Medicare and Medicaid Programs; CY 2018 Home Health Prospective Payment System Rate Update and Proposed CY 2019 Case-Mix Adjustment Methodology Refinements; Home Health Value-Based Purchasing Model; and Home Health Quality Reporting Requirements, 35270-35393 [2017-15825]
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Federal Register / Vol. 82, No. 144 / Friday, July 28, 2017 / Proposed Rules
DEPARTMENT OF HEALTH AND
HUMAN SERVICES
Centers for Medicare & Medicaid
Services
42 CFR Parts 409 and 484
[CMS–1672–P]
RIN 0938–AT01
Medicare and Medicaid Programs; CY
2018 Home Health Prospective
Payment System Rate Update and
Proposed CY 2019 Case-Mix
Adjustment Methodology Refinements;
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 updates
the home health prospective payment
system (HH PPS) payment rates,
including the national, standardized 60day episode payment rates, the national
per-visit rates, and the non-routine
medical supply (NRS) conversion factor,
effective for home health episodes of
care ending on or after January 1, 2018.
This rule also: updates the HH PPS casemix weights using the most current,
complete data available at the time of
rulemaking; implements the 3rd-year of
a 3-year phase-in of a reduction to the
national, standardized 60-day episode
payment to account for estimated casemix growth unrelated to increases in
patient acuity (that is, nominal case-mix
growth) between CY 2012 and CY 2014;
and discusses our efforts to monitor the
potential impacts of the rebasing
adjustments that were implemented in
CY 2014 through CY 2017. This rule
proposes case-mix methodology
refinements, as well as a change in the
unit of payment from 60-day episodes of
care to 30-day periods of care, to be
implemented for home health services
beginning on or after January 1, 2019;
and finally, this rule proposes changes
to the Home Health Value-Based
Purchasing (HHVBP) Model and to the
Home Health Quality Reporting Program
(HH QRP).
DATES: To be assured consideration,
comments must be received at one of
the addresses provided below, no later
than 5 p.m. on September 25, 2017.
ADDRESSES: In commenting, please refer
to file code CMS–1672–P. Because of
staff and resource limitations, we cannot
accept comments by facsimile (FAX)
transmission.
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SUMMARY:
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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–1672–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–1672–P, Mail
Stop C4–26–05, 7500 Security
Boulevard, Baltimore, MD 21244–1850.
4. By hand or courier. If you prefer,
you may deliver (by hand or courier)
your written comments before the close
of the comment period to either of the
following addresses:
a. For delivery in Washington, DC—
Centers for Medicare & Medicaid
Services, Department of Health and
Human Services, Room 445–G, Hubert
H. Humphrey Building, 200
Independence Avenue SW.,
Washington, DC 20201.
(Because access to the interior of the Hubert
H. Humphrey Building is not readily
available to persons without federal
government identification, commenters are
encouraged to leave their comments in the
CMS drop slots located in the main lobby of
the building. A stamp-in clock is available for
persons wishing to retain a proof of filing by
stamping in and retaining an extra copy of
the comments being filed.)
b. For delivery in Baltimore, MD—
Centers for Medicare & Medicaid
Services, Department of Health and
Human Services, 7500 Security
Boulevard, Baltimore, MD 21244–1850.
If you intend to deliver your
comments to the Baltimore address,
please call (410) 786–7195 in advance to
schedule your arrival with one of our
staff members.
Comments mailed to the addresses
indicated as appropriate for hand or
courier delivery may be delayed and
received after the comment period.
For information on viewing public
comments, see the beginning of the
SUPPLEMENTARY INFORMATION section.
FOR FURTHER INFORMATION CONTACT: For
general information about the HH PPS,
please send your inquiry via email to:
HomehealthPolicy@cms.hhs.gov.
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For information about the HHVBP
model, please send your inquiry via
email to: HHVBPquestions@
cms.hhs.gov.
Joan Proctor, (410) 786–0949 for
information about the home health
quality reporting program.
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.
SUPPLEMENTARY INFORMATION:
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. Current System for Payment of Home
Health Services
C. Updates to the Home Health Prospective
Payment System
D. Report to Congress: Home Health Study
on Access to Care for Vulnerable Patient
Populations and Subsequent Research
and Analyses
III. Provisions of the Proposed Rule: Payment
Under the Home Health Prospective
Payment System (HH PPS)
A. Monitoring for Potential Impacts—
Affordable Care Act Rebasing
Adjustments
B. Proposed CY 2018 HH PPS Case-Mix
Weights
C. Proposed CY 2018 Home Health
Payment Rate Update
D. Payments for High-Cost Outliers under
the HH PPS
E. Proposed Implementation of the Home
Health Groupings Model (HHGM) for CY
2019
IV. Proposed Provisions of the Home Health
Value-Based Purchasing (HHVBP) Model
A. Background
B. Quality Measures
C. Quality Measures for Future
Consideration
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V. Proposed Updates to the Home Health
Care Quality Reporting Program (HH
QRP)
A. Background and Statutory Authority
B. General Considerations Used for the
Selection of Quality Measures for the HH
QRP
C. Accounting for Social Risk Factors in
the HH QRP
D. Proposed Data Elements for Removal
From OASIS
E. Proposed Collection of Standardized
Patient Assessment Data Under the HH
QRP
F. HH QRP Quality Measures Proposed
Beginning With the CY 2020 HH QRP
G. HH QRP Quality Measures and Measure
Concepts Under Consideration for Future
Years
H. Proposed Standardized Patient
Assessment Data
I. Proposals Relating to the Form, Manner,
and Timing of Data Submission Under
the HH QRP
J. Other Proposals for the CY 2019 HH QRP
and Subsequent Years
K. Proposals and Policies Regarding Public
Display of Quality Measure Data for the
HH QRP
L. Proposed Mechanism for Providing
Confidential Feedback Reports to HHAs
M. Home Health Care CAHPS® Survey
(HHCAHPS)
VI. Request for Information on CMS
Flexibilities and Efficiencies
VII. Collection of Information Requirements
A. Statutory Requirement for Solicitation
of Comments
B. Collection of Information Requirements
for the HH QRP
C. Submission of PRA-Related Comments
VIII. Response to Public Comments
IX. Regulatory Impact Analysis
A. Statement of Need
B. Overall Impact
C. Detailed Economic Analysis
D. Alternatives Considered
E. Accounting Statement and Table
F. Reducing Regulation and Controlling
Regulatory Costs
G. Conclusion
X. Federalism Analysis
Regulation 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
AM–PAC Activity Measure for Post-Acute
Care
APU Annual Payment Update
ASPE Assistant Secretary for Planning and
Evaluation
BBA Balanced Budget Act of 1997, Public
Law 105–33
BBRA Medicare, Medicaid, and SCHIP
Balanced Budget Refinement Act of 1999,
(Pub. L. 106–113)
BIMS Brief Interview for Mental Status
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BLS Bureau of Labor Statistics
CAD Coronary Artery Disease
CAH Critical Access Hospital
CAM Confusion Assessment Method
CARE Continuity Assessment Record and
Evaluation
CASPER Certification and Survey Provider
Enhanced Reports
CBSA Core-Based Statistical Area
CCN CMS Certification Number
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, Public
Law 109–171, enacted February 8, 2006
DTI Deep Tissue Injury
EOC End of Care
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
HHGM Home Health Groupings Model
HHQRP Home Health Quality Reporting
Program
HHRG Home Health Resource Group
HHVBP Home Health Value-Based
Purchasing
HIPPS Health Insurance Prospective
Payment System
HVBP Hospital Value-Based Purchasing
IADL Instrumental Activities of Daily
Living
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 Care
Transformation Act of 2014 (Pub. L. 113–
185)
IPR Interim Performance Report
IRF Inpatient Rehabilitation Facility
IRF–PAI IRF Patient Assessment Instrument
IV Intravenous
LCDS LTCH CARE Data Set
LEF Linear Exchange Function
LTCH Long-Term Care Hospital
LUPA Low-Utilization Payment Adjustment
MACRA Medicare Access and CHIP
Reauthorization Act of 2015
MAP Measure Applications Partnership
MDS Minimum Data Set
MEPS Medical Expenditures Panel Survey
MFP Multifactor productivity
MMA Medicare Prescription Drug,
Improvement, and Modernization Act of
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35271
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
OLS Ordinary Least Squares
OT Occupational Therapy
OMB Office of Management and Budget
PAC Post-Acute Care
PAC–PRD Post-Acute Care Payment Reform
Demonstration
PAMA Protecting Access to Medicare Act of
2014
PEP Partial Episode Payment Adjustment
PHQ–2 Patient Health Questionnaire-2
PPOC Primary Point of Contact
PPS Prospective Payment System
PRA Paperwork Reduction Act
PRRB Provider Reimbursement Review
Board
PT Physical Therapy
PY Performance Year
QAP Quality Assurance Plan
QIES Quality Improvement Evaluation
System
QRP Quality Reporting Program
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
ROC Resumption of Care
SAF Standard Analytic File
SLP Speech-Language Pathology
SN Skilled Nursing
SNF Skilled Nursing Facility
SOC Start of Care
SSI Surgical Site Infection
TEP Technical Expert Panel
TPS Total Performance Score
UMRA Unfunded Mandates Reform Act of
1995.
VAD Vascular Access Device
VBP Value-Based Purchasing
I. Executive Summary
A. Purpose
This proposed rule would update the
payment rates for home health agencies
(HHAs) for calendar year (CY) 2018, as
required under section 1895(b) of the
Social Security Act (the Act). This
proposed rule would update the casemix weights under section
1895(b)(4)(A)(i) and (b)(4)(B) of the Act
for CY 2018 and implement a 0.97
percent reduction to the national,
standardized 60-day episode payment
amount to account for case-mix growth
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unrelated to increases in patient acuity
(that is, nominal case-mix growth)
between CY 2012 and CY 2014, under
the authority of section 1895(b)(3)(B)(iv)
of the Act. For home health services
beginning on or after January 1, 2019,
this rule also proposes case-mix
methodology refinements under the
authority set out at sections
1895(b)(4)(A)(i) and (b)(4)(B) of the Act,
and a change in the unit of payment
from a 60-day episode of care to a 30day period of care under the authority
set out at section 1895(b)(2) of the Act.
Additionally, this rule proposes changes
to: The Home Health Value Based
Purchasing (HHVBP) model under the
authority of section 1115A of the Act;
and the Home Health Quality Reporting
Program (HH QRP) requirements under
the authority of section 1895(b)(3)(B)(v)
of the Act.
B. Summary of the Major Provisions
Section III.A of this rule discusses our
efforts to monitor for potential impacts
due to the rebasing adjustments
implemented in CY 2014 through CY
2017, as mandated by section 3131(a) of
the Patient Protection and Affordable
Care Act of 2010 (Pub. L. 111–148,
enacted March 23, 2010) as amended by
the Health Care and Education
Reconciliation Act of 2010 (Pub. L. 111–
152, enacted March 30, 2010),
collectively referred to as the
‘‘Affordable Care Act’’. In the CY 2015
HH PPS final rule (79 FR 66072), we
finalized our proposal to recalibrate the
case-mix weights every year with the
most current and complete data
available at the time of rulemaking. In
section III.B 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. Also in section III.B of
this rule, as finalized in the CY 2016 HH
PPS final rule (80 FR 68624), we are
implementing a reduction to the
national, standardized 60-day episode
payment rate for CY 2018 of 0.97
percent to account for estimated casemix growth unrelated to increases in
patient acuity (that is, nominal case-mix
growth) between CY 2012 and CY 2014.
In section III.C of this proposed rule,
we would update the payment rates
under the HH PPS by 1 percent for CY
2018 in accordance with section 411(d)
of the Medicare Access and CHIP
Reauthorization Act of 2015 (MACRA)
(Pub. L. 114–10, enacted April 16, 2015)
which amended section 1895(b)(3)(B) of
the Act. Additionally, section III.C of
this rule, would update the CY 2018
home health wage index using FY 2014
hospital cost report data. In section III.D
of this proposed rule, we note that the
fixed-dollar loss ratio would remain
0.55 for CY 2018 to pay up to, but no
more than, 2.5 percent of total payments
as outlier payments, as required by
section 1895(b)(5)(A) of the Act.
In section III.E of this rule we are
proposing to implement case-mix
methodology refinements and a change
in the unit of payment from a 60-day
episode of care to a 30-day period of
care, effective for home health services
beginning on or after January 1, 2019.
The proposed home health groupings
model (HHGM) relies more heavily on
clinical characteristics and other patient
information to place patients into
meaningful payment categories, while
eliminating therapy service use
thresholds that are currently used to
case-mix adjust payments under the HH
PPS. This includes proposed changes in
the episode timing categories, the
addition of an admission source
category, the creation of six clinical
groups used to categorize patients based
on their primary reason for home health
care, revised functional levels and
corresponding OASIS items, the
addition of a comorbidity adjustment,
and a proposed change in the LowUtilization Payment Adjustment (LUPA)
threshold. The LUPA add-on policy, the
partial [episode] payment adjustment
policy, and the methodology used to
calculate payments for high-cost outliers
would remain unchanged except for
occurring on a 30-day basis rather than
a 60-day basis.
In section IV of this rule, we are
proposing changes to the Home Health
Value-Based Purchasing (HHVBP)
Model implemented January 1, 2016.
We are proposing to amend the
definition of ‘‘applicable measure’’ to
specify that the HHA would have to
submit a minimum of 40 completed
surveys for Home Health Care Consumer
Assessment of Healthcare Providers and
Systems (HHCAHPS) measures, for
purposes of receiving a performance
score for any of the HHCAHPS
measures, and for performance year (PY)
3 and subsequent years, to remove the
Outcome and Assessment Information
Set (OASIS)-based measure, Drug
Education on All Medications Provided
to Patient/Caregiver during All Episodes
of Care, from the set of applicable
measures. We are also soliciting public
comments on composite quality
measures for future consideration.
In section V of this rule, we propose
updates to the Home Health Quality
Reporting Program, including: The
replacement of one quality measure, the
adoption of two new quality measures,
the reporting of standardized patient
assessment data in five categories
described under the IMPACT Act, data
submission requirements, exception and
extension requirements, and
reconsideration and appeals procedures.
C. Summary of Costs and Benefits
TABLE 1—SUMMARY OF COSTS AND TRANSFERS
Costs
Transfers
CY 2018 HH PPS Payment Rate
Update.
CY 2018 HHVBP Model ..................
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Provision description
........................................................
The overall economic impact of the HH PPS payment rate update is
an estimated ¥$80 million (¥0.4 percent) in payments to HHAs.
The overall economic impact of the HHVBP Model provision for CY
2018 through 2022 is an estimated $378 million in total savings
from a reduction in unnecessary hospitalizations and SNF usage
as a result of greater quality improvements in the HH industry
(none of which is attributable to the changes proposed in this proposed rule). As for payments to HHAs, there are no aggregate increases or decreases expected to be applied to the HHAs competing in the model.
CY 2019 HH QRP ...........................
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The overall economic impact of
the HH QRP changes is a savings to HHAs of an estimated
$44.9 million, beginning January
1, 2019.
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TABLE 1—SUMMARY OF COSTS AND TRANSFERS—Continued
Provision description
Costs
Transfers
CY 2019 HH PPS Case-Mix Adjustment Methodology Refinements.
........................................................
The overall impact of the proposed HH PPS case-mix adjustment
methodology refinements, including a change in the unit of payment from 60-day episodes to 30-day periods of care, is an estimated ¥$950 million (¥4.3 percent) in payments to HHAs in CY
2019 if the refinements are implemented in a non-budget neutral
manner for 30-day periods of care beginning on or after January 1,
2019. The overall impact is an estimated ¥$480 million (¥2.2 percent) in payments to HHAs in CY 2019 if the refinements are implemented in a partially budget-neutral manner.
II. Background
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A. Statutory Background
The Balanced Budget Act of 1997
(BBA) (Pub. L. 105–33, enacted August
5, 1997), significantly changed the way
Medicare pays for Medicare HH
services. Section 4603 of the BBA
mandated the development of the HH
PPS. Until the implementation of the
HH PPS on October 1, 2000, HHAs
received payment under a retrospective
reimbursement system.
Section 4603(a) of the BBA mandated
the development of a HH PPS for all
Medicare-covered HH services provided
under a plan of care (POC) that were
paid on a reasonable cost basis by
adding section 1895 of the Act, entitled
‘‘Prospective Payment For Home Health
Services.’’ Section 1895(b)(1) of the Act
requires the Secretary to establish a HH
PPS for all costs of HH services paid
under Medicare.
Section 1895(b)(3)(A) of the Act
requires the following: (1) The
computation of a standard prospective
payment amount 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 an appropriate
case-mix change adjustment factor for
significant variation in costs among
different units of services.
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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 Affordable
Care Act 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 for Fiscal Year 1999
(OCESAA), (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 of 1999, (BBRA) (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
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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 MACRA amended
section 421(a) of the MMA to extend the
rural add-on for 2 more years. Section
421(a) of the MMA, as amended by
section 210 of the MACRA, requires that
the Secretary increase, by 3 percent, the
payment amount otherwise made under
section 1895 of the Act, for HH services
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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. Section 411(d) of
MACRA amended section 1895(b)(3)(B)
of the Act such that for home health
payments for CY 2018, the market
basket percentage increase shall be 1
percent.
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B. Current System for Payment of Home
Health Services
Generally, Medicare currently 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 not part
of the national, standardized 60-day
episode rate, but is computed by
multiplying the relative weight for a
particular NRS severity level by the NRS
conversion factor. 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 casemix 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. Therapy service use is
measured by the number of therapy
visits provided during the episode and
can be categorized into nine visit level
categories (or thresholds): 0–5; 6; 7–9;
10; 11–13; 14–15; 16–17; 18–19; and 20
or more visits.
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.
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C. Updates to the Home Health
Prospective Payment System
As required by section 1895(b)(3)(B)
of the Act, we have historically updated
the HH PPS rates annually in the
Federal Register. The August 29, 2007
final rule with comment period set forth
an update to the 60-day national
episode rates and the national per-visit
rates under the HH PPS for CY 2008.
The CY 2008 HH PPS final rule
included an analysis performed on CY
2005 HH claims data, which indicated
a 12.78 percent increase in the observed
case-mix since 2000. Case-mix
represents the variations in conditions
of the patient population served by the
HHAs. Subsequently, a more detailed
analysis was performed on the 2005
case-mix data to evaluate if any portion
of the 12.78 percent increase was
associated with a change in the actual
clinical condition of HH patients. We
identified 8.03 percent of the total casemix 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.
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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 4-year
period in equal increments, not to
exceed 3.5 percent of the amount (or
amounts) as of the date of enactment of
the Affordable Care Act, and fully
implement the rebasing adjustments by
CY 2017. The statute 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, 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 speechlanguage pathology and removed 170
diagnosis codes from assignment to
diagnosis groups in the HH PPS
Grouper. In the CY 2015 HH PPS final
rule (79 FR 66032), we implemented the
2nd year of the 4 year phase-in of the
rebasing adjustments to the HH PPS
payment rates and made changes to the
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HH PPS case-mix weights. In addition,
we simplified the face-to-face encounter
regulatory requirements and the therapy
reassessment timeframes.
In the CY 2016 HH PPS final rule (80
FR 68624), we implemented the 3rd
year of the 4-year phase-in of the
rebasing adjustments to the national,
standardized 60-day episode payment
amount, the national per-visit rates and
the NRS conversion factor (as outlined
above). In the CY 2016 HH PPS final
rule, we also recalibrated the HH PPS
case-mix weights, using the most
current cost and utilization data
available, in a budget neutral manner
and finalized reductions to the national,
standardized 60-day episode payment
rate in CY 2016, CY 2017, and CY 2018
of 0.97 percent in each year to account
for estimated case-mix growth unrelated
to increases in patient acuity (that is,
nominal case-mix growth) between CY
2012 and CY 2014. Finally, section
421(a) of the MMA, as amended by
section 210 of the MACRA, extended
the payment increase of 3 percent for
HH services provided in rural areas (as
defined in section 1886(d)(2)(D) of the
Act) to episodes or visits ending before
January 1, 2018.
In the CY 2017 HH PPS final rule (81
FR 76702), we implemented the last
year of the 4-year phase-in of the
rebasing adjustments to the national,
standardized 60-day episode payment
amount, the national per-visit rates and
the NRS conversion factor (as outlined
above). We also finalized changes to the
methodology used to calculate outlier
payments under the authority of section
1895(b)(5) of the Act. Lastly, in
accordance with section 1834(s) of the
Act, as added by section 504(a) of the
Consolidated Appropriations Act, 2016
(Pub. L. 114–113, enacted December 18,
2015), we implemented changes in
payment for furnishing Negative
Pressure Wound Therapy (NPWT) using
a disposable device for patients under a
home health plan of care for which
payment would otherwise be made
under section 1895(b) of the Act.
D. Report to Congress: Home Health
Study on Access to Care for Vulnerable
Patient Populations and Subsequent
Research and Analyses
Section 3131(d) of the Affordable Care
Act required CMS to conduct a study on
home health agency costs involved with
providing ongoing access to care to lowincome Medicare beneficiaries or
beneficiaries in medically underserved
areas, and in treating beneficiaries with
varying levels of severity of illness and
submit a report to Congress. As
discussed in the CY 2016 HH PPS
proposed rule (80 FR 39840) and the CY
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2017 HH PPS proposed rule (81 FR
43744), the findings from the Report to
Congress on the ‘‘Medicare Home
Health Study: An Investigation on
Access to Care and Payment for
Vulnerable Patient Populations’’, found
that payment accuracy could be
improved under the current payment
system, particularly for patients with
certain clinical characteristics requiring
more nursing care than therapy.1
The research for the Report to
Congress, released in December 2014,
consisted of extensive analysis of both
survey and administrative data. The
CMS-developed surveys were given to
physicians who referred vulnerable
patient populations to Medicare home
health and to Medicare-certified HHAs.2
The response rates were 72 percent and
59 percent for the HHA and physician
surveys, respectively. The results of the
survey revealed that over 80 percent of
respondent HHAs and over 90 percent
of respondent 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 (64 percent of
respondent HHAs surveyed) 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. Only 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 results of the CMSconducted surveys suggested that CMS’
ability to improve access for certain
vulnerable patient populations through
payment policy may be limited.
However, we are able to revise the casemix system to minimize differences in
payment that could potentially be
serving as a barrier to receiving care. In
this rule, we propose to better align
payment with resource use so that it
reduces HHAs’ financial incentives to
select certain patients over others.
However, we also performed an
analysis of Medicare administrative data
(CY 2010 Medicare claims and cost
1 The Report to Congress can be found in its
entirety at https://www.cms.gov/Medicare/
Medicare-Fee-for-ServicePayment/HomeHealthPPS/
Downloads/HH-Report-to-Congress.pdf.
2 For the purposes of the surveys, ‘‘vulnerable
patient populations’’ were defined as beneficiaries
who were either eligible for the Part D low-income
subsidy (LIS) 27 or residing in a health professional
shortage area (HPSA).
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35275
report data) and calculated margins for
episodes of care. This was done because
margin differences associated with
patient clinical and social
characteristics can indicate whether
financial incentives exist in the current
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, potentially
creating access to care issues. The
findings from the data analysis found
that certain patient characteristics
appear to be strongly associated with
margin levels, and thus may create
financial incentives to select certain
patients over others. Margins were
estimated to be lower for patients who
required parenteral nutrition, who had
traumatic wounds or ulcers, or required
substantial assistance in bathing. For
example, in CY 2010, episodes for
patients with parenteral nutrition were,
on average, associated with a $178.53
lower margin than episodes for patients
without parenteral nutrition. Given that
these variables are already included in
the HH PPS case-mix system, the results
indicated that modifications to the way
the current case-mix system accounts
for resource use differences may be
needed to mitigate any financial
incentives to select certain patients over
others. Margins were also lower for
beneficiaries who were admitted after
acute or post-acute stays or who had
certain poorly-controlled clinical
conditions, such as poorly-controlled
pulmonary disorders, indicating that
accounting for additional patient
characteristic variables in the HH PPS
case-mix system may also reduce
financial incentives to select certain
types of patients over others. More
information on the results from the
Home Health Study required by section
3131(d) of the Affordable Care Act can
be found in the Report to Congress on
the ‘‘Medicare Home Health Study: An
Investigation on Access to Care and
Payment for Vulnerable Patient
Populations’’ available at https://
www.cms.gov/center/provider-Type/
home-Health-Agency-HHA-Center.html.
Section 3131(d)(5) of the Affordable
Care Act allowed for the Secretary to
determine whether a Medicare
demonstration project is appropriate to
conduct based on the result of the Home
Health Study. If the Secretary
determined it was appropriate to
conduct the demonstration project
under this subsection, the Secretary was
to conduct the project for a four year
period beginning not later than January
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number of therapy visits per 60-day
episode of care have increased since the
implementation of the HH PPS, while
the number of skilled nursing and home
health aide visits have decreased over
the same time period as shown in Figure
3 in section III.A of this rule. A study
examining an option of using predicted,
rather than actual, therapy visits in the
HH found that in 2013, 58 percent of
home health episodes included some
therapy services, and these episodes
accounted for 72 percent of all Medicare
home health payments.3 Figure 1 from
that study demonstrates that the
percentage of episodes, and the average
episode payment by the number of
therapy visits for episodes with at least
one therapy visit in 2013 increased
sharply in therapy provision just over
payment thresholds at 6, 7, and 16.
According to the study, the presence of
sharp increases in the percentage of
episodes just above payment thresholds
suggests a response to financial
incentives in the home health payment
system. Similarly, between 2008 and
2013, MedPAC reported a 26 percent
increase in the number of episodes with
at least 6 therapy visits, compared with
a 1 percent increase in the number of
episodes with five or fewer therapy
visits.4 CMS analysis demonstrates that
the average share of therapy visits across
all 60-day episodes of care increased
from 9 percent of all visits in 1997, prior
to the implementation of the HH PPS
(see 64 FR 58151), to 39 percent of all
visits in 2015 (see Table 2 in section
III.A. of this proposed rule).
Figure 1 suggests that HHAs may be
responding to financial incentives in the
home health payment system when
making care plan decisions.
Additionally, an investigation into the
therapy practices of the four largest
publically-traded home health
companies, conducted by the Senate
Committee on Finance in 2010, found
that three out of the four companies
investigated ‘‘encouraged therapists to
target the most profitable number of
therapy visits, even when patient need
alone may not have justified such
patterns’’.5 The Committee on Finance
3 Fout B, Plotzke M, Christian T. (2016). Using
Predicted Therapy Visits in the Medicare Home
Health Prospective Payment System. Home Health
Care Management & Practice, 29(2), 81–90. https://
journals.sagepub.com/doi/abs/10.1177/
1084822316678384.
4 Medicare Payment Advisory Commission
(MedPAC). ‘‘Home Health Care Services.’’ Report to
Congress: Medicare Payment Policy. Washington,
DC, March 2015. P. 223. Accessed on March 28,
2017 at: https://www.medpac.gov/docs/default-
source/reports/mar2015_entirereport_revised.pdf
?sfvrsn=0.
5 Committee on Finance, United States Senate.
Staff Report on Home Health and the Medicare
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1, 2015. We did not determine that it
was appropriate to conduct a
demonstration project based on the
findings from the Home Health Study.
Rather, the findings from the Home
Health Study suggested that follow-on
work should be conducted to better
align payments with costs under the
authority of section 1895 of the Act.
In addition to the findings from the
Report to Congress on the ‘‘Medicare
Home Health Study: An Investigation on
Access to Care and Payment for
Vulnerable Patient Populations’’,
concerns have also been raised about
the use of therapy thresholds in the
current payment system. Under the
current payment system, HHAs receive
higher payments for providing more
therapy visits once certain thresholds
are reached. As a result, the average
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investigation also highlighted the abrupt
and dramatic responses the home health
industry has taken to maximize
reimbursement under the therapy
threshold models (both the original 10visit threshold model and under the
revised thresholds implemented in the
CY 2008 HH PPS final rule (72 FR
49762)). Under the HH PPS, the report
noted that HHAs have broad discretion
over the number of therapy visits to
provide patients and therefore have
control of the single-largest variable in
determining reimbursement and overall
margins. The report recommended that
CMS closely examine a future payment
approach that focuses on patient wellbeing and health characteristics, rather
than the numerical utilization measures.
MedPAC also continues to
recommend the removal of the therapy
thresholds used for determining
payment from the HH PPS, as it believes
that such thresholds run counter to the
goals of a prospective payment system,
create financial incentives that detract
from a focus on patient characteristics
and care needs when agencies are
setting plans of care for their patients,
and incentivize unnecessary therapy
utilization. For the average HHA,
according to MedPAC, the increase in
payment for therapy visits rises faster
than costs resulting in financial
incentives for HHAs to overprovide
therapy services.6 HHAs that provide
more therapy episodes tend to be more
profitable and this higher profitability
and rapid growth in the number of
therapy episodes suggest that financial
incentives are causing agencies to favor
therapy services when possible.7
Eliminating therapy as a payment factor
would base home health payment solely
on patient characteristics, which is a
more patient-focused approach to
payment, as recommended by both
MedPAC and previously by the Senate
Committee on Finance.
After considering the findings from
the Report to Congress and
recommendations from MedPAC and
the Senate Committee on Finance, CMS,
along with our contractor, conducted
additional research on ways to improve
the payment accuracy under the current
payment system. Exploring all options
and different models ultimately led us
to further develop the Home Health
Groupings Model (HHGM) proposal.
The HHGM proposal uses 30-day
periods, rather than 60-day episodes,
and relies more heavily on clinical
characteristics and other patient
information (for example, principal
diagnosis, functional level, comorbid
conditions, admission source, and
timing) to place patients into
meaningful payment categories, rather
than the current therapy driven system.
We believe this patient-centered
approach is consistent with how
clinicians differentiate between home
health patients and would improve
payment accuracy and access for
medically complex cases and not just
cases receiving therapy. The HHGM
proposal leverages many of the same
aspects of the current system; however,
the major differences between the
current system and the HHGM proposal
include a change from a 60-day to a 30day billing cycle and the elimination of
the therapy thresholds in the case-mix
system.
We shared the analyses and
development of the HHGM with both
internal and external stakeholders via
technical expert panels, clinical
workgroups, special open door forums,
and in the CY 2016 HH PPS proposed
rule (80 FR 39840) and the CY 2017 HH
PPS proposed rule (81 FR 43744). Most
recently, we posted a detailed technical
report on the CMS Web site in
December of 2016.8 After posting the
technical report for the public to review,
we also held additional technical expert
panel and clinical workgroup webinars
to garner feedback from the industry
and conducted a National Provider call
that occurred in January 2017 to solicit
35277
feedback from external stakeholders.9
The feedback we received during the
National Provider call on the HHGM
was positive. We discuss the HHGM
proposal further below, in section III.E,
and seek public comment on this
proposal and the underlying analyses.
III. Provisions of the Proposed Rule:
Payment Under the Home Health
Prospective Payment System (HH PPS)
A. Monitoring for Potential Impacts—
Affordable Care Act Rebasing
Adjustments
1. Analysis of FY 2015 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.
Previous years’ cost report and claims
data analyses and results can be found
in the CY 2017 HH PPS proposed rule
(81 FR 43719 through 43720). For this
proposed rule, we analyzed 2015 HHA
cost report data and 2015 HHA claims
data. To determine the 2015 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
2015 cost reports by size, facility type,
and urban/rural location so the costs per
visit were nationally representative
according to 2015 claims data. The 2015
average number of visits was taken from
2015 claims data. We estimated the cost
of a 60-day episode in CY 2015 to be
$2,449.01 using 2015 cost report data as
shown in Table 2. However, the
national, standardized 60-day episode
payment amount in CY 2015 was
$2,961.38. For CY 2015, on average,
payments were 21 percent higher than
costs (($2,961.38—$2,449.01)/
$2,449.01).
TABLE 2—2015 ESTIMATED COST PER EPISODE
2015 Average
costs per visit
Discipline
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Skilled Nursing ...........................................................................................................
Physical Therapy .......................................................................................................
Therapy Threshold. Washington, DC, 2011.
Accessed on March 28, 2017 at https://
www.finance.senate.gov/imo/media/doc/Home_
Health_Report_Final4.pdf.
6 Medicare Payment Advisory Commission
(MedPAC). ‘‘Home Health Services.’’ Report to
Congress: Medicare Payment Policy. Washington,
DC, March 2011. P. 182–183. Accessed on March
28, 2017 at https://www.medpac.gov/docs/defaultsource/reports/Mar11_Ch08.pdf?sfvrsn=0.
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$132.48
156.32
7 Medicare Payment Advisory Commission
(MedPAC). ‘‘Home Health Care Services.’’ Report to
Congress: Medicare Payment Policy. Washington,
DC, March 2017. P. 243–244. Accessed on March
28, 2017 at https://www.medpac.gov/docs/defaultsource/reports/mar17_medpac_ch9.pdf?sfvrsn=0.
8 Ab Associates. Medicare Home Health
Prospective Payment System: Case-Mix
Methodology Refinements. Overview of the Home
Health Groupings Model. Cambridge, MA,
November 18, 2016. Accessed on April 27, 2017 at:
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2015 Average
number
of visits
8.93
5.39
2015 60-day
episode costs
$1,183.05
842.56
https://downloads.cms.gov/files/hhgm%
20technical%20report%20120516%20sxf.pdf.
9 Centers for Medicare & Medicaid Services
(CMS). ‘‘Home Health Groupings Model Technical
Report Call.’’ Baltimore, MD, January 18, 2017.
Accessed on April 27, 2017 at: https://
www.cms.gov/Outreach-and-Education/Outreach/
NPC/National-Provider-Calls-and-Events-Items/
2017-01-18-Home-Health.html?DLPage=
2&DLEntries=10&DLSort=0&DLSortDir=descending.
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TABLE 2—2015 ESTIMATED COST PER EPISODE—Continued
2015 Average
number
of visits
2015 Average
costs per visit
Discipline
2015 60-day
episode costs
Occupational Therapy ................................................................................................
Speech Pathology ......................................................................................................
Medical Social Services .............................................................................................
Home Health Aides ....................................................................................................
154.64
170.96
220.07
62.80
1.41
0.29
0.14
1.99
218.04
49.58
30.81
124.97
Total ....................................................................................................................
..............................
18.15
2,449.01
Source: Medicare cost reports pulled in February 2017 and Medicare claims data from 2014 and 2015 for episodes (excluding low-utilization
payment adjusted episodes and partial-episode-payment adjusted episodes), linked to OASIS assessments for episodes ending in CY 2015.
2. Analysis of CY 2016 HHA Claims
Data
In the CY 2014 HH PPS final rule (78
FR 72283), 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 3 years of the 4-year phase-in
of the rebasing adjustments (CY 2014,
CY 2015, and CY 2016), the first
calendar year of the HH PPS (CY 2001),
and claims data for 2 years before
implementation of the rebasing
adjustments (CY 2012 and CY2013).
Analysis of CY 2016 home health claims
data indicates that the number of
episodes and the number of home
health users that received at least one
episode of care remained virtually the
same (change of less than 1 percent)
from 2015 to 2016, while the number of
FFS beneficiaries increased 2 percent
from 2015 to 2016. 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,
a continued decrease of 1.7 percent from
2014 to 2015, and a decrease of 2.5
percent from 2015 to 2016. The number
of home health users, as a percentage of
FFS beneficiaries, appears to have
slightly decreased from 9.0 percent in
2012 to 8.7 percent in 2016, but remains
higher than the 6.9 percent in 2001. In
CY 2016, there were 2.9 HHAs per
10,000 FFS beneficiaries, which is still
markedly higher than the 1.9 HHAs per
10,000 FFS beneficiaries observed close
to the implementation of the HH PPS in
2001 (see Table 3). Therefore, the
rebasing adjustments made to the HH
PPS payment rates in CYs 2014 through
2016 do not appear to have resulted in
significant HHA closures or otherwise
diminished access to home health
services.
TABLE 3—HOME HEALTH STATISTICS, CY 2001 AND CY 2012 THROUGH CY 2016 10
2001
2013
2014
2015
2016
3,896,502
6,727,875
6,708,923
6,451,283
6,340,932
6,294,234
2,412,318
34,899,167
3,446,122
38,224,640
3,484,579
38,505,609
3,381,635
38,506,534
3,365,512
38,506,534
3,350,174
38,555,150
0.11
0.18
0.17
0.17
0.17
0.16
6.9%
6,511
9.0%
11,746
9.0%
11,889
8.8%
11,693
8.8%
11,381
8.7%
11,102
1.9
Number of episodes .................................
Beneficiaries receiving at least 1 episode
(Home Health Users) ...........................
Part A and/or B FFS beneficiaries ...........
Episodes per Part A and/or B FFS beneficiaries .................................................
Home health users as a percentage of
Part A and/or B FFS beneficiaries .......
HHAs providing at least 1 episode ..........
HHAs per 10,000 Part A and/or B FFS
beneficiaries .........................................
2012
3.1
3.1
3.0
3.0
2.9
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Source: National claims history (NCH) data obtained from Chronic Condition Warehouse (CCW)—Accessed on May 14, 2014 and August 19,
2014 for CY 2011, CY 2012, and CY 2013 data; accessed on May 7, 2015 for CY 2001 and CY 2014 data; accessed on April 7, 2016 for CY
2015 data; and accessed on March 20, 2017 for CY 2016 data and 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 three years of
the implementation of rebasing
adjustments required by the Affordable
Care Act, we examined trends in home
health utilization for all years starting in
CY 2001 and up through CY 2016.
Figure 2, 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 $167 for CY 2016, the
average total number of visits per 60-day
episode of care has declined, most
notably between CY 2009 (21.7 visits
per episode) and CY 2010 (19.8 visits
per episode), which was the first year
that the 10 percent agency-level cap on
HHA outlier payments was
implemented. The average of total visits
per episode has steadily decreased from
21.7 in 2009 to 17.9 in 2016.
10 The data used for this table is not publicly
available. Providers and researchers have access to
similar data via the home health public use files at
https://www.cms.gov/Research-Statistics-Data-and-
Systems/Statistics-Trends-and-Reports/MedicareProvider-Charge-Data/HHA.html and through the
CMS program statistics Web site at: https://
www.cms.gov/Research-Statistics-Data-and-
Systems/Statistics-Trends-and-Reports/
CMSProgramStatistics/.
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average visits in 2009 to 1.5 visits in
2016. The results of the home health
study required by section 3131(d) of the
Affordable Care Act suggest 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.11 The home health study
results seem to be consistent with the
recent trend in the decreased number of
visits per episode of care driven by
decreases in skilled nursing and home
health aide services evident in Figures
2 and 3.
11 The Report to Congress on the Home Health
Study required by Section 3131(d) is available at
https://www.cms.gov/Medicare/Medicare-Fee-for-
Service-Payment/HomeHealthPPS/Downloads/HHReport-to-Congress.pdf.
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Figure 3 displays the average number
of visits by discipline type for a 60-day
episode of care and shows that the
number of therapy visits per 60-day
episode of care has increased steadily.
However, the number of skilled nursing
visits has decreased from 10.7 in 2009
to 8.7 in 2016. The number of home
health aide visits has decreased from 5.6
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As part of our monitoring efforts, we
also examined the trends in episode
timing and service use over time. The
first and second episodes are considered
‘‘early’’ episodes, while third and later
episodes are considered ‘‘late’’ episodes.
Specifically, we examined the
percentage of early episodes with 0 to
19 therapy visits, late episodes with 0 to
19 therapy visits, and episodes with 20+
therapy visits from CY 2008 to CY 2016.
In CY 2008, we implemented
refinements to the HH PPS case-mix
system. As part of those refinements, we
added additional therapy thresholds
and differentiated between early and
late episodes for those episodes with
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less than 20+ therapy visits. When the
case-mix system first differentiated
payments between early and late
episodes of care, late episodes of care
tended to have higher case-mix weights
compared to early episodes of care.
Table 4 shows that while there was a
substantial increase in the number of
late episodes between 2008 and 2009 (8
percentage points), since 2011 the
number of late episodes as a percentage
of total episodes has decreased over
time. In 2015, the case-mix weights for
the third and later episodes of care with
0 to 19 therapy visits decreased as a
result of the CY 2015 recalibration of the
case-mix weights. The recalibration of
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the HH PPS case-mix weights, beginning
in CY 2015, does not seem to have
substantially impacted the percentage of
early versus late episodes of care.
The case-mix weights for episodes
with 20+ therapy visits are not
determined based on the timing of the
episode of care. The percentage of
episodes with 20+ therapy visits
increased from 4.6 percent in CY 2008
to 7.0 percent in CY 2016. The increase
in the percentage of episodes with 20+
therapy visits is consistent with the
overall observed increase in therapy
visits provided during a 60-day episode
of care (see Figure 3).
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35281
TABLE 4—HOME HEALTH EPISODES BY EPISODE TIMING, CY 2008 THROUGH CY 2016
Year
2008
2009
2010
2011
2012
2013
2014
2015
2016
All episodes
.............................
.............................
.............................
.............................
.............................
.............................
.............................
.............................
.............................
Number of
early episodes
(excluding episodes with
20+ therapy
visits)
% of early episodes
(excluding episodes with
20+ therapy
visits)
Number of late
episodes
(excluding episodes with
20+ therapy
visits)
% of late episodes
(excluding episodes with
20+ therapy
visits)
3,571,619
3,701,652
3,872,504
3,912,982
3,955,207
4,023,486
3,980,151
4,008,279
3,802,254
65.9
56.7
56.3
57.1
58.4
59.8
60.2
60.3
60.4
1,600,587
2,456,308
2,586,493
2,564,859
2,458,734
2,347,420
2,263,638
2,205,052
2,053,972
29.5
37.6
37.6
37.4
36.3
34.9
34.2
33.2
32.6
5,423,037
6,530,200
6,877,598
6,857,885
6,767,576
6,733,146
6,616,875
6,644,922
6,294,232
Number of
episodes
with 20+
therapy
visits
% of
episodes
with 20+
therapy
visits
250,831
372,240
418,601
380,044
353,635
362,240
373,086
431,591
438,006
4.6
5.7
6.1
5.5
5.2
5.4
5.6
6.5
7.0
SOURCE: National claims history (NCH) data obtained from Chronic Condition Warehouse (CCW)—Accessed on March 21, 2017.
NOTE(S): Only episodes with a through date in the year specified are included. Episodes with a claim frequency code equal to ‘‘0’’ (‘‘Non-payment/zero claims’’) and ‘‘2’’ (‘‘Interim—first claim’’) are excluded.
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We also examined trends in
admission source for home health
episodes over time. Specifically, we
examined the admission source for the
‘‘first or only’’ episodes of care (first
episodes in a sequence of adjacent
episodes of care or the only episode of
care) from CY 2008 through CY 2016
(Figure 4). The percentage of first or
only episodes with an acute admission
source, defined as episodes with an
inpatient hospital stay within the 14
days prior to a home health episode, has
decreased from 38.6 percent in CY 2008
to 33.9 percent in CY 2016. The
percentage of first or only episodes with
a post-acute admission source, defined
as episodes which had a stay at a skilled
nursing facility (SNF), inpatient
rehabilitation facility (IRF), or long term
care hospital (LTCH) within 14 days
prior to the home health episode,
slightly increased from 16.5 percent in
CY 2008 to 17.5 percent in CY 2016.
The percentage of first or only episodes
with a community admission source,
defined as episodes which did not have
an acute or post-acute stay in the 14
days prior to the home health episode,
increased from 37.4 percent in CY 2008
to 42.6 percent in CY 2016. Our findings
on the trends in admission source are
consistent with MedPAC’s as outlined
in their 2015 Report to the Congress.12
MedPAC examined admission source
trends from 2002 up through 2013 and
concluded that ‘‘there has been
tremendous growth in the use of home
health for patients residing in the
community, episodes not preceded by a
prior hospitalization. The high rates of
volume growth for these types of
episodes, which have more than
doubled since 2001, suggest there is
significant potential for overuse,
particularly since Medicare does not
currently require any cost sharing for
home health care.’’
12 Medicare Payment Advisory Commission
(MedPAC). ‘‘Home Health Care Services.’’ Report to
the Congress: Medicare Payment Policy.
Washington, DC, March 2015. P. 214. Accessed on
3/28/2017 at https://www.medpac.gov/docs/default-
source/reports/chapter-9-home-health-careservices-march-2015-report-.pdf?sfvrsn=0.
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We will continue to monitor for
potential impacts due to the rebasing
adjustments required by section 3131(a)
of the Affordable Care Act and other
policy changes in the future.
Independent effects of any one policy
may be difficult to discern in years
where multiple policy changes occur in
any given year.
B. Proposed CY 2018 HH PPS Case-Mix
Weights
In the CY 2015 HH PPS final rule (79
FR 66072), we finalized a policy to
annually recalibrate the HH PPS casemix weights—adjusting the weights
relative to one another—using the most
current, complete data available. To
recalibrate the HH PPS case-mix weights
for CY 2018, we will use the same
methodology finalized in the CY 2008
HH PPS final rule (72 FR 49762), the CY
2012 HH PPS final rule (76 FR 68526),
and the CY 2015 HH PPS final rule (79
FR 66032). Annual recalibration of the
HH PPS case-mix weights ensures that
the case-mix weights reflect, as
accurately as possible, current home
health resource use and changes in
utilization patterns.
To generate the proposed CY 2018 HH
PPS case-mix weights, we used CY 2016
home health claims data (as of March
17, 2017) with linked OASIS data.
These data are the most current and
complete data available at this time. We
will use CY 2016 home health claims
data (as of June 30, 2017 or later) with
linked OASIS data to generate the CY
2018 HH PPS case-mix weights in the
CY 2018 HH PPS final rule. The process
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 2015 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 2016 home health
claims data, are shown in Table 5. 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 5.—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
4
........................
........................
........................
........................
........................
4
........................
1
2
3
........................
16
........................
........................
1
1
........................
10
1 ....................
2 ....................
3 ....................
4 ....................
5 ....................
6 ....................
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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.
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CLINICAL DIMENSION
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TABLE 5.—CASE-MIX ADJUSTMENT VARIABLES AND SCORES—Continued
7 ....................
8 ....................
9 ....................
10 ..................
11 ..................
12 ..................
13 ..................
14 ..................
15 ..................
16 ..................
17 ..................
18 ..................
19 ..................
20 ..................
21 ..................
22 ..................
23 ..................
24 ..................
25 ..................
26 ..................
27 ..................
28 ..................
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29 ..................
30 ..................
31 ..................
32
33
34
35
36
37
38
39
40
41
42
43
44
45
..................
..................
..................
..................
..................
..................
..................
..................
..................
..................
..................
..................
..................
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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.
Primary Diagnosis = Skin 1–Traumatic wounds, burns, and
post-operative complications.
Other Diagnosis = Skin 1—Traumatic wounds, burns, postoperative 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 ...........................................................
M1311 = 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 ........................
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6
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7
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2
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........................
1
3
........................
2
2
9
6
9
........................
4
........................
4
2
4
1
4
3
........................
9
2
2
........................
4
........................
........................
........................
........................
........................
3
7
5
10
7
1
7
........................
3
........................
3
7
........................
........................
........................
........................
........................
........................
........................
........................
........................
........................
2
........................
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1
........................
3
17
6
17
6
13
8
13
2
........................
........................
........................
2
16
8
17
2
........................
........................
17
17
15
........................
........................
5
17
12
15
........................
........................
3
4
4
8
4
7
2
........................
1
........................
4
........................
15
........................
........................
6
19
31
13
17
7
6
1
3
11
........................
........................
........................
2
4
7
10
7
9
6
5
........................
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........................
8
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25
13
17
13
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8
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TABLE 5—CASE-MIX ADJUSTMENT VARIABLES AND SCORES—Continued
FUNCTIONAL DIMENSION
46 ..................
47
48
49
50
51
..................
..................
..................
..................
..................
M1810
3.
M1830
M1840
M1850
M1860
M1860
or M1820 (Dressing upper or lower body) = 1, 2, or
1
........................
........................
........................
(Bathing) = 2 or more ...............................................
(Toilet transferring) = 2 or more ...............................
(Transferring) = 2 or more ........................................
(Ambulation) = 1, 2 or 3 ...........................................
(Ambulation) = 4 or more .........................................
6
........................
3
7
8
5
1
1
........................
9
5
........................
2
4
6
2
........................
........................
........................
7
Source: CY 2016 Medicare claims data for episodes ending on or before December 31, 2016 (as of December 31, 2016) for which we had a
linked OASIS assessment. LUPA episodes, outlier episodes, and episodes with 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.gov/Medicare/Medicare-Fee-for-Service-Payment/HomeHealthPPS/coding_billing.html for
definitions of primary and secondary diagnoses.
In updating the four-equation model
for CY 2018, using 2016 home health
claims data (the last update to the fourequation model for CY 2017 used CY
2015 home health claims data), there
were few changes to the point values for
the variables in the four-equation
model. These relatively minor changes
reflect the change in the relationship
between the grouper variables and
resource use between CY 2015 and CY
2016. The CY 2018 four-equation model
resulted in 120 point-giving variables
being used in the model (as compared
to the 124 variables for the CY 2017
recalibration). There were 8 variables
that were added to the model and 12
variables that were dropped from the
model due to the absence of additional
resources associated with the variable.
Of the variables that were in both the
four-equation model for CY 2017 and
the four-equation model for CY 2018,
the points for 14 variables increased in
the CY 2018 four-equation model and
the points for 48 variables decreased in
the CY 2018 4-equation model. There
were 50 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 2018 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.13 Also, we looked
at the average resource use associated
with each clinical and functional score
and used that as a guide for setting our
thresholds. We grouped scores with
similar average resource use within the
same level (even if it meant that more
or less than a third of episodes were
placed within a level). The new
thresholds, based off the CY 2018 fourequation model points are shown in
Table 6.
TABLE 6—CY 2018 CLINICAL AND FUNCTIONAL THRESHOLDS
1st and 2nd episodes
3rd+ episodes
All Episodes
0 to 13
therapy visits
14 to 19
therapy visits
0 to 13
therapy visits
14 to 19
therapy visits
20+ therapy
visits
Grouping Step
1
2
3
4
5
Equations used to calculate points
(see Table B1)
1
2
3
4
(2&4)
0 to 1 ................
2 to 3 ................
4+ .....................
0 to 13 ..............
14 .....................
15+ ...................
0 to 1 ................
2 to 7 ................
8+ .....................
0 to 7 ................
8 to 15 ..............
16+ ...................
0 to 1 ................
2 .......................
3+ .....................
0 to 6 ................
7 to 10 ..............
11+ ...................
0 to 1 ................
2 to 9 ................
10+ ...................
0 to 2 ................
3 to 7 ................
8+ .....................
Dimension
Severity
Level
Clinical .............................................
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Functional ........................................
C1
C2
C3
F1
F2
F3
............
............
............
............
............
............
13 For Step 1, 45.4% of episodes were in the
medium functional level (All with score 14).
For Step 2.1, 87.3% of episodes were in the low
functional level (Most with scores 5 to 7).
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For Step 2.2, 81.9% of episodes were in the low
functional level (Most with score 1).
For Step 3, 46.4% of episodes were in the
medium functional level (Most with score 9).
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0 to
4 to
17+
0 to
3 to
7+
3
16
2
6
For Step 4, 48.6% of episodes were in the
medium functional level (Most with score 5 or 6).
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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 7 shows
the regression coefficients for the
35285
variables in the payment regression
model updated with CY 2016 home
health claims data. The R-squared value
for the payment regression model is
0.5073 (an increase from 0.4919 for the
CY 2017 recalibration).
TABLE 7—PAYMENT REGRESSION MODEL
Payment
regression
from 4equation
model for
CY2018
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 ...............................................................................................................................................................................................
$24.35
54.10
71.10
104.74
47.79
133.50
30.46
55.93
39.93
192.15
17.99
53.34
14.03
92.83
56.27
86.76
78.75
260.68
25.95
58.66
497.79
508.40
–67.30
883.46
382.25
mstockstill on DSK30JT082PROD with PROPOSALS2
Source: CY 2016 Medicare claims data for episodes ending on or before December 31, 2016 (as of March 17, 2017) for which we had a linked
OASIS assessment.
Step 4: We use the coefficients from
the payment regression model to predict
each episode’s wage-weighted minutes
of care (resource use). We then divide
these predicted values by the mean of
the dependent variable (that is, the
average wage-weighted minutes of care
across all episodes used in the payment
regression). This division constructs the
weight for each episode, which is
simply the ratio of the episode’s
predicted wage-weighted minutes of
care divided by the average wageweighted minutes of care in the sample.
Each episode is then aggregated into one
of the 153 home health resource groups
(HHRGs) and the ‘‘raw’’ weight for each
HHRG was calculated as the average of
the episode weights within the HHRG.
Step 5: The raw weights associated
with 0 to 5 therapy visits are then
increased by 3.75 percent, the weights
associated with 14–15 therapy visits are
decreased by 2.5 percent, and the
weights associated with 20+ therapy
visits are decreased by 5 percent. These
adjustments to the case-mix weights
were finalized in the CY 2012 HH PPS
final rule (76 FR 68557) and were done
to address MedPAC’s concerns that the
HH PPS overvalues therapy episodes
and undervalues non-therapy episodes
and to better align the case-mix weights
with episode costs estimated from cost
report data.14
Step 6: After the adjustments in Step
5 are applied to the raw weights, the
weights are further adjusted to create an
increase in the payment weights for the
therapy visit steps between the therapy
thresholds. Weights with the same
clinical severity level, functional
severity level, and early/later episode
status were grouped together. Then
within those groups, the weights for
each therapy step between thresholds
are gradually increased. We do this by
interpolating between the main
thresholds on the model (from 0–5 to
14–15 therapy visits, and from 14–15 to
20+ therapy visits). We use a linear
model to implement the interpolation so
the payment weight increase for each
step between the thresholds (such as the
increase between 0–5 therapy visits and
6 therapy visits and the increase
between 6 therapy visits and 7–9
therapy visits) are constant. This
interpolation is identical to the process
finalized in the CY 2012 HH PPS final
rule (76 FR 68555).
Step 7: The interpolated weights are
then adjusted so that the average case-
14 Medicare Payment Advisory Commission
(MedPAC), Report to the Congress: Medicare
Payment Policy. March 2011, P. 176.
15 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.
VerDate Sep<11>2014
22:22 Jul 27, 2017
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28JYP2
35286
Federal Register / Vol. 82, No. 144 / Friday, July 28, 2017 / Proposed Rules
mix for the weights is equal to 1.0000.15
This last step creates the proposed CY
2018 case-mix weights shown in Table
8.
TABLE 8—PROPOSED CY 2018 CASE-MIX PAYMENT WEIGHTS
mstockstill on DSK30JT082PROD with PROPOSALS2
Pay group
10111
10112
10113
10114
10115
10121
10122
10123
10124
10125
10131
10132
10133
10134
10135
10211
10212
10213
10214
10215
10221
10222
10223
10224
10225
10231
10232
10233
10234
10235
10311
10312
10313
10314
10315
10321
10322
10323
10324
10325
10331
10332
10333
10334
10335
21111
21112
21113
21121
21122
21123
21131
21132
21133
21211
21212
21213
21221
21222
21223
21231
21232
Description
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
1st
1st
1st
1st
1st
1st
1st
1st
1st
1st
1st
1st
1st
1st
1st
1st
1st
1st
1st
1st
1st
1st
1st
1st
1st
1st
1st
1st
1st
1st
1st
1st
1st
1st
1st
1st
1st
1st
1st
1st
1st
1st
1st
1st
1st
1st
1st
1st
1st
1st
1st
1st
1st
1st
1st
1st
1st
1st
1st
1st
1st
1st
and
and
and
and
and
and
and
and
and
and
and
and
and
and
and
and
and
and
and
and
and
and
and
and
and
and
and
and
and
and
and
and
and
and
and
and
and
and
and
and
and
and
and
and
and
and
and
and
and
and
and
and
and
and
and
and
and
and
and
and
and
and
2nd
2nd
2nd
2nd
2nd
2nd
2nd
2nd
2nd
2nd
2nd
2nd
2nd
2nd
2nd
2nd
2nd
2nd
2nd
2nd
2nd
2nd
2nd
2nd
2nd
2nd
2nd
2nd
2nd
2nd
2nd
2nd
2nd
2nd
2nd
2nd
2nd
2nd
2nd
2nd
2nd
2nd
2nd
2nd
2nd
2nd
2nd
2nd
2nd
2nd
2nd
2nd
2nd
2nd
2nd
2nd
2nd
2nd
2nd
2nd
2nd
2nd
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
0 to 5 Therapy Visits ...........................................................................
6 Therapy Visits ..................................................................................
7 to 9 Therapy Visits ...........................................................................
10 Therapy Visits ................................................................................
11 to 13 Therapy Visits .......................................................................
0 to 5 Therapy Visits ...........................................................................
6 Therapy Visits ..................................................................................
7 to 9 Therapy Visits ...........................................................................
10 Therapy Visits ................................................................................
11 to 13 Therapy Visits .......................................................................
0 to 5 Therapy Visits ...........................................................................
6 Therapy Visits ..................................................................................
7 to 9 Therapy Visits ...........................................................................
10 Therapy Visits ................................................................................
11 to 13 Therapy Visits .......................................................................
0 to 5 Therapy Visits ...........................................................................
6 Therapy Visits ..................................................................................
7 to 9 Therapy Visits ...........................................................................
10 Therapy Visits ................................................................................
11 to 13 Therapy Visits .......................................................................
0 to 5 Therapy Visits ...........................................................................
6 Therapy Visits ..................................................................................
7 to 9 Therapy Visits ...........................................................................
10 Therapy Visits ................................................................................
11 to 13 Therapy Visits .......................................................................
0 to 5 Therapy Visits ...........................................................................
6 Therapy Visits ..................................................................................
7 to 9 Therapy Visits ...........................................................................
10 Therapy Visits ................................................................................
11 to 13 Therapy Visits .......................................................................
0 to 5 Therapy Visits ...........................................................................
6 Therapy Visits ..................................................................................
7 to 9 Therapy Visits ...........................................................................
10 Therapy Visits ................................................................................
11 to 13 Therapy Visits .......................................................................
0 to 5 Therapy Visits ...........................................................................
6 Therapy Visits ..................................................................................
7 to 9 Therapy Visits ...........................................................................
10 Therapy Visits ................................................................................
11 to 13 Therapy Visits .......................................................................
0 to 5 Therapy Visits ...........................................................................
6 Therapy Visits ..................................................................................
7 to 9 Therapy Visits ...........................................................................
10 Therapy Visits ................................................................................
11 to 13 Therapy Visits .......................................................................
14 to 15 Therapy Visits .......................................................................
16 to 17 Therapy Visits .......................................................................
18 to 19 Therapy Visits .......................................................................
14 to 15 Therapy Visits .......................................................................
16 to 17 Therapy Visits .......................................................................
18 to 19 Therapy Visits .......................................................................
14 to 15 Therapy Visits .......................................................................
16 to 17 Therapy Visits .......................................................................
18 to 19 Therapy Visits .......................................................................
14 to 15 Therapy Visits .......................................................................
16 to 17 Therapy Visits .......................................................................
18 to 19 Therapy Visits .......................................................................
14 to 15 Therapy Visits .......................................................................
16 to 17 Therapy Visits .......................................................................
18 to 19 Therapy Visits .......................................................................
14 to 15 Therapy Visits .......................................................................
16 to 17 Therapy Visits .......................................................................
15 When computing the average, we compute a
weighted average, assigning a value of one to each
VerDate Sep<11>2014
Clinical and
functional
levels
(1 = low;
2 = medium;
3 = high)
22:22 Jul 27, 2017
Jkt 241001
normal episode and a value equal to the episode
length divided by 60 for PEPs.
PO 00000
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E:\FR\FM\28JYP2.SGM
28JYP2
C1F1S1
C1F1S2
C1F1S3
C1F1S4
C1F1S5
C1F2S1
C1F2S2
C1F2S3
C1F2S4
C1F2S5
C1F3S1
C1F3S2
C1F3S3
C1F3S4
C1F3S5
C2F1S1
C2F1S2
C2F1S3
C2F1S4
C2F1S5
C2F2S1
C2F2S2
C2F2S3
C2F2S4
C2F2S5
C2F3S1
C2F3S2
C2F3S3
C2F3S4
C2F3S5
C3F1S1
C3F1S2
C3F1S3
C3F1S4
C3F1S5
C3F2S1
C3F2S2
C3F2S3
C3F2S4
C3F2S5
C3F3S1
C3F3S2
C3F3S3
C3F3S4
C3F3S5
C1F1S1
C1F1S2
C1F1S3
C1F2S1
C1F2S2
C1F2S3
C1F3S1
C1F3S2
C1F3S3
C2F1S1
C2F1S2
C2F1S3
C2F2S1
C2F2S2
C2F2S3
C2F3S1
C2F3S2
Proposed
CY 2018
weight
0.5617
0.6925
0.8232
0.9539
1.0846
0.6662
0.7845
0.9027
1.0209
1.1392
0.7157
0.8311
0.9464
1.0618
1.1772
0.5975
0.7343
0.8711
1.0078
1.1446
0.7020
0.8263
0.9506
1.0749
1.1991
0.7514
0.8729
0.9943
1.1157
1.2372
0.6412
0.7929
0.9446
1.0963
1.2480
0.7457
0.8850
1.0242
1.1634
1.3026
0.7952
0.9315
1.0679
1.2043
1.3406
1.2154
1.3780
1.5406
1.2574
1.4176
1.5779
1.2926
1.4558
1.6189
1.2814
1.4573
1.6332
1.3234
1.4970
1.6705
1.3586
1.5351
Federal Register / Vol. 82, No. 144 / Friday, July 28, 2017 / Proposed Rules
35287
TABLE 8—PROPOSED CY 2018 CASE-MIX PAYMENT WEIGHTS—Continued
mstockstill on DSK30JT082PROD with PROPOSALS2
Pay group
21233
21311
21312
21313
21321
21322
21323
21331
21332
21333
22111
22112
22113
22121
22122
22123
22131
22132
22133
22211
22212
22213
22221
22222
22223
22231
22232
22233
22311
22312
22313
22321
22322
22323
22331
22332
22333
30111
30112
30113
30114
30115
30121
30122
30123
30124
30125
30131
30132
30133
30134
30135
30211
30212
30213
30214
30215
30221
30222
30223
30224
30225
30231
30232
30233
30234
30235
30311
Description
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
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................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
VerDate Sep<11>2014
Clinical and
functional
levels
(1 = low;
2 = medium;
3 = high)
1st and 2nd Episodes, 18 to 19 Therapy Visits .......................................................................
1st and 2nd Episodes, 14 to 15 Therapy Visits .......................................................................
1st and 2nd Episodes, 16 to 17 Therapy Visits .......................................................................
1st and 2nd Episodes, 18 to 19 Therapy Visits .......................................................................
1st and 2nd Episodes, 14 to 15 Therapy Visits .......................................................................
1st and 2nd Episodes, 16 to 17 Therapy Visits .......................................................................
1st and 2nd Episodes, 18 to 19 Therapy Visits .......................................................................
1st and 2nd Episodes, 14 to 15 Therapy Visits .......................................................................
1st and 2nd Episodes, 16 to 17 Therapy Visits .......................................................................
1st and 2nd Episodes, 18 to 19 Therapy Visits .......................................................................
3rd+ Episodes, 14 to 15 Therapy Visits ..................................................................................
3rd+ Episodes, 16 to 17 Therapy Visits ..................................................................................
3rd+ Episodes, 18 to 19 Therapy Visits ..................................................................................
3rd+ Episodes, 14 to 15 Therapy Visits ..................................................................................
3rd+ Episodes, 16 to 17 Therapy Visits ..................................................................................
3rd+ Episodes, 18 to 19 Therapy Visits ..................................................................................
3rd+ Episodes, 14 to 15 Therapy Visits ..................................................................................
3rd+ Episodes, 16 to 17 Therapy Visits ..................................................................................
3rd+ Episodes, 18 to 19 Therapy Visits ..................................................................................
3rd+ Episodes, 14 to 15 Therapy Visits ..................................................................................
3rd+ Episodes, 16 to 17 Therapy Visits ..................................................................................
3rd+ Episodes, 18 to 19 Therapy Visits ..................................................................................
3rd+ Episodes, 14 to 15 Therapy Visits ..................................................................................
3rd+ Episodes, 16 to 17 Therapy Visits ..................................................................................
3rd+ Episodes, 18 to 19 Therapy Visits ..................................................................................
3rd+ Episodes, 14 to 15 Therapy Visits ..................................................................................
3rd+ Episodes, 16 to 17 Therapy Visits ..................................................................................
3rd+ Episodes, 18 to 19 Therapy Visits ..................................................................................
3rd+ Episodes, 14 to 15 Therapy Visits ..................................................................................
3rd+ Episodes, 16 to 17 Therapy Visits ..................................................................................
3rd+ Episodes, 18 to 19 Therapy Visits ..................................................................................
3rd+ Episodes, 14 to 15 Therapy Visits ..................................................................................
3rd+ Episodes, 16 to 17 Therapy Visits ..................................................................................
3rd+ Episodes, 18 to 19 Therapy Visits ..................................................................................
3rd+ Episodes, 14 to 15 Therapy Visits ..................................................................................
3rd+ Episodes, 16 to 17 Therapy Visits ..................................................................................
3rd+ Episodes, 18 to 19 Therapy Visits ..................................................................................
3rd+ Episodes, 0 to 5 Therapy Visits ......................................................................................
3rd+ Episodes, 6 Therapy Visits ..............................................................................................
3rd+ Episodes, 7 to 9 Therapy Visits ......................................................................................
3rd+ Episodes, 10 Therapy Visits ............................................................................................
3rd+ Episodes, 11 to 13 Therapy Visits ..................................................................................
3rd+ Episodes, 0 to 5 Therapy Visits ......................................................................................
3rd+ Episodes, 6 Therapy Visits ..............................................................................................
3rd+ Episodes, 7 to 9 Therapy Visits ......................................................................................
3rd+ Episodes, 10 Therapy Visits ............................................................................................
3rd+ Episodes, 11 to 13 Therapy Visits ..................................................................................
3rd+ Episodes, 0 to 5 Therapy Visits ......................................................................................
3rd+ Episodes, 6 Therapy Visits ..............................................................................................
3rd+ Episodes, 7 to 9 Therapy Visits ......................................................................................
3rd+ Episodes, 10 Therapy Visits ............................................................................................
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 ......................................................................................
22:22 Jul 27, 2017
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E:\FR\FM\28JYP2.SGM
28JYP2
C2F3S3
C3F1S1
C3F1S2
C3F1S3
C3F2S1
C3F2S2
C3F2S3
C3F3S1
C3F3S2
C3F3S3
C1F1S1
C1F1S2
C1F1S3
C1F2S1
C1F2S2
C1F2S3
C1F3S1
C1F3S2
C1F3S3
C2F1S1
C2F1S2
C2F1S3
C2F2S1
C2F2S2
C2F2S3
C2F3S1
C2F3S2
C2F3S3
C3F1S1
C3F1S2
C3F1S3
C3F2S1
C3F2S2
C3F2S3
C3F3S1
C3F3S2
C3F3S3
C1F1S1
C1F1S2
C1F1S3
C1F1S4
C1F1S5
C1F2S1
C1F2S2
C1F2S3
C1F2S4
C1F2S5
C1F3S1
C1F3S2
C1F3S3
C1F3S4
C1F3S5
C2F1S1
C2F1S2
C2F1S3
C2F1S4
C2F1S5
C2F2S1
C2F2S2
C2F2S3
C2F2S4
C2F2S5
C2F3S1
C2F3S2
C2F3S3
C2F3S4
C2F3S5
C3F1S1
Proposed
CY 2018
weight
1.7116
1.3997
1.6178
1.8359
1.4418
1.6575
1.8732
1.4770
1.6956
1.9142
1.2300
1.3877
1.5455
1.2549
1.4159
1.5770
1.3037
1.4632
1.6226
1.2852
1.4598
1.6345
1.3100
1.4880
1.6660
1.3588
1.5352
1.7117
1.4954
1.6816
1.8678
1.5202
1.7098
1.8993
1.5690
1.7570
1.9449
0.4628
0.6163
0.7697
0.9232
1.0766
0.5455
0.6874
0.8293
0.9711
1.1130
0.5903
0.7330
0.8757
1.0183
1.1610
0.4835
0.6438
0.8041
0.9645
1.1248
0.5662
0.7149
0.8637
1.0125
1.1612
0.6110
0.7605
0.9101
1.0597
1.2093
0.5993
35288
Federal Register / Vol. 82, No. 144 / Friday, July 28, 2017 / Proposed Rules
TABLE 8—PROPOSED CY 2018 CASE-MIX PAYMENT WEIGHTS—Continued
Pay group
30312
30313
30314
30315
30321
30322
30323
30324
30325
30331
30332
30333
30334
30335
40111
40121
40131
40211
40221
40231
40311
40321
40331
Description
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
3rd+ Episodes, 6 Therapy Visits ..............................................................................................
3rd+ Episodes, 7 to 9 Therapy Visits ......................................................................................
3rd+ Episodes, 10 Therapy Visits ............................................................................................
3rd+ Episodes, 11 to 13 Therapy Visits ..................................................................................
3rd+ Episodes, 0 to 5 Therapy Visits ......................................................................................
3rd+ Episodes, 6 Therapy Visits ..............................................................................................
3rd+ Episodes, 7 to 9 Therapy Visits ......................................................................................
3rd+ Episodes, 10 Therapy Visits ............................................................................................
3rd+ Episodes, 11 to 13 Therapy Visits ..................................................................................
3rd+ Episodes, 0 to 5 Therapy Visits ......................................................................................
3rd+ Episodes, 6 Therapy Visits ..............................................................................................
3rd+ Episodes, 7 to 9 Therapy Visits ......................................................................................
3rd+ Episodes, 10 Therapy Visits ............................................................................................
3rd+ Episodes, 11 to 13 Therapy Visits ..................................................................................
All Episodes, 20+ Therapy Visits .............................................................................................
All Episodes, 20+ Therapy Visits .............................................................................................
All Episodes, 20+ Therapy Visits .............................................................................................
All Episodes, 20+ Therapy Visits .............................................................................................
All Episodes, 20+ Therapy Visits .............................................................................................
All Episodes, 20+ Therapy Visits .............................................................................................
All Episodes, 20+ Therapy Visits .............................................................................................
All Episodes, 20+ Therapy Visits .............................................................................................
All Episodes, 20+ Therapy Visits .............................................................................................
To ensure the changes to the HH PPS
case-mix weights are implemented in a
budget neutral manner, we then apply a
case-mix budget neutrality factor to the
proposed CY 2018 national,
standardized 60-day episode payment
rate (see section III.C.3. of this proposed
rule). The case-mix budget neutrality
factor is calculated as the ratio of total
payments when the CY 2018 HH PPS
case-mix weights (developed using CY
2016 home health claims data) are
applied to CY 2016 utilization (claims)
data to total payments when CY 2017
HH PPS case-mix weights (developed
using CY 2015 home health claims data)
are applied to CY 2016 utilization data.
This produces a case-mix budget
neutrality factor for CY 2018 of 1.0159.
C. Proposed CY 2018 Home Health
Payment Rate Update
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1. Proposed CY 2018 Home Health
Market Basket Update
Section 1895(b)(3)(B) of the Act
requires that the standard prospective
payment amounts for CY 2018 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
through 67090).
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Section 1895(b)(3)(B)(vi) of the Act,
requires that, in CY 2015 (and in
subsequent calendar years, except CY
2018 (under section 411(c) of the
Medicare Access and CHIP
Reauthorization Act of 2015 (MACRA)
(Pub. L. 114–10, enacted April 16,
2015)), 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. Section
1886(b)(3)(B)(xi)(II) of the Act defines
the productivity adjustment 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.
Prior to the enactment of the MACRA,
which amended section 1895(b)(3)(B) of
the Act, the proposed home health
update percentage for CY 2018 would
have been based on the estimated home
health market basket update of 2.7
percent (based on IHS Global Insight
Inc.’s first-quarter 2017 forecast with
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Proposed
CY 2018
weight
0.7785
0.9577
1.1369
1.3162
0.6820
0.8496
1.0173
1.1849
1.3526
0.7268
0.8952
1.0637
1.2321
1.4006
1.7032
1.7381
1.7821
1.8091
1.8440
1.8881
2.0539
2.0889
2.1329
historical data through fourth-quarter
2016). Due to the requirements specified
at section 1895(b)(3)(B)(vi) of the Act
prior to the enactment of MACRA, the
estimated CY 2018 home health market
basket update of 2.7 percent would have
been reduced by a MFP adjustment as
mandated by the Affordable Care Act
(currently estimated to be 0.5 percentage
point for CY 2018). In effect, the
proposed home health payment update
percentage for CY 2018 would have
been 2.2 percent. However, section
411(c) of the MACRA amended section
1895(b)(3)(B) of the Act, such that for
home health payments for CY 2018, the
market basket percentage increase is
required to be 1 percent.
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 2018, the home
health payment update would be -1
percent (1 percent minus 2 percentage
points).
2. Proposed CY 2018 Home Health Wage
Index
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
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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 2018, 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 2018, the
updated wage data are for hospital cost
reporting periods beginning on or after
October 1, 2013, and before October 1,
2014 (FY 2014 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).
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
2018 HH PPS wage index, we propose
to continue to use the same
methodology discussed in the CY 2007
HH PPS final rule (71 FR 65884) to
address those geographic areas in which
there are no inpatient hospitals. For
rural areas that do not have inpatient
hospitals, we would use the average
wage index from all contiguous Core
Based Statistical Areas (CBSAs) as a
reasonable proxy. Currently, the only
rural area without a hospital from which
hospital wage data could be derived is
Puerto Rico. However, 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 2018, the only urban
area without inpatient hospital wage
data is Hinesville, GA (CBSA 25980).
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
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delineation of these areas. In the CY
2015 HH PPS final rule (79 FR 66085
through 66087), we adopted the OMB’s
new area delineations using a 1-year
transition. The most recent bulletin (No.
15–01) concerning the revised
delineations was published by the OMB
on July 15, 2015.
The proposed CY 2018 wage index is
available on the CMS Web site at https://
www.cms.gov/Medicare/Medicare-Feefor-Service-Payment/HomeHealthPPS/
Home-Health-Prospective-PaymentSystem-Regulations-and-Notices.html.
3. Proposed CY 2018 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 § 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 2018 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.B of this rule. The following
are the steps we take to compute the
case-mix and wage-adjusted 60-day
episode rate:
(1) Multiply the national 60-day
episode rate by the patient’s applicable
case-mix weight.
(2) Divide the case-mix adjusted
amount into a labor (78.535 percent)
and a non-labor portion (21.465
percent).
(3) Multiply the labor portion by the
applicable wage index based on the site
of service of the beneficiary.
(4) Add the wage-adjusted portion to
the non-labor portion, yielding the casemix and wage adjusted 60-day episode
rate, subject to any additional applicable
adjustments.
In accordance with section
1895(b)(3)(B) of the Act, this document
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proposes 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 2
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 2018 National,
Standardized 60-Day Episode Payment
Rate
Section 1895(3)(A)(i) of the Act
requires 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 2018
national, standardized 60-day episode
payment rate, we would apply a wage
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index budget neutrality factor; a casemix budget neutrality factor described
in section III.B. of this proposed rule; a
reduction of 0.97 percent to account for
nominal case-mix growth from 2012 to
2014, as finalized in the CY 2016 HH
PPS final rule (80 FR 68646); and the
home health payment update percentage
discussed in section III.C.1 of this
proposed rule.
To calculate the wage index budget
neutrality factor, we simulated total
payments for non-LUPA episodes using
the proposed CY 2018 wage index and
compared it to our simulation of total
payments for non-LUPA episodes using
the CY 2017 wage index. By dividing
the total payments for non-LUPA
episodes using the proposed CY 2018
wage index by the total payments for
non-LUPA episodes using the CY 2017
wage index, we obtain a wage index
budget neutrality factor of 1.0001. We
would apply the wage index budget
neutrality factor of 1.0001 to the
calculation of the proposed CY 2018
national, standardized 60-day episode
rate.
As discussed in section III.B. of this
proposed rule, to ensure the changes to
the case-mix weights are implemented
in a budget neutral manner, we would
apply a case-mix weight budget
neutrality factor to the CY 2018
national, standardized 60-day episode
payment rate. The case-mix weight
budget neutrality factor is calculated as
the ratio of total payments when CY
2018 case-mix weights are applied to CY
2016 utilization (claims) data to total
payments when CY 2017 case-mix
weights are applied to CY 2016
utilization data. The case-mix budget
neutrality factor for CY 2018 would be
1.0159 as described in section III.B of
this proposed rule.
Next, we would apply a reduction of
0.97 percent to the national,
standardized 60-day payment rate for
CY 2018 to account for nominal casemix growth between CY 2012 and CY
2014. Lastly, we would update the
proposed payment rates by the proposed
CY 2018 home health payment update
percentage of 1 percent as mandated by
section 1895(b)(3)(B)(iii) of the Act. The
proposed CY 2018 national,
standardized 60-day episode payment
rate is calculated in Table 9.
TABLE 9—PROPOSED CY 2018 60-DAY NATIONAL, STANDARDIZED 60-DAY EPISODE PAYMENT AMOUNT
CY 2017 national, standardized 60-day
episode payment
Wage index
budget
neutrality
factor
Case-mix
weights
budget
neutrality
factor
Nominal
case-mix
growth
adjustment
(1–0.0097)
Proposed
CY 2018 HH
payment
update
Proposed
CY 2018
national,
standardized
60-day
episode
payment
$2,989.97 .............................................................................
× 1.0001
× 1.0159
× 0.9903
× 1.01
$3,038.43
The proposed CY 2018 national,
standardized 60-day episode payment
rate for an HHA that does not submit the
required quality data is updated by the
proposed CY 2018 home health
payment update of 1 percent minus 2
percentage points and is shown in Table
10.
TABLE 10—PROPOSED CY 2018 NATIONAL, STANDARDIZED 60-DAY EPISODE PAYMENT AMOUNT FOR HHAS THAT DO
NOT SUBMIT THE QUALITY DATA
CY 2017 national, standardized 60-day
episode payment
Wage index
budget
neutrality
factor
Case-mix
weights
budget
neutrality
factor
Nominal
case-mix
growth
adjustment
(1–0.0097)
Proposed
CY 2018 HH
payment
update minus
2 percentage
points
Proposed
CY 2018
national,
standardized
60-day episode payment
$2,989.97 .............................................................................
× 1.0001
× 1.0159
× 0.9903
× 0.99
$2,978.26
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c. Proposed CY 2018 National Per-Visit
Rates
The national per-visit rates are used to
pay LUPAs (episodes with four or fewer
visits) and are also used to compute
imputed costs in outlier calculations.
The per-visit rates are paid by type of
visit or HH discipline. The six HH
disciplines are as follows:
• Home health aide (HH aide);
• Medical Social Services (MSS);
• Occupational therapy (OT);
• Physical therapy (PT);
• Skilled nursing (SN); and
• Speech-language pathology (SLP).
To calculate the proposed CY 2018
national per-visit rates, we start with the
CY 2017 national per-visit rates. We
then apply a wage index budget
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neutrality factor to ensure budget
neutrality for LUPA per-visit payments.
We calculate the wage index budget
neutrality factor by simulating total
payments for LUPA episodes using the
proposed CY 2018 wage index and
comparing it to simulated total
payments for LUPA episodes using the
CY 2017 wage index. By dividing the
total payments for LUPA episodes using
the proposed CY 2018 wage index by
the total payments for LUPA episodes
using the CY 2017 wage index, we
obtain a wage index budget neutrality
factor of 1.0005. We would apply the
wage index budget neutrality factor of
1.0005 in order to calculate the CY 2018
national per-visit rates.
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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. Lastly, the per-visit rates for
each discipline are updated by the
proposed CY 2018 home health
payment update percentage of 1 percent.
The national per-visit rates are adjusted
by the wage index based on the site of
service of the beneficiary. The per-visit
payments for LUPAs are separate from
the LUPA add-on payment amount,
which is paid for episodes that occur as
the only episode or initial episode in a
sequence of adjacent episodes. The
proposed CY 2018 national per-visit
rates are shown in Tables 11 and 12.
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TABLE 11—PROPOSED CY 2018 NATIONAL PER-VISIT PAYMENT AMOUNTS FOR HHAS THAT DO SUBMIT THE REQUIRED
QUALITY DATA
Home Health Aide ...........................................................................................
