed
in section V.A. of this proposed rule 1899B(e)(3) provides that the
pre-rulemaking process required by section 1890A of the Act applies to
the measures required under section 1899B, subject to certain
exceptions for expedited procedures or, alternatively, waiver of
section 1890A. We initiated an ad hoc MAP process for the review of the
quality measures under consideration for proposal, in preparation for
adoption of those quality measures into the HH QRP that are required by
the IMPACT Act, and that must be implemented by January 1, 2017. The
List of Measures under Consideration (MUC List) under the IMPACT Act
was made public on February 5, 2015. Under the IMPACT Act, these
measures must be standardized so they can be applied across PAC
settings and must correspond to measure domains specified in sections
1899B(c)(1) and (d)(1) of the IMPACT Act. The MAP reviewed each IMPACT
Act-related quality measure proposed in this proposed rule for the HH
QRP, in light of its intended cross-setting use. We refer to sections
V.A. and V.C. of this proposed rule for more information on the MAP's
recommendations. The MAP's final report, MAP Off-Cycle Deliberations
2015: Measures under Consideration to Implement Provisions of the
IMPACT Act: Final Report, is available at https://www.qualityforum.org/
Setting_Priorities/Partnership/MAP_Final_Reports.aspx. As discussed in
section V.A. of this proposed rule, section 1899B(j) of the Act,
requires that we allow for stakeholder input, such as through town
halls, open door forums, and mailbox submissions, before the initial
rulemaking process to implement section 1899B. To meet this
requirement, we provided the following opportunities for stakeholder
input: (a) We convened a technical expert panel (TEP) that included
stakeholder experts and patient representatives on February 3, 2015;
(b) we provided two separate listening sessions on February 10th and
March 24, 2015; (c) we sought public input during the February 2015 ad
hoc MAP process regarding the measures under consideration with respect
to IMPACT Act domains; (d) we sought public comment as part of our
measure maintenance work; and (e) we implemented a public mail box for
the submission of comments in January, 2015 located at
PACQualityInitiative@cms.hhs.gov. The CMS public mailbox can be
accessed on our post-acute care quality initiatives Web site: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014-and-Cross-Setting-Measures.html. Lastly, we held a National Stakeholder
Special Open Door Forum to seek input on the measures on February 25,
2015.
In the absence of NQF endorsement on measures for the home health
setting, or measures that are not fully supported by the MAP for the HH
QRP, we intend to propose for adoption measures that most closely align
with the national priorities discussed above and for which the MAP
supports the measure concept. Further discussion as to the importance
and high-priority status of these measures in the HH setting is
included under each quality measure proposal in this proposed rule. In
addition, for measures not endorsed by the NQF, we have sought, to the
extent practicable, to adopt measures that have been endorsed or
adopted by a national consensus organization, recommended by multi-
stakeholder organizations, and/or developed with the input of
providers, purchasers/payers, and other stakeholders.
C. HH QRP Quality Measures and Measures Under Consideration for Future
Years
In the CY 2014 HH PPS final rule, (78 FR 72256-72320), we finalized
a proposal to add two claims-based measures to the HH QRP, and stated
that we would begin reporting the data from these measures to HHAs
beginning in CY 2014. These claims based measures are: (1)
Rehospitalization during the first 30 days of HH; and (2) Emergency
Department Use without Hospital Readmission during the first 30 days of
HH. In an effort to align with other updates to Home Health Compare,
including the transition to quarterly provider preview reports, we have
made the decision to delay the reporting of data from these measures
until July 2015 (https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HomeHealthQualityInits/HHQISpotlight.html). Also in that rule, we finalized our proposal to
reduce the number of process measures reported on the Certification and
Survey Provider Enhanced Reporting (CASPER) reports by eliminating the
stratification by
[[Page 39897]]
episode length for nine (9) process measures. The removal of these
measures from the CASPER folders occurred in October 2014. The CMS Home
Health Quality Initiative Web site identifies the current HH QRP
measures located at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HomeHealthQualityInits/HHQIQualityMeasures.html. In addition, as stated in the CY 2012 and CY
2013 HH PPS final rules (76 FR 68575 and 77 FR 67093, respectively), we
finalized that we will also use measures derived from Medicare claims
data to measure home health quality. This effort ensures that providers
do not have an additional burden of reporting quality of care measures
through a separate mechanism, and that the costs associated with the
development and testing of a new reporting mechanism are avoided.
(a) We are proposing one standardized cross-setting new measure for
CY 2016 to meet the requirements of the IMPACT Act. The proposed
quality measure that addresses the domain of skin integrity and changes
in skin integrity is the National Quality Forum (NQF)-endorsed measure:
Percent of Residents or Patients with Pressure Ulcers That Are New or
Worsened (Short Stay) (NQF #0678) (https://www.qualityforum.org/QPS/0678).
The IMPACT Act requires the specification of a quality measure to
address skin integrity and changes in skin integrity in the home health
setting by January 1, 2017. We are proposing the implementation of the
quality measure NQF #0678, Percent of Residents or Patients with
Pressure Ulcers that are New or Worsened (Short Stay) in the HH QRP as
a cross-setting quality measure to meet the requirements of the IMPACT
Act for the CY 2018 payment determination and subsequent years. This
measure reports the percent of patients with Stage 2 through 4 pressure
ulcers that are new or worsened since the beginning of the episode of
care.
Pressure ulcers are high-volume in post-acute care settings and
high-cost adverse events. According to the 2014 Prevention and
Treatment Guidelines published by the National Pressure Ulcer Advisory
Panel, European Pressure Ulcer Advisory Panel, and Pan Pacific Pressure
Injury Alliance, pressure ulcer care is estimated to cost approximately
$11 billion annually, and between $500 and $70,000 per individual
pressure ulcer.\64\ Pressure ulcers are a serious medical condition
that result in pain, decreased quality of life, and increased mortality
in aging populations.65 66 67 68 Pressure ulcers typically
are the result of prolonged periods of uninterrupted pressure on the
skin, soft tissue, muscle, and bone.69 70 71 Elderly
individuals are prone to a wide range of medical conditions that
increase their risk of developing pressure ulcers. These include
impaired mobility or sensation, malnutrition or undernutrition,
obesity, stroke, diabetes, dementia, cognitive impairments, circulatory
diseases, dehydration, bowel or bladder incontinence, the use of
wheelchairs, the use of medical devices, polypharmacy, and a history of
pressure ulcers or a pressure ulcer at
admission.72 73 74 75 76 77 78 79 80 81 82
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\64\ National Pressure Ulcer Advisory Panel, European Pressure
Ulcer Advisory Panel and Pan Pacific Pressure Injury Alliance.
Prevention and Treatment of Pressure Ulcers: Clinical Practice
Guideline. Emily Haesler (Ed.) Cambridge Media; Osborne Park,
Western Australia; 2014.
\65\ Casey, G. (2013). ``Pressure ulcers reflect quality of
nursing care.'' Nurs N Z 19(10): 20-24.
\66\ Gorzoni, M. L., and S. L. Pires (2011). ``Deaths in nursing
homes.'' Rev Assoc Med Bras 57(3): 327-331.
\67\ Thomas, J. M., et al. (2013). ``Systematic review: health-
related characteristics of elderly hospitalized adults and nursing
home residents associated with short-term mortality.'' J Am Geriatr
Soc 61(6): 902-911.
\68\ White-Chu, E. F., et al. (2011). ``Pressure ulcers in long-
term care.'' Clin Geriatr Med 27(2): 241-258.
\69\ Bates-Jensen BM. Quality indicators for prevention and
management of pressure ulcers in vulnerable elders. Ann Int Med.
2001;135 (8 Part 2), 744-51.
\70\ Institute for Healthcare Improvement (IHI). Relieve the
pressure and reduce harm. May 21, 2007. Available from https://www.ihi.org/IHI/Topics/PatientSafety/SafetyGeneral/ImprovementStories/FSRelievethePressureandReduceHarm.htm.
\71\ Russo CA, Steiner C, Spector W. Hospitalizations related to
pressure ulcers among adults 18 years and older, 2006 (Healthcare
Cost and Utilization Project Statistical Brief No. 64). December
2008. Available from https://www.hcupus.ahrq.gov/reports/statbriefs/sb64.pdf.
\72\ Agency for Healthcare Research and Quality (AHRQ). Agency
news and notes: pressure ulcers are increasing among hospital
patients. January 2009. Available from https://www.ahrq.gov/research/jan09/0109RA22.htm.=.
\73\ Bates-Jensen BM. Quality indicators for prevention and
management of pressure ulcers in vulnerable elders. Ann Int Med.
2001;135 (8 Part 2), 744-51.
\74\ Cai, S., et al. (2013). ``Obesity and pressure ulcers among
nursing home residents.'' Med Care 51(6): 478-486.
\75\ Casey, G. (2013). ``Pressure ulcers reflect quality of
nursing care.'' Nurs N Z 19(10): 20-24.
\76\ Hurd D, Moore T, Radley D, Williams C. Pressure ulcer
prevalence and incidence across post-acute care settings. Home
Health Quality Measures & Data Analysis Project, Report of Findings,
prepared for CMS/OCSQ, Baltimore, MD, under Contract No. 500-2005-
000181 TO 0002. 2010.
\77\ MacLean DS. Preventing & managing pressure sores. Caring
for the Ages. March 2003;4(3):34-7. Available from https://www.amda.com/publications/caring/march2003/policies.cfm.
\78\ Michel, J. M., et al. (2012). ``As of 2012, what are the
key predictive risk factors for pressure ulcers? Developing French
guidelines for clinical practice.'' Ann Phys Rehabil Med 55(7): 454-
465.
\79\ National Pressure Ulcer Advisory Panel (NPUAP) Board of
Directors; Cuddigan J, Berlowitz DR, Ayello EA (Eds). Pressure
ulcers in America: prevalence, incidence, and implications for the
future. An executive summary of the National Pressure Ulcer Advisory
Panel Monograph. Adv Skin Wound Care. 2001;14(4):208-15.
\80\ Park-Lee E, Caffrey C. Pressure ulcers among nursing home
residents: United States, 2004 (NCHS Data Brief No. 14).
Hyattsville, MD: National Center for Health Statistics, 2009.
Available from https://www.cdc.gov/nchs/data/databriefs/db14.htm.
\81\ Reddy, M. (2011). ``Pressure ulcers.'' Clin Evid (Online)
2011.
\82\ Teno, J. M., et al. (2012). ``Feeding tubes and the
prevention or healing of pressure ulcers.'' Arch Intern Med 172(9):
697-701.
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The IMPACT Act requires the specification of quality measures that
are harmonized across PAC settings. This requirement is consistent with
the NQF Steering Committee report, which stated that to understand the
impact of pressure ulcers across settings, quality measures addressing
prevention, incidence, and prevalence of pressure ulcers must be
harmonized and aligned.\83\ NQF #0678, Percent of Residents or Patients
with Pressure Ulcers That Are New or Worsened (Short Stay) is NQF-
endorsed and has been successfully implemented using a harmonized set
of data elements in IRF, LTCH, and SNF settings. A new item, M1309 was
added to the OASIS-C1/ICD-9 version to collect data on new and worsened
pressure ulcers in home health patients to support harmonization with
NQF #0678; data collection for this item began January 1, 2015. A new
measure, based on this item, was included in the 2014 MUC list and
received conditional endorsement from the National Quality Forum. That
measure was harmonized with NQF #0678, but differed in the
consideration of unstageable pressure ulcers. In this rule, we are
proposing a HH measure that is fully-standardized with NQF #0678.
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\83\ National Quality Forum. National voluntary consensus
standards for developing a framework for measuring quality for
prevention and management of pressure ulcers. April 2008. Available
from https://www.qualityforum.org/Projects/Pressure_Ulcers.aspx.
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A TEP convened by our measure development contractor provided input
on the technical specifications of this quality measure, including the
feasibility of implementing the measure across PAC settings. The TEP
was supportive of the implementation of this measure across PAC
settings and applauded CMS's efforts to standardize this measure for
cross-setting development. Additionally, the NQF MAP met on February 9,
2015 and
[[Page 39898]]
February 27, 2015 and provided input to CMS. The MAP supported the use
of NQF #0678, Percent of Residents or Patients with Pressure Ulcers
that are New or Worsened (Short Stay) in the HH QRP as a cross-setting
quality measure implemented under the IMPACT Act. More information
about the MAPs recommendations for this measure is available at https://www.qualityforum.org/map/.
We propose that data for the standardized quality measure would be
collected using the OASIS-C1 with submission through the Quality
Improvement and Evaluation System (QIES) Assessment Submission and
Processing (ASAP) system. HHAs began submitting data in January 2015
for the OASIS items used to calculate NQF #0678, the Percent of
Residents, or Patients with Pressure Ulcers That Are New or Worsened
(Short Stay), as part of the Home Health Quality Initiative to assess
the number of new or worsened pressure ulcers in January 2015. By
building on the existing reporting and submission infrastructure for
HHAs, we intend to minimize the administrative burden related to data
collection and submission for this measure under the HH QRP. For more
information on HH reporting using the QIES ASAP system, refer to:
https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HomeHealthQualityInits/HHQIOASISUserManual.html and https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/OASIS/?redirect=/oasis/.
Data collected through the OASIS-C1 would be used to calculate this
quality measure. Data items in the OASIS-C1 include M1308 (Current
Number of Unhealed Pressure Ulcers at Each Stage or Unstageable) and
M1309 (Worsening in Pressure Ulcer Status Since SOC/ROC). Data
collected through the OASIS-C1 would be used for risk adjustment of
this measure. We anticipate risk adjustment items would include, but is
not limited to M1850 (Activities of Daily Living Assistance,
Transferring), and M1620 (Bowel Incontinence Frequency). OASIS C1 items
M1016 (Diagnoses Requiring Medical or Treatment Change Within past 14
Days), M1020 (Primary Diagnoses) and M1022 (Other Diagnoses) would be
used to identify patients with a diagnosis of peripheral vascular
disease, diabetes, or malnutrition. More information about the OASIS
items is available in the OASIS Manual https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HomeHealthQualityInits/HHQIOASISUserManual.html.
The calculation of the proposed measure would be based on the items
M1308 (Current Number of Unhealed Pressure Ulcers at Each Stage or
Unstageable) and M1309 (Worsening in Pressure Ulcer Status Since SOC/
ROC). The specifications and data items for NQF #0678, the Percent of
Residents or Patients with Pressure Ulcers that are New or Worsened
(Short Stay), are available at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/PAC-Quality-Initiatives.html.
We invite public comment on our proposal to adopt NQF #0678 Percent
of Residents or Patients with Pressure Ulcers that are New or Worsened
(Short Stay) for the HH QRP to fulfill the timeline requirements for
implementation under the IMPACT Act, for CY2018 HH payment
determination and subsequent years.
As part of our ongoing measure development efforts, we are
considering a future update to the numerator of the quality measure NQF
#0678, Percent of Residents or Patients with Pressure Ulcers that are
New or Worsened (Short Stay). This update would hold providers
accountable for the development of unstageable pressure ulcers and
suspected deep tissue injuries (sDTIs). Under this proposed change the
numerator of the quality measure would be updated to include
unstageable pressure ulcers, including sDTIs that are new/developed
while the patient is receiving home health care, as well as Stage 1 or
2 pressure ulcers that become unstageable due to slough or eschar
(indicating progression to a full thickness [that is, stage 3 or 4]
pressure ulcer) after admission. This would be consistent with the
specifications of the ``New and Worsened Pressure Ulcer'' measure for
HH patients presented to the MAP on the 2014 MUC list. At this time, we
are not proposing the implementation of this change (that is, including
sDTIs and unstageable pressure ulcers in the numerator) in the HH QRP,
but are soliciting public feedback on this potential area of measure
development.
Our measure development contractor convened a cross-setting
pressure ulcer TEP that strongly recommended that CMS hold providers
accountable for the development of new unstageable pressure ulcers and
sDTIs by including these pressure ulcers in the numerator of the
quality measure. Although the TEP acknowledged that unstageable
pressure ulcers and sDTIs cannot and should not be assigned a numeric
stage, panel members recommended that these be included in the
numerator of NQF #0678, the Percent of Residents, or Patients with
Pressure Ulcers That Are New or Worsened (Short Stay), as a new
pressure ulcer if developed during a home health episode. The TEP also
recommended that a Stage 1 or 2 pressure ulcer that becomes unstageable
due to slough or eschar should be considered worsened because the
presence of slough or eschar indicates a full thickness (equivalent to
Stage 3 or 4) wound.84 85 These recommendations were
supported by technical and clinical advisors and the National Pressure
Ulcer Advisory Panel.\86\ Additionally, exploratory data analysis
conducted by our measure development contractor suggests that the
addition of unstageable pressure ulcers, including sDTIs, would
increase the observed incidence of new or worsened pressure ulcers at
the agency level and may improve the ability of the quality measure to
discriminate between poor- and high-performing facilities.
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\84\ Schwartz, M., Nguyen, K.H., Swinson Evans, T.M., Ignaczak,
M.K., Thaker, S., and Bernard, S.L.: Development of a Cross-Setting
Quality Measure for Pressure Ulcers: OY2 Information Gathering,
Final Report. Centers for Medicare & Medicaid Services, November
2013. Available: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/Downloads/Development-of-a-Cross-Setting-Quality-Measure-for-Pressure-Ulcers-Information-Gathering-Final-Report.pdf
\85\ Schwartz, M., Ignaczak, M.K., Swinson Evans, T.M., Thaker,
S., and Smith, L.: The Development of a Cross-Setting Pressure Ulcer
Quality Measure: Summary Report on November 15, 2013, Technical
Expert Panel Follow-Up Webinar. Centers for Medicare & Medicaid
Services, January 2014. Available: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/Downloads/Development-of-a-Cross-Setting-Pressure-Ulcer-Quality-Measure-Summary-Report-on-November-15-2013-Technical-Expert-Pa.pdf
\86\ Schwartz, M., Nguyen, K.H., Swinson Evans, T.M., Ignaczak,
M.K., Thaker, S., and Bernard, S.L.: Development of a Cross-Setting
Quality Measure for Pressure Ulcers: OY2 Information Gathering,
Final Report. Centers for Medicare & Medicaid Services, November
2013. Available: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/Downloads/Development-of-a-Cross-Setting-Quality-Measure-for-Pressure-Ulcers-Information-Gathering-Final-Report.pdf
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In addition, we are also considering whether body mass index (BMI)
should be used as a covariate for risk-adjusting NQF #0678 in the home
health setting, as is done in other post-acute care settings. We invite
public feedback to inform our direction to include unstageable pressure
ulcers and sDTIs in the numerator of the quality measure NQF #0678
Percent of Residents or Patients with Pressure Ulcers that are New or
Worsened (Short Stay), as well as on the possible collection of height
[[Page 39899]]
and weight data for risk-adjustment, as part of our future measure
development efforts.
(b) We have also identified four future, cross-setting measure
constructs to potentially meet requirements of the IMPACT Act domains
of: (1) All-condition risk-adjusted potentially preventable hospital
readmission rates; (2) resource use, including total estimated Medicare
spending per beneficiary; (3) discharge to community; and (4)
medication reconciliation. These are shown in Table 22; we would like
to solicit public feedback to inform future measure development of
these constructs as it relates to meeting the IMPACT Act requirements
in these areas.
Table 22--Future Cross-Setting Measure Constructs Under Consideration To Meet IMPACT Act Requirements
[Home Health Timeline for Implementation--January 1, 2017]
----------------------------------------------------------------------------------------------------------------
Measures to reflect all-condition risk-
IMPACT Act domain adjusted potentially preventable hospital
readmission rates
----------------------------------------------------------------------------------------------------------------
Measures......................................................... Application of (NQF #2510): Skilled Nursing
Facility 30-Day All-Cause Readmission
Measure (SNFRM) CMS is the steward.
Application of the LTCH/IRF All-Cause
Unplanned Readmission Measure for 30 Days
Post Discharge from LTCHs/IRFs.
IMPACT Act Domain................................................ Resource Use, including total estimated
Medicare spending per beneficiary.
Measure.......................................................... Payment Standardized Medicare Spending Per
Beneficiary (MSPB).
IMPACT Act Domain................................................ Discharge to community.
Measure.......................................................... Percentage residents/patients at discharge
assessment, who discharged to a higher level
of care versus to the community.
IMPACT Act Domain................................................ Medication Reconciliation.
Measure.......................................................... Percent of patients for whom any needed
medication review actions were completed.
----------------------------------------------------------------------------------------------------------------
(c) We are working with our measure development and maintenance
contractor to identify setting-specific measure concepts for future
implementation in the HH QRP that align with or complement current
measures and new measures to meet domains specified in the IMPACT Act.