Medical Social Services ...................................................................................
Occupational Therapy ......................................................................................
Physical Therapy .............................................................................................
Skilled Nursing .................................................................................................
Speech- Language Pathology .........................................................................
The proposed CY 2018 per-visit
payment rates for HHAs that do not
submit the required quality data are
Wage index
budget
neutrality
factor
CY 2017
per-visit
payment
HH discipline type
×
×
×
×
×
×
$64.23
227.36
156.11
155.05
141.84
168.52
updated by the proposed CY 2018 HH
payment update percentage of 1 percent
1.0005
1.0005
1.0005
1.0005
1.0005
1.0005
Proposed
CY 2018
HH payment
update
×
×
×
×
×
×
Proposed
CY 2018
per-visit
payment
1.01
1.01
1.01
1.01
1.01
1.01
$64.90
229.75
157.75
156.68
143.33
170.29
minus 2 percentage points and are
shown in Table 12.
TABLE 12—PROPOSED CY 2018 NATIONAL PER-VISIT PAYMENT AMOUNTS FOR HHAS THAT DO NOT SUBMIT THE
REQUIRED QUALITY DATA
HH discipline type
Home Health Aide ...........................................................................................
Medical Social Services ...................................................................................
Occupational Therapy ......................................................................................
Physical Therapy .............................................................................................
Skilled Nursing .................................................................................................
Speech- Language Pathology .........................................................................
d. Low-Utilization Payment Adjustment
(LUPA) Add-On Factors
LUPA episodes that occur as the only
episode or as an initial episode in a
sequence of adjacent episodes are
adjusted by applying an additional
amount to the LUPA payment before
adjusting for area wage differences. In
the CY 2014 HH PPS final rule, we
changed the methodology for
calculating the LUPA add-on amount by
finalizing the use of three LUPA add-on
factors: 1.8451 for SN; 1.6700 for PT;
and 1.6266 for SLP (78 FR 72306). We
multiply the per-visit payment amount
for the first SN, PT, or SLP visit in
LUPA episodes that occur as the only
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, in the case of HHAs that do
Wage index
budget
neutrality
factor
CY 2017
per-visit
rates
×
×
×
×
×
×
$64.23
227.36
156.11
155.05
141.84
168.52
1.0005
1.0005
1.0005
1.0005
1.0005
1.0005
Proposed CY
2018 HH
payment update minus 2
percentage
points
×
×
×
×
×
×
0.99
0.99
0.99
0.99
0.99
0.99
Proposed CY
2018 per-visit
rates
$63.62
225.20
154.63
153.58
140.49
166.92
calculated from the conversion factor is
not wage or case-mix adjusted when the
final claim payment amount is
computed. The proposed NRS
conversion factor for CY 2018 is shown
in Table 13.
submit the required quality data, 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 $264.46 (1.8451
multiplied by $143.33), subject to area
wage adjustment.
e. Proposed CY 2018 Non-Routine
Medical Supply (NRS) Payment Rates
Payments for NRS are computed by
multiplying the relative weight for a
particular severity level by the NRS
conversion factor. To determine the
proposed CY 2018 NRS conversion
factor, we update the CY 2017 NRS
conversion factor ($52.50) by the
proposed CY 2018 home health
payment update percentage of 1 percent.
We do not apply a standardization
factor as the NRS payment amount
TABLE 13—PROPOSED CY 2018 NRS
CONVERSION FACTOR FOR HHAS
THAT DO SUBMIT THE REQUIRED
QUALITY DATA
CY 2017
NRS
conversion
factor
Proposed CY
2018 HH
payment
update
Proposed CY
2018 NRS
conversion
factor
$52.50 .......
× 1.01
$53.03
Using the CY 2018 NRS conversion
factor, the payment amounts for the six
severity levels are shown in Table 14.
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TABLE 14—PROPOSED CY 2018 NRS PAYMENT AMOUNTS FOR HHAS THAT DO SUBMIT THE REQUIRED QUALITY DATA
Points
(scoring)
Severity level
1
2
3
4
...................................................................................................................................................
...................................................................................................................................................
...................................................................................................................................................
...................................................................................................................................................
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0 .....................
1 to 14 ...........
15 to 27 .........
28 to 48 .........
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Relative
weight
0.2698
0.9742
2.6712
3.9686
Proposed
CY 2017
NRS payment
amounts
$ 14.31
51.66
141.65
210.45
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TABLE 14—PROPOSED CY 2018 NRS PAYMENT AMOUNTS FOR HHAS THAT DO SUBMIT THE REQUIRED QUALITY
DATA—Continued
Severity level
Points
(scoring)
5 ...................................................................................................................................................
6 ...................................................................................................................................................
49 to 98 .........
99+ .................
For HHAs that do not submit the
required quality data, we update the CY
2017 NRS conversion factor ($52.50) by
the proposed CY 2018 home health
payment update percentage of 1 percent
minus 2 percentage points. The
proposed CY 2018 NRS conversion
factor for HHAs that do not submit
quality data is shown in Table 15.
Relative
weight
6.1198
10.5254
Proposed
CY 2017
NRS payment
amounts
324.53
558.16
The payment amounts for the various
TABLE 15—PROPOSED CY 2018 NRS
CONVERSION FACTOR FOR HHAS severity levels based on the updated
THAT DO NOT SUBMIT THE RE- conversion factor for HHAs that do not
submit quality data are calculated in
QUIRED QUALITY DATA
Table 16.
CY 2017
NRS
conversion
factor
Proposed CY
2018
HH payment
update
percentage
minus 2 percentage points
Proposed CY
2018 NRS
conversion
factor
$52.50 .......
× 0.99
$51.98
TABLE 16—PROPOSED CY 2018 NRS PAYMENT AMOUNTS FOR HHAS THAT DO NOT SUBMIT THE REQUIRED QUALITY
DATA
Points
(scoring)
Severity level
1
2
3
4
5
6
...................................................................................................................................................
...................................................................................................................................................
...................................................................................................................................................
...................................................................................................................................................
...................................................................................................................................................
...................................................................................................................................................
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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
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0 .....................
1 to 14 ...........
15 to 27 .........
28 to 48 .........
49 to 98 .........
99+ .................
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 MACRA 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.
Therefore, for episodes and visits that
end on or after January 1, 2018, a rural
add-on payment will not apply.
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 home health payment
amount in the case of outliers because
of unusual variations in the type or
amount of medically necessary care.
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Relative
weight
0.2698
0.9742
2.6712
3.9686
6.1198
10.5254
Proposed
CY 2018
NRS payment
amounts
$ 14.02
50.64
138.85
206.29
318.11
547.11
Prior to the enactment of the Affordable
Care Act, section 1895(b)(5) of the Act
stipulated that projected total outlier
payments could not exceed 5 percent of
total projected or estimated HH
payments in a given year. In the July 3,
2000 Medicare Program; Prospective
Payment System for Home Health
Agencies final rule (65 FR 41188
through 41190), we described the
method for determining outlier
payments. Under this system, outlier
payments are made for episodes whose
estimated costs exceed a threshold
amount for each Home Health Resource
Group (HHRG). The episode’s estimated
cost was established as the sum of the
national wage-adjusted per-visit
payment amounts delivered during the
episode. The outlier threshold for each
case-mix group or Partial Episode
Payment (PEP) adjustment is defined as
the 60-day episode payment or PEP
adjustment for that group plus a fixeddollar loss (FDL) amount. The outlier
payment is defined to be a proportion of
the wage-adjusted estimated cost
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beyond the wage-adjusted threshold.
The threshold amount is the sum of the
wage and case-mix adjusted PPS
episode amount and wage-adjusted FDL
amount. The proportion of additional
costs over the outlier threshold amount
paid as outlier payments is referred to
as the loss-sharing ratio.
In the CY 2010 HH PPS proposed rule
(74 FR 40948, 40957), we stated that
outlier payments increased as a
percentage of total payments from 4.1
percent in CY 2005, to 5.0 percent in CY
2006, to 6.4 percent in CY 2007 and that
this excessive growth in outlier
payments was primarily the result of
unusually high outlier payments in a
few areas of the country. In that
discussion, we noted that despite
program integrity efforts associated with
excessive outlier payments in targeted
areas of the country, we discovered that
outlier expenditures still exceeded the 5
percent target in CY 2007 and, in the
absence of corrective measures, would
continue do to so. Consequently, we
assessed the appropriateness of taking
action to curb outlier abuse. As
described in the CY 2010 HH PPS final
rule (74 FR 58080 through 58087), to
mitigate possible billing vulnerabilities
associated with excessive outlier
payments and adhere to our statutory
limit on outlier payments, we finalized
an outlier policy that included a 10
percent agency-level cap on outlier
payments. This cap was implemented in
concert with a reduced FDL ratio of
0.67. These policies resulted in a
projected target outlier pool of
approximately 2.5 percent. (The
previous outlier pool was 5 percent of
total home health expenditures). For CY
2010, we first returned the 5 percent
held for the previous target outlier pool
to the national, standardized 60-day
episode rates, the national per-visit
rates, the LUPA add-on payment
amount, and the NRS conversion factor.
Then, we reduced the CY 2010 rates by
2.5 percent to account for the new
outlier pool of 2.5 percent. This outlier
policy was adopted for CY 2010 only.
As we noted in the CY 2011 HH PPS
final rule (75 FR 70397 through 70399),
section 3131(b)(1) of the Affordable Care
Act amended section 1895(b)(3)(C) of
the Act, and required the Secretary to
reduce the HH PPS payment rates such
that aggregate HH PPS payments were
reduced by 5 percent. In addition,
section 3131(b)(2) of the Affordable Care
Act amended section 1895(b)(5) of the
Act by redesignating the existing
language as section 1895(b)(5)(A) of the
Act, and revising the language to state
that the total amount of the additional
payments or payment adjustments for
outlier episodes may not exceed 2.5
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percent of the estimated total HH PPS
payments for that year. Section
3131(b)(2)(C) of the Affordable Care Act
also added section 1895(b)(5)(B) of the
Act which capped outlier payments as
a percent of total payments for each
HHA at 10 percent.
As such, beginning in CY 2011, our
HH PPS outlier policy is that we reduce
payment rates by 5 percent and target
up to 2.5 percent of total estimated HH
PPS payments to be paid as outliers. To
do so, we first returned the 2.5 percent
held for the target CY 2010 outlier pool
to the national, standardized 60-day
episode rates, the national per visit
rates, the LUPA add-on payment
amount, and the NRS conversion factor
for CY 2010. We then reduced the rates
by 5 percent as required by section
1895(b)(3)(C) of the Act, as amended by
section 3131(b)(1) of the Affordable Care
Act. For CY 2011 and subsequent
calendar years we target up to 2.5
percent of estimated total payments to
be paid as outlier payments, and apply
a 10 percent agency-level outlier cap.
In the CY 2017 HH PPS proposed and
final rules (81 FR 43737 through 43742
and 81 FR 76702), we described our
concerns regarding patterns observed in
home health outlier episodes.
Specifically, we noted that the
methodology for calculating home
health outlier payments may have
created a financial incentive for
providers to increase the number of
visits during an episode of care to
surpass the outlier threshold and
simultaneously created a disincentive
for providers to treat medically complex
beneficiaries who require fewer but
longer visits. Given these concerns, in
the CY 2017 HH PPS final rule (81 FR
76702), we finalized changes to the
methodology used to calculate outlier
payments, using a cost-per-unit
approach rather than a cost-per-visit
approach. This change in methodology
allows for more accurate payment for
outlier episodes, accounting for both the
number of visits during an episode of
care and also the length of the visits
provided. Using this approach, we now
convert the national per-visit rates into
per 15-minute unit rates. These per 15minute unit rates are used to calculate
the estimated cost of an episode to
determine whether the claim will
receive an outlier payment and the
amount of payment for an episode of
care. In conjunction with our finalized
policy to change to a cost-per-unit
approach to estimate episode costs and
determine whether an outlier episode
should receive outlier payments, in the
CY 2017 HH PPS final rule we also
finalized the implementation of a cap on
the amount of time per day that would
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35293
be counted toward the estimation of an
episode’s costs for outlier calculation
purposes (81 FR 76725). Specifically,
we limit the amount of time per day
(summed across the six disciplines of
care) to 8 hours (32 units) per day when
estimating the cost of an episode for
outlier calculation purposes.
2. Fixed Dollar Loss (FDL) Ratio
For a given level of outlier payments,
there is a trade-off between the values
selected for the FDL ratio and the losssharing ratio. A high FDL ratio reduces
the number of episodes that can receive
outlier payments, but makes it possible
to select a higher loss-sharing ratio, and
therefore, increase outlier payments for
qualifying outlier episodes.
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.
Simulations based on CY 2015 claims
data (as of June 30, 2016) completed for
the CY 2017 HH PPS final rule showed
that outlier payments were estimated to
represent approximately 2.84 percent of
total HH PPS payments in CY 2017, and
as such, we raised the FDL ratio from
0.45 to 0.55. We stated that raising the
FDL ratio to 0.55, while maintaining a
loss-sharing ratio of 0.80, struck an
effective balance of compensating for
high-cost episodes while still meeting
the statutory requirement to target up to,
but no more than, 2.5 percent of total
payments as outlier payments (81 FR
76726). The national, standardized 60day 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, using
preliminary CY 2016 claims data (as of
March 17, 2017) and the proposed CY
2018 payment rates presented in section
III.C of this proposed rule, we estimate
that outlier payments would constitute
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approximately 2.47 percent of total HH
PPS payments in CY 2018 under the
current outlier methodology. Given the
statutory requirement to target up to, but
no more than, 2.5 percent of total
payments as outlier payments, we are
not proposing a change to the FDL ratio
for CY 2018 as we believe that
maintaining an FDL ratio of 0.55 with a
loss-sharing ratio of 0.80 is still
appropriate given the percentage of
outlier payments projected for CY 2018.
Likewise, we are not proposing a change
to the loss-sharing ratio (0.80) for the
HH PPS to remain consistent with
payment for high-cost outliers in other
Medicare payment systems (for
example, IRF PPS, IPPS, etc.). While we
are not proposing to change the FDL
ratio of 0.55 for CY 2018, we note that
in the final rule, we will update our
estimate of outlier payments as a
percent of total HH PPS payments using
the most current and complete year of
HH PPS data (CY 2016 claims data as of
June 30, 2017 or later). This may result
in changes to the FDL ratio in the final
rule.
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E. Proposed Implementation of the
Home Health Groupings Model (HHGM)
for CY 2019
1. Overview, Data, and File
Construction
Under the home health prospective
payment system (HH PPS), Medicare
pays for home health services provided
during a 60-day episode of care.
Episodes are case-mix adjusted based on
the timing of the episode within a
sequence of episodes, the patient’s
clinical status and functional status as
determined using information from the
Outcome and Assessment Information
Set (OASIS), and the amount of therapy
service provided during the episode.
Therapy service use is measured by the
number of therapy visits provided
during the episode and can be
categorized into nine visit level
categories (or thresholds): 0–5; 6; 7–9;
10; 11–13; 14–15; 16–17; 18–19; and 20
or more visits. The combinations of
episode timing, clinical and functional
levels, and therapy service use
categories result in 153 home health
resource groups (HHRGs) into which
home health episodes are categorized.
Each HHRG is assigned a relative weight
reflecting the average resource use of
patients in that group compared with
average resource use across all Medicare
home health patients; this weight is
then used to case mix adjust the
episode’s payment (with an additional
adjustment for geographic variation in
wages). Additional payment
adjustments are made for very resource
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intensive (outlier) episodes, episodes
with very few visits, transfers to other
HHAs or to hospitals with a return to
home health during the episode, and the
expected use of non-routine medical
supplies (NRS).
As discussed in section II.D of this
proposed rule, the Report to Congress,
required by section 3131(d) of the
Affordable Care Act, found that
payment accuracy could be improved
under the current payment system,
particularly for patients with certain
clinical characteristics.16 Findings from
the report suggest 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 need therapy services, but require
skilled nursing care. In addition,
MedPAC believes that the Medicare
home health benefit is ill-defined and
the current reliance on therapy service
thresholds for determining payment is
counter to the goals of a prospective
payment system. Under the current
payment system, HHAs receive higher
payments for providing more therapy
visits, which may incentivize
unnecessary utilization. MedPAC
reitereated their recommendation in the
March 2017 Report to Congress that
CMS eliminate the use of the number of
therapy vists as a payment factor in the
home health PPS beginning in 2019.17
To better align payment with patient
care needs and better ensure that
clinically complex and ill beneficiaries
have adequate access to home health
care, we are proposing for CY 2019 casemix methodology refinements through
the implementation of the Home Health
Groupings Model (HHGM). We propose
to implement the HHGM for home
health periods of care beginning on or
after January 1, 2019. The
implementation of the HHGM will
require provider education and training,
updating and revising relevant manuals,
and changing claims processing
systems. Implementation starting in CY
2019 would provide an opportunity for
CMS, its contractors, and the agencies
themselves to prepare. This patientcentered model groups periods of care
16 Report to Congress. Medicare Home Health
Study: An Investigation on Access to Care and
Payment for Vulnerable Patient Populations.
Available at https://www.cms.gov/Medicare/
Medicare-Fee-for-Service-Payment/
HomeHealthPPS/Downloads/HH-Report-toCongress.pdf.
17 Medicare Payment Advisory Commission
(MedPAC). ‘‘Home Health Care Services.’’ Report to
Congress: Medicare Payment Policy. Washington,
DC, March 2015. P. 233. Accessed on March 28,
2017 at https://www.medpac.gov/docs/defaultsource/reports/mar2015_entirereport_
revised.pdf?sfvrsn=0.
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in a manner consistent with how
clinicians differentiate between patients
and the primary reason for needing
home health care. The HHGM uses 30day periods rather than the 60-day
episode used in the current payment
system, eliminates the use of the
number of therapy visits provided to
determine payment, and relies more
heavily on clinical characteristics and
other patient information (for example,
diagnosis, functional level, comorbid
conditions, admission source) to place
patients into clinically meaningful
payment categories. In total, there are
144 different payment groups in the
HHGM.
Costs during an episode/period of
care are estimated based on the concept
of resource use, which measures the
costs associated with visits performed
during a home health episode/period.
For the current HH PPS case-mix
weights, we use Wage Weighted
Minutes of Care (WWMC), which uses
data from the Bureau of Labor Statistics
(BLS) reflecting the Home Health Care
Service Industry. For the HHGM, we
propose shifting to a Cost-Per-Minute
plus Non-Routine Supplies (CPM +
NRS) approach, which uses information
from the Medicare Cost Report. The
CPM + NRS approach incorporates a
wider variety of costs (such as
transportation) compared to the BLS
estimates and the costs are available for
individual HHA providers while the
BLS costs are aggregated for the Home
Health Care Service industry. The
proposed methodology used to calculate
the cost of an episode/period of care is
discussed in detail in section III.E.2. of
this proposed rule.
We propose using the 30-day periods
rather than the 60-day episodes in the
current payment system. Episodes have
more visits, on average, during the first
30 days compared to the last 30 days.18
Costs are much higher earlier in the
episode and lesser later on, therefore we
believe that dividing a single 60-day
episode into two 30-day periods more
accurately apportions payments.
Overall, we found that the average
length of an episode of care was 47
days, but roughly a quarter of all 60
days episodes lasted 30 days or less.
The proposed change from 60-day
billing to 30-day billing under the
HHGM is discussed in detail in section
III.E.3. of this proposed rule.
18 Abt Associates. ‘‘Overview of the Home Health
Groupings Model.’’ Medicare Home Health
Prospective Payment System: Case-Mix
Methodology Refinements. Cambridge, MA,
November 18, 2016. Available at https://
downloads.cms.gov/files/hhgm%20technical
%20report%20120516%20sxf.pdf.
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Similar to the current payment
system, 30-day periods under the
HHGM would be classified as ‘‘early’’ or
‘‘late’’ depending on when they occur
within a sequence of 30-day periods.
Under the current HH PPS, the first two
60-day episodes of a sequence of
adjacent 60-day episodes are considered
early, while the third 60-day episode of
that sequence and any subsequent
episodes are considered late. Under the
HHGM, the first 30-day period is
classified as early. All subsequent 30day periods in the sequence (second or
later) are classified as late. We propose
to adopt this episode timing
classification for 30-day periods with
the implementation of the HHGM.
Similar to the current payment system,
we propose that a 30-day period could
not be considered early unless there was
a gap of more than 60 days between the
end of one period and the start of
another. The comprehensive assessment
would still be completed within 5 days
of the start of care date and completed
no less frequently than during the last
5 days of every 60 days beginning with
the start of care date, as currently
required by § 484.55, Condition of
participation: Comprehensive
assessment of patients. The proposed
episode timing classification is
discussed in detail in section III.E.4. of
this proposed rule.
Under the HHGM, each period would
be classified into one of two admission
source categories—community or
institutional—depending on what
healthcare setting was utilized in the 14
days prior to home health. The 30-day
period would be categorized as
institutional if an acute or post-acute
care stay occurred in the prior 14 days
to the start of the 30-day period of care.
The 30-day period would be categorized
as community if there was no acute or
post-acute care stay in the 14 days prior
to the start of the 30-day period of care.
We propose to adopt this categorization
by admission source with the
implementation of the HHGM. The
proposed admission classification
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source is discussed in detail in section
III.E.5. of this proposed rule.
The HHGM would group 30-day
periods into categories based on a
variety of patient characteristics. Within
the HHGM, one of the steps in case-mix
adjusting the 30-day payment amount
would include grouping periods into
one of six clinical groups based on the
principal diagnosis listed on the home
health claim. We propose grouping
periods into one of six clinical groups
based on the principal diagnosis with
the implementation of the HHGM. The
principal diagnosis reported would
provide information to describe the
primary reason for which patients are
receiving home health services under
the Medicare home health benefit. The
proposed six clinical groups, which are
discussed in detail in section III.E.6. of
this proposed rule, are as follows:
• Musculoskeletal Rehabilitation.
• Neuro/Stroke Rehabilitation.
• Wounds—Post-Op Wound
Aftercare and Skin/Non-Surgical
Wound Care.
• Complex Nursing Interventions.
• Behavioral Health Care.
• Medication Management, Teaching
and Assessment (MMTA).
Under the HHGM, each 30-day period
would be placed into one of three
functional levels. The level would
indicate if, on average, given its
responses on certain functional OASIS
items, a 30-day period is predicted to
have higher costs or lower costs. We
propose classifying 30-day periods
according to functional level. For each
of the six clinical groups, we propose
that periods would be further classified
into one of three functional levels with
roughly 33 percent of periods in each
level. The creation of this functional
level is very similar to how the
functional level is created in the current
payment system. The proposed
functional levels and corresponding
OASIS items are discussed in detail in
section III.E.7. of this proposed rule.
Exploratory analyses determined that
comorbidities—that is, secondary
diagnoses—provide additional
information that can further explain
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35295
resource use differences across 30-day
periods of care even after controlling for
the primary diagnosis. Comorbidities
are tied to poorer health outcomes, more
complex medical need and
management, and higher costs. The
HHGM would include a comorbidity
adjustment category based on the
presence of secondary diagnoses. We
propose that 30-day periods would
receive a comorbidity adjustment if any
diagnosis codes listed on the home
health claim are included on a list of
comorbidities that occurred in at least
0.1 percent of 30-day periods and
associated with increased average
resource use. The proposed comorbidity
adjustment is discussed in detail in
section III.E.8. of this proposed rule.
Currently, if an HHA provides four
visits or less in an episode, they will be
paid a standardized per visit payment
instead of an episode payment for a 60day episode of care. These payment
adjustments are called Low-Utilization
Payment Adjustments (LUPAs). While
the HHGM would still include LUPAs,
the approach to calculating the LUPA
thresholds would need to change in the
HHGM because of the switch to 30-day
periods from 60-day episodes. Whereas
there is a single LUPA threshold of 4
visits for all episodes under the current
payment system, we propose the LUPA
threshold would vary for a 30-day
period under the HHGM depending on
the HHGM payment group to which it
was assigned. To create LUPA
thresholds, 30-day periods (including
those that were LUPAs in the current
payment system) were grouped into the
144 different HHGM payment groups.
For each payment group, we propose to
use the 10th percentile value of visits to
create a payment group specific LUPA
threshold with a minimum threshold of
at least 2 for each group. The proposed
LUPA thresholds are discussed in more
detail in section III.E.9. of this proposed
rule.
Figure 5 represents how each 30-day
period of care would be placed into one
of 144 home health resource groups
(HHRGs) under the proposed HHGM.
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While the proposed HHGM would
reflect a change in the case-mix
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adjustment methodology, the conditions
for payment would remain the same for
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Medicare home health services,
meaning all requirements would still
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FIGURE 5: Structure of the Proposed HHGM
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need to be met in accordance with
§ 424.22. This includes physician
certification that: (1) The individual is
in need or needed intermittent skilled
nursing care, or physical therapy or
speech-language pathology services, and
is confined to the home; (2) a plan of
care has been established and will be
periodically reviewed by a physician
who is a doctor of medicine, osteopathy,
or podiatric medicine; (3) the individual
was under the care of a physician who
is a doctor of medicine, osteopathy, or
podiatric medicine; and, (4) a face-toface patient encounter, which is related
to the primary reason the patient
requires home health services, occurred
no more than 90 days prior to the home
health start of care date or within 30
days of the start of the home health care
and was performed by a physician or
allowed non-physician practitioner.
Likewise, under the HHGM, the
Medicare beneficiary would retain all
rights that currently exist under the
current HH PPS, including those related
to beneficiary liability for services or
any reduction or termination of services.
These would include the issuance of the
Advanced Beneficiary Notice (ABN) and
the Home Health Change of Care Notice
(HHCCN), when appropriate. Medicare
home health agencies are required to
issue an ABN when a HHA believes
Medicare will not pay for some or all of
the patient’s Medicare home health care.
In these circumstances, if the
beneficiary chooses to receive the items/
services in question and Medicare does
not cover the home health care, HHAs
may use the ABN to shift liability for the
non-covered home health care to the
beneficiary. The HHCCN is a written
notice that the HHA provides a
beneficiary when his/her home health
plan of care is changing because the
home health agency makes a business
decision to reduce or stop providing the
patient some or all of the home health
services or supplies OR the beneficiary’s
physician changed orders which may
reduce or stop certain Medicare covered
home health services or supplies.
To create the HHGM proposed model
and related analyses, a data file based
on home health episodes of care as
reported in Medicare home health
claims was utilized. The claims data
provide episode-level data (for example,
episode From and Through Dates, total
number of visits, HHRG, diagnoses), as
well as visit-level data (visit date, visit
length in 15-minute units, discipline of
the staff, etc.). The claims also provide
data on whether NRS was provided
during the episode and total charges for
NRS.
The core file for most of the analyses
for this proposed rule includes 100
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percent of home health episode claims
with Through Dates in Calendar Year
(CY) 2016, processed by March 17,
2017, accessed via the Chronic
Conditions Data Warehouse (CCW).
Original or adjustment claims processed
after March 17, 2017, would not be
reflected in the core file. The claimsbased file was supplemented with
additional variables that were obtained
from the CCW, such as information
regarding other Part A and Part B
utilization.
The data were cleaned by processing
any remaining adjustments and by
excluding duplicates and claims that
were Requests for Anticipated Payment
(RAP). In addition, visit-level variables
needed for the analysis were extracted
from the revenue center trailers (that is,
the line items that describe the visits)
and downloaded as a separate visit-level
file, with selected episode-level
variables merged onto the records for
visits during those episodes. To account
for potential data entry errors, the visitlevel variables for visit length were topcensored at eight hours.19
A set of data cleaning exclusions were
applied to the episode-level file, which
resulted in the exclusion of the
following:
• Episodes with no covered visits.
• Episodes with any missing units or
visit data.
• Episodes with zero payments.
• Episodes with no charges.
• Non-LUPA episodes missing an
HHRG.
The analysis file also includes data on
patient characteristics obtained from the
OASIS assessments conducted by HHA
staff at the start of each episode. The
assessment data are electronically
submitted by home health agencies
(HHAs) to a central CMS repository. In
constructing the core data file, 100
percent of the OASIS assessments
submitted October 2015, through
December 2016 from the CMS repository
were uploaded by CMS to the CCW. A
CCW-derived linking key (Bene_ID) was
used to match the OASIS data with CY
2016 episodes of care. Episodes that
could not be linked with an OASIS
assessment were excluded from the
analysis file, as they included
insufficient patient-level data to create
the HHGM.
To construct measures of resource
use, a variety of data sources were used
(see section III.E.2 of this proposed rule
for the proposed methodology used to
calculate the cost of care under the
HHGM). First, BLS data on average
wages and fringe benefits were used to
19 Less than 0.1 percent of all visits were recorded
as having greater than 8 hours of service.
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35297
produce one version of the wageweighted cost per minute for each home
health discipline. The wage data are for
North American Industry Classification
System (NAICS) 621600—Home Health
Care Services. The wage data are broken
down by the following occupations:
TABLE 17—BLS STANDARD OCCUPATION CLASSIFICATION (SOC) CODES
FOR HOME HEALTH PROVIDERS
Standard Occupation
Code (SOC) No.
Occupation title
29–1141 ..........................
29–2061 ..........................
Registered Nurses.
Licensed Practical and
Licensed Vocational
Nurses.
Physical Therapists.
Physical Therapist Assistants.
Physical Therapist Aides.
Occupational Therapists.
Occupational Therapist
Assistants.
Occupational Therapist
Aides.
Speech-Language Pathologists.
Medical and Public
Health Social Workers.
Mental Health and Substance Abuse Social
Workers.
Home Health Aides.
29–1123 ..........................
31–2021 ..........................
31–2022 ..........................
29–1122 ..........................
31–2011 ..........................
31–2012 ..........................
29–1127 ..........................
21–1022 ..........................
21–1023 ..........................
31–1011 ..........................
For visits where the service
provided—as indicated by the
Healthcare Common Procedure Coding
System (HCPCS) code—can be provided
by only a single standard occupation
classification code; for example,
establishment or review of a plan of care
by a registered nurse (RN; HCPCS =
G0162), the wage (and fringe) rate for
that standard occupation classification
is used to calculate the cost of the
minutes for the visit. For visits where
the service provided can potentially be
provided by different standard
occupation classification, such as
observation and assessment by an RN or
a Licensed Practical Nurse (LPN; HCPCS
= G0163), a blended rate is applied,
with the rate for each standard
occupation classification code weighted
by the total home health employment
for that standard occupation
classification code. The employment
data are available from the same BLS
table as the wage data.
Home Health Agency Medicare Cost
Report (MCR) data were also used to
construct a measure of resource use after
trimming out HHAs whose costs were
outliers. These data are used to provide
a representation of the average costs of
visits provided by HHAs in the six
Medicare home health disciplines:
Skilled nursing; physical therapy;
occupational therapy; speech-language
pathology; medical social services; and
home health aide services. Cost report
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data are publicly available at https://
www.cms.gov/Research-Statistics-Dataand-Systems/Downloadable-Public-UseFiles/Cost-Reports/.
The 2016 analytic file included
6,293,442 episodes. Of these, 469,346
(7.5 percent) were excluded because
they could not be linked to OASIS
assessments or because of the reasons
listed above. This yielded an analysis
file including 5,824,096 episodes. Those
episodes are 60-day episodes under the
current payment system, but for the
HHGM those 60-day episodes were
converted into two 30-day periods. This
yielded a final HHGM analytic file that
included 10,231,507, 30-day periods.
Certain 30-day periods were excluded
for the following reasons:
• Periods missing a diagnosis code or
where the diagnosis code did not link to
a clinical group to case-mix adjust the
period’s payment (after exclusions, n =
10,177,949).
• Inability to merge to certain OASIS
items to create the episode’s functional
level that is used for risk adjustment.
For all the periods in the analytic file,
there was a look-back through CY 2015
for a Start of Care or Resumption of Care
assessment that preceded the period
being analyzed and was in the same
sequence of periods. If such an
assessment was found, it was used to
impute responses for OASIS items that
were not included in the follow-up
assessment. Periods which did not link
to a Start of Care or Resumption of Care
assessment were dropped (after
exclusions, n = 9,477,856).
• No nursing visits or therapy visits
(after exclusions, n = 9,290,340).
• LUPAs were excluded from the
analysis. Periods that are identified as
LUPAs in the current payment system
are excluded in the creation of the
functional score. Following the creation
of the score (and the corresponding
levels), case-mix group specific LUPA
thresholds were created and episodes/
periods were excluded that were below
the new LUPA threshold when
computing the case-mix weights.20
Therefore, the final analytic sample
included 8,642,107 30-day periods that
were used for the analyses in the
HHGM.
As noted in section II.D of this
proposed rule, the analyses and the
20 The case-mix group specific LUPA thresholds
were determined using episodes that were
considered LUPAs under the current payment
system.
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ultimate development of Home Health
Groupings Model (HHGM) have been
shared with both internal and external
stakeholders via technical expert panels,
clinical workgroups, special open door
forums, and in the CY 2017 HH PPS
final rule (81 FR 76702). Technical
expert panel and clinical workgroup
webinars on the technical report were
held in December 2016 and a detailed
technical report was posted on the CMS
home health agency Web page in
December, providing opportunity for
stakeholder feedback.21 We also held a
National Provider call in January 2017,
to further solicit feedback from the
public.22
2. Methodology Used To Calculate the
Cost of Care
To construct the case-mix weights for
the HHGM proposal, the costs of
providing care needed to be determined.
A Wage-Weighted Minutes of Care
(WWMC) approach is used in the
current payment system based on data
from the BLS. However, we are
proposing to adopt a Cost-per-Minute
plus Non-Routine Supplies (CPM +
NRS) approach, which uses information
from Medicare Cost Reports (MCR). We
used the following data sources and
methodology for calculating these
measures of resource use:
• BLS Wage Estimates: For the
WWMC method of calculating home
health resource use, wage and fringe
data was obtained from the BLS by
industry code from the NAICS and
occupation code from the Standard
Operation Classification. These data
provide nationwide average wage rates
and the average value of fringe benefits
per hour of work for specific
occupations.
• Home Health Medicare Cost Report
Data: All Medicare-certified HHAs must
report their own costs through publiclyavailable home health cost reports
21 Abt Associates. ‘‘Overview of the Home Health
Groupings Model.’’ Medicare Home Health
Prospective Payment System: Case-Mix
Methodology Refinements. Cambridge, MA,
November 18, 2016. Available at https://
downloads.cms.gov/files/hhgm%20technical
%20report%20120516%20sxf.pdf.
22 Centers for Medicare & Medicaid Services
(CMS). ‘‘Certifying Patients for the Medicare Home
Health Benefit.’’ MLN ConnectsTM National
Provider Call. Baltimore, MD, December 16, 2016.
Slides, examples, audio recording and transcript
available at https://www.cms.gov/Outreach-andEducation/Outreach/NPC/National-Provider-Callsand-Events-Items/2017-01-18-Home-Health.
html?DLPage=2&DLEntries=10&DLSort=0&
DLSortDir=descending.
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maintained by the Healthcare Cost
Report Information System (HCRIS).
Freestanding HHAs report HHA-specific
cost reports while HHAs that are
hospital-based report on the HHA
component of the hospital cost reports.
These cost reports enable estimation of
the cost per visit by provider and the
estimated NRS cost to charge ratios. To
obtain a more robust estimate of cost, a
trimming process was applied to remove
cost reports with missing or
questionable data and extreme values.23
• Home Health Claims Data:
Medicare home health claims data are
used in both the WWMC and CPM+NRS
methods to obtain minutes of care by
discipline of care.
• Wage-Weighted Minutes of Care
(WWMC) Approach: Used in the current
payment system, this approach
determines resource use for each
episode by multiplying utilization (in
terms of the number of minutes of direct
patient care provided by each
discipline) by the corresponding
opportunity cost of that care
(represented by wage and fringe benefit
rates from the BLS).24 Table 18 shows
the occupational titles and
corresponding mean hourly wage rates
from the BLS. The employer cost per
hour worked shown in the fifth column
is calculated by adding together the
mean hourly wage rates and the fringe
benefit rates from the BLS (generally
around 37 percent of wages). For home
health disciplines that include multiple
occupations (such as skilled nursing),
the opportunity cost is generated by
weighting the employer cost by the
proportions of the labor mix.25
Otherwise, the opportunity cost is the
same as the employer cost per hour.
23 The trimming methodology is described in the
report ‘‘Analyses in Support of Rebasing &
Updating Medicare Home Health Payment Rates’’
(Morefield, Christian, and Goldberg 2013). See
https://www.cms.gov/Medicare/Medicare-Fee-forService-Payment/HomeHealthPPS/Downloads/
Analyses-in-Support-of-Rebasing-and-Updatingthe-Medicare-Home-Health-Payment-RatesTechnical-Report.pdf.
24 Opportunity costs represent the foregone
resources from providing each minute of care
versus using the resources for another purpose (the
next best alternative). Generally, opportunity costs
represent more than the monetary costs, but in
these analyses, they are proxied using hourly wage
rates.
25 Labor mix represents the percentage of
employees with a particular occupational title (as
obtained from the BLS) within a home health
discipline.
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TABLE 18—OCCUPATIONAL EMPLOYMENT AND WAGES PROVIDED BY THE FEDERAL BUREAU OF LABOR STATISTICS
National
employment
counts
Occupation
title
Registered
Nurses.
Licensed Practical and Licensed Vocational Nurses.
Physical Therapists.
Physical Therapist Assistants.
Physical Therapist Aides.
Occupational
Therapists.
Occupational
Therapist Assistants.
Occupational
Therapist
Aides.
Speech-Language Pathologists.
Medical and
Public Health
Social Workers.
Mental Health
and Substance Abuse
Social Workers.
Home Health
Aides.
Estimate
of benefits as
a % of
wages
Mean
hourly
wage
Estimated
employer
cost
per hour
worked
Home
health
discipline
Labor
mix
173,590
$32.94
43.76
$47.36
0.68
82,860
21.86
43.76
31.43
0.32
25,700
46.42
39.91
64.95
0.76
7,460
30.81
35.75
41.83
0.22
500
15.85
35.75
21.52
0.01
10,780
44.17
39.91
61.80
0.82
2,220
32.03
35.75
43.48
0.17
110
25.20
35.75
34.21
0.01
5,340
46.83
39.91
65.52
17,270
28.16
39.91
450
26.87
385,440
10.93
Opportunity
cost
Skilled Nursing .........................
$42.21
Physical Therapy .....................
59.18
Occupational Therapy .............
58.46
..........
Speech Therapy ......................
65.52
39.40
0.97
Medical Social Service ............
39.35
39.91
37.59
0.03
35.75
14.84
..........
Home Health Aide ...................
14.84
Source: May 2015 National Industry-Specific Occupational Employment and Wage Estimates NAICS 621600—Home Health Care Services.
For each home health period of care,
the number of minutes of care provided
(obtained from the home health claims)
is weighted by the corresponding
opportunity cost for each discipline
providing the minutes. The resulting
wage-weighted minutes of care are
summed for the 30-day period to obtain
total costs. Table 19 shows these costs
overall for 30-day periods in CY 2016 (n
= 8,642,107). On average, total period
costs were $374.52. The distribution
ranged from a 5th percentile value of
$73.87 to a 95th percentile value of
$912.10.
TABLE 19—DISTRIBUTION OF AVERAGE RESOURCE USE USING WWMC APPROACH
[30 day periods]
Mean
N
5th
Percentile
10th
Percentile
25th
Percentile
50th
Percentile
75th
Percentile
90th
Percentile
95th
Percentile
Average
Resource
Use
(WWMC)
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Statistics
$374.52
8,642,107
$73.87
$94.97
$158.29
$303.19
$517.063
$749.22
$912.10
In the current HH PPS, all episodes
without a LUPA payment receive
payment for NRS, regardless of whether
or not the HHA provided NRS during
that episode. NRS payment amounts are
determined through a payment model
separately from the one used to
construct the episode’s case-mix weight.
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The current payment system determines
NRS payment using the presence of
clinical factors associated with NRS
provision from the OASIS. Two-thirds
of episodes do not include provision of
NRS, yet those episodes still receive an
NRS payment.
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We are proposing to calculate
resource use under the HHGM using a
Cost-per-Minute plus Non-Routine
Supplies (CPM + NRS) approach. It
determines resource use using
information from Medicare cost reports.
Under the proposed HHGM, we would
group episodes into their case-mix
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groups taking into account admission
source, timing, clinical group,
functional level, and comorbidity
adjustment. From there, the average
resource use for each case-mix group
dictates the group’s case-mix weight.
Resource use is the estimated cost of
visits recorded on the home health
claim plus the cost of NRS recorded on
the claims. The cost of NRS is generated
by taking NRS charges on claims and
converting them to costs using a NRS
cost to charge ratio that is specific to
each HHA. When NRS is factored into
the average resource use, NRS costs are
reflected in the average resource use
that drives the case-mix weights. CMS
would return $53.03 to the base rate
(that is, the NRS conversion factor). If
there is a high amount of NRS cost for
all episodes in a particular group
(holding all else equal), the resource use
will be higher relative to the average
and the case-mix weight will
correspondingly be higher. Similar to
the current system, NRS would still be
paid prospectively under the HHGM,
but the HHGM eliminates the separate
case-mix adjustment model for NRS.
Incorporating the NRS cost into the
measure of overall resource use (that is,
the dependent variable of the payment
model) requires adjusting the NRS
charges submitted on claims based on
the NRS cost-to-charge ratio from cost
report data.
The following steps would be used to
generate the measure of resource use
under this CPM + NRS approach:
(1) From the cost reports, obtain total
costs for each of the six home health
disciplines for each HHA.
(2) From the cost reports, obtain the
number of visits by each of the six home
health disciplines for each HHA.
(3) Calculate discipline-specific cost
per visit values by dividing total costs
[1] by number of visits [2] for each
discipline for each HHA. For HHAs that
did not have a cost report available (or
a cost report that was trimmed from the
sample), imputed values were used as
follows:
• A state-level mean was used if the
HHA was not hospital-based. The statelevel mean was computed using all nonhospital based HHAs in each state.
• An urban nationwide mean was
used for all hospital-based HHAs
located in a Core-based Statistical Area
(CBSA). The urban nation-wide mean
was computed using all hospital-based
HHAs located in any CBSA.
• A rural nationwide mean was used
for all hospital-based HHAs not in a
CBSA. The rural nation-wide mean was
computed using all hospital-based
HHAs not in a CBSA.
(4) From the home health claims data,
obtain the average number of minutes of
care provided by each discipline across
all episodes for a HHA.
(5) From the home health claims data,
obtain the average number of visits
provided by each discipline across all
episodes for each HHA.
(6) Calculate a ratio of average visits
to average minutes by discipline by
dividing average visits provided [5] by
average minutes of care [4] by discipline
for each HHA.
(7) Calculate costs per minute by
multiplying the HHA’s cost per visit [3]
by the ratio of average visits to average
minutes [6] by discipline for each HHA.
(8) Obtain 30-day period costs by
multiplying costs per minute [7] by the
total number of minutes of care
provided during a 30-day period by
discipline. Then, sum these costs across
the disciplines for each period.
This approach accounts for variation
in the length of a visit by discipline.
NRS costs are added to the resource use
calculated in [8] in the following way:
(9) From the cost reports, determine
the NRS cost-to-charge ratio for each
HHA. The NRS ratio is trimmed if the
value falls in the top or bottom 1
percent of the distribution across all
HHAs from the trimmed sample.
Imputation for missing or trimmed
values is done in the same manner as it
was done for cost per visit (see [3]
above).
(10) From the home health claims
data, obtain NRS charges for each
period.
(11) Obtain NRS costs for each period
by multiplying charges from the home
health claims data [10] by the cost-tocharge ratio from the cost reports [9] for
each HHA.
Resource use is then obtained by:
(12) Summing costs from [8] with
NRS costs from [11] for each 30-day
period.
Table 20 shows these costs overall for
30-day periods in CY 2015 (n =
8,642,107). On average, total 30-day
period costs are $1,585.48. The
distribution ranges from a 5th percentile
value of $300.03 to a 95th percentile
value of $3,908.93.
TABLE 20—DISTRIBUTION OF AVERAGE RESOURCE USE USING CPM + NRS APPROACH
[30 day periods]
Statistics
mstockstill on DSK30JT082PROD with PROPOSALS2
Average Resource Use (CPM +
NRS) ......................................
Mean
$1,585.48
8,642,107
The distributions and magnitude of
the estimates of costs for the two
methods are very different. The
differences arise because the CPM +
NRS method incorporates HHA-specific
costs that represent the total costs
incurred during a 30-day period
(including overhead costs), while the
WWMC method provides an estimate of
only the labor costs (wage + fringe)
related to direct patient care from
patient visits that are incurred during a
30-day period. Those costs are not HHAspecific and do not account for any nonlabor costs (such as transportation costs)
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5th
Percentile
N
10th
Percentile
$300.03
$396.82
25th
Percentile
$671.96
or the non-direct patient care labor costs
(such as, administration and general
labor costs). Because the costs estimated
using the two approaches are measuring
different items, they cannot be directly
compared. However, if the true cost of
a 30-day period is correlated with the
labor that is provided during visits, the
two approaches should be highly
correlated. The correlation coefficient
between the two approaches to
calculating resource use is equal to
0.8016 (n = 8,642,107). Therefore, the
relationship in relative costs is similar
between the two methods.
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50th
Percentile
$1262.65
75th
Percentile
$2,119.49
90th
Percentile
$3,135.38
95th
Percentile
$3,908.93
Using cost report data to develop
case-mix weights more evenly weights
skilled nursing services and therapy
services than the BLS data. Table 21
shows the ratios between the estimated
costs per hour for each of the home
health disciplines compared with
skilled nursing resulting from the CPM
+NRS versus WWMC methods. Under
the CPM+NRS methodology, the ratio
for physical therapy costs per hour to
skilled nursing is 1.14 compared with
1.40 using the WWMC method.
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TABLE 21—RELATIVE VALUES IN COSTS PER HOUR BY DISCIPLINE
[Skilled nursing is base]
Estimated cost per hour
Skilled nursing
CPM+NRS ...............................................
WWMC .....................................................
1.00
1.00
We believe that using cost report data
to calculate the cost of home health care
better aligns the case-mix weights with
the total relative cost for treating various
patients. In addition, using cost report
data allows us to incorporate NRS into
the case-mix system, rather than
maintaining a separate payment system.
Therefore, we are proposing to calculate
the cost of a 30-day period of home
health care under the HHGM using the
cost per minute plus non-routine
supplies (CPM+NRS) approach outlined
above. We invite comments on the
proposed methodology for calculating
the cost of a 30-day period of care under
the HHGM.
3. Change From 60-Day Billing to 30Day Billing Under the HHGM
mstockstill on DSK30JT082PROD with PROPOSALS2
a. 30-Day Unit of Payment
Currently, HHAs are paid for each 60day episode of home health care
provided. We are proposing 30-day
periods of payment for the HHGM.
Through examination of the resources
used within a 60-day episode of care,
we identified differences in resources
used between the first 30-day period
within a 60-day episode and the second
30-day period within a 60-day episode.
Episodes have more visits, on average,
during the first 30 days compared to the
last 30 days (see Tables 22 and 23).
Costs are much higher earlier in the
episode and lesser later on, therefore,
dividing a single 60-day episode into
two 30-day periods more accurately
apportions payments. This difference in
resource use between the first and
second 30-day period within a 60-day
episode is one of the main reasons we
are proposing 30-day periods of
payment for the HHGM. Another reason
for proposing to change the unit of
payment from 60-days to 30-days is the
removal of the therapy visit thresholds
from the case-mix adjustment
methodology under the HHGM (the
current system accounts for therapy
visit variation through the use of these
thresholds). Without thresholds being
used to account for resource use
variation, a shorter period of care is
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Physical
therapy
Occupational
therapy
1.14
1.40
1.16
1.39
needed to reduce the variation and
improve the accuracy of the case-mix
weights generated under the HHGM.
The HHGM’s goodness of fit statistics
(for example, R-squared) improve due to
reduced resource use variation when a
shorter, more constrained time period is
examined. Therefore, the case-mix
weights and proposed move to a 30-day
period under the HHGM better
approximate relative resource use.
Furthermore, by switching to a 30-day
period, the billing cycle for Medicare
home health services would be the same
as for other Medicare health care
settings, such as hospices and SNFs,
which currently bill on a monthly basis.
Using two segments of the current 60day episodes, 30-day periods were
constructed as follows for the
development of the HHGM:
• A 30-day period comprising days 1–
30 of a current 60-day episode where
‘‘day 1’’ is the current 60-day episode’s
From Date.
• A second period comprising days
31 and above of a current 60-day
episode. This period would be 30-days
in length if the current episode was 60days (from the From Date of the episode
to the Through Date of the episode) and
some lesser length if the current episode
were fewer than 60-days.
A typical 60-day episode was broken
down into two portions: A first 30-day
period; and a second 30-day period
consisting of the remaining days. For
example, if the current episode was 58
days, then the first period was 30-days,
and the second period was comprised of
the remaining 28 days. Resource
utilization was calculated for each 30day period based on the discipline visits
that occur within each respective 30-day
time span. The OASIS information that
is applied to the two 30-day periods (for
example, OASIS information) is
established by the same OASIS that is
linked to the current 60-day episode.
Table 22 shows the average number of
visits by discipline and resource use
estimates during 15-day periods in a 60day episode, and shows that visit
patterns differ over the course of a 60day episode. Across all labor categories
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Speech
therapy
1.24
1.50
Medical
social service
1.36
0.95
Home
health aide
0.41
0.36
there is a decline in visits as the episode
proceeds; in total there are 6.8 visits on
average in days 1–15 and 2.6 visits on
average in days 46–60 which is a 61.8
percent decline from the first 15 days of
care in a 60-day episode to the last 15
days of care in a 60-day episode.
Table 23 shows the average number of
visits and resource use estimates by
discipline during 15-day periods in a
60-day episode, but for only those
episodes that are first in a sequence of
episodes and last a full 60-days. A
sequence of episodes contains episodes
where no more than 60-days elapse from
the end of one episode to the start of the
next. Therefore, first episodes are those
where the beneficiary has not had home
health in the 60-days prior to the start
of the first episode. Even among this
subset of episodes, there is a decline in
average visits by quarter as the episode
proceeds.
These results show that there is
variation in average resource use across
60-day episodes. By moving to two 30day periods within a 60-day episode (or
a single 30-day period if the 60-day
episode contains 30 or fewer days), the
HH PPS case mix weights better align
with the resource use patterns across the
current 60-day episode. Though the
analyses are based on two 30-day
periods in a 60-day episode, we are not
proposing a change in the requirements
for completing the comprehensive
assessment. Under the HHGM, the
comprehensive assessment would still
be required, as outlined in § 484.55
roughly every 60-days as is required
under the current HH PPS. While we
examined resource use in 15-day
periods in a 60-day episode of care, as
outlined in Tables 22 and 23, in order
to strike an appropriate balance between
increasing payment accuracy and being
cognizant of increasing burden for the
home health industry, we are not
proposing to adjust payments every 15
days. We expect that billing on a 30-day
basis should not be completely
unfamiliar to HHAs as HHAs billed as
such prior to the implementation of the
HH PPS.
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Federal Register / Vol. 82, No. 144 / Friday, July 28, 2017 / Proposed Rules
TABLE 22—AVERAGE VISITS PER 15 DAYS DURING A 60-DAY EPISODE
Days 1–15
Average
Average
Average
Average
Average
Average
Average
Days 16–30
Days 31–45
Days 46–60
Daily Resource Use ..........................................................................
Skilled Nursing Visits .........................................................................
PT Visits ............................................................................................
OT Visits ............................................................................................
SLP Visits ..........................................................................................
Aide Visits .........................................................................................
MSS Visits .........................................................................................
$261.97
3.3
2.2
0.6
0.1
0.5
0.1
$162.44
2.1
1.7
0.5
0.1
0.5
0.0
$107.49
1.6
1.0
0.3
0.1
0.4
0.0
$88.67
1.4
0.6
0.2
0.0
0.3
0.0
Average Total Visits .................................................................................
6.8
4.9
3.3
2.6
TABLE 23—AVERAGE VISITS PER 15 DAYS DURING A 60-DAY EPISODE
[Only First Episodes in a Sequence of Episodes That Last a Full 60-Days]
Days 1–15
Days 31–45
Days 46–60
Daily Resource Use ..........................................................................
Skilled Nursing Visits .........................................................................
PT Visits ............................................................................................
OT Visits ............................................................................................
SLP Visits ..........................................................................................
Aide Visits .........................................................................................
MSS Visits .........................................................................................
$326.78
3.9
2.6
0.8
0.1
0.5
0.1
$217.75
2.5
2.4
0.8
0.2
0.5
0.1
$174.82
2.2
1.7
0.5
0.1
0.5
0.0
$167.69
2.3
1.4
0.4
0.1
0.4
0.0
Average Total Visits .................................................................................
8.1
6.4
5.1
4.6
mstockstill on DSK30JT082PROD with PROPOSALS2
Overall, approximately 25 percent of
episodes are 30 days or less in length,
and therefore, would produce no second
30-day period under the HHGM. These
episodes (with 30 days or fewer) would
convert to only one 30-day period each;
any 60-day episode that is 31 days or
more would produce two 30-day
periods: A first period comprising 30
days in length and then a second period
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with the remaining days in the 60-day
episode.
Overall, after conversion from the
5,110,629 60-day episodes, there were
8,642,107 30-day periods:
• There were 1,197,740 30-day
periods that could potentially be one-toone conversions from 60-day episodes
that were 30-days or fewer in length.
• Additionally, there were 3,912,889
60-day episodes that were between 31
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Sfmt 4725
and 60-days in length in which two 30day periods could be produced. That is,
those 60-day episodes could produce up
to 7,825,778 30-day periods.
• However, from the above episodes
(which were used to create the 30-day
periods), there were 381,411 periods
that had no visits included or were
considered a LUPA under the HHGM
and therefore were excluded. This is
shown in Table 24.
E:\FR\FM\28JYP2.SGM
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EP28JY17.004</GPH>
Average
Average
Average
Average
Average
Average
Average
Days 16–30
Federal Register / Vol. 82, No. 144 / Friday, July 28, 2017 / Proposed Rules
Tables 25 and 26 show the frequency
of episode length in days and estimates
of resource use among the original, 60day episodes and the corresponding
distribution of episode length and
resource use estimates among the
simulated 30-day periods. Again, these
results show differences by the length of
care. By shortening the unit of time that
CMS pays for within the HH PPS (from
35303
60-day episodes to 30-day periods),
payment would more accurately relate
to the variation in costs seen across
episodes and periods of care.
TABLE 25—FREQUENCY OF LENGTH OF 60-DAY EPISODES AND AVERAGE RESOURCE USE FOR EPISODES OF A CERTAIN
LENGTH
mstockstill on DSK30JT082PROD with PROPOSALS2
Length of
episode
in days
Number of
episodes
Percent of
episodes
Average
resource use
Standard
deviation of
resource use
25th
Percentile of
resource use
Median
resource use
75th
Percentile of
resource use
1 ...................................
2 ...................................
3 ...................................
4 ...................................
5 ...................................
6 ...................................
7 ...................................
8 ...................................
9 ...................................
10 .................................
11 .................................
12 .................................
13 .................................
14 .................................
15 .................................
16 .................................
17 .................................
18 .................................
19 .................................
20 .................................
21 .................................
22 .................................
23 .................................
24 .................................
25 .................................
26 .................................
27 .................................
28 .................................
29 .................................
30 .................................
31 .................................
32 .................................
33 .................................
34 .................................
35 .................................
36 .................................
37 .................................
38 .................................
39 .................................
40 .................................
41 .................................
42 .................................
43 .................................
44 .................................
45 .................................
46 .................................
47 .................................
48 .................................
49 .................................
50 .................................
51 .................................
52 .................................
53 .................................
54 .................................
55 .................................
56 .................................
57 .................................
58 .................................
59 .................................
60 .................................
189
1,204
3,796
6,051
9,385
11,793
16,587
19,887
21,026
25,724
29,757
34,725
40,923
49,796
55,035
47,921
48,442
48,802
48,998
53,699
59,071
66,055
58,291
59,211
58,481
58,245
63,077
67,228
73,202
61,139
54,481
48,964
45,330
47,568
50,567
54,810
44,844
43,262
40,322
39,193
42,316
43,428
44,866
36,714
34,973
32,604
31,457
33,588
35,758
38,505
34,081
35,200
37,353
42,039
57,053
133,103
134,831
124,027
131,881
2,339,771
0.0
0.0
0.1
0.1
0.2
0.2
0.3
0.4
0.4
0.5
0.6
0.7
0.8
1.0
1.1
0.9
0.9
1.0
1.0
1.1
1.2
1.3
1.1
1.2
1.1
1.1
1.2
1.3
1.4
1.2
1.1
1.0
0.9
0.9
1.0
1.1
0.9
0.8
0.8
0.8
0.8
0.8
0.9
0.7
0.7
0.6
0.6
0.7
0.7
0.8
0.7
0.7
0.7
0.8
1.1
2.6
2.6
2.4
2.6
45.8
$390.10
542.52
673.54
751.09
829.89
873.31
941.17
972.38
1,024.75
1,078.33
1,130.59
1,210.00
1,264.30
1,328.34
1,348.52
1,386.45
1,417.42
1,467.76
1,538.06
1,583.97
1,649.78
1,678.50
1,743.90
1,797.28
1,847.21
1,919.71
1,976.10
2,038.34
2,056.06
2,131.43
2,054.35
2,106.57
2,162.62
2,249.85
2,323.60
2,355.59
2,429.51
2,474.67
2,521.79
2,611.98
2,676.84
2,717.91
2,723.30
2,784.62
2,825.00
2,843.98
2,901.93
2,967.28
2,985.66
3,006.91
3,069.10
3,044.64
3,041.44
3,050.40
3,031.82
2,739.54
2,910.43
2,979.59
3,056.59
3,167.25
$200.87
348.55
418.19
474.35
521.12
505.81
560.28
556.43
592.64
623.90
645.67
661.38
704.44
737.07
744.31
780.24
818.41
851.49
887.62
897.61
939.64
958.48
995.17
1,026.42
1,059.00
1,098.44
1,115.08
1,156.00
1,176.25
1,219.42
1,239.89
1,320.10
1,347.74
1,433.54
1,436.69
1,436.60
1,534.67
1,561.76
1,611.74
1,669.37
1,652.00
1,713.02
1,692.49
1,751.30
1,800.40
1,881.88
1,914.85
1,890.38
1,881.80
1,948.18
1,987.99
1,968.48
2,031.19
1,995.63
1,993.77
1,902.85
1,957.02
2,032.32
2,106.81
2,582.35
$348.85
453.72
596.78
667.26
730.17
785.61
838.68
875.29
920.13
965.80
1,021.82
1,094.30
1,138.39
1,194.49
1,210.83
1,245.80
1,265.56
1,311.49
1,377.47
1,427.87
1,482.19
1,501.48
1,565.59
1,605.71
1,656.07
1,734.72
1,799.37
1,845.61
1,850.93
1,925.44
1,844.53
1,876.72
1,940.78
2,011.03
2,094.77
2,133.82
2,185.85
2,208.94
2,258.31
2,348.75
2,433.86
2,433.05
2,429.86
2,489.70
2,498.55
2,516.21
2,568.74
2,637.52
2,661.29
2,656.75
2,711.23
2,699.22
2,656.68
2,691.98
2,686.03
2,402.36
2,568.83
2,616.53
2,671.40
2,584.60
$249.99
318.34
403.37
447.37
506.40
542.35
588.23
613.68
641.04
671.36
708.30
769.13
791.18
829.00
840.75
850.81
865.41
883.41
926.88
954.98
995.89
1,012.61
1,047.09
1,085.07
1,103.81
1,145.08
1,188.51
1,229.39
1,227.68
1,266.69
1,175.90
1,183.96
1,206.50
1,250.25
1,331.92
1,372.34
1,389.64
1,423.02
1,429.43
1,487.83
1,570.54
1,570.70
1,594.39
1,608.51
1,617.88
1,592.33
1,637.72
1,692.59
1,728.52
1,714.03
1,754.01
1,730.90
1,663.20
1,681.25
1,655.26
1,337.71
1,506.89
1,506.76
1,531.18
1,381.40
$495.03
673.97
846.78
940.19
1,021.84
1,083.79
1,152.63
1,200.88
1,272.40
1,345.45
1,418.14
1,515.79
1,585.99
1,667.27
1,697.71
1,754.75
1,796.48
1,864.69
1,955.85
2,014.18
2,097.03
2,129.05
2,225.60
2,292.14
2,363.45
2,456.08
2,534.66
2,608.78
2,630.45
2,748.63
2,664.68
2,745.18
2,828.61
2,928.78
3,004.86
3,017.30
3,114.63
3,166.09
3,244.51
3,344.28
3,392.77
3,486.36
3,475.35
3,560.94
3,621.28
3,649.60
3,722.24
3,802.17
3,810.65
3,846.70
3,911.27
3,902.26
3,911.30
3,935.63
3,929.67
3,653.27
3,835.12
3,934.52
4,042.43
4,146.38
Total ......................
5,110,629
100.0
2,668.61
2,167.89
2,126.24
1,223.35
3,471.50
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Federal Register / Vol. 82, No. 144 / Friday, July 28, 2017 / Proposed Rules
TABLE 26A—FREQUENCY OF LENGTH OF 30-DAY PERIODS AND AVERAGE RESOURCE USE FOR EPISODES OF A CERTAIN
LENGTH
Length of
period
in days
Number of
periods
Percent of
periods
Average
resource use
Standard
deviation of
resource use
25th
Percentile of
resource use
Median
resource use
75th
Percentile of
resource use
3,524
8,369
15,906
23,219
32,751
41,608
43,863
51,527
52,384
57,437
64,917
71,310
79,309
81,603
86,340
77,411
77,257
79,981
82,356
89,669
91,247
99,530
94,124
99,779
113,978
188,106
195,398
189,012
202,819
6,247,373
0.0
0.1
0.2
0.3
0.4
0.5
0.5
0.6
0.6
0.7
0.8
0.8
0.9
0.9
1.0
0.9
0.9
0.9
1.0
1.0
1.1
1.2
1.1
1.2
1.3
2.2
2.3
2.2
2.3
72.3
$324.24
388.82
457.10
505.38
548.40
574.07
659.05
701.40
750.57
821.25
871.27
937.62
990.00
1,097.23
1,154.17
1,180.96
1,217.06
1,251.95
1,296.30
1,336.50
1,426.72
1,472.50
1,494.61
1,513.58
1,486.39
1,282.22
1,372.37
1,465.50
1,541.39
1,719.92
$263.35
369.29
366.59
421.31
454.32
450.58
534.21
524.40
575.81
612.49
626.24
667.37
697.39
740.41
754.00
793.23
828.31
846.54
881.05
899.78
942.61
956.21
993.71
1,018.60
1,035.65
1,006.44
1,038.05
1,086.75
1,118.11
1,375.02
$280.90
315.71
362.89
389.49
422.29
448.54
512.49
566.85
606.90
679.85
738.18
791.38
832.05
943.52
999.52
1,017.08
1,044.18
1,070.55
1,109.47
1,144.26
1,230.61
1,274.66
1,285.28
1,302.00
1,260.53
1,027.40
1,126.05
1,219.26
1,295.04
1,396.74
$211.49
239.78
264.75
278.90
293.29
304.63
332.18
362.61
383.81
416.34
452.60
482.71
514.47
584.53
634.63
634.79
656.03
665.44
687.23
709.84
773.65
809.29
793.44
791.75
749.62
550.41
617.79
668.85
727.83
728.43
$370.04
433.16
533.87
600.01
661.01
704.08
825.53
892.13
957.98
1,056.92
1,118.16
1,220.16
1,288.99
1,432.03
1,495.77
1,538.93
1,579.78
1,632.13
1,690.54
1,748.36
1,859.45
1,910.76
1,959.20
1,989.40
1,964.15
1,727.53
1,844.29
1,967.27
2,060.18
2,305.59
Total ......................
mstockstill on DSK30JT082PROD with PROPOSALS2
1 ...................................
2 ...................................
3 ...................................
4 ...................................
5 ...................................
6 ...................................
7 ...................................
8 ...................................
9 ...................................
10 .................................
11 .................................
12 .................................
13 .................................
14 .................................
15 .................................
16 .................................
17 .................................
18 .................................
19 .................................
20 .................................
21 .................................
22 .................................
23 .................................
24 .................................
25 .................................
26 .................................
27 .................................
28 .................................
29 .................................
30 .................................
8,642,107
100.0
1,585.48
1,289.23
1,262.65
671.96
2,119.49
The 60-day episode unit of payment
was originally implemented on October
1, 2000, because most episodes in the
HHA per-episode PPS demonstration,
which was used to inform the
development of the HH PPS, ended in
60 days or less, the OASIS data would
be captured on a 60-day cycle, and
Medicare plan of care/certification
requirements continue to be bimonthly
(64 FR 58143). In the FY 2001 HH PPS
proposed rule, we noted that about 60
percent of episodes paid under the HH
PPS were completed within one 60-day
episode and 73 percent within two 60day episodes. In the FY 2001 HH PPS
final rule, we noted that we would
continue to monitor the appropriateness
of the 60-day unit of payment, and
would consider modifying our approach
to the episode definition in subsequent
years of PPS, if warranted (65 FR
41136).
In CY 2016, 73 percent of episodes
were completed within one 60-day
episode and 86 percent within two 60day episodes. We currently observe
wide variation in the length of care in
the current HH PPS. Overall, the average
length of home health care was
approximately 46 days, but roughly a
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quarter of all 60-day episodes lasted 30
days or less. For example, those
episodes that had a hospital stay in the
seven days prior to the start of the
episode where the Diagnosis Related
Group (DRG) was either 469 or 470
(major joint replacement or
reattachment of lower extremity) had an
average length equal to 23.7 days. As
noted above, there is a decline in visits
as the episode proceeds with a 61.8
percent decline from the first 15 days of
care in a 60-day episode to the last 15
days of care in a 60-day episode.
The wide variation in resource use
and trends toward shorter episodes of
care, the difference in resources
between the first and second 30-day
period within a 60-day episode, and the
removal of the therapy visit thresholds
from the case-mix adjustment
methodology (which currently account
for variation in resource use, but create
adverse incentives as outlined in section
II.D of this proposed rule) result in less
accurate case-mix weights. When a
shorter, more constrained time period is
used for payment, the HHGM’s
goodness of fit statistics (for example, Rsquared) improve due to reduced
resource use variation. Accordingly, the
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Sfmt 4702
case-mix weights under the HHGM
better approximate relative resource use.
Therefore, we are proposing to change
the unit of payment under section
1895(b)(2) of the Act from a 60-day
episode of care to 30-day periods of
care. Section 1895(b)(2) of the Act
requires the Secretary to consider
potential changes in the mix of services
provided within that unit and their cost.
Our analysis shows evidence of a
change in the mix of services under a
60-day episode of care, as outlined
above and in section II.D of this
proposed rule. Therefore, to better
account for changes in the mix of
services over time; to ensure that the
unit of payment reflects an appropriate
number, type, and duration of visits
provided within a unit of payment; and
to provide continued access to quality
services, we are proposing to change the
unit of payment from a 60-day episode
of care to a 30-day period of care and
to implement case-mix adjustment
methodology refinements, outlined in
sections III.E.1 through III.E.12 of this
proposed rule.
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Federal Register / Vol. 82, No. 144 / Friday, July 28, 2017 / Proposed Rules
b. National, Standardized 30-Day
Payment Amount
We note that we propose to
implement the HHGM for 30-day
periods of care beginning on or after
January 1, 2019.26 As a result, we would
calculate a proposed national,
standardized 30-day payment amount in
the CY 2019 HH PPS proposed rule. In
calculating a national, standardized 30day payment amount for CY 2019, we
propose to start with the CY 2019
national, standardized 60-day episode
payment amount reflecting the HHA
market basket update as specified in
section 1895(b)(3)(B) of the Act, add
back in the CY 2019 non-routine
medical supply (NRS) conversion factor
amount reflecting the HHA market
basket update as specified in section
1895(b)(3)(B) of the Act, and then divide
the sum by two.
If we had proposed to implement the
HHGM in CY 2018, we would have
calculated a proposed 30-day payment
amount for CY 2018 by starting with the
CY 2018 proposed national,
standardized 60-day episode payment
amount of $3,038.43, adding back in the
CY 2018 proposed NRS conversion
factor amount of $53.03, and dividing
the sum by two to produce a 30-day
payment amount of $1,545.73. However,
we reiterate that we propose to
implement the HHGM for 30-day
periods of care beginning on or after
January 1, 2019; so we propose to
calculate a national, standardized 30day payment amount for CY 2019 using
the CY 2019 60-day episode payment
amount, adding back in the CY 2019
NRS conversion factor and dividing the
sum by two to produce a 30-day
payment amount. Finally, we note that
the calculation proposed above would
only be used to calculate a national,
standardized 30-day payment amount
for CY 2019. To calculate a national,
standardized 30-day payment amount
for CY 2020 and subsequent years, we
would update the national, standardized
30-day payment amount from the
immediate preceding year by the home
health payment update percentage
required by the statute, as described in
section III.C.1 of this rule.
In determining the 30-day payment
amount, we evaluated whether starting
with the national, standardized 60-day
episode payment amount, adding back
in the NRS conversion factor amount
and dividing the sum by two was an
appropriate estimate of the cost of a 30day period of care. Section 1895(b)(3) of
the Act provides a methodology for
determining an initial payment amount
for the PPS and for calculating annual
increases. As noted in this proposed
rule, the Act at section 1895(b)(2) gives
the Secretary the discretion to
determine the ‘‘unit of payment’’ (also
referred to in the statute as a ‘‘unit of
service’’) on which a standard
prospective payment amount would be
based. Since we are proposing to change
the unit of payment, we believe it is
necessary to calculate a 30-day payment
amount that would accurately reflect
what a 30-day payment would be had
we chosen to use a 30-day rather than
a 60-day unit of payment when we first
implemented the PPS.
To do this, we calculated an estimated
30-day payment amount by taking the
average number of visits per discipline
per 30-day period of care in CY 2016
multiplied by the FY 2001 per-visit
amounts (including average NRS costs
per visit) initially established under the
HH PPS based on the most recent
audited cost report data available to the
Secretary in accordance with section
1895(b)(3)(A)(I) of the Act, as adjusted
for inflation and productivity. The FY
2001 per-visit amounts were adjusted
for inflation by the actual HHA market
basket updates (reflecting historical data
from FY 2002 to CY 2016), the
regulatory HHA market basket updates
for CY 2017 (which is based on the CY
2017 forecasted data at the time of CY
2017 rulemaking (81 FR 76714)) and CY
2018 (which is based on the CY 2018
forecasted data in this CY 2018
proposed rule), and for productivity
(using Economy-wide Multifactor
Productivity as specified in section
1895(b)(3)(B)(vi) to the Act and
described in section 1886(b)(3)(B)(xi)(II)
of the Act) beginning in 2015, as
reflected in Table 26B.
TABLE 26B—HHA MARKET BASKET UPDATES AND PRODUCTIVITY ADJUSTMENTS, FY 2002 THROUGH CY 2018
FY 02
Market Basket Update (Historical Data FY02 to CY16,
forecast CY17 and CY18) ............................................
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Market Basket Update (Historical FY02 to CY16, forecast CY 17 and CY 18) ................................................
Multi-Factor Productivity Adjustment (historical CY15,
preliminary historical CY16, forecast CY17 and CY18)
FY 03
FY/CY
04*
CY 05
CY 06
CY 07
CY 08
CY 09
CY 10
3.4
............
CY 11
3.2
............
CY 12
4.0
............
CY 13
3.1
............
CY 14
3.1
............
CY 15
3.5
............
CY 16
3.2
............
CY 17
1.7
............
CY18
1.7
............
............
2.0
1.7
1.6
1.6
1.6
2.0
2.8
2.7
............
............
............
............
............
0.4
0.6
0.3
0.5
............
As shown in Table 28, using the FY
2001 per-visit amounts initially
established under the HH PPS results in
an estimated 30-day payment amount of
$1,494.64. This value is less than, but
similar to half the sum of the proposed
CY 2018 national, standardized 60-day
episode payment amount and proposed
CY 2018 NRS conversion factor amount
($1,545.73).
We also calculated an estimated 30day payment amount by taking the
average number of visits per discipline
per 30-day period of care in CY 2016
multiplied by the FY 2015 costs-pervisit, per discipline, based on the most
recent cost report data available at the
time of CY 2018 HH PPS rulemaking (as
outlined in Table 2 in section III.A of
this proposed rule) and further adjusted
to include average NRS costs per visit,
for outliers in accordance with section
1895(b)(3)(C) of the Act, and for
inflation and productivity. As shown in
Table 29, using 2015 costs-per-visit, per
discipline, based on the most recent cost
report data available at the time of CY
2018 HH PPS rulemaking, results in an
estimated 30-day payment amount of
$1,485.11. This value is also less than,
but similar to half the sum of the
proposed CY 2018 national,
standardized 60-day episode payment
amount and proposed CY 2018 NRS
conversion factor amount ($1,545.73).
26 60-day episodes of care that begin on or before
December 31, 2018 and end on or after January 1,
2019, will be paid using the current case-mix
adjustment methodology (153-group system) and a
CY 2019 national, standardized 60-day episode
payment amount and/or CY 2019 national per-visit
amounts.
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TABLE 27—AVERAGE VISITS PER DISCIPLINE FOR 30-DAY PERIODS OF
CARE, CY 2016
TABLE 27—AVERAGE VISITS PER DISCIPLINE FOR 30-DAY PERIODS OF
CARE, CY 2016—Continued
CY 2016 Average number of
visits in 30-day
period
Discipline
Skilled Nursing ......................
Physical Therapy ..................
Occupational Therapy ..........
Speech-Language Pathology
Medical Social Services .......
5.0
3.3
0.9
0.2
0.1
TABLE 27—AVERAGE VISITS PER DISCIPLINE FOR 30-DAY PERIODS OF
CARE, CY 2016—Continued
CY 2016 Average number of
visits in 30-day
period
Discipline
Home Health Aides ..............
CY 2016 Average number of
visits in 30-day
period
Discipline
Total ...............................
1.0
10.5
Source: CY 2016 claims data (as of March
17, 2017), excluding 30-day periods of care
with no visits and those classified as LUPAs
as outlined in section III.E.9 of this proposed
rule.
TABLE 28—ESTIMATED 30-DAY PAYMENT AMOUNT IN CY 2018 (USING FY 2001 HH PPS PER-VISIT AMOUNTS, PER
DISCIPLINE, ADJUSTED FOR INFLATION AND FOR PRODUCTIVITY BEGINNING IN 2015)
FY 2001 pervisit amounts 1
Discipline
FY 2001 pervisit amounts
trended forward to 2018
CY 2016 average number of
visits in 30-day
period
CY 2018 30day period
costs
Skilled Nursing .................................................................................................
Physical Therapy .............................................................................................
Occupational Therapy ......................................................................................
Speech-Language Pathology ..........................................................................
Medical Social Services ...................................................................................
Home Health Aides ..........................................................................................
$95.34
104.27
104.97
113.32
152.95
43.05
$143.03
156.43
157.48
170.01
229.47
64.59
5.0
3.3
0.9
0.2
0.1
1.0
$715.15
516.22
141.73
34.00
22.95
64.59
Total ..........................................................................................................
........................
........................
10.5
1,494.64
1
The FY 2001 per-visit amounts can be found in 65 FR 41187 through 41188 (Table 6).
Note(s): When the HH PPS was established on October 1, 2000, the original per-visit payment amounts for each discipline included a onetime adjustment of $0.21 to reflect the costs associated with OASIS assessment schedule refinements (65 FR 41187). In addition, the resulting
per-visit rates were then divided by 1.05 to account for the estimated percentage of outlier payments, a calculation further refined in the CY 2008
HH PPS final rule (72 FR 49868) by multiplying by 1.05 and 0.95. The FY 2001 per-visit amounts in the text reflect removing the $0.21 from the
FY 2001 per-visit amounts and include the effects of the CY 2008 outlier calculation refinement.
TABLE 29—ESTIMATED 30-DAY PAYMENT AMOUNT IN CY 2018 (USING FY 2015 AVERAGE COSTS-PER-VISIT, PER
DISCIPLINE, ADJUSTED FOR INFLATION AND FOR PRODUCTIVITY BEGINNING IN 2015)
FY 2015 average costs-pervisit
FY 2015 average NRS
costs-pervisit 1
FY 2015 average NRS
costs-per-visit
plus NRS
FY 2015 average costs-pervisit plus NRS
trended forward to 2018
Outlier adjustment factor
CY 2016 average number of
visits in 30-day
period
Skilled Nursing .............
Physical Therapy .........
Occupational Therapy ..
Speech-Language Pathology ......................
Medical Social Services
Home Health Aides ......
$132.48
156.32
154.64
+$3.36
3.36
3.36
$135.84
159.68
158.00
$144.29
169.61
167.83
× 0.95
× 0.95
× 0.95
5.0
3.3
0.9
$685.38
531.73
143.50
170.96
220.07
62.80
3.36
3.36
3.36
174.32
223.43
66.16
185.17
237.33
70.28
× 0.95
× 0.95
× 0.95
0.2
0.1
1.0
35.18
22.55
66.77
Total ......................
........................
........................
........................
........................
........................
10.5
1,485.11
Discipline
CY 2018 30day period
costs
1 Of
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the 8,032 FY 2015 HHA cost reports used for the analysis presented in Table 2 in section III.A of this proposed rule, NRS costs totaled
$301,207,702. For those same 8,032 HHAs, visits (all visits, all episode types) where the claim through date fell on or between the FY start end
date of the agency’s cost report totaled 89,726,272. $301,207,702 divided by 89,726,272 = $3.36 per visit.
We believe our proposal to start with
the national, standardized 60-day
episode payment amount, add back in
NRS conversion factor amount, and then
divide the sum by two is a reasonable
estimate of the cost of a 30-day period
of care. We propose to implement the
change in the unit of payment from 60day episodes of care to 30-day periods
of care in a non-budget neutral manner.
We note that in its March 2017 Report
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to Congress, MedPAC highlighted that
home health payments have
consistently and substantially exceeded
costs because agencies are able to
reduce the number of visits provided
and cost growth is generally lower than
the annual payment updates for home
health care.27 MedPAC recommended a
Payment Advisory Commission
(MedPAC). ‘‘Home Health Care Services.’’ Report to
Congress: Medicare Payment Policy. Washington,
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27 Medicare
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5 percent reduction in the base rate for
2018 and a 2-year rebasing beginning in
2019.28 We invite comments on the
proposed calculations for determining
the 30-day payment amount, including
our rationale for proposing to
DC, March 2017. P. 232. Accessed on July 16, 2017
at: https://www.medpac.gov/docs/default-source/
reports/mar17_medpac_ch9.pdf?sfvrsn=0.
28 Ibid.
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implement the HHGM in a non-budget
neutral manner.
We are further proposing to
implement the HHGM in a fully nonbudget neutral manner beginning in CY
2019 or alternatively to use a phased
approach to implementation. We
acknowledge that implementing the
HHGM in a partially budget-neutral
manner could lessen the economic
impact for HHAs in transitioning to the
HHGM. Therefore, we considered
potential alternative implementation
approaches for the HHGM, including,
but not limited to, a partially budgetneutral approach with a phase-out
period. Specifically, for the phased
approach, we propose to apply a HHGM
partial budget neutrality adjustment
factor in CY 2019 that would reduce the
estimated impact of the HHGM from an
estimated ¥4.3 percent to ¥2.2 percent
in the initial year of implementation
with the removal of the HHGM partial
budget neutrality adjustment factor in
CY 2020. We invite comments on
whether to implement the HHGM in a
fully non-budget neutral manner
beginning in CY 2019; whether to
alternatively implement the HHGM in
CY 2019 with a HHGM partial budget
neutrality adjustment factor applied and
then subsequently removed in CY 2020;
or whether a HHGM partial budget
neutrality adjustment factor should be
applied and then phased-out over a
longer period of time.
c. Split Percentage Payment Approach
for 30-Day Periods of Care
In the current HH PPS there is a split
percentage payment approach to the 60day episode. The first bill, a Request for
Anticipated Payment (RAP), is
submitted at the beginning of the
episode. The second, final bill is
submitted at the end of the 60-day
episode of care. An initial percentage
payment of 60 percent of the anticipated
final claim payment amount is paid at
the beginning of the episode and a final
percent payment of 40 percent is paid
at the end of the episode. For all
subsequent episodes for beneficiaries
who receive continuous home health
care, the episodes are paid at a 50/50
percentage payment split. A new initial
and final bill must be submitted for each
60-day episode period. HHAs are
encouraged to submit the RAP as soon
as possible after care begins to assure
being established as the primary HHA
for the beneficiary and so that the
claims processing system is alerted that
a beneficiary is under a HH episode of
care to enforce the consolidating billing
edits required by law.