In identifying priority areas for future measure enhancement and
development, we take into consideration results of environmental scans
and resulting gaps analysis for relevant home health quality measure
constructs, along with input from numerous stakeholders, including the
Measures Application Partnership (MAP), the Medicare Payment Advisory
Commission (MedPAC), Technical Expert Panels, and national priorities,
such as those established by the National Priorities Partnership, the
HHS Strategic Plan, the National Strategy for Quality Improvement in
Healthcare, and the CMS Quality Strategy. Based on input from
stakeholders, CMS has identified several high priority concept areas
for future measure development in Table 23.
Table 23--Future Setting-Specific Measure Constructs Under Consideration
------------------------------------------------------------------------
National quality strategy domain Measure construct
------------------------------------------------------------------------
Safety............................ Falls risk composite process
measure: Percentage of home health
patients who were assessed for
falls risk and whose care plan
reflects the assessment, and which
was implemented appropriately.
Effective Prevention and Treatment Nutrition assessment composite
measure: Percentage of home health
patients who were assessed for
nutrition risk with a validated
tool and whose care plan reflects
the assessment, and which was
implemented appropriately.
Improvement in Dyspnea in Patients
with a Primary Diagnosis of
Congestive Heart Failure (CHF),
Chronic Obstructive Pulmonary
Disease (COPD), and/or Asthma:
Percentage of home health episodes
of care during which a patient with
a primary diagnosis of CHF, asthma
and/or COPD became less short of
breath or dyspneic.
Improvement in Patient-Reported
Interference due to Pain: Percent
of home health patients whose self-
reported level of pain interference
on the Patient-Reported Objective
Measurement Information System
(PROMIS) tool improved.
Improvement in Patient-Reported Pain
Intensity: Percent of home health
patients whose self-reported level
of pain severity on the PROMIS tool
improved.
Improvement in Patient-Reported
Fatigue: Percent of home health
patients whose self-reported level
of fatigue on the PROMIS tool
improved.
Stabilization in 3 or more
Activities of Daily Living (ADLs):
Percent of home health patients
whose functional scores remain the
same between admission and
discharge for at least 3 ADLs.
------------------------------------------------------------------------
These measure concepts are under development, and details regarding
measure definitions, data sources, data collection approaches, and
timeline for implementation would be communicated in future rulemaking.
We invite feedback about these seven high priority concept areas for
future measure development.
D. 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 39900]]
comprehensive assessment must 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 do not need to submit OASIS data for those patients who are
excluded from the OASIS submission requirements. As described in the
December 23, 2005 Medicare and Medicaid Programs: Reporting Outcome and
Assessment Information Set Data as Part of the Conditions of
Participation for Home Health Agencies final rule (70 FR 76202), we
defined the exclusion as those patients:
Receiving only non-skilled services;
For whom neither Medicare nor Medicaid is paying for HH
care (patient receiving care under a Medicare or Medicaid Managed Care
Plan are not excluded from the OASIS reporting requirement);
Receiving pre- or post-partum services; or
Under the age of 18 years.
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
do not affect the HHAs' reporting responsibilities as announced 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).
2. Home Health Quality Reporting Program Requirements for CY 2016
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 1st of the calendar year 2 years prior to
the calendar year of the Annual Payment Update (APU) effective date and
ending June 30th 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 data to the
Secretary in accordance with subclause (II) with respect to such a
year. This pay-for-reporting requirement was implemented on January 1,
2007. In the CY 2015 HH PPS Final rule (79 FR 38387), we finalized a
proposal to define the quantity of OASIS assessments each HHA must
submit to meet the pay-for-reporting requirement.
We believe that defining a more explicit performance requirement
for the submission of OASIS data by HHAs would better meet section
5201(c)(2) of the Deficit Reduction Act of 2005 (DRA), which requires
that each home health agency shall submit to the Secretary such data
that the Secretary determines are appropriate for the measurement of
health care quality. Such data shall be submitted in a form and manner,
and at a time, specified by the Secretary for purposes of this clause.
In the CY 2015 HH PPS Final rule (79 FR 38387), we reported
information on a study performed by the Department of Health & Human
Services, Office of the Inspector General (OIG) in February 2012 to:
(1) Determine the extent to which HHAs met federal reporting
requirements for the OASIS data; (2) to determine the extent to which
states met federal reporting requirements for OASIS data; and (3) to
determine the extent to which CMS was overseeing the accuracy and
completeness of OASIS data submitted by HHAs. Based on the OIG report
we proposed a performance requirement for submission of OASIS quality
data, which would be responsive to the recommendations of the OIG.
In response to these requirements and the OIG report, 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. However, it was determined that there are
several scenarios that could meet this matching assessment requirement
of the new pay-for-reporting performance requirement. These scenarios
or quality assessments are defined as assessments that create a quality
episode of care during the reporting period or could create a quality
episode if the reporting period were expanded to an earlier reporting
period or into the next reporting period.
Seven types of assessments submitted by an HHA fit this definition
of a quality assessment. These are:
1. A Start of Care (SOC; M0100 = `01') or Resumption of Care (ROC;
M0100 = `03') assessment that can be matched to an End of Care (EOC;
M0100 = `06', `07', `08', or `09') assessment. These SOC/ROC
assessments are the first assessment in the pair of assessments that
create a standard quality of care episode describe in the previous
paragraph.
2. An End of Care (EOC) assessment that can be matched to a Start
of Care (SOC) or Resumption of Care (ROC) assessment. These EOC
assessments are the second assessment in the pair of assessments that
create a standard quality of care episode describe in the previous
paragraph.
3. A SOC/ROC assessment that could begin an episode of care, but
the assessment occurs in the last 60 days of the performance period.
This is labeled as a Late SOC/ROC quality assessment. The assumption is
that the EOC assessment will occur in the next reporting period.
4. An EOC assessment that could end an episode of care that began
in the previous reporting period, (that is, an EOC that occurs in the
first 60 days of the performance period). This is labeled as an Early
EOC quality assessment. The
[[Page 39901]]
assumption is that the matching SOC/ROC assessment occurred in the
previous reporting period.
5. A SOC/ROC assessment that is followed by one or more follow-up
assessments, the last of which occurs in the last 60 days of the
performance period. This is labeled as an SOC/ROC Pseudo Episode
quality assessment.
6. An EOC assessment is preceded by one or more follow-up
assessments, the first of which occurs in the first 60 days of the
performance period. This is labeled an EOC Pseudo Episode quality
assessment.
7. A SOC/ROC assessment that is part of a known one-visit episode.
This is labeled as a One-Visit episode quality assessment. This
determination is made by consulting HH claims data.
SOC, ROC, and EOC assessments that do not meet any of these
definitions are labeled as Non-Quality assessments. Follow-up
assessments (that is, where the M0100 Reason for Assessment = `04' or
`05') are considered Neutral assessments and do not count toward or
against the pay-for-reporting performance requirement.
Compliance with this performance requirement can be measured
through the use of an uncomplicated mathematical formula. This pay-for-
reporting performance requirement metric has been titled as the
``Quality Assessments Only'' (QAO) formula because only those OASIS
assessments that contribute, or could contribute, to creating a quality
episode of care are included in the computation.
The formula based on this definition is as follows:
[GRAPHIC] [TIFF OMITTED] TP10JY15.008
Our ultimate goal is to require all HHAs to achieve a pay-for-
reporting performance requirement compliance rate of 90 percent or
more, as calculated using the QAO metric illustrated above. In the CY
2015 HH PPS final rule (79 FR 66074), we proposed implementing a pay-
for-reporting performance requirement over a three-year period. After
consideration of the public comments received, we adopted as final our
proposal to establish a pay-for-reporting performance requirement for
assessments submitted on or after July 1, 2015 and before June 30, 2016
with appropriate start of care dates, HHAs must score at least 70
percent on the QAO metric of pay-for-reporting performance requirement
or be subject to a 2 percentage point reduction to their market basket
update for CY 2017.
HHAs have been statutorily required to report OASIS for a number of
years and therefore should have many years of experience with the
collection of OASIS data and transmission of this data to CMS. Given
the length of time that HHAs have been mandated to report OASIS data
and based on preliminary analyses that indicate that the majority of
HHAs are already achieving the target goal of 90 percent on the QAO
metric, we believe that HHAs would adapt quickly to the implementation
of the pay-for-reporting performance requirement, if phased in over a
three-year period.
In the CY2015 rule, we did not finalize a proposal to increase the
reporting requirement in 10 percent increments over a two-year period
until the maximum rate of 90 percent is reached, but instead proposed
to analyze historical data to set the reporting requirements. To set
the threshold for the 2nd year, we analyzed the most recently available
data, from 2013 and 2014, to make a determination about what the pay-
for-reporting performance requirement should be. Specifically, we
reviewed OASIS data from this time period simulating the pay-for-
reporting performance 70 percent submission requirement to determine
the hypothetical performance of each HHA as if the pay-for-reporting
performance requirement were in effect during the reporting period
preceding its implementation. This analysis indicated a nominal
increase of 10 percent each year would provide the greatest opportunity
for successful implementation versus an increase of 20 percent from
year 1 to year 2.
Based on this analysis, we propose to set the performance threshold
at 80 percent for the reporting period from July 1, 2016 through June
30, 2017. For the reporting period from July 1, 2017 through June 30,
2018 and thereafter, we propose the performance threshold would be 90
percent.
We provided a report to each HHA of their hypothetical performance
under the pay-for-reporting performance requirement during the 2014-
2015 pre-implementation reporting period in June 2015. On January 1,
2015, the data submission process for OASIS converted from the current
state-based OASIS submission system to a new national OASIS submission
system known as the Assessment Submission and Processing (ASAP) System.
On July 1, 2015, when the pay-for-reporting performance requirement of
70 percent goes into effect, providers would be required to submit
their OASIS assessment data into the ASAP system. Successful submission
of an OASIS assessment would consist of the submission of the data into
the ASAP system with a receipt of no fatal error messages. Error
messages received during submission can be an indication of a problem
that occurred during the submission process and could also be an
indication that the OASIS assessment was rejected. Successful
submission can be verified by ascertaining that the submitted
assessment data resides in the national database after the assessment
has met all of the quality standards for completeness and accuracy
during the submission process. Should one or more OASIS assessments
submitted by a HHA be rejected due to an IT/servers issue caused by
CMS, we may, at our discretion, excuse the non-submission of OASIS
data. We anticipate that such a scenario would rarely, if ever, occur.
In the event that a HHA believes, they were unable to submit OASIS
assessments due to an IT/server issue on the part of CMS, the HHA
should be prepared to provide any documentation or proof available,
which demonstrates that no fault on their part contributed to the
failure of the OASIS records to transmit to CMS.
The initial performance period for the pay-for-reporting
performance requirement would be July 1, 2015 through June 30, 2016.
Prior to and during this performance period, we have scheduled Open
Door Forums and webinars to educate HHA personnel as needed about the
pay-for-reporting performance requirement program and the pay-for-
reporting performance QAO metric, and distributed individual provider
preview reports. Additionally, OASIS Education Coordinators (OECs)
would be trained to provide state-level instruction on this program and
metric. We have already posted a report, which provides a detailed
explanation of the methodology for this pay-for-reporting QAO
methodology. To view this report, go to: https://www.cms.gov/Medicare/
Quality-Initiatives-Patient-Assessment-
[[Page 39902]]
Instruments/HomeHealthQualityInits/Home-Health-Quality-Reporting-
Requirements.html. Training announcements and additional educational
information related to the pay-for-reporting performance requirement
would be provided on the HH Quality Initiatives Web page. We invite
public comment on our proposal to implement an 80 percent Pay-for-
Reporting Performance Requirement for Submission of OASIS Quality Data
for Year 2 reporting period July 1, 2016 to June 30, 2017 as described
previously, for the HH QRP.
E. Home Health Care CAHPS Survey (HHCAHPS)
In the CY 2015 HH PPS final rule (79 FR 66031), we stated that the
home health quality measures reporting requirements for Medicare-
certified agencies include the Home Health Care CAHPS[supreg] (HHCAHPS)
Survey for the CY 2015 Annual Payment Update (APU). We maintained the
stated HHCAHPS data requirements for CY 2015 set out in previous 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 originally endorsed
by the NQF in March 2009 (NQF Number 0517) and recently NQF re-endorsed
in 2015. 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 HHCAHPS Survey is approved under OMB Control Number
0938-1066 through May 31, 2017. 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 the HHCAHPS 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.
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. HHCAHPS data was first publicly reported in April 2012 on
Home Health Compare. 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. If you need
additional language translations of the HHCAHPS Survey, please contact
us at HHCAHPS@rti.org.
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. We update the HHCAHPS Protocols and
Guidelines Manual annually, and the current version is 7.0. 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
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 all their survey-eligible home
health care 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. Update training is required annually for all
approved HHCAHPS survey vendors. We have approximately 30 approved
HHCAHPS survey vendors. The most current 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. As stated previously in the six prior final rules to
this proposed rule, all HHCAHPS approved survey vendors must develop a
Quality Assurance Plan (QAP) for survey administration in accordance
with the HHCAHPS Protocols and Guidelines Manual. An HHCAHPS survey
vendor's first QAP must be submitted within 6 weeks of the data
submission deadline date after the vendor's first quarterly data
submission. The QAP must be updated and submitted annually thereafter
and at any time that changes occur in staff or vendor capabilities or
systems. A model QAP is included in the HHCAHPS Protocols and
Guidelines Manual. The QAP must include the following:
Organizational Background and Staff Experience;
Work Plan;
Sampling Plan;
[[Page 39903]]
Survey Implementation Plan;
Data Security, Confidentiality and Privacy Plan; and
Questionnaire Attachments.
As part of the oversight activities, the HHCAHPS Survey
Coordination Team conducts on-site visits to all approved HHCAHPS
survey vendors. The purpose of the site visits is to allow the HHCAHPS
Coordination Team to observe the entire HHCAHPS Survey implementation
process, from the sampling stage through file preparation and
submission, as well as to assess data security and storage. The HHCAHPS
Survey Coordination Team reviews the HHCAHPS survey vendor's survey
systems, and assesses administration protocols based on the HHCAHPS
Protocols and Guidelines Manual posted at https://homehealthcahps.org.
The systems and program site visit review includes, but is not limited
to the following:
Survey management and data systems;
Printing and mailing materials and facilities;
Telephone call center facilities;
Data receipt, entry and storage facilities; and
Written documentation of survey processes.
After the site visits, HHCAHPS survey vendors are given a defined
time period in which to correct any identified issues and provide
follow-up documentation of corrections for review. HHCAHPS survey
vendors are subject to follow-up site visits on an as-needed basis.
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 2016 APU
In the CY 2015 HH PPS final rule (79 FR 66031), we stated that for
the CY 2016 APU, we would require continued monthly HHCAHPS data
collection and reporting for four quarters. The data collection period
for CY 2016, APU includes the second quarter 2014 through the first
quarter 2015 (the months of April 2014 through March 2015). Although
these dates are past, we wished to state them in this proposed rule so
that HHAs are again reminded of what months constituted the
requirements for the CY 2016 APU. HHAs are required to submit their
HHCAHPS data files to the HHCAHPS Data Center for the HHCAHPS data from
the first quarter of 2015 data by 11:59 p.m., EST on July 16, 2015.
This deadline is firm; no exceptions are permitted.
For the CY 2016 APU, we required that all HHAs that had fewer than
60 HHCAHPS-eligible unduplicated or unique patients in the period of
April 1, 2013 through March 31, 2014 are exempted from the HHCAHPS data
collection and submission requirements for the CY 2016 APU, upon
completion of the CY 2016 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, 2013, through March 31, 2014, were required to
submit their patient counts on the HHCAHPS Participation Exemption
Request form for the CY 2016 APU posted on https://homehealthcahps.org
by 11:59 p.m., EST on March 31, 2015. This deadline was 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 counts. HHAs receiving
Medicare certification on or after April 1, 2014 are exempt from the
HHCAHPS reporting requirement for the CY 2016 APU. These newly-
certified HHAs did not need to complete a HHCAHPS Participation
Exemption Request form for the CY 2016 APU.
4. HHCAHPS Requirements for the CY 2017 APU
For the CY 2017 APU, we require continued 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 would
be 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 will be firm; no exceptions will be permitted.
For the CY 2017 APU, we require that all HHAs that have fewer than
60 HHCAHPS-eligible unduplicated or unique patients in the period of
April 1, 2014 through March 31, 2015 are exempted 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 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 HHCAHPS Participation Exemption Request
form for the CY 2017 APU posted on https://homehealthcahps.org by 11:59
p.m., EST on 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 counts. 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 did not need to complete a HHCAHPS Participation
Exemption Request form for the CY 2017 APU.
5. HHCAHPS Requirements for the CY 2018 APU
For the CY 2018 APU, we require continued 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 would
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 will be firm; no exceptions will be permitted.
For the CY 2018 APU, we require that all HHAs that have fewer than
60 HHCAHPS-eligible unduplicated or unique patients in the period of
April 1, 2015 through March 31, 2016 are exempted 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 HHCAHPS Participation Exemption Request
form for the CY 2018 APU posted on https://homehealthcahps.org by 11:59
p.m., EST on March 31, 2017. This deadline is firm, as are all of the
quarterly data
[[Page 39904]]
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 counts. 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 did not need to complete a HHCAHPS Participation
Exemption Request form for the CY 2018 APU.
6. 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 would help HHAs ensure that their data are submitted in the proper
format for data processing to the HHCAHPS Data Center.
We will continue HHCAHPS oversight activities as finalized in the
CY 2014 rule. In the CY 2013 HH PPS final rule (77 FR 6704, 67164), we
codified the current guideline that all approved HHCAHPS survey vendors
must fully comply with all HHCAHPS oversight activities. We included
this survey requirement at Sec. 484.250(c)(3).
We propose to continue the OASIS and HHCAHPS reconsiderations and
appeals process that we have finalized and that we have used for prior
periods for the CY 2012, CY 2013, CY 2014, and CY 2015 APU
determinations. We have described the reconsiderations process
requirements in the CMS Technical Direction Letter that we sent to the
affected HHAs, on or in late September. HHAs have 30 days from their
receipt of the Technical Direction Letter informing them that they did
not meet the OASIS and HHCAHPS requirements for the CY period, to send
all documentation that supports their requests for reconsideration to
CMS. It is important that the affected HHAs send in comprehensive
information in their reconsideration letter/package because we would
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, the 2 percent reduction
in the APU would be upheld. If clear evidence of compliance is present,
the 2 percent reduction for the APU would be reversed. We notify
affected HHAs by December 31st annually for the APU period that begins
on January 1st. If we determine to uphold the 2 percent reduction, the
HHA may further appeal the 2 percent reduction via the Provider
Reimbursement Review Board (PRRB) appeals process. The PRRB contact
information is provided to the HHAs receiving letters in December about
the CMS reconsideration decisions.
Providers who wish to submit a reconsideration request should
continue to follow the reconsideration and appeals process as finalized
in the CY 2012, CY 2013, CY 2014, and CY 2015 Home Health Prospective
Payment System Rate Update Final Rules.
7. Summary
We are not proposing 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 in the 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 telephone toll-free (1-866-
354-0985) for more information about HHCAHPS.
F. Public Display of Home Health Quality Data for the HH QRP
Section 1895(b)(3)(B)(v)(III) of the Act and section 1899B(f) of
the IMPACT Act states the Secretary shall establish procedures for
making data submitted under subclause (II) available to the public.
Such procedures shall ensure that a home health agency has the
opportunity to review the data that is to be made public with respect
to the agency prior to such data being made public. 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 be meaningful and that comparing
performance across home health agencies requires that measures be
constructed from data collected in a standardized and uniform manner.
We also recognize the need to ensure that each home health agency has
the opportunity to review the data before publication. Medicare home
health regulations, as codified at Sec. 484.250(a), requires 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.
In addition, beginning April 1, 2015 HHAs began to receive Provider
Preview Reports (for all Process Measures and Outcome Measures) on a
quarterly, rather than annual, basis. The opportunity for providers to
review their data and to submit corrections prior to public reporting
aligns with the other quality reporting programs and the requirement
for provider review under the IMPACT Act. We provide quality measure
data to HHAs via the Certification and Survey Provider Enhanced Reports
(CASPER reports), which are available through the CMS Health Care
Quality Improvement and Evaluation System (QIES).
As part of our ongoing efforts to make healthcare more transparent,
affordable, and accountable, the HH QRP has developed a CMS Compare Web
site for home health agencies, which identifies home health providers
based on the areas they serve. Consumers can search for all Medicare-
certified home health providers that serve their city or ZIP code and
then find the agencies offering the types of services they need. A
subset of the HH quality measures has been publicly reported on the
Home Health Compare (HH Compare) Web site since 2003. The selected
measures that are made available to the public can be viewed on the HH
Compare Web site located at https://www.medicare.gov/HHCompare/Home.asp.