We are not proposing a change to the
split percentage payment approach in
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conjunction with proposing to change
the unit of payment from a 60-day
episode to a 30-day period of care.
Under the proposed HHGM, we propose
that the initial payment for initial 30day periods would be paid at 60 percent
of the case-mix and wage-adjusted 30day payment rate. The residual final
payment for initial 30-day periods
would be paid at 40 percent of the casemix and wage-adjusted 30-day payment
rate. We propose the initial payment for
subsequent 30-day periods would be
paid at 50 percent of the case-mix and
wage-adjusted 30-day payment rate. The
residual final payment for subsequent
30-day periods would be paid at 50
percent of the case-mix and wageadjusted 30-day payment rate.
However, we note the length of time
HHAs currently take to submit the RAP
indicates that the RAP payment might
not be necessary for the majority of
HHAs to maintain an adequate cash
flow (see Table 30). Approximately 5
percent of RAPs (95th percentile) are
not submitted until the end of an
episode of care and the median length
of days for RAP submission is 12 days
from the start of the episode. In
addition, eliminating RAP payments
would address existing program
integrity vulnerabilities. For example,
$1.8 billion in RAP payments (July 1,
2015 through July 31, 2016) were autocancelled, and of that amount, a final
claim was never submitted for $321
million worth of RAP payments.29
TABLE 30—NUMBER OF DAYS FROM
THE START OF CARE TO INITIAL RAP
SUBMISSION
Number of
days from the
start of care to
initial RAP
submission
Percentile
1 ............................................
10 ..........................................
25 ..........................................
50 ..........................................
75 ..........................................
90 ..........................................
95 ..........................................
99 ..........................................
1
5
8
12
21
36
57
169
Source: Analysis of CWF data from July 1,
2015 through July 31, 2016 and HIGLAS payments and recoupments.
We are soliciting comments as to
whether the split payment approach
would still be needed for HHAs to
maintain adequate cash flow if the unit
of payment changes from 60-day
29 A RAP is auto-cancelled and recouped on the
next disbursement if the final claim is not received
within 4 months of the start of care or within 2
months of when the RAP was paid (whichever is
greater).
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35307
episodes to 30-day periods of care under
our proposal. In addition, we are
soliciting comments on ways to phaseout the split percentage payment
approach in the future if the proposed
HHGM is finalized with the split
percentage payment approach being
initially maintained. Specifically, we
are soliciting comments on reducing the
percentage of the upfront payment over
a period of time. We believe that
payment based on 30-day periods would
reduce, if not eliminate, the need for
these partial, up-front payments that
occur in the current payment system.
Home health agencies would bill on a
monthly basis, similar to hospices and
SNFs, and thus receive final payment
sooner.
If in the future the split percentage
approach was eliminated, we are also
soliciting comments on the need for
HHAs to submit a notice of admission
within 5 days of the start of care to
assure being established as the primary
HHA for the beneficiary and so that the
claims processing system is alerted that
a beneficiary is under a HH period of
care to enforce the consolidating billing
edits required by law.
We invite comments on the proposed
change in the unit of payment from a
60-day episode of care to a 30-day
period of care under the HHGM; the
calculation of the national, standardized
30-day payment amount, initially
maintaining the split percentage
payment approach and applying such
policy to 30-day periods of care; and the
associated regulations text changes
outlined in section III.E.13. of this
proposed rule. We are also soliciting
comments on ways the split percentage
payment approach could be phased-out
and whether to implement a notice of
admission process if the split percentage
payment approach is eliminated in the
future.
4. Episode Timing Categories
To advance the goals of better aligning
payment with patient needs, as well as
addressing payment incentives and
vulnerabilities within the current
system, we investigated the impact of
episode timing on home health resource
use. In the current payment system, 60day episodes are classified as ‘‘early’’ if
they are the first or second in a
sequence of episodes and ‘‘late’’ if they
are the third or later in the sequence.
Episodes are defined as being in the
same sequence if there are no more than
60 days between the end of one episode
and the start of the next. In the
development of the proposed HHGM,
we sought to evaluate whether
payments to providers appropriately
reflect the varying resource needs of
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home health beneficiaries during
various portions of the home health
stay, accounting for contrasting patient
characteristics.
We endeavored to evaluate whether
beneficiaries in their first 30-day period
of care have different needs and patterns
of resource use than those in later 30day periods, thus possibly resulting in
the potential need for differentiated
payment amounts. We reviewed related
research, held technical and clinical
expert panels, and performed our own
investigative analyses. In particular, we
were interested in whether home health
patients utilize more resources at the
beginning of home health than in later
periods of the home health stay, and, if
so, does the current payment structure
sufficiently account for this elevated
need. In a review of research related to
episode timing, studies show that more
frequent skilled visits in the first few
weeks of a home health stay can prove
beneficial for certain diagnoses by
reducing the likelihood of readmission
to an institutional setting and easing the
transition from hospital to home, which
can be challenging for patients.
The Visiting Nurse Associations of
America defines ‘‘frontloading’’ as the
practice of providing an increase in
intensity of visits during the first two to
three weeks of the home health care
episode for patients that have been
determined to be at high risk for
hospitalization.30 A 2014 literature
review titled ‘‘Frontloading and
Intensity of Skilled Home Health Visits:
A State of the Science’’ found that
Medicare patients benefited from an
intensified level of care through a
‘‘frontloading’’ approach, which
reduced the need for re-hospitalization
among skilled home health patients, and
especially for those with heart failure.31
For the purposes of this particular
study, frontloading was defined as
providing 60 percent of planned visits
within the first 2 weeks of the home
health episode of care. Furthermore,
frontloading was also found by the
Briggs® National Quality Improvement/
Hospitalization Reduction Study,32 to
30 Care-Initiation-Frontloading. (n.d.). Retrieved
March 20, 2017, from https://vnaablueprint.org/
Care-Initiation-Frontloading.html.
31 O’Connor, M., Bowles, K.H., Feldman, P. H.,
´
Pierre, M. S., Jarrın, O., Shah, S., & Murtaugh, C.
M. (2014). Frontloading and Intensity of Skilled
Home Health Visits: A State of the Science.
Retrieved March 02, 2017, from https://
www.ncbi.nlm.nih.gov/pmc/articles/PMC4532304/.
32 Briggs National Quality Improvement/
Hospitalization * * * (n.d.). Retrieved March 2,
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be one of 15 best practices routinely
employed by 64 percent of the HHAs
who were most successful at reducing
hospitalizations. Similarly, in an article
titled ‘‘The Effect of Frontloading Visits
on Patient Outcomes,’’ 33 the authors
assessed the impact of frontloading on
patients with insulin-dependent
diabetes and with heart failure. In their
research, the authors found that
frontloading was effective for patients
with heart failure, decreasing rehospitalization by more than half (39.4
percent vs. 16 percent), with fewer visits
overall (15.5 vs. 9.5) and equal clinical
outcomes and patient satisfaction. These
improvements in overall outcomes were
presumably due to the timing of the
services, where more visits were
provided in the beginning portion of the
episode, even when fewer visits were
provided overall. However, we note that
there was no significant impact for those
patients with diabetes. No specific effect
for patients with mental health or
behavioral health conditions was noted.
Given the potential positive outcomes of
the practice of frontloading, specifically
for those beneficiaries with heart
disease, we expect that HHAs would
provide more frequent skilled services
in the beginning portion of a home
health stay to educate patients in
medication management, coordinate the
instruction of both the patient and
family, and support patients in
navigating their clinical situation,
especially in cases of heart disease. The
first and fourth reported top primary
reasons for home health care in CY 2016
were hypertension and heart failure,
respectively, and we therefore believe
an opportunity exists for HHAs to
improve the outcomes for these highvolume home health beneficiaries by
providing more resources in the early
period of a home health stay.
For many patients admitted to home
health, the transition from hospital or
other institutional settings back to the
home environment can be very
challenging and lead to adverse effects
for the beneficiary, such as medication
errors, harmful drug events, and
additional complications. The provision
of intensified home health services early
2017, from https://www.briggscorp.com/
ACHstrategies/BriggsStudy.pdf.
33 Rogers, J., Perlic, M., & Madigan, E. A. (2007).
The Effect of Frontloading Visits on Patient
Outcomes. Home Healthcare Nurse: The Journal for
the Home Care and Hospice Professional, 25(2),
103–109. doi:10.1097/00004045–200702000–00011;
https://www.ncbi.nlm.nih.gov/pubmed/17285038.
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in a home health stay can potentially
help to mitigate any negative events that
could result from this time of transition
from the institutional setting to the
home. As such, we would expect that
beneficiaries would require more
resources, particularly from skilled
disciplines providing teaching and
medication management, during the
first 30 days of a home health
admission.
As described in section III.E.3 of this
proposed rule, analysis of home health
data demonstrates that HHAs provide
more services in the first 30-day period
of home health than in later periods of
care. The differences in the resource
utilization during home health episodes
are presented in Table 22, which shows
the average resource use of home health
episodes divided into 15-day segments.
The first two 15-day periods in a home
health episode have significantly higher
average resource use at $261.97 and
$162.44, respectively, as compared with
the third and fourth 15-day segments in
a 60-day period, at $107.49 and $88.67,
respectively. Additionally, the average
number of visits by the six disciplines
is also significantly higher in the first
two 15-day segments, at 6.8 and 4.9
visits per segment, respectively as
compared to the third and fourth 15-day
segments of a 60-day episode, at 3.3 and
2.6, respectively.
Further analysis of home health data
demonstrates that under the current
payment system, when analyzed by 30day periods, HHAs provide more
resources in the first 30-day period of
home health (‘‘early’’) than in later
periods of care. The differences in the
average resource use during early and
late home health episodes when divided
into 30-day periods are presented in
Table 28, and shows the first 30-day
periods in a home health sequence have
significantly higher average resource use
at $2,102.29 as compared with
subsequent 30-day periods. Specifically,
the later 30-day periods showed an
average resource use of $1,348.18, a
difference of more than $700 or a 36
percent decrease. Table 31 also shows a
significant difference between the early
and late episode median values of
resource use. The median for the first
30-day period is $1,848.12, while the
median for subsequent 30-day periods is
$987.54, a difference of more than $850
or an approximately 47 percent
decrease.
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TABLE 31—AVERAGE RESOURCE USE BY TIMING (30 DAY PERIODS)
Timing
Average
resource use
($)
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Early Episodes .............
Late Episodes ..............
Total ......................
Number of
episodes
2,102.29
1,348.18
1,585.48
2,719,495
5,922,612
8,642,107
There is significant difference in the
resource utilization between early and
late 30-day periods as demonstrated in
Table 31. Moreover, the predictive
power of the HHGM in terms of
estimating resource utilization
improved when separating episodes into
30-day periods rather than 60-day
periods (that is, the first and second 30day periods). We believe that an HHGM
that accounts for the demonstrated
increase in resource utilization in the
first 30-day period better captures the
variations in resource utilization and
further promotes the goal of payment
accuracy within the HH PPS. We are
proposing to classify the 30-day periods
under the proposed HHGM as ‘‘early’’ or
‘‘late’’ depending on when they occur
within a sequence of 30-day periods.
For the purposes of defining ‘‘early’’ and
‘‘late’’ periods for the proposed HHGM,
we are proposing that only the first 30day period in a sequence of periods be
defined as ‘‘early’’ and all other
subsequent 30-day periods would be
considered ‘‘late’’. Additionally, we are
proposing that the definition of a ‘‘home
health sequence’’ (as currently
described in § 484.230) will remain
unchanged relative to the current
system, that is, 30-day periods are
considered to be in the same sequence
as long as no more than 60 days pass
between the end of one period and the
start of the next, which is consistent
with the definition of a ‘‘home health
spell of illness’’ described at section
1861(tt)(2) of the Act. We note that
because section 1861(tt)(2) of the Act is
a definition related to eligibility for
home health services as described at
section 1812(a)(3) of the Act, it does not
affect or restrict our ability to propose
a 30-day prospective payment period.
To identify the first 30-day period
within a sequence, the Medicare claims
processing system would verify that the
claim ‘‘From date’’ and ‘‘Admission
date’’ match. If this condition were to be
met, our systems would send the
‘‘early’’ indicator to the HH Grouper for
the 30-day period of care. When the
claim is received by CMS’s Common
Working File, the system would look
back 60 days to ensure there is not a
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Percent of
episodes
(%)
Standard
deviation of
resource use
($)
31.47
68.53
100.00
1,265.68
1,229.14
1,289.23
prior, related episode. If not, the claim
would continue to be paid as ‘‘early.’’ If
another related episode were to be
identified, that is an earlier 30-day
period in the sequence, the claim would
be returned to the shared systems for
subsequent regrouping and re-pricing.
Those periods that are not the first 30day period in a sequence of adjacent
periods, separated by no more than a 60
day gap, would be categorized as ‘‘late’’
periods and placed in corresponding
HHGM categories.
We invite public comments on the
timing categories in the proposed
HHGM and the associated regulations
text changes outlined in section III.E.13
of this proposed rule.
5. Admission Source Category
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) implementing
the HH PPS. In that final rule, we
discussed and finalized the use of a
methodology that included variables
identifying pre-admission location (that
is, whether certain inpatient and other
stays occurred in the 14-day period
immediately preceding the home health
episode) as part of our case-mix
adjustment methodology. We stated that
not only were pre-admission inpatient
stays a traditional indication of need in
clinical practice, but also that such
variables were useful correlates of
resource cost in our evaluation of the
home health case-mix data (65 FR
41146). This pre-admission information
was submitted by HHAs via OASIS
assessments.
In the CY 2008 HH PPS final rule, we
removed elements from the case-mix
adjustment methodology that were
based upon the source of admission (72
FR 49766). In the CY 2008 HH PPS
proposed and final rules, we assessed
variables for policy and payment
appropriateness and ultimately decided
to remove the variable that had been
used to identify the patient’s preadmission location from the case-mix
adjustment methodology (72 FR 25361
and 72 FR 49766, respectively). This
decision was based, in part, upon
concerns that some agencies were
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25th percentile
of resource
use ($)
1,213.51
537.85
671.96
Median
resource use
($)
1,848.12
987.54
1,262.65
75th
percentile
of
resource use
($)
2,681.90
1,760.20
2,119.49
encountering challenges in obtaining
concrete information regarding the
patient’s preadmission location while
performing the initial home health
assessment and thus the OASIS item
used to indicate the preadmission
location of the patient was not always
reliable. Moreover, the pre-admission
information did not perform well in
terms of the four-equation model used
for payment estimation and also had a
small impact in terms of payment
accuracy within the model. In the CY
2008 HH PPS final rule, we further
noted that the item’s results across the
four equation model created difficulties
in terms of interpretation and the
explanatory power (for example, its
contribution to the R-squared value) was
minimal (72 FR 49766).
For the purposes of constructing the
HHGM, which would not use a 4equation model or otherwise adjust
payments based on therapy visit
thresholds; we reexamined the impact
of beneficiary admission source, either
from the community or from an
institutional setting, on home health
resource use. In our review of related
scholarly research, we found that
beneficiaries admitted directly or
recently from an institutional setting
(acute or post-acute care (PAC)) tend to
have different care needs and higher
resource use than those admitted from
the community, thus indicating the
need for differentiated payment
amounts. For instance, a literature
review of 25 research studies published
between 2002 and 2011, titled
‘‘Hospitalization Among MedicareReimbursed Skilled Home Health
Recipients,’’ found that Medicare
beneficiaries discharged from PAC and
acute facilities differ significantly in
resource need when compared to
community-admitted beneficiaries.34
Patients discharged from acute and PAC
settings tend to be sicker upon
admission and are being discharged
rapidly back to the community.
Additionally, they are more likely to be
34 O’Connor, M. (2012, February). Hospitalization
Among Medicare-Reimbursed Skilled Home Health
Recipients. Retrieved March 02, 2017, from https://
www.ncbi.nlm.nih.gov/pmc/articles/PMC4690459.
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re-hospitalized after discharge due to
the acute nature of their illness. One
study discussed in this literature review
determined that patients being
discharged from an inpatient
hospitalization typically present with
multiple comorbidities, suggesting that
initially-hospitalized patients
subsequently transferred to home care
were more likely to have four or more
secondary diagnoses, as well as a
pressure or stasis ulcer, urinary
incontinence, a urinary catheter,
depression, or dyspnea.35 They
generally had more than five
medications than their non-hospitalized
counterparts and required assistance
with medication management.36 As
such, patients referred to home health
after an institutional stay tend to be
more infirm, requiring significant
resources upon admission to home
health. Additionally, the same literature
review also highlighted a study titled
‘‘Unplanned hospital readmissions: A
home care perspective’’ that
demonstrated that patients referred from
acute and PAC settings are at a high risk
of hospitalization within 14 to 21 days
of admission to home health.37 Given
that the first few weeks after an
institutional stay represent a critical
window in terms of providing
beneficiaries with appropriately
intensive supports and services, as well
as preventing re-hospitalization, we
would expect that providing care for
those beneficiaries admitted from
institutional settings would require
more resource use compared to patients
admitted to home health from the
community. Comprehensive and
deliberate interventions in this
timeframe could also potentially reduce
re-hospitalization rates.
Research studies also demonstrate
that patients admitted to home health
from institutional settings are more
vulnerable to adverse effects and injury
because of the functional decline that
occurs as a result of their institutional
stay, indicating that this patient
population requires more concentrated
resources and supports to account for
and mitigate this functional decline. In
35 Rosati, R. J., Huang, L., Navaie-Waliser, M., &
Feldman, P. H. (2003). Risk Factors for Repeated
Hospitalizations Among Home Healthcare
Recipients. Journal For Healthcare Quality, 25(2),
4–11. doi:10.1111/j.1945–1474.2003.tb01038.x.
36 Rosati, R. J., Huang, L., Navaie-Waliser, M., &
Feldman, P. H. (2003). Risk Factors for Repeated
Hospitalizations Among Home Healthcare
Recipients. Journal For Healthcare Quality, 25(2),
4–11. doi:10.1111/j.1945–1474.2003.tb01038.x.
37 Anderson, M. A., Helms, L. B., Hanson, K. S.,
& Devilder, N. W. (1999). Unplanned Hospital
Readmissions: A Home Care Perspective. Nursing
Research, 48(6), 299–307. doi:10.1097/00006199–
199911000–00005.
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the article titled ‘‘The Incidence and
Severity of Adverse Events Affecting
Patients after Discharge from the
Hospital,’’ 38 Alan J. Forster, MD noted
that beneficiaries are susceptible to
harm post-hospitalization: ‘‘Patients
may be especially vulnerable to injuries
during this [post-discharge] period
because they may still have functional
impairments and because
discontinuities may occur at the
interface of acute and ambulatory care.’’
The author also notes that the current
health care environment encourages
potentially expedited discharges from
hospital stays, ‘‘in which patients are
leaving the hospital ‘quicker and
sicker.’ ’’ Patients may be leaving the
hospital environment in a tenuous and
fragile state, leaving them vulnerable to
further harm once returned to the home
environment. Additionally, the change
from constant monitoring in the
inpatient facility to less frequent
monitoring in the home environment
can potentially cause gaps in care and
consequently increased risk for adverse
events for the newly-admitted home
health beneficiary. The article notes that
many of the negative impacts of the
transition can be reduced by an
appropriate increase in care for the
beneficiary in the home setting, notably
with more frequent assessment of their
condition and ongoing monitoring.
Therefore, we believe that an
opportunity may exist for the HHGM to
account for this increased need and
accordingly provide a differentiated
payment to facilitate the provision of
more frequent assessments and
monitoring for beneficiaries admitted to
home health from acute and PAC
settings, which could in turn help
prevent re-hospitalizations and adverse
events. We expect that HHAs would
provide more resource-intensive
services after discharge from an
institutional setting to educate patients
in new medication management,
facilitate discharge education for the
patient and family, and provide support
in the recovery from the illness that
caused the originating hospitalization or
institutional stay.
In the guidebook ‘‘Patient Safety and
Quality: An Evidence-based Handbook
for Nurses,’’ authors Ruth M. Kleinpell,
Kathy Fletcher, of and Bonnie M.
Jennings note in chapter 11 that
deconditioning, a status characterized
by a ‘‘decrease in muscle mass and the
other physiologic changes related to bed
38 Forster, A.J. (2003). The Incidence and Severity
of Adverse Events Affecting Patients after Discharge
from the Hospital. Annals of Internal Medicine,
138(3), 161. doi:10.7326/0003–4819–138–3–
200302040–00007.
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rest, contributes to overall weakness,’’
has become commonplace in the postinstitutional beneficiary population.39
This physiological weakening of the
institutionalized beneficiary can then,
in turn, lead to significant functional
decline, resulting in reduction in ability
to perform Activities of Daily Living
(ADLs), and ultimately in increased
home health resource utilization. The
article notes that hospitalization of the
elderly is usually marked by decreased
levels of mobility and increased levels
of bed rest, with deterioration from their
baseline levels as soon as day two of the
hospitalization. Hence, a hospitalization
itself leads to declines in mobility,
which consequently yields reduced
functionality in patients relative to their
status before their inpatient stay. This
decline in functional ability likewise
merits appropriate skilled services to
support the patient’s increased needs
after a hospital stay.
In the article ‘‘Determinants of health
after hospital discharge: Rationale and
design of the Vanderbilt Inpatient
Cohort Study (VICS),’’ the authors
describe the period after a
hospitalization as a ‘‘vulnerable time’’
for patients.40 This vulnerability is due
to a number of factors, including the
need to manage new health care issues,
major modifications to medication
interventions, and the coordination of
follow-up appointments, all while a
beneficiary strives to recuperate after a
hospital stay for an acute medical event.
Of particular concern are the risks for
adverse drug events, for errors in a
beneficiary’s medication regimen, and
for the need to readmit to the hospital
due to deterioration of the patient’s
condition. Given the risks during this
intense, challenging, and potentially
costly period after discharge, we would
expect that beneficiaries would require
more visits from skilled disciplines,
particularly for the purpose of teaching
and medication management. This
increased utilization of resources
would, in turn, warrant a differentiated,
potentially higher payment for such
services, and the proposed HHGM
payment system refinement could
account for this difference with varying
39 Hughes, R. (2008). Patient safety and quality:
An evidence-based handbook for nurses. Rockville,
MD: Agency for Healthcare Research and Quality,
U.S. Dept. of Health and Human Services. https://
archive.ahrq.gov/professionals/cliniciansproviders/resources/nursing/resources/nurseshdbk/
nurseshdbk.pdf, 259–274.
40 Meyers, A.G., Salanitro, A., Wallston, K.A.,
Cawthon, C., Vasilevskis, E.E., Goggins, K. M.,
. . . Kripalani, S. (2014). Determinants of health
after hospital discharge: Rationale and design of the
Vanderbilt Inpatient Cohort Study (VICS). BMC
Health Services Research, 14(1). doi:10.1186/1472–
6963–14–10.
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payment amounts based upon
admission source. We note that we do
not expect the source of the patient’s
admission would lead to an HHA
furnishing home health services that
would replace any orders made by the
referring physician regarding the type or
frequency of services the patient might
need during the home health stay. The
admission source variable in the
proposed HHGM is meant to serve as a
meaningful indicator of resource
utilization, which determines Medicare
payment. The HHA, in consultation
with the physician and ordered by the
physician, will continue to articulate, in
the plan of care, what services are
required to meet the needs of the
patient, as well as the frequency of such
services.
With regard to beneficiaries admitted
to home health from the community,
research related to home health
admission source demonstrates that
community-admitted beneficiaries tend
to receive care from the less-costly
disciplines. In its 2016 Report to
Congress, MedPAC noted that, in their
analysis of CY 2013 HH claims,
beneficiaries admitted from the
community tend to receive more visits
from home health aides than their noncommunity counterparts, stating that
‘‘aide services were the majority of
services provided in 14 percent of the
episodes for community-admitted users
compared with 5 percent for PAC
users.’’ 41 However, these same
community entrants averaged 2.6, 60day episodes, while the institutional
admits averaged only 1.4, 60-day
episodes, demonstrating longer lengths
of stay for the community-admitted
beneficiaries than those entering from
institutional settings. These findings
suggest that beneficiaries admitted to
home health from the community
typically require less resources but for
longer periods of time when compared
to the beneficiaries admitted from an
institutional stay. Additionally, a 2001
Department of Health and Human
Services Office of Inspector General
study found Medicare home health
referrals coming from the community
(in this case defined as a referral for a
beneficiary who had not been admitted
to an overnight stay in a hospital or
skilled nursing facility for 15 days prior
to beginning a home health care
episode) were more likely to have
chronic conditions than those referred
from hospitals, and therefore, were more
likely to require ongoing but less
resource-intensive care.42
In addition to our review of related
research, we also evaluated home health
utilization and patient assessment data
as described in section III.E.1 of this
proposed rule, and our findings
demonstrate that those beneficiaries
admitted from PAC, as well as acute
care settings demonstrate higher
resource utilization than their
community-admitted counterparts.
The differences in care needs during
home health based on admission source
are illustrated in the resource utilization
figures presented in Table 32, which
shows the distribution of admission
sources as well as average resource use
for 30-day periods by admission source.
Institutional admissions have
significantly higher average resource use
at $2,165.06 compared with community
admissions at $1,393.10, a difference of
$771.96. Median values of resource use
also show a significant difference
between sources of admission, with
institutional resource use at $1,899.41
while community resource use is at
$1,060.51, a difference of nearly $840.
The pattern of higher resource use for
institutional admissions as compared to
community admissions continues for
the 25th and 75th percentiles, with a
difference of approximately $700 and
$900, respectively.
TABLE 32—AVERAGE RESOURCE USE BY ADMISSION SOURCE (14 DAY LOOK-BACK) ADMISSION SOURCE
Average
resource use
Number of
30-day
periods
Percent of
30-day
periods
Standard
deviation of
resource use
25th
percentile
of
resource use
Median
resource use
75th
percentile
of
resource use
Institutional ...................
Community ...................
$2,165.06
1,393.10
$2,153,712
6,488,395
24.92
75.08
$1,350.43
1,208.29
$1,224.83
571.97
$1,899.41
1,060.51
$2,772.04
1,838.39
Total ......................
1,585.48
8,642,107
100.00
1,289.23
671.96
1,262.65
2,119.49
mstockstill on DSK30JT082PROD with PROPOSALS2
Source: CY 2016 Medicare Home Health Claims Data (as of March 17, 2017).
For all of these reasons, we are
proposing to establish two admission
source categories for grouping 30-day
periods of care under the HHGM—
institutional and community—as
determined by the healthcare setting
utilized in the 14 days prior to home
health admission. We are proposing the
institutional category would include 30day periods of care for patients admitted
from either acute care or PAC settings.
Thirty-day periods for beneficiaries with
any inpatient acute care
hospitalizations, skilled nursing facility
stays, inpatient rehabilitation facility
stays, or long term care hospital stays
within the 14 days prior to a home
health admission would be designated
as institutional admissions. Similarly,
we are proposing that the institutional
admission source category would also
include patients that had an acute care
hospital stay during a previous 30-day
period of care and within 14 days prior
to the subsequent, contiguous 30-day
period of care and for which the patient
was not discharged from home health
and readmitted (that is, the admission
date and from date for the subsequent
30-day period of care do not match) as
we acknowledge that HHAs have
discretion as to whether they discharge
the patient due to a hospitalization and
then readmit the patient after hospital
discharge. However, we would not
categorize post-acute care stays that
occur during a previous 30-day period
and within 14 days of a subsequent,
contiguous 30-day period of care (that
is, the admission date and from date for
the subsequent 30-day period of care do
not match) as institutional as we would
expect the HHA to discharge the patient
if the patient requires post-acute care in
a different setting (for example, a SNF
or IRF) and then readmit the patient, if
necessary, after discharge from such
setting. If the patient is discharged and
then readmitted to home health, the
admission date and from date on the 30day claim will match and the claims
41 Medicare Payment Advisory Commission
(MedPAC). ‘‘Home Health Care Services.’’ Report to
Congress: Medicare Payment Policy. Washington,
DC, March 2016. P. XX. Accessed on March 28,
2017 at https://www.medpac.gov/docs/defaultsource/reports/chapter-8-home-health-careservices-march-2016-report-.pdf?sfvrsn=0.
42 https://oig.hhs.gov/oei/reports/oei-02-0100070.pdf; ‘‘Medicare Home Health Care
Community Beneficiaries 2001’’; HHSM–500–2010–
00072C 12.
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processing system will look for an acute
or a post-acute care stay within 14 days
of the home health admission date. This
admission source designation process
would be applicable to institutional
stays paid by Medicare or any other
payer. All other 30-day periods would
be designated as community
admissions.
We initially investigated maintaining
two separate institutional categories,
one for PAC and another for acute care
settings, to identify any meaningful
differences in resource use. However,
we observed similar resource use in
those cases where the patient was
admitted from both PAC and acute care
settings. Furthermore, in our analysis of
the data from CY 2013, we found that
the volume of home health cases with
an admission from PAC settings across
all 30-day periods of care was a low
value at 736,112 cases (approximately 8
percent) out of a total of 8,539,996 cases
as compared with cases admitted from
acute settings at 1,376,567 cases
(approximately 16 percent). The number
of cases admitted from acute settings
was approximately double the number
of cases admitted from PAC settings.
Moreover, in the creation of case-mix
groups that differentiated between
community, acute, and PAC admission
sources, there were some case-mix
groups with a very low number of 30day periods of care, which in turn can
result in substantial variability in the
average resource use from year- to- year.
We were concerned that this variability
could introduce unnecessary instability
in the case-mix weights under the
proposed HHGM. As such, we are
proposing to group 30-day periods of
care for patients admitted from acute
care and PAC settings together as
‘‘institutional’’ admissions.
We also considered the employment
of a ‘‘look-back’’ period for determining
the admission source that was longer
than 14 days and thus examined data for
a longer 30-day ‘‘look-back’’ period to
assess the resource utilization for
patients admitted to home health from
institutional and community settings;
however, our findings indicated that
there is only a slight difference in
resource use, as well as volume of
beneficiaries utilizing PAC or acute
services before home health between the
two timeframes. Table 33 shows the
distribution of 30-day periods and
average resource utilization with
admission source categories now
defined by service use for beneficiaries
in the 30 days prior instead of 14 days
prior. In general, results are similar to
those for the 14-day look-back period
when compared to the 30-day ‘‘lookback’’ window. Average resource use
under a 14-day ‘‘look-back’’ period for
institutional entrants is at $2,165.06
while the 30-day entrants show an
average resource use of $2,140.40. The
same similarity holds true for
community entrants, who show an
average resource use of $1,393.10 for the
14-day ‘‘look-back’’ period versus
$1,382.38 under the 30-day window. We
note that the 30-day ‘‘look-back’’ period
only produces a slightly higher
proportion of institutional periods of
care, at 2,315,557 periods as compared
with the 14-day period value of
2,153,712, a difference of approximately
10 percent.
TABLE 33—AVERAGE RESOURCE USE BY ADMISSION SOURCE
[30 Day look-back]
Admission source
Average
resource use
Number of 30day periods
Percent of 30day periods
Standard
deviation of
resource use
25th Percentile
of resource
use
Median
resource use
75th Percentile
of resource
use
Institutional ...................
Community ...................
$2,140.40
1,382.38
2,315,557
6,326,550
26.79%
73.21
$1,354.34
1,202.14
$1,197.39
567.05
$1,873.71
1,049.66
$2,748.79
1,823.04
Total ......................
1,585.48
8,642,107
100.00
1,289.23
671.96
1,262.65
2,119.49
mstockstill on DSK30JT082PROD with PROPOSALS2
Source: CY2016 Medicare Home Health Claims Data (as of March 17, 2017).
We believe that a 14-day ‘‘look-back’’
period is more likely to be directly
related to the patients’ need for home
health care than a 30-day ‘‘look-back’’
period. This would also be more
intuitive for HHAs, as the OASIS item
M1000 specifically assesses whether a
beneficiary was discharged from an
institutional setting within the past 14
days. Thus, we ultimately are proposing
to use the 14-day ‘‘look-back’’ period as
we believe it will better categorize those
beneficiaries with a relatively short
transition between institutional care and
home health care. Given that beneficiary
admission source has previously been
utilized for the purposes of Medicare
home health payment, HHAs will be
familiar with this concept. Moreover,
the proposed 14-day ‘‘look-back’’ period
simplifies the structure of the proposed
model and limits burden on claims
systems and related processing.
Additionally, a ‘‘look-back’’ period of 14
days is consistent with section
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1861(tt)(1) of the Act, which defines the
term ‘‘post-institutional home health
services’’.
To differentiate between an
institutional and community admission
source, we would establish an
evaluation process whereby the
Medicare claims processing system
would check for the presence of an
acute/post-acute Medicare claim
occurring within 14 days of the home
health admission on an ongoing basis.
In the past, HHAs stated that they had
encountered challenges in terms of
identifying the source of admission for
home health beneficiaries, and we
believe that an automated systems
approach where Medicare systems
evaluate for the presence of an
institutional claim within the 14-day
‘‘look-back’’ window will serve to
overcome this earlier challenge. Under
this approach, the Medicare systems
would only evaluate for whether an
acute/post-acute Medicare claim
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occurring within 14 days of the home
health admission was processed by
Medicare, not whether it was paid.
Moreover, we propose that newlycreated occurrence codes would also be
established that would allow HHAs to
manually indicate on Medicare home
health claims an institutional admission
source prior to an acute/post-acute
Medicare claim, if any, being processed
by Medicare systems. We note that the
use of these occurrence codes would not
be limited to home health beneficiaries
for whom the acute/post-acute claims
were paid by Medicare. HHAs would
also use the occurrence codes for
beneficiaries with acute/post-acute care
stays paid by other payers, such as the
Veterans Administration. Although a
home health claim with a non-Medicare
institutional admission source can be
categorized by the HHA as an
institutional admission and paid
accordingly, we may conduct medical
review as discussed below. We expect
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home health agencies would utilize
discharge summaries from institutional
providers to inform the usage of these
occurrence codes. We note that these
discharge documents should already be
part of the beneficiary’s home health
medical record used to support the
certification of patient eligibility as
outlined in § 424.22(c).
If an occurrence code is submitted on
the home health claim, the home health
claim would be categorized as an
institutional admission. However, if a
home health claim is submitted without
an institutional admission occurrence
code, thereby categorizing it with a
community admission source, and later
an acute/post-acute Medicare claim for
an institutional stay occurring within 14
days of the home health admission is
submitted within the timely filing
deadline and processed by the Medicare
systems, the home health claim would
be automatically adjusted and recategorized as an institutional
admission and appropriate payment
modifications would be made. Our
systems would adjust communityadmitted home health claims on a
claim-by-claim, flow basis if an acute/
post-acute Medicare claim for an
institutional stay occurring within 14
days of the home health admission is
received. Given that our systems can
only evaluate for the presence of a
Medicare acute/post-acute claim, if
there was a non-Medicare institutional
stay occurring within 14 days of the
home health admission but the HHA
was not aware of such a stay, upon
learning of the institutional stay, the
HHA would be able to resubmit a home
health claim that included an
occurrence code, subject to the timely
filing deadline, and payment
adjustments would be made
accordingly.
Conversely, if an occurrence code is
submitted on the home health claim
along with dates of the institutional
stay, and an acute/post-acute Medicare
claim for an institutional stay occurring
within 14 days of the home health
admission is not subsequently
submitted within the timely filing
deadline and processed by the Medicare
systems, or an acute/post-acute
Medicare claim for an institutional stay
occurring within 14 days of the home
health admission was submitted but
later denied for payment, we may
conduct post-payment medical review
of the home health claim to determine
whether the admission was in fact
preceded by an institutional stay
occurring within 14 days of the home
health admission. If upon medical
review a determination is made that the
admission was not from an institutional
setting, we would take appropriate
administrative action, including
correcting any improper payments and
potentially referring the provider to
another CMS review contractor for
further review or investigation. In
summary, we believe that allowing
HHAs to submit a claim with an
institutional admission occurrence code
for a beneficiary with either a Medicare
or non-Medicare institutional admission
source would enable HHAs to receive
appropriate payment for the home
health services, while also allowing us
the opportunity and flexibility to verify
the source of the admission and correct
any improper payments as deemed
appropriate.
For the purposes of a RAP, we would
only adjust the final home health claim
submitted for source of admission. For
example, if a RAP for a community
admission was submitted and paid, and
then an acute/post-acute Medicare claim
was submitted for that patient before the
final home health claim was submitted,
we would not adjust the RAP and would
only adjust the final home health claim
so that it reflected an institutional
admission. Additionally, HHAs would
only indicate admission source
occurrence codes on the final claim and
not on any RAPs submitted.
We invite public comments on the
admission source component of the
proposed HHGM payment system.
6. Proposed Clinical Groupings
a. Background
As discussed in section II.D of this
proposed rule, the Home Health Study
35313
Report to Congress found that the
current payment system may encourage
HHAs to select certain types of patients
over others, as some clinical sub-groups
within the current case mix system are
associated with lower margins.43 These
sub-groups include patients with a
higher severity of illness, including
those receiving a greater level of skilled
nursing care; for example, patients with
wounds, with ostomies, or who are
receiving total parenteral nutrition or
mechanical ventilation. Additionally,
the Medicare Payment Advisory
Commission (MedPAC) has expressed
concerns that the HH PPS
disincentivizes care for patients needing
skilled nursing visits, thereby limiting
access of care to the most clinically
vulnerable patient populations.44
Although the clinical domain of the
current case-mix system accounts for
whether or not the patient has one or
more certain clinical conditions, there
could be improvements in clarity
regarding patient needs to clearly
explain resource use and cost. Given
that payment should be predicated on
resource use, providing additional
clinical groups in the case-mix system
and adjusting payment based on
identified clinical characteristics and
associated services, along with other
patient variables, should better align
payment with resource use. As such,
under the HHGM, we propose grouping
30-day periods of care into six clinical
groups designed to capture the most
common types of care that HHAs
provide. The proposed groups mirror
how clinicians differentiate between
patients as to what types of care they are
receiving. To inform the development of
the clinical groups, Abt Associates and
CMS conducted an extensive review of
diagnosis codes to identify the primary
reasons for home health services under
the Medicare home health benefit. The
workgroup developed six clinical
groups reflecting the reported principal
diagnosis, clinical relevance, and coding
guidelines and conventions, see Table
34.
TABLE 34—CLINICAL GROUPS USED IN THE HOME HEALTH GROUPINGS MODEL
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Clinical groups
The primary reason for the home health encounter is to provide:
Musculoskeletal Rehabilitation ........
Neuro/Stroke Rehabilitation ............
Therapy (physical, occupational or speech) for a musculoskeletal condition.
Therapy (physical, occupational or speech) for a neurological condition or stroke.
43 Report to Congress. Medicare Home Health
Study: An Investigation on Access to Care and
Payment for Vulnerable Patient Populations.
Available at https://www.cms.gov/Medicare/
Medicare-Fee-for-Service-Payment/
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HomeHealthPPS/Downloads/HH-Report-toCongress.pdf.
44 Report to the Congress: Medicare Payment
Policy. (2015) Home health care services: Assessing
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payment adequacy and updating payments. Ch.9
https://www.medpac.gov/docs/default-source/
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TABLE 34—CLINICAL GROUPS USED IN THE HOME HEALTH GROUPINGS MODEL—Continued
Clinical groups
The primary reason for the home health encounter is to provide:
Wounds—Post-Op
Wound
Aftercare and Skin/Non-Surgical
Wound Care.
Behavioral Health Care ...................
Complex Nursing Interventions .......
Medication Management, Teaching
and Assessment (MMTA).
Assessment, treatment & evaluation of a surgical wound(s); assessment, treatment & evaluation of nonsurgical wounds, ulcers, burns, and other lesions.
Assessment, treatment & evaluation of psychiatric conditions.
Assessment, treatment & evaluation of complex medical & surgical conditions including IV, TPN, enteral
nutrition, ventilator, and ostomies.
Assessment, evaluation, teaching, and medication management for a variety of medical and surgical conditions not classified in one of the above listed groups.
The 30-day periods of care were
assigned to one of the six clinical groups
based on the reported principal
diagnosis. However, roughly 19 percent
of 30-day periods could not be assigned
to a clinical group based on principal
diagnosis alone. Reasons for the
inability to group 30-day periods based
on primary diagnoses included codes
that were too vague, meaning the code
did not provide adequate information to
support the need for home health
services (for example, T14.90 Injury,
unspecified); codes that would not be
Medicare covered services in other
settings (for example, dental codes);
codes that would be unlikely to require
skilled home health services (for
example, R68.89 Other general
symptoms and signs); codes that
indicate death as the outcome (for
example, G93.82, Brain death);
manifestation codes, where coding
guidelines require an etiology code to be
reported as a principal diagnosis (for
example, I39 Endocarditis and heart
valve disorders in diseases classified
elsewhere); or code first, meaning the
diagnosis is subject to sequencing
conventions under ICD–10–CM, where
the underlying condition must be
sequenced first (for example, dementia
in Parkinson’s disease, in which
Parkinson’s disease must be sequenced
first). In these instances, 30-day periods
were considered ‘‘questionable
encounters’’ and secondary diagnosis
codes were examined to group the 30day period of care. An ICD–10–CM list
with all of the codes that would assign
30-day periods into the six clinical
groupings can be found on CMS’s HHA
Center Web page at https://
www.cms.gov/center/provider-Type/
home-Health-Agency-HHA-Center.html.
More information on the analysis and
development of the groupings can be
found in the HHGM technical report,
also available on the HHA Center Web
page. Table 35 shows the distribution of
episodes and associated resource use
across the six clinical groups.
TABLE 35—FREQUENCY AND ASSOCIATED RESOURCE USE OF CLINICAL GROUPS
Average resource use
Clinical group
N
Standard
deviation of
resource
use
Percent
25th Percentile of resource use
Median resource use
75th Percentile of resource use
$1,713.10
1,811.74
2,055.47
1,252.08
1,703.24
1,437.37
1,430,813
772,579
906,782
289,513
336,249
4,906,171
16.56
8.94
10.49
3.35
3.89
56.77
$1,149.61
1,319.45
1,666.59
1,019.25
1,573.15
1,200.35
$1,495.09
1,511.06
1,609.16
954.32
1,240.74
1,105.63
$878.95
851.12
955.17
505.15
675.88
589.92
$2,276.98
2,434.60
2,623.31
1,704.72
2,206.54
1,936.81
Total ..................................................
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Musculoskeletal Rehabilitation .................
Neuro/Stroke Rehabilitation .....................
Wound ......................................................
Behavioral Health .....................................
Complex Nursing Interventions ................
MMTA .......................................................
1,585.48
8,642,107
100.00
1,289.23
1,262.65
671.96
2,119.49
Table 35 illustrates the differences in
average resource use between 30-day
periods with similar care needs. Under
the HHGM, we propose that each 30-day
period would be assigned to a clinical
group according to the primary reason
the patient was receiving home health,
which would be derived from the
principal diagnosis code reported on the
home health claims. If a 30-day period
of care could not be grouped based on
the home health reported principal
diagnosis due to the reasons listed
above, we propose that the claim for
that 30-day period would remain a
questionable encounter and be returned
to the provider for more accurate or
definitive coding. Upon publication of
this proposed rule, we will post a
complete list of ICD–10 codes and their
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assigned clinical groupings on the CMS
HHA Center Web page (https://
www.cms.gov/center/provider-Type/
home-Health-Agency-HHA-Center.html)
to allow ample time for HHAs to
understand those codes which would be
considered a ‘‘questionable encounter.’’
We believe this will help to minimize
any returned claims for more definitive
coding. Each code should be reported to
the level of certainty and specificity
known for the home health admission.
Under our proposal, secondary
diagnosis codes would not be used to
assign the clinical group, as the intent
of the HHGM is to increase clarity by
classifying the 30-day period based on
the primary reason for home health
services. Although the principal
diagnosis code is the basis for the home
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health period, secondary diagnosis
codes would then be used to case-mix
adjust the period further through
additional elements of the model, such
as the comorbidity adjustment. Using
principal diagnoses as the core of the
model would create a clinically
intuitive payment system that more
clearly identifies the types of patients
that are treated in home health.
Diagnosis codes would also provide
clarity and transparency since they are
clearly described and reported on
claims and other care tools.
Additionally, they would support
medical necessity for services furnished,
and provide information for establishing
the home health plan of care.
Ultimately, developing clinically similar
groups based on the reported principal
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diagnosis as part of the larger structure
of the model would allow for more
meaningful analysis of home health
resource use, ensure that patients are
receiving care commiserate with their
level of need, and more accurately align
payment with cost.
b. Musculoskeletal and Neuro/Stroke
Rehabilitation
premorbid or optimal level of functional
independence.’’ 48 Neuro-rehabilitation
resource use can encompass evaluation
and treatment of impairments in
cognitive and spatial functioning,
swallowing, communication, and
psychological or emotional deficit;
whereas musculoskeletal rehabilitation
generally focuses on evaluation and
treatment of the impaired muscle, bone,
or joint. Musculoskeletal rehabilitation
is more targeted toward proprioception,
strength, imbalances, orthopedic
surgeries, and abnormal functional
movement patterns, and generally
streamlines resources following a
surgery or injury. Because of these
clinical differences and associated
resource use differences based on
variables in length and intensity of
rehabilitation, the HHGM would adjust
payment between musculoskeletal and
neuro/stroke rehabilitation accordingly.
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Rehabilitation is an integral part of
recovery following an illness, injury, or
surgical procedure, whether due to a
neurological or a musculoskeletal
condition. Given that different care
goals and expected outcomes of neurorehabilitation and musculoskeletal
rehabilitation affect resource use, the
clinical groups in the HHGM would
differentiate between the two. Patient
characteristics between the two groups
determine whether resources are
directed towards preventing the loss of
function or slowing the rate of loss of
function; improvement or restoration of
function; compensation for lost
function; and maintenance of current
function.45 Musculoskeletal
rehabilitation focuses on individuals
with impairments or disabilities due to
disease, disorders, or trauma to the
muscles or bones, whereas neurological
rehabilitation is designed for
individuals with disease, trauma, or
disorders of the nervous system.46
Rehabilitation following a stroke, for
instance, is primarily initiated early and
intensively with the most recovery of
function occurring within the first 3
months; 47 however, reacquiring the
skills to perform ADLs may be an ongoing process depending on the extent
and area of injury. However, if
improvement or recovery are not
expected or achieved, the focus of
therapy may shift to maintenance to
prevent further decline. Therefore, the
VA Clinical Practice Guidelines for
Management of Stroke Rehabilitation
‘‘strongly recommend that rehabilitation
therapy should start as early as possible,
once medical stability is reached’’ and
‘‘recommend that the patient receive as
much therapy as needed and tolerated
to adapt, recover, and/or reestablish the
c. Wounds
Wound care is provided in a variety
of settings, including in the home.
Advances in wound care treatments
have increasingly allowed for a wide
range of wound therapies to be provided
in the home.49 According to the article
‘‘Wound Care Outcomes and Associated
Cost Among Patients Treated in US
Outpatient Wound Centers: Data From
the US Wound Registry,’’ a ‘‘rough
population prevalence rate for chronic
non-healing wounds in the United
States is 2 percent of the general
population,’’ with an estimated cost of
caring for these wounds exceeding $50
billion a year.50 Non-healing, chronic
wounds are often found in home health
patients considering ‘‘prolonged and
non-healing connective tissue injuries
are often associated with common
diseases, such as metabolic disorders,
obesity, hypertension, arteriosclerosis,
neuropathy, and diabetes mellitus,’’ 51
which are among the top home health
diagnoses.
Surgical wound care is essential at
preventing post-operative complications
such as surgical site infections (SSIs)
and dehiscence. Research has shown
that post-discharge SSIs occur in 3 to 5
45 World Health Organization. (2011).
Rehabilitation. World Report on Disability. Chapter
4. Retrieved from https://www.who.int/disabilities/
world_report/2011/chapter4.pdf.
46 Johns Hopkins Online Health Library.
Neurological Rehabilitation. Retrieved from https://
www.hopkinsmedicine.org/healthlibrary/
conditions/adult/physical_medicine_and_
rehabilitation/neurological_rehabilitation_
85,P01163/.
47 Stinear,C., Ackerley,S., Byblow, W. (2013)
Rehabilitation is Initiated Early After Stroke, but
Most Motor Rehabilitation Trials Are Not. Stroke.
2013; 44:2039–2045. https://doi.org/10.1161/
STROKEAHA.113.000968.
48 https://www.healthquality.va.gov/guidelines/
Rehab/stroke/Mgmt_of_Stroke_Rehab_03151.pdf.
49 Rhee, S., Valle, M., Wilson, L., Lazarus, G.,
Zenilman, J., Robinson, K. (2015). Negative pressure
wound therapy technologies for chronic wound
care in the home setting: A systematic review.
Wound Repair and Regeneration. 23, 506–517.
50 https://www.woundsresearch.com/article/
wound-care-outcomes-and-associated-cost-amongpatients-treated-us-outpatient-wound-centers-d.
51 Ackermann, P., Hart, D. Influence of
Comorbidities: Neuropathy, Vasculopathy, and
Diabetes on Healing Response Quality. (2013) Adv
Wound Care (New Rochelle), 2(8): 410–421. doi:
10.1089/wound.2012.0437.
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35315
percent of all surgical patients, and up
to 33 percent of patients undergoing
abdominal surgery, and that ‘‘more than
half of patients who develop postdischarge SSIs are readmitted to the
hospital, making SSIs the overall
costliest healthcare-associated
infection.’’ 52 Home care management of
burns requires a variety of resources as
‘‘burn patients are unique, representing
the most severe model of trauma.’’ 53
The management of burn injury
involves a multidisciplinary approach
which may include nurses, occupational
and physical therapists, dieticians, and
psychosocial experts. Pressure ulcers
are associated with an increased risk of
morbidity and mortality and have a
variety of intrinsic and external factors
affecting their incidence and treatment.
The incidence of pressure ulcers in
home health is projected to rise due to
the aging population, increasingly
fragmented care, and nursing shortage.54
Ultimately, wound care depends on a
multitude of characteristics driving
resource utilization. By highlighting
them as a clinical group, the HHGM
would recognize the variety of resources
and skills that necessitate careful
treatment and healing of different types
of wounds, and more accurately ascribe
resource use to payment.
d. Behavioral Health Care
The World Health Organization
(WHO) defines health as ‘‘a state of
complete physical, mental and social
well-being and not merely the absence
of disease or infirmity.’’ 55 As such,
behavioral and mental home health is
an important clinical group of the
HHGM. If all eligibility and coverage
criteria are met according to § 409.42,
then a patient may receive skilled
nursing services for the assessment,
treatment, and evaluation of psychiatric
conditions. The Home Health Benefit
Policy Manual states that ‘‘the
evaluation, psychotherapy, and teaching
needed by a patient suffering from a
diagnosed psychiatric disorder that
requires active treatment by a
52 Sanger, P., Hartzler, A., Han,S., et al. (2014)
Patient Perspectives on Post-Discharge Surgical Site
Infections: Towards a Patient-Centered Mobile
Health Solution. PLoS One. 2014; 9(12):
e114016.Published online 2014 Dec 1. doi: 10.1371/
journal.pone.0114016.
53 Al-Mousawi, A. MD, Mecott-Rivera, G. MD,
Jeschke, M. MD, Ph.D., et al. (2009). Burn Teams
and Burn Centers: The Importance of a
Comprehensive Team Approach to Burn Care: Clin
Plast Surg. 2009 Oct; 36(4): 547–554: doi: 10.1016/
j.cps.2009.05.015.
54 Lyder, C., Ayello, Elizabeth. (2008). Pressure
Ulcers: A Patient Safety Issue. Patient Safety and
Quality: An Evidence-based Handbook for Nurses.
Chapter 12.
55 Constitution of WHO: principles: https://
www.who.int/about/mission/en/.
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Federal Register / Vol. 82, No. 144 / Friday, July 28, 2017 / Proposed Rules
psychiatrically trained nurse, and the
costs of the psychiatric nurse’s services
may be covered as a skilled nursing
service.’’ 56 However, the psychiatric
care must be furnished by an agency
that does not primarily provide care and
treatment of mental diseases. Older
adults may be more susceptible to
psychiatric and behavioral health issues
due to limited mobility, bereavement,
loss of ability to live independently, or
drop in socioeconomic status due to
retirement.57 Although psychiatric and
behavioral conditions have different
signs, symptoms, and treatment options
than physical illness, mental health can
have major consequences on physical
health. Behavioral health research
suggests that ‘‘a model of care including
solely hospital based provision (usually
inpatient and outpatient care) will be
insufficient to provide access for people
facing barriers to care.’’ 58 Additionally,
the length of stay among Medicare
beneficiaries who have been
hospitalized for mental illness has
declined over the last decade, with
patients being discharged to home
health rather than extending a
hospitalization.59 For these reasons,
behavioral home health remains a
crucial aspect of keeping beneficiaries
out of the hospital. Distinguishing it as
a clinical group delineates the resources
associated with the unique care needs of
these patients and would more
accurately assign payment based on
patient characteristics.
e. Complex Nursing Interventions
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Understandably, the growing trend
toward providing more healthcare
services in the community shifts an
increasing number of complex nursing
interventions to home health. Providing
complex nursing interventions in the
home reflects a patient population with
‘‘more complex health care needs who
require more intensive medical services
coordinated across multiple providers,
as well as a wide range of social
supports to maintain health and
56 https://www.cms.gov/Regulations-andGuidance/Guidance/Manuals/Downloads/
bp102c07.pdf.
57 World Health Organization: Mental Health and
Older Adults. Retrieved from https://www.who.int/
mediacentre/factsheets/fs381/en/.
58 Thornicroft, G., Deb, T., Henderson, C. (2016)
Community mental health care worldwide: current
status and further developments. World Psychiatry,
15(3): 276–286.Published online 2016 Sep 22. doi:
10.1002/wps.20349.
59 Banta, J., Belk, I., Newton, K., Sherzai, A.
(2010) Inpatient Charges and Mental Illness:
Findings from the Inpatient Sample 1999–2007.
Clinicoecon Outcomes Res2010; 2: 149–158.
Published online 2010 Oct 11. doi: 10.2147/
CEOR.S7560.
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functioning.’’ 60 Because of the range
and intensity of services needed, these
patients tend to generate high resource
utilization and associated costs due to
the need for a higher level of knowledge
and expertise.61 Additionally,
readmission rates can be high in this
vulnerable population as patients adjust
to their home with therapies generally
administered in the hospital or postacute environment.62
For instance, the introduction of
home mechanical ventilation is a
technological advancement that not
only keeps healthcare costs down but
also allows patients, whose condition
would otherwise necessitate an
institutional environment, a maximum
quality of life. For example, the results
from one study found that long-term
mechanical ventilation on average costs
$14,500 less per patient, per month
when administered at home rather than
in an acute or post-acute facility.63
However, it does not come without
challenges. Caregiver competency,
evolving technology, changes in patient
medical status, and safety of home
environment can lead to higher home
health resource utilization. Likewise,
management of ostomies and vascular
access devices (VADs) are associated
with higher resource use in the home.
The impact on patients living with
VADs and ostomies is significant, with
research identifying physical,
psychological, and social effects.64
Ostomy and VAD specific challenges or
complications may occur initially and
persist and change daily as patients
learn to troubleshoot and manage life
with an ostomy or VAD. Care often
60 Rich, E., Lipson, D., Libersky, J., Parchman, M.
(2012). Coordinating Care for Adults With Complex
Care Needs in the Patient-Centered Medical Home:
Challenges and Solutions WHITE PAPER, prepared
by Mathematica Policy Research AHRQ Publication
No. 12–0010 January 2012: https://
www.mathematica-mpr.com/our-publications-andfindings/publications/coordinating-care-for-adultswith-complex-care-needs-in-the-patientcenteredmedical-home-challenges-and-solutions.
61 Huisman-de Waal G., van Achterberg, T.,
Jansen, J., Wanten, G., Schoonhoven, L. (2011)
High-tech home care: overview of professional care
in patients on home parenteral nutrition and
implications for nursing care: J Clin Nurs. 2011
Aug;20(15–16):2125–34. doi: 10.1111/j.1365–
2702.2010.03682.x. Epub 2011 May 25.
62 Vallab, H., Konrad, D., DeChicco, R., et al
(2016). Thirty-Day Readmission Rate Is High for
Hospitalized Patients Discharged With Home
Parenteral Nutrition or Intravenous Fluids, JPEN J
Parenter Enteral Nutr. 2016 Aug 18. doi:
0148607116664785.
63 King, A. Long-Term Home Mechanical
Ventilation in the United States. (2012). Respiratory
Care June 2012, 57 (6) 921–932; doi: https://doi.org/
10.4187/respcare.01741.
64 Grant, M. RN, DNS, FAAN, McCorkle, R. Ph.D.,
FAAN, Hornbrook, M. Ph.D., et al. (2013).
Development of a Chronic Care Ostomy SelfManagement Program. J Cancer Educ. 2013 Mar;
28(1): 70–78. doi: 10.1007/s13187–012–0433–1.
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requires resources aimed at education
and support in addition to physical
care. This can be made more
challenging by the social and
psychological effects that many new
patients experience. Under the HHGM,
ICD–10–CM codes on the home health
claim that identify complex nursing
interventions as the principal reason for
home health would generate higher
payment to account for these inherent
challenges requiring additional resource
utilization.
f. Medication Management, Teaching,
and Assessment (MMTA)
Based on our analysis, the majority of
30-day periods of care in the HHGM
would likely be classified under the
MMTA clinical group. These 30-day
periods would be characterized by
codes that identify direct services
related to the management and
evaluation of the care plan, observation
and assessment of the patient’s
condition, and training and/or
education of a patient or family member
that are not classified into one of the
other clinical groups. The numerous
and diverse conditions found in home
health, and their associated medications
and interventions, influence the
principal diagnosis that would classify
a 30-day period as under the MMTA
clinical group.
Research on home health patient
characteristics, home health nursing
interventions, and outcomes of care
show that there are four broad categories
of interventions most frequently
provided in the home:
(1) Health teaching, guidance and
counseling;
(2) Treatments and procedures;
(3) Case management; and,
(4) Surveillance 65
Of these interventions, surveillance is
the most frequently occurring
intervention, closely followed by health
teaching, guidance and counseling.66
Specific patient problems most
frequently identified in the home health
setting are related to medication
regimens, especially with
polypharmacy, and health-related
behaviors.67 The majority of home
health care patients routinely take more
than five prescription drugs, and many
likely deviate from their prescribed
medication regimen.68 This increases
65 Martin, K., Scheet, N., Stegman, M.R. (1993).
Home Health Clients: Characteristics, Outcomes of
Care, and Nursing Interventions. American Journal
of Public Health. 83(12), 1730–1734.
66 Ibid.
67 Ibid.
68 Ellenbecker, C., Samia, L., Cushman, M.,
Alster, K. (2008). Patient Safety and Quality in
Home Health Care. Patient Safety and Quality: An
Evidence-based Handbook for Nurses. Chapter 13.
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the potential for medication errors or
adverse effects in home health,
highlighting the substantial need for
education and medication management
regardless of whether the patient needs
wound care, rehabilitation, or complex
nursing interventions.
Additionally, patients with
comorbidities tend to be high users of
home health,69 making education and
assessment of disease diagnosis,
medication interactions, lifestyle
changes, and avoidance of adverse
events a considerable portion of home
health care. In an elderly patient
population, the number of chronic
conditions increases with age.
Medications used to treat or prevent
blood clots (anticoagulants), diabetes
(insulin), and pain (opioid analgesics)
are some of the most commonly
implicated drugs in emergency room
visits and emergent hospitalizations for
adverse drug events in older adults.70
These adverse events can potentially be
reduced by improving dosing and
monitoring of these drugs in high risk
populations and settings like older
adults in home health programs.71
Anticoagulants are challenging to
manage in home health settings and
have been identified as targets for
improvements in monitoring and care
coordination by HHS. Also, as the
number of medications being taken
increases, so does the risk of adverse
drug reactions, and the risk of drug
reaction related emergency room visits
and hospital admissions, especially in
patients who are in poor health.72
Elderly patients are especially at risk for
adverse drug reactions as the organs that
metabolize drugs have reduced
functional ability which can lead to
increased toxicity.73 Similarly, roughly
31 percent of younger Medicare
beneficiaries with disabilities report
having five or more chronic
conditions.74 Polypharmacy can lead to
reduced compliance with medication
69 Center for Healthcare and Transformation.
(2010). Health Care Cost drivers: Chronic Disease,
Comorbidity and Health Risk Factors in the U.S.
and Michigan. Center for Healthcare and
Transformation.
70 Budnitz DS, Lovegrove MC, Shehab N,
Richards CL. Emergency hospitalizations for
adverse drug events among older Americans. N Engl
J Med 2011;365:2002–2012.
71 U.S. Department of Health and Human
Services, Office of Disease Prevention and Health
Promotion. (2014). National Action Plan for
Adverse Drug Event Prevention. Washington, DC.
72 Alpert, P., Gatlin, T. (2015). Polypharmacy in
Older Adults. Homehealth Care Now. 33(10), 524–
529.
73 Ibid.
74 Cubanski, J., Neuman, T., Damico, A. (2010,
August) Medicare’s Role for People Under Age 65
with Disabilities. Retrieved from https://kff.org/
medicare/issue-brief/medicares-role-for-peopleunder-age-65-with-disabilities/.
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regimens, thus putting the patient at risk
for adverse events resulting from poorly
managed conditions. In the home
healthcare setting, management of
polypharmacy is a primary focus of
nursing interventions.75 These
interventions include assessment of the
patient’s chronic conditions and
medications used to treat those
conditions; assessment of the patient’s
understanding of and compliance with
his or her medication regimen; and
teaching and reinforcing treatment and
medication regimens. The medication
review by the home health nurse can
help reduce duplicate medications,
medications that are contraindicated for
older adults, and provide ways to
ensure patients are being appropriately
monitored and understand why they are
taking the medications as well as how
to take them correctly.76
Other studies show that primary
functions of home health care skilled
nursing interventions include providing
disease-specific and general health
information; helping patients to practice
and refine disease management skills;
assessing efficacy of treatment; and,
advocating for any needed changes to
established treatment and drug
regimens.77 The interventions
encompassed under the MMTA clinical
group are shown extensively in research
literature to be the most prevalent
services provided by home health
clinicians. Analysis of home health
episodes for the HHGM suggests that the
MMTA services would be the most
frequent home health service being
provided to Medicare home health
beneficiaries.
We believe that the proposed clinical
groupings add a needed level of clarity
in identifying and meeting the needs of
home health patients; particularly the
patient populations addressed in the
Home Health Study Report to Congress
as outlined in section II.D. of this
proposed rule. Recognizing that all 30day periods of home health care cannot
be defined by the principal diagnosis
alone, the clinical groupings would only
be one step in the case-mix adjustment
under the HHGM. We invite comments
on the proposed clinical groups, which
are designed to capture the most
common types of care that HHAs
provide.
75 Ibid.
76 Ibid.
77 Liebel, D., Powers, B.A., Friedman, B., Watson,
N. (2011). Barriers and Facilitators to Optimize
Function and Prevent Disability Worsening: A
Content Analysis of a Nurse Home Intervention.
Journal of Advanced Nursing. 68(1), 80–93.
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35317
7. Functional Levels and Corresponding
OASIS Items
Research has shown a relationship
exists between functional status, rates of
hospital readmission, and the overall
costs of health care services.78
Functional status is defined in a number
of ways, but generally, functional status
reflects an individual’s ability to carry
out activities of daily living (ADLs) and
to participate in various life situations
and in society.79 The assessment of
functional status is often called ‘‘the
sixth vital sign’’, which reflects its
clinical relevance in the plan of care.
CMS requires the collection of data on
functional status in home health
through a standardized assessment
instrument: The Outcome and
Assessment Information Set (OASIS).80
Under the current HH PPS, functional
status is assessed through the following
OASIS items:
• M1810: Dressing Upper Body.
• M1820: Dressing Lower Body.
• M1830: Bathing.
• M1840: Toileting.
• M1850: Transferring.
• M1860: Ambulation/Locomotion.
For each of these OASIS items, the
clinician or therapist conducting the
assessment selects a numbered
checkbox that best describes the
patient’s functional status in terms of
ability to perform certain tasks. These
numbered checkboxes typically range
from zero, meaning independent with
the task or no functional deficits, to
higher numbers, meaning decreasing
independence and/or increasing
deficits. Responses to these OASIS
items result in ‘‘points’’ to calculate an
overall functional score which conveys
the functional status of the patient. This
means that patients with a higher
functional score (that is, reduced
functional status) have, on average,
higher resource use compared to
patients with a lower functional score
(that is, higher functional status). As
such, the functional status of the patient
is a useful case-mix adjuster. Including
functional status in the case-mix
adjustment methodology allows for
higher payment for those patients with
78 Burke, R. MD, MS, Whitfield, E. Ph.D., Hittle,
D. Ph.D., Min, S. Ph.D., Levy, C. MD, Ph.D.,
Prochazka, A. MD, MS, Coleman, E. MD, MPH,
Schwartz, R. MD, Ginde, A. (2016). ‘‘Hospital
Readmission From Post-Acute Care Facilities: Risk
Factors, Timing, and Outcomes’’. The Journal of
Post-Acute Care and Long Term Care Medicine.
(17), 249–255.
79 Clauser, S. Ph.D., and Arlene S. Bierman, M.D.,
M.S. (2003). ‘‘Significance of Functional Status Data
for Payment and Quality’’. Health Care Financing
Review. 24(3), 1–12.
80 Bierman, A. (2001). ‘‘Functional Status: The
Sixth Vital Sign’’. Journal of Internal Medicine.
16(11), 785–786.
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higher service needs. As functional
status is commonly used for risk
adjustment in various payment systems,
including in the current HH PPS, the
proposed HHGM would also adjust
payments to account for differences in
resource use associated with functional
status.
During the development of the
HHGM, each OASIS–C item was
evaluated using clinical review and
analytical methods. Because the current
case-mix adjustment methodology
already utilizes OASIS items associated
with functional status to adjust the
home health payment, utilizing these
OASIS items for inclusion in the HHGM
was a primary focus. All OASIS items,
including items not used in the current
case-mix adjustment methodology, were
evaluated for potential inclusion in the
HHGM. OASIS items were eliminated
for inclusion based on statistical factors
(for example, the relationship of the
item with resource use), clinical factors
(for example, clinical appropriateness of
using the item for payment purposes)
and incentive factors (for example,
potential for unintended consequences
such as overutilization solely for
increased reimbursement).
We presented our analysis of the
OASIS items to a clinical workgroup
that included physicians, nurses, and
therapists with substantial home health
clinical expertise, to obtain input
regarding which OASIS items to include
in the HHGM. Based on the clinical
workgroup feedback and additional
analyses by the research team, the
following decisions were made
regarding the narrowed list of OASIS
items being considered for a functional
status payment adjustment under the
HHGM: 81
• M066, M0110: Age, Episode
timing—Both age and episode timing
were determined to be appropriate for
the HHGM, but both items can be
accurately obtained directly from the
home health claims data, rather than the
OASIS. As such, responses on these
OASIS items would not be used for this
functional status adjustment under the
HHGM.
• M1018, M1030: Selected prior
conditions and types of therapies a
patient receives—These OASIS items
would not be used for functional status
adjustment in the HHGM because the
clinical groups, specifically Complex
Nursing Interventions, (described in
section III.E.6. of this proposed rule)
account for most of the conditions
described in these OASIS items (for
example, IV therapy, TPN) so using
81 Version OASIS C items were used for this
initial analysis.
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these OASIS items would be
duplicative.
• M1200: Vision—The clinical
workgroup believed this OASIS item to
be clinically significant. However, while
this item is used in the current HH PPS,
there are no longer ‘‘points’’ associated
with this item for the clinical domain
because there is no additional resource
use related to this item beyond the
average across all periods of care.
Additionally, analysis of this vision
impairment OASIS item showed
decreased resource use in the HHGM
and; therefore, was determined to have
a counterintuitive relationship. As a
result, this OASIS item would not be
used for functional status adjustment in
the HHGM. Analysis of this item is
found in the ‘‘Overview of the Home
Health Groupings Model’’ technical
report found on the HHA Center Web
page.82
• M1220, M1230: Understanding of
verbal content, speech and oral—These
items were determined to be subjective
in nature and may not provide
information that is an accurate
reflection of the patient’s cognitive
status. As with other OASIS items in
this analysis, these items showed that
there was decreased resource costs
associated with worsening status. As a
result, these OASIS items would not be
used for functional status adjustment in
the HHGM.
• M1242: Pain—While this item is
used in the current HH PPS, this is
shown to have only a minimal
relationship with resource use in the
current payment model. Although the
clinical workgroup believed this item to
be clinically significant, CMS clinicians
agreed this one item alone may not be
robust enough to fully capture the pain
presentation of the patient and its
impact on resource utilization.
Therefore, this OASIS item would not
be used for functional status adjustment
in the HHGM.
• M1302, M1308, M1320, M1322,
M1324, M1332, M1334, and M1340:
Ulcers and wounds—These OASIS
items would not be used for functional
status adjustment in the HHGM because
the Wound clinical group (described in
section III.E.6.of this proposed rule)
already adjusts the period payment for
these conditions and using these OASIS
items would be duplicative.
• M1400: Shortness of breath—
Although the clinical workgroup
believed this item to be clinically
significant, this OASIS item would not
82 ‘‘Overview of the Home Health Groupings
Model’’ technical report, Appendix Exhibit A7–1 on
the HHA Center Web page (https://www.cms.gov/
center/provider-type/home-health-agency-hhacenter.html).
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be used for functional status adjustment
in the HHGM because the analysis
showed decreased resource costs with
worsening dyspnea which appears to be
clinically counterintuitive.83
• M1700—M1750: Cognitive items—
These items were initially determined to
be clinically appropriate for inclusion in
the HHGM but were later removed due
to analysis that showed a
counterintuitive relationship, meaning
costs decreased as cognitive status
worsened. This negative relationship
with resource use was consistent with
most of the OASIS cognitive items. This
analysis is discussed more in depth in
this section below and the full analysis
of all of the cognitive items is found in
the technical report.
• M1800—M1890: Functional items—
These OASIS items include both ADLs
and Instrumental Activities of Daily
Living (IADLs). ADLs are routine
activities that people tend to do every
day without needing assistance. There
are six basic ADLs: Eating, bathing,
dressing, toileting, transferring
(walking) and continence. IADLs are
activities related to independent living
and include preparing meals, managing
money, shopping for groceries or
personal items, performing light or
heavy housework, doing laundry, and
using a telephone. While most of these
items were determined to be clinically
appropriate for inclusion in the HHGM,
M1870–M1890 (IADLs) would not be
used for functional status adjustment in
the HHGM due to responses having a
negative relationship with resource use
(for example, worsening status in
performing IADLs was associated with
decreased resource use).
• M2030: Management of injectable
medications—This OASIS item would
not be used for functional status
adjustment in the HHGM because most
of the responses associated with this
item reflected less resource use when
the patient increasingly had issues with
preparing and taking injectable
medications. We believe that clinically
counterintuitive relationships resulting
from responses to OASIS items, where
the expectation would be to see
increased resource costs associated with
decreased function or ability, should not
be included in the case mix adjustment.
In addition to the OASIS items listed
above, the clinical workgroup also
discussed M2100 (types and sources of
assistance-specifically non-HHA
caregiver assistance). Workgroup
members agreed that the availability of
non-agency caregiver assistance can be
an important determinant of home
health care needs. Caregiver availability
83 Ibid.
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caregiver(s), also showed a
counterintuitive and contradicting
relationship with M2100. Therefore,
these OASIS items would not be
included as part of the functional status
payment adjustment under the HHGM.
During the analysis of functional case
mix adjustment under the HHGM, a
review of the literature revealed growing
evidence suggesting that cognitive
dysfunction is an important risk factor
in the development of functional
disability and loss of independence.86
The research team analyzed the
responses to the OASIS items associated
with cognitive status, but found there
was decreased resource use associated
with worsening cognitive status. We
decided to further evaluate OASIS
cognitive items (M1700–1750) in
addition to functional items (M1800–
1860), as well as other possible OASIS
items that may contribute to overall
function status. The following OASIS
items were determined to be indicators
of cognitive and functional status that
potentially could be used as case mix
adjusters:
• M066: Age.
• M1032: Risk of Hospitalization.
• M1220: Understanding of Verbal
Content.
• M1230: Speech and Oral (Verbal)
Expression of Language.
• M1700: Cognitive functioning.
• M1710: Confusion indicator.
• M1720: Anxiety indicator.
• M1740: Cognitive, behavioral, and
psychiatric symptoms.
• M1745: Frequency of disruptive
behavior symptoms.
• M1750: Receipt of psychiatric
nursing services.
• M1800: Grooming.
• M1810: Current ability to dress
upper body safely.
• M1820: Current ability to dress
lower body safely.
• M1830: Bathing.
• M1840: Toilet transferring.
• M1845: Toilet hygiene.
• M1850: Transferring.
• M1860: Ambulation/locomotion.
One difficulty in using certain OASIS
items (for example, M1700) to examine
relationships with resource use is that
they are only questioned on the Start of
Care and Resumption of Care
assessments, and not on follow-up
assessments. Therefore, for this analysis,
as outlined in the technical report, we
looked back for the most recent period
in the same sequence of periods that
was linked to a Start of Care or
Resumption of Care assessment, and
carried forward the information from
that assessment to the subsequent
periods of care linked to follow-up
(recertification) assessments. Analysis of
these items, including looking at
interactions between certain items,
continued to show decreased resource
use associated with worsening severity.
The research team believed that
clinically counterintuitive relationships
to resource use may have the
unintended consequence of
discouraging HHAs to provide the
appropriate amount of care to the
patients who are clinically complex and
need home health services the most.
For several of the OASIS items listed
above, particularly the functional items,
worsening status is associated with
higher resource use, indicating that
these items may be useful as adjustors
to construct case-mix weights for the
HHGM. However, several responses
within other individual OASIS items
had very similar average resource use.
Due to the lack of variation in resource
use across certain responses and
because certain responses were
infrequently chosen, some responses
were combined into larger response
categories to better capture the
relationship between worsening status
and resource use. Responses on these
OASIS items were combined using the
following methodology:
• Responses that corresponded to a
small number of periods were combined
with responses that corresponded to a
larger number of periods and;
• Responses that had similar average
resource use were combined together.
The resulting combinations of
responses for these OASIS items are
found at Exhibit 7–2 in the HHGM
technical report.87
After making these combinations, the
newly combined OASIS items and
resource use were analyzed again to
determine if those OASIS items could
be used to help case-mix adjust periods
within the HHGM. Results showed that
decreasing functional status, increasing
age, and increasing risk of
hospitalization tended to be associated
with higher resource use, while
worsening cognitive status tended to be
associated with lower resource use. The
relationship between worsening
cognitive status but lower resource use
is counterintuitive to existing research
regarding cognitive status and health
86 Njegovan, V., Man-Song-Hing, M., Mitchell, S.,
Molnar, F.(2001). ‘‘The Hierarchy of Functional
Loss Associated with Cognitive Decline in Older
Persons’’. Journal of Gerontology. 56A(10), M638–
643.
and assistance was a focus in the Report
to Congress ‘‘Medicare Home Health
Study: An Investigation on Access to
Care and Payment for Vulnerable
Patient Populations’’. Vulnerable patient
populations examined in this study
included those patients with minimal or
no caregiver support. Results from this
study revealed that HHAs and
physicians stated that family or
caregiver issues are an important
contributing factor in the inability to
admit or place patients in home
health.84 However, 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 alone may be limited.85 OASIS–
C item M2100 identifies the ability and
willingness of the caregiver(s) (other
than home health agency staff) to
provide categories of assistance needed
by the patient, including ADL/IADL
assistance, medication administration,
and management of equipment. This
particular OASIS item is multi-faceted,
meaning this items requires one of six
responses for seven different types of
caregiver assistance. Because the
responses to this item generally are not
based on direct observation by the
clinician conducting the assessment,
this presents a limitation for use in a
case mix adjustment as the accuracy of
the responses cannot be easily
validated. Patients or caregivers may
overestimate or underestimate their
ability or willingness to assist in the
patient’s care. Analysis of the resource
use associated with this item showed
ambiguous results where the same
response (‘‘assistance needed, but no
caregiver(s) available’’) would be
associated with increased resource costs
for certain types of assistance but
decreased resource costs for other types
of assistance. We believe this is
clinically counterintuitive as it would
be expected that if a need for caregiver
assistance exists but there are no
available caregivers, then the result
would be an increased need for
resources for all of the types of caregiver
assistance listed on this OASIS item.
Analysis of OASIS–C item M2110,
frequency of ADL/IADL assistance,
which identifies the frequency of
assistance provided by non-agency
84 Report to Congress Medicare Home Health
Study: An Investigation on Access to Care and
Payment for Vulnerable Patient Populations.
Available at https://www.cms.gov/Medicare/
Medicare-Fee-for-Service-Payment/
HomeHealthPPS/Downloads/HH-Report-toCongress.pdf.
85 Ibid.
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87 https://www.cms.gov/center/provider-type/
home-health-agency-hha-center.html?redirect=/
center/hha.asp; https://downloads.cms.gov/files/
hhgm%20technical%20report%20120516%20
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care costs.88 To further explore the
relationship between the functional and
cognitive OASIS items and resource use,
additional analyses were conducted
where the coefficients (that is, resource
costs) associated with the functional
and cognitive items were converted into
a table of points to calculate the
functional score for home health periods
of care. However, even after controlling
for each OASIS variable (as well as
other components of the HHGM), the
general trends between the cognitive
and functional items from the other
analyses remained the same. That is,
worsening cognitive status was
generally associated with less resource
use; worsening functional status was
generally associated with increased
resource use; increased risk of
hospitalization was associated with
increased resource use; and age was not
associated with either increased or
decreased resource use. The summary
statistics of these analyses are found at
Exhibit 7–3 of the technical report,
‘‘Overview of the Home Health
Groupings Model’’.89 Therefore, we
decided not to include those OASIS
items with these types of inverse
relationships to resource costs as part of
the adjustment to the HHGM period
payment. However, given the research
support and clinical input from home
health clinicians, we will continue to
analyze the inclusion of cognitive items
into the HHGM case mix adjustment.
The analyses of the complete list of all
OASIS items analyzed can be found in
the Appendix Exhibits A7–1 and A7–2
of the technical report mentioned above.
On the basis of input from the clinical
workgroup and these analytic results, all
cognitive items, functional items with a
negative relationship with resource use,
and age were removed and the model
was re-estimated. Each OASIS item
included in the final model has a
positive relationship with resource use,
meaning as functional status declines
(as measured by a higher response
category), periods have more resource
use on average. Additionally, periods
with a higher risk of hospitalization
(meaning four or more items checked on
M1033) are associated with higher
resource use compared with periods
with a lower risk of hospitalization.
This indicates that these items could be
used to help risk adjust a period’s
payment and help determine case-mix
weights for the HHGM. As such, we are
proposing that the following OASIS
items be included as part of the
functional payment adjustment under
the proposed HHGM:
• M1800: Grooming.
• M1810: Current Ability to Dress
Upper Body.
• M1820: Current Ability to Dress
Lower Body.
• M1830: Bathing.
• M1840: Toilet Transferring.
• M1850: Transferring.
• M1860: Ambulation/Locomotion.
• M1032 (M1033 in OASIS–C1): Risk
of Hospitalization.90
While the original analyses of these
OASIS functional items were conducted
using CY 2013 data from the OASIS–C
version (as presented in the technical
report), the updated analyses for CY
2016 reported in Tables 36, 37, and 38
are based on data obtained from OASIS
C–1. While the OASIS item number for
‘‘Risk of Hospitalization’’ changed from
M1032 (in OASIS C) to M1033 (in
OASIS C–1), the remaining OASIS items
(and item numbers) used for this
functional adjustment analysis are the
same. As discussed earlier in this
section, to facilitate the interpretation of
this analysis of the functional items
used to construct the case mix weights,
the results of this analysis were
converted into a table of points that can
be used to calculate the functional score
for a home health period. Table 36
shows the points for 2013 and 2016 for
those items associated with increased
resource use using a reduced set of
OASIS C–1 items:
TABLE 36—OASIS POINTS TABLE FOR THOSE ITEMS ASSOCIATED WITH INCREASED RESOURCE USE USING A REDUCED
SET OF OASIS ITEMS, CY 2013 AND CY 2016
Variable
Response
category
M1800: Grooming ................................................................