The Affordable Care Act calls for transparent, easily understood
information on provider quality to be publicly reported and made widely
available. To provide home health care consumers with a summary of
existing quality measures in an accessible format, we plan to publish a
star rating based on the quality of care measures for home health
agencies on Home Health Compare starting in July 2015. This is part of
our plan to adopt star ratings across all Medicare.gov Compare Web
sites. Star ratings are currently publicly displayed on Nursing Home
Compare, Physician Compare, the Medicare Advantage Plan Finder, and
Dialysis Facility Compare, and they are scheduled to be displayed on
Hospital Compare in 2015.
The Quality of Patient Care star rating methodology assigns each
home health agency a rating between one (1) and five (5) stars, using
half stars for adjustment and reporting. All Medicare-certified home
health agencies are eligible to receive a Quality of Patient Care star
rating providing that they have quality data reported on at least 5 out
of the 9 quality measures that are included in the calculation.
Home health agencies would continue to have prepublication access
to their agency's quality data, which enables each agency to know how
it is
[[Page 39905]]
performing before public posting of the data on the Compare Web site.
Starting in April 2015, HHAs are receiving quarterly preview reports
showing their Quality of Patient Care star rating and how it was
derived well before public posting, and they have several weeks to
review and provide feedback.
The Quality of Patient Care star ratings methodology was developed
through a transparent process the included multiple opportunities for
stakeholder input, which was subsequently the basis for refinements to
the methodology. An initial proposed methodology for calculating the
Quality of Patient Care star ratings was posted on the CMS.gov Web site
in December 2014. CMS then held two Special Open Door Forums (SODFs) on
December 17, 2014 and February 5, 2015 to present the proposed
methodology and solicit input. At each SODF, stakeholders provided
immediate input, and were invited to submit additional comments via the
Quality of Patient Care star ratings Help Desk mailbox:
HHC_Star_Ratings_Helpdesk@cms.hhs.gov. CMS refined the methodology,
based on comments received and additional analysis. The final
methodology report is posted on the new star ratings Web page: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HomeHealthQualityInits/HHQIHomeHealthStarRatings.html. A
Frequently-Asked-Questions (FAQ) document is also posted on the same
Web page, addressing the issues raised in the comments that were
received. We tested the Web site language used to present the Quality
of Patient Care star ratings with Medicare beneficiaries to assure that
it allowed them to accurately understand the significance of the
various star ratings.
Additional information regarding the Quality of Patient Care star
rating would be posted on the star ratings Web page at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HomeHealthQualityInits/HHQIHomeHealthStarRatings.html.
Additional communications regarding the Quality of Patient Care star
ratings would be announced via regular HH QRP communication channels.
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 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 proposed HHVBP model would apply a payment adjustment based on
[[Page 39906]]
an HHA's performance on quality measures to test the effects on quality
and costs of care. This proposed HHVBP model was developed based on the
experiences we gained from the implementation of the Home Health Pay-
for-Performance (HHPP) demonstration as well as the successful
implementation of the HVBP program. The model design was also developed
from the public comments received on the discussion of a HHVBP model
being considered in the CY 2015 HH PPS proposed and final rules. Value-
based purchasing programs have also been included in the President's
budget for most providers types, including Home Health.
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). 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 proposed changes
in payments under the HH PPS for CY 2016 are estimated to be -$350
million. The savings impacts related to the proposed HHVBP model are
estimated at a total projected 5-year gross savings of $380 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. In accordance with the provisions of Executive Order 12866,
this regulation was reviewed by the Office of Management and Budget.
1. HH PPS
The update set forth in this rule applies to Medicare payments
under HH PPS in CY 2016. Accordingly, the following analysis describes
the impact in CY 2016 only. We estimate that the net impact of the
proposals in this rule is approximately $350 million in decreased
payments to HHAs in CY 2016. 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 2016 wage index proposed in section III.C.3 of
this proposed rule and the recalibration of the case-mix weights for
2016 proposed in section III.B. of this proposed rule is zero. The -
$350 million impact reflects the distributional effects of the 2.3
percent HH payment update percentage ($420 million increase), the
effects of the third 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 -2.5 percent ($470 million decrease), and the
effects of the -1.72 percent adjustment for nominal case-mix growth
($300 million decrease). The $350 million in decreased payments is
reflected in the last column of the first row in Table 24 as a 0.1
percent decrease in expenditures when comparing CY 2015 payments to
estimated CY 2016 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 conclude that the policies proposed in this rule will
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 will have a
significant economic impact on a substantial number of small entities.
Further detail is presented in Table 24, 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 2016. For the proposed reduction
to the national, standardized 60-day episode payment amount of 1.72
percent for CY 2016 described in section III.B.2 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 below, we note that we considered proposing the full 3.41
percent reduction to the 60-day episode rate in CY 2016 to account for
nominal case-mix growth between CY 2012 and CY 2014. However, we
instead proposed to reduce the 60-day episode rate by 1.72 percent in
CY 2016 and 1.72 percent in CY 2017 to account for estimated nominal
case-mix growth between CY 2012 and CY 2014.
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
[[Page 39907]]
beyond CY 2016. 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.
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 applies to HHAs. Therefore, the
Secretary has determined that the HH PPS proposed rule will not have a
significant economic impact on the operations of small rural hospitals.
2. Proposed HHVBP Model
To test the impact of upside and downside value-based payment
adjustments, beginning in calendar year 2018 and in each succeeding
calendar year through calendar year 2022, the proposed model would
adjust the final claim payment amount for a home health agency for each
episode in a calendar year by an amount equal to the applicable
percent. For purposes of this proposed rule, we have limited our
analysis of the economic impacts to the value-based incentive payment
adjustments. Under the proposed model design, the incentive payment
adjustments would be limited to the total payment reductions to home
health agencies included in the model and would be no less than the
total amount available for value-based incentive payment adjustment.
Overall, the distributive impact of this proposed rule is estimated at
$380 million for CY 2018-2022. Therefore, this proposed rule is
economically significant and thus a major rule under the Congressional
Review Act. The proposed model would test the effect on quality and
costs of care by applying payment adjustments based on HHAs'
performance on quality measures. This proposed rule was developed based
on extensive research and experience with value-based purchasing
models.
Guidance issued by the Department of Health and Human Services
interpreting the Regulatory Flexibility Act considers the 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. Among the over 1900 HHAs in the selected states that would be
expected to be included in the proposed HHVBP model, we estimate that
the maximum percent payment adjustment resulting from this proposed
rule will only be greater than -5 percent for 10 percent of the HHAs
included in the model (using the 8 percent maximum payment adjustment
threshold applied in CY2021 and CY2022). As a result, only 2 percent of
all HHA providers nationally would be significantly impacted, falling
well below the RFA threshold. In addition, only HHAs that are impacted
with lower payments are those providers that provide the poorest
quality which is the main tenet of the model. This falls well below the
threshold for economic significance established by HHS for requiring a
more detailed impact assessment under the RFA. Thus, we are not
preparing an analysis under the RFA because the Secretary has
determined that this proposed rule would not have a significant
economic impact on a substantial number of small entities.
In addition, section 1102(b) of the Act requires us to prepare a
regulatory impact analysis if a rule may have a significant impact on
the operations of a substantial number of small rural HHAs. This
analysis must conform to the provisions of section 603 of the RFA. For
purposes of section 1102(b) of the Act, we have identified less than 5
percent of HHAs included in the proposed selected states that primarily
serve beneficiaries that reside in rural areas (greater than 50 percent
of beneficiaries served). We are not preparing an analysis under
section 1102(b) of the Act because the Secretary has determined that
the proposed HHVBP model would not have a significant impact on the
operations of a substantial number of small rural HHAs.
Section 202 of the Unfunded Mandates Reform Act of 1995 also
requires that agencies assess anticipated costs and benefits before
issuing any rule whose mandates require spending in any 1 year of $100
million in 1995 dollars, updated annually for inflation. In 2015, that
threshold is approximately $144 million. This rule will have no
consequential effect on state, local, or tribal governments or on the
private sector.
Executive Order 13132 establishes certain requirements that an
agency must meet when it promulgates a proposed rule (and subsequent
final rule) that imposes substantial direct requirement costs on State
and local governments, preempts state law, or otherwise has Federalism
implications. Since this regulation does not impose any costs on state
or local governments, the requirements of Executive Order 13132 are not
applicable.
In accordance with the provisions of Executive Order 12866, this
regulation was reviewed by the Office of Management and Budget.
C. Detailed Economic Analysis
1. HH PPS
This proposed rule sets forth updates for CY 2016 to the HH PPS
rates contained in the CY 2015 HH PPS final rule (79 FR 66032 through
66118). 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 preliminary Medicare claims data from 2014. 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 24 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 2014 HH claims data (as of December 31,
2014) for dates of service that ended on or before December 31, 2014,
and OASIS assessments. The first column of Table 24 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 proposed CY 2016 wage index. The fourth
column shows the payment
[[Page 39908]]
effects of the proposed CY 2016 case-mix weights. The fifth column
shows the effects the proposed reduction of 1.72 percent 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 2016, the average impact for all HHAs due to the effects
of rebasing is an estimated 2.5 percent decrease in payments. The
seventh column shows the effects of the CY 2016 home health payment
update percentage (the home health market basket update adjusted for
multifactor productivity as discussed in section III.C.1. of this
proposed rule).
The last column shows the combined effects of all the proposed
policies for HH PPS. Overall, it is projected that aggregate payments
in CY 2016 will decrease by 1.8 percent. As illustrated in Table 24,
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 group may experience different impacts on payments than others due
to the distributional impact of the CY 2016 wage index, the extent to
which HHAs had episodes in case-mix groups where the case-mix weight
decreased for CY 2016 relative to CY 2015, 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 24--Estimated Home Health Agency Impacts by Facility Type and Area of the Country, CY 2016
--------------------------------------------------------------------------------------------------------------------------------------------------------
60-day
CY 2016 wage CY 2016 case- episode rate HH payment
Number of index \1\ mix weights nominal case- Rebasing \3\ update Total
agencies (percent) \2\ (percent) mix reduction (percent) percentage \4\ (percent)
(percent) (percent)
--------------------------------------------------------------------------------------------------------------------------------------------------------
All Agencies............................... 11,432 0.0 0.0 -1.6 -2.5 2.3 -1.8
--------------------------------------------------------------------------------------------------------------------------------------------------------
Facility Type and Control
--------------------------------------------------------------------------------------------------------------------------------------------------------
Free-Standing/Other Vol/NP................. 1,054 0.2 -0.2 -1.6 -2.5 2.3 -1.8
Free-Standing/Other Proprietary............ 8,917 0.0 0.0 -1.6 -2.5 2.3 -1.8
Free-Standing/Other Government............. 379 -0.2 -0.1 -1.6 -2.5 2.3 -2.1
Facility-Based Vol/NP...................... 741 0.1 -0.2 -1.6 -2.5 2.3 -1.9
Facility-Based Proprietary................. 116 -0.3 -0.1 -1.6 -2.5 2.3 -2.2
Facility-Based Government.................. 225 -0.2 -0.2 -1.6 -2.5 2.3 -2.2
Subtotal: Freestanding..................... 10,350 0.0 0.0 -1.6 -2.5 2.3 -1.8
Subtotal: Facility-based................... 1,082 0.0 -0.2 -1.6 -2.5 2.3 -2.0
Subtotal: Vol/NP........................... 1,795 0.1 -0.2 -1.6 -2.5 2.3 -1.9
Subtotal: Proprietary...................... 9,033 0.0 0.0 -1.6 -2.5 2.3 -1.8
Subtotal: Government....................... 604 -0.2 -0.1 -1.6 -2.5 2.3 -2.1
--------------------------------------------------------------------------------------------------------------------------------------------------------
Facility Type and Control: Rural
--------------------------------------------------------------------------------------------------------------------------------------------------------
Free-Standing/Other Vol/NP................. 188 -0.8 -0.2 -1.6 -2.4 2.3 -2.7
Free-Standing/Other Proprietary............ 143 -0.2 -0.1 -1.6 -2.5 2.3 -2.1
Free-Standing/Other Government............. 448 -0.5 -0.1 -1.6 -2.5 2.3 -2.4
Facility-Based Vol/NP...................... 231 -0.6 -0.2 -1.6 -2.5 2.3 -2.6
Facility-Based Proprietary................. 25 0.0 -0.2 -1.6 -2.5 2.3 -2.0
Facility-Based Government.................. 136 -0.4 -0.1 -1.6 -2.5 2.3 -2.3
--------------------------------------------------------------------------------------------------------------------------------------------------------
Facility Type and Control: Urban
--------------------------------------------------------------------------------------------------------------------------------------------------------
Free-Standing/Other Vol/NP................. 912 0.2 -0.2 -1.6 -2.5 2.3 -1.8
Free-Standing/Other Proprietary............ 8,604 0.0 0.0 -1.6 -2.5 2.3 -1.8
Free-Standing/Other Government............. 152 -0.4 -0.1 -1.6 -2.5 2.3 -2.3
Facility-Based Vol/NP...................... 510 0.2 -0.2 -1.6 -2.5 2.3 -1.8
Facility-Based Proprietary................. 91 -0.3 -0.1 -1.6 -2.4 2.3 -2.1
Facility-Based Government.................. 89 -0.1 -0.2 -1.6 -2.5 2.3 -2.1
--------------------------------------------------------------------------------------------------------------------------------------------------------
Facility Location: Urban or Rural
--------------------------------------------------------------------------------------------------------------------------------------------------------
Rural...................................... 1,074 -0.5 -0.1 -1.6 -2.5 2.3 -2.4
Urban...................................... 10,358 0.1 0.0 -1.6 -2.5 2.3 -1.7
--------------------------------------------------------------------------------------------------------------------------------------------------------
[[Page 39909]]
Facility Location: Region of the Country
--------------------------------------------------------------------------------------------------------------------------------------------------------
Northeast.................................. 837 0.2 -0.1 -1.6 -2.4 2.3 2.3
Midwest.................................... 3,044 -0.1 0.0 -1.6 -2.5 2.3 -1.9
South...................................... 5,623 -0.1 0.0 -1.6 -2.5 2.3 -1.9
West....................................... 1,837 0.4 -0.1 -1.6 -2.5 2.3 -1.5
Other...................................... 91 0.4 0.1 -1.6 -2.5 2.3 -1.3
--------------------------------------------------------------------------------------------------------------------------------------------------------
Facility Location: Region of the Country (Census Region)
--------------------------------------------------------------------------------------------------------------------------------------------------------
New England................................ 296 0.2 -0.1 -1.6 -2.4 2.3 2.3
Mid Atlantic............................... 541 0.3 -0.1 -1.6 -2.5 2.3 -1.6
East North Central......................... 2,407 -0.1 0.0 -1.6 -2.6 2.3 -2.0
West North Central......................... 637 0.0 0.0 -1.6 -2.5 2.3 -1.8
South Atlantic............................. 1,826 0.2 0.1 -1.6 -2.5 2.3 -1.5
East South Central......................... 444 -0.4 0.0 -1.6 -2.6 2.3 -2.3
West South Central......................... 3,353 -0.2 -0.1 -1.6 -2.5 2.3 -2.1
Mountain................................... 602 0.2 0.0 -1.6 -2.5 2.3 -1.6
Pacific.................................... 1,235 0.5 -0.2 -1.6 -2.5 2.3 -1.5
--------------------------------------------------------------------------------------------------------------------------------------------------------
Facility Size (Number of 1st Episodes)
--------------------------------------------------------------------------------------------------------------------------------------------------------
< 100 episodes............................. 3,171 0.1 -0.1 -1.6 -2.5 2.3 2.3
100 to 249................................. 2,861 0.1 0.0 -1.6 -2.5 2.3 -1.7
250 to 499................................. 2,425 0.1 0.0 -1.6 -2.5 2.3 -1.7
500 to 999................................. 1,679 0.0 0.0 -1.6 -2.5 2.3 -1.8
1,000 or More.............................. 1,296 0.0 -0.1 -1.6 -2.5 2.3 -1.9
--------------------------------------------------------------------------------------------------------------------------------------------------------
Source: CY 2014 Medicare claims data for episodes ending on or before December 31, 2014 (as of December 31, 2014) for which we had a linked OASIS
assessment.
\1\ The impact of the proposed CY 2016 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 proposed CY 2016 home health case-mix weights reflects the recalibration of the case-mix weights as outlined in section III.B.1 of
this proposed rule offset by the case-mix weights budget neutrality factor described in section III.C.3 of this proposed rule.
\3\ The impact of rebasing includes the rebasing adjustments to the national, standardized 60-day episode payment rate (-2.74 percent after the CY 2016
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 2016 home health payment update percentage reflects the home health market basket update of 2.9 percent, reduced by a 0.6 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. Proposed HHVBP Model
Table 25 displays our analysis of the distribution of possible
payment adjustments at the 5 percent, 6 percent and 8 percent rates
that are being proposed in the model based on 2013-2014 data, providing
information on the estimated impact of this proposed rule. We note that
this impact analysis is based on the aggregate value of all 9 states
identified in section IV.C.2. of this proposed rule by applying the
proposed state selection methodology.
Table 26 displays our analysis of the distribution of possible
payment adjustments based on 2013-2014 data, 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 states (identified
in section IV.C.2. of this proposed rule) by applying the proposed
state selection methodology.
If our methodology is finalized as proposed, all Medicare-certified
HHAs that provide services in Massachusetts, Maryland, North Carolina,
Florida, Washington, Arizona, Iowa, Nebraska, and Tennessee will be
required to compete in this model. However, should the methodology we
propose in this rule change as a result of comments received during the
rulemaking process, it could result in different states being selected
for the model. In such an event, we would apply the final methodology
and announce the selected states in the final rule. The estimates
presented here may also change accordingly.
Value-based incentive payment adjustments for the estimated 1,900
plus HHAs in the proposed selected states that would compete in the
HHVBP model are stratified by the size as defined in section F. For
example, Arizona has 31 HHAs that do not provide services to enough
beneficiaries to be required to complete CAHPS
[[Page 39910]]
surveys and therefore are considered lower-volume under the proposed
model. Using 2013-2014 data and the highest payment adjustment of 5
percent (which we propose to be applied in CYs 2021 and 2022), based on
10 process and outcome measures currently available on home health
compare, the small HHAs in Arizona would have a mean payment adjustment
of positive 0.64 percent. Only 10 percent of home health agencies would
be subject to downward payment adjustments of more than -3.3 percent.
The next columns provide the distribution of scores by percentile;
we see that the value-based incentive percentage payments for home
health agencies in Arizona range from -3.3 percent at the 10th
percentile to +5.0 percent at the 90th percentile, while the value-
based incentive payment at the 50th percentile is 0.56 percent.
The smaller-volume HHA cohorts table identifies that some
consideration will have to be made for MD, WA and TN where there are
too few HHAs in the smaller-volume cohort and would be included in the
larger-volume cohort without being measured on HHCAHPS.
Table 27 provides the payment adjustment distribution based on
proportion of dual-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 TPS score and the payment methodology at the state and size
level were calculated so that each home health agency'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 1,931 HHAs in the nine selected states out of 1,991 HHAs
that were found in the HHA data sources which yielded the sufficient
measures to be included 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.
Table 25--Adjustment Distribution by Percentile level of Quality Total Performance Score at Different Model Payment Adjustment Rates
--------------------------------------------------------------------------------------------------------------------------------------------------------
Lowest quality providers Highest quality providers
--------------------------------------------------------------------------------------------------
Payment adjustment distribution Range Lowest Highest
10th 20th 30th 40th 50th 60th 70th 80th 10th
pctile* pctile* pctile* pctile* pctile* pctile* pctile* pctile* pctile*
--------------------------------------------------------------------------------------------------------------------------------------------------------
5% Payment Adjustment for Year 1 and Year 7.69 -2.98 -2.04 -1.23 -0.54 0.15 0.83 1.74 3.08 4.71
2 of Model...............................
6% Payment Adjustment for Year 3 of Model. 9.24 -3.60 -2.46 -1.50 -0.66 0.18 1.02 2.10 3.72 5.64
8% Payment Adjustment for Year 4 and Year 12.31 -4.77 -3.27 -1.97 -0.86 0.25 1.33 2.78 4.92 7.54
5 of Model...............................