M1810: Current Ability to Dress Upper Body ......................
M1820: Current Ability to Dress Lower Body ......................
1
1
1
2
1
2
3
1
1
2
1
2
3
4 or more
items checked
M1830: Bathing ....................................................................
M1840: Toilet Transferring ...................................................
M1850: Transferring .............................................................
M1860: Ambulation/Locomotion ..........................................
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M1032 (M1033 for OASIS C–1): Risk of Hospitalization ....
88 P.P. Pandharipande, T.D. Girard, J.C. Jackson,
A. Morandi, J.L. Thompson, B.T. Pun, N.E.
Brummel, C.G. Hughes, E.E. Vasilevskis, A.K.
Shintani, K.G. Moons, S.K. Geevarghese, A.
Canonico, R.O. Hopkins, G.R. Bernard, R.S. Dittus,
and E.W. Ely. (2013). ‘‘Long-Term Cognitive
Impairment after Critical Illness’’. The New England
Journal of Medicine. 369(14), 1306–14.
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Points
(2013)
Points
(2016)
3
4
7
10
6
17
25
4
7
13
13
17
27
12
89 Abt Associates. ‘‘Overview of the Home Health
Groupings Model.’’ Medicare Home Health
Prospective Payment System: Case-Mix
Methodology Refinements. Cambridge, MA,
November 18, 2016. Accessed on April 27, 2017 at
https://www.cms.gov/center/provider-type/homehealth-agency-hha-center.html?redirect=/center/
hha.asp; https://downloads.cms.gov/files/
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Percent of
periods in
2013
with this
response
category
(%)
4
6
6
12
4
14
22
5
4
9
12
15
27
11
41.5
46.6
52.1
16.4
24.4
46.1
19.1
20.3
61.6
29.2
37.7
33.0
12.7
12.6
Percent of
periods in
2016
with this
response
category
(%)
51.9
55.6
57.5
19.6
20.3
51.6
21.9
28.2
47.7
48.0
29.0
47.8
14.2
16.3
hhgm%20technical%20report%20120516
%20sxf.pdf.
90 In Version OASIS C–1, two responses were
excluded: ‘‘currently reports exhaustion’’ and
‘‘other risks not listed in 1–8’’.
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Similar to the current case-mix
adjustment methodology, the points
generated in Table 36 were then used to
create a functional score for each home
health period of care in the HHGM. That
is, a home health period of care receives
points based on each of the responses
associated with the OASIS items listed
above. The sum of all of these points
results in a functional score which is
used in the HHGM to group home
health periods into a functional level.
As part of the HHGM case-mix
adjustment, we are proposing to assign
points for each of the responses to the
proposed OASIS functional items and to
sum up the points to create a functional
score for the period of care. Whereas the
results presented in the technical report
showed that the number of functional
levels varied by clinical group,
continued analysis ultimately
established three functional levels for
each of the clinical groups—low,
medium and high, with approximately
one third of home health periods from
each of the clinical groups within each
level. This means home health periods
in the low level have responses for the
above OASIS items that are associated
with the lowest resource use on average.
Home health periods in the high level
have responses on the above OASIS
items that are associated with the
highest resource use on average. We are
proposing to use the three functional
levels of low, medium, and high, based
on the CY 2016 data for each of the
clinical groups. Table 37 shows the
functional thresholds for each
functional level by clinical group for
CYs 2013 and 2016.
TABLE 37—THRESHOLDS FOR FUNCTIONAL LEVELS BY CLINICAL GROUP, CY 2013 AND CY 2016
Clinical group
Level
MMTA ................................................................................................................................................
Low ..........
Medium ....
High .........
Low ..........
Medium ....
High .........
Low ..........
Medium ....
High .........
Low ..........
Medium ....
High .........
Low ..........
Medium ....
High .........
Low ..........
Medium ....
High .........
Behavioral Health ..............................................................................................................................
Complex Nursing Interventions .........................................................................................................
Musculoskeletal Rehabilitation ..........................................................................................................
Neuro Rehabilitation ..........................................................................................................................
Wound ................................................................................................................................................
Points
(2013 data)
0–36
37–55
56+
0–30
31–55
56+
0–33
34–60
61+
0–37
38–55
56+
0–48
49–67
68+
0–41
42–65
66+
Points
(2016 data)
0–36
37–54
55+
0–38
39–57
58+
0–36
37–59
60+
0–39
40–55
56+
0–49
50–66
67+
0–42
43–65
66+
Table 38 shows the average resource
use by clinical group and functional
level for CY 2016:
TABLE 38—AVERAGE RESOURCE USE BY CLINICAL GROUP AND FUNCTIONAL LEVEL, CY 2016
mstockstill on DSK30JT082PROD with PROPOSALS2
Mean resource
use
Frequency
of periods
Percent of
periods
Standard
deviation
of resource
use
25th Percentile
of resource
use
Median
resource use
75th Percentile
of resource
use
MMTA—Low ................
MMTA—Medium ..........
MMTA—High ................
Behavioral Health—Low
Behavioral Health—Medium ..........................
Behavioral Health—
High ..........................
Complex—Low .............
Complex—Medium .......
Complex—High ............
MS Rehab—Low ..........
MS Rehab—Medium ....
MS Rehab—High .........
Neuro—Low .................
Neuro—Medium ...........
Neuro—High ................
Wound—Low ................
Wound—Medium .........
Wound—High ...............
$1,216.76
1,466.19
1,637.21
963.97
1,683,279
1,594,451
1,628,441
100,572
19.48
18.45
18.84
1.16
$1,091.11
1,182.78
1,284.34
847.72
$880.56
1,163.49
1,334.00
679.14
$507.63
617.07
695.10
407.74
$1,589.76
1,979.71
2,216.12
1,255.47
1,308.10
94,030
1.09
1,018.11
1,040.79
543.96
1,780.03
1,501.87
1,425.30
1,797.33
1,917.72
1,519.02
1,730.99
1,891.42
1,594.59
1,847.36
2,020.14
1,860.42
2,052.45
2,258.66
94,911
120,528
106,056
109,665
478,059
480,676
472,078
283,573
233,398
255,608
305,556
303,435
297,791
1.10
1.39
1.23
1.27
5.53
5.56
5.46
3.28
2.70
2.96
3.54
3.51
3.45
1,107.73
1,356.53
1,593.76
1,723.31
1,048.29
1,121.66
1,241.57
1,169.30
1,271.54
1,473.75
1,550.96
1,603.05
1,814.01
1,237.97
1,019.77
1,354.89
1,430.70
1,298.20
1,534.42
1,671.24
1,327.08
1,581.08
1,682.68
1,436.36
1,646.76
1,771.12
662.86
582.12
739.39
756.59
753.88
921.87
1,004.59
739.60
914.70
947.61
861.98
980.27
1,043.72
2,047.39
1,795.04
2,340.46
2,536.16
2,025.52
2,296.70
2,501.81
2,137.34
2,487.14
2,715.74
2,345.97
2,634.01
2,897.54
Total ......................
1,585.48
8,642,107
100.00
1,289.23
1,262.65
671.96
2,119.49
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Like the annual recalibration of the
case-mix weights under the current HH
PPS, we expect that annual
recalibrations would also be made to the
HHGM case-mix weights. If the HHGM
is finalized, we will continue to analyze
all of the components of the case-mix
adjustment, including adjustment for
functional status, and would make
refinements as necessary to ensure that
payment for home health periods are in
alignment with costs. We invite
comments on the proposed OASIS items
and the associated points and
thresholds used to group patients into
three functional levels under the
HHGM, as outlined above.
8. Comorbidity Adjustment
The HHGM groups home health
periods based on the primary reason for
home health care (principal diagnosis),
functional level, admission source, and
timing. To further account for
differences in resource use based on
patient characteristics in the
development of the HHGM, we analyzed
the presence of comorbidities as another
factor that could impact resource
utilization and costs. We conducted a
comprehensive literature review
examining published, peer-reviewed
research regarding the relationship
between comorbidity and resource
use.91 This review also included
findings on those conditions that impact
health care resource utilization. Based
on this review and findings, we propose
a comorbidity adjustment to account for
higher costs associated with
comorbidities.
A comorbidity is most often defined
as two or more coexisting medical
conditions or disease processes that are
in addition to an initial diagnosis.92
Typically, a comorbidity is a
condition(s) in which there is no direct
correlation in the treatment of the
principal diagnosis, but the presence of
that condition(s) may impact the home
health plan of care in terms of resource
utilization and costs. With aging, the
presence of comorbidity increases
markedly because the frequency of
individual conditions arises with age.
While the elderly are far more likely to
have multiple comorbidities,
comorbidities also are prevalent in
Medicare beneficiaries under the age of
65 who have intellectual and physical
disabilities.93 Research has repeatedly
91 Appendix Exhibit A9–1, ‘‘Overview of the
Home Health Groupings Model’’, 2016. 12–23–12–
26. https://www.cms.gov/center/provider-type/
home-health-agency-hha-center.html.
92 Mosby’s Medical Dictionary, 9th edition.
©2009, Elsevier.
93 Cooper, S., McLean, G., Guthrie, B.,
McConnachie, A., Mercer, S., Sullivan, F.,
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shown that comorbidity is associated
with high health care utilization and
expenditures.94 Additionally,
comorbidity is tied to worse health
outcomes and the need for more
complex treatment and disease
management, which in turn results in
higher health care costs.95 Patients with
comorbidities tend to be high users of
home health visits and overall Medicare
spending increases with the number of
chronic conditions.96
In the home health setting,
information regarding the patient’s
health conditions for which home
health services are provided are
assessed and documented by skilled
clinicians on the OASIS. These
conditions would include secondary
diagnoses in addition to the principal
diagnosis supporting the need for home
health services. As such, exploratory
analyses for the HHGM determined that
secondary diagnoses (that is,
comorbidities) provide additional
information that can predict resource
use even after controlling for the
period’s clinical group. We examined
multiple approaches for a comorbidity
adjustment in the HHGM and the
analyses on these approaches is found
in the ‘‘Overview of the Home Health
Groupings Model’’ technical report
found on the HHA Center Web page.
Based on the results of these analyses,
we moved towards the development of
a home health specific comorbidity list
for the HHGM comorbidity adjustment.
For the analysis of a comorbidity
adjustment in the HHGM, some
diagnosis exclusions were made. Under
the HHGM, certain reported principal
diagnosis codes, including some ICD–
10–CM ‘‘R-codes’’ (R00–R99) which
identify symptoms and abnormal
clinical findings, would be considered a
‘‘questionable encounter’’, meaning
these codes may be too vague to group
the home health period, subject to
sequencing or other ICD–10–CM coding
conventions, not a Medicare-covered
diagnosis, or a condition unlikely to
require home health services. For these
‘‘questionable encounters’’, more
Morrison, J. (2015). ‘‘Multiple physical and mental
health comorbidity in adults with intellectual
disabilities’’. BMC Family Practice. 16(110), 1–11.
doi 10.1186/s12875–015–0329–3.
94 Fried, L., Ferrucci, L., Darer, J., Williamson, J.,
Anderson, G. (2004). ‘‘Untangling the Concepts of
Disability, Frailty, and Comorbidity: Implications
for Improved Targeting and Care’’. Journal of
Gerontology. 59(3), 255–263.
95 Starfield, B., Lemke, K., Bernhardt, T., Foldes,
S., Forrest, C., Weiner, J. (2003). ‘‘Comorbidity:
Implications for the Importance of Primary Care in
Case Management’’. Annals of Family Medicine.
1(1), 8–14.
96 https://www.cdc.gov/chronicdisease/about/
multiple-chronic.html.
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information was needed to assign the
period to a clinical group. This meant,
for analysis purposes only, we looked at
the secondary diagnoses to assign the
home health period to one of the six
clinical groups. As such, those periods
with a principal diagnosis that was
determined to be a ‘‘questionable
encounter’’ code were excluded from
our comorbidity adjustment analysis.
However, if the HHGM is finalized, we
are proposing that claims submitted
with principal reported diagnosis codes
that are considered ‘‘questionable
encounters’’ would be returned to the
provider for more definitive coding.
Once the claim is resubmitted without
a principal diagnosis that is considered
a ‘‘questionable encounter’’, the home
health period would be grouped into
one of the six clinical groups. The
secondary diagnoses on those
resubmitted claims would then be
eligible for the comorbidity adjustment.
Another exclusion from this
comorbidity analysis included those
secondary diagnoses that had the same
three character ICD–10–CM code as the
diagnosis used to assign a case to a
particular clinical group (that is,
musculoskeletal rehab, neuro/stroke
rehab, wounds, behavioral health,
complex nursing interventions, and
MMTA). An additional exclusion was
added that applied to diagnoses that
identify an unspecified site or side
(meaning the code is defined by
laterality or site specificity). There are
ICD–10–CM codes that are specific to
site, laterality, and proximal versus
distal parts of the body. For example,
L89.004, Pressure ulcer of unspecified
elbow, stage 4, can be coded to identify
whether the pressure ulcer is on the left
or right elbow. ICD–10 CM coding
guidelines state to report diagnoses to
the greatest level of specificity. The
home health clinician should be able to
identify the specific side or body part
involved through either direct
assessment or of a query of the
certifying physician.
Finally, an exclusion was added for
some secondary diagnoses that would
not be considered a comorbidity if
reported with certain Z codes. For
example, if Z96.651, presence of right
artificial knee joint, is reported as
secondary, it would not be considered a
comorbidity if Z47.1, aftercare following
joint replacement surgery, was reported
as the principal diagnosis. The
secondary diagnosis in this scenario is
not a comorbidity because this
secondary diagnosis explains the reason
for the aftercare. We are utilizing this
approach to minimize the unintended
consequence of providers reporting
comorbidities that are duplicative of the
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principal diagnosis, or are a further
description of the principal diagnosis,
which could potentially overestimate
the actual resources needed for a home
health period and could result in
inaccurate payment.
Using the research from the
comprehensive literature review, we
identified common chronic comorbid
conditions frequently cited as drivers of
increased health care resource
utilization, including coronary artery
disease, congestive heart failure,
diabetes, COPD, asthma, chronic
wounds, and depression.97 In addition
to chronic comorbid conditions, other
acute comorbid conditions have been
shown to affect overall resource
utilization as well. These conditions
include pneumonia, Clostridium
difficile (c-diff), and Methicillinresistant Staphylococcus aureus
(MRSA).98 After compiling a list of both
acute and chronic comorbid diagnoses
that could affect home health resource
utilization, we conducted initial
analyses looking at controlling for the
presence of the individual diagnoses.
However, these analyses showed some
counterintuitive relationships with
resource use, meaning the presence of
certain comorbidities showed that there
would be less resource use than if the
comorbidity was not present.
Because the core of the HHGM is a
clinical one, CMS clinicians utilized the
principles of patient assessment by body
systems and their associated diseases,
conditions, and injuries as a way to
examine potential clinically relevant
relationships. Next, we combined those
individual diagnoses into larger
categories utilizing the body systems as
a clinically intuitive way to consider
what diagnoses potentially could impact
the home health plan of care and
resource utilization. When combining
the individual diagnoses into larger
comorbidity categories, the
counterintuitive relationships
decreased. These broad body system
categories include conditions, diseases,
and injuries that affect each of the
individual body systems (for example,
heart disease). Neoplasms and
infectious diseases were given their own
97 Center for Healthcare Research and
Transformation. (2010) ‘‘Healthcare Cost Drivers:
Chronic Disease, Comorbidity, and Health Risk
Factors in the U.S. and Michigan.’’ https://
www.chrt.org/publication/health-care-cost-driverschronic-disease-comorbidity-health-risk-factors-u-smichigan/.
98 Drikoningen, J., Rohde, G., (2010).
‘‘Pneumococcal Infection in Adults: Burden of
Disease’’. Clinical Microbiology and Infection. 45–
51. Kyne, L., Hamel, M.B., Polavaram, R., Kelly, C.
(2002). ‘‘Health Care Costs and Mortality Associated
with Nosocomial Diarrhea due to Clostridium
difficile’’. Clinical Infectious Diseases. 346–353.
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discrete categories because of their
potential to affect more than one body
system. The broad categories used to
group comorbidities within the HHGM
were further refined by grouping similar
diagnoses within the broad categories
into subcategories. The subcategories
allowed for additional refinement of
diagnoses to include as part of the home
health specific list. Subcategories were
distinguished primarily (but not
exclusively) by the first three characters
of the ICD–10–CM diagnosis code to
represent related conditions within the
same body system. For example,
subcategory Heart 10 includes diagnoses
associated with various cardiac
arrhythmias. The home health specific
comorbidity list includes 13 broad body
system based categories and 116 total
subcategories using ICD–10–CM
diagnosis codes. The broad categories
used to group comorbidities within the
HHGM include the following:
• Heart Disease (11 subcategories).
• Respiratory Disease (9
subcategories).
• Circulatory Disease and Blood
Disorders (12 subcategories).
• Cerebral Vascular Disease (4
subcategories).
• Gastrointestinal Disease (9
subcategories).
• Neurological Disease and
Associated Conditions (11
subcategories).
• Endocrine Disease (6 subcategories).
• Neoplasm (24 subcategories).
• Genitourinary and Renal Disease (5
subcategories).
• Skin Disease (5 subcategories).
• Musculoskeletal Disease or Injury (5
subcategories).
• Behavioral Health (11
subcategories).
• Infectious Disease (4 subcategories).
The secondary diagnoses listed on the
OASIS that are attributed to any one of
the listed subcategories were used to
identify whether a period fell into one
or more comorbidity categories and
subcategories.
For the purpose of evaluating these
identified comorbidities for inclusion in
the HHGM, we assigned the CY 2016
home health periods that reported a
secondary diagnosis included on this
home health specific list to a
comorbidity subcategory and
subsequently dropped any subcategories
that were in less than 0.1 percent of
periods. This was done because low
volume leads to instability in our
estimates of how resource use is related
to the comorbidity. A regression model
was used to determine the relationship
between the remaining subcategories
and resource use. After this analysis, we
dropped comorbidity subcategories that
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35323
were not statistically significant with
regards to their relationship to resource
use (a coefficient with a p-value greater
than 0.05). After these exclusions, we
kept the subcategories associated with
increased resource use that was at least
as high as the median resource use, as
they indicated a direct relationship
between the comorbidity subcategories
and resource utilization. These
remaining subcategories would receive a
comorbidity adjustment. As such, there
are 15 subcategories that meet the
current criteria for the comorbidity
adjustment in the HHGM. This is a
decreased number of subcategories that
were presented in the technical report
where 29 subcategories met the criteria
to qualify for the comorbidity
adjustment. The comorbidity analysis
presented in the technical report was
based on CY 2013 data and used ICD–
9–CM diagnosis codes. There are several
potential reasons for this decrease
including that the analysis exclusions
for the 2016 analysis were slightly
different than were used in the technical
report. Another potential reason for the
decrease in subcategories may be due to
diagnosis exclusions based on changes
from ICD–9–CM to ICD–10–CM with
regards to specificity. Some of this
decrease could be related to the changes
in case-mix weights from 2013 to 2016
where secondary conditions that
received clinical points in 2013 may not
have had any associated points in 2016
and hence, there would be no incentive
to report those conditions. The analysis
on the CY 2013 and CY 2016 data,
including all of the diagnoses and their
assigned subcategories is posted on the
HHA Center Web page.99 The 15
subcategories included in the
comorbidity adjustment in the HHGM
are as follows:
• Heart Disease 1: Includes
hypertensive heart disease.
• Cerebral Vascular Disease 4:
Includes sequelae of cerebrovascular
disease.
• Circulatory Disease and Blood
Disorders 9: Includes venous embolisms
and thrombosis.
• Circulatory Disease and Blood
Disorders 10: Includes varicose veins of
lower extremities with ulcers and
inflammation, and esophageal varices.
• Circulatory Disease and Blood
Disorders 11: Includes lymphedema.
• Endocrine Disease 2: Includes
diabetes with complications due to an
underlying condition.
• Neoplasm 18: Includes secondary
malignant neoplasms.
99 https://www.cms.gov/center/provider-type/
home-health-agency-hha-center.html.
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• Neurological Disease and
Associated Conditions 5: Includes
secondary parkinsonism.
• Neurological Disease and
Associated Conditions 7: Includes
encephalitis, myelitis,
encephalomyelitis, and hemiplegia,
paraplegia, and quadriplegia.
• Neurological Disease and
Associated Conditions 10: Includes
diabetes with neurological
complications.
• Respiratory Disease 7: Includes
pneumonia, pneumonitis, and
pulmonary edema.
• Skin Disease 1: Includes cutaneous
abscesses, and cellulitis.
• Skin Disease 2: Includes stage one
pressure ulcers.
• Skin Disease 3: Includes
atherosclerosis with gangrene.
• Skin Disease 4: Includes
unstageable and stages two through four
pressure ulcers.
We propose that if a period had at
least one secondary diagnosis reported
on the home health claim that fell into
one of the 15 subcategories, that period
would receive a comorbidity adjustment
to account for higher costs associated
with the comorbidity. The comorbidity
adjustment amount would be the same
across all of the subcategories. A period
would receive only one comorbidity
adjustment regardless of the number of
secondary diagnoses reported on the
home health claim that fell into one of
the 15 subcategories. Table 39 shows
information on resource use for periods
with and without the comorbidity
adjustment.
TABLE 39—FREQUENCY OF COMORBIDITY GROUPS AND DISTRIBUTION OF AVERAGE RESOURCE USE
Comorbidity group
Mean resource
use
Frequency of
periods
Percent of
periods
Standard
deviation of
resource use
25th Percentile
of resource
use
Median
resource use
75th Percentile
of resource
use
No Comorbidity Adjustment ..........................
Comorbidity Adjustment
$1,534.17
1,881.60
7,365,806
1,276,301
85.23
14.77
$1,228.43
1,562.89
$1,227.35
1,484.39
$653.57
803.15
$2,061.88
2,475.20
Total ......................
1,585.48
8,642,107
100.00
1,289.23
1,262.65
671.96
2,119.49
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The HHGM payment adjustment for
comorbidities is predicated on the
presence of one of the identified
diagnoses within the subcategories
associated with increased resource use
at or above the median. If there is no
reported diagnosis that meets the
comorbidity adjustment criteria, the
period would not qualify for the
payment adjustment. We consider this
comorbidity adjustment component of
the proposed HHGM to be fluid, where
OASIS-reported secondary diagnoses
may be removed from, or added to the
home health specific comorbidity list
dependent upon the relationship
between the comorbidity and resource
costs. If the HHGM is finalized and
implemented, we anticipate there may
be behavioral shifts in secondary
diagnosis reporting and the proposed
comorbidity list and its associated
subcategories may change to capture
resource utilization associated with
these or other conditions. We invite
comments on the proposed comorbidity
diagnoses, including additions or
subtractions to the proposed home
health specific list, and this comorbidity
adjustment approach under the HHGM.
9. Change in the Low-Utilization
Payment Adjustment (LUPA) Threshold
An episode with four or fewer visits
is paid the national per visit amount by
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discipline, adjusted by the appropriate
wage index based on the site of service
of the beneficiary, instead of the full
episode amount. Such payment
adjustments are called Low Utilization
Payment Adjustments (LUPAs). While
the proposed HHGM system would still
include LUPA payments, we are
proposing that the approach to
calculating the LUPA thresholds would
change in the HHGM because of the
proposed change in the unit of payment
to 30-day periods from 60-day episodes.
Whereas LUPAS are paid for all
episodes consisting of four or fewer
visits under the current payment
system, in order to receive full episode
amount under the HHGM (rather than
receive a LUPA where the episode
would be paid the national per visit
amount by discipline) we propose to
vary the LUPA threshold for a 30-day
period under the HHGM depending on
the HHGM payment group to which it
is assigned. The 30-day periods have
substantially more instances of four or
fewer visits than 60-day episodes. To
create LUPA thresholds, 30-day periods
(including those that were LUPAs in the
current payment system) were grouped
into the 144 different HHGM payment
groups. For each payment group, we
propose to set the LUPA threshold at the
10th percentile value of visits or 2 visits,
whichever is higher. In the current
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payment system approximately 8
percent of episodes are LUPAs. Under
the HHGM, we propose the 10th
percentile value of visits or 2 visits,
whichever is higher, to target
approximately the same percentage of
LUPAs (approximately 7 percent of 30day periods would be LUPAs (assuming
no behavior change)).
For example, for 30-day periods of
care in the payment group
corresponding to ‘‘MMTA– Functional
Level Medium—Early Timing—
Institutional Admission—No
Comorbidity Adjustment’’, the threshold
is four visits. If 30-day periods assigned
to that particular payment group had
three or fewer visits they would be paid
using the national per-visit rates in
section III.C.3 of this proposed rule
instead of the case-mix adjusted 30-day
payment amount. We propose that the
LUPA thresholds for each HHGM
payment group would be re-evaluated
every year based on the most current,
complete utilization data available. The
LUPA thresholds, based on the most
current utilization data available (CY
2016 data as of March 17, 2017), for
each corresponding HIPPS code, are
listed in Table 40. We would propose
updated LUPA thresholds using the
most current, complete utilization data
available at the time of rulemaking.
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TABLE 40—PROPOSED LUPA THRESHOLDS FOR THE PROPOSED HHGM PAYMENT GROUPS BASED ON CY 2016
UTILIZATION DATA
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HIPPS
Clinical group and functional level
1AAN ................
1AAY .................
1ABN ................
1ABY .................
1ACN ................
1ACY ................
1BAN ................
1BAY .................
1BBN ................
1BBY .................
1BCN ................
1BCY ................
1CAN ................
1CAY ................
1CBN ................
1CBY ................
1CCN ................
1CCY ................
1DAN ................
1DAY ................
1DBN ................
1DBY ................
1DCN ................
1DCY ................
1EAN ................
1EAY .................
1EBN ................
1EBY .................
1ECN ................
1ECY ................
1FAN .................
1FAY .................
1FBN .................
1FBY .................
1FCN ................
1FCY .................
2AAN ................
2AAY .................
2ABN ................
2ABY .................
2ACN ................
2ACY ................
2BAN ................
2BAY .................
2BBN ................
2BBY .................
2BCN ................
2BCY ................
2CAN ................
2CAY ................
2CBN ................
2CBY ................
2CCN ................
2CCY ................
2DAN ................
2DAY ................
2DBN ................
2DBY ................
2DCN ................
2DCY ................
2EAN ................
2EAY .................
2EBN ................
2EBY .................
2ECN ................
2ECY ................
2FAN .................
MMTA—Low ................................................
MMTA—Low ................................................
MMTA—Medium ..........................................
MMTA—Medium ..........................................
MMTA—High ...............................................
MMTA—High ...............................................
Neuro—Low .................................................
Neuro—Low .................................................
Neuro—Medium ..........................................
Neuro—Medium ..........................................
Neuro—High ................................................
Neuro—High ................................................
Wound—Low ...............................................
Wound—Low ...............................................
Wound—Medium .........................................
Wound—Medium .........................................
Wound—High ..............................................
Wound—High ..............................................
Complex—Low ............................................
Complex—Low ............................................
Complex—Medium ......................................
Complex—Medium ......................................
Complex—High ...........................................
Complex—High ...........................................
MS Rehab—Low .........................................
MS Rehab—Low .........................................
MS Rehab—Medium ...................................
MS Rehab—Medium ...................................
MS Rehab—High ........................................
MS Rehab—High ........................................
Behavioral Health—Low ..............................
Behavioral Health—Low ..............................
Behavioral Health—Medium ........................
Behavioral Health—Medium ........................
Behavioral Health—High .............................
Behavioral Health—High .............................
MMTA—Low ................................................
MMTA—Low ................................................
MMTA—Medium ..........................................
MMTA—Medium ..........................................
MMTA—High ...............................................
MMTA—High ...............................................
Neuro—Low .................................................
Neuro—Low .................................................
Neuro—Medium ..........................................
Neuro—Medium ..........................................
Neuro—High ................................................
Neuro—High ................................................
Wound—Low ...............................................
Wound—Low ...............................................
Wound—Medium .........................................
Wound—Medium .........................................
Wound—High ..............................................
Wound—High ..............................................
Complex—Low ............................................
Complex—Low ............................................
Complex—Medium ......................................
Complex—Medium ......................................
Complex—High ...........................................
Complex—High ...........................................
MS Rehab—Low .........................................
MS Rehab—Low .........................................
MS Rehab—Medium ...................................
MS Rehab—Medium ...................................
MS Rehab—High ........................................
MS Rehab—High ........................................
Behavioral Health—Low ..............................
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Comorbidity
adjustment
Timing and admission source
Early—Community
Early—Community
Early—Community
Early—Community
Early—Community
Early—Community
Early—Community
Early—Community
Early—Community
Early—Community
Early—Community
Early—Community
Early—Community
Early—Community
Early—Community
Early—Community
Early—Community
Early—Community
Early—Community
Early—Community
Early—Community
Early—Community
Early—Community
Early—Community
Early—Community
Early—Community
Early—Community
Early—Community
Early—Community
Early—Community
Early—Community
Early—Community
Early—Community
Early—Community
Early—Community
Early—Community
Early—Institutional
Early—Institutional
Early—Institutional
Early—Institutional
Early—Institutional
Early—Institutional
Early—Institutional
Early—Institutional
Early—Institutional
Early—Institutional
Early—Institutional
Early—Institutional
Early—Institutional
Early—Institutional
Early—Institutional
Early—Institutional
Early—Institutional
Early—Institutional
Early—Institutional
Early—Institutional
Early—Institutional
Early—Institutional
Early—Institutional
Early—Institutional
Early—Institutional
Early—Institutional
Early—Institutional
Early—Institutional
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Early—Institutional
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28JYP2
No .....................
Yes ...................
No .....................
Yes ...................
No .....................
Yes ...................
No .....................
Yes ...................
No .....................
Yes ...................
No .....................
Yes ...................
No .....................
Yes ...................
No .....................
Yes ...................
No .....................
Yes ...................
No .....................
Yes ...................
No .....................
Yes ...................
No .....................
Yes ...................
No .....................
Yes ...................
No .....................
Yes ...................
No .....................
Yes ...................
No .....................
Yes ...................
No .....................
Yes ...................
No .....................
Yes ...................
No .....................
Yes ...................
No .....................
Yes ...................
No .....................
Yes ...................
No .....................
Yes ...................
No .....................
Yes ...................
No .....................
Yes ...................
No .....................
Yes ...................
No .....................
Yes ...................
No .....................
Yes ...................
No .....................
Yes ...................
No .....................
Yes ...................
No .....................
Yes ...................
No .....................
Yes ...................
No .....................
Yes ...................
No .....................
Yes ...................
No .....................
Threshold
(10th percentile or 2—
whichever is
higher)
4
4
4
4
4
4
4
5
5
5
5
5
5
4
5
5
5
5
3
3
3
3
3
3
5
5
5
5
5
5
3
3
4
4
4
4
3
4
4
5
4
4
5
5
6
6
5
5
4
4
5
5
4
5
3
4
4
4
4
4
5
5
6
6
6
7
3
35326
Federal Register / Vol. 82, No. 144 / Friday, July 28, 2017 / Proposed Rules
TABLE 40—PROPOSED LUPA THRESHOLDS FOR THE PROPOSED HHGM PAYMENT GROUPS BASED ON CY 2016
UTILIZATION DATA—Continued
mstockstill on DSK30JT082PROD with PROPOSALS2
HIPPS
Clinical group and functional level
Timing and admission source
Comorbidity
adjustment
2FAY .................
2FBN .................
2FBY .................
2FCN ................
2FCY .................
3AAN ................
3AAY .................
3ABN ................
3ABY .................
3ACN ................
3ACY ................
3BAN ................
3BAY .................
3BBN ................
3BBY .................
3BCN ................
3BCY ................
3CAN ................
3CAY ................
3CBN ................
3CBY ................
3CCN ................
3CCY ................
3DAN ................
3DAY ................
3DBN ................
3DBY ................
3DCN ................
3DCY ................
3EAN ................
3EAY .................
3EBN ................
3EBY .................
3ECN ................
3ECY ................
3FAN .................
3FAY .................
3FBN .................
3FBY .................
3FCN ................
3FCY .................
4AAN ................
4AAY .................
4ABN ................
4ABY .................
4ACN ................
4ACY ................
4BAN ................
4BAY .................
4BBN ................
4BBY .................
4BCN ................
4BCY ................
4CAN ................
4CAY ................
4CBN ................
4CBY ................
4CCN ................
4CCY ................
4DAN ................
4DAY ................
4DBN ................
4DBY ................
4DCN ................
4DCY ................
4EAN ................
4EAY .................
Behavioral Health—Low ..............................
Behavioral Health—Medium ........................
Behavioral Health—Medium ........................
Behavioral Health—High .............................
Behavioral Health—High .............................
MMTA—Low ................................................
MMTA—Low ................................................
MMTA—Medium ..........................................
MMTA—Medium ..........................................
MMTA—High ...............................................
MMTA—High ...............................................
Neuro—Low .................................................
Neuro—Low .................................................
Neuro—Medium ..........................................
Neuro—Medium ..........................................
Neuro—High ................................................
Neuro—High ................................................
Wound—Low ...............................................
Wound—Low ...............................................
Wound—Medium .........................................
Wound—Medium .........................................
Wound—High ..............................................
Wound—High ..............................................
Complex—Low ............................................
Complex—Low ............................................
Complex—Medium ......................................
Complex—Medium ......................................
Complex—High ...........................................
Complex—High ...........................................
MS Rehab—Low .........................................
MS Rehab—Low .........................................
MS Rehab—Medium ...................................
MS Rehab—Medium ...................................
MS Rehab—High ........................................
MS Rehab—High ........................................
Behavioral Health—Low ..............................
Behavioral Health—Low ..............................
Behavioral Health—Medium ........................
Behavioral Health—Medium ........................
Behavioral Health—High .............................
Behavioral Health—High .............................
MMTA—Low ................................................
MMTA—Low ................................................
MMTA—Medium ..........................................
MMTA—Medium ..........................................
MMTA—High ...............................................
MMTA—High ...............................................
Neuro—Low .................................................
Neuro—Low .................................................
Neuro—Medium ..........................................
Neuro—Medium ..........................................
Neuro—High ................................................
Neuro—High ................................................
Wound—Low ...............................................
Wound—Low ...............................................
Wound—Medium .........................................
Wound—Medium .........................................
Wound—High ..............................................
Wound—High ..............................................
Complex—Low ............................................
Complex—Low ............................................
Complex—Medium ......................................
Complex—Medium ......................................
Complex—High ...........................................
Complex—High ...........................................
MS Rehab—Low .........................................
MS Rehab—Low .........................................
Early—Institutional .......................................
Early—Institutional .......................................
Early—Institutional .......................................
Early—Institutional .......................................
Early—Institutional .......................................
Late—Community ........................................
Late—Community ........................................
Late—Community ........................................
Late—Community ........................................
Late—Community ........................................
Late—Community ........................................
Late—Community ........................................
Late—Community ........................................
Late—Community ........................................
Late—Community ........................................
Late—Community ........................................
Late—Community ........................................
Late—Community ........................................
Late—Community ........................................
Late—Community ........................................
Late—Community ........................................
Late—Community ........................................
Late—Community ........................................
Late—Community ........................................
Late—Community ........................................
Late—Community ........................................
Late—Community ........................................
Late—Community ........................................
Late—Community ........................................
Late—Community ........................................
Late—Community ........................................
Late—Community ........................................
Late—Community ........................................
Late—Community ........................................
Late—Community ........................................
Late—Community ........................................
Late—Community ........................................
Late—Community ........................................
Late—Community ........................................
Late—Community ........................................
Late—Community ........................................
Late—Institutional ........................................
Late—Institutional ........................................
Late—Institutional ........................................
Late—Institutional ........................................
Late—Institutional ........................................
Late—Institutional ........................................
Late—Institutional ........................................
Late—Institutional ........................................
Late—Institutional ........................................
Late—Institutional ........................................
Late—Institutional ........................................
Late—Institutional ........................................
Late—Institutional ........................................
Late—Institutional ........................................
Late—Institutional ........................................
Late—Institutional ........................................
Late—Institutional ........................................
Late—Institutional ........................................
Late—Institutional ........................................
Late—Institutional ........................................
Late—Institutional ........................................
Late—Institutional ........................................
Late—Institutional ........................................
Late—Institutional ........................................
Late—Institutional ........................................
Late—Institutional ........................................
Yes ...................
No .....................
Yes ...................
No .....................
Yes ...................
No .....................
Yes ...................
No .....................
Yes ...................
No .....................
Yes ...................
No .....................
Yes ...................
No .....................
Yes ...................
No .....................
Yes ...................
No .....................
Yes ...................
No .....................
Yes ...................
No .....................
Yes ...................
No .....................
Yes ...................
No .....................
Yes ...................
No .....................
Yes ...................
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Yes ...................
No .....................
Yes ...................
No .....................
Yes ...................
No .....................
Yes ...................
No .....................
Yes ...................
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Yes ...................
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Yes ...................
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Yes ...................
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Threshold
(10th percentile or 2—
whichever is
higher)
3
4
5
4
4
2
2
2
2
2
2
2
2
2
3
2
3
3
3
3
3
3
3
2
2
2
2
2
2
2
2
2
2
2
3
2
2
2
2
2
3
3
3
3
3
3
3
4
4
4
4
4
4
3
3
4
4
4
4
2
3
3
3
3
3
4
4
Federal Register / Vol. 82, No. 144 / Friday, July 28, 2017 / Proposed Rules
35327
TABLE 40—PROPOSED LUPA THRESHOLDS FOR THE PROPOSED HHGM PAYMENT GROUPS BASED ON CY 2016
UTILIZATION DATA—Continued
HIPPS
Clinical group and functional level
4EBN ................
4EBY .................
4ECN ................
4ECY ................
4FAN .................
4FAY .................
4FBN .................
4FBY .................
4FCN ................
4FCY .................
MS Rehab—Medium ...................................
MS Rehab—Medium ...................................
MS Rehab—High ........................................
MS Rehab—High ........................................
Behavioral Health—Low ..............................
Behavioral Health—Low ..............................
Behavioral Health—Medium ........................
Behavioral Health—Medium ........................
Behavioral Health—High .............................
Behavioral Health—High .............................
We invite public comments on the
LUPA threshold methodology proposed
for the HHGM and the associated
regulations text changes in section VIII.
of this proposed rule.
10. HH PPS Case-Mix Weights Under
the HHGM
Section 1895(b)(4)(B) of the Act
requires the Secretary to establish
appropriate case mix adjustment factors
for home health services in a manner
that explains a significant amount of the
variation in cost among different units
of services. We are proposing the HHGM
case-mix adjustment methodology,
which sorts 30-day periods of care into
different payment groups based on five
categories (admission source, timing,
clinical group, functional level, and
comorbidity group), for 30-day periods
of care that begin on or after January 1,
2019. In combination, this would yield
a total of 144 HHGM payment groups,
which we would still refer to as Home
Health Resource Groups (HHRGs) under
Comorbidity
adjustment
Timing and admission source
Late—Institutional
Late—Institutional
Late—Institutional
Late—Institutional
Late—Institutional
Late—Institutional
Late—Institutional
Late—Institutional
Late—Institutional
Late—Institutional
........................................
........................................
........................................
........................................
........................................
........................................
........................................
........................................
........................................
........................................
the HHGM. To generate HHGM case-mix
weights, we utilized a data file based on
home health episodes of care, as
reported in Medicare home health
claims, as well as OASIS assessment
data. The claims data provide episodelevel data, as well as visit-level data.
The claims also provide data on
whether NRS was provided during the
episode and the total charges for NRS.
We determined the case-mix weight for
each of the different HHGM payment
groups by regressing resource use on a
series of indicator variables for each of
the five categories listed above using a
fixed effects model. The regression
measures resource use with the
proposed Cost per Minute (CPS) + NRS
approach outlined in section III.E.2 of
this proposed rule.
To normalize the results from the
fixed effects regression model, we
divided the predicted resource use for
each 30-day period by the overall
average resource use for all 30-day
No .....................
Yes ...................
No .....................
Yes ...................
No .....................
Yes ...................
No .....................
Yes ...................
No .....................
Yes ...................
Threshold
(10th percentile or 2—
whichever is
higher)
4
4
4
5
2
3
3
3
3
3
periods used to estimate the model to
calculate the case mix weight of all 30day periods within a particular payment
group, where each payment group is
defined as the unique combination of
the subgroups within the five HHGM
categories (admission source, timing of
the episode, clinical grouping,
functional level, and comorbidity
adjustment). The case-mix weight is
then used to adjust the 30-day payment
rate to determine each 30-day period
payment. Table 41 shows the
coefficients of the payment regression
used to generate the weights, and the
coefficients divided by average resource
use. Information can be found in section
III.E.6 of this proposed rule for the
clinical groups, section III.E.7 of this
proposed rule for the functional levels,
section III.E.5 of this proposed rule for
admission source, section III.E.4 of this
proposed rule for episode timing, and
section III.E.8 of this proposed rule for
the comorbidity adjustment.
TABLE 41—COEFFICIENT OF PAYMENT REGRESSION AND COEFFICIENT DIVIDED BY AVERAGE RESOURCE USE FOR HHGM
PAYMENT GROUP
Coefficient
Coefficient
divided by
average
resource use
mstockstill on DSK30JT082PROD with PROPOSALS2
Clinical Group and Functional Level (MMTA—Low is excluded)
MMTA—Medium ......................................................................................................................................................
MMTA—High ...........................................................................................................................................................
Behavioral Health—Low ..........................................................................................................................................
Behavioral Health—Medium ....................................................................................................................................
Behavioral Health—High .........................................................................................................................................
Complex—Low .........................................................................................................................................................
Complex—Medium ..................................................................................................................................................
Complex—High ........................................................................................................................................................
MS Rehab—Low ......................................................................................................................................................
MS Rehab—Medium ...............................................................................................................................................
MS Rehab—High .....................................................................................................................................................
Neuro—Low .............................................................................................................................................................
Neuro—Medium .......................................................................................................................................................
Neuro—High ............................................................................................................................................................
Wound—Low ...........................................................................................................................................................
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28JYP2
$238.93
434.36
¥116.43
177.47
350.98
99.82
472.79
638.62
154.72
353.44
597.31
356.33
636.52
804.50
582.68
0.151
0.274
¥0.073
0.112
0.221
0.063
0.298
0.403
0.098
0.223
0.377
0.225
0.401
0.507
0.368
35328
Federal Register / Vol. 82, No. 144 / Friday, July 28, 2017 / Proposed Rules
TABLE 41—COEFFICIENT OF PAYMENT REGRESSION AND COEFFICIENT DIVIDED BY AVERAGE RESOURCE USE FOR HHGM
PAYMENT GROUP—Continued
Coefficient
Wound—Medium .....................................................................................................................................................
Wound—High ...........................................................................................................................................................
Coefficient
divided by
average
resource use
812.76
1,048.55
0.513
0.661
¥618.74
271.07
83.61
¥0.390
0.171
0.053
Comorbidity Adjustment Group ...............................................................................................................................
244.01
0.154
Constant ...................................................................................................................................................................
N ..............................................................................................................................................................................
Adjusted R2 .............................................................................................................................................................
Average Resource Use ...........................................................................................................................................
1,533.33
8,642,107
0.2704
1,585.48
0.967
........................
........................
........................
Referral Source With Timing (Community Early excluded)
Community Late .......................................................................................................................................................
Institutional Early .....................................................................................................................................................
Institutional Late .......................................................................................................................................................
Comorbidity Adjustment (No Comorbidity Adjustment Group is excluded)
Source: CY 2016 Medicare claims data for episodes ending on or before December 31, 2016 (as of March 17, 2017) for which we had a
linked OASIS assessment. LUPA episodes, outlier episodes, and episodes with PEP adjustments were excluded.
Table 42 presents the case-mix weight
for each HHRG in the regression model
(from Table 46’s coefficients). LUPA
episodes, outlier episodes, and episodes
with PEP adjustments were excluded.
These are the case-mix weights for the
HHGM based on the most current,
complete data available (CY 2016 data
as of March 17, 2017). We would
propose updated case-mix weights using
the latest CY 2017 data in the CY 2019
HH PPS proposed rule. LUPA
information can be found in section
III.E.9 of this proposed rule. Weights are
determined by first calculating the
predicted resource use for episodes with
a particular combination of admission
source, episode timing, clinical
grouping, functional level, and
comorbidity adjustment. This
combination specific calculation is then
divided by the average resource use of
all the episodes that were used to
estimate, which is $1,585.48. The
resulting ratio represents the case-mix
weight for that particular combination
of a HHRG payment group. The adjusted
R-squared value for this model is
0.2704. The adjusted R-squared value
provides a measure of how well
observed outcomes are replicated by the
model, based on the proportion of total
variation of outcomes explained by the
model. In this instance, the fixed effects
regression model used to generate the
case-mix weight under the HHGM
predicts about 27 percent of the
variation in resource use in a given 30day period of home health care.
As noted above, there are 144
different HHRG payment groups under
the HHGM. There are 9 HHRG payment
groups that represent roughly 50.5
percent of the total episodes. There are
33 HHRG payment groups that represent
roughly 1.0 percent of total episodes.
The HHRG payment group with the
smallest weight has a weight of 0.5034
(community, late, behavioral health, low
functional level, with no comorbidity
adjustment). The HHRG payment group
with the largest weight has a weight of
1.9533 (institutional admission, early,
wound, high functional level, with
comorbidity adjustment).
TABLE 42—CASE-MIX WEIGHTS FOR EACH HHRG PAYMENT GROUP, BASED ON 2016 DATA
mstockstill on DSK30JT082PROD with PROPOSALS2
HIPPS
Clinical group and functional level
1AAN ................
1AAY .................
1ABN ................
1ABY .................
1ACN ................
1ACY ................
1BAN ................
1BAY .................
1BBN ................
1BBY .................
1BCN ................
1BCY ................
1CAN ................
1CAY ................
1CBN ................
1CBY ................
1CCN ................
MMTA—Low ................................................
MMTA—Low ................................................
MMTA—Medium ..........................................
MMTA—Medium ..........................................
MMTA—High ...............................................
MMTA—High ...............................................
Neuro—Low .................................................
Neuro—Low .................................................
Neuro—Medium ..........................................
Neuro—Medium ..........................................
Neuro—High ................................................
Neuro—High ................................................
Wound—Low ...............................................
Wound—Low ...............................................
Wound—Medium .........................................
Wound—Medium .........................................
Wound—High ..............................................
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Comorbidity
adjustment
Timing and admission source
Early—Community
Early—Community
Early—Community
Early—Community
Early—Community
Early—Community
Early—Community
Early—Community
Early—Community
Early—Community
Early—Community
Early—Community
Early—Community
Early—Community
Early—Community
Early—Community
Early—Community
Fmt 4701
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No .....................
Yes ...................
No .....................
Yes ...................
No .....................
Yes ...................
No .....................
Yes ...................
No .....................
Yes ...................
No .....................
Yes ...................
No .....................
Yes ...................
No .....................
Yes ...................
No .....................
Weight based
on CY 2016
data
0.9671
1.1210
1.1178
1.2717
1.2411
1.3950
1.1919
1.3458
1.3686
1.5225
1.4745
1.6284
1.3346
1.4885
1.4797
1.6336
1.6284
35329
Federal Register / Vol. 82, No. 144 / Friday, July 28, 2017 / Proposed Rules
TABLE 42—CASE-MIX WEIGHTS FOR EACH HHRG PAYMENT GROUP, BASED ON 2016 DATA—Continued
mstockstill on DSK30JT082PROD with PROPOSALS2
HIPPS
Clinical group and functional level
Timing and admission source
Comorbidity
adjustment
1CCY ................
1DAN ................
1DAY ................
1DBN ................
1DBY ................
1DCN ................
1DCY ................
1EAN ................
1EAY .................
1EBN ................
1EBY .................
1ECN ................
1ECY ................
1FAN .................
1FAY .................
1FBN .................
1FBY .................
1FCN ................
1FCY .................
2AAN ................
2AAY .................
2ABN ................
2ABY .................
2ACN ................
2ACY ................
2BAN ................
2BAY .................
2BBN ................
2BBY .................
2BCN ................
2BCY ................
2CAN ................
2CAY ................
2CBN ................
2CBY ................
2CCN ................
2CCY ................
2DAN ................
2DAY ................
2DBN ................
2DBY ................
2DCN ................
2DCY ................
2EAN ................
2EAY .................
2EBN ................
2EBY .................
2ECN ................
2ECY ................
2FAN .................
2FAY .................
2FBN .................
2FBY .................
2FCN ................
2FCY .................
3AAN ................
3AAY .................
3ABN ................
3ABY .................
3ACN ................
3ACY ................
3BAN ................
3BAY .................
3BBN ................
3BBY .................
3BCN ................
3BCY ................
3CAN ................
3CAY ................
3CBN ................
Wound—High ..............................................
Complex—Low ............................................
Complex—Low ............................................
Complex—Medium ......................................
Complex—Medium ......................................
Complex—High ...........................................
Complex—High ...........................................
MS Rehab—Low .........................................
MS Rehab—Low .........................................
MS Rehab—Medium ...................................
MS Rehab—Medium ...................................
MS Rehab—High ........................................
MS Rehab—High ........................................
Behavioral Health—Low ..............................
Behavioral Health—Low ..............................
Behavioral Health—Medium ........................
Behavioral Health—Medium ........................
Behavioral Health—High .............................
Behavioral Health—High .............................
MMTA—Low ................................................
MMTA—Low ................................................
MMTA—Medium ..........................................
MMTA—Medium ..........................................
MMTA—High ...............................................
MMTA—High ...............................................
Neuro—Low .................................................
Neuro—Low .................................................
Neuro—Medium ..........................................
Neuro—Medium ..........................................
Neuro—High ................................................
Neuro—High ................................................
Wound—Low ...............................................
Wound—Low ...............................................
Wound—Medium .........................................
Wound—Medium .........................................
Wound—High ..............................................
Wound—High ..............................................
Complex—Low ............................................
Complex—Low ............................................
Complex—Medium ......................................
Complex—Medium ......................................
Complex—High ...........................................
Complex—High ...........................................
MS Rehab—Low .........................................
MS Rehab—Low .........................................
MS Rehab—Medium ...................................
MS Rehab—Medium ...................................
MS Rehab—High ........................................
MS Rehab—High ........................................
Behavioral Health—Low ..............................
Behavioral Health—Low ..............................
Behavioral Health—Medium ........................
Behavioral Health—Medium ........................
Behavioral Health—High .............................
Behavioral Health—High .............................
MMTA—Low ................................................
MMTA—Low ................................................
MMTA—Medium ..........................................
MMTA—Medium ..........................................
MMTA—High ...............................................
MMTA—High ...............................................
Neuro—Low .................................................
Neuro—Low .................................................
Neuro—Medium ..........................................
Neuro—Medium ..........................................
Neuro—High ................................................
Neuro—High ................................................
Wound—Low ...............................................
Wound—Low ...............................................
Wound—Medium .........................................
Early—Community .......................................
Early—Community .......................................
Early—Community .......................................
Early—Community .......................................
Early—Community .......................................
Early—Community .......................................
Early—Community .......................................
Early—Community .......................................
Early—Community .......................................
Early—Community .......................................
Early—Community .......................................
Early—Community .......................................
Early—Community .......................................
Early—Community .......................................
Early—Community .......................................
Early—Community .......................................
Early—Community .......................................
Early—Community .......................................
Early—Community .......................................
Early—Institutional .......................................
Early—Institutional .......................................
Early—Institutional .......................................
Early—Institutional .......................................
Early—Institutional .......................................
Early—Institutional .......................................
Early—Institutional .......................................
Early—Institutional .......................................
Early—Institutional .......................................
Early—Institutional .......................................
Early—Institutional .......................................
Early—Institutional .......................................
Early—Institutional .......................................
Early—Institutional .......................................
Early—Institutional .......................................
Early—Institutional .......................................
Early—Institutional .......................................
Early—Institutional .......................................
Early—Institutional .......................................
Early—Institutional .......................................
Early—Institutional .......................................
Early—Institutional .......................................
Early—Institutional .......................................
Early—Institutional .......................................
Early—Institutional .......................................
Early—Institutional .......................................
Early—Institutional .......................................
Early—Institutional .......................................
Early—Institutional .......................................
Early—Institutional .......................................
Early—Institutional .......................................
Early—Institutional .......................................
Early—Institutional .......................................
Early—Institutional .......................................
Early—Institutional .......................................
Early—Institutional .......................................
Late—Community ........................................
Late—Community ........................................
Late—Community ........................................
Late—Community ........................................
Late—Community ........................................
Late—Community ........................................
Late—Community ........................................
Late—Community ........................................
Late—Community ........................................
Late—Community ........................................
Late—Community ........................................
Late—Community ........................................
Late—Community ........................................
Late—Community ........................................
Late—Community ........................................
Yes ...................
No .....................
Yes ...................
No .....................
Yes ...................
No .....................
Yes ...................
No .....................
Yes ...................
No .....................
Yes ...................
No .....................
Yes ...................
No .....................
Yes ...................
No .....................
Yes ...................
No .....................
Yes ...................
No .....................
Yes ...................
No .....................
Yes ...................
No .....................
Yes ...................
No .....................
Yes ...................
No .....................
Yes ...................
No .....................
Yes ...................
No .....................
Yes ...................
No .....................
Yes ...................
No .....................
Yes ...................
No .....................
Yes ...................
No .....................
Yes ...................
No .....................
Yes ...................
No .....................
Yes ...................
No .....................
Yes ...................
No .....................
Yes ...................
No .....................
Yes ...................
No .....................
Yes ...................
No .....................
Yes ...................
No .....................
Yes ...................
No .....................
Yes ...................
No .....................
Yes ...................
No .....................
Yes ...................
No .....................
Yes ...................
No .....................
Yes ...................
No .....................
Yes ...................
No .....................
VerDate Sep<11>2014
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Fmt 4701
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E:\FR\FM\28JYP2.SGM
28JYP2
Weight based
on CY 2016
data
1.7823
1.0301
1.1840
1.2653
1.4192
1.3699
1.5238
1.0647
1.2186
1.1900
1.3439
1.3438
1.4977
0.8937
1.0476
1.0790
1.2329
1.1885
1.3424
1.1381
1.2920
1.2888
1.4427
1.4120
1.5659
1.3628
1.5167
1.5395
1.6934
1.6455
1.7994
1.5056
1.6595
1.6507
1.8046
1.7994
1.9533
1.2010
1.3549
1.4363
1.5902
1.5409
1.6948
1.2357
1.3896
1.3610
1.5149
1.5148
1.6687
1.0646
1.2185
1.2500
1.4039
1.3594
1.5133
0.5769
0.7308
0.7276
0.8815
0.8508
1.0047
0.8016
0.9555
0.9783
1.1322
1.0843
1.2382
0.9444
1.0983
1.0895
35330
Federal Register / Vol. 82, No. 144 / Friday, July 28, 2017 / Proposed Rules
TABLE 42—CASE-MIX WEIGHTS FOR EACH HHRG PAYMENT GROUP, BASED ON 2016 DATA—Continued
HIPPS
Clinical group and functional level
3CBY ................
3CCN ................
3CCY ................
3DAN ................
3DAY ................
3DBN ................
3DBY ................
3DCN ................
3DCY ................
3EAN ................
3EAY .................
3EBN ................
3EBY .................
3ECN ................
3ECY ................
3FAN .................
3FAY .................
3FBN .................
3FBY .................
3FCN ................
3FCY .................
4AAN ................
4AAY .................
4ABN ................
4ABY .................
4ACN ................
4ACY ................
4BAN ................
4BAY .................
4BBN ................
4BBY .................
4BCN ................
4BCY ................
4CAN ................
4CAY ................
4CBN ................
4CBY ................
4CCN ................
4CCY ................
4DAN ................
4DAY ................
4DBN ................
4DBY ................
4DCN ................
4DCY ................
4EAN ................
4EAY .................
4EBN ................
4EBY .................
4ECN ................
4ECY ................
4FAN .................
4FAY .................
4FBN .................
4FBY .................
4FCN ................
4FCY .................
Wound—Medium .........................................
Wound—High ..............................................
Wound—High ..............................................
Complex—Low ............................................
Complex—Low ............................................
Complex—Medium ......................................
Complex—Medium ......................................
Complex—High ...........................................
Complex—High ...........................................
MS Rehab—Low .........................................
MS Rehab—Low .........................................
MS Rehab—Medium ...................................
MS Rehab—Medium ...................................
MS Rehab—High ........................................
MS Rehab—High ........................................
Behavioral Health—Low ..............................
Behavioral Health—Low ..............................
Behavioral Health—Medium ........................
Behavioral Health—Medium ........................
Behavioral Health—High .............................
Behavioral Health—High .............................
MMTA—Low ................................................
MMTA—Low ................................................
MMTA—Medium ..........................................
MMTA—Medium ..........................................
MMTA—High ...............................................
MMTA—High ...............................................
Neuro—Low .................................................
Neuro—Low .................................................
Neuro—Medium ..........................................
Neuro—Medium ..........................................
Neuro—High ................................................
Neuro—High ................................................
Wound—Low ...............................................
Wound—Low ...............................................
Wound—Medium .........................................
Wound—Medium .........................................
Wound—High ..............................................
Wound—High ..............................................
Complex—Low ............................................
Complex—Low ............................................
Complex—Medium ......................................
Complex—Medium ......................................
Complex—High ...........................................
Complex—High ...........................................
MS Rehab—Low .........................................
MS Rehab—Low .........................................
MS Rehab—Medium ...................................
MS Rehab—Medium ...................................
MS Rehab—High ........................................
MS Rehab—High ........................................
Behavioral Health—Low ..............................
Behavioral Health—Low ..............................
Behavioral Health—Medium ........................
Behavioral Health—Medium ........................
Behavioral Health—High .............................
Behavioral Health—High .............................
Comorbidity
adjustment
Timing and admission source
Late—Community
Late—Community
Late—Community
Late—Community
Late—Community
Late—Community
Late—Community
Late—Community
Late—Community
Late—Community
Late—Community
Late—Community
Late—Community
Late—Community
Late—Community
Late—Community
Late—Community
Late—Community
Late—Community
Late—Community
Late—Community
Late—Institutional
Late—Institutional
Late—Institutional
Late—Institutional
Late—Institutional
Late—Institutional
Late—Institutional
Late—Institutional
Late—Institutional
Late—Institutional
Late—Institutional
Late—Institutional
Late—Institutional
Late—Institutional
Late—Institutional
Late—Institutional
Late—Institutional
Late—Institutional
Late—Institutional
Late—Institutional
Late—Institutional
Late—Institutional
Late—Institutional
Late—Institutional
Late—Institutional
Late—Institutional
Late—Institutional
Late—Institutional
Late—Institutional
Late—Institutional
Late—Institutional
Late—Institutional
Late—Institutional
Late—Institutional
Late—Institutional
Late—Institutional
........................................
........................................
........................................
........................................
........................................
........................................
........................................
........................................
........................................
........................................
........................................
........................................
........................................
........................................
........................................
........................................
........................................
........................................
........................................
........................................
........................................
........................................
........................................
........................................
........................................
........................................
........................................
........................................
........................................
........................................
........................................
........................................
........................................
........................................
........................................
........................................
........................................
........................................
........................................
........................................
........................................
........................................
........................................
........................................
........................................
........................................
........................................
........................................
........................................
........................................
........................................
........................................
........................................
........................................
........................................
........................................
........................................
Yes ...................
No .....................
Yes ...................
No .....................
Yes ...................
No .....................
Yes ...................
No .....................
Yes ...................
No .....................
Yes ...................
No .....................
Yes ...................
No .....................
Yes ...................
No .....................
Yes ...................
No .....................
Yes ...................
No .....................
Yes ...................
No .....................
Yes ...................
No .....................
Yes ...................
No .....................
Yes ...................
No .....................
Yes ...................
No .....................
Yes ...................
No .....................
Yes ...................
No .....................
Yes ...................
No .....................
Yes ...................
No .....................
Yes ...................
No .....................
Yes ...................
No .....................
Yes ...................
No .....................
Yes ...................
No .....................
Yes ...................
No .....................
Yes ...................
No .....................
Yes ...................
No .....................
Yes ...................
No .....................
Yes ...................
No .....................
Yes ...................
Weight based
on CY 2016
data
1.2434
1.2382
1.3921
0.6398
0.7937
0.8751
1.0290
0.9796
1.1335
0.6744
0.8283
0.7998
0.9537
0.9536
1.1075
0.5034
0.6573
0.6888
0.8427
0.7982
0.9521
1.0198
1.1737
1.1705
1.3244
1.2938
1.4477
1.2446
1.3985
1.4213
1.5752
1.5273
1.6812
1.3874
1.5413
1.5325
1.6864
1.6812
1.8351
1.0828
1.2367
1.3180
1.4719
1.4226
1.5765
1.1174
1.2713
1.2428
1.3967
1.3966
1.5505
0.9464
1.1003
1.1318
1.2857
1.2412
1.3951
mstockstill on DSK30JT082PROD with PROPOSALS2
Source: CY 2016 Medicare claims data for episodes ending on or before December 31, 2016 for which we had a linked OASIS assessment.
LUPA episodes, outlier episodes, and episodes with PEP adjustments were excluded.
We invite comments on the proposed
case-mix weight methodology under the
HHGM.
11. Low-Utilization Payment
Adjustment (LUPA) Add-On Payments
and Partial Payment Adjustments Under
the HHGM
LUPA episodes that occur as the only
episode or as an initial episode in a
sequence of adjacent episodes are
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adjusted by applying an additional
amount to the LUPA payment before
adjusting for area wage differences.
Under the HHGM, we propose the
LUPA add-on factors will remain the
same as the current payment system,
described in section III.C.3. of this
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Federal Register / Vol. 82, No. 144 / Friday, July 28, 2017 / Proposed Rules
mstockstill on DSK30JT082PROD with PROPOSALS2
proposed rule. We propose to 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 (1.8451 for SN, 1.6700 for PT, and
1.6266 for SLP) 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 in CY
2019, if the first skilled visit is SN, the
payment for that visit would be the CY
2019 per-visit rate for SN, multiplied by
1.8451, subject to area wage adjustment.
The current partial episode payment
(PEP) adjustment is a proportion of the
episode payment and is based on the
span of days including the start-of-care
date or first billable service date through
and including the last billable service
date under the original plan of care
before the intervening event in a home
health beneficiary’s care defined as:
• A beneficiary elected transfer, or
• A discharge and return to home
health that would warrant, for purposes
of payment, a new OASIS assessment,
physician certification of eligibility, and
a new plan of care.
For 30-day periods of care, we
propose the process for partial payment
adjustments would remain the same as
the existing policies pertaining to partial
episode payments. When a new 30-day
period begins due to the intervening
event of the beneficiary elected transfer
or there was a discharge and return to
home health during the 30-day period,
we propose the original 30-day period
would be proportionally adjusted to
reflect the length of time the beneficiary
remained under the agency’s care prior
to the intervening event. The
proportional payment is the partial
payment adjustment. The partial
payment adjustment is calculated by
using the span of days (first billable
service date through and including the
last billable service date) under the
original plan of care as a proportion of
30. The proportion is multiplied by the
original case-mix and wage index to
produce the 30-day payment.
12. Payments for High-Cost Outliers
Under the HHGM
As described in section III.D. of this
proposed rule, section 1895(b)(5) of the
Act allows for the provision of an
addition or adjustment to the home
health payment amount in the case of
outliers because of unusual variations in
the type or amount of medically
necessary care. The history of and
current methodology for payment of
high-cost outliers under the HH PPS is
described in detail in section III.D. of
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this proposed rule. We are proposing to
maintain the current methodology for
payment of high-cost outliers upon
implementation of the HHGM in CY
2019 and we would calculate payment
for high-cost outliers on 30-day periods
of care.
Simulating payments using
preliminary CY 2016 claims data and
the CY 2018 payment rates, we estimate
that outlier payments under the
proposed HHGM with 30-day periods of
care would comprise approximately
4.50 percent of total HH PPS payments
in CY 2018. Given the statutory
requirement to target up to, but no more
than, 2.5 percent of total payments as
outlier payments, we currently estimate
that the FDL ratio under the HHGM
would need to change from 0.55 to 0.93.
However, given the proposed
implementation of the HHGM for 30-day
periods of care beginning on or after
January 1, 2019, we will update our
estimate of outlier payments as a
percent of total HH PPS payments using
the most current and complete
utilization data available at the time of
CY 2019 rate-setting. We would propose
a change in the FDL ratio for CY 2019,
if needed.
We invite public comments on
maintaining the current outlier payment
methodology outlined in section III.D. of
this proposed rule for the proposed
HHGM and the associated changes in
the regulations text as described in
section III.E.13 of this proposed rule.
13. Conforming Regulations Text
Revisions for the Implementation of the
HHGM in CY 2019
We are proposing to make a number
of revisions to the regulations to
implement the HHGM for periods
beginning on or after January 1, 2019, as
outlined in sections III.E.1. through
III.E.12. of this proposed rule. We
propose to make conforming changes in
§ 409.43 and part 484 subpart E to revise
the unit of service from a 60-day
episode to a 30-day period. In addition,
we are proposing to restructure
§ 484.205. These revisions would be
effective on January 1, 2019. We are not
proposing any revisions to the
regulations for CY 2018. These revisions
and others are discussed below.
Specifically, we propose to:
• Revise § 409.43, which outlines
plan of care requirements. We propose
to revise several paragraphs to phase out
the unit of service from a 60-day
episode for episodes beginning on or
before December 31, 2018, and to
implement a 30-day period as the new
unit of service for periods beginning on
or after January 1, 2019 under the
HHGM.
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35331
• Revise the definitions of rural area
and urban area in § 484.202 to remove
‘‘with respect to home health episodes
ending on or after January 1, 2006’’ from
each definition, as this verbiage is no
longer necessary.
• Restructure § 484.205 to provide
more logical organization. Specifically,
we propose to add paragraphs to
paragraph (b) to define the unit of
payment. We propose to move language
which addresses the requirement for
OASIS submission from § 484.210 and
insert it into § 484.205 as new paragraph
(c). We also propose to add paragraph (f)
to discuss split percentage payments
under the current model and the
proposed HHGM. In addition, we
propose to revise § 484.205 to remove
references to ‘‘60-day episode’’ and to
refer more generally to the ‘‘national,
standardized prospective payment’’.
While we are proposing to revise
§ 484.205 to account for the change in
the unit of payment under the HH PPS
for CY 2019, we are not proposing to
change the requirements or policies
relating to durable medical equipment
or furnishing negative pressure wound
therapy using a disposable device.
• Remove § 484.210 which discusses
data used for the calculation of the
national prospective 60-day episode
payment as we believe that this
information is incorporated in other
sections of part 484 subpart E, such as
§ 484.205(c), § 484.215(a) and (b),
§ 484.220 and § 484.215.
• Revise the section heading of
§ 484.215 from ‘‘Initial establishment of
the calculation of the national 60-day
episode payment’’ to ‘‘Initial
establishment of the calculation of the
national, standardized prospective 60day episode payment and 30-day
payment rates.’’ Also, we propose to add
paragraph (f) to this section to describe
how the national, standardized
prospective 60-day episode payment
rate is converted into a national,
standardized prospective 30-day period
payment and when it applies.
• Revise the section heading of
§ 484.220 from ‘‘Calculation of the
adjusted national prospective 60-day
episode payment rate for case-mix and
area wage levels’’ to ‘‘Calculation of the
case-mix and wage area adjusted
prospective payment rates.’’ We propose
to remove the reference to ‘‘national 60day episode payment rate’’ and replace
it with ‘‘national, standardized
prospective payment’’.
• Revise the section heading in
§ 484.225 from ‘‘Annual update of the
unadjusted national prospective 60-day
episode payment rate’’ to ‘‘Annual
update of the unadjusted national,
standardized prospective 60-day
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28JYP2
mstockstill on DSK30JT082PROD with PROPOSALS2
35332
Federal Register / Vol. 82, No. 144 / Friday, July 28, 2017 / Proposed Rules
episode and 30-day payment rates’’.
Also, we propose to revise § 484.225 to
remove references to ‘‘60-day episode’’
and to refer more generally to the
‘‘national, standardized prospective
payment’’. In addition, we propose to
add paragraph (d) to describe the annual
update for CY 2019.
• Revise the section heading of
§ 484.230 from ‘‘Methodology used for
the calculation of low-utilization
payment adjustment’’ to ‘‘Low
utilization payment adjustment’’. Also,
we propose to designate the current text
to paragraph (a) and insert language
such that proposed paragraph (a)
applies to episodes beginning on or
before December 31, 2018, using the
current payment system. We propose to
add paragraph (b) to describe how low
utilization payment adjustments are
determined for periods beginning on or
after January 1, 2019, using the
proposed HHGM.
• Revise the section heading of
§ 484.235 from ‘‘Methodology used for
the calculation of partial episode
payment adjustments’’ to ‘‘Partial
payment adjustments’’. We propose to
remove paragraphs (a), (b), and (c). We
propose to remove paragraphs (1), (2),
and (3) which describe partial payment
adjustments from paragraph (d) in
§ 484.205 and incorporate them into
§ 484.235. We propose to add paragraph
(a) to describe partial payment
adjustments under the current system,
that is, for episodes beginning on or
before December 31, 2018, and
paragraph (b) to describe partial
payment adjustments under the
proposed HHGM, that is, for periods
beginning on or after January 1, 2019.
• Revise the section heading for
§ 484.240 from ‘‘Methodology used for
the calculation of the outlier payment’’
to ‘‘Outlier payments.’’ In addition, we
propose to remove language at
paragraph (b) and append it to
paragraph (a). We propose to add
language to proposed revised paragraph
(a) such that paragraph (a) will apply to
payments under the current system, that
is, for episodes beginning on or before
December 31, 2018. We propose to
revise paragraph (b) to describe
payments under the proposed HHGM,
that is, for periods beginning on or after
January 1, 2019. In paragraph (c), we
propose to replace the ‘‘estimated’’ cost
with ‘‘imputed’’ cost. Lastly, we propose
to revise paragraph (d) to reflect the per15 minute unit approach to imputing
the cost for each claim.
We are soliciting comments on the
proposed HHGM as outlined in sections
III.E.1. through III.E.12. and the
associated regulations text changes
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Jkt 241001
described above and in the regulations
text of this proposed rule.
IV. Proposed Provisions of the Home
Health Value-Based Purchasing
(HHVBP) Model
A. Background
As authorized by section 1115A of the
Act and finalized in the CY 2016 HH
PPS final rule (80 FR 68624), we began
testing the HHVBP Model on January 1,
2016. The HHVBP Model has an overall
purpose of improving the quality and
delivery of home health care services to
Medicare beneficiaries. The specific
goals of the Model are to: (1) Provide
incentives for better quality care with
greater efficiency; (2) study new
potential quality and efficiency
measures for appropriateness in the
home health setting; and (3) enhance the
current public reporting process.
Using the randomized selection
methodology finalized in the CY 2016
HH PPS final rule, nine states were
selected for inclusion in the HHVBP
Model, representing each geographic
area across the nation. All Medicarecertified HHAs providing services in
Arizona, Florida, Iowa, Maryland,
Massachusetts, Nebraska, North
Carolina, Tennessee, and Washington
(competing HHAs) are required to
compete in the Model. Requiring all
Medicare-certified HHAs providing
services in the selected states to
participate in the Model ensures that:
(1) there is no selection bias; (2)
participating HHAs are representative of
HHAs nationally; and, (3) there is
sufficient participation to generate
meaningful results.
As finalized in the CY 2016 HH PPS
final rule, the HHVBP Model will utilize
the waiver authority under section
1115A(d)(1) of the Act to adjust
Medicare payment rates under section
1895(b) of the Act beginning in CY 2018
based on performance on applicable
measures. Payment adjustments will be
increased incrementally over the course
of the HHVBP Model in the following
manner: (1) A maximum payment
adjustment of 3 percent (upward or
downward) in CY 2018; (2) a maximum
payment adjustment of 5 percent
(upward or downward) in CY 2019; (3)
a maximum payment adjustment of 6
percent (upward or downward) in CY
2020; (4) a maximum payment
adjustment of 7 percent (upward or
downward) in CY 2021; and (5) a
maximum payment adjustment of 8
percent (upward or downward) in CY
2022. Payment adjustments will be
based on each HHA’s Total Performance
Score (TPS) in a given performance year
(PY) on (1) a set of measures already
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reported via OASIS and HHCAHPS for
all patients serviced by the HHA and
select claims data elements, and (2)
three New Measures where points are
achieved for reporting data.
As finalized in the CY 2017 HH PPS
final rule (81 FR 76741 through 76752),
in addition to providing an update on
the progress towards developing public
reporting of performance under the
HHVBP Model, we finalized the
following changes related to the HHVBP
Model:
• Calculating benchmarks and
achievement thresholds at the state level
rather than the level of the size-cohort
and revising the definition for
benchmark to state that benchmark
refers to the mean of the top decile of
Medicare-certified HHA performance on
the specified quality measure during the
baseline period, calculated for each
state;
• Requiring a minimum of eight
HHAs in a size-cohort;
• Increasing the timeframe for
submitting New Measure data from
seven calendar days to 15 calendar days
following the end of each reporting
period to account for weekends and
holidays;
• Removing four measures (Care
Management: Types and Sources of
Assistance, Prior Functioning Activities
of Daily Living (ADL)/Instrumental ADL
(IADL), Influenza Vaccine Data
Collection Period, and Reason
Pneumococcal Vaccine Not Received)
from the set of applicable measures;
• Adjusting the reporting period and
submission date for the Influenza
Vaccination Coverage for Home Health
Personnel measure from a quarterly
submission to an annual submission;
and
• Allowing for an appeals process
that includes the recalculation process
finalized in the CY 2016 HH PPS final
rule (80 FR 68688 through 68689), as
modified, and adds a reconsideration
process.
B. Quality Measures
1. Proposed Adjustment to the
Minimum Number of Completed Home
Health Care Consumer Assessment of
Healthcare Providers and System
(HHCAHPS) Surveys
The 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.
The survey is designed to measure the
experiences of people receiving home
health care from Medicare-certified
home health care agencies and meet the
following three broad goals to: (1)
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Produce comparable data on the
patient’s perspective that allows
objective and meaningful comparisons
between home health agencies on
domains that are important to
consumers; (2) create incentives through
public reporting of survey results for
agencies to improve their quality of
care; and (3) enhance public
accountability in health care by
increasing the transparency of the
quality of care provided in return for
public investment through public
reporting.
As finalized in the CY 2016 HH PPS
final rule (80 FR 68685 through 68686),
if a HHA does not have a minimum of
20 episodes of care during a
performance year to generate a
performance score on at least five
measures, that HHA would not be
included in the Linear Exchange
Function (LEF) and would not have a
payment adjustment percentage
calculated. The LEF is used to translate
an HHA’s Total Performance Score
(TPS) into a percentage of the valuebased payment adjustment earned by
each HHA under the HHVBP Model. For
the HHCAHPS measures, a minimum of
20 HHCAHPS completed surveys would
be necessary in order for scores to be
generated for the HHCAHPS quality
measures that can be included in the
calculation of the TPS.
We believe, however, that using a
minimum of 40 completed HHCAHPS
surveys, rather than a minimum of 20
completed HHCAHPS surveys, would
better align the Model with HHCAHPS
policy for the Patient Survey Star
Ratings on Home Health Compare.100
The decision to use a minimum of 40
completed surveys for these star ratings
was a result of balancing two competing
goals. One goal was to provide star
ratings that were meaningful and
minimized random variations. This goal
was best served by calculating star
ratings for large numbers of cases by
having a larger minimum of completed
HHCAHPS surveys (for example, 50 or
100 completed HHCAHPS surveys). At
the same time, we also wanted to be
able to provide star ratings for as many
HHAs as possible. This goal was best
served by using a lower minimum of
completed HHCAHPS surveys (for
example, 20 completed HHCAHPS
surveys). We chose to balance these
opposing and necessary goals by using
40 completed HHCAHPS surveys for the
Patient Survey Star Ratings. Because we
believe that aligning the Patient Survey
Star Ratings system and the HHVBP
100 Patient Survey Star Ratings https://
www.medicare.gov/HomeHealthCompare/Data/
Patient-Survey-Star-Ratings.html.
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model provides uniformity, consistency,
and standard transformability for
different healthcare platforms, we
therefore propose using a minimum of
40 instead of 20 completed HHCAHPS
surveys under the HHVBP.
We note that we received a comment
in response to the CY 2016 HH PPS
proposed rule in support of using a
higher minimum threshold for
HHCAHPS completed surveys for the
Patient Survey Star Ratings if the data
are going to be used in HHVBP or any
other quality assessment program (80 FR
68709). We also note that we received
public comment in response to the CY
2017 HH PPS proposed rule in support
of using a higher minimum threshold
for HHCAHPS completed surveys in the
HHVBP Model, including a
recommendation to use a minimum of
100 HHCAHPS rather than a sample size
of 20 surveys (81 FR 76747). We believe
that proposing a minimum of 40
completed HHCAHPS surveys for the
Model would be more appropriate than
the higher minimums previously
recommended by some commenters
because it represents a balance between
providing meaningful data and having
sufficient numbers of HHAs with
performance scores for at least 5
measures in the cohorts. Moreover, as
we noted, it aligns with the Patient
Survey Star Ratings on Home Health
Compare.
To understand the possible impact of
our proposal to use a minimum of 40
HHCAHPS completed surveys, we note
that HHAs may refer to the Interim
Performance Reports (IPRs) issued in
October 2016, January 2017 and April
2017, which analyzed 40 or more
completed HHCAHPS surveys across
both small and large cohorts in
determining each HHA’s HHCAHPS
quality measure scores. As a point of
comparison to the minimum of 40
HHCAHPS completed surveys, we note
that these IPRs will be reissued using 20
or more completed HHCAHPS surveys
and include quality measure scores, for
these same time periods, calculated
with HHAs that qualify for the LEF by
having sufficient data for at least five
measures. HHAs will have the
opportunity to submit a request for
recalculation of the revised interim
performance scores.
HHAs have an opportunity to evaluate
these IPRs in light of our proposal to
change to a minimum of 40 HHCAHPS
completed surveys, as well as seek
clarification on the difference in their
reports. The participating HHAs will
receive concurrent IPRs in July 2017
and concurrent Annual Total
Performance Score and Payment
Adjustment Reports, which we plan to
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35333
make available in the last week of
August 2017. The concurrent reports
will show one report with HHCAHPS
quality measure scores calculated based
on a minimum of 40 completed surveys
and one report with HHCAHPS quality
measure scores calculated based on a
minimum of 20 completed surveys.
Because this proposed rule will not be
finalized before the timeline for
submission of recalculation and
reconsideration requests, HHAs will
have the opportunity to submit
recalculation requests for the interim
performance scores based on both a
minimum of 40 and 20 completed
surveys, and recalculation and
reconsideration requests, as applicable,
for the annual total performance scores
included in these reports for these
thresholds in accordance with the
appeals process set forth at § 484.335,
which was finalized in the CY 2017 HH
PPS final rule.
We analyzed the effects on
participating HHAs of using the
proposed 40 or more completed
HHCAHPS surveys as compared to
using 20 or more completed HHCAHPS
surveys by examining OASIS measures
submitted from January 1, 2015 through
December 31, 2016, claims measures
submitted from September 1, 2015
through September 30, 2016, and 12
months ending June 30, 2016 for
HHCAHPS-based measures. We also
found that achievement thresholds,
which are calculated as the median of
all HHAs’ performance on the specified
quality measures during the 2015
baseline year for each state, would not
change by more than ±1.1 percent, with
the largest changes occurring in the
statewide achievement thresholds for
the HHCAHPS Willingness to
Recommend the Agency measure in
Arizona (+1.1 percent) and Nebraska
(¥1.1 percent). Benchmarks (the mean
of the top decile of Medicare-certified
HHA performance on the specified
quality measures during the 2015
baseline year, calculated for each state)
had greater potential for change, ranging
down to ¥3.2 percent. For instance, we
found that when calculated using a
minimum of 40 surveys rather than a
minimum of 20 surveys, there was a
¥2.0 percent reduction in the
benchmark for the HHCAHPS
Willingness to Recommend the Agency
measure for Arizona and a ¥1.7 percent
reduction in the benchmark for
Nebraska. We also found that when
calculated using a minimum of 40
surveys rather than a minimum of 20
surveys, there was a ¥1.7 percent
reduction in the benchmark for the
HHCAHPS Communications between
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Providers and Patients measure for
Arizona, a ¥1.7 percent reduction in
the benchmark for Florida, and a ¥3.2
percent reduction in the benchmark for
Nebraska.