--------------------------------------------------------------------------------------------------------------------------------------------------------
*pctile = percentile
Table 26--HHA Cohort Payment Adjustment Distributions by State
[Based on a 5 percent payment adjustment]
--------------------------------------------------------------------------------------------------------------------------------------------------------
Average
Number of payment
State HHAs adjustment 10% 20% 30% 40% 50% 60% 70% 80% 90%
(%)
--------------------------------------------------------------------------------------------------------------------------------------------------------
Smaller-Volume HHA Cohort by State
--------------------------------------------------------------------------------------------------------------------------------------------------------
AZ................................ 31 0.64 -3.33 -2.72 -2.17 -0.82 0.56 1.31 3.36 4.75 5.00
FL................................ 353 0.44 -3.01 -1.76 -1.00 -0.39 0.21 0.94 1.84 3.04 4.38
IA................................ 23 0.17 -3.14 -2.53 -2.01 -1.41 -0.97 0.31 2.74 3.25 5.00
MA................................ 29 0.39 -3.68 -1.75 -0.70 -0.10 0.39 0.79 1.33 2.46 4.68
MD................................ 2 -0.47 -2.71 -2.71 -2.71 -2.71 -0.47 1.78 1.78 1.78 1.78
NC................................ 9 0.72 -2.38 -1.84 -1.41 -1.23 -0.68 0.34 3.67 5.00 5.00
NE................................ 16 -0.51 -2.26 -1.80 -1.64 -1.43 -1.13 -0.44 0.40 0.42 1.46
TN................................ 2 2.48 -0.05 -0.05 -0.05 -0.05 2.48 5.00 5.00 5.00 5.00
WA................................ 1 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
---------------------------------------------------------------------------------------------------------------------
Larger-volume HHA Cohort by State
--------------------------------------------------------------------------------------------------------------------------------------------------------
AZ................................ 82 0.39 -3.31 -2.75 -2.19 -0.81 0.56 1.31 3.38 4.75 5.00
FL................................ 672 0.41 -3.00 -1.75 -1.60 -0.38 0.19 0.94 1.81 3.06 4.38
IA................................ 129 -0.31 -3.13 -2.31 -2.70 -1.13 -0.56 0.13 0.56 1.19 3.50
MA................................ 101 0.64 -2.88 -2.19 -1.50 -0.38 0.63 1.25 2.06 3.81 4.88
MD................................ 50 0.41 -2.75 -2.06 -2.30 -0.88 0.00 0.81 2.38 2.94 4.13
NC................................ 163 0.65 -2.75 -1.56 -1.30 -0.06 0.38 0.94 1.88 3.06 4.88
NE................................ 48 0.37 -2.63 -2.19 -1.40 -0.56 -0.19 0.50 1.31 2.31 5.00
[[Page 39911]]
TN................................ 134 0.39 -2.56 -1.81 -2.00 -0.63 -0.06 0.81 1.44 2.50 4.69
WA................................ 55 0.39 -2.75 -1.63 -2.00 -0.94 -0.19 0.69 1.94 3.31 4.06
--------------------------------------------------------------------------------------------------------------------------------------------------------
Table 27--Payment Adjustment Distributions by Characteristics
[based on a 5 percent payment adjustment]
--------------------------------------------------------------------------------------------------------------------------------------------------------
Number of
Percentage Dually-eligible HHAs 10% 20% 30% 40% 50% 60% 70% 80% 90%
--------------------------------------------------------------------------------------------------------------------------------------------------------
Low % Dually-eligible............................. 498 -3.21 -2.57 -1.86 -1.29 -0.60 0.12 0.78 2.13 3.97
Medium % Dually-eligible.......................... 995 -2.91 -2.10 -1.33 -0.63 0.01 0.67 1.39 2.47 4.12
High % Dually-eligible............................ 498 -2.46 -1.04 -0.24 0.59 1.29 2.34 3.38 4.53 5.00
Acuity (HCC):
Low Acuity.................................... 499 -2.83 -1.76 -0.94 -0.23 0.46 1.16 2.03 3.40 5.00
Middle acuity................................. 993 -3.05 -2.08 -1.24 -0.50 0.19 0.90 1.71 2.81 4.51
High Acuity................................... 499 -3.04 -2.04 -1.29 -0.51 0.26 1.06 2.00 3.16 4.91
% Rural Beneficiaries:
All non-rural................................. 800 -2.81 -1.51 -0.66 0.08 0.78 1.54 2.64 3.94 5.00
Up to 35% rural............................... 925 -3.12 -2.37 -1.71 -1.01 -0.42 0.32 1.18 2.24 3.97
over 35% rural................................ 250 -2.91 -2.01 -1.17 -0.62 -0.11 0.56 1.32 2.86 4.58
Organizational Type:
Church........................................ 62 -2.92 -2.04 -1.33 -0.46 0.12 0.64 1.30 2.58 4.22
Private Not-For-Profit........................ 194 -2.78 -1.74 -0.97 -0.42 0.27 0.85 1.77 2.89 4.55
Other......................................... 93 -2.62 -1.68 -0.95 -0.38 0.36 1.08 1.86 3.09 4.63
Private For-Profit............................ 1538 -3.09 -2.08 -1.27 -0.53 0.24 1.02 1.88 3.02 4.83
Federal....................................... 83 -2.44 -1.61 -0.67 0.01 0.53 1.13 1.80 3.09 4.58
State......................................... 5 -3.03 -1.11 -.37 -0.01 0.24 0.42 1.66 2.96 3.24
Local......................................... 61 -2.30 -1.28 -0.48 0.16 0.98 1.91 2.88 4.11 5.00
--------------------------------------------------------------------------------------------------------------------------------------------------------
D. Alternatives Considered
As described in section III.B.2 of this proposed rule, 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
estimate that the aggregate impact would be a net decrease of $650
million in payments to HHAs, resulting from a $470 million decrease (-
2.5 percent) due to the third year of the Affordable Care Act mandated
rebasing adjustments, a $420 million increase (2.3 percent) due to the
home health payment update percentage, and a $600 million decrease due
to reducing the national, standardized 60-day episode payment rate by
3.41 percent. However, instead of proposing 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 proposed to reduce the national, standardized 60-day episode
payment rate by 1.72 percent in CY 2016 and 1.72 percent in CY 2017 to
account for nominal case-mix growth from CY 2012 through CY 2014 as
outlined in section III.B.2 of this proposed rule.
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 -0.6 percentage point productivity adjustment to the
[[Page 39912]]
proposed CY 2016 home health market basket update (2.9 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).
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 27, 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 27 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 27--Accounting Statement: HH PPS Classification of Estimated
Transfers and Costs, From the CYs 2015 to 2016 *
------------------------------------------------------------------------
Category Transfers
------------------------------------------------------------------------
Annualized Monetized Transfers............ -$350 million.
From Whom to Whom?........................ Federal Government to HHAs.
------------------------------------------------------------------------
* The estimates reflect 2016 dollars.
Table 28 provides our best estimate of the decrease in Medicare
payments under the proposed HHVBP model.
Table 28--Accounting Statement: HHVBP Model Classification of Estimated
Transfers and Costs for CY 2018-2022
------------------------------------------------------------------------
Category Transfers
------------------------------------------------------------------------
Annualized Monetized Transfers............ -$380 million.
From Whom to Whom?........................ Federal Government to
Hospitals and SNFs.
------------------------------------------------------------------------
F. Conclusion
1. HH PPS
In conclusion, we estimate that the net impact of the HH PPS
proposals in this rule is a decrease in Medicare payments to HHAs of
$350 million for CY 2016. The $350 million decrease in estimated
payments to HHAs for CY 2016 reflects the distributional effects of the
2.3 percent CY 2016 HH payment update percentage ($420 million
increase), the proposed reduction to the national, standardized 60-day
episode payment rate in CY 2016 of 1.72 percent to account for nominal
case-mix growth ($300 million decrease), and the third year of the 4-
year phase-in of the rebasing adjustments required by section 3131(a)
of the Affordable Care Act of -2.5 percent ($470 million decrease).
This analysis, together with the remainder of this preamble, provides
an initial Regulatory Flexibility Analysis.
2. Proposed HHVBP Model
In conclusion, we estimate there will be no net impact of the
proposals in this rule in Medicare payments to HHAs for CY 2016.
However, the overall economic impact of the HHVBP model provision is an
estimated $380 million in total savings from a reduction in unnecessary
hospitalizations and SNF usage as a result of greater quality
improvements in the HH industry over the life of the proposed model.
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 424
Emergency medical services, Health facilities, Health professions,
Medicare, and Reporting and recordkeeping requirements.
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 proposes to amend 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 Social Security Act (42
U.S.C. 1302 and 1395hh).
0
2. Section 409.43 is amended by revising paragraph (e)(1)(iii) to read
as follows:
Sec. 409.43 Plan of care requirements.
* * * * *
(e) * * *
(1) * * *
(iii) Discharge with goals met and/or no expectation of a return to
home health care and the patient returns to home health care during the
60 day episode.
* * * * *
PART 424--CONDITIONS FOR MEDICARE PAYMENT
0
3. The authority citation for part 424 continues to read as follows:
Authority: Secs. 1102 and 1871 of the Social Security Act (42
U.S.C. 1302 and 1395hh).
Sec. 424.22 [Amended]
0
4. Section 424.22 is amended by redesignating paragraph (a)(1)(v)(B)(1)
as paragraph (a)(2) and by removing reserved paragraph (a)(1)(v)(B)(2).
PART 484--HOME HEALTH SERVICES
0
5. The authority citation for part 484 continues to read as follows:
Authority: Secs 1102 and 1871 of the Social Security Act (42
U.S.C. 1302 and 1395(hh)) unless otherwise indicated.
0
6. Section 484.205 is amended by revising paragraphs (d) and (e) to
read as follows:
Sec. 484.205 Basis of payment.
* * * * *
(d) Partial episode payment adjustment. (1) An HHA receives a
national 60-day episode payment of a predetermined rate for home health
services unless CMS determines an intervening event, defined as a
beneficiary elected transfer or discharge with goals met or no
expectation of return to home health and the beneficiary returned to
home health during the 60-day episode, warrants a new 60-day episode
for purposes of payment. A start of care OASIS assessment and physician
certification of the new plan of care are required.
(2) The PEP adjustment will not apply in situations of transfers
among HHAs of common ownership. Those situations will be considered
services provided under arrangement on behalf of the originating HHA by
the receiving HHA with the common ownership interest for the balance of
the 60-day episode. The common ownership exception to the transfer PEP
adjustment does not apply if the beneficiary moves to a different MSA
or Non-MSA during the 60-day
[[Page 39913]]
episode before the transfer to the receiving HHA. The transferring HHA
in situations of common ownership not only serves as a billing agent,
but must also exercise professional responsibility over the arranged-
for services in order for services provided under arrangements to be
paid.