Overall, the proposed change in the
HHCAHPS minimum of 40 completed
surveys is estimated to result in a
limited percent change in the average
statewide TPS for larger-volume HHAs,
ranging from ¥0.4 through +2.2
percent. Because the underlying data
does not cover the full 2016 calendar
year, the data limitation may impact the
final total performance scores and
corresponding payment adjustment
percentages. We provide estimates of
the expected payment adjustment
distribution based on the proposed
minimum of 40 completed HHCAHPS
surveys in the impact analysis of this
proposed rule.
We are inviting public comments on
our proposal to use 40 or more
completed HHCAHPS surveys as the
minimum to generate a quality measure
score on the HHCAHPS measures, as is
currently used in Home Health Compare
and the Patient Survey Star Ratings.
Therefore, we propose to revise the
definition of ‘‘applicable measure’’ at
§ 484.305 to reflect this proposal, from
a measure for which the competing
HHA has provided 20 home health
episodes of care per year to a measure
for which a competing HHA has
provided a minimum of 20 home health
episodes of care per year for the OASISbased measures, 20 home health
episodes of care per year for the claimsbased measures, or 40 completed
surveys for the HHCAHPS measures.
This proposal, if finalized, would apply
to the calculation of the benchmark and
achievement thresholds and the
calculation of performance scores for all
Model years, beginning with
Performance Year (PY) One.
2. Proposal To Remove One OASISBased Measure Beginning With
Performance Year 3
In the CY 2016 HH PPS final rule, we
finalized a set of quality measures in
Figure 4a: Final PY1 Measures and
Figure 4b: Final PY1 New Measures (80
FR 68671 through 68673) for the
HHVBP Model to be used in the first
performance year (PY1), referred to as
the starter set.
The measures were selected for the
Model using the following guiding
principles: (1) Use a broad measure set
that captures the complexity of the
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services HHAs provide; (2) Incorporate
the flexibility for future inclusion of the
Improving Medicare Post-Acute Care
Transformation Act of 2014 (IMPACT)
measures that cut across post-acute care
settings; (3) Develop ‘second generation’
(of the HHVBP Model) measures of
patient outcomes, health and functional
status, shared decision making, and
patient activation; (4) Include a balance
of process, outcome and patient
experience measures; (5) Advance the
ability to measure cost and value; (6)
Add measures for appropriateness or
overuse; and (7) Promote infrastructure
investments. This set of quality
measures encompasses the multiple
National Quality Strategy (NQS)
domains 101 (80 FR 68668). The NQS
domains include six priority areas
identified in the CY 2016 HH PPS final
rule (80 FR 68668) as the CMS
Framework for Quality Measurement
Mapping. These areas are: (1) Clinical
quality of care; (2) Care coordination; (3)
Population & community health; (4)
Person- and Caregiver-centered
experience and outcomes; (5) Safety;
and (6) Efficiency and cost reduction.
Figures 4a and 4b of the CY 2016 HH
PPS final rule identified 15 outcome
measures (five from the HHCAHPS,
eight from Outcome and Assessment
Information Set (OASIS), and two from
the Chronic Care Warehouse (claims)),
and nine process measures (six from
OASIS, and three New Measures, which
were not previously reported in the
home health setting).
In the CY 2017 HH PPS final rule, we
removed the following four measures
from the measure set for PY 1 and
subsequent performance years: (1) Care
Management: Types and Sources of
Assistance; (2) Prior Functioning ADL/
IADL; (3) Influenza Vaccine Data
Collection Period: Does this episode of
care include any dates on or between
October 1 and March 31?; and (4)
Reason Pneumococcal Vaccine Not
Received, for the reasons discussed in
that final rule (81 FR 76743 through
76747).
For Performance Year 3 (PY 3), we are
proposing to remove one OASIS-based
measure, Drug Education on All
Medications Provided to Patient/
Caregiver during All Episodes of Care,
from the set of applicable measures. As
part of our ongoing monitoring efforts,
101 2015 Annual Report to Congress, https://
www.ahrq.gov/workingforquality/reports/annualreports/nqs2015annlrpt.htm.
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we found that based on the standard
metrics of measure performance, many
providers have achieved full
performance on the Drug Education
measure. For example, for the January
2017 IPRs (which covered the 12-month
period of October 1, 2015 through
September 30, 2016), the average value
for this measure across all participating
HHAs was 95.69 percent from October
2015 through September 2016. When
looking at just September 2016, the
mean value on this measure across all
participating HHAs had increased to
97.8 percent. Also, there are few HHAs
with poor performance on the measure.
Based on the January 2017 IPRs, across
all participating HHAs, the 10th
percentile was 89 percent and the 5th
percentile was 81.8 percent, but only 1.8
percent of HHAs had a value below 70
percent on the measure. We believe that
removing this measure would be
consistent with our policy, as noted in
the CY 2017 HH PPS final rule (81 FR
76746), that when a measure has
achieved full performance, we may
propose the removal of the measure in
future rulemaking. In addition, our
contractor’s Technical Expert Panel
(TEP), which consists of 11 panelists
with expertise in home health care and
quality measures, expressed concern
that the Drug Education measure does
not capture whether the education
provided by the HHA was meaningful.
The revised set of applicable
measures, if our proposal to remove the
OASIS-based measure, Drug Education
on All Medications Provided to Patient/
Caregiver during All Episodes of Care, is
finalized, is presented in Table 43. This
measure set would be applicable to PY3
and each subsequent performance year
until such time that another set of
applicable measures, or changes to this
measure set, are proposed and finalized
in future rulemaking.
102 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/HHQIQuality
Measures.html. For information on HHCAHPS
measures see https://homehealthcahps.org/
SurveyandProtocols/SurveyMaterials.aspx.
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TABLE 43—MEASURE SET FOR THE HHVBP MODEL 102 BEGINNING PY 3
Measure title
Measure type
Identifier
Data
source
Numerator
Denominator
Clinical Quality of
Care.
Improvement in
Ambulation-Locomotion.
Outcome .......
NQF0167 .......
OASIS
(M1860).
Improvement in
Bed Transferring.
Outcome .......
NQF0175 .......
OASIS
(M1850).
Clinical Quality of
Care.
Improvement in
Bathing.
Outcome .......
NQF0174 .......
OASIS
(M1830).
Clinical Quality of
Care.
Improvement in
Dyspnea.
Outcome .......
NA .................
OASIS
(M1400).
Communication &
Care Coordination.
Discharged to
Community.
Outcome .......
NA .................
OASIS
(M2420).
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
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 a discharge during the reporting period, other than
those covered by generic or
measure-specific exclusions.
Clinical Quality of
Care.
Efficiency & Cost
Reduction.
Acute Care Hospitalization: Unplanned Hospitalization during first 60 days
of Home Health.
Outcome .......
NQF0171 .......
CCW
(Claims).
Number of home health stays for patients who have a Medicare claim
for an unplanned admission to an
acute care hospital in the 60 days
following the start of the home
health stay.
Efficiency & Cost
Reduction.
Emergency Department Use
without Hospitalization.
Outcome .......
NQF0173 .......
CCW
(Claims).
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.
Patient Safety ......
Improvement in
Pain Interfering
with Activity.
Outcome .......
NQF0177 .......
OASIS
(M1242).
Patient Safety ......
Improvement in
Management of
Oral Medications.
Outcome .......
NQF0176 .......
OASIS
(M2020).
Population/Community Health.
Influenza Immunization Received
for Current Flu
Season.
Process .........
NQF0522 .......
OASIS
(M1046).
Population/Community Health.
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NQS domains
Pneumococcal
Polysaccharide
Vaccine Ever
Received.
Process .........
NQF0525 .......
OASIS
(M1051).
Number of home health episodes of
care where the value recorded on
the discharge assessment indicates less frequent pain at discharge than at the start (or resumption) of care.
Number of home health episodes of
care where the value recorded on
the discharge assessment indicates less impairment in taking
oral medications correctly at discharge than at start (or resumption) of care.
Number of home health episodes
during which patients (a) received
vaccination from the HHA or (b)
had received vaccination from
HHA during earlier episode of
care, or (c) was determined to
have received vaccination from
another provider.
Number of home health episodes
during which patients were determined to have ever received
Pneumococcal
Polysaccharide
Vaccine (PPV).
Patient & Caregiver-Centered
Experience.
Patient & Caregiver-Centered
Experience.
Care of Patients ..
Outcome .......
........................
CAHPS ....
NA .....................................................
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.
Communications
between Providers and Patients.
Outcome .......
........................
CAHPS ....
NA .....................................................
NA.
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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.
Number of home health episodes of
care ending with discharge or
transfer to inpatient facility during
the reporting period, other than
those covered by generic or
measure-specific exclusions.
Number of home health stays that
begin during the 12-month observation period.
A home health stay is a sequence of
home health payment episodes
separated from other home health
payment episodes by at least 60
days.
Number of home health stays that
begin during the 12-month observation period.
A home health stay is a sequence of
home health payment episodes
separated from other home health
payment episodes by at least 60
days.
Number of home health episodes of
care ending with a discharge during the reporting period, other than
those covered by generic or
measure-specific exclusions.
Number of home health episodes of
care ending with a discharge during the reporting period, other than
those covered by generic or
measure-specific exclusions.
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.
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TABLE 43—MEASURE SET FOR THE HHVBP MODEL 102 BEGINNING PY 3—Continued
NQS domains
Measure title
Measure type
Identifier
Data
source
Numerator
Denominator
Patient & Caregiver-Centered
Experience.
Patient & Caregiver-Centered
Experience.
Patient & Caregiver-Centered
Experience.
Population/Community Health.
Specific Care
Issues.
Outcome .......
........................
CAHPS ....
NA .....................................................
NA.
Overall rating of
home health
care.
Willingness to recommend the
agency.
Influenza Vaccination Coverage
for Home
Health Care
Personnel.
Outcome .......
........................
CAHPS ....
NA .....................................................
NA.
Outcome .......
........................
CAHPS ....
NA .....................................................
NA.
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?
Advance 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.
Communication &
Care Coordination.
We invite public comment on the
proposal to remove one OASIS-based
measure, Drug Education on All
Medications Provided to Patient/
Caregiver during All Episodes of Care,
from the set of applicable measures for
PY3 and subsequent performance years
and Table 43.
mstockstill on DSK30JT082PROD with PROPOSALS2
C. Quality Measures for Future
Consideration
The CY 2016 HH PPS final rule
discusses the HHVBP Model design, the
guiding principles to select measures,
and the six priority areas of the National
Quality Strategy (NQS) we considered
for the Model (80 FR 68656 through
68678). Under the HHVBP Model, any
measures we determine to be good
indicators of quality will be considered
for use in the HHVBP Model in future
years, and may be added or removed
through the rulemaking process. To
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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.
further our commitment to objectively
assess HHVBP quality measures, we are
utilizing an implementation contractor
that invited a group of measure experts
to provide advice on the adjustment of
the current measure set for
consideration. The contractor convened
a technical expert panel (TEP)
consisting of 11 panelists with expertise
in home health care and quality
measures that met on September 7,
2016, in Baltimore, Maryland and via
conference call on December 2, 2016.
The TEP discussed developing a
composite total change in ADL/IADL
measure; a composite functional decline
measure; a measure to capture when an
HHA correctly identifies the patient’s
need for mental and behavioral health
supervision; and a measure to identify
if a caregiver is able to provide the
patient’s mental or behavioral health
supervision, to align with
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Total number of Medicare beneficiaries aged 60 years and over
receiving services from the HHA.
All patients aged 65 years and older.
§ 409.45(b)(3)(iii) and the Medicare
Benefit Policy Manual (Pub. 100–02),
Chapter 7, Section 20.2. We discuss
each of these potential measures in
further detail in this section of the
proposed rule. While any new measures
would be proposed for use in future
rulemaking, we are inviting comment on
these potential measures now to inform
measure development and selection.
As noted in the CY 2017 HH PPS final
rule (81 FR 76747), we received several
comments expressing concern that the
measures under the Model do not reflect
the patient population served under the
Medicare Home Health benefit as the
outcome measures focus on a patient’s
clinical improvement and do not
address patients with chronic illnesses;
deteriorating neurological, pulmonary,
cardiac, and other conditions; and some
with terminal illness. These
commenters opined that the value of
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including stabilization measures in the
HHVBP Model is readily apparent as it
aligns the Model with the Medicare
Home Health benefit. Commenters also
expressed concerns that improvement is
not always the goal for each patient and
that stabilization is a reasonable clinical
goal for some patients. Commenters
suggested the addition of stabilization or
maintenance measures be considered for
the HHVBP Model. Many commenters
objected to the use of improvement
measures in the HHVBP Model. We did
not receive any specific measures for
future consideration. In the subsections
that follow, we are identifying measures
that we are considering for possible
inclusion under the Model in future
rulemaking and are seeking input from
the public on the measures mentioned,
as well as any input about the
development or construction of the
measures and their features or
methodologies.
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1. Total Change in ADL/IADL
Performance by HHA Patients
The measure set finalized in the CY
2016 HH PPS final rule included
Change in Daily Activity Function as
Measured by the Activity Measure for
Post-Acute Care (AM–PAC) (NQF
#0430). However, the measure was
removed in the CY 2017 HH PPS final
rule and never used in the HHVBP
Model because the measure required use
of a proprietary data collection
instrument in the home health
environment. We are considering
replacing Change in Daily Activity
Function as Measured by AM–PAC
(NQF #0430) with a composite total
ADL/IADL change performance
measure. During the September 2016
TEP meeting, an alternative to the
Change in Daily Activity Function
measure was presented. The TEP
requested that a composite Total ADL/
IADL Change measure be investigated
empirically. This measure was
discussed as part of the follow-up
conference call, and the TEP supported
continued development of the measure
in the HHVBP Model as a way of
including a measure that captures all
three potential outcomes for home
health patients: Stabilization; decline;
and improvement. They provided input
on the technical specifications of the
potential composite measure, including
the feasibility of implementing the
measure and the overall measure
reliability and validity. We have
reviewed this suggested alternative and
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believe this measure would provide
actionable and transparent information
that would support HHA efforts to
improve care and prevent functional
decline for all patients across a broad
range of patient functional outcomes.
The measure would also improve
accountability during an episode of care
when the patient is directly under the
HHA’s care.
The name of this potential composite
measure could be Total Change in ADL/
IADL Performance by HHA Patients.
The measure would report the average,
normalized, total improved functioning
across the 11 ADL/IADL items on the
current OASIS–C2 instrument. The
measure is calculated by comparing
scores from the start-of-care/resumption
of care to scores at discharge. For each
item the patient’s discharge assessed
performance score is subtracted from
the patient’s start of care/resumption of
care assessed performance score, and
then divided by the maximum
improvement value based on the
number of response options for that
item. These values are summed into a
total normalized change score that can
range from ¥11 (that is, for an episode
where there is maximum decline on all
11 items used in the measure) to +11
(that is, for an episode where there is
the maximum improvement on all 11
items). An HHA’s score on the measure
is based on its average across all eligible
episodes. Patients who are independent
on all 11 ADL/IADL items at Start of
Care (SOC)/Resumption of Care (ROC)
would also be included in the measure.
The HHA’s observed score on the
measure is the average of the
normalized total scores for all eligible
episodes for its patients during the
reporting period.
The following 11 ADLs/IADL-related
items from OASIS–C2 items were
included in developing a composite
measure:
ADL OASIS–C2 items related to SelfCare:
• M1800 (Grooming).
• M1810 (Upper body dressing).
• M1820 (Lower body dressing).
• M1845 (Toileting hygiene).
• M1870 (Eating).
ADL OASIS–C2 items related to
Mobility:
• M1840 (Toilet transferring).
• M1840 (Bed transferring).
• M1860 (Ambulation).
Other IADLs OASIS items:
• M1880 (Light meal preparation).
• M1890 (Telephone use).
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35337
• M2020 (Oral medication
management).
Based on the measures identified
above, we would risk-adjust using
OASIS–C2 items to account for case-mix
variation and other factors that affect
functional decline but are beyond the
influence of the HHA. The riskadjustment model uses an ordinary least
squares (OLS) 103 104 regression
framework because the outcome
measure (normalized change in ADL/
IADL performance) is a continuous
variable.
The prediction model for this
outcome measure was derived using the
predicted values from the 11 individual
outcomes that are currently used to risk
adjust these 11 individual quality
measures. Of the 11 values tested, the 8
identified in this proposed rule were
found to be statistically related to the
Total Change in ADL/IADL Performance
by HHA Patients measure at p <0.0001
level and would be used in the
prediction model that we are
considering proposing to use to risk
adjust the HHA’s observed value with
respect to this potential future measure.
The prediction model for this outcome
measure uses predicted values from the
following individual outcomes (Note:
The primary source OASIS item is listed
in parenthesis after the name of the
quality measure):
• Improvement in Upper Body
Dressing (M1810).
• Improvement in Management of
Oral Medications (M2020).
• Improvement in Bed Transferring
(M1850).
• Improvement in Ambulation/
Locomotion (M1860).
• Improvement in Grooming (M1800).
• Improvement in Toileting Hygiene
(M1845).
• Discharged to the Community
(M2420).
• Improvement in Toileting Transfer
(M1840).
Two predictive models, one based on
predicted values from CY2014 and one
from CY2015, were computed. The
correlations at the episode level
between observed and predicted values
for the target outcome measure Total
Change in ADL/IADL Performance by
HHA Patients are shown in Table 44.
103 Fox, John (1997). Applied Regression
Analysis, Linear Models, and Related Methods/
Edition 1, 1997, SAGE.
104 Green, William H. (2017). Econometric
analysis (8th ed.). New Jersey: Pearson. ISBN 978–
0134461366.
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TABLE 44—CORRELATIONS AT THE EPISODE LEVEL BETWEEN OBSERVED AND PREDICTED VALUES FOR THE TARGET
OUTCOME MEASURE TOTAL CHANGE IN ADL/IADL PERFORMANCE BY HHA PATIENTS
Data group
CY2014,
CY2014,
CY2015,
CY2015,
National .....................................................................................................................
HHVBP states ...........................................................................................................
National .....................................................................................................................
HHVBP states ...........................................................................................................
The results in Table 44 suggest that
either model would account for 25
percent or more of the variability in the
outcome measure. These models could
be considered very strong predictive
models for the target outcome measure.
Although the analysis supports
developing a composite measure, the
analysis assumes that the OASIS–C2
items identified to be used in the
composite measure do not change;
however, we recognize that OASIS–C2
items could be removed or added in any
given year. We expect to conduct an
additional analysis, in advance of any
future proposal, to assess whether
changes to OASIS–C2 items that are
removed or added could significantly
impact a HHA’s ability to address
several measures to improve its overall
score in the composite measure. We are
soliciting public comments on whether
or not to include a composite total ADL/
IADL change performance measure in
the set of applicable measures, the name
of any such measure, the risk
adjustment method, and whether we
should conduct an analysis of the
impact of removal/addition of OASIS–
C2 items.
2. Composite Functional Decline
Measure
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Correlation
The second measure we are
considering for possible inclusion under
the Model in future rulemaking is a
Composite Functional Decline Measure
that could be the percentage of episodes
where there was decline on one or more
of the eight ADL items used in the
measure. As noted in this proposed rule,
we received comments on the CY 2017
HH PPS proposed rule suggesting that
we consider the addition of stabilization
or maintenance measures. To address
this suggestion, we are considering a
composite functional decline measure
because the existing functional
stabilization measures, taken
individually, are topped out, with HHA
level means of 95 percent or higher.
This type of composite functional
decline measure is similar to the
composite ADL decline measure that is
used in the Skilled Nursing Facility
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(SNF) Quality Reporting program
(QRP).105 The SNF QRP measure is
constructed from four ADL items: Bed
mobility; transfer; eating; and toileting.
An HHVBP composite functional
decline measure could provide
actionable and transparent information
that could support HHA efforts to
improve care and prevent functional
decline for all patients, including those
for whom improvement in functional
status is not a realistic care goal. This
concept was discussed during the TEP
meeting on September 7, 2016, with a
follow-up conference call held on
December 2, 2016. The TEP supported
the inclusion of measures of
stabilization and decline in the HHVBP
Model, as well as further development
of the composite functional decline
measure. They provided input on the
technical specifications of the potential
composite measure, including the
feasibility of implementing the measure
and the overall measure reliability and
validity.
When calculating the composite
functional decline measure, we could
use the following 8 existing OASIS–C2
items identified below:
• Ambulation/Locomotion (M1860).
• Bed Transferring (M1840).
• Toilet Transferring (M1840).
• Bathing (M1830).
• Toilet Hygiene (M1845).
• Lower Body Dressing (M1820).
• Upper Body Dressing (M1810).
• Grooming (M1800).
The measure could be defined as 1 if
there is decline reported in one or more
of these items between the Start of Care
and the Discharge assessments and zero
if no decline is reported on any of these
items. As with other OASIS-based
measures, a performance score for the
measure would only be calculated for
HHAs that have 20 or more episodes of
care during a performance year.
The measure could be risk-adjusted
using OASIS–C2 items to account for
105 ‘‘Long-stay Nursing Home Care: Percent of
Residents Whose Need for help with Activities of
Daily Living has Increased.’’ https://
www.qualitymeasures.ahrq.gov/summaries/
summary/50060.
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0.5022
0.5094
0.5011
0.5076
Significance
(p < )
0.0001
0.0001
0.0001
0.0001
r2
(Coeff.
Determination)
(%)
25.22
25.95
25.11
25.76
case-mix variation and other factors that
affect functional decline but are beyond
the influence of the HHA. The riskadjustment model uses a logistic
regression framework. The model
includes a large number of patient
clinical conditions and other
characteristics measured at start of care.
A logistic regression model is estimated
to predict whether the patient will have
length of stay of greater than 60 days.
The predicted probability of length of
stay of greater than 60 days is used,
along with other patient characteristics,
to construct a logistic regression model
to predict the probability of decline in
any of eight ADLs. This model is used
to estimate the predicted percent of ADL
decline at the HHA level. To calculate
case-mix adjusted values, the observed
value of the measure is adjusted by the
difference between the HHA predicted
percent and the national predicted
percent. The risk-adjustment model
reduces the adjusted difference between
HHAs that serve a disproportionate
number of longer-stay patients and
those that serve patients with more
typical lengths of stay of one episode.
Across all participating HHAs in the
HHVBP Model, for HHAs that had less
than 20 percent of episodes lasting more
than 60 days, the average on the
functional decline measure was 8.08
percent. This increased to 11.08 percent
for HHAs with 20 percent to 40 percent
of episodes lasting more than 60 days,
14.23 percent for HHAs with 40 percent
to 60 percent of episodes lasting more
than 60 days, and 20.59 percent for
HHAs with more than 60 percent of
episodes lasting more than 60 days. This
finding suggests that, in addition to
focusing on prevention of functional
decline, we should also attempt to better
predict a patient’s functional trajectory
and potentially stratify the population
to exclude those on a likely downward
trajectory. However, in spite of this
finding, the inclusion of a measure that
rewards providers for avoiding
functional decline has the advantage of
diversifying the set of measures for the
HHVBP model. We are soliciting public
comments on whether or not to include
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a composite functional decline measure
in the set of applicable measures, the
name of any such measure, the risk
adjustment method, and whether we
should conduct an analysis of the
impact of removal/addition of OASIS–
C2 items.
3. Behavioral Health Measures
Although we did not receive
comments or suggestions through the
rulemaking process for the HHVBP
Model regarding behavioral or mental
health measures, we recognize that the
Model does not include such measures.
The OASIS–C2 collects several items
related to behavioral and mental health
(M1700 Cognitive Functioning; M1710
Confusion Frequency; M1720 Anxiety;
M1730 Depression Screening; M1740
Cognitive, Behavioral, and Psychiatric
Symptoms; M1745 Frequency of
Disruptive Behavior Symptoms; and
M1750 Psychiatric Nursing Services).
These items are used to compute both
Improvement and Process measures as
well as Potentially Avoidable Events.
The inclusion of behavioral health
measures is important for care
transformation and improvement
activities as many persons served by the
Home Health program may have
behavioral health needs.
The TEP made several suggestions
during the December 2016 conference
call as to whether the focus of a
behavioral or mental health measure
could be identifying whether a patient
needed mental or behavioral health
assistance compared to the supervision
of the patient or advocacy assistance.
The TEP supports the supervision type
measure due to its opportunity for
potential improvement. In further
analyses, we identified two underlying
components to outcomes for providing
assistance. We developed a method,
described below, to identify patients
who have or do not have needs for
mental or behavioral health supervision.
We are considering further refining this
method by identifying the involvement
of the caregiver in addressing the
patient’s mental or behavioral health
supervision needs as an important
outcome measure, and we seek
comment on whether this is an
appropriate factor or feature that we
should consider in developing such a
measure in future rulemaking.
a. HHA Correctly Identifies Patient’s
Need for Mental or Behavioral Health
Supervision
We are considering adding a HHA
Correctly Identifies Patient’s Need for
Mental or Behavioral Health
Supervision measure to the HHVBP
Model in the future to capture a
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patient’s need for mental or behavioral
health supervision based on an
identifier. This identifier is based on
information from existing Neuro/
Emotional/Behavioral Status OASIS
items, along with other indicators of
mental/behavioral health problems to
identify a patient in need of supervisory
assistance. The outcome measure
assesses whether the HHA correctly
identifies whether or not the patient
needs mental or behavioral health
supervision based on the OASIS SOC/
ROC assessment item M2102f, Types
and Sources of Assistance: Supervision
and Safety.
A composite Mental/Behavioral
Health measure could be a dichotomous
measure that reports the percentage of
episodes of care where the HHA
correctly identifies: (a) Patients who
need mental or behavioral health
supervision; and (b) patients who don’t
need mental or behavioral health
supervision. The numerator could be a
combination of two values: (1) The
number of episodes of care where the
HHA correctly identifies patients who
need mental or behavioral health
supervision; plus (2) the number of
episodes of care where the HHA
correctly identifies patients who don’t
need mental or behavioral health
supervision. The denominator is all
episodes of care.
The composite measure requires that
a patient’s need for mental or behavioral
health supervision be identified. The
following algorithm was designed to
identify if a patient was in need of
mental or behavioral health supervision.
If the patient met any of the following
conditions, the patient was identified by
the algorithm as in need of mental or
behavioral health supervision:
• Was discharged from a psychiatric
hospital prior to entering home health
care (M1000 = 6);
• Is diagnosed as having chronic
mental behavioral problems (M1021 and
M1023);
• Is diagnosed with a mental illness
(M1021 and M1023);
• Is cognitively impaired (M1700 > =
2);
• Is confused (M1710 > = 2);
• Is identified as having a memory
deficit (M1740 = 1);
• Is identified as having impaired
decision-making (M1740 = 2);
• Is identified as being verbally
disruptive (M1740 = 3);
• Is identified as being physically
aggressive (M1740 = 4);
• Is identified as exhibiting
disruptive, infantile, or inappropriate
behaviors (M1740 = 5);
• Is identified as being delusional
(M1740 = 6); or
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35339
• Has a frequency of disruptive
symptoms (M1745 >= 2.
The measure also requires that the
HHA identify if the patient is in need of
mental or behavioral health supervision.
This requirement is based on the SOC/
ROC code for M2102f, Types and
Sources of Assistance: Supervision and
Safety. If the HHA codes a value of 0,
then the HHA has identified this patient
as not needing mental or behavioral
health supervision. If the HHA codes
another value for M2102f, Types and
Sources of Assistance: Supervision and
Safety, then the HHA has identified this
patient as needing mental or behavioral
health supervision. The outcome
measure is defined as the agreement
between the algorithm’s identification of
a patient’s need for mental or behavioral
health supervision and the HHA’s
coding of this need. That is, if—
• The algorithm identifies the patient
as not in need of mental or behavioral
health supervision and the HHA
identifies the patient as not in need of
mental or behavioral health supervision,
or
• The algorithm identifies the patient
as in need of mental or behavioral
health supervision and the HHA
identifies the patient as in need of
mental or behavioral health supervision,
then
• The outcome is coded as 1,
successful.
As with other OASIS-based measures,
a performance score for the measure
would only be calculated for HHAs that
have 20 or more episodes of care during
a performance year.
The measure is risk-adjusted using
OASIS–C2 items to account for case-mix
variation and other factors that affect
functional decline but are beyond the
influence of the HHA. The riskadjustment model uses a logistic
regression framework. The model
includes a large number of patient
clinical conditions and other
characteristics measured at the start of
care. To calculate case-mix adjusted
values, the observed value of the
measure is adjusted by the difference
between the HHA predicted percent and
the national predicted percent.
The prediction model for this
outcome measure uses 39 risk factors 106
with each risk factor statistically
significant at <0.0001. The correlation
for the model between observed and
predicted values as estimated by
106 ‘‘Home Health Quality Initiative: Quality
Measures’’ https://www.cms.gov/Medicare/QualityInitiatives-Patient-Assessment-Instruments/Home
HealthQualityInits/HHQIQualityMeasures.html.
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Somers’ D 107 is 0.427, that yields an
estimated coefficient of determination
(r2) value based on the Tau-a 108 of
0.201. This suggests that the variability
in the model accounts for (predicts)
approximately 20 percent of the
variability in the outcome measure. The
best statistic for evaluating the power of
a prediction model that is derived using
logistic regression is the c-statistic.109
This statistic identifies the overall
accuracy of prediction by comparing
observed and predicted value pairs to
the proportion of the time that both
predict the outcome in the same
direction with 0.500 being a coin-flip.
The discussed prediction model has a cstatistic equal to 0.713, which is
considered to be strong. Using data from
CY 2015, the episode-level mean for the
HHA Correctly Identifies Patient’s Need
for Mental or Behavioral Health
Supervision measure is 61.98 percent,
nationally, and 62.98 percent for the
HHVBP states.
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b. Caregiver Can/Does Provide for
Patient’s Mental or Behavioral Health
Supervision Need
We are considering including under
the Model in future rulemaking a
Caregiver Can/Does Provide for Patient’s
Mental or Behavioral Health
Supervision Need measure that would
encourage HHAs to ensure that patients
who need mental or behavioral health
supervision are receiving such care from
the patient’s caregivers, and would be a
realistic care goal.
107 Somers’ D is a statistic that is based on the
concept of concordant vs. discordant pairs for two
related values. In this case, if both the observed and
predicted values are higher than the average or if
both values are less than the average, then the pair
of numbers is considered concordant. However, if
one value is higher than average and the other is
lower than average—or vice versa, then the pair of
values is considered discordant. The Somer’s D is
(# of concordant pairs ¥ # of discordant pairs)/total
# of pairs. The higher the ratio, the stronger the
concordance between the two set of values.
108 The Kendall Tau-a assumes that if there is a
correlation between two variables, then sorting the
variables based on one of the values will result in
ordering the second variable. It uses the same
concept of concordant pairs in Somers’ D but a
different formula: t = [(4P)/[(n) (n¥1)]¥1 where p
= # of concordant pairs and n = # of pairs. This
correlation method reduces the effect of outlier
values as the values are essentially ranked.
109 The C-statistic (sometimes called the
‘‘concordance’’ statistic or C-index) is a measure of
goodness of fit for binary outcomes in a logistic
regression model. In clinical studies, the C-statistic
gives the probability a randomly selected patient
who experienced an event (for example, a disease
or condition) had a higher risk score than a patient
who had not experienced the event. It is equal to
the area under the Receiver Operating Characteristic
(ROC) curve and ranges from 0.5 to 1.
• A value below 0.5 indicates a very poor model.
• A value of 0.5 means that the model is no better
than predicting an outcome than random chance.
• Values over 0.7 indicate a good model.
• Values over 0.8 indicate a strong model.
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When considering how to develop a
measure to determine whether or not
the caregiver can/does provide the
patient’s mental or behavioral health
supervision, we would create an
identifier of a patient’s need for mental
or behavioral health supervision. This
identifier is based on the same
algorithm described in the previous
section from existing Neuro/Emotional/
Behavioral Status OASIS items along
with other indicators of mental/
behavioral health problems to identify a
patient in need of supervisory
assistance. The outcome measure is
whether the HHA correctly identifies
this patient as having the need for
mental or behavioral health supervision
based on the OASIS SOC/ROC
assessment item M2102f, Types and
Sources of Assistance: Supervision and
Safety.
The measure could be a dichotomous
measure that reports the percentage of
episodes where patients with identified
mental or behavioral health supervision
needs have their needs met or could
have their needs met by the patient’s
caregiver with additional training (if
needed) and support by the HHA. The
numerator is the intersection of: (1) The
number of episodes of care where the
patient needs mental or behavioral
health supervision; and (2) the number
of episodes of care where these patients
have their needs met or could have their
needs met by the patient’s caregiver
with additional training (if needed) and
support by the HHA. By intersection, we
mean that, for the numerator to equal
one, a patient has to need mental or
behavioral health supervision and has to
have these needs met by his or her
caregiver, or could have their needs met
by the caregiver with additional training
and/or support by the HHA. The
denominator is all episodes of care. The
algorithm discussed above for HHA
Correctly Identifies Patient’s Need for
Mental or Behavioral Health
Supervision could also be used to first
identify if a patient was in need of
mental or behavioral health supervision.
To identify whether caregivers are
able to provide supervisory care or, with
training, could be able to provide
supervisory care for these patients, we
could use the SOC/ROC code for
M2102f, Types and Sources of
Assistance: Supervision and Safety. If
the HHA codes a value of 1 (Non-agency
caregiver(s) currently provide
assistance) or 2 (Non-agency caregiver(s)
need training/supportive services to
provide assistance), then the measure
identifies that a caregiver does or could
provide supervision to a patient who
has been identified as needing mental or
behavioral health supervision.
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The outcome measure is defined as
the agreement between the algorithm’s
identification of a patient’s need for
mental or behavioral health supervision
and the availability of supervision from
the patient’s caregiver(s). That is, if—
• The algorithm identifies the patient
as in need of mental or behavioral
health supervision and there is
documentation that the patient’s
caregiver(s) do or could provide this
supervision; then
• The outcome is coded as 1,
successful.
As with other OASIS-based measures,
a performance score for the measure
would only be calculated for HHAs that
have 20 or more episodes during a
performance year. We would use the
same methodology to risk-adjust by
using OASIS–C2 items and the
prediction model described above. The
prediction model for this outcome
measure uses 55 risk factors with each
risk factor significant at p < 0.0001. The
correlation for the model between
observed and predicted values as
estimated by Somers’ D is 0.672, that
yields an estimated coefficient of
determination (r2) value based on the
Tau-a of 0.205. This suggests that the
variability in the model accounts for
(predicts) approximately 20 percent of
the variability in the outcome measure.
The best statistic for evaluating the
power of a prediction model that is
derived using logistic regression is the
c-statistic. This statistic identifies the
overall accuracy of prediction by
comparing observed and predicted
value pairs to the proportion of the time
that both predict the outcome in the
same direction with 0.500 being a coinflip. The prediction model has a cstatistic equal to 0.836, which is
considered to be extremely strong.
We are considering whether the HHA
Correctly Identifies Patient’s Need for
Mental or Behavioral Health
Supervision measure or the Caregiver
Can/Does Provide for Patient’s Mental
or Behavioral Health Supervision Need
measure would be most meaningful to
include in the Model. We are also
considering the interactions between the
Home Health Grouping Model (HHGM)
proposal on quality measures discussed
in section III of this proposed rule and
the HHVBP Model for the quality
measures discussed in section IV.B of
this proposed rule. We are soliciting
public comments on the methodologies,
analyses used to test the quality
measure, and issues described in this
section for future measure
considerations. We will continue to
share analyses as they become available
with participating HHAs during future
webinars.
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V. Proposed Updates to the Home
Health Care Quality Reporting Program
(HH QRP)
A. Background and Statutory Authority
Section 1895(b)(3)(B)(v)(II) of the Act
requires that for 2007 and subsequent
years, each HHA submit to the Secretary
in a form and manner, and at a time,
specified by the Secretary, such data
that the Secretary determines are
appropriate for the measurement of
health care quality. To the extent that an
HHA does not submit data in
accordance with this clause, the
Secretary is directed to reduce the home
health market basket percentage
increase applicable to the HHA for such
year by 2 percentage points. As
provided at section 1895(b)(3)(B)(vi) of
the Act, depending on the market basket
percentage increase applicable for a
particular year, the reduction of that
increase by 2 percentage points for
failure to comply with the requirements
of the HH QRP, and further reduction of
the increase by the productivity
adjustment described in section
1886(b)(3)(B)(xi)(II) of the Act, may
result in the home health market basket
percentage increase 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.
We use the terminology ‘‘CY [year]
HH QRP’’ to refer to the calendar year
for which the HH QRP requirements
applicable to that calendar year must be
met in order for an HHA to avoid a 2
percentage point reduction to its market
basket percentage increase under
section 1895(b)(3)(B)(v)(I) of the Act
when calculating the payment rates
applicable to it for that calendar year.
The Improving Medicare Post-Acute
Care Transformation Act of 2014 (Pub.
L. 113–185, enacted on October 6, 2014)
(IMPACT Act) amended Title XVIII of
the Act, in part, by adding new section
1899B of the Act, entitled
‘‘Standardized Post-Acute Care
Assessment Data for Quality, Payment,
and Discharge Planning,’’ and by
enacting new data reporting
requirements for certain post-acute care
(PAC) providers, including Home
Health Agencies (HHAs). Specifically,
new sections 1899B(a)(1)(A)(ii) and (iii)
of the Act require HHAs, Inpatient
Rehabilitation Facilities (IRFs), Long
Term Care Hospitals (LTCHs) and
Skilled Nursing Facilities (SNFs), under
each of their respective quality reporting
program (which, for HHAs, is found at
section 1895(b)(3)(B)(v) of the Act), to
report data on quality measures
specified under section 1899B(c)(1) of
the Act for at least five domains, and
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data on resource use and other measures
specified under section 1899B(d)(1) of
the Act for at least three domains.
Section 1899B(a)(1)(A)(i) of the Act
further requires each of these PAC
providers to report under their
respective quality reporting program
standardized patient assessment data in
accordance with subsection (b) for at
least the quality measures specified
under subsection (c)(1) and that is for
five specific categories: Functional
status; cognitive function and mental
status; special services, treatments, and
interventions; medical conditions and
co-morbidities; and impairments. All of
the data that must be reported in
accordance with section 1899B(a)(1)(A)
of the Act must be standardized and
interoperable, so as to allow for the
exchange of the information among PAC
providers and other providers, as well
as for the use of such data to enable
access to longitudinal information and
to facilitate coordinated care. We refer
readers to the CY 2016 HH PPS final
rule (80 FR 68690 through 68692) for
additional information on the IMPACT
Act and its applicability to HHAs.
B. General Considerations Used for the
Selection of Quality Measures for the
HH QRP
We refer readers to the CY 2016 HH
PPS final rule (80 FR 68695 through
68698) for a detailed discussion of the
considerations we apply in measure
selection for the HH QRP, such as
alignment with the CMS Quality
Strategy,110 which incorporates the
three broad aims of the National Quality
Strategy.111 As part of our consideration
for measures for use in the HH QRP, we
review and evaluate measures that have
been implemented in other programs
and take into account measures that
have been endorsed by NQF for
provider settings other than the HH
setting. We have previously adopted
measures with the term ‘‘Application
of’’ in the names of those measures. We
have received questions pertaining to
the term ‘‘application’’ and want to
clarify that when we refer to a measure
as an ‘‘Application of’’ the measure, we
mean that the measure would be used
in a setting other than the setting for
which it was endorsed by the NQF. For
example, in the FY 2016 SNF PPS Rule
(80 FR 46440 through 46444 we adopted
an Application of Percent of Residents
with Experiencing Falls with Major
Injury (Long Stay) (NQF #0674), which
110 https://www.cms.gov/Medicare/QualityInitiatives-Patient-Assessment-Instruments/Quality
InitiativesGenInfo/CMS-Quality-Strategy.html.
111 https://www.ahrq.gov/workingforquality/nqs/
nqs2011annlrpt.htm.
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is endorsed for the Nursing Home
setting but not the SNF setting. For such
measures, we intend to seek NQF
endorsement for the HH setting, and if
the NQF endorses one or more of them,
we will update the title of the measure
to remove the reference to ‘‘Application
of.’’
C. Accounting for Social Risk Factors in
the HH QRP
We consider related factors that may
affect measures in the HH QRP. We
understand that social risk factors such
as income, education, race and
ethnicity, employment, disability,
community resources, and social
support (certain factors of which are
also sometimes referred to as
socioeconomic status (SES) factors or
socio-demographic status (SDS) factors)
play a major role in health. One of our
core objectives is to improve beneficiary
outcomes including reducing health
disparities, and we want to ensure that
all beneficiaries, including those with
social risk factors, receive high quality
care. In addition, we seek to ensure that
the quality of care furnished by
providers and suppliers is assessed as
fairly as possible under our programs
while ensuring that beneficiaries have
adequate access to excellent care.
We have been reviewing reports
prepared by the Office of the Assistant
Secretary for Planning and Evaluation
(ASPE 112) and the National Academies
of Sciences, Engineering, and Medicine
on the issue of measuring and
accounting for social risk factors in
CMS’ value-based purchasing and
quality reporting programs, and
considering options on how to address
the issue in these programs. On
December 21, 2016, ASPE submitted a
Report to Congress on a study it was
required to conduct under section 2(d)
of the Improving Medicare Post-Acute
Care Transformation (IMPACT) Act of
2014. The study analyzed the effects of
certain social risk factors of Medicare
beneficiaries on quality measures and
measures of resource use used in one or
more of nine Medicare value-based
purchasing programs.113 The report also
included considerations for strategies to
account for social risk factors in these
programs. In a January 10, 2017 report
released by The National Academies of
Sciences, Engineering, and Medicine,
that body provided various potential
112 https://aspe.hhs.gov/pdf-report/reportcongress-social-risk-factors-and-performanceunder-medicares-value-based-purchasingprograms.
113 https://aspe.hhs.gov/pdf-report/reportcongress-social-risk-factors-and-performanceunder-medicares-value-based-purchasingprograms.
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methods for measuring and accounting
for social risk factors, including
stratified public reporting.114
As discussed in the CY 2017 HH PPS
final rule, the NQF has undertaken a 2year trial period in which new
measures, measures undergoing
maintenance review, and measures
endorsed with the condition that they
enter the trial period can be assessed to
determine whether risk adjustment for
selected social risk factors is appropriate
for these measures. Measures from the
HH QRP, Rehospitalization During the
First 30 Days of Home Health (NQF
#2380), and Emergency Department Use
without Hospital Readmission During
the First 30 Days of Home Health (NQF
#2505) are being addressed in this trial.
This trial entails temporarily allowing
inclusion of social risk factors in the
risk-adjustment approach for these
measures. At the conclusion of the trial,
NQF will issue recommendations on the
future inclusion of social risk factors in
risk adjustment for quality measures.
As we continue to consider the
analyses and recommendations from
these reports and await the results of the
NQF trial on risk adjustment for quality
measures, we are continuing to work
with stakeholders in this process. As we
have previously communicated, we are
concerned about holding providers to
different standards for the outcomes of
their patients with social risk factors
because we do not want to mask
potential disparities or minimize
incentives to improve the outcomes for
disadvantaged populations. Keeping
this concern in mind, while we sought
input on this topic previously, we
continue to seek public comment on
whether we should account for social
risk factors in measures in the HH QRP,
and if so, what method or combination
of methods would be most appropriate
for accounting for social risk factors.
Examples of methods include:
Confidential reporting to providers of
measure rates stratified by social risk
factors, public reporting of stratified
measure rates, and potential risk
adjustment of a particular measure as
appropriate based on data and evidence.
In addition, we are seeking public
comment on which social risk factors
might be most appropriate for reporting
stratified measure scores and potential
risk adjustment of a particular measure.
Examples of social risk factors include,
but are not limited to, dual eligibility/
low-income subsidy, race and ethnicity,
and geographic area of residence. We
are seeking comments on which of these
factors, including current data sources
where this information would be
available, could be used alone or in
combination, and whether other data
should be collected to better capture the
effects of social risk. We will take
commenters’ input into consideration as
we continue to assess the
appropriateness and feasibility of
accounting for social risk factors in the
HH QRP. We note that any such changes
would be proposed through future
notice and comment rulemaking.
We look forward to working with
stakeholders as we consider the issue of
accounting for social risk factors and
reducing health disparities in CMS
programs. Of note, implementing any of
the above methods would be taken into
consideration in the context of how this
and other CMS programs operate (for
example, data submission methods,
availability of data, statistical
considerations relating to reliability of
data calculations, among others), so we
also welcome comment on operational
considerations. We are committed to
ensuring that beneficiaries have access
to and receive excellent care, and that
the quality of care furnished by
providers and suppliers is assessed
fairly in CMS programs.
D. Proposed Data Elements for Removal
From OASIS
We are proposing to remove 247 data
elements from 35 OASIS items collected
at specific time points during a home
health episode. These data elements are
not used in the calculation of quality
measures already adopted in the HH
QRP, nor are they being used for
previously established purposes
unrelated to the HH QRP, including
payment, survey, the HH VBP Model or
care planning. A list of the proposed 35
OASIS items and data elements are
listed in Table 45 and also at https://
www.cms.gov/Medicare/QualityInitiatives-Patient-AssessmentInstruments/HomeHealthQualityInits/
OASIS-Data-Sets.html.
TABLE 45—PROPOSED DATA ELEMENTS TO BE REMOVED FROM OASIS ON JANUARY 1, 2019
Specific time point
Start of
care
Resumption
of care
Follow-up
Transfer
to an
inpatient
facility
Death at
home
Discharge
from agency
........................
6
6
6
12
1
4
1
1
1
1
1
1
1
1
........................
........................
1
3
........................
........................
6
6
6
12
1
4
1
1
1
1
1
1
1
1
........................
........................
1
3
........................
........................
6
........................
........................
12
........................
........................
1
........................
........................
........................
........................
........................
........................
........................
........................
........................
........................
........................
........................
1
........................
........................
........................
........................
........................
........................
........................
........................
........................
........................
........................
........................
........................
........................
........................
........................
........................
........................
1
1
........................
........................
........................
........................
........................
........................
........................
........................
........................
........................
........................
........................
........................
........................
........................
........................
........................
........................
........................
1
........................
........................
........................
........................
........................
........................
........................
........................
........................
1
........................
........................
........................
1
1
1
........................
........................
1
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OASIS item
M0903
M1011
M1017
M1018
M1025
M1034
M1036
M1200
M1210
M1220
M1230
M1240
M1300
M1302
M1320
M1322
M1332
M1350
M1410
M1501
......................................................
......................................................
......................................................
......................................................
......................................................
......................................................
......................................................
......................................................
......................................................
......................................................
......................................................
......................................................
......................................................
......................................................
......................................................
......................................................
......................................................
......................................................
......................................................
......................................................
114 National Academies of Sciences, Engineering,
and Medicine. 2017. Accounting for social risk
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factors in Medicare payment. Washington, DC: The
National Academies Press.
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TABLE 45—PROPOSED DATA ELEMENTS TO BE REMOVED FROM OASIS ON JANUARY 1, 2019—Continued
Specific time point
Start of
care
Resumption
of care
Follow-up
Transfer
to an
inpatient
facility
Death at
home
Discharge
from agency
M1511 ......................................................
M1610 ......................................................
M1615 ......................................................
M1730 ......................................................
M1750 ......................................................
M1880 ......................................................
M1890 ......................................................
M1900 ......................................................
M2030 ......................................................
M2040 ......................................................
M2102 * ....................................................
M2110 ......................................................
M2250 ......................................................
M2310 ......................................................
M2430 ......................................................
........................
........................
1
3
1
1
1
4
1
2
6
1
7
........................
........................
........................
........................
1
3
1
1
1
4
1
2
6
1
7
........................
........................
........................
........................
........................
........................
........................
........................
........................
........................
1
........................
........................
........................
........................
........................
........................
5
........................
........................
........................
........................
........................
........................
........................
........................
........................
........................
........................
........................
*** 15
20
........................
........................
........................
........................
........................
........................
........................
........................
........................
........................
........................
........................
........................
........................
........................
5
1
1
........................
........................
1
1
........................
1
........................
** 3
........................
........................
*** 15
........................
Total ..................................................
75
75
20
42
1
34
OASIS item
* M2102 row f to remain collected at Start of Care, Resumption of Care and Discharge from Agency as part of the HH VBP program.
** M2102 rows a,c,d to remain collected at Discharge from Agency for survey purposes.
*** M2310 responses 1,10,OTH,UK to remain collected at Transfer to an Inpatient Facility and Discharge from Agency for survey purposes.
We are inviting public comment on
this proposal.
E. Proposed Collection of Standardized
Patient Assessment Data Under the HH
QRP
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1. Proposed Definition of Standardized
Patient Assessment Data
Section 1895(b)(3)(B)(v)(IV)(bb) of the
Act requires that beginning with the CY
2019 HH QRP, HHAs report
standardized patient assessment data
required under section 1899B(b)(1) of
the Act. For purposes of meeting this
requirement, section
1895(b)(3)(B)(v)(IV)(cc) of the Act
requires that a HHA submit the
standardized patient assessment data
required under section 1899B(b)(1) of
the Act in the form and manner, and at
the time, as specified by the Secretary.
Section 1899B(b)(1)(B) of the Act
describes standardized patient
assessment data as data required for at
least the quality measures described in
sections 1899B(c)(1) of the Act and
regarding the following categories:
• Functional status, such as mobility
and self-care at admission to a PAC
provider and before discharge from a
PAC provider;
• Cognitive function, such as ability
to express and understand ideas, and
mental status, such as depression and
dementia;
• Special services, treatments and
interventions such as the need for
ventilator use, dialysis, chemotherapy,
central line placement, and total
parenteral nutrition;
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• Medical conditions and
comorbidities such as diabetes,
congestive heart failure and pressure
ulcers;
• Impairments, such as incontinence
and an impaired ability to hear, see or
swallow; and
• Other categories deemed necessary
and appropriate by the Secretary.
As required under section
1899B(b)(1)(A) of the Act, the
standardized patient assessment data
must be reported at least for the
beginning of the home health episode
(for example, HH start of care/
resumption of care) and end of episode
(discharge), but the Secretary may
require the data to be reported more
frequently.
In this proposed rule, we are
proposing to define the standardized
patient assessment data that HHAs must
report under the HH QRP, as well as the
requirements for the reporting of these
data. The collection of standardized
patient assessment data is critical to our
efforts to drive improvement in
healthcare quality across the four postacute care (PAC) settings to which the
IMPACT Act applies. We intend to use
these data for a number of purposes,
including facilitating their exchange and
longitudinal use among healthcare
providers to enable high quality care
and outcomes through care
coordination, as well as for quality
measure calculation, and identifying
comorbidities that might increase the
medical complexity of a particular
admission.
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HHAs are currently required to report
patient assessment data through the
Outcome and Assessment Information
Set (OASIS) by responding to an
identical set of assessment questions
using an identical set of response
options (we refer to a solitary question/
response option as a data element and
we refer to a group of questions/
responses as data elements), both of
which incorporate an identical set of
definitions and standards. The primary
purpose of the identical questions and
response options is to ensure that we
collect a set of standardized data
elements across HHAs, which we can
then use for a number purposes,
including HH payment and measure
calculation for the HH QRP.
LTCHs, IRFs, and SNFs are also
required to report patient assessment
data through their applicable PAC
assessment instruments, and they do so
by responding to identical assessment
questions developed for their respective
settings using an identical set of
response options (which incorporate an
identical set of definitions and
standards). Like the OASIS, the
questions and response options for each
of these other PAC assessment
instruments are standardized across the
PAC provider type to which the PAC
assessment instrument applies.
However, the assessment questions and
response options in the four PAC
assessment instruments are not
currently standardized with each other.
As a result, questions and response
options that appear on the OASIS
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cannot be readily compared with
questions and response options that
appear, for example, on the Inpatient
Rehabilitation Facility-Patient
Assessment Instrument (IRF–PAI) the
PAC assessment instrument used by
IRFs. This is true even when the
questions and response options are
similar. This lack of standardization
across the four PAC provider types has
limited our ability to compare one PAC
provider type with another for purposes
such as care coordination and quality
improvement.
To achieve a level of standardization
across HHAs, LTCHs, IRFs, and SNFs
that enables us to make comparisons
between them, we are proposing to
define ‘‘standardized patient assessment
data’’ as patient or resident assessment
questions and response options that are
identical in all four PAC assessment
instruments, and to which identical
standards and definitions apply.
Standardizing the questions and
response options across the four PAC
assessment instruments is an essential
step in making that data interoperable,
allowing it to be shared electronically,
or otherwise, between PAC provider
types. It will enable the data to be
comparable for various purposes,
including the development of crosssetting quality measures and to inform
payment models that take into account
patient characteristics rather than
setting, as described in the IMPACT Act.
We are inviting public comment on
this proposed definition.
2. General Considerations Used for the
Selection of Proposed Standardized
Patient Assessment Data
As part of our effort to identify
appropriate standardized patient
assessment data for purposes of
collecting under the HH QRP, we sought
input from the general public,
stakeholder community, and subject
matter experts on items that would
enable person-centered, high quality
health care, as well as access to
longitudinal information to facilitate
coordinated care and improved
beneficiary outcomes.
To identify optimal data elements for
standardization, our data element
contractor organized teams of
researchers for each category, with each
team working with a group of advisors
made up of clinicians and academic
researchers with expertise in PAC.
Information-gathering activities were
used to identify data elements, as well
as key themes related to the categories
described in section 1899B(b)(1)(B) of
the Act. In January and February 2016,
our data element contractor also
conducted provider focus groups for
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each of the four PAC provider types,
and a focus group for consumers that
included current or former PAC patients
and residents, caregivers, ombudsmen,
and patient advocacy group
representatives. The Development and
Maintenance of Post-Acute Care CrossSetting Standardized Patient
Assessment Data Focus Group Summary
Report is available at https://
www.cms.gov/Medicare/QualityInitiatives-Patient-AssessmentInstruments/Post-Acute-Care-QualityInitiatives/IMPACT-Act-of-2014/
IMPACT-Act-Downloads-andVideos.html.
Our data element contractor also
assembled a 16-member TEP that met on
April 7 and 8, 2016, and January 5 and
6, 2017, in Baltimore, Maryland, to
provide expert input on data elements
that are currently in each PAC
assessment instrument, as well as data
elements that could be standardized.
The Development and Maintenance of
Post-Acute Care Cross-Setting
Standardized Patient Assessment Data
TEP Summary Reports are available at
https://www.cms.gov/Medicare/QualityInitiatives-Patient-AssessmentInstruments/Post-Acute-Care-QualityInitiatives/IMPACT-Act-of-2014/
IMPACT-Act-Downloads-andVideos.html.
As part of the environmental scan,
data elements currently in the four
existing PAC assessment instruments
were examined to see if any could be
considered for proposal as standardized
patient assessment data. Specifically,
this evaluation included consideration
of data elements in OASIS–C2 (effective
January 2017); IRF–PAI, v1.4 (effective
October 2016); LCDS, v3.00 (effective
April 2016); and MDS 3.0, v1.14
(effective October 2016). Data elements
in the standardized assessment
instrument that we tested in the PostAcute Care Payment Reform
Demonstration (PAC PRD)—the
Continuity Assessment Record and
public reporting Evaluation (CARE)—
were also considered. A literature
search was also conducted to determine
whether additional data elements to
propose as standardized patient
assessment data could be identified.
Additionally, we held four Special
Open Door Forums (SODFs) on October
27, 2015; May 12, 2016; September 15,
2016; and December 8, 2016, to present
data elements we were considering and
to solicit input. At each SODF, some
stakeholders provided immediate input,
and all were invited to submit
additional comments via the CMS
IMPACT Mailbox:
PACQualityInitiative@cms.hhs.gov.
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We also convened a meeting with
federal agency subject matter experts
(SMEs) on May 13, 2016. In addition, a
public comment period was open from
August 12 to September 12, 2016 to
solicit comments on detailed candidate
data element descriptions, data
collection methods, and coding
methods. The IMPACT Act Public
Comment Summary Report containing
the public comments (summarized and
verbatim) and our responses is available
at https://www.cms.gov/Medicare/
Quality-Initiatives-Patient-AssessmentInstruments/Post-Acute-Care-QualityInitiatives/IMPACT-Act-of-2014/
IMPACT-Act-Downloads-andVideos.html.
We specifically sought to identify
standardized patient assessment data
that we could feasibly incorporate into
the LTCH, IRF, SNF, and HHA
assessment instruments and that have
the following attributes: (1) Being
supported by current science; (2) testing
well in terms of their reliability and
validity, consistent with findings from
the Post-Acute Care Payment Reform
Demonstration (PAC PRD); (3) the
potential to be shared (for example,
through interoperable means) among
PAC and other provider types to
facilitate efficient care coordination and
improved beneficiary outcomes; (4) the
potential to inform the development of
quality, resource use and other
measures, as well as future payment
methodologies that could more directly
take into account individual beneficiary
health characteristics; and (5) the ability
to be used by practitioners to inform
their clinical decision and care planning
activities. We also applied the same
considerations that we apply with
quality measures, including the CMS
Quality Strategy which is framed using
the three broad aims of the National
Quality Strategy.
3. Policy for Retaining HH QRP
Measures and Proposal To Apply That
Policy to Standardized Patient
Assessment Data
In the CY 2017 HH PPS final rule (81
FR 76702), we adopted a policy that
would allow for any quality measure
adopted for use in the HH QRP to
remain in effect until the measure is
removed, suspended, or replaced. For
further information on how measures
are considered for removal, suspension
or replacement, we refer readers to the
CY 2017 HH PPS final rule (81 FR
76702). We propose to apply this same
policy to the standardized patient
assessment data that we adopt for the
HH QRP.
We are inviting public comment on
our proposal.
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4. Policy for Adopting Changes to HH
QRP Measures and Proposal To Apply
That Policy to Standardized Patient
Assessment Data
In the CY 2017 HH PPS final rule (81
FR 76702), we adopted a subregulatory
process to incorporate updates to HH
quality measure specifications that do
not substantively change the nature of
the measure. Substantive changes will
be proposed and finalized through
rulemaking. For further information on
what constitutes a substantive versus a
nonsubstantive change and the
subregulatory process for
nonsubstantive changes, we refer
readers to the CY 2017 HH PPS final
rule (81 FR 76702). We propose to apply
this policy to the standardized patient
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assessment data that we adopt for HH
QRP.
We are inviting public comment on
our proposal.
5. Quality Measures Previously
Finalized for the HH QRP
The HH QRP currently has 23
measures, as outlined in Table 47.
TABLE 47—MEASURES CURRENTLY ADOPTED FOR THE HH QRP
Short name
Measure name & data source
OASIS-based
Pressure Ulcers ....................
DRR ......................................
Ambulation ...........................
Bathing .................................
Dyspnea ...............................
Oral Medications ..................
Pain ......................................
Surgical Wounds ..................
Bed Transferring ..................
Timely Care ..........................
Depression Assessment ......
Influenza ...............................
PPV ......................................
Falls Risk ..............................
Diabetic Foot Care ...............
Drug Education ....................
Percent of Patients or Residents with Pressure Ulcers that are New or Worsened (NQF #0678).* +
Drug Regimen Review Conducted with Follow-Up for Identified Issues-Post Acute Care (PAC) Home Health
Quality Reporting Program.+
Improvement in Ambulation/Locomotion (NQF #0167).
Improvement in Bathing (NQF #0174).
Improvement in Dyspnea.
Improvement in Management of Oral Medication (NQF #0176).
Improvement in Pain Interfering with Activity (NQF #0177).
Improvement in Status of Surgical Wounds (NQF #0178).
Improvement in Bed Transferring (NQF #0175).
Timely Initiation Of Care (NQF #0526).
Depression Assessment Conducted.
Influenza Immunization Received for Current Flu Season (NQF #0522).
Pneumococcal Polysaccharide Vaccine Ever Received (NQF #0525).
Multifactor Fall Risk Assessment Conducted For All Patients Who Can Ambulate (NQF #0537).
Diabetic Foot Care and Patient/Caregiver Education Implemented during All Episodes of Care (NQF #0519).
Drug Education on All Medications Provided to Patient/Caregiver during All Episodes of Care.
Claims-based
MSPB ...................................
DTC ......................................
PPR ......................................
ACH ......................................
ED Use .................................
Rehospitalization ..................
ED Use without Readmission
Total Estimated Medicare Spending Per Beneficiary (MSPB)—Post Acute Care (PAC) Home Health (HH) Quality
Reporting Program (QRP).+
Discharge to Community-Post Acute Care (PAC) Home Health (HH) Quality Reporting Program (QRP).+
Potentially Preventable 30-Day Post-Discharge Readmission Measure for Home Health Quality Reporting Program.+
Acute Care Hospitalization During the First 60 Days of Home Health (NQF #0171).
Emergency Department Use without Hospitalization During the First 60 Days of Home Health (NQF #0173).
Rehospitalization During the First 30 Days of Home Health (NQF #2380).
Emergency Department Use without Hospital Readmission During the First 30 Days of Home Health (NQF
#2505).
HHCAHPs-based
Professional Care .................
Communication ....................
Team Discussion ..................
Overall Rating ......................
Willing to Recommend .........
How often the home health team gave care in a professional way.
How well did the home health team communicate with patients.
Did the home health team discuss medicines, pain, and home safety with patients.
How do patients rate the overall care from the home health agency.
Would patients recommend the home health agency to friends and family.
* Not currently NQF-endorsed for the HH Setting.
+ The data collection period will begin with CY 2017 Q1&2 reporting for CY 2018 APU determination, followed by the previously established HH
QRP use of 12 months (July 1, 2017–June 30, 2018) of CY 2017 reporting for CY 2019 APU determination. Subsequent years will be based on
the HH July 1–June 30 timeframe for APU purposes. For claims data, the performance period will use rolling CY claims for subsequent reporting
purposes.
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F. HH QRP Quality Measures Proposed
Beginning With the CY 2020 HH QRP
Beginning with the CY 2020 HH QRP,
in addition to the quality measures we
are retaining under our policy described
in section V.B. of the preamble of this
proposed rule, we are proposing to
replace the current pressure ulcer
measure entitled Percent of Residents or
Patients with Pressure Ulcers That Are
New or Worsened (Short Stay) (NQF
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#0678) with a modified version of the
measure and to adopt one measure on
patient falls and one measure on
assessment of patient functional status.
We are also proposing to characterize
the data elements described below, as
standardized patient assessment data
under section 1899B(b)(1)(B) of the Act
that must be reported by HHAs under
the HH QRP through the OASIS, under
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section 1895(b)(3)(B)(v) of the Act. The
proposed measures are as follows:
• Changes in Skin Integrity PostAcute Care: Pressure Ulcer/Injury.
• Application of Percent of Residents
Experiencing One or More Falls with
Major Injury (NQF #0674).
• Application of Percent of LongTerm Care Hospital Patients with an
Admission and Discharge Functional
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Assessment and a Care Plan That
Addresses Function (NQF #2631).
The measures are described in more
detail below.
1. Proposal To Replace the Current
Pressure Ulcer Quality Measure,
Entitled Percent of Residents or Patients
With Pressure Ulcers That Are New or
Worsened (Short Stay) (NQF #0678),
With a Modified Pressure Ulcer
Measure, Entitled Changes in Skin
Integrity Post-Acute Care: Pressure
Ulcer/Injury
a. Measure Background
In this rule, we are proposing to
remove the current pressure ulcer
measure, Percent of Residents or
Patients with Pressure Ulcers That Are
New or Worsened (Short Stay) (NQF
#0678), from the HH QRP measure set
and to replace it with a modified
version of that measure, Changes in
Skin Integrity Post-Acute Care: Pressure
Ulcer/Injury, beginning with the CY
2020 HH QRP. The change in the
measure name is to reduce confusion
about the new modified measure. The
modified version differs from the
current version of the measure because
it includes new or worsened
unstageable pressure ulcers, including
deep tissue injuries (DTIs), in the
measure numerator. The proposed
modified version of the measure also
contains updated specifications
intended to eliminate redundancies in
the assessment items needed for its
calculation and to reduce the potential
for underestimating the frequency of
pressure ulcers. The modified version of
the measure would satisfy the IMPACT
Act domain of ‘‘Skin integrity and
changes in skin integrity.’’
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b. Measure Importance
As described in the CY 2016 HH PPS
final rule (80 FR 68697), pressure ulcers
are high-cost adverse events and are an
important measure of quality. For
information on the history and rationale
for the relevance, importance, and
applicability of having a pressure ulcer
measure in the HH QRP, we refer
readers to the CY 2016 HH PPS final
rule (80 FR 68623).
We are proposing to adopt a modified
version of the current pressure ulcer
measure because unstageable pressure
ulcers, including DTIs, are similar to
Stage 2, Stage 3, and Stage 4 pressure
ulcers in that they represent poor
outcomes, are a serious medical
condition that can result in death and
disability, are debilitating and painful
and are often an avoidable outcome of
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medical care.115 116 117 118 119 120 Studies
show that most pressure ulcers can be
avoided and can also be healed in acute,
post-acute, and long term care settings
with appropriate medical care.121
Furthermore, some studies indicate that
DTIs, if managed using appropriate care,
can be resolved without deteriorating
into a worsened pressure ulcer.122 123
While there are few studies that
provide information regarding the
incidence of unstageable pressure ulcers
in PAC settings, an analysis conducted
by our measure development contractor
indicated that adding unstageable
pressure ulcers to the quality measure
numerator would result in a higher
percentage of patients with new or
worsened pressure ulcers in HHA
settings and increase the variability of
measure scores. A higher percentage
indicates lower quality. This increased
variability serves to improve the
measure by improving the ability of the
measure to distinguish between high
and low quality home health agencies.
Given the low prevalence of pressure
ulcers in the home health setting, the
addition of unstageable ulcers to this
measure should enhance variability.
Analysis of 2015 OASIS data found that
in approximately 1.2 percent, or more
than 70,000 episodes, the patient had an
unstageable ulcer upon admission.
Patients in more than 13,000 episodes
were discharged with an unstageable
ulcer. In addition, unstageable ulcers
115 Casey, G. (2013). ‘‘Pressure ulcers reflect
quality of nursing care.’’ Nurs N Z 19(10): 20–24.
116 Gorzoni, M.L. and S.L. Pires (2011). ‘‘Deaths
in nursing homes.’’ Rev Assoc Med Bras 57(3): 327–
331.
117 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.
118 White-Chu, E.F., et al. (2011). ‘‘Pressure ulcers
in long-term care.’’ Clin Geriatr Med 27(2): 241–258.
119 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.
120 Bennet, G, Dealy, C, Posnett, J (2004). The cost
of pressure ulcers in the UK, Age and Aging,
33(3):230–235.
121 Black, Joyce M., et al. ‘‘Pressure ulcers:
avoidable or unavoidable? Results of the national
pressure ulcer advisory panel consensus
conference.’’ Ostomy-Wound Management 57.2
(2011): 24.
122 Sullivan, R. (2013). A Two-year Retrospective
Review of Suspected Deep Tissue Injury Evolution
in Adult Acute Care Patients. Ostomy Wound
Management 59(9) https://www.o-wm.com/article/
two-year-retrospective-review-suspected-deeptissue-injury-evolution-adult-acute-care-patien.
123 Posthauer, ME, Zulkowski, K. (2005). Special
to OWM: The NPUAP Dual Mission Conference:
Reaching Consensus on Staging and Deep Tissue
Injury. Ostomy Wound Management 51(4) https://
www.o-wm.com/content/the-npuap-dual-missionconference-reaching-consensus-staging-and-deeptissue-injury.
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due to slough/eschar worsened between
admission and discharge in
approximately 5,000 episodes of care. In
conclusion, the inclusion of unstageable
pressure ulcers, including DTIs, in the
numerator of this measure is expected to
increase measure scores and variability
in measure scores, thereby improving
the ability to discriminate among poorand high-performing HHAs.
Testing shows similar results in other
PAC settings. For example, in SNFs,
using data from Quarter 4 2015 through
Quarter 3 2016, the mean score on the
currently implemented pressure ulcer
measure is 1.75 percent, compared with
2.58 percent in the proposed measure.
In the proposed measure, the SNF mean
score is 2.58 percent; the 25th and 75th
percentiles are 0.65 percent and 3.70
percent, respectively; and 20.32 percent
of facilities have perfect scores. In
LTCHs, using data from Quarter 1
through Quarter 4 2015, the mean score
on the currently implemented pressure
ulcer measure is 1.95 percent, compared
with 3.73 percent in the proposed
measure. In the proposed measure, the
LTCH mean score is 3.73 percent; the
25th and 75th percentiles are 1.53
percent and 4.89 percent, respectively;
and 5.46 percent of facilities have
perfect scores. In IRFs, using data from
Quarter 4 2016, the mean score on the
currently implemented pressure ulcer
measure is 0.64 percent, compared with
1.46 percent in the proposed measure.
In the proposed measure, the IRF mean
score is 1.46 percent and the 25th and
75th percentiles are 0 percent and 2.27
percent, respectively. The inclusion of
unstageable pressure ulcers, including
DTIs, in the numerator of this measure
is expected to increase measure scores
and variability in measure scores,
thereby improving the ability to
distinguish between poor and high
performing HHAs.
This increased variability of scores
across quarters and deciles may improve
the ability of the measure to distinguish
between high and low performing
providers across PAC settings.
c. Stakeholder Feedback
Our measure development contractor
sought input from subject matter
experts, including Technical Expert
Panels (TEPs), over the course of several
years on various skin integrity topics
and specifically those associated with
the inclusion of unstageable pressure
ulcers including DTIs. Most recently, on
July 18, 2016, a TEP convened by our
measure development contractor
provided input on the technical
specifications of this proposed quality
measure, including the feasibility of
implementing the proposed measure’s
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updates across PAC settings. The TEP
supported the use of the proposed
measure across PAC settings, including
the use of different data elements for
measure calculation. The TEP supported
the updates to the measure across PAC
settings, including the inclusion in the
numerator of unstageable pressure
ulcers due to slough and/or eschar that
are new or worsened, new unstageable
pressure ulcers due to a non-removable
dressing or device, and new DTIs. The
TEP recommended supplying additional
guidance to providers regarding each
type of unstageable pressure ulcer. This
support was in agreement with earlier
TEP meetings, held on June 13, and
November 15, 2013, which had
recommended that CMS update the
specifications for the pressure ulcer
measure to include unstageable pressure
ulcers in the numerator.124 125
Exploratory data analysis conducted by
our measure development contractor
suggests that the addition of unstageable
pressure ulcers, including DTIs, will
increase the observed incidence of new
or worsened pressure ulcers at the
facility level and may improve the
ability of the proposed quality measure
to discriminate between poor- and highperforming agencies.
We solicited stakeholder feedback on
this proposed measure by means of a
public comment period held from
October 17, through November 17, 2016.
In general, we received considerable
support for the proposed measure. A
few commenters supported all of the
changes to the current pressure ulcer
measure that resulted in the proposed
measure, with one commenter noting
the significance of the work to align the
pressure ulcer quality measure
specifications across the PAC settings.
Many commenters supported the
inclusion of unstageable pressure ulcers
due to slough/eschar, due to nonremovable dressing/device, and DTIs in
124 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.
125 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.
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the proposed quality measure. Other
commenters did not support the
inclusion of DTIs in the proposed
quality measure because they stated that
there is no universally accepted
definition for this type of skin injury.
Some commenters provided feedback
on the data elements used to calculate
the proposed quality measure. We
believe that these data elements will
promote facilitation of cross-setting
quality comparison as mandated by the
IMPACT Act, alignment between quality
measures and payment, reduction in
redundancies in assessment items, and
prevention of inappropriate
underestimation of pressure ulcers. The
currently implemented pressure ulcer
measure is calculated using
retrospective data elements that assess
the number of new or worsened
pressure ulcers at each stage, while the
proposed measure is calculated using
data elements that assess the current
number of unhealed pressure ulcers at
each stage, and the number of these that
were present upon admission, which are
subtracted from the current number at
that stage. Some commenters did not
support the data elements that would be
used to calculate the proposed measure,
and requested further testing of these
data elements. Other commenters
supported the use of these data elements
stating that these data elements
simplified the measure calculation
process.
The public comment summary report
for the proposed measure is available on
the CMS Web site at https://
www.cms.gov/Medicare/QualityInitiatives-Patient-AssessmentInstruments/Post-Acute-Care-QualityInitiatives/IMPACT-Act-of-2014/
IMPACT-Act-Downloads-andVideos.html.
The NQF-convened Measures
Application Partnership (MAP) PostAcute Care/Long-Term Care (PAC/LTC)
Workgroup met on December 14 and 15,
2016, and provided input to us about
this proposed measure. The MAP
provided a recommendation of ‘‘support
for rulemaking’’ for use of the proposed
measure in the HH QRP. The MAP
Coordinating Committee met on January
24 and 25, 2017, and provided a
recommendation of ‘‘conditional
support for rulemaking’’ for use of the
proposed measure in the HH QRP. The
MAP’s conditions of support include
that, as a part of measure
implementation, we provide guidance
on the correct collection and calculation
of the measure result, as well as
guidance on public reporting Web sites
explaining the impact of the
specification changes on the measure
result. The MAP’s conditions also
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specify that CMS continue analyzing the
proposed measure to investigate
unexpected results reported in public
comment. We intend to fulfill these
conditions by offering additional
training opportunities and educational
materials in advance of public reporting,
and by continuing to monitor and
analyze the proposed measure. We
provide private provider feedback
reports as well as a Quarterly Quality
Measure report that allow HHAs to track
their measure outcomes for QI purposes.
Aside from those reports, we conduct
internal monitoring and evaluation of
our measures to ensure that the
measures are performing as they were
intended to perform during the
development of the measure. More
information about the MAP’s
recommendations for this measure is
available at https://www.quality
forum.org/WorkArea/linkit.aspx?
LinkIdentifier=id&ItemID=84452.
We reviewed the NQF’s consensus
endorsed measures and were unable to
identify any home health measures that
address changes in skin integrity related
to pressure ulcers. Therefore, based on
the evidence previously discussed, we
are proposing to adopt the quality
measure entitled, Changes in Skin
Integrity Post-Acute Care: Pressure
Ulcer/Injury, for the HH QRP beginning
with the CY 2020 HH QRP. We plan to
submit the proposed measure to the
NQF for endorsement consideration as
soon as feasible.
d. Data Collection
The data for this quality measure
would be collected using the OASIS
data set, which is currently submitted
by HHAs through the Quality
Improvement and Evaluation System
(QIES) Assessment Submission and
Processing (ASAP) System. The
required items applicable to this
measure are already reported by HHAs
for patients and episodes of care
meeting statutorily-defined criteria.
While the inclusion of unstageable
wounds in the proposed measure results
in a measure calculation methodology
that is different from the methodology
used to calculate the current pressure
ulcer measure, the data elements needed
to calculate the proposed measure are
already included on the OASIS data set.
In addition, our proposal to eliminate
duplicative data elements that were
used in calculation of the current
pressure ulcer measure will result in an
overall reduced reporting burden for
HHAs for the proposed measure. For
more information on OASIS data set
submission using the QIES ASAP
System, we refer readers to https://
www.qtso.com/.
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For technical information about this
proposed measure, including
information about the measure
calculation and the standardized patient
assessment data elements used to
calculate this measure, we refer readers
to the document titled, Proposed
Measure Specifications and
Standardized Data Elements for CY
2018 HH QRP Notice of Proposed
Rulemaking, available at https://
www.cms.gov/Medicare/QualityInitiatives-Patient-AssessmentInstruments/HomeHealthQualityInits/
HHQIQualityMeasures.html.
We are proposing that HHAs would
begin reporting the proposed pressure
ulcer measure, Changes in Skin Integrity
Post-Acute Care: Pressure Ulcer/Injury,
which will replace the current pressure
ulcer measure, with data collection
beginning with respect to admissions
and discharges occurring on or after
January 1, 2019.
We are inviting public comment on
our proposal to remove the current
pressure ulcer measure, Percent of
Residents or Patients with Pressure
Ulcers That Are New or Worsened
(Short Stay) (NQF #0678), and replace it
with a modified version of that measure,
entitled, Changes in Skin Integrity PostAcute Care: Pressure Ulcer/Injury,
beginning with the CY 2020 HH QRP.
2. Proposal To Address the IMPACT Act
Domain of Functional Status, Cognitive
Function, and Changes in Function and
Cognitive Function: Application of
Percent of Long-Term Care Hospital
Patients With an Admission and
Discharge Functional Assessment and a
Care Plan That Addresses Function
(NQF #2631)
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a. Measure Background
Sections 1899B(d)(1)(B) of the Act
requires that no later than the specified
application date (which under section
1899B(a)(1)(E)(ii) is January 1, 2019 for
HHAs, and October 1, 2016 for SNFs,
IRFs and LTCHs), the Secretary specify
a quality measure to address the domain
of ‘‘Functional status, cognitive
function, and changes in function and
cognitive function.’’ We propose to
adopt the measure, Application of
Percent of Long-Term Care Hospital
Patients with an Admission and
Discharge Functional Assessment and a
Care Plan That Addresses Function
(NQF #2631) for the HH QRP, beginning
with the CY 2020 program year. This is
a process measure that reports the
percentage of patients with an
admission and discharge functional
assessment and treatment goal that
addresses function. The treatment goal
provides evidence that a care plan with
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a goal has been established for the HH
patient.
The National Committee on Vital and
Health Statistics’ Subcommittee on
Health,126 noted that ‘‘information on
functional status is becoming
increasingly essential for fostering
healthy people and a healthy
population. Achieving optimal health
and well-being for Americans requires
an understanding across the life span of
the effects of people’s health conditions
on their ability to do basic activities and
participate in life situations in other
words, their functional status.’’ This is
supported by research showing that
patient and resident functioning is
associated with important outcomes
such as discharge destination and length
of stay in inpatient settings,127 as well
as the risk of nursing home placement
and hospitalization of older adults
living in the community.128 For
example, many patients who utilize HH
services may be at risk for a decline in
function due to limited mobility and
ambulation.129 Thus, impairment in
function activities such as self-care and
mobility is highly prevalent in HH
patients. For example, in 98 percent of
the over six million HH episodes in
2015, the patient had at least one
limitation or was not completely
independent in self-care activities such
as grooming, upper and lower body
dressing, bathing, toilet hygiene, and/or
feeding/eating.130
The primary goal of home health care
is to provide restorative care when
improvement is expected, maintain
function and health status if
improvement is not expected, slow the
rate of functional decline to avoid
institutionalization in an acute or postacute setting, and/or facilitate transition
to end-of-life care as appropriate.131 132
126 Subcommittee on Health National Committee
on Vital and Health Statistics, ‘‘Classifying and
Reporting Functional Status’’ (2001).
127 Reistetter TA, Graham JE, Granger CV, Deutsch
A, Ottenbacher KJ. Utility of Functional Status for
Classifying Community Versus Institutional
Discharges after Inpatient Rehabilitation for Stroke.
Archives of Physical Medicine and Rehabilitation,
2010; 91:345–350.
128 Miller EA, Weissert WG. Predicting Elderly
People’s Risk for Nursing Home Placement,
Hospitalization, Functional Impairment, and
Mortality: A Synthesis. Medical Care Research and
Review, 57; 3: 259–297.
129 Kortebein, P., Ferrando, A., Lombebeida, J.,
Wolfe, R., & Evans, W.J. (2007). Effect of 10 days
of bed rest on skeletal muscle in health adults.
JAMA; 297(16):1772–4.
130 Kortebein, P., Ferrando, A., Lombebeida, J.,
Wolfe, R., & Evans, W.J. (2007). Effect of 10 days
of bed rest on skeletal muscle in health adults.
JAMA; 297(16):1772–4.
131 Riggs, J. S. & Madigan, E. A. (2012). Describing
variation in home health care episodes for patients
with heart failure. Home Health Care Management
and Practice, 24(3): 146–152.
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Home health care can positively impact
functional outcomes. In stroke patients,
home-based rehabilitation programs
administered by home health clinicians
significantly improved ADL function
and gait performance.133 Home health
services, delivered by a registered nurse,
positively impacted patient Quality of
Life (QOL) and clinical outcomes,
including significant improvement in
dressing lower body, bathing, meal
preparation, shopping, and
housekeeping. For some home health
patients, achieving independence
within the living environment and
improved community mobility might be
the goal of care. For others, the goal of
care might be to slow the rate of
functional decline to avoid
institutionalization.134
Patients’ functional status is
associated with important patient
outcomes, so measuring and monitoring
the patients’ extent of engaging in selfcare and mobility is valuable.
Functional decline among the
elderly;135 and chronic illness
comorbidities, such as chronic pain
among the older adult population 136 137
are associated with decreases in selfsufficiency and patient activation
(defined as the patient’s knowledge and
confidence in self-managing their
health). Impaired mobility, frailty, and
low physical activity are associated with
institutionalization,138 higher risk of
132 Ellenbecker, C.H., Samia, L., Cushman, M.J., &
Alster, K (2008). Patient safety and quality: an
evidence-based handbook for nurses. Rockville
(MD): agency for healthcare research and quality
(US); 2008 Apr. Chapter 13.
133 Asiri, F. Y., Marchetti, G. F., Ellis, J. L., Otis,
L., Sparto, P. J., Watzlaf, V., & Whitney, S. L. (2014).
Predictors of functional and gait outcomes for
persons poststroke undergoing home-based
rehabilitation. Journal of Stroke and
Cerebrovascular Diseases: The Official Journal of
National Stroke Association, 23(7), 1856–1864.
https://doi.org/10.1016/j.jstrokecerebrovasdis.
2014.02.025.
134 Ellenbecker, C.H., Samia, L., Cushman, M.J., &
Alster, K (2008). Patient safety and quality: an
evidence-based handbook for nurses. Rockville
(MD): agency for healthcare research and quality
(US); 2008 Apr. Chapter 13.
135 Gleason, K. T., Tanner, E. K., Boyd, C. M.,
Saczynski, J. S., & Szanton, S. L. (2016). Factors
associated with patient activation in an older adult
population with functional difficulties. Patient
Education and Counseling, 99(8), 1421–1426.
https://doi.org/10.1016/j.pec.2016.03.011.
136 Roberts AR, Betts Adams K, Beckette & Warner
C. (2016). Effects of chronic illness on daily life and
barriers to self-care for older women: a mixedmethods exploration. J Women Aging, Jul 25:1–11.
137 Wu, J.-R., Lennie, T. A., & Moser, D. K. (2016).
A prospective, observational study to explore health
disparities in patients with heart failure-ethnicity
and financial status. European Journal of
Cardiovascular Nursing: Journal of the Working
Group on Cardiovascular Nursing of the European
Society of Cardiology. https://doi.org/10.1177/
1474515116641296.
138 Hajek, A., Brettschneider, C., Lange, C.,
Posselt, T., Wiese, B., Steinmann, S., Weyerer, S.,
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falls and falls-related hip fracture and
death,139 140 greater risk of
undernutrition,141 higher rates of
inpatient admission from the emergency
department,142 and higher prevalence of
hypertension and diabetes.143
In addition, the assessment of
functional ability and provision of
treatment plans directed toward
improving or maintaining functional
ability could impact health care costs.
Providing comprehensive home health
care, which includes improving or
maintaining functional ability for frail
elderly adults, can reduce the likelihood
of hospital readmissions or emergency
department visits, leading to reduced
health care service
expenditures.144 145 146 Reducing
preventable rehospitalizations, which
made up approximately 17 percent of
Medicare’s $102.6 billion in 2004
Werle, J., Pentzek, M., Fuchs, A., Stein, J., Luck, T.,
¨
Bickel, H., Mosch, E., Wagner, M., Jessen, F., Maier,
¨
W., Scherer, M., Riedel-Heller, S.G., Konig, H.H., &
AgeCoDe Study Group. (2015). Longitudinal
Predictors of Institutionalization in Old Age. PLoS
One, 10(12):e0144203.
139 Akahane, M., Maeyashiki, A., Yoshihara, S.,
Tanaka, Y., & Imamura, T. (2016). Relationship
between difficulties in daily activities and falling:
loco-check as a self-assessment of fall risk.
Interactive Journal of Medical Research, 5(2), e20.
https://doi.org/10.2196/ijmr.5590.
140 Zaslavsky, O., Zelber-Sagi, S., Gray, S. L.,
LaCroix, A. Z., Brunner, R. L., Wallace, R. B., . . .
Woods, N. F. (2016). Comparison of Frailty
Phenotypes for Prediction of Mortality, Incident
Falls, and Hip Fracture in Older Women. Journal of
the American Geriatrics Society, 64(9), 1858-–1862.
https://doi.org/10.1111/jgs.14233.
141 van der Pols-Vijlbrief, R., Wijnhoven, H. A. H.,
Bosmans, J. E., Twisk, J. W. R., & Visser, M. (2016).
Targeting the underlying causes of undernutrition.
Cost-effectiveness of a multifactorial personalized
intervention in community-dwelling older adults: A
randomized controlled trial. Clinical Nutrition
(Edinburgh, Scotland). https://doi.org/10.1016/
j.clnu.2016.09.030.
142 Hominick, K., McLeod, V., & Rockwood, K.
(2016). Characteristics of older adults admitted to
hospital versus those discharged home, in
emergency department patients referred to internal
medicine. Canadian Geriatrics Journal: CGJ, 19(1),
9–14. https://doi.org/10.5770/cgj.19.195.
143 Halaweh, H., Willen, C., Grimby-Ekman, A., &
Svantesson, U. (2015). Physical activity and healthrelated quality of life among community dwelling
elderly. J Clin Med Res, 7(11), 845–52.
144 Hirth, V., Baskins, J., & Dever-Bumba, M.
(2009). Program of all-inclusive care (PACE): Past,
present, and future. Journal of the American
Medical Directors Association, 10, 155–160.
145 Mukamel, D. B., Fortinsky, R. H., White, A.,
Harrington, C., White, L. M., & Ngo-Metzger, Q.
(2014). The policy implications of the cost structure
of home health agencies. Medicare & Medicaid
Research Review, 4(1). https://doi.org/10.5600/
mmrr2014-004-01-a03.
146 Meunier, M. J., Brant, J. M., Audet, S.,
Dickerson, D., Gransbery, K., & Ciemins, E. L.
(2016). Life after PACE (Program of All-Inclusive
Care for the Elderly): A retrospective/prospective,
qualitative analysis of the impact of closing a nurse
practitioner centered PACE site. Journal of the
American Association of Nurse Practitioners.
https://doi.org/10.1002/2327-6924.12379.
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hospital payments, creates the potential
for large health care cost savings.147 148
Further, improving and maintaining
functional ability in individuals with
high needs, defined as those with three
or more chronic conditions, may also
account for an increase in healthcare
savings. Adults with three or more
chronic conditions have nearly four
times the average annual per-person
spending for health care services and
prescription medications than the
average for all U.S. adults, and high
needs adults with limitations in their
ability to perform ADLs, have even
higher average annual health care
expenditures.149 High needs individuals
with functional limitations spend, on
average, $21,021 on annual health care
services, whereas the average annual
health care expenditures for all U.S.
adults are approximately $4,845.45
b. Measure Importance
The majority of individuals who
receive PAC services, including care
provided by HHAs, SNFs, IRFs, and
LTCHs, have functional limitations, and
many of these individuals are at risk for
further decline in function due to
limited mobility and ambulation.150 The
patient populations treated by HHAs,
SNFs, IRFs, and LTCHs vary in terms of
their functional abilities. For example,
for home health patients, achieving
independence within the home
environment and promoting community
mobility may be the goal of care. For
other home health patients, the goal of
care may be to slow the rate of
functional decline in order to allow the
person to remain at home and avoid
institutionalization.151 The clinical
practice guideline Assessment of
Physical Function 152 recommends that
147 Jencks, S.F., Williams, M.V., and Coleman,
E.A. (2009). Rehospitalizations among patients in
the Medicare fee-for-service program. New England
Journal of Medicine; 360(14):1418–28.
148 Tao, H., Ellenbecker, C. H., Chen, J., Zhan, L.,
& Dalton, J. (2012). The influence of social
environmental factors on rehospitalization among
patients receiving home health care services. ANS.
Advances in Nursing Science, 35(4), 346–358.
https://doi.org/10.1097/ANS.0b013e318271d2ad.
149 Hayes, S.L., Salzberg, C.A., McCarthy, D.,
Radley, DC, Abrams, M.K., Shah, T., and Anderson,
G.F. (2016). High-Need, High-Cost Patients: Who are
they and how do they use health care—A
population-based comparison of demographics,
health care use, and expenditures. The
Commonwealth Fund.
150 Kortebein P, Ferrando A, Lombebeida J, Wolfe
R, Evans WJ. Effect of 10 days of bed rest on skeletal
muscle in health adults. JAMA; 297(16):1772–4.
151 Ellenbecker CH, Samia L, Cushman MJ, Alster
K. Patient safety and quality in home health care.
Patient Safety and Quality: An Evidence-Based
Handbook for Nurses. Vol 1.
152 Kresevic DM. Assessment of physical
function. In: Boltz M, Capezuti E, Fulmer T,
Zwicker D, editor(s). Evidence-based geriatric
nursing protocols for best practice. 4th ed. New
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clinicians document functional status at
baseline and over time to validate
capacity, decline, or progress. Therefore,
assessment of functional status at
admission and discharge, as well as
establishing a functional goal for
discharge as part of the care plan is an
important aspect of patient or resident
care across PAC settings.
Currently, functional assessment data
are collected by all four PAC providers,
yet data collection has employed
different assessment instruments, scales,
and item definitions. The data cover
similar topics, but are not standardized
across PAC settings. The different sets of
functional assessment items coupled
with different rating scales makes
communication about patient and
resident functioning challenging when
patients and residents transition from
one type of setting to another. Collection
of standardized functional assessment
data across HHAs, SNFs, IRFs, and
LTCHs using common data items would
establish a common language for patient
and resident functioning, which may
facilitate communication and care
coordination as patients and residents
transition from one type of provider to
another. The collection of standardized
functional status data may also help
improve patient functioning during an
episode of care by ensuring that basic
daily activities are assessed for all PAC
residents at the start and end of care,
and that at least one functional goal is
established.
The functional assessment items
included in the proposed functional
status quality measure were originally
developed and tested as part of the PostAcute Care Payment Reform
Demonstration version of the Continuity
Assessment Record and Evaluation
(CARE) Item Set, which was designed to
standardize the assessment of a person’s
status, including functional status,
across acute and post-acute settings
(HHAs, SNFs, IRFs, and LTCHs). The
functional status items on the CARE
Item Set are daily activities that
clinicians typically assess at the time of
admission and/or discharge to
determine patient or resident needs,
evaluate patient or resident progress,
and prepare patients, residents, and
their families for a transition to home or
to another setting. The development of
the CARE Item Set and a description
and rationale for each item is described
in a report entitled ‘‘The Development
and Testing of the Continuity
Assessment Record and Evaluation
(CARE) Item Set: Final Report on the
Development of the CARE Item Set:
York (NY): Springer Publishing Company; 2012. p.
89–103.
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Volume 1 of 3.’’ 153 Reliability and
validity testing were conducted as part
of CMS’s Post-Acute Care Payment
Reform Demonstration (PAC–PRD), and
we concluded that the functional status
items have acceptable reliability and
validity. Testing for the functional
assessment items concluded that the
items were able to evaluate all patients
on basic self-care and mobility
activities, regardless of functional level
or PAC setting. A description of the
testing methodology and results are
available in several reports, including
the report entitled ‘‘The Development
and Testing of the Continuity
Assessment Record And Evaluation
(CARE) Item Set: Final Report On
Reliability Testing: Volume 2 of 3’’ 154
and the report entitled ‘‘The
Development and Testing of The
Continuity Assessment Record And
Evaluation (CARE) Item Set: Final
Report on Care Item Set and Current
Assessment Comparisons: Volume 3 of
3.’’ 155 These reports are available on our
Post-Acute Care Quality Initiatives Web
page at https://www.cms.gov/Medicare/
Quality-Initiatives-Patient-AssessmentInstruments/Post-Acute-Care-QualityInitiatives/CARE-Item-Set-and-BCARE.html.
Additional testing of these functional
assessment items was conducted in a
small field test occurring in 2016–2017,
capturing data from 12 HHAs.
Preliminary data results yielded
moderate to substantial reliability for
the self-care and mobility data items.
More information about testing design
and results can be found at https://
www.cms.gov/Medicare/QualityInitiatives-Patient-AssessmentInstruments/HomeHealthQualityInits/
OASIS-Data-Sets.html. The functional
status quality measure we are proposing
to adopt beginning with the CY 2020
HH QRP is a process quality measure
that is an application of the NQFendorsed quality measure, the Percent
of Long-Term Care Hospital Patients
with an Admission and Discharge
Functional Assessment and a Care Plan
that Addresses Function (NQF #2631).
This quality measure reports the percent
of patients with both an admission and
a discharge functional assessment and a
functional treatment goal.
This process measure requires the
collection of admission and discharge
functional status data by clinicians
using standardized patient assessment
153 Barbara Gage et al., ‘‘The Development and
Testing of the Continuity Assessment Record and
Evaluation (CARE) Item Set: Final Report on the
Development of the CARE Item Set’’ (RTI
International, 2012).
154 Ibid.
155 Ibid.
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data elements, which assess specific
functional activities, such as self-care
and mobility activities. The self-care
and mobility function activities are
coded using a 6-level rating scale that
indicates the resident’s level of
independence with the activity at both
admission and discharge. A higher score
indicates more independence. These
functional assessment data elements
will be collected at Start or Resumption
of Care (SOC/ROC) and discharge.
For this quality measure, there must
be documentation at the time of
admission (SOC) that at least one
activity performance (function) goal is
recorded for at least one of the
standardized self-care or mobility
function items using the 6-level rating
scale. This indicates that an activity
goal(s) has been established. Following
this initial assessment, the clinical best
practice would be to ensure that the
patient’s care plan reflected and
included a plan to achieve such activity
goal(s). At the time of discharge, goal
setting and establishment of a care plan
to achieve the goal, is reassessed using
the same 6-level rating scale, allowing
for the ability to evaluate success in
achieving the patient’s activity
performance goals.
To the extent that a patient has an
unplanned discharge, for example,
transfer to an acute care facility, the
collection of discharge functional status
data may not be feasible. Therefore, for
patients with unplanned discharges,
admission functional status data and at
least one treatment goal must be
reported, but discharge functional status
data are not required to be reported.
c. Stakeholder Feedback
Our measures contractor convened a
TEP on October 17, and October 18,
2016. The TEP was composed of a
diverse group of stakeholders with HH,
PAC, and functional assessment
expertise. The panel provided input on
the technical specifications of this
proposed measure, including the
feasibility of implementing the measure,
as well as the overall measure of
reliability and validity. The TEP
additionally provided feedback on the
clinical assessment items used to
calculate the measure. The TEP
reviewed the measure ‘‘Percent of LongTerm Care Patients with an Admission
and Discharge Functional Assessment
and a Care Plan That Addresses
Function (NQF 2631)’’ for potential
application to the home health setting.
Overall they were supportive of a
functional process measure, noting it
could have the positive effect of
focusing clinician attention on
functional status and goals. A summary
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of the TEP proceedings is available on
the PAC Quality Initiatives Downloads
and Videos Web page at https://
www.cms.gov/medicare/qualityinitiatives-patient-assessmentinstruments/post-acute-care-qualityinitiatives/impact-act-of-2014/impactact-downloads-and-videos.html.
We also solicited stakeholder
feedback on the development of this
measure through a public comment
period held from November 4, 2016
through December 5, 2016. Several
stakeholders and organizations
supported this measure for
implementation and for measure
standardization. Some commenters also
provided feedback on the standardized
patient assessment data elements used
to calculate the proposed quality
measure. Commenters offered
suggestions, including providing
education regarding the difference in
measure scales for the standardized
items relative to current OASIS
functional items, and guidance on the
type of clinical staff input needed to
appropriately complete new functional
assessment items. Commenters also
addressed the feasibility of collecting
data for the individual standardized
self-care and mobility items in the home
health setting. Finally, commenters
noted the importance of appropriate
goal setting when functional
improvement for a patient may not be
feasible. The public comment summary
report for the proposed measure is
available on the CMS Web site at
https://www.cms.gov/medicare/qualityinitiatives-patient-assessmentinstruments/post-acute-care-qualityinitiatives/impact-act-of-2014/impactact-downloads-and-videos.html.
The NQF-convened MAP met on
December 14 and 15, 2016, and
provided input on the use of this
proposed measure in the HH QRP. The
MAP recommended ‘‘conditional
support for rulemaking’’ for this
measure. MAP members noted the
measure would drive care coordination
and improve transitions by encouraging
the use of standardized functional
assessment items across PAC settings,
but recommended submission to the
NQF for endorsement to include the
home health setting. More information
about the MAP’s recommendations for
this measure is available at https://
www.qualityforum.org/Publications/
2017/02/MAP_2017_Considerations_
for_Implementing_Measures_in_
Federal_Programs_-_PAC–LTC.aspx.
We reviewed the NQF’s consensus
endorsed measures and were unable to
identify any home health measures that
address functional assessment, and
treatment goals that address function.
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There are five functional measures in
home health that assess functional
activities: (1) Improvement in
Ambulation/Locomotion (NQF #0167);
(2) Improvement in Bathing (NQF
#0174); (3) Improvement in Bed
Transfer (NQF #0175); (4) Improvement
in Management of Oral Medications
(NQF # 0176); and (5) Improvement in
Pain Interfering with Activity (NQF
#0177). Our review determined that
these setting-specific measures are not
appropriate to meet the specified
IMPACT Act domain as they do not
include standardized items or are not
included for various other PAC
populations. Specifically:
• The items used to collect data for
the current home health measures are
less specific, leading to broader measure
results, whereas the standardized
patient assessment data items used for
the proposed measure assess core
activities such as rolling in bed, walking
a specified distance, or wheelchair
capability.
• The item coding responses are more
detailed when compared to the nonstandardized OASIS item responses,
allowing for more granular data for the
measure.
• The proposed functional measure
will capture a patient’s discharge goal at
admission into home health; this detail
is not captured in the existing endorsed
HH function measures.
Therefore, based on the evidence
discussed above, we are proposing to
adopt the quality measure entitled,
Application of Percent of Long-Term
Care Hospital Patients with an
Admission and Discharge Functional
Assessment and a Care Plan That
Addresses Function (NQF #2631), for
the HH QRP beginning with the CY
2020 HH QRP. We plan to submit the
proposed measure to the NQF for
endorsement consideration as soon as is
feasible.
For technical information about this
proposed measure, including
information about the measure
calculation and the standardized patient
assessment data elements used to
calculate this measure, we refer readers
to the document titled, Proposed
Measure Specifications and
Standardized Data Elements for CY
2018 HH QRP Notice of Proposed
Rulemaking, available at https://
www.cms.gov/Medicare/QualityInitiatives-Patient-AssessmentInstruments/HomeHealthQualityInits/
HHQIQualityMeasures.html.
d. Data Collection
For purposes of assessment data
collection, we propose to add new
functional status items to the OASIS, to
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be collected at SOC/ROC and discharge.
These items would assess specific selfcare and mobility activities, and would
be based on functional items included
in the PAC–PRD version of the CARE
Item Set. More information pertaining to
item testing is available on our PostAcute Care Quality Initiatives Web page
at https://www.cms.gov/Medicare/
Quality-Initiatives-Patient-AssessmentInstruments/Post-Acute-Care-QualityInitiatives/CARE-Item-Set-and-BCARE.html.
To allow HHAs to fulfill the
requirements of the Home Health
Agency Conditions of Participation
(HHA CoPs) (82 FR 4504), we are
proposing to add a subset of the
functional assessment items to the
OASIS, with collection of these items at
Follow-Up (FU). The collection of these
assessment items at FU by HHAs will
allow them to fulfill the requirements
outlined in the HHA CoPs that suggest
that the collection of a patient’s current
health, including functional status, be
collected on the comprehensive
assessment.
These new functional status items are
standardized across PAC settings and
support the proposed standardized
measure. They are organized into two
functional domains: Self-Care and
Mobility. Each domain includes
dimensions of these functional
constructs that are relevant for home
health patients. The proposed function
items that we would add to the OASIS
for purposes of the calculation of this
proposed quality measure do not
duplicate existing items currently
collected in that assessment instrument
for other purposes. The current OASIS
function items evaluate current ability,
whereas the proposed functional items
would evaluate an individual’s usual
performance at the time of admission
and at the time of discharge for goal
setting purposes. Additionally, there are
several key differences between the
existing and new proposed function
items that may result in variation in the
patient assessment results including: (1)
The data collection and associated data
collection instructions; (2) the rating
scales used to score a resident’s level of
independence; and (3) the item
definitions. A description of these
differences is provided with the
measure specifications available at
https://www.cms.gov/Medicare/QualityInitiatives-Patient-AssessmentInstruments/HomeHealthQualityInits/
HHQIQualityMeasures.html.
Because of the differences between
the current function assessment items
(OASIS C–2) and the proposed function
assessment items that we would collect
for purposes of calculating the proposed
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measure, we would require that HHAs
submit data on both sets of items. Data
collection for the new proposed
function items do not substitute for the
data collection under the current OASIS
ADL and IADL items. Although
providers will collect on the proposed
function assessment items as well as the
current assessment items, for reasons
previously described, we believe these
items are not duplicative. However, we
request comment on opportunities to
streamline reporting to avoid
duplication and minimize burden.
We are proposing that data for the
proposed quality measure would be
collected through the OASIS, which
HHAs currently submit through the
QIES ASAP system. We refer readers to
section V.F.2 of this proposed rule for
more information on the proposed data
collection and submission timeline for
this proposed quality measure. If this
measure is finalized, we intend to
provide initial confidential feedback to
home health agencies, prior to the
public reporting of this measure.
We invite public comment on our
proposal to adopt the measure,
Application of Percent of Long-Term
Care Hospital Patients with an
Admission and Discharge Functional
Assessment and a Care Plan That
Addresses Function (NQF #2631).
3. Proposal To Address the IMPACT Act
Domain of ‘‘Incidence of Major Falls’’
Measure: Percent of Residents
Experiencing One or More Falls With
Major Injury
a. Measure Background
Sections 1899B(c)(1)(D) of the Act
requires that no later than the specified
application date (which under section
1899B(a)(1)(E)(i)(IV) is January 1, 2019
for HHAs, and October 1, 2016 for SNFs,
IRFs and LTCHs), the Secretary specify
a measure to address the domain of
incidence of major falls, including falls
with major injury. We propose to adopt
the measure, Application of Percent of
Residents Experiencing One or More
Falls with Major Injury (NQF #0674), for
which we would begin to collect data on
January 1, 2019 for the CY 2020 HH
QRP to meet this requirement. This
proposed outcome measure reports the
percentage of residents who have
experienced falls with major injury
during episodes ending in a 3-month
period.
b. Measure Importance
Falls affect an estimated 6 to 12
million older adults each year and are
the leading cause of both fatal injury
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and nonfatal hospital admissions.156 157
Within the home health population, the
risk of falling is significant as
approximately one third of individuals
over the age of 65 experienced at least
one fall annually.158 Major fall-related
injuries among older communitydwelling adults are a growing health
concern within the United States159 160
because they can have high medical and
cost implications for the Medicare
community.161 In 2013, the direct
medical cost for falls in older adults was
$34 billion 162 and is projected to
increase to over $101 billion by 2030
due to the aging population.163
Evidence from various studies
indicates that implementing effective
fall prevention interventions and
minimizing the impact of falls that do
occur reduces overall costs, emergency
department visits, hospital
readmissions, and overall Medicare
resource utilization.164 165 166 167 In the
156 Bohl, A. A., Phelan, E. A., Fishman, P. A., &
Harris, J. R. (2012). How are the costs of care for
medical falls distributed? The costs of medical falls
by component of cost, timing, and injury severity.
The Gerontologist, 52(5): 664–675.
157 National Council on Aging (2015). Falls
Prevention Fact Sheet. Retrieved from https://
www.ncoa.org/wp-content/uploads/Fact-Sheet_
Falls-Prevention.pdf.
158 Avin G., K., Hanke A., T., Kirk-Sanche, N.,
McDonough M., C., Shubert E., T., Hardage, J., &
Hartley, G. (2015). Management of Falls in
Community-Dwelling Older Adults: Clinical
Guidance Statement From the Academy of Geriatric
Physical Therapy of the American Physical Therapy
Association. Physical Therapy, 95(6), 815–834.
doi:10.2522/ptj.20140415.
159 Hester, A. L. & Wei, F. (2013). Falls in the
community: state of the science. Clinical
Interventions in Aging, 8:675–679.
160 Orces, C. H. & Alamgir, H. (2014). Trends in
fall-related injuries among older adults treated in
emergency departments in the USA. Injury
Prevention, 20: 421–423.
161 Liu, S. W., Obermeyer, Z., Chang, Y., &
Shankar, K. N. (2015). Frequency of ED revisits and
death among older adults after a fall. American
Journal of Emergency Medicine, 33(8), 1012–1018.
doi:10.1016/j.ajem.2015.04.023.
162 Centers for Disease Control and Prevention
(2015b). Important facts about falls. https://
www.cdc.gov/homeandrecreationalsafety/falls/
adultfalls.html. Accessed April 19, 2016.
163 Houry, D., Florence, C. Bladwin, G., Stevens,
J., & McClure, R. (2015). The CDC Injury Center’s
response to the growing public health problem of
falls among older adults. American Journal of
Lifestyle Medicine, 10(1), 74–77.
164 Bamgbade, S., & Dearmon, V. (2016). Fall
prevention for older adults receiving home
healthcare. Home Healthcare Now, 34(2), 68–75.
165 Carande-Kulis, V., Stevens, J. A., Florence, C.
S., Beattie, B. L., & Arias, I. (2015). A cost-benefit
analysis of three older adult fall prevention
interventions. Journal of Safety Research, 52, 65–70.
doi:10.1016/j.jsr.2014.12.007.
166 Cohen, A. M., Miller, J., Shi, X., Sandhu, J.,
& Lipsitz, A. (2015). Prevention program lowered
the risk of falls and decreased claims for long-term
care services among elder participants. Health
Affairs, 34(6), 971–977.
167 Howland, J., Shankar, K. N., Peterson, E. W.,
& Taylor, A. A. (2015). Savings in acute care costs
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2006 Home Assessments and
Modification study, a home visit by an
occupational therapist or home care
worker to identify and mitigate potential
home hazards and risky behavior,
resulted in a 46 percent reduction in fall
rates for those receiving the intervention
compared to controls.168 Overall,
patients participating in interventions
experienced improved quality of life
due to reduced morbidity, improved
functional ability and mobility, reduced
number of falls and injurious falls, and
a decrease in the fear of falling. 169 170
Falls also represent a significant cost
burden to Medicare. Each year, 2.8
million older people are treated in
Emergency Departments for fall related
injuries and over 800,000 require
hospitalization.171 Adjusted to 2015
dollars, nationally, direct medical costs
for non-fatal fall related injuries in older
adults were over $31.3 billion.172
Additional health care costs (in 2010
dollars) can range from $3,500 for a fall
without serious injury to $27,000 for a
fall with a serious injury.173 Between
1988 and 2005, fractures accounted for
84 percent of hospitalizations for fallrelated injuries among older adults.174
Researchers evaluated the cost of fallrelated hospitalizations among older
adults using the 2011 Texas Hospital
Inpatient Discharge Data and
determined that the average cost for fallrelated hip fractures was $61,715 for
individuals 50 and older living in
if all older adults treated for fall-related injuries
completed matter of balance. Injury Epidemiology,
2(25), 1–7.
168 Pighills AC, Torgerson DJ, Sheldon TA,
Drummond AE, Bland JM. Environmental
assessment and modification to prevent falls in
older people. Journal of the American Geriatrics
Society. 2011;59(1):26–33.
169 Chase, C. A., Mann, K., Wasek, S., &
Arbesman, M. (2012). Systematic review of the
effect of home modification and fall prevention
programs on falls and the performance of
community-dwelling older adults. American
Journal of Occupational Therapy, 66(3), 284–291.
170 Patil, R., Uusi-Rasi, K., Tokola, K., Karinkanta,
S., Kannus, P., & Sievanen, H. (2015). Effects of a
Multimodal Exercise Program on Physical Function,
Falls, and Injuries in Older Women: A 2-Year
Community-Based, Randomized Controlled Trial.
Journal of the American Geriatrics Society, 63(7),
1306–1313.
171 Centers for Disease Control and Prevention,
National Center for Injury Prevention and Control.
Web-based Injury Statistics Query and Reporting
System (WISQARS) [online]. Accessed August 5,
2016.
172 Burns ER, Stevens JA, Lee R. The direct costs
of fatal and non-fatal falls among older adults—
United States. J Safety Res 2016;58:99–103.
173 Wu S, Keeler EB, Rubenstein LZ, Maglione
MA, Shekelle PG. A cost-effectiveness analysis of a
proposed national falls prevention program. Clin
Geriatr Med. 2010;26(4): 751–66.
174 Orces, C. H. & Alamgir, H. (2014). Trends in
fall-related injuries among older adults treated in
emergency departments in the USA. Injury
Prevention, 20: 421–423.
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metropolitan areas and $55,366 for
those living nonmetropolitan areas.175
To meet the IMPACT Act provision
requiring the development of a
standardized quality measure for the
domain of Incidence of Major Falls
(sections 1899B(c)(1)(D) of the Act), we
developed the proposed standardized
measure, The Percent of Residents
Experiencing One or More Falls with
Major Injury (Long Stay) (NQF #0674).
This quality measure is NQF-endorsed
and has been successfully implemented
in the Nursing Home Quality Initiative
for nursing facility long-stay residents
since 2011, demonstrating the measure
is feasible, appropriate for assessing
PAC quality of care, and could be used
as a platform for standardized quality
measure development. This quality
measure is standardized across PAC
settings and contains items that are
collected uniformly in each setting’s
assessment instruments (that is, MDS,
IRF–PAI, and LCDS). Further, an
application of the quality measure was
adopted for use in the LTCH QRP in the
FY 2014 IPPS/LTCH PPS final rule (78
FR 50874 through 50877), revised in the
FY 2015 IPPS/LTCH PPS final rule (79
FR 50290), and adopted to fulfill
IMPACT Act requirements in the FY
2016 IPPS/LTCH PPS final rule (80 FR
49736 through 49739). Data collection
began in April 1, 2016 for LTCHs, and
October 1, 2016 for SNFs and IRFs.
More information on the NQFendorsed quality measure, the Percent
of Residents Experiencing One or More
Falls with Major Injury (Long Stay)
(NQF #0674) is available at https://
www.qualityforum.org/QPS/0674.
c. Stakeholder Feedback
A TEP convened by our measure
development contractor provided input
on the technical specifications of an
application of the quality measure, the
Percent of Residents Experiencing One
or More Falls with Major Injury (Long
Stay) (NQF #0674), including the
feasibility of implementing the measure
across PAC settings. The TEP was
supportive of the implementation of this
measure across PAC settings and was
also supportive of our efforts to
standardize this measure for crosssetting development. More information
about this TEP can be found at https://
www.cms.gov/medicare/qualityinitiatives-patient-assessmentinstruments/post-acute-care-qualityinitiatives/impact-act-of-2014/impactact-downloads-and-videos.html.
175 Towne, S. D., Ory, M. G., & Smith, M. L.
(2014). Cost of fall-related hospitalizations among
older adults: environmental comparisons from the
2011 Texas hospital inpatient discharge data.
Population Health Management, 17(6), 351–356.
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In addition, we solicited public
comment on this measure from
September 19, 2016 through October 14,
2016. Overall, commenters were
generally supportive of the measure, but
raised concerns about the attribution
given that home health clinicians are
not present in the home at all times and
recommended risk-adjusting the
measure. The summary of this public
comment period can be found at https://
www.cms.gov/medicare/qualityinitiatives-patient-assessmentinstruments/post-acute-care-qualityinitiatives/impact-act-of-2014/impactact-downloads-and-videos.html.
Finally, we presented this measure to
the NQF-convened MAP on December
14, 2016. The MAP conditionally
supported the use of an application of
the quality measure, the Percent of
Residents Experiencing One or More
Falls with Major Injury (Long Stay)
(NQF #0674) in the HH QRP as a crosssetting quality measure. The MAP
highlighted the clinical significance of
falls with major injury, while noting
potential difficulties in collecting falls
data and more limited actionability in
the HH setting. The MAP suggested that
CMS explore stratification of measure
rates by referral origin when public
reporting. More information about the
MAP’s recommendations for this
measure is available at https://
www.qualityforum.org/Publications/
2017/02/MAP_2017_Considerations_
for_Implementing_Measures_in_
Federal_Programs_-_PAC-LTC.aspx. We
are inviting public comment on the
stratification of the proposed measure,
specifically on the measure rates for
public reporting. The quality measure,
the Percent of Residents Experiencing
One or More Falls with Major Injury
(Long Stay) (NQF #0674) is not
currently endorsed for the HH setting.
We reviewed the NQF’s consensus
endorsed measures and were unable to
identify any NQF-endorsed cross-setting
quality measures for that setting that are
focused on falls with major injury. We
found one falls-related measure in home
health titled, Multifactor Fall Risk
Assessment Conducted for All Patients
Who Can Ambulate (NQF #0537).
We are also aware of one NQFendorsed measure, Falls with Injury
(NQF #0202), which is a measure
designed for adult acute inpatient and
rehabilitation patients capturing ‘‘all
documented patient falls with an injury
level of minor or greater on eligible unit
types in a calendar quarter, reported as
injury falls per 100 days.’’ 176 After
careful review, we have determined that
these measures are not appropriate to
meet the IMPACT Act domain of
incidence of major falls. Specifically:
• NQF #0202 includes minor injuries
in the numerator definition. Including
all falls in an outcome measure could
result in providers limiting activity for
individuals at higher risk for falls.
• NQF #0537 is a process-based
measure of HHAs’ efforts to assess the
risk for any fall, but not actual falls.
• Neither measure is standardized
across PAC settings.
We are unaware of any other crosssetting quality measures for falls with
major injury that have been endorsed or
adopted by another consensus
organization for the HH setting.
Therefore, based on the evidence
discussed above, we are proposing to
adopt the quality measure entitled, An
Application of the Measure Percent of
Residents Experiencing One or More
Falls with Major Injury (Long Stay)
(NQF #0674), for the HH QRP beginning
with the CY 2020 HH QRP. We plan to
submit the proposed measure to the
NQF for endorsement consideration as
soon as it is feasible.
d. Data Collection
For purposes of assessment data
collection, we propose to add two new
falls-related items to the OASIS. The
proposed falls with major injury item
used to calculate the proposed quality
measure does not duplicate existing
items currently collected in the OASIS.
We propose to add two standardized
items to the OASIS for collection at End
of Care (EOC), which comprises the
Discharge from Agency, Death at Home,
35353
and Transfer to an Inpatient Facility
time points: J1800 and J1900. The first
item (J1800) is a gateway item that asks
whether the patient has experienced any
falls since admission/resumption of care
(prior assessment). If the answer to
J1800 is yes, the next item (J1900) asks
for the number of falls with: (a) No
injury, (b) injury (except major), and (c)
major injury. The measure is calculated
using data reported for J1900C (number
of falls with major injury). This measure
would be calculated at the time of
discharge (see Section V.F.3 of this
proposed rule). For technical
information about this proposed
measure, including information
pertaining to measure calculation and
the standardized patient assessment
data element used to calculate this
measure, we refer readers to the
document titled, Proposed Measure
Specifications and Standardized Data
Elements for CY 2018 HH QRP Notice of
Proposed Rulemaking, available at
https://www.cms.gov/Medicare/QualityInitiatives-Patient-AssessmentInstruments/HomeHealthQualityInits/
HHQIQualityMeasures.html.
We are proposing that data for the
proposed quality measure would be
collected through the OASIS, which
HHAs currently submit through the
QIES ASAP system. We refer readers to
section V.I.4 of this proposed rule for
more information on the proposed data
collection and submission timeline for
this proposed quality measure.
We are inviting public comments on
our proposal to adopt an application of
the quality measure, the Percent of
Residents Experiencing One or More
Falls with Major Injury (Long Stay)
(NQF #0674) for the CY 2020 HH QRP.
G. HH QRP Quality Measures and
Measure Concepts Under Consideration
for Future Years
We are inviting public comment on
the importance, relevance,
appropriateness, and applicability of
each of the quality measures listed in
Table 48 for use in future years in the
HH QRP.
TABLE 48—HH QRP QUALITY MEASURES UNDER CONSIDERATION FOR FUTURE YEARS
IMPACT Act domain
Functional status, cognitive function, and changes in function and cognitive function
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Measures ............................................................
A. Application of NQF #2633—Change in Self-Care Score for Medical Rehabilitation Patients.
B. Application of NQF #2634—Change in Mobility Score for Medical Rehabilitation Patients.
C. Application of NQF #2635—Discharge Self-Care Score for Medical Rehabilitation Patients.
D. Application of NQF #2636—Discharge Mobility Score for Medical Rehabilitation Patients.
176 American Nurses Association (2014, April 9).
Falls with injury. Retrieved from https://
www.qualityforum.org/QPS/0202.
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We are considering four measures that
would assess a change in functional
outcomes such as self-care and mobility
across a HH episode. These measures
would be standardized to measures
finalized in other PAC quality reporting
programs, such as the IRF QRP. We
invite feedback on the importance,
relevance, appropriateness, and
applicability of these measure
constructs.
Based on input from stakeholders, we
have identified additional concept areas
for potential future measure
development for the HH QRP. These
include claims-based within stay
potentially preventable hospitalization
measures. The potentially preventable
within-stay hospitalization measures
would look at the percentage of HH
episodes in which patients were
admitted to an acute care hospital or
seen in an emergency department for a
potentially preventable condition
during an HH episode. We invite
feedback on the importance, relevance,
appropriateness, and applicability of
these measure constructs.
In alignment with the requirements of
the IMPACT Act to develop quality
measures and standardize data for
comparative purposes, we believe that
evaluating outcomes across the postacute settings using standardized data is
an important priority. Therefore, in
addition to proposing a process-based
measure for the domain of ‘‘Functional
status, cognitive function, and changes
in function and cognitive function’’,
included in this year’s proposed rule,
we also intend to develop outcomesbased quality measures, including
functional status and other quality
outcome measures to further satisfy this
domain.
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1. IMPACT Act Implementation Update
As a result of the input and
suggestions provided by technical
experts at the TEPs held by our measure
developer, and through public
comment, we are engaging in additional
development work for two measures
that would satisfy 1899B(c)(1)(E) of the
Act, including performing additional
testing. We intend to specify these
measures under section 1899B(c)(1)(E)
of the Act no later than January 1, 2019
and we intend to propose to adopt them
for the CY 2021 HH QRP, with data
collection beginning on or about January
1, 2020.
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H. Proposed Standardized Patient
Assessment Data
1. Proposed Standardized Patient
Assessment Data Reporting for the CY
2019 HH QRP
Section 1895(b)(3)(B)(v)(IV)(bb) of the
Act requires that for calendar years
beginning on or after January 1, 2019,
HHAs submit to the Secretary
standardized patient assessment data
required under section 1899B(b)(1) of
the Act.
As we describe in more detail above,
we are proposing that the current
pressure ulcer measure, Application of
Percent of Residents or Patients with
Pressure Ulcers That Are New or
Worsened (Short Stay) (NQF #0678), be
replaced with the proposed pressure
ulcer measure, Changes in Skin Integrity
Post-Acute Care: Pressure Ulcer/Injury,
beginning with the CY 2020 HH QRP.
The current pressure ulcer measure will
remain in the HH QRP until that time.
Accordingly, for the requirement that
HHAs report standardized patient
assessment data for the CY 2019 HH
QRP, we are proposing that the data
elements used to calculate that measure
meet the definition of standardized
patient assessment data for medical
conditions and co-morbidities under
section 1899B(b)(1)(B)(iv) of the Act,
and that the successful reporting of that
data under section
1895(b)(3)(b)(v)(IV)(aa) of the Act for the
beginning of the HH episode (for
example, HH start of care/resumption of
care), as well as the end of the HH
episode (discharges) occurring during
the first two quarters of CY 2018 would
also satisfy the requirement to report
standardized patient assessment data
beginning with the CY 2019 HH QRP.
The collection of assessment data
pertaining to skin integrity, specifically
pressure related wounds, is important
for multiple reasons. Clinical decision
making, care planning, and quality
improvement all depend on reliable
assessment data collection. Pressure
related wounds represent poor
outcomes, are a serious medical
condition that can result in death and
disability, are debilitating and painful,
and are often avoidable.
177 178 179 180 181 182 Pressure related
177 Casey, G. (2013). ‘‘Pressure ulcers reflect
quality of nursing care.’’ Nurs N Z 19(10): 20–24.
178 Gorzoni, M.L. and S.L. Pires (2011). ‘‘Deaths
in nursing homes.’’ Rev Assoc Med Bras 57(3): 327–
331.
179 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.
180 White-Chu, E.F., et al. (2011). ‘‘Pressure ulcers
in long-term care.’’ Clin Geriatr Med 27(2): 241–258.
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wounds are considered healthcare
acquired conditions.
As we note above, the data elements
needed to calculate the current pressure
ulcer measure are already included on
the OASIS data set and reported by
HHAs, and exhibit validity and
reliability for use across PAC providers.
Item reliability for these data elements
was also tested for the nursing home
setting during implementation of MDS
3.0. Testing results are from the RAND
Development and Validation of MDS 3.0
project.183 The RAND pilot test of the
MDS 3.0 data elements showed good
reliability and are applicable to the
OASIS because the data elements tested
are the same as those used in the OASIS
Data Set. Across the pressure ulcer data
elements, the average gold-standard
nurse to gold-standard nurse kappa
statistic was 0.905. The average goldstandard nurse to facility-nurse kappa
statistic was 0.937. Data elements used
to risk adjust this quality measure were
also tested under this same pilot test,
and the gold-standard to gold-standard
kappa statistic, or percent agreement
(where kappa statistic not available),
ranged from 0.91 to 0.99 for these data
elements. These kappa scores indicate
‘‘almost perfect’’ agreement using the
Landis and Koch standard for strength
of agreement.184
The data elements used to calculate
the current pressure ulcer measure
received public comment on several
occasions, including when that measure
was proposed in the CY 2016 HH PPS
(80 FR 68623). Further, they were
discussed in the past by TEPs held by
our measure development contractor on
June 13 and November 15, 2013, and
recently by a TEP on July 18, 2016. TEP
members supported the measure and its
cross-setting use in PAC. The report,
Technical Expert Panel Summary
Report: Refinement of the Percent of
Patients or Residents with Pressure
Ulcers that are New or Worsened (ShortStay) (NQF #0678) Quality Measure for
Skilled Nursing Facilities (SNFs),
Inpatient Rehabilitation Facilities
(HHAs), Long-Term Care Hospitals
181 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.
182 Bennet, G, Dealy, C Posnett, J (2004). The cost
of pressure ulcers in the UK, Age and Aging,
33(3):230–235.
183 Saliba, D., & Buchanan, J. (2008, April).
Development and validation of a revised nursing
home assessment tool: MDS 3.0. Contract No. 500–
00–0027/Task Order #2. Santa Monica, CA: Rand
Corporation. Retrieved from https://
www.cms.hhs.gov/NursingHomeQualityInits/
Downloads/MDS30FinalReport.pdf.
184 Landis, R., & Koch, G. (1977, March). The
measurement of observer agreement for categorical
data. Biometrics 33(1), 159–174.
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(LTCHs), and Home Health Agencies
(HHAs), is available at and https://
www.cms.gov/Medicare/QualityInitiatives-Patient-AssessmentInstruments/Post-Acute-Care-QualityInitiatives/IMPACT-Act-of-2014/
IMPACT-Act-Downloads-andVideos.html.
We are inviting public comment on
this proposal.
2. Proposed Standardized Patient
Assessment Data Reporting Beginning
With the CY 2020 HH QRP
We describe below our proposals for
the reporting of standardized patient
assessment data by HHAs beginning
with the CY 2020 HH QRP. LTCHs,
IRFs, and SNFs are also required to
report standardized patient assessment
data through their applicable PAC
assessment instruments, and they do so
by responding to identical assessment
questions developed for their respective
settings using an identical set of
response options (which incorporate an
identical set of definitions and
standards). HHAs would be required to
report these data at admission (SOC/
ROC) and discharge beginning on
January 1, 2019, with the exception of
three data elements (Brief Interview of
Mental Status (BIMS), Hearing, and
Vision) that will be required at SOC/
ROC only, as described below. The
BIMS, Hearing and Vision data elements
would be assessed at SOC/ROC only
due to the relatively stable nature of the
types of cognitive function, hearing
impairment, and vision impairment,
making it unlikely that these
assessments would change between the
start and end of the HHA episode of
care. Assessment of the BIMS, Hearing,
and Vision data elements at EOC would
introduce additional burden without
improving the quality or usefulness of
the data, and is deemed unnecessary.
Following the initial reporting year
(which would be based on 6 months of
data) for the CY 2020 HH QRP,
subsequent years for the HH QRP would
be based on a full calendar year of such
data reporting.
In selecting the data elements
described below, we carefully weighed
the balance of burden in assessmentbased data collection and aimed to
minimize additional burden through the
utilization of existing data in the
assessment instruments. We also note
that the patient and resident assessment
instruments are considered part of the
medical record and sought the inclusion
of data elements relevant to patient care.
We also took into consideration the
following factors for each data element:
overall clinical relevance; ability to
support clinical decisions, care
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planning, and interoperable exchange to
facilitate care coordination during
transitions in care; and the ability to
capture medical complexity and risk
factors that can inform both payment
and quality. In addition, the data
elements had to have strong scientific
reliability and validity; be meaningful
enough to inform longitudinal analysis
by providers; had to have received
general consensus agreement for its
usability; and had to have the ability to
collect such data once but support
multiple uses. Further, to inform the
final set of data elements for proposal,
we took into account technical and
clinical subject matter expert review,
public comment, and consensus input
in which such principles were applied.
3. Proposed Standardized Patient
Assessment Data by Category
a. Functional Status Data
We are proposing that the data
elements that would be reported by
HHAs to calculate the measure,
Application of Percent of Long-Term
Care Hospital Patients with an
Admission and Discharge Functional
Assessment and a Care Plan That
Addresses Function (NQF #2631), as
described in section V.F.2 would also
meet the definition of standardized
patient assessment data for functional
status under section 1899B(b)(1)(B)(i) of
the Act, and that the successful
reporting of that data under section
1895(b)(3)(B)(v)(IV)(aa) of the Act would
also satisfy the requirement to report
standardized patient assessment data
under section 1895(b)(3)(B)(v)(IV)(bb) of
the Act. Details on the data used to
calculate this measure is discussed in
section V.F.2.
To further satisfy the requirements
under section 1899B(b)(1)(B)(i) of the
Act and specifically our efforts to
achieve standardized patient assessment
data pertaining to functional status,
such as mobility and self-care at
admission to a PAC provider and before
discharge from a PAC provider, we are
also proposing to adopt the functional
status data elements that specifically
address mobility and self-care as
provided in the Act. These data
elements are also used to calculate the
function outcome measures
implemented and/or proposed for
implementation in three other postacute quality reporting programs to
which the IMPACT Act applies
(Application of NQF #2633—Change in
Self-Care Score for Medical
Rehabilitation Patients; Application of
NQF #2634—Change in Mobility Score
for Medical Rehabilitation Patients;
Application of NQF #2635—Discharge
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35355
Self-Care Score for Medical
Rehabilitation Patients; and Application
of NQF #2636—Discharge Mobility
Score for Medical Rehabilitation
Patients). To achieve standardization,
we have implemented such data
elements, or sub-sets of the items, into
the other post-acute care patient/
resident assessment instruments and we
are proposing that they also meet the
definition of standardized patient
assessment data for functional status
under section 1899B(b)(1)(B)(i) of the
Act, and that the successful reporting of
such data under section
1895(b)(3)(B)(v)(IV)(aa) of the Act would
also satisfy the requirement to report
standardized patient assessment data
under section 1895(b)(3)(B)(v)(IV)(bb) of
the Act. These data elements currently
are collected in the Section GG:
Functional Abilities and Goals located
in current versions of the MDS and the
IRF–PAI assessment instruments.
As previously described, these patient
assessment data that assess for
functional status are from the CARE
Item Set. They were specifically
developed for cross-setting application
and are the result of consensus building
and public input. Further, we received
public comment and input. Their
reliability and validity testing were
conducted as part of CMS’ Post-Acute
Care Payment Reform Demonstration,
and we concluded that the functional
status items have acceptable reliability
and validity. We refer the reader to
section V.F.2 for a full description of the
CARE Item Set and description of the
testing methodology and results that are
available in several reports. For more
information about this quality measure
and the data elements used to calculate
it, we refer readers to the FY 2016 IPPS/
LTCH PPS final rule (80 FR 49739
through 49747), the FY 2016 IRF PPS
final rule (80 FR 47100 through 47111),
and the FY 2016 SNF PPS final rule (80
FR 46444 through 46453).
Therefore, we are proposing to adopt
the functional status data elements that
as for the CY 2020 HH QRP, HHAs
would be required to report these data
at SOC/ROC or discharge starting on
January 1, 2019. This aligns with the
required reporting timeframe for the CY
2020 HH QRP. Following the initial two
quarters of reporting for the CY 2020 HH
QRP, subsequent years for the HH QRP
would be based on 12 months of data
reporting beginning with July 1, 2019,
through June 30, 2020 for the CY 2021
HH QRP.
We seek comment on this proposal.
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b. Cognitive Function and Mental Status
Data
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Cognitive function and mental status
in PAC patient and resident populations
can be affected by a number of
underlying conditions, including
dementia, stroke, traumatic brain injury,
side effects of medication, metabolic
and/or endocrine imbalances, delirium,
and depression.185 The assessment of
cognitive function and mental status by
PAC providers is important because of
the high percentage of patients and
residents with these conditions,186 and
to improve quality of care. Symptoms of
dementia may improve with
pharmacotherapy, occupational therapy,
or physical activity,187 188 189 and
promising treatments for severe
traumatic brain injury are currently
being tested.190 For older patients and
residents diagnosed with depression,
treatment options to reduce symptoms
and improve quality of life include
antidepressant medication and
psychotherapy,191 192 193 194 and targeted
services, such as therapeutic recreation,
exercise, and restorative nursing, to
185 National Institute on Aging. (2014). Assessing
Cognitive Impairment in Older Patients. A Quick
Guide for Primary Care Physicians. Retrieved from
https://www.nia.nih.gov/alzheimers/publication/
assessing-cognitive-impairment-older-patients.
186 Gage B., Morley M., Smith L., et al. (2012).
Post-Acute Care Payment Reform Demonstration
(Final report, Volume 4 of 4). Research Triangle
Park, NC: RTI International.
187 Casey D.A., Antimisiaris D., O’Brien J. (2010).
Drugs for Alzheimer’s Disease: Are They Effective?
Pharmacology & Therapeutics, 35, 208–11.
188 Graff M.J., Vernooij-Dassen M.J., Thijssen M.,
Dekker J., Hoefnagels W.H., Rikkert M.G.O. (2006).
Community Based Occupational Therapy for
Patients with Dementia and their Care Givers:
Randomised Controlled Trial. BMJ, 333(7580):
1196.
189 Bherer L., Erickson K.I., Liu-Ambrose T.
(2013). A Review of the Effects of Physical Activity
and Exercise on Cognitive and Brain Functions in
Older Adults. Journal of Aging Research, 657508.
190 Giacino J.T., Whyte J., Bagiella E., et al. (2012).
Placebo-controlled trial of amantadine for severe
traumatic brain injury. New England Journal of
Medicine, 366(9), 819–826.
191 Alexopoulos G.S., Katz I.R., Reynolds C.F. 3rd,
Carpenter D., Docherty J.P., Ross R.W. (2001).
Pharmacotherapy of depression in older patients: a
summary of the expert consensus guidelines.
Journal of Psychiatric Practice, 7(6), 361–376.
192 Arean P.A., Cook B.L. (2002). Psychotherapy
and combined psychotherapy/pharmacotherapy for
late life depression. Biological Psychiatry, 52(3),
293–303.
193 Hollon S.D., Jarrett R.B., Nierenberg A.A.,
Thase M.E., Trivedi M., Rush A.J. (2005).
Psychotherapy and medication in the treatment of
adult and geriatric depression: which monotherapy
or combined treatment? Journal of Clinical
Psychiatry, 66(4), 455–468.
194 Wagenaar D., Colenda C.C., Kreft M., Sawade
J., Gardiner J., Poverejan E. (2003). Treating
depression in nursing homes: practice guidelines in
the real world. J Am Osteopath Assoc. 103(10), 465–
469.
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increase opportunities for psychosocial
interaction.195
Accurate assessment of cognitive
function and mental status of patients
and residents in PAC would be expected
to have a positive impact on the
National Quality Strategy’s domains of
patient and family engagement, patient
safety, care coordination, clinical
process/effectiveness, and efficient use
of health care resources. For example,
standardized assessment of cognitive
function and mental status of patients
and residents in PAC will support
establishing a baseline for identifying
changes in cognitive function and
mental status (for example, delirium),
anticipating the patient or resident’s
ability to understand and participate in
treatments during a PAC stay, ensuring
patient and resident safety (for example,
risk of falls), and identifying appropriate
support needs at the time of discharge
or transfer. Standardized assessment
data elements will enable or support
clinical decision-making, early clinical
intervention, as well as person-centered,
high quality care through: Facilitating
better care continuity and coordination;
better data exchange and
interoperability between settings; and
longitudinal outcome analysis. Hence,
reliable data elements assessing
cognitive impairment and mental status
are needed to initiate a care plan that
can best manage a patient or resident’s
prognosis and reduce the possibility of
adverse events.
i. Brief Interview for Mental Status
(BIMS)
We are proposing that the data
elements that comprise the Brief
Interview for Mental Status meet the
definition of standardized patient
assessment data for cognitive function
and mental status under section
1899B(b)(1)(B)(ii) of the Act. The
proposed data elements consist of seven
BIMS questions that result in a cognitive
function score. For more information on
the BIMS, we refer readers to the
document titled, Proposed Measure
Specifications and Standardized Data
Elements for CY 2018 HH QRP Notice of
Proposed Rulemaking, available at
https://www.cms.gov/Medicare/QualityInitiatives-Patient-AssessmentInstruments/HomeHealthQualityInits/
HHQIQualityMeasures.html.
The BIMS is a performance-based
cognitive assessment that assesses
repetition, recall with and without
195 Crespy S.D., Van Haitsma K., Kleban M., Hann
C.J. Reducing Depressive Symptoms in Nursing
Home Residents: Evaluation of the Pennsylvania
Depression Collaborative Quality Improvement
Program. J Healthc Qual. 2016. Vol. 38, No. 6, pp.
e76–e88.
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prompting, and temporal orientation. It
was developed to be a brief screener to
assess cognition, with a focus on
learning and memory. Dementia and
cognitive impairment are associated
with long-term functional dependence
and, consequently, poor quality of life,
increased health care costs, and
mortality.196 This makes assessment of
mental status and early detection of
cognitive decline or impairment critical
in the PAC setting. The intensity of
routine nursing care is higher for
patients and residents with cognitive
impairment than for those without, and
dementia is a significant variable in
predicting readmission after discharge
to the community from PAC
providers.197
The BIMS data elements are currently
in use in two of the PAC assessments:
The MDS 3.0 in SNFs and the IRF–PAI
in IRFs. The BIMS was tested in the
PAC PRD where it was found to have
substantial to almost perfect agreement
for inter-rater reliability (kappa range of
0.71 to 0.91) when tested in all four PAC
settings.198 Clinical and subject matter
expert advisors working with our data
element contractor agreed that the BIMS
is feasible for use by PAC providers.
Additionally, discussions during a TEP
convened on April 6 and 7, 2016,
demonstrated support for the BIMS. The
Development and Maintenance of PostAcute Care Cross-Setting Standardized
Patient Assessment Data Technical
Expert Panel Summary Report is
available at https://www.cms.gov/
Medicare/Quality-Initiatives-PatientAssessment-Instruments/Post-AcuteCare-Quality-Initiatives/IMPACT-Act-of2014/IMPACT-Act-Downloads-andVideos.html.
To solicit additional feedback on the
BIMS, we requested public comment
from August 12 to September 12, 2016.
Many commenters expressed support
for use of the BIMS, noting that it is
reliable, feasible to use across settings,
and will provide useful information
about patients and residents. These
comments noted that the data collected
through the BIMS will provide a clearer
picture of patient or resident
complexity, help with the care planning
196 Aguero-Torres, H., Fratiglioni, L., Guo, Z.,
¨
Viitanen, M., von Strauss, E., & Winblad, B. (1998).
‘‘Dementia is the major cause of functional
dependence in the elderly: 3-year follow-up data
from a population-based study.’’ Am J of Public
Health 88(10): 1452–1456.
197 RTI International. Proposed Measure
Specifications for Measures Proposed in the FY
2017 LTCH QRP NPRM. Research Triangle Park,
NC. 2016.
198 Gage B., Morley M., Smith L., et al. (2012).
Post-Acute Care Payment Reform Demonstration
(Final report, Volume 2 of 4). Research Triangle
Park, NC: RTI International.
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process, and be useful during care
transitions and when coordinating
across providers. A full report of the
comments is available at https://
www.cms.gov/Medicare/QualityInitiatives-Patient-AssessmentInstruments/Post-Acute-Care-QualityInitiatives/IMPACT-Act-of-2014/
IMPACT-Act-Downloads-andVideos.html.
Therefore, we are proposing to adopt
the BIMS for use in the HH QRP. We are
proposing to add the data elements that
comprise the BIMS to the OASIS, and
that HHAs would be required to report
these data at SOC/ROC between January
1, 2019 and June 30, 2019. Following
the initial two quarters of reporting for
the CY 2020 HH QRP, subsequent years
for the HH QRP would be based on 12
months of such data reporting beginning
with July 1, 2019 through June 30, 2020
for the CY 2021 HH QRP. The BIMS
data elements would be assessed at
SOC/ROC only due to the relatively
stable nature of the types of cognitive
function assessed by the BIMS, making
it unlikely that a patient’s score on this
assessment would change between the
start and end of care. Assessment at
discharge would introduce additional
burden without improving the quality or
usefulness of the data, and we believe
it is unnecessary.
We are inviting public comment on
these proposals.
ii. Confusion Assessment Method
(CAM)
We are proposing that the data
elements that comprise the Confusion
Assessment Method (CAM) meet the
definition of standardized patient
assessment data for cognitive function
and mental status under section
1899B(b)(1)(B)(ii) of the Act. The CAM
is a six-question instrument that screens
for overall cognitive impairment, as well
as distinguishes delirium or reversible
confusion from other types of cognitive
impairment. For more information on
the CAM, we refer readers to the
document titled, Proposed Measure
Specifications and Standardized Data
Elements for CY 2018 HH QRP Notice of
Proposed Rulemakings, available at
https://www.cms.gov/Medicare/QualityInitiatives-Patient-AssessmentInstruments/HomeHealthQualityInits/
HHQIQualityMeasures.html.
The CAM was developed to identify
the signs and symptoms of delirium. It
results in a score that suggests whether
the patient or resident should be
assigned a diagnosis of delirium.
Because patients and residents with
multiple comorbidities receive services
from PAC providers, it is important to
assess delirium, as it is associated with
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a high mortality rate and prolonged
duration of stay in hospitalized older
adults with dementia.199 Assessing for
signs and symptoms of delirium is
clinically relevant for care planning by
PAC providers.
The CAM is currently in use in two
of the PAC assessments: The MDS 3.0 in
SNFs and the LCDS in LTCHs. The
CAM was tested in the PAC PRD where
it was found to have substantial
agreement for inter-rater reliability for
the ‘‘Inattention and Disorganized
Thinking’’ questions (kappa range of
0.70 to 0.73); and moderate agreement
for the ‘‘Altered Level of
Consciousness’’ question (kappa of
0.58).200
Clinical and subject matter expert
advisors working with our data element
contractor agreed that the CAM is
feasible for use by PAC providers, that
it assesses key aspects of cognition, and
that this information about patient or
resident cognition would be clinically
useful both within and across PAC
provider types. The CAM was also
supported by a TEP that discussed and
rated candidate data elements during a
meeting on April 6 and 7, 2016. The
Development and Maintenance of PostAcute Care Cross-Setting Standardized
Patient Assessment Data Technical
Expert Panel Summary Report is
available at https://www.cms.gov/
Medicare/Quality-Initiatives-PatientAssessment-Instruments/Post-AcuteCare-Quality-Initiatives/IMPACT-Act-of2014/IMPACT-Act-Downloads-andVideos.html. We requested public
comment on the CAM from August 12
to September 12, 2016. Many
commenters expressed support for use
of the CAM, noting that it would
provide important information for care
planning and care coordination, and
therefore, contribute to quality
improvement. The commenters noted it
is particularly helpful in distinguishing
delirium and reversible confusion from
other types of cognitive impairment. A
full report of the comments is available
at https://www.cms.gov/Medicare/
Quality-Initiatives-Patient-AssessmentInstruments/Post-Acute-Care-QualityInitiatives/IMPACT-Act-of-2014/
IMPACT-Act-Downloads-andVideos.html.
Therefore, we are proposing to add
the CAM data elements to the OASIS,
199 Fick, D.M., Steis, M.R., Waller, J.L., & Inouye,
S.K. (2013). ‘‘Delirium superimposed on dementia
is associated with prolonged length of stay and poor
outcomes in hospitalized older adults.’’ J of
Hospital Med 8(9): 500–505.
200 Gage B., Morley M., Smith L., et al. (2012).
Post-Acute Care Payment Reform Demonstration
(Final report, Volume 2 of 4). Research Triangle
Park, NC: RTI International.
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and that HHAs would be required to
report these data for the CY 2020 HH
QRP at SOC/ROC and discharge
between January 1, 2019 and June 30,
2019. Following the initial two quarters
of reporting for the CY 2020 HH QRP,
subsequent years for the HH QRP would
be based on 12 months of such data
reporting beginning with July 1, 2019
through June 30, 2020 for the CY 2021
HH QRP.
We are inviting public comment on
these proposals.
iii. Behavioral Signs and Symptoms
We are proposing that the Behavioral
Signs and Symptoms data elements
meet the definition of standardized
patient assessment data for cognitive
function and mental status under
section 1899B(b)(1)(B)(ii) of the Act. The
proposed data elements consist of three
Behavioral Signs and Symptoms
questions and result in three scores that
categorize patients as having or not
having certain types of behavioral signs
and symptoms. For more information on
the Behavioral Signs and Symptoms
data elements, we refer readers to the
document titled, Proposed Measure
Specifications and Standardized Data
Elements for CY 2018 HH QRP Notice of
Proposed Rulemaking, available at
https://www.cms.gov/Medicare/QualityInitiatives-Patient-AssessmentInstruments/HomeHealthQualityInits/
HHQIQualityMeasures.html.
The questions included in the
Behavioral Signs and Symptoms group
assess whether the patient or resident
has exhibited any behavioral symptoms
that may indicate cognitive impairment
or other mental health issues during the
assessment period, including physical,
verbal, and other disruptive or
dangerous behavioral symptoms, but
excluding patient wandering. Such
behaviors can indicate unrecognized
needs and care preferences and are
associated most commonly with
dementia and other cognitive
impairment, and less commonly with
adverse drug events, mood disorders,
and other conditions.201 Assessing
behavioral disturbances can lead to
early intervention, patient- and residentcentered care planning, clinical decision
support, and improved staff and patient
or resident safety. Assessment and
documentation of these behaviors can
help inform care planning and patient
transitions, and provide important
information about resource use.
Data elements that capture behavioral
symptoms are currently included in two
201 Desai A, Grossbert G. Recognition and
management of behavioral disturbances in
dementia. The Primary Care Companion to the
Journal of Clinical Psychiatry. 2001; 3(3):93–109.
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of the PAC assessments: The MDS 3.0 in
SNFs and the OASIS–C2 in HHAs. In
the MDS, each question includes four
response options ranging from
‘‘behavior not exhibited’’ (0) to behavior
‘‘occurred daily’’ (3). The OASIS–C2
includes some similar data elements
which record the frequency of
disruptive behaviors on a 6-point scale
ranging from ‘‘never’’ (0) to ‘‘at least
daily’’ (5). Data elements that mirror
those used in the MDS and serve the
same assessment purpose were tested in
post-acute providers in the PAC PRD
and found to be clinically relevant,
meaningful for care planning, and
feasible for use in each of the four PAC
settings.202
The proposed data elements were
supported by comments from the
Standardized Patient Assessment Data
TEP held by our data element
contractor. The TEP identified patient
and resident behaviors as an important
consideration for resource intensity and
care planning, and affirmed the
importance of the standardized
assessment of patient behaviors through
data elements such as those in use in the
MDS. The Development and
Maintenance of Post-Acute Care CrossSetting Standardized Patient
Assessment Data Technical Expert Panel
Summary Report is available at https://
www.cms.gov/Medicare/QualityInitiatives-Patient-AssessmentInstruments/Post-Acute-Care-QualityInitiatives/IMPACT-Act-of-2014/
IMPACT-Act-Downloads-andVideos.html.
Because the PAC PRD version of the
Behavioral Signs and Symptoms data
elements were previously tested across
PAC providers, we solicited additional
feedback on this version of the data
elements by including these data
elements in a call for public comment
that was open from August 12 to
September 12, 2016. Consistent with the
TEP discussion on the importance of
patient and resident behaviors, many
commenters expressed support for use
of the Behavioral Signs and Symptoms
data elements, noting that they would
provide useful information about
patient and resident behavior at both
admission and discharge, and contribute
to care planning regarding the most
appropriate treatment and resource use
for the patient or resident. Public
comment also supported the use of a
highly similar MDS version of the data
elements to provide continuity with
existing assessment processes in SNFs.
202 Gage B., Morley M., Smith L., et al. (2012).
Post-Acute Care Payment Reform Demonstration
(Final report, Volume 2 of 4). Research Triangle
Park, NC: RTI International.
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A full report of the comments is
available at https://www.cms.gov/
Medicare/Quality-Initiatives-PatientAssessment-Instruments/Post-AcuteCare-Quality-Initiatives/IMPACT-Act-of2014/IMPACT-Act-Downloads-andVideos.html.
Therefore, we are proposing the MDS
version of the Behavioral Signs and
Symptoms data elements because they
focus more closely on behavioral
symptoms than the OASIS data
elements, and include more detailed
response categories than those used in
the PAC PRD version, capturing more
information about the frequency of
behaviors. We are proposing that HHAs
would be required to report these data
for the CY 2020 HH QRP at SOC/ROC
and discharge between January 1, 2019
and June 30, 2019. Following the initial
two quarters of reporting for the CY
2020 HH QRP, subsequent years for the
HH QRP would be based on 12 months
of such data reporting beginning with
July 1, 2019 through June 30, 2020 for
the CY 2021 HH QRP.
We are inviting public comment on
these proposals.
iv. Patient Health Questionnaire-2
(PHQ–2)
We are proposing that the PHQ–2 data
elements meet the definition of
standardized patient assessment data for
cognitive function and mental status
under section 1899B(b)(1)(B)(ii) of the
Act. The proposed data elements consist
of the PHQ–2 two-item questionnaire
that assesses the cardinal criteria for
depression: depressed mood and
anhedonia (inability to feel pleasure).
For more information on the PHQ–2, we
refer readers to the document titled,
Proposed Measure Specifications and
Standardized Data Elements for CY
2018 HH QRP Notice of Proposed
Rulemaking, available at https://
www.cms.gov/Medicare/QualityInitiatives-Patient-AssessmentInstruments/HomeHealthQualityInits/
HHQIQualityMeasures.html.
Depression is a common mental
health condition that is often missed
and under-recognized. Assessing
depression helps PAC providers better
understand the needs of their patients
and residents by: Prompting further
evaluation (that is, to establish a
diagnosis of depression); elucidating the
patient’s or resident’s ability to
participate in therapies for conditions
other than depression during their stay;
and identifying appropriate ongoing
treatment and support needs at the time
of discharge. A PHQ–2 score beyond a
predetermined threshold signals the
need for additional clinical assessment
to determine a depression diagnosis.
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The proposed data elements that
comprise the PHQ–2 are currently used
in the OASIS–C2 for HHAs and the
MDS 3.0 for SNFs (as part of the PHQ–
9). The PHQ–2 data elements were
tested in the PAC PRD, where they were
found to have almost perfect agreement
for inter-rater reliability (kappa range of
0.84 to 0.91) when tested by all four
PAC providers.203
Clinical and subject matter expert
advisors working with our data element
contractor agreed that the PHQ–2 is
feasible for use in PAC, that it assesses
key aspects of mental status, and that
this information about patient or
resident mood would be clinically
useful both within and across PAC
settings. We note that both the PHQ–9
and the PHQ–2 were supported by TEP
members who discussed and rated
candidate data elements during a
meeting on April 6 and 7, 2016. They
particularly noted that the brevity of the
PHQ–2 made it feasible with low
burden for both assessors and PAC
patients or residents. The Development
and Maintenance of Post-Acute Care
Cross-Setting Standardized Patient
Assessment Data Technical Expert Panel
Summary Report is available at https://
www.cms.gov/Medicare/QualityInitiatives-Patient-AssessmentInstruments/Post-Acute-Care-QualityInitiatives/IMPACT-Act-of-2014/
IMPACT-Act-Downloads-andVideos.html.
To solicit additional feedback on the
PHQ–2, we requested public comment
from August 12 to September 12, 2016.
Many commenters provided feedback
on using the PHQ–2 for the assessment
of mood. Overall, commenters believed
that collecting these data elements
across PAC settings was appropriate,
given the role that depression plays in
well-being. Several commenters
expressed support for an approach that
would use PHQ–2 as a gateway to the
longer PHQ–9 and would maintain the
reduced burden on most patients and
residents, as well as test administrators,
which is a benefit of the PHQ–2, while
ensuring that the PHQ–9, which
exhibits higher specificity,204 would be
administered for patients and residents
who showed signs and symptoms of
depression on the PHQ–2. Specific
203 Gage B., Smith L., Ross J. et al. (2012). The
Development and Testing of the Continuity
Assessment Record and Evaluation (CARE) Item Set
(Final Report on Reliability Testing, Volume 2 of 3).
Research Triangle Park, NC: RTI International.
204 Arroll B, Goodyear-Smith F, Crengle S, Gunn
J, Kerse N, Fishman T, et al. Validation of PHQ–2
and PHQ–9 to screen for major depression in the
primary care population. Annals of family
medicine. 2010;8(4):348–53. doi: 10.1370/afm.1139
pmid:20644190; PubMed Central PMCID:
PMC2906530.
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comments are described in a full report
available at https://www.cms.gov/
Medicare/Quality-Initiatives-PatientAssessment-Instruments/Post-AcuteCare-Quality-Initiatives/IMPACT-Act-of2014/IMPACT-Act-Downloads-andVideos.html.
Therefore, we are proposing to adopt
the PHQ–2 data elements for use in the
HH QRP as standardized patient
assessment data. As noted above in this
section, the PHQ–2 is already included
on the OASIS. HHAs would be required
to report these data for the CY 2020 HH
QRP at SOC/ROC and discharge
between January 1, 2019 and June 30,
2019. Following the initial two quarters
of reporting for the CY 2020 HH QRP,
subsequent years for the HH QRP would
be based on 12 months of such data
reporting beginning with July 1, 2019
through June 30, 2020 for the CY 2021
HH QRP.
We are inviting public comment on
these proposals.
c. Special Services, Treatments, and
Interventions Data
Special services, treatments, and
interventions performed in PAC can
have a major effect on an individual’s
health status, self-image, and quality of
life. The assessment of these special
services, treatments, and interventions
in PAC is important to ensure the
continuing appropriateness of care for
the patients and residents receiving
them, and to support care transitions
from one PAC setting to another, an
acute care hospital, or discharge.
Accurate assessment of special services,
treatments, and interventions of patients
and residents served by PAC providers
are expected to have a positive impact
on the National Quality Strategy’s
domains of patient and family
engagement, patient safety, care
coordination, clinical process/
effectiveness, and efficient use of
healthcare resources.
For example, standardized assessment
of special services, treatments, and
interventions used in PAC can promote
patient and resident safety through
appropriate care planning (for example,
mitigating risks such as infection or
pulmonary embolism associated with
central intravenous access), and
identifying life-sustaining treatments
that must be continued, such as
mechanical ventilation, dialysis,
suctioning, and chemotherapy, at the
time of discharge or transfer.
Standardized assessment of these data
elements will enable or support:
Clinical decision-making and early
clinical intervention; person-centered,
high quality care through, for example,
facilitating better care continuity and
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coordination; better data exchange and
interoperability between settings; and
longitudinal outcome analysis. Hence,
reliable data elements assessing special
services, treatments, and interventions
are needed to initiate a care plan that
can improve, maintain, or best manage
a patient or resident’s condition and
reduce the possibility of adverse events.
We are proposing 15 special services,
treatments, and interventions as
presented below in this section grouped
by cancer treatments, respiratory
treatments, other treatments, and
nutritional approaches. A TEP convened
by our data element contractor provided
input on the 15 data elements for
Special Services, Treatments, and
Interventions. This TEP, held on
January 5 and 6, 2017, opined that these
data elements are appropriate for
standardization because they would
provide useful clinical information to
inform care planning and care
coordination. The TEP affirmed that
assessment of these services and
interventions is standard clinical
practice, and that the collection of these
data by means of a list and checkbox
format would conform with common
workflow for PAC providers. A full
report of the TEP discussion is available
at https://www.cms.gov/Medicare/
Quality-Initiatives-Patient-AssessmentInstruments/Post-Acute-Care-QualityInitiatives/IMPACT-Act-of-2014/
IMPACT-Act-Downloads-andVideos.html.
i. Cancer Treatment: Chemotherapy (IV,
Oral, Other)
We are proposing that the
Chemotherapy (IV, Oral, Other) data
elements meet the definition of
standardized patient assessment data for
special services, treatments, and
interventions under section
1899B(b)(1)(B)(iii) of the Act. The
proposed data elements consist of the
principal Chemotherapy data element
and three sub-elements: IV
Chemotherapy, Oral Chemotherapy, and
Other. For more information on the
Chemotherapy (IV, Oral, Other) data
elements, we refer readers to the
document titled, https://www.cms.gov/
Medicare/Quality-Initiatives-PatientAssessment-Instruments/HomeHealth
QualityInits/HHQIQuality
Measures.html.
Chemotherapy is a type of cancer
treatment that uses drugs to destroy
cancer cells. It is typically used when a
patient has a malignancy (cancer),
which is a serious, often life-threatening
or life-limiting condition. Both
intravenous (IV) and oral chemotherapy
can have serious side effects, including
nausea/vomiting, extreme fatigue, risk
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of infection due to a suppressed
immune system, anemia, and an
increased risk of bleeding due to low
platelet counts. Oral chemotherapy can
have as many side effects as IV
chemotherapy, but can also be
significantly more convenient and less
resource-intensive to administer.
Because of the toxicity of these agents,
special care must be exercised in
handling and transporting
chemotherapy drugs. IV chemotherapy
may be given by peripheral IV, but is
more commonly given via an indwelling
central line, which raises the risk of
bloodstream infections. Given the
significant burden of malignancy, the
resource intensity of administering
chemotherapy, and the side effects and
potential complications of these highlytoxic medications, assessing the receipt
of chemotherapy is important in the
PAC setting for care planning and
determining resource use.
The need for chemotherapy predicts
resource intensity, both because of the
complexity of administering these
potent, toxic drug combinations under
specific protocols, and because of what
the need for chemotherapy signals about
the patient’s underlying medical
condition. Furthermore, the resource
intensity of IV chemotherapy is higher
than for oral chemotherapy, as the
protocols for administration and the
care of the central line (if present)
require significant resources.
The Chemotherapy (IV, Oral, Other)
data elements consist of a principal data
element and three sub-elements: IV
chemotherapy, which is generally
resource-intensive; oral chemotherapy,
which is less invasive and generally less
intensive with regard to administration
protocols; and a third category provided
to enable the capture of other less
common chemotherapeutic approaches.
This third category is potentially
associated with higher risks and is more
resource intensive due to delivery by
other routes (for example,
intraventricular or intrathecal).
The principal Chemotherapy data
element is currently in use in the MDS
3.0. One proposed sub-element, IV
Chemotherapy, was tested in the PAC
PRD and found feasible for use in each
of the four PAC settings. We solicited
public comment on IV Chemotherapy
from August 12 to September 12, 2016.
Several commenters provided support
for the data element and suggested it be
included as standardized patient
assessment data. Commenters stated
that assessing the use of chemotherapy
services is relevant to share across the
care continuum to facilitate care
coordination and care transitions and
noted the validity of the data element.
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Commenters also noted the importance
of capturing all types of chemotherapy,
regardless of route, and stated that
collecting data only on patients and
residents who received chemotherapy
by IV would limit the usefulness of this
standardized data element. A full report
of the comments is available at https://
www.cms.gov/Medicare/QualityInitiatives-Patient-AssessmentInstruments/Post-Acute-Care-QualityInitiatives/IMPACT-Act-of-2014/
IMPACT-Act-Downloads-andVideos.html.
Therefore, we are proposing that the
Chemotherapy (IV, Oral, Other) data
elements with a principal data element
and three sub-elements meet the
definition of standardized patient
assessment data for special services,
treatments, and interventions under
section 1899B(b)(1)(B)(iii) of the Act.
We are proposing to add the
Chemotherapy (IV, Oral, Other) data
elements to the OASIS, and that HHAs
would be required to report these data
for the CY 2020 HH QRP at SOC/ROC
and discharge between January 1, 2019
and June 30, 2019. Following the initial
two quarters of reporting for the CY
2020 HH QRP, subsequent years for the
HH QRP would be based on 12 months
of such data reporting beginning with
July 1, 2019, through June 30, 2020 for
the CY 2021 HH QRP.
We are inviting public comment on
these proposals.
ii. Cancer Treatment: Radiation
We are proposing that the Radiation
data element meets the definition of
standardized patient assessment data for
special services, treatments, and
interventions under section
1899B(b)(1)(B)(iii) of the Act. The
proposed data element consists of the
single Radiation data element. For more
information on the Radiation data
element, we refer readers to the
document titled, Proposed Measure
Specifications and Standardized Data
Elements for CY 2018 HH QRP Notice of
Proposed Rulemaking, available at
https://www.cms.gov/Medicare/QualityInitiatives-Patient-AssessmentInstruments/HomeHealthQualityInits/
HHQIQualityMeasures.html.
Radiation is a type of cancer treatment
that uses high-energy radioactivity to
stop cancer by damaging cancer cell
DNA, but it can also damage normal
cells. Radiation is an important therapy
for particular types of cancer, and the
resource utilization is high, with
frequent radiation sessions required,
often daily for a period of several weeks.
Assessing whether a patient or resident
is receiving radiation therapy is
important to determine resource
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utilization, as PAC patients and
residents will need to be transported to
and from radiation treatments, and
monitored and treated for side effects
after receiving this intervention.
Therefore, assessing the receipt of
radiation therapy, which would
compete with other care processes given
the time burden, would be important for
care planning and care coordination by
PAC providers.
The Radiation data element is
currently in use in the MDS 3.0. This
data element was not tested in the PAC
PRD. However, public comment and
other expert input on the Radiation data
element supported its importance and
clinical usefulness for patients in PAC
settings, due to the side effects and
consequences of radiation treatment on
patients that need to be considered in
care planning and care transitions. To
solicit additional feedback on the
Radiation data element we are
proposing, we requested public
comment from August 12 to September
12, 2016. Several commenters provided
support for the data element, noting the
relevance of this data element in
facilitating care coordination and
supporting care transitions, the
feasibility of the item, and the potential
for quality improvement. A full report of
the comments is available at https://
www.cms.gov/Medicare/QualityInitiatives-Patient-AssessmentInstruments/Post-Acute-Care-QualityInitiatives/IMPACT-Act-of-2014/
IMPACT-Act-Downloads-andVideos.html.