(3) If the intervening event warrants a new 60-day episode payment
and a new physician certification and a new plan of care, the initial
HHA receives a partial episode payment adjustment reflecting the length
of time the patient remained under its care. A partial episode payment
adjustment is determined in accordance with Sec. 484.235.
(e) Outlier payment. An HHA receives a national 60-day episode
payment of a predetermined rate for a home health service, unless the
imputed cost of the 60-day episode exceeds a threshold amount. The
outlier payment is defined to be a proportion of the imputed costs
beyond the threshold. An outlier payment is a payment in addition to
the national 60-day episode payment. The total of all outlier payments
is limited to no more than 2.5 percent of total outlays under the HHA
PPS. An outlier payment is determined in accordance with Sec. 484.240.
0
7. Section 484.220 is amended by revising paragraph (a)(3) and adding
paragraphs (a)(4) through (6) to read as follows:
Sec. 484.220 Calculation of the adjusted national prospective 60-day
episode payment rate for case-mix and area wage levels.
* * * * *
(a) * * *
(3) For CY 2011, the adjustment is 3.79 percent.
(4) For CY 2012, the adjustment is 3.79 percent.
(5) For CY 2013, the adjustment is 1.32 percent.
(6) For CY 2016 and CY 2017, the adjustment is 1.72 percent in each
year.
* * * * *
0
8. Section 484.225 is revised to read as follows:
Sec. 484.225 Annual update of the unadjusted national prospective 60-
day episode payment rate.
(a) CMS updates the unadjusted national 60-day episode payment rate
on a fiscal year basis (as defined in section 1895(b)(1)(B) of the
Act).
(b) For 2007 and subsequent calendar years, in accordance with
section 1895(b)(3)(B)(v) of the Act, in the case of a home health
agency that submits home health 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 home health market basket index amount.
(c) For 2007 and subsequent calendar years, in accordance with
section 1895(b)(3)(B)(v) of the Act, in the case of a home health
agency that does not submit home health 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 home health market basket index amount minus 2 percentage
points. Any reduction of the percentage change will apply only to the
calendar year involved and will not be taken into account in computing
the prospective payment amount for a subsequent calendar year.
Sec. 484.230 [Amended]
0
9. Section 484.230 is amended by removing the last sentence.
0
10. Section 484.240 is amended by revising paragraphs (b) and (e) and
adding paragraph (f) to read as follows:
Sec. 484.240 Methodology used for the calculation of the outlier
payment.
* * * * *
(b) The outlier threshold for each case-mix group is the episode
payment amount for that group, or the PEP adjustment amount for the
episode, plus a fixed dollar loss amount that is the same for all case-
mix groups
* * * * *
(e) The fixed dollar loss amount and the loss sharing proportion
are chosen so that the estimated total outlier payment is no more than
2.5 percent of total payment under home health PPS.
(f) The total amount of outlier payments to a specific home health
agency for a year may not exceed an amount equal to 10 percent of the
total payments to the specific agency under home health PPS for the
year.
Sec. 484.245 [Removed and Reserved]
0
11. Section 484.245 is removed and reserved.
Sec. 484.250 [Amended]
0
12. Section Sec. 484.250(a)(2) is amended by removing the reference
``Sec. 484.225(i)'' and adding in its place the reference ``Sec.
484.225(c)''.
0
13. Subpart F is added to read as follows:
Subpart F--Home Health Value-Based Purchasing (HHVBP) Model Components
for Medicare-Certified Home Health Agencies Within State Boundaries
Sec.
484.300 Basis and scope of subpart.
484.305 Definitions.
484.310 Applicability of the Home Health Value-Based Purchasing
(HHVBP) model.
484.315 Data reporting for measures and evaluation under the Home
Health Value-Based Purchasing (HHVBP) model.
484.320 Calculation of the Total Performance Score.
484.325 Payments for home health services under Home Health Value-
Based Purchasing (HHVBP) model.
484.330 Process for determining and applying the value-based payment
adjustment under the Home Health Value-Based Purchasing (HHVBP)
model.
Subpart F--Home Health Value-Based Purchasing (HHVBP) Model
Components for Medicare-Certified Home Health Agencies Within State
Boundaries
Sec. 484.300 Basis and scope of subpart.
This subpart is established under section 1115A(a)(1) of the Act
(42 U.S.C. 1315a), which authorizes the Secretary to test innovative
payment and service delivery models to improve coordination, quality,
and efficiency of health care services furnished under Title XVIII.
Sec. 484.305 Definitions.
As used in this subpart--
Applicable measure means a measure for which the Medicare-certified
HHA has provided 20 home health episodes of care per year.
Applicable percent means a maximum upward or downward adjustment
for a given performance year, not to exceed the following:
(1) For CY 2018 and 2019, 5 percent.
(2) For CY 2020, 6 percent.
(3) For CY 2021 and 2022, 8 percent.
Benchmark refers to the mean of the top decile of Medicare-
certified HHA performance on the specified quality measure during the
baseline period, calculated separately for the larger-volume and
smaller-volume cohorts within each state.
Home health prospective payment system (HH PPS) refers to the basis
of payment for home health agencies as set forth in Sec. Sec. 484.200
through 484.245.
Larger-volume cohort means the group of Medicare-certified home
health agencies within the boundaries of selected states that are
participating in HHCAHPs in accordance with Sec. 484.250.
Linear exchange function is the means to translate a Medicare-
certified HHA's Total Performance Score into a value-based payment
adjustment percentage.
Medicare-certified home health agency means an agency:
[[Page 39914]]
(1) That has a current Medicare certification; and,
(2) Is being reimbursed by CMS for home health care delivered
within any of the states specified in accordance with CMS's selection
methodology.
New measures means those measures to be reported by Medicare-
certified HHAs under the HHVBP model that are not otherwise reported by
Medicare-certified HHAs to CMS and were identified to fill gaps to
cover National Quality Strategy Domains not completely covered by
existing measures in the home health setting.
Payment adjustment means the amount by which a Medicare-certified
HHA's final claim payment amount under the HH PPS is changed in
accordance with the methodology described in Sec. 484.325.
Performance period means the time period during which data are
collected for the purpose of calculating a Medicare-certified HHA's
performance on measures.
Selected state(s) means those nine states that were randomly
selected to compete/participate in the HHVBP model via a computer
algorithm designed for random selection.
Smaller-volume cohort means the group of Medicare-certified home
health agencies within the boundaries of selected states that are
exempt from participation in HHCAHPs in accordance with Sec. 484.250.
Starter set means the quality measures selected for the first year
of this model.
Total Performance Score means the numeric score ranging from 0 to
100 awarded to each Medicare-certified HHA based on its performance
under the HHVBP model.
Value-based purchasing means measuring, reporting, and rewarding
excellence in health care delivery that takes into consideration
quality, efficiency, and alignment of incentives. Effective health care
services and high performing health care providers may be rewarded with
improved reputations through public reporting, enhanced payments
through differential reimbursements, and increased market share through
purchaser, payer, and/or consumer selection.
Sec. 484.310 Applicability of the Home Health Value-Based Purchasing
(HHVBP) model.
(a) General rule. The HHVBP model applies to all Medicare-certified
home health agencies (HHAs) in selected states.
(b) Nine states are selected in accordance with CMS's selection
methodology. All Medicare-certified HHAs that provide services in
Massachusetts, Maryland, North Carolina, Florida, Washington, Arizona,
Iowa, Nebraska, and Tennessee will be required to compete in this
model.
Sec. 484.315 Data reporting for measures and evaluation under the
Home Health Value-Based Purchasing (HHVBP) model.
(a) Medicare-certified home health agencies will be evaluated using
a starter set of quality measures.
(b) Medicare-certified home health agencies in selected states will
be required to report information on New Measures, as determined
appropriate by the Secretary, to CMS in the form, manner, and at a time
specified by the Secretary.
(c) Medicare-certified home health agencies in selected states will
be required to collect and report such information as the Secretary
determines is necessary for purposes of monitoring and evaluating the
HHVBP model under section 1115A(b)(4) of the Act (42 U.S.C. 1315a).
Sec. 484.320 Calculation of the Total Performance Score.
A Medicare-certified home health agency's Total Performance Score
for a model year is calculated as follows:
(a) CMS will award points to the Medicare-certified home health
agency for performance on each of the applicable measures in the
starter set, other than New Measures.
(b) CMS will award points to the Medicare-certified home health
agency for reporting on each of the New Measures in the starter set,
worth up to ten percent of the Total Performance Score.
(c) CMS will sum all points awarded for each applicable measure in
the starter set, weighted equally at the individual measure level, to
calculate a value worth up to 90 percent of the Total Performance
Score.
(d) The sum of the points awarded to a Medicare-certified HHA for
each applicable measure in the starter set and the points awarded to a
Medicare-certified HHA for reporting data on each New Measure is the
Medicare-certified HHA's Total Performance Score for the calendar year.
Sec. 484.325 Payments for home health services under Home Health
Value-Based Purchasing (HHVBP) model.
CMS will determine a payment adjustment up to the maximum
applicable percentage, upward or downward, under the HHVBP model for
each Medicare-certified home health agency based on the agency's Total
Performance Score using a linear exchange function. Payment adjustments
made under the HHVBP model will be calculated as a percentage of
otherwise-applicable payments for home health services provided under
section 1895 of the Act (42 U.S.C. 1395fff).
Sec. 484.330 Process for determining and applying the payment
adjustment under the Home Health Value-Based Purchasing (HHVBP) model.
(a) General. Medicare-certified home health agencies will be ranked
within the larger-volume and smaller-volume cohorts in selected states
based on the performance standards that apply to the HHVBP model for
the baseline year, and CMS will make value-based payment adjustments to
the Medicare-certified HHAs as specified in this section.
(b) Calculation of the value-based payment adjustment amount. The
value-based payment adjustment amount is calculated by multiplying the
Home Health Prospective Payment final claim payment amount as
calculated in accordance with Sec. 484.205 by the payment adjustment
percentage.
(c) Calculation of the payment adjustment percentage. The payment
adjustment percentage is calculated as the product of: The applicable
percent as defined in Sec. 484.320, the Medicare-certified HHA's Total
Performance Score divided by 100, and the linear exchange function
slope.
Dated: June 25, 2015.
Andrew M. Slavitt,
Administrator, Centers for Medicare & Medicaid Services.
Dated: June 26, 2015.
Sylvia M. Burwell,
Secretary.
[FR Doc. 2015-16790 Filed 7-6-15; 4:15 pm]
BILLING CODE 4120-01-P