The proposed data element was
presented to and supported by the TEP
held by our data element contractor on
January 5 and 6, 2017, which opined
that Radiation provided important
corollary information about cancer
treatment in addition to Chemotherapy
(IV, Oral, Other), and that, because
capturing this information is a
customary part of clinical practice, the
proposed data element would be
feasible, reliable, and easily
incorporated into existing workflow.
Therefore, we are proposing that the
Radiation data element meets the
definition of standardized patient
assessment data for special services,
treatments, and interventions under
section 1899B(b)(1)(B)(iii) of the Act.
We are proposing to add the Radiation
data element to the OASIS, and that
HHAs would be required to report these
data for the CY 2020 HH QRP at SOC/
ROC and discharge between January 1,
2019 and June 30, 2019. Following the
initial two quarters of reporting for the
CY 2020 HH QRP, subsequent years for
the HH QRP would be based on 12
months of such data reporting beginning
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with July 1, 2019 through June 30, 2020
for the CY 2021 HH QRP.
We are inviting public comment on
these proposals.
iii. Respiratory Treatment: Oxygen
Therapy (Continuous, Intermittent)
We are proposing that the Oxygen
Therapy (Continuous, Intermittent) data
elements meet the definition of
standardized patient assessment data for
special services, treatments, and
interventions under section
1899B(b)(1)(B)(iii) of the Act. The
proposed data elements consist of the
principal Oxygen data element and two
sub-elements, ‘‘Continuous’’ (whether
the oxygen was delivered continuously,
typically defined as >=14 hours per
day), or ‘‘Intermittent.’’ For more
information on the Oxygen Therapy
(Continuous, Intermittent) data
elements, we refer readers to the
document titled, Proposed Measure
Specifications and Standardized Data
Elements for CY 2018 HH QRP Notice of
Proposed Rulemaking, available at
https://www.cms.gov/Medicare/QualityInitiatives-Patient-AssessmentInstruments/HomeHealthQualityInits/
HHQIQualityMeasures.html.
Oxygen therapy provides a patient or
resident with extra oxygen when
medical conditions such as chronic
obstructive pulmonary disease,
pneumonia, or severe asthma prevent
the patient or resident from getting
enough oxygen from room air. Oxygen
administration is a resource-intensive
intervention, as it requires specialized
equipment such as the source of oxygen,
delivery systems (for example, oxygen
concentrator, liquid oxygen containers,
and high-pressure systems), the patient
interface (for example, nasal cannula or
mask), and other accessories (for
example, regulators, filters, tubing).
These data elements capture patient or
resident use of two types of oxygen
therapy (continuous and intermittent)
which are reflective of intensity of care
needs, including the level of monitoring
and direct patient care required.
Assessing the receipt of this service is
important for care planning and
resource use for PAC providers.
The proposed data elements were
developed based on similar data
elements that assess oxygen therapy,
currently in use in the MDS 3.0
(‘‘Oxygen Therapy’’) and OASIS–C2
(‘‘Oxygen (intermittent or continuous)’’),
and a data element tested in the PAC
PRD that focused on intensive oxygen
therapy (‘‘High O2 Concentration
Delivery System with FiO2 > 40%’’).
As a result of input from expert
advisors, we solicited public comment
on the single data element, Oxygen
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(inclusive of intermittent and
continuous oxygen use), from August 12
to September 12, 2016. Several
commenters supported the importance
of the Oxygen data element, noting
feasibility of this item in PAC, and the
relevance in facilitating care
coordination and supporting care
transitions, but suggesting that the
extent of oxygen use be documented. A
full report of the comments is available
at https://www.cms.gov/Medicare/
Quality-Initiatives-Patient-AssessmentInstruments/Post-Acute-Care-QualityInitiatives/IMPACT-Act-of-2014/
IMPACT-Act-Downloads-andVideos.html.
As a result of public comment and
input from expert advisors about the
importance and clinical usefulness of
documenting the extent of oxygen use,
we expanded the single data element to
include two sub-elements, intermittent
and continuous.
Therefore, we are proposing that the
Oxygen Therapy (Continuous,
Intermittent) data elements with a
principal data element and two subelements meet the definition of
standardized patient assessment data for
special services, treatments, and
interventions under section
1899B(b)(1)(B)(iii) of the Act. We are
proposing to expand the existing
Oxygen (intermittent or continuous)data element in the OASIS to include
sub-elements for Continuous and
Intermittent, and that HHAs would be
required to report these data for the CY
2020 HH QRP at SOC/ROC and
discharge between January 1, 2019 and
June 30, 2019. Following the initial two
quarters of reporting for the CY 2020 HH
QRP, subsequent years for the HH QRP
would be based on 12 months of such
data reporting beginning with July 1,
2019 through June 30, 2020 for the CY
2021 HH QRP.
We are inviting public comment on
these proposals.
iv. Respiratory Treatment: Suctioning
(Scheduled, As needed)
We are proposing that the Suctioning
(Scheduled, As needed) data elements
meet the definition of standardized
patient assessment data for special
services, treatments, and interventions
under section 1899B(b)(1)(B)(iii) of the
Act. The proposed data elements consist
of the principal Suctioning data
element, and two sub-elements,
‘‘Scheduled’’ and ‘‘As needed.’’ These
sub-elements capture two types of
suctioning. ‘‘Scheduled’’ indicates
suctioning based on a specific
frequency, such as every hour. ‘‘As
needed’’ means suctioning only when
indicated. For more information on the
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Suctioning (Scheduled, As needed) data
elements, we refer readers to the
document titled, Proposed Measure
Specifications and Standardized Data
Elements for CY 2018 HH QRP Notice of
Proposed Rulemaking, available at
https://www.cms.gov/Medicare/QualityInitiatives-Patient-AssessmentInstruments/HomeHealthQualityInits/
HHQIQualityMeasures.html.
Suctioning is an intervention used to
clear secretions from the airway when a
person cannot clear those secretions on
his or her own. It is done by aspirating
secretions through a catheter connected
to a suction source. Types of suctioning
include oropharyngeal and
nasopharyngeal suctioning, nasotracheal
suctioning, and suctioning through an
artificial airway such as a tracheostomy
tube. Oropharyngeal and
nasopharyngeal suctioning are a key
part of many patients’ care plans, both
to prevent the accumulation of
secretions that can lead to aspiration
pneumonia (a common condition in
patients with inadequate gag reflexes),
and to relieve obstructions from mucus
plugging during an acute or chronic
respiratory infection, which can often
lead to desaturation and increased
respiratory effort. Suctioning can be
done on a scheduled basis if the patient
is judged to clinically benefit from
regular interventions; or can be done as
needed, such as when secretions
become so copious that gurgling or
choking is noted, or a sudden
desaturation occurs from a mucus plug.
As suctioning is generally performed by
a care provider rather than
independently, this intervention can be
quite resource-intensive if it occurs
every hour, for example, rather than
once a shift. It also signifies an
underlying medical condition that
prevents the patient from clearing his/
her secretions effectively (such as after
a stroke, or during an acute respiratory
infection). Generally, suctioning is
necessary to ensure that the airway is
clear of secretions which, if left, can
inhibit successful oxygenation of the
individual and/or lead to infection. The
intent of suctioning is to maintain a
patent airway, the loss of which can
lead to death, or complications
associated with hypoxia.
The proposed data elements are based
on an item currently in use in the MDS
3.0 (‘‘Suctioning’’ without the two subelements), and data elements tested in
the PAC PRD that focused on the
frequency of suctioning required for
patients with tracheostomies (‘‘Trach
Tube with Suctioning: Specify most
intensive frequency of suctioning during
stay [Every ll hours]’’).
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Clinical and subject matter expert
advisors working with our data element
contractor agreed that the proposed
Suctioning (Scheduled, As needed) data
elements are feasible for use in PAC,
and that they indicate important
treatment that would be clinically
useful to capture both within and across
PAC providers. We solicited public
comment on the suctioning data
element currently included in the MDS
3.0 from August 12 to September 12,
2016. Several commenters wrote in
support of this data element, noting
feasibility of this item in PAC, and the
relevance of this data element to
facilitating care coordination and
supporting care transitions. We also
received comments suggesting that we
examine the frequency of suctioning to
better understand the use of staff time,
the impact on a patient or resident’s
capacity to speak and swallow, and
intensity of care required. Based on
these comments, we decided to add two
sub-elements (scheduled and as needed)
to the suctioning element. The proposed
data elements, Suctioning (Scheduled,
As needed) includes both the principal
suctioning data element that is included
on the MDS 3.0 and two sub-elements,
‘‘scheduled’’ and ‘‘as needed.’’ A full
report of the comments is available at
https://www.cms.gov/Medicare/QualityInitiatives-Patient-AssessmentInstruments/Post-Acute-Care-QualityInitiatives/IMPACT-Act-of-2014/
IMPACT-Act-Downloads-andVideos.html.
A TEP convened by the data element
contractor provided input on the
proposed data elements. This TEP, held
on January 5 and 6, 2017, opined that
these data elements are appropriate for
standardization because they would
provide useful clinical information to
inform care planning and care
coordination. The TEP affirmed that
assessment of these services and
interventions is standard clinical
practice. A full report of the TEP
discussion is available at https://
www.cms.gov/Medicare/QualityInitiatives-Patient-AssessmentInstruments/Post-Acute-Care-QualityInitiatives/IMPACT-Act-of-2014/
IMPACT-Act-Downloads-andVideos.html.
Therefore, we are proposing that the
Suctioning (Scheduled, As needed) data
elements with a principal data element
and two sub-elements meet the
definition of standardized patient
assessment data for special services,
treatments, and interventions under
section 1899B(b)(1)(B)(iii) of the Act.
We are proposing to add the Suctioning
(Scheduled, As needed) data elements
to the OASIS, and that HHAs would be
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required to report these data for the CY
2020 HH QRP at SOC/ROC and
discharge between January 1, 2019, and
June 30, 2019. Following the initial two
quarters of reporting for the CY 2020 HH
QRP, subsequent years for the HH QRP
would be based on 12 months of such
data reporting beginning with July 1,
2019, through June 30, 2020 for the CY
2021 HH QRP.
We are inviting public comment on
these proposals.
v. Respiratory Treatment: Tracheostomy
Care
We are proposing that the
Tracheostomy Care data element meets
the definition of standardized patient
assessment data for special services,
treatments, and interventions under
section 1899B(b)(1)(B)(iii) of the Act.
The proposed data element consists of
the single Tracheostomy Care data
element. For more information on the
Tracheostomy Care data element, we
refer readers to the document titled,
Proposed Measure Specifications and
Standardized Data Elements for CY
2018 HH QRP Notice of Proposed
Rulemaking, available at https://
www.cms.gov/Medicare/QualityInitiatives-Patient-AssessmentInstruments/HomeHealthQualityInits/
HHQIQualityMeasures.html.
A tracheostomy provides an airway to
help a patient or resident breathe when
the usual route for breathing is
obstructed or impaired. Generally, in all
of these cases, suctioning is necessary to
ensure that the tracheostomy tube is
clear of secretions which can inhibit
successful oxygenation of the
individual, or accumulate and cause
infection. Often, individuals with
tracheostomies are also receiving
supplemental oxygenation. The
presence of a tracheostomy, whether
permanent or temporary, warrants
careful monitoring and immediate
intervention if the tracheostomy tube
becomes occluded or dislodged. While
in rare cases the presence of a
tracheostomy is not associated with
increased care demands (and in some of
those instances, the care of the ostomy
is performed by the patient), in general
the presence of such a device is
associated with increased patient risk
and resource use. Tracheostomy care
should include close monitoring to
prevent occlusion or decannulation,
skin infection or necrosis, and other
complications to ensure adequate air
flow and oxygenation. In addition to
suctioning, skin care, dressing changes,
and replacement or cleaning of the
tracheostomy cannula (tube), is also a
critical part of the tracheostomy care
plan. Regular cleaning and suctioning is
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important in preventing infections such
as pneumonia, preventing skin
breakdown, and preventing any
occlusions leading to inadequate
oxygenation.
The proposed data element is
currently in use in the MDS 3.0
(‘‘Tracheostomy care’’). Data elements
(‘‘Trach Tube with Suctioning’’) that
were tested in the PAC PRD included an
equivalent principal data element on the
presence of a tracheostomy. This data
element was found feasible for use in
each of the four PAC settings as the data
collection aligned with usual work flow.
Clinical and subject matter expert
advisors working with our data element
contractor agreed that the Tracheostomy
Care data element is feasible for use in
PAC and that it assesses an important
treatment that would be clinically
useful both within and across PAC
provider types.
We solicited public comment on this
data element from August 12 to
September 12, 2016. Several
commenters wrote in support of this
data element, noting the feasibility of
this item in PAC, and the relevance of
this data element to facilitating care
coordination and supporting care
transitions. A full report of the
comments is available at https://
www.cms.gov/Medicare/QualityInitiatives-Patient-AssessmentInstruments/Post-Acute-Care-QualityInitiatives/IMPACT-Act-of-2014/
IMPACT-Act-Downloads-andVideos.html.
A TEP convened by the data element
contractor provided input on the
proposed data elements. This TEP, held
on January 5 and 6, 2017, opined that
these data elements are appropriate for
standardization because they would
provide useful clinical information to
inform care planning and care
coordination. The TEP affirmed that
assessment of these services and
interventions is standard clinical
practice. A full report of the TEP
discussion is available at https://
www.cms.gov/Medicare/QualityInitiatives-Patient-AssessmentInstruments/Post-Acute-Care-QualityInitiatives/IMPACT-Act-of-2014/
IMPACT-Act-Downloads-andVideos.html.
Therefore, we are proposing that the
Tracheostomy Care data element meets
the definition of standardized patient
assessment data for special services,
treatments, and interventions under
section 1899B(b)(1)(B)(iii) of the Act.
We are proposing to add the
Tracheostomy Care data element to the
OASIS, and that HHAs would be
required to report these data for the CY
2020 HH QRP at SOC/ROC and
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discharge between January 1, 2019 and
June 30, 2019. Following the initial two
quarters of reporting for the CY 2020 HH
QRP, subsequent years for the HH QRP
would be based on 12 months of such
data reporting beginning with July 1,
2019, through June 30, 2020 for the CY
2021 HH QRP.
We are inviting public comment on
these proposals.
vi. Respiratory Treatment: Non-Invasive
Mechanical Ventilator (BiPAP, CPAP)
We are proposing that the Noninvasive Mechanical Ventilator (Bilevel
Positive Airway Pressure [BiPAP],
Continuous Positive Airway Pressure
[CPAP]) data elements meet the
definition of standardized patient
assessment data for special services,
treatments, and interventions under
section 1899B(b)(1)(B)(iii) of the Act.
The proposed data elements consist of
the principal Non-invasive Mechanical
Ventilator data element and two subelements, BiPAP and CPAP. For more
information on the Non-invasive
Mechanical Ventilator (BiPAP, CPAP)
data elements, we refer readers to the
document titled, Proposed Measure
Specifications and Standardized Data
Elements for CY 2018 HH QRP Notice of
Proposed Rulemaking, available at
https://www.cms.gov/Medicare/QualityInitiatives-Patient-AssessmentInstruments/HomeHealthQualityInits/
HHQIQualityMeasures.html.
BiPAP and CPAP are respiratory
support devices that prevent the airways
from closing by delivering slightly
pressurized air via electronic cycling
throughout the breathing cycle (Bilevel
Positive Airway Pressure, referred to as
BiPAP) or through a mask continuously
(Continuous PAP, referred to as CPAP).
Assessment of non-invasive mechanical
ventilation is important in care
planning, as both CPAP and BiPAP are
resource-intensive (although less so
than invasive mechanical ventilation)
and signify a more complex or
underlying medical condition.
Particularly when used in the context of
acute illness or progressive respiratory
decline, additional staff (for example,
respiratory therapists) are required to
monitor and adjust the CPAP and BiPAP
settings. Additionally the patient or
resident may require more nursing
assessment, education, and
interventions, such as pulse oximetry or
venipuncture for blood gas evaluation.
Data elements that assess BiPAP and
CPAP are currently included on the
OASIS–C2 for HHAs (‘‘Continuous/Bilevel positive airway pressure’’), LCDS
for the LTCH setting (‘‘Non-invasive
Ventilator (BIPAP, CPAP)’’), and the
MDS 3.0 for the SNF setting (‘‘BiPAP/
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CPAP’’). A data element that focused on
CPAP was tested across the four PAC
providers in the PAC PRD study and
found to be feasible for standardization.
All of these data elements assess BiPAP
or CPAP with a single check box, not
separately.
Clinical and subject matter expert
advisors working with our data element
contractor agreed that the standardized
assessment of Non-invasive Mechanical
Ventilator (BiPAP, CPAP) data elements
would be feasible for use in PAC, and
assess an important treatment that
would be clinically useful both within
and across PAC provider types.
To solicit additional feedback on the
form of the Non-invasive Mechanical
Ventilator (BiPAP, CPAP) data elements
best suited for standardization, we
requested public comment on a single
data element, BiPAP/CPAP, equivalent
(but for labeling) to what is currently in
use on the MDS, OASIS, and LCDS,
from August 12 to September 12, 2016.
Several commenters wrote in support of
this data element, noting the feasibility
of these items in PAC, and the relevance
of these data elements for facilitating
care coordination and supporting care
transitions. In addition, there was
support in the public comment
responses for separating out BiPAP and
CPAP as distinct sub-elements, as they
are therapies used for different types of
patients and residents. A full report of
the comments is available at https://
www.cms.gov/Medicare/QualityInitiatives-Patient-AssessmentInstruments/Post-Acute-Care-QualityInitiatives/IMPACT-Act-of-2014/
IMPACT-Act-Downloads-andVideos.html.
A TEP convened by the data element
contractor provided input on the
proposed data elements. This TEP, held
on January 5 and 6, 2017, opined that
these data elements are appropriate for
standardization because they would
provide useful clinical information to
inform care planning and care
coordination. The TEP affirmed that
assessment of these services and
interventions is standard clinical
practice. A full report of the TEP
discussion is available at https://
www.cms.gov/Medicare/QualityInitiatives-Patient-AssessmentInstruments/Post-Acute-Care-QualityInitiatives/IMPACT-Act-of-2014/
IMPACT-Act-Downloads-andVideos.html.
Therefore, we are proposing that the
Non-invasive Mechanical Ventilator
(BiPAP, CPAP) data elements with a
principal data element and two subelements meet the definition of
standardized patient assessment data for
special services, treatments, and
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interventions under section
1899B(b)(1)(B)(iii) of the Act. We are
proposing that the existing
‘‘Continuous/Bi-level positive airway
pressure’’ data element in the OASIS be
expanded and relabeled as the Noninvasive Mechanical Ventilator (BiPAP,
CPAP) data elements, and that HHAs
would be required to report these data
for the CY 2020 HH QRP at SOC/ROC
and discharge between January 1, 2019
and June 30, 2019. Following the initial
two quarters of reporting for the CY
2020 HH QRP, subsequent years for the
HH QRP would be based on 12 months
of such data reporting beginning with
July 1, 2019, through June 30, 2020 for
the CY 2021 HH QRP.
We are inviting public comment on
these proposals.
vii. Respiratory Treatment: Invasive
Mechanical Ventilator
We are proposing that the Invasive
Mechanical Ventilator data element
meets the definition of standardized
patient assessment data for special
services, treatments, and interventions
under section 1899B(b)(1)(B)(iii) of the
Act. The proposed data element consists
of a single Invasive Mechanical
Ventilator data element. For more
information on the Invasive Mechanical
Ventilator data element, we refer readers
to the document titled, Proposed
Measure Specifications and
Standardized Data Elements for CY
2018 HH QRP Notice of Proposed
Rulemaking, available at https://
www.cms.gov/Medicare/QualityInitiatives-Patient-AssessmentInstruments/HomeHealthQualityInits/
HHQIQualityMeasures.html.
Invasive mechanical ventilation
includes ventilators and respirators that
ventilate the patient through a tube that
extends via the oral airway into the
pulmonary region (intubation), or
through a surgical opening directly into
the trachea (tracheostomy). Thus,
assessment of invasive mechanical
ventilation is important in care planning
and risk mitigation. Ventilation in this
manner is a resource-intensive therapy
associated with life-threatening
conditions without which the patient or
resident would not survive. However,
ventilator use has inherent risks
requiring close monitoring. Failure to
adequately care for the patient or
resident who is ventilator dependent
can lead to iatrogenic events such as
death, pneumonia and sepsis.
Mechanical ventilation further signifies
the complexity of the patient’s
underlying medical or surgical
condition. Of note, invasive mechanical
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ventilation is associated with high daily
and aggregate costs.205
Data elements that capture invasive
mechanical ventilation, but vary in their
level of specificity, are currently in use
in the MDS 3.0 (‘‘Ventilator or
respirator’’), LCDS (‘‘Invasive
Mechanical Ventilator: weaning’’ and
‘‘Invasive Mechanical Ventilator: nonweaning’’), and related data elements
that assess invasive ventilator use and
weaning status were tested in the PAC
PRD (‘‘Ventilator—Weaning’’ and
‘‘Ventilator—Non-Weaning’’) and found
feasible for use in each of the four PAC
settings.
Clinical and subject matter expert
advisors working with our data element
contractor agreed that assessing Invasive
Mechanical Ventilator use is feasible in
PAC, and would be clinically useful
both within and across PAC providers.
To solicit additional feedback on the
form of a data element on this topic that
would be appropriate for
standardization, data elements that
assess invasive ventilator use and
weaning status that were tested in the
PAC PRD (‘‘Ventilator—Weaning’’ and
‘‘Ventilator—Non-Weaning’’) were
included in a call for public comment
that was open from August 12 to
September 12, 2016 because they were
being considered for standardization.
Several commenters wrote in support of
these data elements, highlighting the
importance of this information in
supporting care coordination and care
transitions. Some commenters
expressed concern about the
appropriateness for standardization,
given the prevalence of ventilator
weaning across PAC providers; the
timing of administration; how weaning
is defined; and how weaning status in
particular relates to quality of care.
These comments guided the decision to
propose a single data element focused
on current use of invasive mechanical
ventilation only, and does not attempt
to capture weaning status. A full report
of the comments is available at https://
www.cms.gov/Medicare/QualityInitiatives-Patient-AssessmentInstruments/Post-Acute-Care-QualityInitiatives/IMPACT-Act-of-2014/
IMPACT-Act-Downloads-andVideos.html.
A TEP convened by the data element
contractor provided input on the
proposed data elements. This TEP, held
on January 5 and 6, 2017, opined that
these data elements are appropriate for
standardization because they would
205 Wunsch, H., Linde-Zwirble, W.T., Angus, D.
C., Hartman, M.E., Milbrandt, E.B., & Kahn, J.M.
(2010). ‘‘The epidemiology of mechanical
ventilation use in the United States.’’ Critical Care
Med 38(10): 1947–1953.
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mstockstill on DSK30JT082PROD with PROPOSALS2
provide useful clinical information to
inform care planning and care
coordination. The TEP affirmed that
assessment of these services and
interventions is standard clinical
practice. A full report of the TEP
discussion is available at https://
www.cms.gov/Medicare/QualityInitiatives-Patient-AssessmentInstruments/Post-Acute-Care-QualityInitiatives/IMPACT-Act-of-2014/
IMPACT-Act-Downloads-andVideos.html.
Therefore, we are proposing that the
Invasive Mechanical Ventilator data
element that assesses the use of an
invasive mechanical ventilator, but does
not assess weaning status, meets the
definition of standardized patient
assessment data for special services,
treatments, and interventions under
section 1899B(b)(1)(B)(iii) of the Act.
We are proposing to add the Invasive
Mechanical Ventilator data element to
the OASIS, and that HHAs would be
required to report these data for the CY
2020 HH QRP at SOC/ROC and
discharge between January 1, 2019 and
June 30, 2019. Following the initial two
quarters of reporting for the CY 2020 HH
QRP, subsequent years for the HH QRP
would be based on 12 months of such
data reporting beginning with July 1,
2019 through June 30, 2020 for the CY
2021 HH QRP.
We are inviting public comment on
these proposals.
viii. Other Treatment: Intravenous (IV)
Medications (Antibiotics,
Anticoagulation, Other)
We are proposing that the IV
Medications (Antibiotics,
Anticoagulation, Other) data elements
meet the definition of standardized
patient assessment data for special
services, treatments, and interventions
under section 1899B(b)(1)(B)(iii) of the
Act. The proposed data elements consist
of the principal IV Medications data
element and three sub-elements,
Antibiotics, Anticoagulation, and Other.
For more information on the IV
Medications (Antibiotics,
Anticoagulation, Other) data elements,
we refer readers to the document titled,
Proposed Measure Specifications and
Standardized Data Elements for CY
2018 HH QRP Notice of Proposed
Rulemaking, available at https://
www.cms.gov/Medicare/QualityInitiatives-Patient-AssessmentInstruments/HomeHealthQualityInits/
HHQIQualityMeasures.html.
IV medications are solutions of a
specific medication (for example,
antibiotics, anticoagulants)
administered directly into the venous
circulation via a port or intravenous
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tubing. IV medications are administered
via intravenous push (bolus), single,
intermittent, or continuous infusion
through a catheter placed into the vein
(for example, through central, midline,
or peripheral ports). Further, IV
medications are more resource intensive
to administer than oral medications, and
signify a higher patient complexity (and
often higher severity of illness).
The clinical indications for each of
the sub-elements of the IV Medication
data element (Antibiotics,
Anticoagulants, and Other) are very
different. IV antibiotics are used for
severe infections when: (1) The
bioavailability of the oral form of the
medication would be inadequate to kill
the pathogen; (2) an oral form of the
medication does not exist; or (3) the
patient is unable to take the medication
by mouth. IV anticoagulants refer to
anti-clotting medications (that is, ‘‘blood
thinners’’), often used for the prevention
and treatment of deep vein thrombosis
and other thromboembolic
complications. IV anticoagulants are
commonly used in patients with limited
mobility (either chronically or acutely,
in the post-operative setting), who are at
risk of deep vein thrombosis, or patients
with certain cardiac arrhythmias such as
atrial fibrillation. The indications, risks,
and benefits of each of these classes of
IV medications are distinct, making it
important to assess and monitor each
separately in PAC. Knowing whether or
not patients are receiving IV medication
and the type of medication provided by
each PAC provider will improve quality
of care.
The principal IV Medication data
element is currently in use on the MDS
3.0 and there is a related data element
in OASIS–C2 that collects information
on Intravenous and Infusion Therapies.
One sub-element of the proposed data
elements, IV Anti-coagulants, and two
other data elements related to IV
therapy (IV Vasoactive Medications and
IV Chemotherapy), were tested in the
PAC PRD and found feasible for use in
that the data collection aligned with
usual work flow in each of the four PAC
settings, demonstrating the feasibility of
collecting IV medication information,
including type of IV medication,
through similar data elements in these
settings.
Clinical and subject matter expert
advisors working with our data element
contractor agreed that standardized
collection of information on
medications, including IV medications,
would be feasible in PAC, and assess an
important treatment that would be
clinically useful both within and across
PAC provider types.
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We solicited public comment on a
related data element, Vasoactive
Medications, from August 12 to
September 12, 2016. While commenters
supported this data element with one
noting the importance of this data
element in supporting care transitions,
others criticized the need for collecting
specifically on Vasoactive Medications,
giving feedback that the data element
was too narrowly focused. Additionally,
comments received indicated that the
clinical significance of vasoactive
medications administration alone was
not high enough in PAC to merit
mandated assessment, noting that
related and more useful information
could be captured in an item that
assessed all IV medication use.
Overall, public comment indicated
the importance of including the
additional check box data elements to
distinguish particular classes of
medications. A full report of the
comments is available at https://
www.cms.gov/Medicare/QualityInitiatives-Patient-AssessmentInstruments/Post-Acute-Care-QualityInitiatives/IMPACT-Act-of-2014/
IMPACT-Act-Downloads-andVideos.html.
A TEP convened by the data element
contractor provided input on the
proposed data elements. This TEP, held
on January 5 and 6, 2017, opined that
these data elements are appropriate for
standardization because they would
provide useful clinical information to
inform care planning and care
coordination. The TEP affirmed that
assessment of these services and
interventions is standard clinical
practice. A full report of the TEP
discussion is available at https://
www.cms.gov/Medicare/QualityInitiatives-Patient-AssessmentInstruments/Post-Acute-Care-QualityInitiatives/IMPACT-Act-of-2014/
IMPACT-Act-Downloads-andVideos.html.
Therefore, we are proposing that the
IV Medications (Antibiotics,
Anticoagulation, Other) data elements
with a principal data element and three
sub-elements meet the definition of
standardized patient assessment data for
special services, treatments, and
interventions under section
1899B(b)(1)(B)(iii) of the Act. We are
proposing to add the IV Medications
(Antibiotics, Anticoagulation, Other)
data elements to the OASIS, and that
HHAs would be required to report these
data for the CY 2020 HH QRP at SOC/
ROC and discharge between January 1,
2019 and June 30, 2019. Following the
initial two quarters of reporting for the
CY 2020 HH QRP, subsequent years for
the HH QRP would be based on 12
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months of such data reporting beginning
with July 1, 2019 through June 30, 2020
for the CY 2021 HH QRP.
We are inviting public comment on
these proposals.
mstockstill on DSK30JT082PROD with PROPOSALS2
ix. Other Treatment: Transfusions
We are proposing that the
Transfusions data element meets the
definition of standardized patient
assessment data for special services,
treatments, and interventions under
section 1899B(b)(1)(B)(iii) of the Act.
The proposed data element consists of
the single Transfusions data element.
For more information on the
Transfusions data element, we refer
readers to the document titled, Proposed
Measure Specifications and
Standardized Data Elements for CY
2018 HH QRP Notice of Proposed
Rulemaking, available at https://
www.cms.gov/Medicare/QualityInitiatives-Patient-AssessmentInstruments/HomeHealthQualityInits/
HHQIQualityMeasures.html.
Transfusion refers to introducing
blood, blood products, or other fluid
into the circulatory system of a person.
Blood transfusions are based on specific
protocols, with multiple safety checks
and monitoring required before, during,
and after the infusion to prevent errors
and adverse events. Coordination with
the provider’s blood bank is necessary,
as well as documentation by clinical
staff to ensure compliance with
regulatory requirements. In addition, the
need for transfusions signifies
underlying patient complexity that is
likely to require care coordination and
patient monitoring, and impacts
planning for transitions of care, as
transfusions are not performed by all
PAC providers.
The proposed data element was
selected from three existing assessment
items on transfusions and related
services, currently in use in the MDS 3.0
(‘‘Transfusions’’) and OASIS–C2
(‘‘Intravenous or Infusion Therapy’’),
and a data element tested in the PAC
PRD (‘‘Blood Transfusions’’), that was
found feasible for use in each of the four
PAC settings. We chose to propose the
MDS version because of its greater level
of specificity over the OASIS–C2 data
element. This selection was informed by
expert advisors and reviewed and
supported in the proposed form by the
Standardized Patient Assessment Data
TEP held by our data element contractor
on January 5 and 6, 2017. A full report
of the TEP discussion is available at
https://www.cms.gov/Medicare/QualityInitiatives-Patient-AssessmentInstruments/Post-Acute-Care-QualityInitiatives/IMPACT-Act-of-2014/
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IMPACT-Act-Downloads-andVideos.html.
Therefore, we are proposing that the
Transfusions data element that is
currently in use in the MDS meets the
definition of standardized patient
assessment data for special services,
treatments, and interventions under
section 1899B(b)(1)(B)(iii) of the Act.
We are proposing to add the
Transfusions data element to the OASIS,
and that HHAs would be required to
report these data for the CY 2020 HH
QRP at SOC/ROC and discharge
between January 1, 2019 and June 30,
2019. Following the initial two quarters
of reporting for the CY 2020 HH QRP,
subsequent years for the HH QRP would
be based on 12 months of such data
reporting beginning with July 1, 2019
through June 30, 2020 for the CY 2021
HH QRP.
We are inviting public comment on
these proposals.
x. Other Treatment: Dialysis
(Hemodialysis, Peritoneal Dialysis)
We are proposing that the Dialysis
(Hemodialysis, Peritoneal dialysis) data
elements meet the definition of
standardized patient assessment data for
special services, treatments, and
interventions under section
1899B(b)(1)(B)(iii) of the Act. The
proposed data elements consist of the
principal Dialysis data element and two
sub-elements, Hemodialysis and
Peritoneal dialysis. For more
information on the Dialysis
(Hemodialysis, Peritoneal dialysis) data
elements, we refer readers to the
document titled, Proposed Measure
Specifications and Standardized Data
Elements for CY 2018 HH QRP Notice of
Proposed Rulemaking, available at
https://www.cms.gov/Medicare/QualityInitiatives-Patient-AssessmentInstruments/HomeHealthQualityInits/
HHQIQualityMeasures.html.
Dialysis is a treatment primarily used
to provide replacement for lost kidney
function. Both forms of dialysis
(hemodialysis and peritoneal dialysis)
are resource intensive, not only during
the actual dialysis process but before,
during, and after treatment. Patients and
residents who need and undergo
dialysis procedures are at high risk for
physiologic and hemodynamic
instability from fluid shifts and
electrolyte disturbances, as well as
infections that can lead to sepsis.
Further, patients or residents receiving
hemodialysis are often transported to a
different facility, or at a minimum, to a
different location in the same facility.
Close monitoring for fluid shifts, blood
pressure abnormalities, and other
adverse effects is required prior to,
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35365
during and following each dialysis
session. Nursing staff typically perform
peritoneal dialysis at the bedside, and as
with hemodialysis, close monitoring is
required.
The principal Dialysis data element is
currently included on the MDS 3.0 and
the LCDS v3.0 and assesses the overall
use of dialysis. The sub-elements for
Hemodialysis and Peritoneal dialysis
were tested across the four PAC
providers in the PAC PRD study, and
found to be feasible for standardization.
Clinical and subject matter expert
advisors working with our data element
contractor opined that the standardized
assessment of dialysis is feasible in
PAC, and that it assesses an important
treatment that would be clinically
useful both within and across PAC
providers. As the result of expert and
public feedback, described below, we
decided to propose data elements that
include both the principal Dialysis data
element and the two sub-elements
(hemodialysis and peritoneal dialysis).
The Hemodialysis data element,
which was tested in the PAC PRD, was
included in a call for public comment
that was open from August 12 to
September 12, 2016. Commenters
supported the assessment of
hemodialysis and recommended that
the data element be expanded to include
peritoneal dialysis. Several commenters
supported the Hemodialysis data
element, noting the relevance of this
information for sharing across the care
continuum to facilitate care
coordination and care transitions, the
potential for this data element to be
used to improve quality, and the
feasibility for use in PAC. In addition,
we received comment that the item
would be useful in improving patient
and resident transitions of care. Several
commenters also stated that peritoneal
dialysis should be included in a
standardized data element on dialysis
and recommended collecting
information on peritoneal dialysis in
addition to hemodialysis. The rationale
for including peritoneal dialysis from
commenters included the fact that
patients and residents receiving
peritoneal dialysis will have different
needs at post-acute discharge compared
to those receiving hemodialysis or not
having any dialysis. Based on these
comments, the Hemodialysis data
element was expanded to include a
principal Dialysis data element and two
sub-elements, hemodialysis and
peritoneal dialysis; these are the same
two data elements that were tested in
the PAC PRD. This expanded version,
Dialysis (Hemodialysis, Peritoneal
dialysis), are the data elements being
proposed. A full report of the comments
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is available at https://www.cms.gov/
Medicare/Quality-Initiatives-PatientAssessment-Instruments/Post-AcuteCare-Quality-Initiatives/IMPACT-Act-of2014/IMPACT-Act-Downloads-andVideos.html.
We note that the Dialysis
(Hemodialysis, Peritoneal dialysis) data
elements were also supported by the
TEP that discussed candidate data
elements for Special Services,
Treatments, and Interventions during a
meeting on January 5 and 6, 2017. A full
report of the TEP discussion is available
at https://www.cms.gov/Medicare/
Quality-Initiatives-Patient-AssessmentInstruments/Post-Acute-Care-QualityInitiatives/IMPACT-Act-of-2014/
IMPACT-Act-Downloads-andVideos.html.
Therefore, we are proposing that the
Dialysis (Hemodialysis, Peritoneal
dialysis) data elements with a principal
data element and two sub-elements
meet the definition of standardized
patient assessment data for special
services, treatments, and interventions
under section 1899B(b)(1)(B)(iii) of the
Act. We are proposing to add the
Dialysis (Hemodialysis, Peritoneal
dialysis) data elements to the OASIS,
and that HHAs would be required to
report these data for the CY 2020 HH
QRP at SOC/ROC and discharge
between January 1, 2019 and June 30,
2019. Following the initial two quarters
of reporting for the CY 2020 HH QRP,
subsequent years for the HH QRP would
be based on 12 months of such data
reporting beginning with July 1, 2019
through June 30, 2020 for the CY 2021
HH QRP.
We are inviting public comment on
these proposals.
mstockstill on DSK30JT082PROD with PROPOSALS2
xi. Other Treatment: Intravenous (IV)
Access (Peripheral IV, Midline, Central
Line, Other)
We are proposing that the IV Access
(Peripheral IV, Midline, Central line,
Other) data elements meet the definition
of standardized patient assessment data
for special services, treatments, and
interventions under section
1899B(b)(1)(B)(iii) of the Act. The
proposed data elements consist of the
principal IV Access data element and
four sub-elements, Peripheral IV,
Midline, Central line, and Other. For
more information on the IV Access
(Peripheral IV, Midline, Central line,
Other) data elements, we refer readers to
the document titled, Proposed Measure
Specifications and Standardized Data
Elements for CY 2018 HH QRP Notice of
Proposed Rulemaking, available at
https://www.cms.gov/Medicare/QualityInitiatives-Patient-Assessment-
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Instruments/HomeHealthQualityInits/
HHQIQualityMeasures.html.
Patients or residents with central
lines, including those peripherally
inserted or who have subcutaneous
central line ‘‘port’’ access, always
require vigilant nursing care to ensure
patency of the lines and prevent any
potentially life-threatening events such
as infection, air embolism, or bleeding
from an open lumen. Clinically complex
patients and residents are likely to be
receiving medications or nutrition
intravenously. The sub-elements
included in the IV Access data elements
distinguish between peripheral access
and different types of central access.
The rationale for distinguishing between
a peripheral IV and central IV access is
that central lines confer higher risks
associated with life-threatening events
such as pulmonary embolism, infection,
and bleeding.
The proposed IV Access (Peripheral
IV, Midline, Central line, Other) data
elements are not currently included on
any of the mandated PAC assessment
instruments. However, related data
elements (for example, IV Medication in
MDS 3.0 for SNF, Intravenous or
infusion therapy in OASIS–C2 for
HHAs) currently assess types of IV
infusions or service. Several related data
elements that describe types of IV
infusions and services (for example,
Central Line Management, IV Vasoactive
Medications) were tested across the four
PAC providers in the PAC PRD study,
and found to be feasible for
standardization.
Clinical and subject matter expert
advisors working with our data element
contractor agreed that assessing type of
IV access would be feasible for use in
PAC and that it assesses an important
treatment that would be clinically
useful both within and across PAC
provider types.
We requested public comment on one
of the PAC PRD data elements, Central
Line Management, from August 12 to
September 12, 2016. A central line is
one type of IV access. Commenters
supported the assessment of central line
management and recommended that the
data element be broadened to also
include other types of IV access. Several
commenters supported the data
element, noting feasibility and
importance for facilitating care
coordination and care transitions.
However, a few commenters
recommended that the definition of this
data element be broadened to include
peripherally inserted central catheters
(‘‘PICC lines’’) and midline IVs. Based
on public comment feedback and in
consultation with clinical and subject
matter experts, we expanded the Central
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Line Management data element to
include more types of IV access
(Peripheral IV, Midline, Central line,
Other). This expanded version, IV
Access (Peripheral IV, Midline, Central
line, Other), are the data elements being
proposed. A full report of the comments
is available at https://www.cms.gov/
Medicare/Quality-Initiatives-PatientAssessment-Instruments/Post-AcuteCare-Quality-Initiatives/IMPACT-Act-of2014/IMPACT-Act-Downloads-andVideos.html.
We note that the IV Access
(Peripheral IV, Midline, Central line,
Other) data elements were supported by
the TEP that discussed candidate data
elements for Special Services,
Treatments, and Interventions during a
meeting on January 5 and 6, 2017. A full
report of the TEP discussion is available
at https://www.cms.gov/Medicare/
Quality-Initiatives-Patient-AssessmentInstruments/Post-Acute-Care-QualityInitiatives/IMPACT-Act-of-2014/
IMPACT-Act-Downloads-andVideos.html.
Therefore, we are proposing that the
IV access (Peripheral IV, Midline,
Central line, Other) data elements with
a principal data element and four subelements meet the definition of
standardized patient assessment data for
special services, treatments, and
interventions under section
1899B(b)(1)(B)(iii) of the Act. We are
proposing to add the IV Access
(Peripheral IV, Midline, Central line,
Other) data elements to the OASIS and
that HHAs would be required to report
these data for the CY 2020 HH QRP at
SOC/ROC and discharge between
January 1, 2019 and June 30, 2019.
Following the initial two quarters of
reporting for the CY 2020 HH QRP,
subsequent years for the HH QRP would
be based on 12 months of such data
reporting beginning with July 1, 2019
through June 30, 2020 for the CY 2021
HH QRP.
We are inviting public comment on
these proposals.
xii. Nutritional Approach: Parenteral/IV
Feeding
We are proposing that the Parenteral/
IV Feeding data element meets the
definition of standardized patient
assessment data for special services,
treatments, and interventions under
section 1899B(b)(1)(B)(iii) of the Act.
The proposed data element consists of
the single Parenteral/IV Feeding data
element. For more information on the
Parenteral/IV Feeding data element, we
refer readers to the document titled,
Proposed Measure Specifications and
Standardized Data Elements for CY
2018 HH QRP Notice of Proposed
E:\FR\FM\28JYP2.SGM
28JYP2
mstockstill on DSK30JT082PROD with PROPOSALS2
Federal Register / Vol. 82, No. 144 / Friday, July 28, 2017 / Proposed Rules
Rulemaking, available at https://
www.cms.gov/Medicare/QualityInitiatives-Patient-AssessmentInstruments/HomeHealthQualityInits/
HHQIQualityMeasures.html.
Parenteral/IV Feeding refers to a
patient or resident being fed
intravenously using an infusion pump,
bypassing the usual process of eating
and digestion. The need for IV/
parenteral feeding indicates a clinical
complexity that prevents the patient or
resident from meeting his/her
nutritional needs enterally, and is more
resource intensive than other forms of
nutrition, as it often requires monitoring
of blood chemistries, and maintenance
of a central line. Therefore, assessing a
patient or resident’s need for parenteral
feeding is important for care planning
and resource use. In addition to the
risks associated with central and
peripheral intravenous access, total
parenteral nutrition is associated with
significant risks such as embolism,
sepsis, and glucose abnormalities.
The Parenteral/IV Feeding data
element is currently in use in the MDS
3.0, and equivalent or related data
elements are in use in the LCDS, IRF–
PAI, and the OASIS–C2. An equivalent
data element was tested in the PAC PRD
(‘‘Total Parenteral Nutrition’’) and found
feasible for use in each of the four PAC
settings, demonstrating the feasibility of
collecting information about this
nutritional service in these settings.
Total Parenteral Nutrition (an item
with the same meaning as the proposed
data element, but with the label used in
the PAC PRD) was included in a call for
public comment that was open from
August 12 to September 12, 2016.
Several commenters supported this data
element, noting its relevance to
facilitating care coordination and
supporting care transitions. After the
public comment period, the Total
Parenteral Nutrition data element was
re-named Parenteral/IV Feeding, to be
consistent with how this data element is
referred to in the MDS. A full report of
the comments is available at https://
www.cms.gov/Medicare/QualityInitiatives-Patient-AssessmentInstruments/Post-Acute-Care-QualityInitiatives/IMPACT-Act-of-2014/
IMPACT-Act-Downloads-andVideos.html.
A TEP convened by the data element
contractor provided input on the
proposed data elements. This TEP, held
on January 5 and 6, 2017, opined that
these data elements are appropriate for
standardization because they would
provide useful clinical information to
inform care planning and care
coordination. The TEP affirmed that
assessment of these services and
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22:22 Jul 27, 2017
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interventions is standard clinical
practice. A full report of the TEP
discussion is available at https://
www.cms.gov/Medicare/QualityInitiatives-Patient-AssessmentInstruments/Post-Acute-Care-QualityInitiatives/IMPACT-Act-of-2014/
IMPACT-Act-Downloads-andVideos.html.
Therefore, we are proposing that the
Parenteral/IV Feeding data element
meets the definition of standardized
patient assessment data for special
services, treatments, and interventions
under section 1899B(b)(1)(B)(iii) of the
Act. We are proposing to rename the
existing ‘‘Parenteral nutrition (TPN or
lipids)’’ data element in the OASIS to
the Parenteral/IV Feeding data element,
and that HHAs would be required to
report these data for the CY 2020 HH
QRP at SOC/ROC and discharge
between January 1, 2019, and June 30,
2019. Following the initial two quarters
of reporting for the CY 2020 HH QRP,
subsequent years for the HH QRP would
be based on 12 months of such data
reporting beginning with July 1, 2019,
through June 30, 2020 for the CY 2021
HH QRP.
We are inviting public comment on
these proposals.
xiv. Nutritional Approach: Feeding
Tube
We are proposing that the Feeding
Tube data element meets the definition
of standardized patient assessment data
for special services, treatments, and
interventions under section
1899B(b)(1)(B)(iii) of the Act. The
proposed data element consists of the
single Feeding Tube data element. For
more information on the Feeding Tube
data element, we refer readers to the
document titled, Proposed Measure
Specifications and Standardized Data
Elements for CY 2018 HH QRP Notice of
Proposed Rulemaking, available at
https://www.cms.gov/Medicare/QualityInitiatives-Patient-AssessmentInstruments/HomeHealthQualityInits/
HHQIQualityMeasures.html.
The majority of patients admitted to
acute care hospitals experience
deterioration of their nutritional status
during their hospital stay, making
assessment of nutritional status and
method of feeding, if unable to eat
orally, very important in PAC. A feeding
tube can be inserted through the nose or
the skin on the abdomen to deliver
liquid nutrition into the stomach or
small intestine. Feeding tubes are
resource intensive and are therefore
important to assess for care planning
and resource use. Patients with severe
malnutrition are at higher risk for a
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variety of complications.206 In PAC
settings, there are a variety of reasons
that patients and residents may not be
able to eat orally (including clinical or
cognitive status).
The Feeding Tube data element is
currently included in the MDS 3.0 for
SNFs, and in the OASIS–C2 for HHAs,
where it is labeled Enteral Nutrition. A
related data element is collected in the
IRF–PAI for IRFs (Tube/Parenteral
Feeding). The testing of similar
nutrition-focused data elements in the
PAC PRD, and the current assessment of
feeding tubes and related nutritional
services and devices, demonstrates the
feasibility of collecting information
about this nutritional service in these
settings.
Clinical and subject matter expert
advisors working with our data element
contractor opined that the Feeding Tube
data element is feasible for use in PAC,
and supported its importance and
clinical usefulness for patients in PAC
settings, due to the increased level of
nursing care and patient monitoring
required for patients who received
enteral nutrition with this device.
We solicited additional feedback on
an Enteral Nutrition data element (an
item with the same meaning as the
proposed data element, but with the
label used in the OASIS) in a call for
public comment that was open from
August 12 to September 12, 2016.
Several commenters supported the data
element, noting the importance of
assessing enteral nutrition status for
facilitating care coordination and care
transitions. After the public comment
period, the Enteral Nutrition data
element used in public comment was renamed Feeding Tube, indicating the
presence of an assistive device. A full
report of the comments is available at
https://www.cms.gov/Medicare/QualityInitiatives-Patient-AssessmentInstruments/Post-Acute-Care-QualityInitiatives/IMPACT-Act-of-2014/
IMPACT-Act-Downloads-andVideos.html.
We note that the Feeding Tube data
element was also supported by the TEP
that discussed candidate data elements
for Special Services, Treatments, and
Interventions during a meeting on
January 5 and 6, 2017. A full report of
the TEP discussion is available at
https://www.cms.gov/Medicare/QualityInitiatives-Patient-AssessmentInstruments/Post-Acute-Care-QualityInitiatives/IMPACT-Act-of-2014/
206 Dempsey, D.T., Mullen, J.L., & Buzby, G.P.
(1988). ‘‘The link between nutritional status and
clinical outcome: can nutritional intervention
modify it?’’ Am J of Clinical Nutrition 47(2): 352–
356.
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IMPACT-Act-Downloads-andVideos.html.
Therefore, we are proposing that the
Feeding Tube data element meets the
definition of standardized patient
assessment data for special services,
treatments, and interventions under
section 1899B(b)(1)(B)(iii) of the Act.
We are proposing to rename the existing
‘‘Enteral nutrition (nasogastric,
gastrostomy, jejunostomy, or any other
artificial entry into the alimentary
canal)’’ data element in the OASIS to
the Feeding Tube data element and that
HHAs would be required to report these
data for the CY 2020 HH QRP at SOC/
ROC and discharge between January 1,
2019, and June 30, 2019. Following the
initial two quarters of reporting for the
CY 2020 HH QRP, subsequent years for
the HH QRP would be based on 12
months of such data reporting beginning
with July 1, 2019 through June 30, 2020
for the CY 2021 HH QRP.
We are inviting public comment on
these proposals.
xv. Nutritional Approach: Mechanically
Altered Diet
We are proposing that the
Mechanically Altered Diet data element
meets the definition of standardized
patient assessment data for special
services, treatments, and interventions
under section 1899B(b)(1)(B)(iii) of the
Act. The proposed data element consists
of the single Mechanically Altered Diet
data element. For more information on
the Mechanically Altered Diet data
element, we refer readers to the
document titled, Proposed Measure
Specifications and Standardized Data
Elements for CY 2018 HH QRP Notice of
Proposed Rulemaking, available at
https://www.cms.gov/Medicare/QualityInitiatives-Patient-AssessmentInstruments/HomeHealthQualityInits/
HHQIQualityMeasures.html.
The Mechanically Altered Diet data
element refers to food that has been
altered to make it easier for the patient
or resident to chew and swallow, and
this type of diet is used for patients and
residents who have difficulty
performing these functions. Patients
with severe malnutrition are at higher
risk for a variety of complications.207 In
PAC settings, there are a variety of
reasons that patients and residents may
have impairments related to oral
feedings, including clinical or cognitive
status. The provision of a mechanically
altered diet may be resource intensive,
and can signal difficulties associated
207 Dempsey, D.T., Mullen, J.L., & Buzby, G.P.
(1988). ‘‘The link between nutritional status and
clinical outcome: can nutritional intervention
modify it?’’ Am J of Clinical Nutrition 47(2): 352–
356.
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with swallowing/eating safety,
including dysphagia. In other cases, it
signifies the type of altered food source,
such as ground or puree, which will
enable the safe and thorough ingestion
of nutritional substances and ensure
safe and adequate delivery of
nourishment to the patient. Often,
patients on mechanically altered diets
also require additional nursing supports
such as individual feeding, or direct
observation, to ensure the safe
consumption of the food product.
Assessing whether a patient or resident
requires a mechanically altered diet is
therefore important for care planning
and resource identification.
The proposed data element for a
mechanically altered diet is currently
included on the MDS 3.0 for SNFs. A
related data element for modified food
consistency/supervision is currently
included on the IRF–PAI for IRFs. A
related data element is included in the
OASIS–C2 for HHAs that collects
information about independent eating
that requires ‘‘a liquid, pureed or
ground meat diet.’’ The testing of
similar nutrition-focused data elements
in the PAC PRD, and the current
assessment of various nutritional
services across the four PAC settings,
demonstrates the feasibility of collecting
information about this nutritional
service in these settings.
Clinical and subject matter expert
advisors working with our data element
contractor agreed that the proposed
Mechanically Altered Diet data element
is feasible for use in PAC, and it
assesses an important treatment that
would be clinically useful both within
and across PAC settings. Expert input
on the Mechanically Altered Diet data
element highlighted its importance and
clinical usefulness for patients in PAC
settings, due to the increased
monitoring and resource use required
for patients on special diets. We note
that the Mechanically Altered Diet data
element was also supported by the TEP
that discussed candidate data elements
for Special Services, Treatments, and
Interventions during a meeting on
January 5 and 6, 2017. A full report of
the TEP discussion is available at
https://www.cms.gov/Medicare/QualityInitiatives-Patient-AssessmentInstruments/Post-Acute-Care-QualityInitiatives/IMPACT-Act-of-2014/
IMPACT-Act-Downloads-andVideos.html.
Therefore, we are proposing that the
Mechanically Altered Diet data element
meets the definition of standardized
patient assessment data for special
services, treatments, and interventions
under section 1899B(b)(1)(B)(iii) of the
Act. We are proposing to add the
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Mechanically Altered Diet data element
to the OASIS, and that HHAs would be
required to report these data for the CY
2020 HH QRP at SOC/ROC and
discharge between January 1, 2019 and
June 30, 2019. Following the initial two
quarters of reporting for the CY 2020 HH
QRP, subsequent years for the HH QRP
would be based on 12 months of such
data reporting beginning with July 1,
2019, through June 30, 2020 for the CY
2021 HH QRP.
We are inviting public comment on
these proposals.
xvi. Nutritional Approach: Therapeutic
Diet
We are proposing that the Therapeutic
Diet data element meets the definition
of standardized patient assessment data
for special services, treatments, and
interventions under section
1899B(b)(1)(B)(iii) of the Act. The
proposed data element consists of the
single Therapeutic Diet data element.
For more information on the
Therapeutic Diet data element, we refer
readers to the document titled, Proposed
Measure Specifications and
Standardized Data Elements for CY
2018 HH QRP Notice of Proposed
Rulemaking, available at https://
www.cms.gov/Medicare/QualityInitiatives-Patient-AssessmentInstruments/HomeHealthQualityInits/
HHQIQualityMeasures.html.
Therapeutic Diet refers to meals
planned to increase, decrease, or
eliminate specific foods or nutrients in
a patient or resident’s diet, such as a
low-salt diet, for the purpose of treating
a medical condition. The use of
therapeutic diets among patients in PAC
provides insight on the clinical
complexity of these patients and their
multiple comorbidities. Therapeutic
diets are less resource intensive from
the bedside nursing perspective, but can
signify one or more underlying clinical
conditions that preclude the patient
from eating a regular diet. They also
often require more education and
lifestyle modification training. The
communication among PAC providers
about whether a patient is receiving a
particular therapeutic diet is critical to
ensure safe transitions of care.
The Therapeutic Diet data element is
currently in use in the MDS 3.0. The
testing of similar nutrition-focused data
elements in the PAC PRD, and the
current assessment of various
nutritional services across the four PAC
settings, demonstrates the feasibility of
collecting information about this
nutritional service in these settings.
Clinical and subject matter expert
advisors working with our data element
contractor supported the importance
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and clinical usefulness of the proposed
Therapeutic Diet data element for
patients in PAC settings, due to the
increased monitoring and resource use
required for patients on special diets,
and agreed that it is feasible for use in
PAC and that it assesses an important
treatment that would be clinically
useful both within and across PAC
settings. We note that the Therapeutic
Diet data element was also supported by
the TEP that discussed candidate data
elements for Special Services,
Treatments, and Interventions during a
meeting on January 5 and 6, 2017.
Therefore, we are proposing that the
Therapeutic Diet data element meets the
definition of standardized patient
assessment data for special services,
treatments, and interventions under
section 1899B(b)(1)(B)(iii) of the Act.
We are proposing to add the
Therapeutic Diet data element to the
OASIS, and that HHAs would be
required to report these data for the CY
2020 HH QRP at SOC/ROC and
discharge between January 1, 2019 and
June 30, 2019. Following the initial two
quarters of reporting for the CY 2020 HH
QRP, subsequent years for the HH QRP
would be based on 12 months of such
data reporting beginning with July 1,
2019, through June 30, 2020 for the CY
2021 HH QRP.
We are inviting public comment on
these proposals.
d. Medical Condition and Comorbidity
Data
We are proposing that the data
elements needed to calculate the current
measure, Percent of Residents or
Patients with Pressure Ulcers That Are
New or Worsened (Short Stay) (NQF
#0678), and that the proposed measure,
Changes in Skin Integrity Post-Acute
Care: Pressure Ulcer/Injury, meet the
definition of standardized patient
assessment data with respect to medical
conditions and co-morbidities under
section 1899B(b)(1)(B)(iv) of the Act,
and that the successful reporting of that
data under section
1895(b)(3)(B)(v)(IV)(aa) of the Act would
also satisfy the requirement to report
standardized patient assessment data
under section 1895(b)(3)(B)(v)(IV)(bb) of
the Act.
‘‘Medical conditions and comorbidities’’ and the conditions
addressed in the standardized data
elements used in the calculation and
risk adjustment of these measures, that
is, the presence of pressure ulcers,
diabetes, incontinence, peripheral
vascular disease or peripheral arterial
disease, mobility, as well as low body
mass index (BMI), are all health-related
conditions that indicate medical
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complexity that can be indicative of
underlying disease severity and other
comorbidities.
Specifically, the data elements used
in the measure are important for care
planning and provide information
pertaining to medical complexity.
Pressure ulcers are serious wounds
representing poor outcomes, and can
result in sepsis and death. Assessing
skin condition, care planning for
pressure ulcer prevention and healing,
and informing providers about their
presence in patient transitions of care is
imperative a customary and best
practice. Venous and arterial disease
and diabetes are associated with
insufficient low blood flow, which may
increase the risk of tissue damage. These
diseases commonly are indicators of
factors that may place individuals at
risk for pressure ulcer development and
are therefore important for care
planning. Low BMI, which may be an
indicator of underlying disease severity,
may be associated with loss of fat and
muscle, resulting in potential risk for
pressure ulcers due to shearing. Bowel
incontinence, and the possible
maceration to the skin associated, can
lead to higher risk for pressure ulcers.
In addition, the bacteria associated with
bowel incontinence can complicate
current wounds and cause local
infection. Mobility is an indicator of
impairment or reduction in mobility
and movement which is a major risk
factor for the development of pressure
ulcers. Taken separately and together,
these data elements are important for
care planning, transitions in services
and identifying medical complexities.
e. Impairment Data
Hearing and vision impairments are
conditions that, if unaddressed, affect
activities of daily living,
communication, physical functioning,
rehabilitation outcomes, and overall
quality of life. Sensory limitations can
lead to confusion in new settings,
increase isolation, contribute to mood
disorders, and impede accurate
assessment of other medical conditions.
Failure to appropriately assess,
accommodate, and treat these
conditions increases the likelihood that
patients will require more intensive and
prolonged treatment. Onset of these
conditions can be gradual, so
individualized assessment with accurate
screening tools and regular follow-up
evaluations are essential to determining
which patients need hearing- or visionspecific medical attention or assistive
devices, and accommodations,
including auxiliary aids and/or services,
and to ensure that person-directed care
plans are developed to accommodate a
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patient’s needs. Accurate diagnosis and
management of hearing or vision
impairment would likely improve
rehabilitation outcomes and care
transitions, including transition from
institutional-based care to the
community. Accurate assessment of
hearing and vision impairment would
be expected to lead to appropriate
treatment, accommodations, including
the provision of auxiliary aids and
services during the stay, and ensure that
patients continue to have their vision
and hearing needs met when they leave
the facility.
Accurate individualized assessment,
treatment, and accommodation of
hearing and vision impairments of
patients and residents in PAC would be
expected to have a positive impact on
the National Quality Strategy’s domains
of patient and family engagement,
patient safety, care coordination,
clinical process/effectiveness, and
efficient use of healthcare resources. For
example, standardized assessment of
hearing and vision impairments used in
PAC will support ensuring patient
safety (for example, risk of falls)
identifying accommodations needed
during the stay, and appropriate support
needs at the time of discharge or
transfer. Standardized assessment of
these data elements will enable or
support clinical decision-making and
early clinical intervention; personcentered, high quality care (for example,
facilitating better care continuity and
coordination); better data exchange and
interoperability between settings; and
longitudinal outcome analysis. Hence,
reliable data elements assessing hearing
and vision impairments are needed to
initiate a management program that can
optimize a patient or resident’s
prognosis and reduce the possibility of
adverse events.
i. Hearing
We are proposing that the Hearing
data element meets the definition of
standardized patient assessment data for
impairments under section
1899B(b)(1)(B)(v) of the Act. The
proposed data element consists of the
single Hearing data element. This data
element assesses level of hearing
impairment, and consists of one
question. For more information on the
Hearing data element, we refer readers
to the document titled, Proposed
Measure Specifications and
Standardized Data Elements for CY
2018 HH QRP Notice of Proposed
Rulemaking, available at https://
www.cms.gov/Medicare/QualityInitiatives-Patient-AssessmentInstruments/HomeHealthQualityInits/
HHQIQualityMeasures.html.
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Accurate assessment of hearing
impairment is important in the PAC
setting for care planning and resource
use. Hearing impairment has been
associated with lower quality of life,
including poorer physical, mental, and
social functioning, and emotional
health.208 209 Treatment and
accommodation of hearing impairment
led to improved health outcomes,
including but not limited to increased
quality of life.210 For example, hearing
loss in elderly individuals has been
associated with depression and
cognitive impairment,211 212 213 higher
rates of incident cognitive impairment
and cognitive decline,214 and less time
in occupational therapy.215 Accurate
assessment of hearing impairment is
important in the PAC setting for care
planning and defining resource use.
The proposed data element was
selected from two forms of the Hearing
data element based on expert and
stakeholder feedback. We considered
the two forms of the Hearing data
element, one of which is currently in
use in the MDS 3.0 (Hearing) and
another data element with different
wording and fewer response option
categories that is currently in use in the
OASIS–C2 (Ability to Hear). Ability to
Hear was also tested in the PAC PRD
and found to have substantial agreement
for inter-rater reliability across PAC
settings (kappa of 0.78).216
208 Dalton DS, Cruickshanks KJ, Klein BE, Klein
R, Wiley TL, Nondahl DM. The impact of hearing
loss on quality of life in older adults. Gerontologist.
2003;43(5):661–668.
209 Hawkins K, Bottone FG, Jr., Ozminkowski RJ,
et al. The prevalence of hearing impairment and its
burden on the quality of life among adults with
Medicare Supplement Insurance. Qual Life Res.
2012;21(7):1135–1147.
210 Horn KL, McMahon NB, McMahon DC, Lewis
JS, Barker M, Gherini S. Functional use of the
Nucleus 22-channel cochlear implant in the elderly.
The Laryngoscope. 1991;101(3):284–288.
211 Sprinzl GM, Riechelmann H. Current trends in
treating hearing loss in elderly people: a review of
the technology and treatment options—a minireview. Gerontology. 2010;56(3):351–358.
212 Lin FR, Thorpe R, Gordon-Salant S, Ferrucci
L. Hearing Loss Prevalence and Risk Factors Among
Older Adults in the United States. The Journals of
Gerontology Series A: Biological Sciences and
Medical Sciences. 2011;66A(5):582–590.
213 Hawkins K, Bottone FG, Jr., Ozminkowski RJ,
et al. The prevalence of hearing impairment and its
burden on the quality of life among adults with
Medicare Supplement Insurance. Qual Life Res.
2012;21(7):1135–1147.
214 Lin FR, Metter EJ, O’Brien RJ, Resnick SM,
Zonderman AB, Ferrucci L. Hearing Loss and
Incident Dementia. Arch Neurol. 2011;68(2):214–
220.
215 Cimarolli VR, Jung S. Intensity of
Occupational Therapy Utilization in Nursing Home
Residents: The Role of Sensory Impairments. J Am
Med Dir Assoc. 2016;17(10):939–942.
216 Gage B., Smith L., Ross J. et al. (2012). The
Development and Testing of the Continuity
Assessment Record and Evaluation (CARE) Item Set
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Several data elements that assess
hearing impairment were presented to
the Standardized Patient Assessment
Data TEP held by our data element
contractor. The TEP did not reach
consensus on the ideal number of
response categories or phrasing of
response options, which are the primary
differences between the current MDS
(Hearing) and OASIS (Ability to Hear)
items. The Development and
Maintenance of Post-Acute Care CrossSetting Standardized Patient
Assessment Data Technical Expert Panel
Summary Report is available at https://
www.cms.gov/Medicare/QualityInitiatives-Patient-AssessmentInstruments/Post-Acute-Care-QualityInitiatives/IMPACT-Act-of-2014/
IMPACT-Act-Downloads-andVideos.html.
The PAC PRD form of the data
element (Ability to Hear) was included
in a call for public comment that was
open from August 12 to September 12,
2016. This data element includes three
response choices, in contrast to the
Hearing data element (in use in the MDS
3.0 and being proposed for
standardization), which includes four
response choices. Several commenters
supported the use of the Ability to Hear
data element, although some
commenters raised concerns that the
three-level response choice was not
compatible with the current, four-level
response used in the MDS, and favored
the use of the MDS version of the
Hearing data element. In addition, we
received comments stating that
standardized assessment related to
hearing impairment has the ability to
improve quality of care if information
on hearing is included in medical
records of patients and residents, which
would improve care coordination and
facilitate the development of patientand resident-centered treatment plans.
Based on comments that the three-level
response choice (Ability to Hear) was
not congruent with the current, fourlevel response used in the MDS
(Hearing), and support for the use of the
MDS version of the Hearing data
element received in the public
comment, we are proposing the Hearing
data element from the MDS. A full
report of the comments is available at
https://www.cms.gov/Medicare/QualityInitiatives-Patient-AssessmentInstruments/Post-Acute-Care-QualityInitiatives/IMPACT-Act-of-2014/
IMPACT-Act-Downloads-andVideos.html.
Therefore, we are proposing the
Hearing data element currently in use in
(Final Report on Reliability Testing, Volume 2 of 3).
Research Triangle Park, NC: RTI International.
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the MDS. We are proposing to add the
Hearing data element to the OASIS, and
that HHAs would be required to report
these data for the CY 2020 HH QRP at
SOC/ROC between January 1, 2019 and
June 30, 2019. Following the initial two
quarters of reporting for the CY 2020 HH
QRP, subsequent years for the HH QRP
would be based on 12 months of such
data reporting beginning with July 1,
2019, through June 30, 2020 for the CY
2021 HH QRP. The Hearing data
element would be assessed at SOC/ROC
only due to the relatively stable nature
of hearing impairment, making it
unlikely that this assessment would
change between the start and end of
care. Assessment at discharge would
introduce additional burden without
improving the quality or usefulness of
the data, and we believe it is
unnecessary.
We are inviting public comment on
these proposals.
ii. Vision
We are proposing that the Vision data
element meets the definition of
standardized patient assessment data for
impairments under section
1899B(b)(1)(B)(v) of the Act. The
proposed data element consists of the
single Vision (Ability To See in
Adequate Light) data element that
consists of one question with five
response categories. For more
information on the Vision data element,
we refer readers to the document titled,
Proposed Measure Specifications and
Standardized Data Elements for CY
2018 HH QRP Notice of Proposed
Rulemaking, available at https://
www.cms.gov/Medicare/QualityInitiatives-Patient-AssessmentInstruments/HomeHealthQualityInits/
HHQIQualityMeasures.html.
Evaluation of an individual’s ability
to see is important for assessing for risks
such as falls and provides opportunities
for improvement through treatment and
the provision of accommodations,
including auxiliary aids and services,
which can safeguard patients and
improve their overall quality of life.
Further, vision impairment is often a
treatable risk factor associated with
adverse events and poor quality of life.
For example, individuals with visual
impairment are more likely to
experience falls and hip fracture, have
less mobility, and report depressive
symptoms.217 218 219 220 221 222 223
217 Colon-Emeric CS, Biggs DP, Schenck AP, Lyles
KW. Risk factors for hip fracture in skilled nursing
facilities: who should be evaluated? Osteoporos Int.
2003;14(6):484–489.
218 Freeman EE, Munoz B, Rubin G, West SK.
Visual field loss increases the risk of falls in older
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Individualized initial screening can
lead to life-improving interventions
such as accommodations, including the
provision of auxiliary aids and services,
during the stay and/or treatments that
can improve vision and prevent or slow
further vision loss. For patients with
some types of visual impairment, use of
glasses and contact lenses can be
effective in restoring vision.224 Other
conditions, including glaucoma225 and
age-related macular degeneration,226 227
have responded well to treatment.
Accurate assessment of vision
impairment is important in the PAC
setting for care planning and defining
resource use.
The Vision data element that we are
proposing for standardization was tested
as part of the development of the MDS
3.0 and is currently in use in that
assessment. Similar data elements, but
with different wording and fewer
response option categories, are in use in
the OASIS–C2 and were tested in postacute providers in the PAC PRD and
found to be clinically relevant,
meaningful for care planning, reliable
(kappa of 0.74),228 and feasible for use
in each of the four PAC settings.
adults: the Salisbury eye evaluation. Invest
Ophthalmol Vis Sci. 2007;48(10):4445–4450.
219 Keepnews D, Capitman JA, Rosati RJ.
Measuring patient-level clinical outcomes of home
health care. J Nurs Scholarsh. 2004;36(1):79–85.
220 Nguyen HT, Black SA, Ray LA, Espino DV,
Markides KS. Predictors of decline in MMSE scores
among older Mexican Americans. J Gerontol A Biol
Sci Med Sci. 2002;57(3):M181–185.
221 Prager AJ, Liebmann JM, Cioffi GA, Blumberg
DM. Self-reported Function, Health Resource Use,
and Total Health Care Costs Among Medicare
Beneficiaries With Glaucoma. JAMA
ophthalmology. 2016;134(4):357–365.
222 Rovner BW, Ganguli M. Depression and
disability associated with impaired vision: the
MoVies Project. J Am Geriatr Soc. 1998;46(5):617–
619.
223 Tinetti ME, Ginter SF. The nursing home lifespace diameter. A measure of extent and frequency
of mobility among nursing home residents. J Am
Geriatr Soc. 1990;38(12):1311–1315.
224 Rein DB, Wittenborn JS, Zhang X, et al. The
Cost-effectiveness of Welcome to Medicare Visual
Acuity Screening and a Possible Alternative
Welcome to Medicare Eye Evaluation Among
Persons Without Diagnosed Diabetes Mellitus.
Archives of ophthalmology. 2012;130(5):607–614.
225 Leske M, Heijl A, Hussein M, et al. Factors for
glaucoma progression and the effect of treatment:
The early manifest glaucoma trial. Archives of
Ophthalmology. 2003;121(1):48–56.
226 Age-Related Eye Disease Study Research G. A
randomized, placebo-controlled, clinical trial of
high-dose supplementation with vitamins c and e,
beta carotene, and zinc for age-related macular
degeneration and vision loss: AREDS report no. 8.
Archives of Ophthalmology. 2001;119(10):1417–
1436.
227 Takeda AL, Colquitt J, Clegg AJ, Jones J.
Pegaptanib and ranibizumab for neovascular
age-related macular degeneration: a systematic
review. The British Journal of Ophthalmology.
2007;91(9):1177–1182.
228 Gage B., Smith L., Ross J. et al. (2012). The
Development and Testing of the Continuity
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Several data elements that assess
vision were presented to the TEP held
by our data element contractor. The TEP
did not reach consensus on the ideal
number of response categories or
phrasing of response options, which are
the primary differences between the
current MDS and OASIS items; some
members preferring more granular
response options (for example, mild
impairment and moderate impairment)
while others were comfortable with
collapsed response options (that is,
mild/moderate impairment). The
Development and Maintenance of PostAcute Care Cross-Setting Standardized
Patient Assessment Data Technical
Expert Panel Summary Report is
available at https://www.cms.gov/
Medicare/Quality-Initiatives-PatientAssessment-Instruments/Post-AcuteCare-Quality-Initiatives/IMPACT-Act-of2014/IMPACT-Act-Downloads-andVideos.html.
We solicited public comment from
August 12 to September 12, 2016, on the
Ability to See in Adequate Light data
element (version tested in the PAC PRD
with three response categories). The
data element in public comment
differed from the proposed data
element, but the comments supported
the assessment of vision in PAC settings
and the useful information a vision data
element would provide. The
commenters stated that the Ability to
See item would provide important
information that would facilitate care
coordination and care planning, and
consequently improve the quality of
care. Other commenters suggested it
would be helpful as an indicator of
resource use and noted that the item
would provide useful information about
the abilities of patients and residents to
care for themselves. Additional
commenters noted that the item could
feasibly be implemented across PAC
providers and that its kappa scores from
the PAC PRD support its validity. Some
commenters noted a preference for MDS
version of the Vision data element over
the form put forward in public
comment, citing the widespread use of
this data element. A full report of the
comments is available at https://
www.cms.gov/Medicare/QualityInitiatives-Patient-AssessmentInstruments/Post-Acute-Care-QualityInitiatives/IMPACT-Act-of-2014/
IMPACT-Act-Downloads-andVideos.html.
Clinical and subject matter expert
advisors working with our data element
contractor agreed that assessing vision
Assessment Record and Evaluation (CARE) Item Set
(Final Report on Reliability Testing, Volume 2 of 3).
Research Triangle Park, NC: RTI International.
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impairment of patients and residents
with a standardized data element is
feasible in PAC, that it can reliably and
accurately identify adults with objective
impaired vision, and that this
information about impaired vision
would be clinically useful to identify
needed accommodations and/or
treatment both within and across PAC
settings.
Therefore, we are proposing the
Vision data element from the MDS. We
are proposing to add the Vision data
element to the OASIS, and that HHAs
would be required to report these data
for the CY 2020 HH QRP at the start of
care between January 1, 2019 and June
30, 2019. Following the initial two
quarters of reporting for the CY 2020 HH
QRP, subsequent years for the HH QRP
would be based on 12 months of such
data reporting beginning with July 1,
2019 through June 30, 2020 for the CY
2021 HH QRP. The Vision data element
would be assessed at start of care only
due to the relatively stable nature of
vision impairment, making it unlikely
that this assessment would change
between the start and end of care.
Assessment at the end of care would
introduce additional burden without
improving the quality or usefulness of
the data, and we believe it is
unnecessary.
We are inviting public comment on
these proposals.
I. Proposals Relating to the Form,
Manner, and Timing of Data
Submission Under the HH QRP
1. Proposed Start Date for Reporting
Standardized Patient Assessment Data
by New HHAs
In the CY 2016 HH PPS final rule (80
FR 68624), we adopted timing for new
HHAs to begin reporting standardized
quality data under the HH QRP. We are
proposing in this proposed rule that
new HHAs will be required to begin
reporting standardized patient
assessment data on the same schedule.
We are inviting public comment on this
proposal.
2. Proposed Mechanism for Reporting
Standardized Patient Assessment Data
Beginning With the CY 2019 HH QRP
Under our current policy, HHAs
report data by completing applicable
sections of the OASIS, and submitting
the OASIS to CMS through the QIES,
ASAP system. For more information on
HH QRP reporting through the QIES
ASAP system, refer to https://
www.qtso.com/index.php. In addition to
the data currently submitted on quality
measures as previously finalized and
described in Table 49 of this proposed
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rule, we are proposing that HHAs would
be required to begin submitting the
proposed standardized patient
assessment data for HHA Medicare and
Medicaid quality episodes that begin or
end on or after January 1, 2019 using the
OASIS, as described here.
Further, the proposed standardized
patient assessment data elements
described above would be added to the
OASIS, so the new reporting
requirements regarding those elements
would result in no changes to the
mechanism by which HHAs report data
under the HH QRP. All standardized
patient assessment data elements would
be collected at SOC/ROC using the
OASIS item set, and all except the Brief
Interview for Mental Status (BIMS),
Hearing, and Vision data elements are or
would be collected at discharge using
the OASIS item set. Details on the
modifications and assessment collection
for the OASIS for the proposed
standardized data are available at
https://www.cms.gov/Medicare/QualityInitiatives-Patient-AssessmentInstruments/HomeHealthQualityInits/
HHQIQualityMeasures.html.
We are inviting public comments on
these proposals.
3. Proposed Schedule for Reporting
Standardized Patient Assessment Data
Beginning With the CY 2019 HH QRP
Starting with the CY 2019 HH QRP,
we are proposing to apply our current
schedule for the reporting of measure
data to the reporting of standardized
patient assessment data. Under that
policy, except for the first program year
for which a measure is adopted, HHAs
must report data on measures for HHA
Medicare and Medicaid quality episodes
that occur during the 12-month period
(between July 1 and June 30) that
applies to the program year. For the first
program year for which a measure is
adopted, HHAs are only required to
report data on HHA Medicare and
Medicaid quality episodes that begin on
or after January 1 and end up to and
including June 30 of the calendar year
that applies to that program year. For
example, for the CY 2019 HH QRP, data
on measures adopted for earlier program
years must be reported for all HHA
Medicare and Medicaid quality episodes
that begin on or after July 1, 2017 and
end on or before June 30, 2018.
However, data on new measures
adopted for the first time for the CY
2019 HH QRP program year must only
be reported for HHA Medicare and
Medicaid quality episodes that begin or
end during the first two quarters of CY
2018. Tables 49 and 50 illustrate this
policy.
TABLE 49—SUMMARY ILLUSTRATION OF INITIAL REPORTING FOR NEWLY ADOPTED MEASURES AND STANDARDIZED
PATIENT ASSESSMENT DATA REPORTING USING CY Q1 AND Q2 DATA FOR THE HH QRP *:
Proposed data submission deadlines beginning with CY 2019 HH
QRP *
Proposed data collection/submission reporting period *
January 1, 2018–June 30, 2018 ..............................................................
July 31, 2018.
*We
note that submission of the OASIS must also adhere to the HH PPS deadlines.
The term ‘‘CY 2019 HH QRP’’ means the calendar year for which the HH QRP requirements applicable to that calendar year must be met in
order for a HHA to avoid a two percentage point reduction to its market basket percentage when calculating the payment rates applicable to it for
that calendar year.
∧
TABLE 50—SUMMARY ILLUSTRATION OF OASIS 12 MONTH DATA REPORTING FOR MEASURES AND STANDARDIZED
PATIENT ASSESSMENT DATA REPORTING FOR THE HH QRP *
Proposed data submission deadlines beginning with CY 2020 HH
QRP * ∧
Proposed data collection/submission reporting period *
July 1, 2018—June 30, 2019 ...................................................................
July 31, 2019.
*
We note that submission of the OASIS must also adhere to the HH PPS deadlines.
∧ The term ‘‘CY 2020 HH QRP’’ means the calendar year for which the HH QRP requirements applicable to that calendar year must be met in
order for a HHA to avoid a two percentage point reduction to its market basket percentage when calculating the payment rates applicable to it for
that calendar year.
We are inviting comment on our
proposal to extend our current policy
governing the schedule for reporting the
quality measure data to the reporting of
standardized patient assessment data for
the HH QRP beginning with the CY
2019 HH QRP.
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4. Proposed Schedule for Reporting the
Proposed Quality Measures Beginning
With the CY 2020 HH QRP
As discussed in section V.I. of this
proposed rule, we are proposing to
adopt three quality measures beginning
with the CY 2020 HH QRP: Changes in
Skin Integrity Post-Acute Care: Pressure
Ulcer/Injury; Application of The Percent
of Residents Experiencing One or More
Falls with Major Injury (NQF # 0674);
and Application of Percent of LongTerm Care Hospital Patients with an
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Admission and Discharge Functional
Assessment and a Care Plan That
Addresses Function (NQF #2631). We
are proposing that HHAs would report
data on these measures using OASIS
reporting that is submitted through the
QIES ASAP system. More information
on OASIS reporting using the QIES
ASAP system is located at https://
www.cms.gov/Medicare/QualityInitiatives-Patient-AssessmentInstruments/OASIS/Data
Specifications.html.
For the CY 2020 HH QRP, HHAs
would be required to report these data
for HHA Medicare and Medicaid quality
episodes that begin or end during the
period from January 1, 2019 to June 30,
2019. Beginning with the CY 2021 HH
QRP, HHAs would be required to
submit data for the entire 12-month
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period from July 1 to June 30. Further,
for the purposes of measure calculation,
our policy was established in the CY
2017 HH PPS final rule (81 FR 76702)
that data are utilized using calendar
year timeframes with review and
correction periods.
We are inviting public comment on
this proposal.
5. Input Sought for Data Reporting
Related to Assessment Based Measures
Through various means of public
input, including through previous rules,
public comment on measures, and the
MAP, we have received input suggesting
that we expand the population for
quality measurement to include all
patients regardless of payer.
Approximately 75 percent of home
health expenditures in 2014 were made
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by either Medicare or Medicaid and
currently both Medicare and Medicaid
collect and report data for OASIS. We
believe that expanding the patient
population for which OASIS collects
data will allow us to ensure data that is
representative of quality provided to all
patients in the HHA setting and
therefore allow us to better determine
whether HH Medicare beneficiaries
receive the same quality of care that
other patients receive. We also
appreciate that collecting quality data
on all patients regardless of payer
source may create additional burden.
However, we also received input that
the effort to separate out Medicare and
Medicaid beneficiaries, who are
currently reported through OASIS, from
other patients creates clinical and work
flow implications with an associated
burden too, and we further appreciate
that it is common practice for HHAs to
collect OASIS data on all patients,
regardless of payer source. Thus, we are
seeking input on whether we should
require quality data reporting on all HH
patients, regardless of payer, where
feasible—noting that because Medicare
Part A claims data are submitted only
with respect to Medicare beneficiaries,
claims-based measures rates would
continue to be calculated only for
Medicare beneficiaries.
We are inviting public comments on
this topic.
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J. Other Proposals for the CY 2019 HH
QRP and Subsequent Years
1. Proposal To Apply the HH QRP Data
Completion Thresholds to the
Submission of Standardized Patient
Assessment Data Beginning With the CY
2019 HH QRP
In the CY 2016 HH PPS final rule (80
FR 68703 through 68705), we defined
the pay-for-reporting performance
system model that could accurately
measure the level of an HHA’s
submission of OASIS data 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. EOC assessments
comprise the Discharge from Agency,
Death at Home and Transfer to an
Inpatient Facility time points. For
further information on successful
submission of OASIS assessments, types
of assessments submitted by an HHA
that fit the definition of a quality
assessment, defining the ‘‘Quality
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Assessments Only’’ (QAO) formula, and
implementing a pay-for-reporting
performance requirement over a 3-year
period, please see the CY 2016 HH PPS
final rule (80 FR 68704 to 68705).
Additionally, we finalized the payfor-reporting threshold requirements in
the CY 2016 HH PPS rule. We finalized
a policy through which HHAs must
score at least 70 percent on the QAO
metric of pay-for-reporting performance
requirement for CY 2017 (reporting
period July 1, 2015 to June 30, 2016), 80
percent for CY 2018 (reporting period
July 1, 2016 to June 30, 2017) and 90
percent for CY 2019 (reporting period
July 1, 2017 to June 30, 2018). An HHA
that does not meet this requirement for
a calendar year will be subject to a two
percentage point reduction to the
market basket percentage increase that
would otherwise apply for that calendar
year. We are now proposing to apply the
threshold requirements established in
the CY 2016 HH PPS rule to the
submission of standardized patient
assessment data beginning with the CY
2019 HH QRP.
We are inviting public comment on
our proposal to extend our current HH
QRP data completion requirements to
the submission of standardized patient
assessment data.
2. Proposal for the HH QRP Submission
Exception and Extension Requirements
Our experience with other QRPs has
shown that there are times when
providers are unable to submit quality
data due to extraordinary circumstances
beyond their control (for example,
natural, or man-made disasters). Other
extenuating circumstances are reviewed
on a case-by-case basis. We propose to
define a ‘‘disaster’’ as any natural or
man-made catastrophe which causes
damages of sufficient severity and
magnitude to partially or completely
destroy or delay access to medical
records and associated documentation.
Natural disasters could include events
such as hurricanes, tornadoes,
earthquakes, volcanic eruptions, fires,
mudslides, snowstorms, and tsunamis.
Man-made disasters could include such
events as terrorist attacks, bombings,
floods caused by man-made actions,
civil disorders, and explosions. A
disaster may be widespread and impact
multiple structures or be isolated and
impact a single site only.
In certain instances of either natural
or man-made disasters, an HHA may
have the ability to conduct a full patient
assessment, and record and save the
associated data either during or before
the occurrence of the extraordinary
event. In this case, the extraordinary
event has not caused the agency’s data
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35373
files to be destroyed, but it could hinder
the HHA’s ability to meet the QRP’s data
submission deadlines. In this scenario,
the HHA would potentially have the
ability to report the data at a later date,
after the emergency has passed. In such
cases, a temporary extension of the
deadlines for reporting might be
appropriate.
In other circumstances of natural or
man-made disaster, an HHA may not
have had the ability to conduct a full
patient assessment, or to record and
save the associated data before the
occurrence of the extraordinary event.
In such a scenario, the agency may not
have complete data to submit to CMS.
We believe that it may be appropriate,
in these situations, to grant a full
exception to the reporting requirements
for a specific period of time.
We do not wish to penalize HHAs in
these circumstances or to unduly
increase their burden during these
times. Therefore, we propose a process
for HHAs to request and for us to grant
exceptions and extensions for the
reporting requirements of the HH QRP
for one or more quarters, beginning with
the CY 2019 HH QRP, when there are
certain extraordinary circumstances
beyond the control of the HHA. When
an exception or extension is granted, we
would not reduce the HHA’s PPS
payment for failure to comply with the
requirements of the HH QRP.
We propose that if an HHA seeks to
request an exception or extension for
the HH QRP, the HHA should request an
exception or extension within 90 days
of the date that the extraordinary
circumstances occurred. The HHA may
request an exception or extension for
one or more quarters by submitting a
written request to CMS that contains the
information noted below, via email to
the HHA Exception and Extension
mailbox at HHAPureConsiderations@
cms.hhs.gov. Requests sent to CMS
through any other channel would not be
considered as valid requests for an
exception or extension from the HH
QRP’s reporting requirements for any
payment determination.
The subject of the email must read
‘‘HH QRP Exception or Extension
Request’’ and the email must contain
the following information:
• HHA CCN;
• HHA name;
• CEO or CEO-designated personnel
contact information including name,
telephone number, email address, and
mailing address (the address must be a
physical address, not a post office box);
• HHA’s reason for requesting an
exception or extension;
• Evidence of the impact of
extraordinary circumstances, including
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but not limited to photographs,
newspaper and other media articles; and
• A date when the HHA believes it
will be able to again submit HH QRP
data and a justification for the proposed
date.
We propose that exception and
extension requests be signed by the
HHA’s CEO or CEO-designated
personnel, and that if the CEO
designates an individual to sign the
request, the CEO-designated individual
has the appropriate authority to submit
such a request on behalf of the HHA.
Following receipt of the email, we
would: (1) Provide a written
acknowledgement, using the contact
information provided in the email, to
the CEO or CEO-designated contact
notifying them that the request has been
received; and (2) provide a formal
response to the CEO or any CEOdesignated HHA personnel, using the
contact information provided in the
email, indicating our decision.
This proposal does not preclude us
from granting exceptions or extensions
to HHAs that have not requested them
when we determine that an
extraordinary circumstance, such as an
act of nature, affects an entire region or
locale. If we make the determination to
grant an exception or extension to all
HHAs in a region or locale, we propose
to communicate this decision through
routine communication channels to
HHAs and vendors, including, but not
limited to, issuing memos, emails, and
notices on our HH QRP Web site once
it is available at https://www.cms.gov/
Medicare/Quality-Initiatives-PatientAssessment-Instruments/HomeHealth
QualityInits/HomeHealth
QualityReporting-Reconsideration-andException-and-Extension.html.
We also propose that we may grant an
exception or extension to HHAs if we
determine that a systemic problem with
one of our data collection systems
directly affected the ability of the HHA
to submit data. Because we do not
anticipate that these types of systemic
errors will happen often, we do not
anticipate granting an exception or
extension on this basis frequently.
If an HHA is granted an exception, we
would not require that the HHA submit
any measure data for the period of time
specified in the exception request
decision. If we grant an extension to the
original submission deadline, the HHA
would still remain responsible for
submitting quality data collected during
the timeframe in question, although we
would specify a revised deadline by
which the HHA must submit this
quality data.
We also propose that any exception or
extension requests submitted for
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purposes of the HH QRP would apply to
that program only, and not to any other
program we administer for HHAs such
as survey and certification. OASIS
requirements, including electronic
submission, during Declared Public
Health Emergencies can be found at
FAQs I–5, I–6, I–7, I–8 at https://
www.cms.gov/Medicare/ProviderEnrollment-and-Certification/Survey
CertEmergPrep/downloads/
AllHazardsFAQs.pdf.
We intend to provide additional
information pertaining to exceptions
and extensions for the HH QRP,
including any additional guidance, on
the HH QRP Web site at https://
www.cms.gov/Medicare/QualityInitiatives-Patient-AssessmentInstruments/HomeHealthQualityInits/
HomeHealthQualityReportingReconsideration-and-Exception-andExtension.html.
We propose to add the HH QRP
Submission Exception and Extension
Requirements at § 484.250(d). We
welcome comment on these proposals.
3. Proposed HH QRP Submission
Reconsideration and Appeals
Procedures
The HH QRP reconsiderations and
appeals process was finalized in the CY
2013 HH PPS final rule (77 FR 67096)
and has been used for prior all periods
cited in the previous rules, and utilized
in the CY 2012 to CY 2017 APU
determinations. At the conclusion of the
required quality data reporting and
submission period, we review the data
received from each HHA during that
reporting period to determine if the
HHA met the HH QRP reporting
requirements. HHAs that are found to be
noncompliant with the HH QRP
reporting requirements for the
applicable calendar year will receive a
2 percentage point reduction to its
market basket percentage update for that
calendar year.
Similar to our other quality reporting
programs, such as the SNF QRP, the
LTCH QRP, and the IRF QRP, we
include an opportunity for the providers
to request a reconsideration of our
initial noncompliance determination.
To be consistent with other established
quality reporting programs and to
provide an opportunity for HHAs to
seek reconsideration of our initial
noncompliance decision, we are
proposing a process that enables an
HHA to request reconsideration of our
initial non-compliance decision in the
event that it believes that it was
incorrectly identified as being noncompliant with the HH QRP reporting
requirements for a particular calendar
year. These proposals clarify the HH
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QRP reconsiderations and appeals
process that we have finalized in
previous rules.
For the CY 2019 HH QRP, and
subsequent years, we are proposing that
a HHA would receive a notification of
noncompliance if we determine that the
HHA did not submit data in accordance
with the HH QRP reporting
requirements for the applicable CY. The
purpose of this notification is to put the
HHA on notice that the HHA: (1) Has
been identified as being non-compliant
with the HH QRP’s reporting
requirements for the applicable calendar
year; (2) will be scheduled to receive a
reduction in the amount of two
percentage points to its market basket
percentage update for the applicable
calendar year; (3) may file a request for
reconsideration if it believes that the
finding of noncompliance is erroneous,
has submitted a request for an extension
or exception that has not yet been
decided, or has been granted an
extension or exception; and (4) must
follow a defined process on how to file
a request for reconsideration, which will
be described in the notification. We
would only consider requests for
reconsideration after an HHA has been
found to be noncompliant.
Notifications of noncompliance and
any subsequent notifications from CMS
would be sent via a traceable delivery
method, such as certified U.S. mail or
registered U.S. mail, or through other
practicable notification processes, such
as a report from CMS to the provider as
a Certification and Survey Provider
Enhanced Reports (CASPER) report, that
will provide information pertaining to
their compliance with the reporting
requirements for the given reporting
cycle or from the Medicare
Administrative Contractors assigned to
process the provider’s claims. To obtain
the compliance reports, providers
should access the CASPER Reporting
Application. HHA providers access the
CASPER Reporting application via their
CMS OASIS System Welcome page by
selecting the CASPER Reporting link.
The ‘‘CASPER Reports’’ link will
connect an HHA to the QIES National
System Login page for CASPER
Reporting.
We propose to disseminate
communications regarding the
availability of compliance reports
through routine channels to HHAs and
vendors, including, but not limited to
issuing memos, emails, Medicare
Learning Network (MLN)
announcements, and notices on our HH
QRP Web site once it is available at
https://www.cms.gov/Medicare/QualityInitiatives-Patient-AssessmentInstruments/HomeHealthQualityInits/
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An HHA would have 30 days from the
date of the letter of noncompliance to
submit to us a request for
reconsideration. This proposed time
frame allows us to balance our desire to
ensure that HHA s have the opportunity
to request reconsideration with our need
to complete the process and provide
HHAs with our reconsideration decision
in a timely manner. We are proposing
that an HHA may withdraw its request
at any time and may file an updated
request within the proposed 30-day
deadline. We are also proposing that, in
very limited circumstances, we may
grant a request by an HHA to extend the
proposed deadline for reconsideration
requests. It would be the responsibility
of an HHA to request an extension and
demonstrate that extenuating
circumstances existed that prevented
the filing of the reconsideration request
by the proposed deadline.
We also are proposing that as part of
the HHA’s request for reconsideration,
the HHA would be required to submit
all supporting documentation and
evidence demonstrating full compliance
with all HH QRP reporting requirements
for the applicable calendar year, that the
HHA has requested an extension or
exception for which a decision has not
yet been made, that the HHA has been
granted an extension or exception, or
has experienced an extenuating
circumstance as defined in section V.I.2
of this rule but failed to file a timely
request of exception. We propose that
we would not review any
reconsideration request that fails to
provide the necessary documentation
and evidence along with the request.
The documentation and evidence may
include copies of any communications
that demonstrate the HHA’s compliance
with the HH QRP, as well as any other
records that support the HHA’s rationale
for seeking reconsideration, but should
not include any protected health
information (PHI). We intend to provide
a sample list of acceptable supporting
documentation and evidence, as well as
instructions for HHAs on how to
retrieve copies of the data submitted to
CMS for the appropriate program year in
the future on our HH QRP Web site at
https://www.cms.gov/Medicare/QualityInitiatives-Patient-AssessmentInstruments/HomeHealthQualityInits/
HomeHealthQualityReportingReconsideration-and-Exception-andExtension.html.
We are proposing that an HHA
wishing to request a reconsideration of
our initial noncompliance
determination would be required to do
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so by submitting an email to the
following email address:
HHAPureConsiderations@cms.hhs.gov.
Any request for reconsideration
submitted to us by an HHA would be
required to follow the guidelines
outlined on our HH QRP Web site once
it is available at https://www.cms.gov/
Medicare/Quality-Initiatives-PatientAssessment-Instruments/HomeHealth
QualityInits/HomeHealthQuality
Reporting-Reconsideration-andException-and-Extension.html.
All emails must contain a subject line
that reads ‘‘HH QRP Reconsideration
Request.’’ Electronic email submission
is the only form of reconsideration
request submission that will be accepted
by us. Any reconsideration requests
communicated through another channel
including, but not limited to, U.S. Postal
Service or phone, will not be considered
as a valid reconsideration request.
We are proposing that a
reconsideration request include the
following information:
• HHA CMS Certification Number
(CCN);
• HHA Business Name;
• HHA Business Address;
• The CEO contact information
including name, email address,
telephone number and physical mailing
address; or The CEO-designated
representative contact information
including name, title, email address,
telephone number and physical mailing
address; and
• CMS identified reason(s) for
noncompliance from the noncompliance notification; and
• The reason(s) for requesting
reconsideration.
The request for reconsideration must
be accompanied by supporting
documentation demonstrating
compliance. Following receipt of a
request for reconsideration, we would
provide an email acknowledgment,
using the contact information provided
in the reconsideration request, to the
CEO or CEO-designated representative
that the request has been received. Once
we have reached a decision regarding
the reconsideration request, an email
would be sent to the HHA CEO or CEO
designated representative, using the
contact information provided in the
reconsideration request, notifying the
HHA of our decision.
We also propose that the notifications
of our decision regarding
reconsideration requests may be made
available through a traceable delivery
method, such as certified U.S. mail or
registered U.S. mail or through the use
of CASPER reports. If the HHA is
dissatisfied with the decision rendered
at the reconsideration level, the HHA
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35375
may appeal the decision to the PRRB
under 42 CFR 405.1835. We believe this
proposed process is more efficient and
less costly for CMS and for HHAs
because it decreases the number of
PRRB appeals by resolving issues earlier
in the process. Additional information
about the reconsideration process
including details for submitting a
reconsideration request will be posted
in the future to our HH QRP Web site
at https://www.cms.gov/Medicare/
Quality-Initiatives-Patient-AssessmentInstruments/HomeHealthQualityInits/
HomeHealthQualityReportingReconsideration-and-Exception-andExtension.html.
We propose to add the HH QRP
Submission Reconsideration and
Appeals Procedures at § 484.250(e) and
(f). We welcome comment on these
proposals.
K. Proposals and Policies Regarding
Public Display of Quality Measure Data
for the HH QRP
Our home health regulations, at
§ 484.250(a), require HHAs to submit
OASIS assessments and Home Health
Care Consumer Assessment of
Healthcare Providers and Systems
Survey® (HHCAHPS) data to meet the
quality reporting requirements of
section 1895(b)(3)(B)(v) of the Act.
Section 1899B(g) of the Act requires that
data and information of provider
performance on quality measures and
resource use and other measures be
made publicly available beginning not
later than two years after the applicable
specified ‘‘application date’’. In
addition, sections 1895(b)(3)(B)(v)(III)
requires the Secretary to establish
procedures for making data submitted
under section 1895(b)(3)(B)(v)(II)
available to the public, and section
1899B(g)(1) of the Act requires the
Secretary to do the same with respect to
HHA performance on measures
specified under sections 1899B(c)(1)
and (d)(1) of the Act. Section
1895(b)(3)(B)(v)(III) of the Act requires
that the public reporting procedures for
data submitted under subclause (II)
ensure that a HHA has the opportunity
to review the data that is to be made
public with respect to it prior to such
data being made public. Under section
1899B(g)(2) of the Act, the public
reporting procedures for performance on
measures under sections 1899B(c)(1)
and (d)(1) of the Act must ensure,
including through a process consistent
with the process applied under section
1886(b)(3)(B)(viii)(VII) of the Act,
(which refers to public display and
review requirements in the Hospital
Inpatient Quality Reporting (Hospital
IQR) Program), that a HHA has the
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opportunity to review and submit
corrections to its data and information
that are to be made public for the agency
prior to such data being made public.
We recognize that public reporting of
quality data is a vital component of a
robust quality reporting program and are
fully committed to ensuring that the
data made available to the public are
meaningful. Further, we agree that
measures for comparing performance
across home health agencies should be
constructed from data collected in a
standardized and uniform manner.
In the CY 2017 HH PPS final rule (81
FR 76785 through 76786), we finalized
procedures that allow individual HHAs
to review and correct their data and
information on IMPACT Act measures
that are to be made public before those
measure data are made public.
Information on how to review and
correct data on IMPACT Act measures
that are to be made public before those
measure data are made public can be
found on the HH QRP Web site at
https://www.cms.gov/Medicare/QualityInitiatives-Patient-AssessmentInstruments/HomeHealthQualityInits/
Home-Health-Quality-Reporting-
Requirements.html. We are not
proposing any changes to these policies.
In this CY 2018 HH PPS proposed
rule, pending the availability of data, we
are proposing to publicly report data
beginning in CY 2019 for the following
two assessment-based measures: (1)
Percent of Patients or Residents with
Pressure Ulcers that are New or
Worsened (NQF #0678); and (2) Drug
Regimen Review Conducted with
Follow-Up for Identified Issues-PAC HH
QRP. Data collection for these two
assessment-based measures began on
OASIS on January 1, 2017. We propose
to publicly report data beginning in CY
2019 for these assessment-based
measures based on four rolling quarters
of data, beginning with data collected
for discharges in 2017.
In addition, we are proposing to
publicly report data beginning in CY
2019 for the following 3 claims-based
measures: (1) Medicare Spending Per
Beneficiary-PAC HH QRP; (2) Discharge
to Community-PAC HH QRP; and (3)
Potentially Preventable 30-Day PostDischarge Readmission Measure for HH
QRP. As adopted in the CY 2017 HH
PPS final rule (81 FR 43773), for the
MSPB–PAC HH QRP measure, we will
use one year of claims data beginning
with CY 2016 claims data to inform
confidential feedback reports for HHAs,
and CY 2017 claims data for public
reporting for the HH QRP. For the
Discharge to Community—PAC HH QRP
measure we will use 2 years of claims
data, beginning with CYs 2015 and 2016
claims data to inform confidential
feedback and CYs 2016 and 2017 claims
data for public reporting. For the
Potentially Preventable 30-Day PostDischarge Readmission Measure for HH
QRP, we will use 3 years of claims data,
beginning with CY 2014, 2015 and 2016
claims data to inform confidential
feedback reports for HHAs, and CY
2015, 2016 and 2017 claims data for
public reporting.
Finally, we are proposing to assign
HHAs with fewer than 20 eligible cases
during a performance period to a
separate category: ‘‘The number of
patient episodes for this measure is too
small to report,’’ 229 to ensure the
statistical reliability of the measures. If
a HHA had fewer than 20 eligible cases,
the HHA’s performance would not be
publicly reported for the measure for
that performance period.
TABLE 51—SUMMARY OF PROPOSED NEW HH QRP MEASURES FOR CY 2019 PUBLIC DISPLAY
Proposed Measures:
Percent of Residents or Patients with Pressure Ulcers that Are New or Worsened (Short Stay) (NQF #0678).
Drug Regimen Review Conducted with Follow-Up for Identified Issues-PAC HH QRP.
Potentially Preventable 30-Day Post-Discharge Readmission Measure for HH QRP.
Discharge to Community—(PAC) HH QRP.
Medicare Spending Per Beneficiary (PAC) HH QRP.
We are inviting public comment on
these proposals for the public display of
quality data, as described in this
proposed rule.
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L. Proposed Mechanism for Providing
Confidential Feedback Reports to HHAs
Information on how to obtain these and
other reports available to the HH QRP
can be found at https://www.cms.gov/
Medicare/Quality-Initiatives-PatientAssessment-Instruments/HomeHealth
QualityInits/Home-Health-QualityReporting-Requirements.html. We are
not proposing any changes to this
policy.
Section 1899B(f) of the Act requires
the Secretary to provide confidential
feedback reports to post-acute care
(PAC) providers on their performance
on the measures specified under
subsections (c)(1) and (d)(1) of section
1899B of the Act, beginning one year
after the specified application date that
applies to such measures and PAC
providers. In the CY 2017 HH PPS final
rule (81 FR 76702), we finalized
processes to allow HH providers the
opportunity to review their data and
information using confidential feedback
reports that will enable HHAs to review
their performance on the measures
required under the HH QRP.
In the CY 2017 HH PPS final rule (81
FR 76787), we stated that the home
health quality measures reporting
requirements for Medicare-certified
agencies includes the Home Health Care
CAHPS® (HHCAHPS) Survey for the
Home Health Quality Reporting Program
and along with OASIS measures,
HHCAHPS participation is required for
the Annual Payment Update (APU). In
the CY 2017 HH PPS final rule, we
finalized the reporting requirements and
229 This language is currently available as
Footnote #4 on Home Health Compare (https://
the data submission dates for the CY
2017–CY 2020 APU periods. We
proposed to continue the HHCAHPS
requirements in future years for the
continuous monthly data collection and
quarterly data submission of HHCAHPS
data.
www.medicare.gov/HomeHealthCompare/Data/
Footnotes.html).
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M. Home Health Care CAHPS® Survey
(HHCAHPS)
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1. Background and Description of
HHCAHPS
The HHCAHPS survey is part of a
family of CAHPS® surveys that asks
patients to report on and rate their
experiences with health care. For more
details about the HH CAHPS Survey
please see 81 FR 76787 through 76788.
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 are required to provide a
monthly list of their HHCAHPS-eligible
patients to their respective HHCAHPS
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survey vendors. Home health agencies
are not allowed to influence their
patients about how the HHCAHPS
survey.
As previously required, new
HHCAHPS survey vendors are required
to attend Introduction training, and
current HHCAHPS vendors are required
to attend Update training conducted by
CMS and the HHCAHPS Survey
Coordination Team. New HHCAHPS
vendors need to pass a post-training
certification test. We have
approximately 30 approved HHCAHPS
survey vendors. The list of approved
HHCAHPS survey vendors is available
at https://homehealthcahps.org.
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2. HHCAHPS Oversight Activities
We stated in prior final rules that all
approved HHCAHPS survey vendors are
required to participate in HHCAHPS
oversight activities to ensure
compliance with HHCAHPS protocols,
guidelines, and survey requirements.
The purpose of the oversight activities
is to ensure that approved HHCAHPS
survey vendors follow the HHCAHPS
Protocols and Guidelines Manual.
In the CY 2013 HH PPS final rule (77
FR 67094, 67164), we codified the
current guideline that all approved
HHCAHPS survey vendors fully comply
with all HHCAHPS oversight activities.
We included this survey requirement at
§ 484.250(c)(3).
For the sake of continuity with this
proposed rule, we are reiterating the
HHCAHPS requirements for CY 2019,
because participation occurs in the
period of the publication of the
proposed and final rules for CY 2018.
We are additionally presenting the
HHCAHPS requirements for CY 2020 for
the sake of continuity. We are proposing
the HHCAHPS requirements for the CY
2021 Annual Payment Update.
3. HHCAHPS Requirements for the CY
2019 HH QRP
In the CY 2017 HH PPS final rule, we
finalized the requirements for the CY
2019 HH QRP. For the CY 2019 HH
QRP, we require continuous monthly
HHCAHPS data collection and reporting
for four quarters. The data collection
period for the CY 2018 HH QRP
includes the second quarter 2017
through the first quarter 2018 (the
months of April 2017 through March
2018). HHAs will be required to submit
their HHCAHPS data files to the
HHCAHPS Data Center for the second
quarter 2017 by 11:59 p.m., eastern
daylight time (e.d.t.) on October 19,
2017; for the third quarter 2017 by 11:59
p.m., eastern standard time (e.s.t.) on
January 18, 2018; for the fourth quarter
2017 by 11:59 p.m., e.d.t. on April 19,
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2018; and for the first quarter 2018 by
11:59 p.m., e.d.t. on July 19, 2018. These
deadlines are firm; no exceptions will
be permitted.
For more details on the CY 2019 HH
QRP, we refer readers to 81 FR 76789.
4. HHCAHPS Requirements for the CY
2020 HH QRP
In the CY 2017 HH PPS final rule, we
finalized the requirements for the CY
2020 HH QRP. For the CY 2020 HH
QRP, we require continued monthly
HHCAHPS data collection and reporting
for four quarters. The data collection
period for the CY 2020 HH QRP
includes the second quarter 2018
through the first quarter 2019 (the
months of April 2018 through March
2019). HHAs will be required to submit
their HHCAHPS data files to the
HHCAHPS Data Center for the second
quarter 2018 by 11:59 p.m., e.d.t. on
October 18, 2018; for the third quarter
2018 by 11:59 p.m., e.s.t. on January 17,
2019; for the fourth quarter 2018 by
11:59 p.m., e.d.t. on April 18, 2019; and
for the first quarter 2019 by 11:59 p.m.,
e.d.t. on July 18, 2019. These deadlines
are firm; no exceptions will be
permitted.
For more details about the CY 2020
HH QRP, we refer readers to 81 FR
76789.
5. HHCAHPS Requirements for the CY
2021 HH QRP
For the CY 2021 HH QRP, we propose
to require the continued monthly
HHCAHPS data collection and reporting
for four quarters. The data collection
period for the CY 2021 HH QRP
includes the second quarter 2019
through the first quarter 2020 (the
months of April 2019 through March
2020). HHAs will be required to submit
their HHCAHPS data files to the
HHCAHPS Data Center for the second
quarter 2019 by 11:59 p.m., e.d.t. on
October 17, 2019; for the third quarter
2019 by 11:59 p.m., e.s.t. on January 16,
2020; for the fourth quarter 2019 by
11:59 p.m., e.d.t. on April 16, 2020; and
for the first quarter 2020 by 11:59 p.m.,
e.d.t. on July 16, 2020. These deadlines
are firm; no exceptions will be
permitted.
For the CY 2021 HH QRP, we propose
to require that all HHAs with fewer than
60 HHCAHPS-eligible unduplicated or
unique patients in the period of April 1,
2018 through March 31, 2019 are
exempt from the HHCAHPS data
collection and submission requirements
for the CY 2021 HH QRP, upon
completion of the CY 2021 HHCAHPS
Participation Exemption Request form,
and upon CMS verification of the HHA
patient counts. Agencies with fewer
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35377
than 60 HHCAHPS-eligible,
unduplicated or unique patients in the
period of April 1, 2018 through March
31, 2019 are proposed to be required to
submit their patient counts on the CY
2021 HHCAHPS Participation
Exemption Request form posted on
https://homehealthcahps.org from April
1, 2019 to 11:59 p.m., e.d.t. to March 31,
2020. This deadline is firm, as are all of
the quarterly data submission deadlines
for the HHAs that participate in
HHCAHPS.
We propose to automatically exempt
HHAs receiving Medicare certification
on or after the start of the period in
which HHAs do their patient count for
a particular year’s HHCAHPS data
submission from the HHCAHPS
reporting requirement for the year. We
propose that HHAs receiving Medicarecertification on or after April 1, 2019
would be exempt from the HHCAHPS
reporting requirement for the CY 2021
HH QRP. As we have finalized in
previous years, we propose that these
newly-certified HHAs do not need to
complete the HHCAHPS Participation
Exemption Request Form for the CY
2021 HH QRP.
6. HHCAHPS Reconsiderations and
Appeals Process
As finalized in previous rules, we
propose that HHAs should monitor their
respective HHCAHPS survey vendors to
ensure that vendors submit their
HHCAHPS data on time, by accessing
their HHCAHPS Data Submission
Reports on https://
homehealthcahps.org. This helps HHAs
ensure that their data are submitted in
the proper format for data processing to
the HHCAHPS Data Center.
We propose to continue HHCAHPS
oversight activities as finalized in the
previous rules. In the CY 2013 HH PPS
final rule (77 FR 67068, 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).
For further information on the HH
QRP reconsiderations and appeals
process, please see Section V.J.3. of this
proposed rule.
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 for future HH QRP years. We again
strongly encourage HHAs to keep up-todate about the HHCAHPS by regularly
viewing the official Web site for the
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HHCAHPS at https://
homehealthcahps.org. HHAs can also
send an email to the HHCAHPS Survey
Coordination Team at hhcahps@rti.org
or to CMS at homehealthcahps@
cms.hhs.gov, or telephone toll-free (1–
866–354–0985) for more information
about the HHCAHPS Survey.
VI. Request for Information on CMS
Flexibilities and Efficiencies
CMS is committed to transforming the
health care delivery system—and the
Medicare program—by putting an
additional focus on patient-centered
care and working with providers,
physicians, and patients to improve
outcomes. We seek to reduce burdens
for hospitals, physicians, and patients,
improve the quality of care, decrease
costs, and ensure that patients and their
providers and physicians are making the
best health care choices possible. These
are the reasons we are including this
Request for Information in this proposed
rule.
As we work to maintain flexibility
and efficiency throughout the Medicare
program, we would like to start a
national conversation about
improvements that can be made to the
health care delivery system that reduce
unnecessary burdens for clinicians,
other providers, and patients and their
families. We aim to increase quality of
care, lower costs improve program
integrity, and make the health care
system more effective, simple and
accessible.
We would like to take this
opportunity to invite the public to
submit their ideas for regulatory,
subregulatory, policy, practice, and
procedural changes to better accomplish
these goals. Ideas could include
payment system redesign, elimination
or streamlining of reporting, monitoring
and documentation requirements,
aligning Medicare requirements and
processes with those from Medicaid and
other payers, operational flexibility,
feedback mechanisms and data sharing
that would enhance patient care,
support of the physician-patient
relationship in care delivery, and
facilitation of individual preferences.
Responses to this Request for
Information could also include
recommendations regarding when and
how CMS issues regulations and
policies and how CMS can simplify
rules and policies for beneficiaries,
clinicians, physicians, providers, and
suppliers. Where practicable, data and
specific examples would be helpful. If
the proposals involve novel legal
questions, analysis regarding CMS’
authority is welcome for CMS’
consideration. We are particularly
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interested in ideas for incentivizing
organizations and the full range of
relevant professionals and
paraprofessionals to provide screening,
assessment and evidence-based
treatment for individuals with opioid
use disorder and other substance use
disorders, including reimbursement
methodologies, care coordination,
systems and services integration, use of
paraprofessionals including community
paramedics and other strategies. We are
requesting commenters to provide clear
and concise proposals that include data
and specific examples that could be
implemented within the law.
We note that this is a Request for
Information only. Respondents are
encouraged to provide complete but
concise responses. This Request for
Information is issued solely for
information and planning purposes; it
does not constitute a Request for
Proposal (RFP), applications, proposal
abstracts, or quotations. This Request for
Information does not commit the U.S.
Government to contract for any supplies
or services or make a grant award.
Further, CMS is not seeking proposals
through this Request for Information
and will not accept unsolicited
proposals. Responders are advised that
the U.S. Government will not pay for
any information or administrative costs
incurred in response to this Request for
Information; all costs associated with
responding to this Request for
Information will be solely at the
interested party’s expense. We note that
not responding to this Request for
Information does not preclude
participation in any future procurement,
if conducted. It is the responsibility of
the potential responders to monitor this
Request for Information announcement
for additional information pertaining to
this request. In addition, we note that
CMS will not respond to questions
about the policy issues raised in this
Request for Information. CMS will not
respond to comment submissions in
response to this Request for Information
in the FY 2018 HH PPS final rule.
Rather, CMS will actively consider all
input as we develop future regulatory
proposals or future subregulatory policy
guidance. CMS may or may not choose
to contact individual responders. Such
communications would be for the sole
purpose of clarifying statements in the
responders’ written responses.
Contractor support personnel may be
used to review responses to this Request
for Information. Responses to this notice
are not offers and cannot be accepted by
the Government to form a binding
contract or issue a grant. Information
obtained as a result of this Request for
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Sfmt 4702
Information may be used by the
Government for program planning on a
nonattribution basis. Respondents
should not include any information that
might be considered proprietary or
confidential. This Request for
Information should not be construed as
a commitment or authorization to incur
cost for which reimbursement would be
required or sought. All submissions
become U.S. Government property and
will not be returned. CMS may
publically post the public comments
received, or a summary of those public
comments.
VII. Collection of Information
Requirements
A. Statutory Requirement for
Solicitation of Comments
Under the Paperwork Reduction Act
of 1995 (PRA), we are required to
provide 60-day notice in the Federal
Register and solicit public comment
before a collection of information
requirement is submitted to the OMB for
review and approval. We note that we
will submit a revised information
collection request (OMB control number
0938–1279) to OMB for review. This
will also extend the information
collection request which expires
December 30, 2019. To fairly evaluate
whether an information collection
should be approved by OMB, section
3506(c)(2)(A) of the PRA requires that
we solicit comment on the following
issues:
• The need for the information
collection and its usefulness in carrying
out the proper functions of our agency.
• The accuracy of our estimate of the
information collection burden.
• The quality, utility, and clarity of
the information to be collected.
• Recommendations to minimize the
information collection burden on the
affected public, including automated
collection techniques.
This proposed rule makes reference to
associated information collections that
are not discussed in the regulation text
contained in this document.
B. Collection of Information
Requirements for the HH QRP
We believe that the burden associated
with the HH QRP is the time and effort
associated with data collection and
reporting. As of April 1, 2017, there are
approximately 12,149 HHAs currently
reporting quality data to CMS. For the
purposes of calculating the costs
associated with the collection of
information requirements, we obtained
mean hourly wages for these staff from
the U.S. Bureau of Labor Statistics’ May
2016 National Occupational
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Employment and Wage Estimates
(https://www.bls.gov/oes/current/oes_
nat.htm). To account for overhead and
fringe benefits (100 percent), we have
35379
doubled the hourly wage. These
amounts are detailed in Table 52.
TABLE 52—U.S. BUREAU OF LABOR STATISTICS’ MAY 2016 NATIONAL OCCUPATIONAL EMPLOYMENT AND WAGE
ESTIMATES
Occupation
code
Occupation title
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Registered Nurse (RN) ....................................................................................
Physical therapists HHAs ................................................................................
Speech-Language Pathologists (SLP) ............................................................
Occupational Therapists (OT) .........................................................................
The OASIS changes proposed in
section V.D of this proposed rule will
result in the removal of 75 data
elements from the OASIS at the time
point of Start of Care (SOC), 75 data
elements at the time point of
Resumption of Care (ROC), 20 data
elements at the time point of Follow-up
(FU), 42 data elements at the time point
of Transfer to an Inpatient Facility
(TOC), 1 data element at the time point
of Death at Home (Death), and 34 data
elements at the time point of Discharge
from Agency (Discharge). These data
items will not be used in the calculation
of quality measures adopted in the HH
QRP nor are they used for previously
established purposes that are nonrelated to our HH QRP. More detail on
these OASIS data elements proposed for
removal can be found at https://
www.cms.gov/Medicare/QualityInitiatives-Patient-AssessmentInstruments/HomeHealthQualityInits/
OASIS-Data-Sets.html.
Section V.F.1 of this rule proposes to
adopt a new pressure ulcer measure to
replace the current pressure ulcer
measure that has been specified under
section 1899B(c)(1)(B) of the Act
beginning with the CY 2020 HH QRP.
The proposed replacement measure is
entitled, ‘‘Changes in Skin Integrity
Post-Acute Care: Pressure Ulcer/Injury.’’
The new measure will be calculated
using data elements that are currently
collected and reported using the
OASIS–C2 (version effective January 1,
2017). Adoption of the Changes in Skin
Integrity Post-Acute Care: Pressure
Ulcer/Injury measure would result in
the removal of item M1313, related to
pressure ulcer assessment that we
believe is duplicative and no longer
necessary. Specifically, with adoption of
Changes in Skin Integrity Post-Acute
Care: Pressure Ulcer/Injury measure, we
would remove 6 data elements at
Discharge.
In sections V.F.2 of this proposed
rule, we are proposing a new quality
measure to meet requirements of the
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29–1141
29–1123
29–1127
29–1122
IMPACT Act under section
1899B(c)(1)(A) of the Act beginning
with the CY 2020 HH QRP titled
‘‘Application of Percent of Long-Term
Care Hospital Patients with an
Admission and Discharge Functional
Assessment and a Care Plan That
Addresses Function (NQF #2631).’’
Specifically, we are proposing to add 13
standardized patient assessment data
elements at SOC, 13 data elements at
ROC, 15 standardized patient
assessment data elements at FU, and 13
standardized patient assessment data
elements at Discharge.
In sections V.F.3 of this proposed
rule, we are proposing a new quality
measure to meet requirements of the
IMPACT Act under section
1899B(c)(1)(D) of the Act beginning with
the CY 2020 HH QRP titled
‘‘Application of Percent of Residents
Experiencing One or More Falls with
Major Injury (NQF# 0674).’’ The new
measure will be calculated using new
standardized data elements added to the
OASIS. Specifically, we are proposing
to add 4 data elements at TOC, 4 data
elements at Death, and 4 data elements
at Discharge.
In sections V.H.2 and V.H.3 of this
proposed rule, we are proposing
requirements related to the reporting of
standardized patient assessment data
beginning with the CY 2019 HH QRP.
We are proposing to define the term
‘‘standardized patient assessment data’’
as patient assessment questions and
response options that are identical in all
four PAC assessment instruments, and
to which identical standards and
definitions apply. The standardized
patient assessment data is intended to
be shared electronically among PAC
providers and will otherwise enable the
data to be comparable for various
purposes, including the development of
cross-setting quality measures and to
inform payment models that take into
account patient characteristics rather
than setting. Specifically, we are
proposing to add 53 standardized
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Mean hourly
wage
($/hr)
$34.70
46.42
37.60
40.25
Fringe
benefit
(100%)
($/hr)
$34.70
46.42
37.60
40.25
Adjusted
hourly wage
($/hr)
$69.40
92.84
75.20
80.50
patient assessment data elements at
SOC, 53 standardized patient
assessment data elements at ROC, and
36 standardized patient assessment data
elements at Discharge.
The OASIS instrument is used for
both the HH QRP and the HH PPS. As
outlined in section III.E of this proposed
rule, to calculate the case-mix adjusted
payment amount (specifically the
functional level assignment), we are
proposing to add collection of two
current OASIS–C2 items (10 data
elements) at the FU time point:
• M1033: Risk for Hospitalization (9
data elements)
• M1800: Grooming (1 data element).
As outlined in section III.E of this
proposed rule, OASIS integumentary
status items would not be needed in
case-mix adjusting the period payment;
therefore, we are proposing to remove
collection of eight current OASIS–C2
items (19 data elements) at the FU time
point:
• M1311: Current Number of Unhealed
Pressure Ulcers at Each Stage (12 data
elements)
• M1322: Current Number of Stage 1
Pressure Ulcers (1 data element)
• M1324: Stage of Most Problematic
Unhealed Pressure Ulcer that is
Stageable (1 data element)
• M1330: Does this patient have a Stasis
Ulcer? (1 data element)
• M1332: Current Number of Stasis
Ulcer(s) that are Observable (1 data
element)
• M1334: Status of Most Problematic
Stasis Ulcer that is Observable (1 data
element)
• M1340: Does this patient have a
Surgical Wound? (1 data element)
• M1342: Status of Most Problematic
Surgical Wound that is Observable (1
data element).
Therefore, we are proposing the net
removal associated with the HHGM of 9
data elements at FU.
In summary, there is a net reduction
of 9 data elements at SOC, 9 data
elements at ROC,14 data elements at FU
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and 38 data elements at TOC. There is
a net increase of 3 data elements at
Death and 13 data elements at
Discharge.
Under section 1899B(m) of the Act,
the Paperwork Reduction Act does not
apply to section 1899B, or to the
sections of the OASIS that require
modification to achieve the
standardization of patient assessment
data. We are, however, setting out the
burden as a courtesy to advise interested
parties of the proposed actions’ time
and costs and for reference in the
regulatory impact analysis (RIA) section
IX. The requirement and burden will be
submitted to OMB for review and
approval when the modifications to the
OASIS have achieved standardization
and are no longer exempt from the
requirements under section 1899B(m) of
the Act.
We assume that each data element
requires 0.3 minutes of clinician time to
complete. Therefore, there is a reduction
in clinician burden per OASIS
assessment of 2.7 minutes at SOC, 2.7
minutes at ROC, 4.2 minutes at FU and
11.4 minutes at TOC. There is an
increase in clinician burden per
assessment of 0.9 minutes at Death and
3.9 minutes at Discharge.
The OASIS is completed by RNs or
PTs, or very occasionally by
occupational therapists (OT) or speech
language pathologists (SLP/ST). Data
from 2016 show that the SOC/ROC
OASIS is completed by RNs
(approximately 87 percent of the time),
PTs (approximately 12.7 percent of the
time), and other therapists, including
OTs and SLP/STs (approximately 0.3
percent of the time). Based on this
analysis we estimated a weighted
clinician average hourly wage of $72.40,
inclusive of fringe benefits, using the
hourly wage data in Table 52.
Individual providers determine the
staffing resources necessary.
Table 53 shows the total number of
assessments submitted in CY 2016 and
estimated burden at each time point.
TABLE 53—CY 2016 OASIS SUBMISSIONS AND ESTIMATED BURDEN, BY TIME POINT
CY 2016 assessments
completed
Time point
Estimated burden
($)
Start of Care ................................................................................................................................................
Resumption of Care .....................................................................................................................................
Follow-up .....................................................................................................................................................
Transfer to an inpatient facility ....................................................................................................................
Death at Home ............................................................................................................................................
Discharge from agency ................................................................................................................................
6,261,934
1,049,247
3,797,410
1,892,099
41,128
5,120,124
¥$20,401,380.97
¥3,418,446.73
¥19,245,273.88
¥26,027,713.84
44,665.01
24,095,303.54
Total ......................................................................................................................................................
18,161,942
¥44,952,846.87
* Estimated Burden ($) at each Time-Point = (# CY 2016 Assessments Completed) × (clinician burden [min]/60) × ($72.40 [weighted clinician
average hourly wage]).
Guidance/Legislation/Paperwork
ReductionActof1995/PRA-Listing.html.
2. Email your request, including your
address, phone number, OMB number,
and CMS document identifier, to
Paperwork@cms.hhs.gov.
3. Call the Reports Clearance Office at
(410) 786–1326.
See this rule’s DATES and ADDRESSES
sections for the comment due date and
for additional instructions.
C. Submission of PRA-Related
Comments
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Based on the data in Table 53, for the
12,149 active Medicare-certified HHAs
in April 2017, we estimate the total
average decrease in cost associated with
proposed changes to the HH QRP at
$3,700,74 per HHA annually, or
$44,952,846.87 for all HHAs annually.
This decrease in burden will be
accounted for in the information
collection under OMB control number
0938–1279.
VIII. Response to Public Comments
We have submitted a copy of this
proposed rule to OMB for its review of
the rule’s information collection and
recordkeeping requirements. The
requirements are not effective until they
have been approved by OMB.
We invite public comments on these
information collection requirements. If
you wish to comment, please identify
the rule (CMS–1672–P) and, where
applicable, the ICR’s CFR citation, CMS
ID number, and OMB control number.
To obtain copies of a supporting
statement and any related forms for the
proposed collection(s) summarized in
this notice, you may make your request
using one of following:
1. Access CMS’ Web site address at
https://www.cms.gov/Regulations-and-
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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.
IX. 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) of
the Act requires: (1) The computation of
a standard prospective payment amount
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Fmt 4701
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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; (2) the prospective payment
amount under the HH PPS to be an
appropriate unit of service based on the
number, type, and duration of visits
provided within that unit; and (3) 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
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
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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.
The HHVBP Model will apply a
payment adjustment based on an HHA’s
performance on quality measures to test
the effects on quality and costs of care.
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), the
Congressional Review Act (5 U.S.C.
804(2) and Executive Order 13771 on
Reducing Regulation and Controlling
Regulatory Costs (January 30, 2017).
Executive Orders 12866 and 13563
direct agencies to assess all costs and
benefits of available regulatory
alternatives and, if regulation is
necessary, to select regulatory
approaches that maximize net benefits
(including potential economic,
environmental, public health and safety
effects, distributive impacts, and
equity).
Section 3(f) of Executive Order 12866
defines a ‘‘significant regulatory action’’
as an action that is likely to result in a
rule: (1) Having an annual effect on the
economy of $100 million or more in any
1 year, or adversely and materially
affecting a sector of the economy,
productivity, competition, jobs, the
environment, public health or safety, or
state, local or tribal governments or
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communities (also referred to as
‘‘economically significant’’); (2) creating
a serious inconsistency or otherwise
interfering with an action taken or
planned by another agency; (3)
materially altering the budgetary
impacts of entitlement grants, user fees,
or loan programs or the rights and
obligations of recipients thereof; or (4)
raising novel legal or policy issues
arising out of legal mandates, the
President’s priorities, or the principles
set forth in the Executive Order.
A regulatory impact analysis (RIA)
must be prepared for major rules with
economically significant effects ($100
million or more in any 1 year). The net
transfer impact related to the changes in
payments under the HH PPS for CY
2018 is estimated to be ¥$80 million
(¥0.4 percent). The net transfer impact
in CY 2019 related to the change in the
unit of payment under the proposed
HHGM is estimated to be ¥$950 million
(¥4.3 percent) if the HHGM is
implemented in a fully non-budget
neutral manner in CY 2019. The net
transfer impact in CY 2019 related to the
change in the unit of payment under the
proposed HHGM is estimated to be
¥$480 million (¥2.2 percent) if the
HHGM is implemented in a partially
budget-neutral manner in CY 2019 with
the removal of the HHGM partial budget
neutrality adjustment factor in CY 2020.
The savings impacts related to the
HHVBP model as a whole are estimated
at a total projected 5-year gross savings
of $378 million assuming a savings
estimate of a 6 percent annual reduction
in hospitalizations and a 1.0 percent
annual reduction in SNF admissions;
the portion attributable to this proposed
rule is negligible. In the CY 2018 HH
PPS proposed rule, we have identified
a reduction in our regulatory reporting
burden of $44,952,846.87. We estimate
that this rulemaking is ‘‘economically
significant’’ as measured by the $100
million threshold, and hence also a
major rule under the Congressional
Review Act. Accordingly, we have
prepared a Regulatory Impact Analysis
that, to the best of our ability, presents
the costs and benefits of the rulemaking.
In addition, section 1102(b) of the Act
requires us to prepare a RIA if a rule
may have a significant impact on the
operations of a substantial number of
small rural hospitals. This analysis must
conform to the provisions of section 603
of RFA. For purposes of section 1102(b)
of the Act, we define a small rural
hospital as a hospital that is located
outside of a metropolitan statistical area
and has fewer than 100 beds. This
proposed rule is applicable exclusively
to HHAs. Therefore, the Secretary has
determined this rule would not have a
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35381
significant economic impact on the
operations of small rural hospitals.
Section 202 of the Unfunded
Mandates Reform Act of 1995 (UMRA)
also requires that agencies assess
anticipated costs and benefits before
issuing any rule whose mandates
require spending in any 1 year of $100
million in 1995 dollars, updated
annually for inflation. In 2017, that
threshold is approximately $148
million. This proposed rule is not
anticipated to have an effect on State,
local, or tribal governments, in the
aggregate, or on the private sector of
$148 million or more.
If regulations impose administrative
costs on private entities, such as the
time needed to read and interpret this
proposed rule, we should estimate the
cost associated with regulatory review.
Due to the uncertainty involved with
accurately quantifying the number of
entities that will review the rule, we
assume that the total number of unique
commenters on last year’s proposed rule
will be the number of reviewers of this
proposed rule. We acknowledge that
this assumption may understate or
overstate the costs of reviewing this
rule. It is possible that not all
commenters reviewed last year’s rule in
detail, and it is also possible that some
reviewers chose not to comment on the
proposed rule. For these reasons we
thought that the number of past
commenters would be a fair estimate of
the number of reviewers of this rule. We
welcome any comments on the
approach in estimating the number of
entities that will review this proposed
rule.
We also recognize that different types
of entities are in many cases affected by
mutually exclusive sections of this
proposed rule, and therefore for the
purposes of our estimate we assume that
each reviewer reads approximately 50
percent of the rule. We seek comments
on this assumption.
Using the wage information from the
BLS for medical and health service
managers (Code 11–9111), we estimate
that the cost of reviewing this rule is
$105.16 per hour, including overhead
and fringe benefits (https://www.bls.gov/
oes/2016/may/naics4_621100.htm).
Assuming an average reading speed, we
estimate that it would take
approximately 3.8 hours for the staff to
review half of this proposed rule. For
each HHA that reviews the rule, the
estimated cost is $399.61 (3.8 hours ×
$105.16). Therefore, we estimate that
the total cost of reviewing this
regulation is $33,966.85 ($399.61 × 85
reviewers).
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1. HH PPS for CY 2018
The update set forth in this rule
applies to Medicare payments under HH
PPS in CY 2018. Accordingly, the
following analysis describes the impact
in CY 2018 only. We estimate that the
net impact of the policies in this rule is
approximately $80 million in decreased
payments to HHAs in CY 2018. 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 2018 wage index and the
recalibration of the case-mix weights for
2018 is zero. The ¥$80 million impact
reflects the distributional effects of a 0.5
percent reduction in payments due to
the sunset of the rural add-on provision
($100 million decrease), a 1 percent
home health payment update percentage
($190 million increase), and a ¥0.97
percent adjustment to the national,
standardized 60-day episode payment
rate to account for nominal case-mix
growth for an impact of ¥0.9 percent
($170 million decrease). The $80
million in decreased payments is
reflected in the last column of the first
row in Table 54 as a 0.4 percent
decrease in expenditures when
comparing CY 2017 payments to
estimated CY 2018 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 would 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 would have a
significant economic impact on a
substantial number of small entities.
Further detail is presented in Table 54,
by HHA type and location.
With regards to options for regulatory
relief, the sunset of rural add-on
payments for CY 2018 is statutory and
we do not have the authority to
authorize rural add-on payments past
December 31, 2017. We believe it is
appropriate to reduce the national,
standardized 60-day episode payment
amount by 0.97 percent in CY 2018 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.
2. HH PPS for CY 2019 (Proposed
HHGM)
The net transfer impacts in CY 2019
related to the proposed change in the
unit of payment under the HHGM are
estimated to be ¥$950 million (¥4.3
percent) if implemented in a fully nonbudget neutral manner in CY 2019. The
net transfer impact in CY 2019 related
to the change in the unit of payment
under the proposed HHGM is estimated
to be ¥$480 million (¥2.2 percent) if
the HHGM is implemented in a partially
budget-neutral manner in CY 2019 with
the removal of the HHGM partial budget
neutrality adjustment factor in CY 2020.
Based on our analysis, we conclude that
the implementation of the HHGM in CY
2019 would result in an estimated total
impact of 3 to 5 percent or more on
Medicare revenue for greater than 5
percent of HHAs, and therefore, would
have a significant economic impact on
a substantial number of small entities.
Further detail is presented in Table 55,
by HHA type and location.
With regards to options for regulatory
relief, changing the unit of payment
from a 60-day episode to a 30-day
period is not subject to the budget
neutrality requirements under section
1895 of the Act and would result in an
estimated 4.3 percent decrease (¥$950
million) in total HH PPS payments in
CY 2019. As outlined in section III.E.3,
we are proposing to implement the
change in the unit of payment from 60day episodes of care to 30-day periods
care in a non-budget neutral manner as
doing so would better align home health
payments with the costs of providing
care. However, as noted in section
III.E.3, we are considering potential
alternative implementation approaches
for the HHGM, including, but not
limited to, a partially budget-neutral
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approach with a phase-out period.
Specifically, we are considering
applying a HHGM partial budget
neutrality adjustment factor that would
reduce the estimated impact of the
HHGM from an estimated ¥4.3 percent
to ¥2.2 percent in CY 2019, to be
eliminated as soon as CY 2020. We
invite comments on whether to
implement the HHGM in a fully nonbudget neutral manner beginning in CY
2019, as proposed; whether to
implement the HHGM in CY 2019 with
a HHGM partial budget neutrality
adjustment factor applied and then
subsequently removed in CY 2020; or
whether a HHGM partial budget
neutrality adjustment factor should be
applied and then phased-out over a
longer period of time.
HHAs that provide a larger percentage
of overall visits as therapy visits
compared to skilled nursing visits may
experience larger decreases in payments
under the HHGM. We do not believe it
would be appropriate to offer regulatory
relief, or otherwise mitigate the impact
of the proposed HHGM, for HHAs that
provide a preponderance of their visits
as therapy visits compared to nursing
visits. The HHGM would still provide
adequate reimbursement for therapy
services and was developed, in part, to
eliminate the current therapy thresholds
that encourage the provision of the most
profitable number of therapy visits, even
when patient need may not justify such
services. We anticipate that HHAs
currently providing excess therapy
visits solely to maximize
reimbursement, as outlined in section
II.D of this proposed rule, will no longer
do so under the HHGM. We note that
therapy continues to be a valued home
health service, as two of the six clinical
groups (neuro/stroke rehabilitation and
musculoskeletal rehabilitation) under
the HHGM reflect instances where
therapy would be the primary focus of
home health care.
3. HHVBP Model
Under the HHVBP Model, the first
payment adjustment will apply in CY
2018 based on PY1 (2016) data and the
final payment adjustment will apply in
CY 2022 based on PY5 (2020) data. In
the CY 2016 HH PPS final rule, we
estimated that the overall impact of
HHVBP Model from CY 2018 through
CY 2022 was a reduction of
approximately $380 million (80 FR
68716). In the CY 2017 HH PPS final
rule, we estimated that the overall
impact of the HHVBP Model from CY
2018 through CY 2022 was a reduction
of approximately $378 million (81 FR
76795). We do not believe the proposed
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changes in this rule would affect the
prior estimates.
C. Detailed Economic Analysis
This rule proposes updates for CY
2018 to the HH PPS rates contained in
the CY 2017 HH PPS final rule (81 FR
76702 through 76797). The impact
analysis of this proposed rule presents
the estimated expenditure effects of
policy changes proposed in this rule.
We use the latest data and best analysis
available, but we do not make
adjustments for future changes in such
variables as number of visits or casemix.
This analysis incorporates the latest
estimates of growth in service use and
payments under the Medicare HH
benefit, based primarily on Medicare
claims data from 2016. 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.
1. HH PPS for CY 2018
Table 54 represents how HHA
revenues are likely to be affected by the
policy changes proposed in this rule for
CY 2018. For this analysis, we used an
analytic file with linked CY 2016 OASIS
assessments and HH claims data for
dates of service that ended on or before
December 31, 2016. The first column of
Table 54 classifies HHAs according to a
number of characteristics including
provider type, geographic region, and
urban and rural locations. The second
column shows the number of facilities
in the impact analysis. The third
column shows the payment effects of
the CY 2018 wage index. The fourth
column shows the payment effects of
the CY 2018 case-mix weights. The fifth
column shows the effects the 0.97
percent reduction to the national,
standardized 60-day episode payment
amount to account for nominal case-mix
growth. The sixth column shows the
payment effects from the sunset of the
rural add-on payment provision in
statute. The seventh column shows the
effects of the CY 2018 home health
payment update percentage.
The last column shows the combined
effects of all the policies proposed in
this rule. Overall, it is projected that
aggregate payments in CY 2018 would
decrease by 0.4 percent. As illustrated
in Table 54, 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 2018
wage index, the extent to which HHAs
had episodes in case-mix groups where
the case-mix weight decreased for CY
2018 relative to CY 2017, 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. In addition, we clarify that
there are negative estimated impacts
attributed to the sunset of the rural addon provision for HHAs located in urban
areas as well as rural areas. This is due
to the fact that HHAs located in urban
areas provide services to patients
located in rural areas and payments are
based on the location of the beneficiary.
TABLE 54—ESTIMATED HHA IMPACTS BY FACILITY TYPE AND AREA OF THE COUNTRY, CY 2018
CY 2018
wage
index 1
(%)
Number of
agencies
All Agencies .............................................
10,930
CY 2018
case-mix
weights 2
(%)
0.0
60-day
episode
rate nominal
case-mix
reduction 3
(%)
Sunset of
rural add-on
(%)
HH payment
update
percentage 4
(%)
¥0.9
¥0.5
1.0
¥0.4
0.0
Total
(%)
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:
Subtotal:
Subtotal:
Subtotal:
Subtotal:
Freestanding ......................
Facility-based ....................
Vol/NP ...............................
Proprietary .........................
Government .......................
1,089
8,588
322
646
92
193
0.0
0.0
¥0.2
0.0
¥0.2
¥0.2
0.1
0.0
0.2
0.3
0.2
0.2
¥0.8
¥0.9
¥0.9
¥0.8
¥0.9
¥0.9
¥0.4
¥0.4
¥1.4
¥0.7
¥1.3
¥1.4
1.0
1.0
1.0
1.0
1.0
1.0
¥0.1
¥0.3
¥1.3
¥0.2
¥1.2
¥1.3
9,999
931
1,735
8,680
515
0.0
¥0.1
0.0
0.0
¥0.2
0.0
0.3
0.2
0.0
0.2
¥0.9
¥0.8
¥0.8
¥0.9
¥0.9
¥0.4
¥0.8
¥0.5
¥0.5
¥1.4
1.0
1.0
1.0
1.0
1.0
¥0.3
¥0.4
¥0.1
¥0.4
¥1.3
¥0.9
¥0.9
¥0.9
¥0.9
¥0.9
¥0.9
¥2.5
¥2.3
¥2.6
¥2.7
¥2.7
¥2.6
1.0
1.0
1.0
1.0
1.0
1.0
¥2.0
¥2.5
¥2.8
¥2.8
¥2.5
¥2.5
¥0.8
¥0.1
1.0
¥0.8
mstockstill on DSK30JT082PROD with PROPOSALS2
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 ......................
267
814
229
291
47
142
0.2
¥0.2
¥0.4
¥0.4
¥0.1
¥0.2
0.2
¥0.1
0.1
0.2
0.2
0.2
Facility Type and Control: Urban
Free-Standing/Other Vol/NP ....................
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TABLE 54—ESTIMATED HHA IMPACTS BY FACILITY TYPE AND AREA OF THE COUNTRY, CY 2018—Continued
Number of
agencies
Free-Standing/Other Proprietary ..............
Free-Standing/Other Government ...........
Facility-Based Vol/NP ..............................
Facility-Based Proprietary ........................
Facility-Based Government ......................
CY 2018
wage
index 1
(%)
7,774
93
355
45
51
CY 2018
case-mix
weights 2
(%)
0.0
0.0
0.1
¥0.3
¥0.2
60-day
episode
rate nominal
case-mix
reduction 3
(%)
Sunset of
rural add-on
(%)
HH payment
update
percentage 4
(%)
¥0.9
¥0.9
¥0.8
¥0.9
¥0.9
¥0.2
¥0.1
¥0.1
¥0.2
¥0.3
1.0
1.0
1.0
1.0
1.0
¥0.1
0.2
0.5
¥0.2
¥0.1
¥0.9
¥0.9
¥2.4
¥0.2
1.0
1.0
¥2.4
¥0.1
¥0.8
¥0.8
¥0.9
¥0.9
¥0.9
¥0.9
¥0.9
¥0.9
¥0.9
¥0.8
¥0.3
¥0.2
¥0.4
¥0.8
¥0.3
¥1.3
¥0.7
¥0.4
¥0.1
¥0.6
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
0.1
0.0
¥0.1
¥0.2
¥0.4
¥1.6
¥0.6
¥0.5
0.6
¥1.2
¥0.9
¥0.9
¥0.9
¥0.9
¥0.9
¥0.4
¥0.5
¥0.5
¥0.5
¥0.5
1.0
1.0
1.0
1.0
1.0
0.0
¥0.1
¥0.1
¥0.3
¥0.5
0.0
0.2
0.3
0.2
0.3
Total
(%)
Facility Location: Urban or Rural
Rural .........................................................
Urban .......................................................
1,790
9,140
¥0.1
0.0
0.0
0.0
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 .......................................................
Other ........................................................
346
488
2,216
706
1,721
423
2,972
668
1,343
47
0.1
0.0
0.0
0.3
¥0.1
¥0.2
0.2
¥0.3
0.1
0.2
0.1
0.0
0.2
0.2
¥0.1
¥0.2
¥0.2
0.1
0.5
¥1.0
Facility Size (Number of 1st Episodes)
<100 episodes .........................................
100 to 249 ................................................
250 to 499 ................................................
500 to 999 ................................................
1,000 or More ..........................................
3,109
2,478
2,203
1,646
1,494
0.1
0.1
0.1
0.0
0.0
0.2
0.2
0.2
0.1
¥0.1
Source: CY 2016 Medicare claims data for episodes ending on or before December 31, 2016 for which we had a linked OASIS assessment.
1 The impact of the CY 2018 home health wage index is offset by the wage index budget neutrality factor described in section III.C.3 of this
proposed rule.
2 The impact of the CY 2018 home health case-mix weights reflects the recalibration of the case-mix weights offset by the case-mix weights
budget neutrality factor described in section III.B of this proposed rule.
3 The 0.97 percent reduction to the national, standardized 60-day episode payment amount in CY 2018 is estimated to have a 0.9 percent impact on overall HH PPS expenditures.
4 The CY 2018 home health payment update percentage reflects the home health payment update of 1 percent 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.
mstockstill on DSK30JT082PROD with PROPOSALS2
2. HH PPS for CY 2019 (Proposed
HHGM)
Table 55 represents how HHA
revenues are likely to be affected by the
policy changes proposed in this rule for
CY 2019. For this analysis, we used an
analytic file with linked CY 2016 OASIS
assessments and CY 2016 HH claims
data (as of March 17, 2017) for dates of
service that ended on or before
December 31, 2016. The first column of
Table 55 classifies HHAs according to a
number of characteristics including
provider type, geographic region, and
urban and rural locations. The second
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column shows the number of facilities
in the impact analysis. The third and
fourth columns shows the impact of the
proposed HHGM as outlined in section
III.E of this proposed rule. Overall,
before application of the home health
payment update percentage for CY 2019,
it is projected that aggregate payments
in CY 2019 would decrease by $950
million (¥4.3 percent) if implemented
in a fully non-budget neutral manner
and by ¥$480 million (¥2.2 percent) if
the HHGM is implemented in a partially
budget-neutral manner in CY 2019 with
the removal of the HHGM partial budget
neutrality adjustment factor in CY 2020.
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As illustrated in Table 55, the effect of
the proposed HHGM varies 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. This is due to distributional
differences among HHAs with regards to
the percentage of total HH PPS
payments that were subject to the lowutilization payment adjustment (LUPA)
or paid as outlier payments, the degree
of Medicare utilization, and the ratio of
overall visits that were provided as
therapy versus skilled nursing.
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TABLE 55—ESTIMATED HHA IMPACTS BY FACILITY TYPE AND AREA OF THE COUNTRY, CY 2019
Number of
agencies
All Agencies .................................................................................................................................
Implementation of the
HHGM
(not budget
neutral)
(%)
Implementation of the
HHGM
(partially budget neutral)
(%)
10,860
¥4.3
¥2.2
1,085
8,525
319
646
92
193
¥1.3
¥5.7
¥2.9
¥0.2
0.4
1.3
0.9
¥3.6
¥0.7
2.0
2.6
3.6
9,929
931
1,731
8,617
512
¥4.7
0.0
¥1.0
¥5.7
¥0.7
¥2.6
2.2
1.2
¥3.6
1.5
267
808
226
291
47
142
0.2
¥0.6
¥1.7
0.3
5.0
1.8
2.5
1.7
0.6
2.5
7.3
4.1
818
7,717
93
355
45
51
¥1.5
¥6.3
¥4.2
¥0.3
¥3.1
0.9
0.7
¥4.3
¥2.0
1.9
¥1.0
3.1
1,781
9,079
¥0.2
¥4.9
2.1
¥2.8
339
485
2,199
705
1,713
423
2,947
662
1,340
47
¥2.3
¥0.6
¥5.2
¥7.9
¥10.2
¥3.2
¥0.3
¥9.7
0.1
6.0
¥0.2
1.5
¥3.1
¥5.9
¥8.2
¥1.0
1.9
¥7.8
2.3
8.4
3,040
2,478
2,203
1,645
1,494
¥2.9
¥3.8
¥3.9
¥4.6
¥4.4
¥0.8
¥1.7
¥1.8
¥2.5
¥2.3
2,715
2,715
2,715
¥14.4
¥4.6
2.6
¥12.6
¥2.5
4.9
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:
Subtotal:
Subtotal:
Subtotal:
Subtotal:
Freestanding .........................................................................................................
Facility-based ........................................................................................................
Vol/NP ...................................................................................................................
Proprietary .............................................................................................................
Government ...........................................................................................................
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 .........................................................................................................
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 .........................................................................................................
Facility Location: Urban or Rural
Rural ............................................................................................................................................
Urban ...........................................................................................................................................
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 ..........................................................................................................................................
Other ............................................................................................................................................
mstockstill on DSK30JT082PROD with PROPOSALS2
Facility Size (Number of 1st Episodes)
< 100 episodes ............................................................................................................................
100 to 249 ....................................................................................................................................
250 to 499 ....................................................................................................................................
500 to 999 ....................................................................................................................................
1,000 or More ..............................................................................................................................
Nursing/Therapy Visits Ratio
1st Quartile (Lowest 25 Nursing) .................................................................................................
2nd Quartile .................................................................................................................................
3rd Quartile ..................................................................................................................................
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TABLE 55—ESTIMATED HHA IMPACTS BY FACILITY TYPE AND AREA OF THE COUNTRY, CY 2019—Continued
Number of
agencies
4th Quartile (Top 25 Nursing) ......................................................................................................
2,715
Implementation of the
HHGM
(not budget
neutral)
(%)
12.9
Implementation of the
HHGM
(partially budget neutral)
(%)
15.5
mstockstill on DSK30JT082PROD with PROPOSALS2
Source: CY 2016 Medicare claims data (as of March 17, 2017) for episodes ending on or before December 31, 2016 for which we had a linked
OASIS assessment.
Notes: This analysis includes assumptions on behavioral responses as a result of the new case-mix adjustment methodology and omits
360,683 individuals not grouped under the HHGM (either due to a missing OASIS, because they could be assigned to a clinical grouping, or had
missing therapy/nursing visits). After converting 60-day episodes to 30-day periods for the HHGM, a further 28 periods were excluded with missing wage index information, 17 periods with missing NRS weights, and 2,376 periods with a missing urban/rural indicator. These excluded episodes results overall in 70 fewer HHAs being represented than in Table 54.
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.
3. HHVBP Model
Table 57 displays our analysis of the
distribution of possible payment
adjustments at the 3-percent, 5-percent,
6-percent, 7-percent, and 8-percent rates
that are being used in the Model using
the 2015 and 2016 OASIS-based
measures, claims-based hospitalization
and Emergency Department (ED)
measures, and HHCAHPS data. Full
2016 data are not yet available for
claims-based and HHCAHPS-based
measures. For these measures, we used
the available data—12 months of
episodes ending September 30, 2016 for
claims-based measures and 12 months
ending June 30, 2016 for HHCAHPSbased measures. The estimated impacts
account for the minimum 40 HHCAHPS
completed surveys proposal and the
proposal to remove the OASIS-based
measure, Drug Education on All
Medications Provided to Patient/
Caregiver during all Episodes of Care
beginning in PY 3. We simulated the
impacts based on nine (9) OASIS quality
measures, two (2) claims-based
measures in QIES, and the three (3) New
Measures (using the October 2016 and
January 2017 submission data), using
the QIES Roll Up File data in the same
manner as they will be in the Model.
HHAs were classified as being in the
smaller or larger volume cohort using
the 2015 Quality Episode File, which is
created using OASIS assessments. The
basis of the payment adjustment was
derived from complete 2015 claims
data. We note that this impact analysis
is based on the aggregate value of all
nine (9) states.
Table 58 displays our analysis of the
distribution of possible payment
adjustments based on the same 2015–
2016 data used to calculate Table 57,
providing information on the estimated
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impact of the proposals in this rule. We
note that this impact analysis is based
on the aggregate value across all nine (9)
Model states. Note that all Medicarecertified HHAs that provide services in
Massachusetts, Maryland, North
Carolina, Florida, Washington, Arizona,
Iowa, Nebraska, and Tennessee are
required to compete in this Model. This
analysis reflects that under our
proposal, only HHAs that have data for
at least five measures that meet the
requirements of proposed § 484.305
would be included in the LEF and
would have a payment adjustment
calculated. Value-based incentive
payment adjustments for the estimated
1,600 plus HHAs in the selected states
that will compete in the HHVBP Model
are stratified by size as described in
section IV.B. of the CY 2017 HH PPS
final rule. As finalized in section IV.B.
of the CY 2017 final rule, there must be
a minimum of eight (8) HHAs in any
cohort.
Those HHAs that are in states that do
not have at least eight smaller-volume
HHAs will not have a separate smallervolume cohort and thus there will only
be one cohort that will include all the
HHAs in that state. As indicated in
Table 58, Maryland, North Carolina,
Tennessee and Washington will only
have one cohort while Arizona, Florida,
Iowa, Massachusetts, and Nebraska will
have both a smaller-volume cohort and
a larger-volume cohort. For example,
Iowa has 32 HHAs eligible to be exempt
from being required to have their
beneficiaries complete HHCAHPS
surveys because they provided HHA
services to less than 60 beneficiaries.
Therefore, those 32 HHAs would be
competing in Iowa’s smaller-volume
cohort for the 2016 performance year
under the Model.
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Using 2015–2016 data and the
maximum payment adjustment for
performance year 1 of 3-percent (as
applied in CY 2018), based on the nine
(9) OASIS quality measures, two (2)
claims-based measures in QIES, the five
(5) HHCAHPS measures, and the three
(3) New Measures, the smaller-volume
HHAs in Iowa would have a mean
payment adjustment of 0.0 percent
(Table 58). Only 10-percent of HHAs in
the smaller-volume cohort would be
subject to downward payment
adjustments of more than minus 1.4
percent (¥1.4 percent). The next
columns provide the distribution of
scores by percentile; we see that the
cohort payment adjustment distribution
for HHAs in Iowa in the smaller-volume
cohort ranges from ¥1.4 percent at the
10th percentile to +1.3 percent at the
90th percentile, while the cohort
payment adjustment distribution
median is ¥0.2 percent.
Table 59 provides the payment
adjustment distribution based on agency
size, proportion of dually-eligible
beneficiaries, average case mix (using
the average case-mix for non-LUPA
episodes), the proportion of the HHA’s
beneficiaries that reside in rural areas
and HHA organizational status. HHAs
with a higher proportion of duallyeligible beneficiaries and HHAs whose
beneficiaries have higher acuity tend to
have better performance.
The payment adjustment percentages
were calculated at the state and size
cohort level. Hence, the values of each
separate analysis in the tables are
representative of the baseline year of
2015 and the performance year of 2016
(though full 2016 data are not yet
available for claims- and HHCAHPSbased measures). There were 1,674
HHAs in the nine selected states out of
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completed HHCAHPS surveys versus 20
or more completed HHCAHPS surveys.
The percentage difference in the average
TPS across all larger-volume HHAs for
each state ranged from ¥0.4 percent
through 2.2 percent and the majority of
states were close to zero. We include
information on average statewide TPS
(by size cohort) because this is what is
used to determine payment adjustment
amounts in HHVBP. The relative
1,894 HHAs that had a sufficient
number of measures to receive a
payment adjustment in the Model. It is
expected that a certain number of HHAs
will not have a payment adjustment
because they may be servicing too small
of a population to report on an adequate
number of measures to calculate a TPS.
Additional analysis (see Table 60) was
conducted to illustrate the effect of our
proposal to require 40 or more
ranking of one HHA’s TPS to the
average TPS will directly affect the
HHA’s payment adjustment amount.
The reporting of TPS also shows that
this change has no impact on the TPS
for the smaller volume cohort, for which
the HHCAHPS measures are not used
(regardless of the minimum sample
size).
TABLE 57—ADJUSTMENT DISTRIBUTION BY PERCENTILE LEVEL OF QUALITY TOTAL PERFORMANCE SCORE AT DIFFERENT
MODEL PAYMENT ADJUSTMENT RATES
[Percentage]
Range
(%)
Payment adjustment distribution
3%
5%
6%
7%
8%
Payment
Payment
Payment
Payment
Payment
Adjustment
Adjustment
Adjustment
Adjustment
Adjustment
For
For
For
For
For
Performance
Performance
Performance
Performance
Performance
Year
Year
Year
Year
Year
1
2
3
4
5
of
of
of
of
of
the
the
the
the
the
Model
Model
Model
Model
Model
.....
.....
.....
.....
.....
3.0
5.0
6.0
7.0
8.0
10%
¥1.5
¥2.5
¥2.9
¥3.4
¥3.9
20%
30%
¥1.0
¥1.6
¥2.0
¥2.3
¥2.6
¥0.7
¥1.1
¥1.3
¥1.5
¥1.8
40%
¥0.4
¥0.7
¥0.8
¥0.9
¥1.1
Median
(%)
60%
¥0.1
¥0.1
¥0.2
¥0.2
¥0.2
70%
0.2
0.4
0.4
0.5
0.6
0.6
0.9
1.1
1.3
1.5
80%
0.9
1.5
1.8
2.1
2.4
90%
1.5
2.6
3.1
3.6
4.1
TABLE 58—HHA COHORT PAYMENT ADJUSTMENT DISTRIBUTIONS BY STATE/COHORT
[Based on a 3-percent payment adjustment]
# of
HHAs
Cohort
Average
payment
adj. %
10%
20%
30%
40%
50%
60%
70%
80%
90%
HHA Cohort in States with no small cohorts (percent)
MD .........................................................................
NC .........................................................................
TN ..........................................................................
WA .........................................................................
51
167
124
57
0.0
¥0.1
¥0.2
¥0.2
¥1.0
¥1.3
¥1.4
¥1.1
¥0.8
¥0.9
¥0.9
¥0.9
¥0.6
¥0.6
¥0.7
¥0.6
¥0.4
¥0.3
¥0.5
¥0.3
0.1
¥0.1
¥0.1
0.0
0.3
0.1
0.1
0.2
0.5
0.4
0.5
0.3
0.6
0.7
0.7
0.4
1.1
0.9
1.0
0.7
¥1.0
¥0.2
¥0.2
¥1.3
0.5
¥0.9
0.6
0.2
¥0.9
1.0
0.4
1.1
0.6
0.1
1.8
1.4
1.6
1.1
1.2
2.4
2.1
2.9
1.3
1.2
3.1
¥0.3
0.0
¥0.2
¥0.3
0.2
0.2
0.3
0.1
0.1
0.3
0.6
0.7
0.5
0.3
0.7
0.7
1.1
0.9
0.7
0.9
1.2
1.8
1.4
1.1
1.1
Smaller-volume HHA Cohort in states with small cohort (percent)
AZ ..........................................................................
FL ..........................................................................
IA ...........................................................................
MA .........................................................................
NE .........................................................................
¥0.4
0.2
0.0
¥0.7
0.4
8
103
32
23
16
¥2.4
¥1.7
¥1.4
¥2.6
¥1.8
¥1.7
¥1.3
¥1.0
¥2.0
¥1.3
¥1.3
¥0.8
¥0.7
¥1.7
¥1.2
¥1.1
¥0.5
¥0.5
¥1.5
¥0.7
Large-volume HHA Cohort in states with small cohorts (percent)
AZ ..........................................................................
FL ..........................................................................
IA ...........................................................................
MA .........................................................................
NE .........................................................................
¥0.1
0.1
¥0.1
¥0.2
0.1
105
723
94
111
44
¥1.5
¥1.4
¥1.5
¥1.6
¥1.3
¥1.0
¥0.9
¥1.1
¥1.2
¥0.9
¥0.7
¥0.6
¥0.7
¥0.8
¥0.5
¥0.5
¥0.3
¥0.4
¥0.5
¥0.1
TABLE 59—PAYMENT ADJUSTMENT DISTRIBUTIONS BY CHARACTERISTICS
[Based on a 3-percent payment adjustment]
# of
HHAs
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Cohort
Small HHA (<60 patients in CY 2015) ..................
Large HHA (≥60 patients in CY 2015) ..................
Low % Dually—Eligible .........................................
Medium % Dually—Eligible ...................................
High % Dually—Eligible ........................................
Low Acuity .............................................................
Mid Acuity ..............................................................
High Acuity ............................................................
All non-rural beneficiaries .....................................
Up to 35% rural beneficiaries ...............................
Over 35% rural beneficiaries ................................
Non-Profit HHAs ....................................................
For-Profit HHAs .....................................................
Government HHAs ................................................
Freestanding .........................................................
Facility-based ........................................................
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Average
payment
adj. %
189
1,469
414
830
414
415
828
414
989
389
280
304
1,238
116
1,494
164
PO 00000
0.1
0.0
0.1
¥0.1
0.1
¥0.3
0.0
0.4
0.1
¥0.1
¥0.1
0.1
0.0
¥0.1
0.0
0.0
Frm 00119
10%
¥1.8
¥1.4
¥1.1
¥1.4
¥1.7
¥1.8
¥1.3
¥1.1
¥1.5
¥1.5
¥1.4
¥1.2
¥1.5
¥1.3
¥1.5
¥1.2
Fmt 4701
20%
30%
¥1.4
¥1.0
¥0.8
¥1.0
¥1.3
¥1.4
¥0.9
¥0.6
¥1.0
¥1.0
¥1.0
¥0.8
¥1.0
¥1.0
¥1.0
¥0.9
Sfmt 4702
230 231
¥1.0
¥0.6
¥0.5
¥0.7
¥0.8
¥1.0
¥0.6
¥0.3
¥0.7
¥0.6
¥0.7
¥0.6
¥0.7
¥0.7
¥0.7
¥0.5
40%
¥0.6
¥0.4
¥0.2
¥0.4
¥0.5
¥0.7
¥0.4
0.0
¥0.4
¥0.4
¥0.5
¥0.3
¥0.4
¥0.5
¥0.4
¥0.3
E:\FR\FM\28JYP2.SGM
50%
¥0.2
¥0.1
0.1
¥0.2
0.0
¥0.5
¥0.1
0.3
0.0
¥0.1
¥0.2
0.0
¥0.1
¥0.3
¥0.1
0.0
28JYP2
60%
0.5
0.2
0.4
0.1
0.4
¥0.1
0.2
0.6
0.3
0.1
0.0
0.3
0.2
0.0
0.2
0.3
70%
1.1
0.5
0.6
0.4
0.9
0.2
0.5
0.9
0.7
0.4
0.4
0.6
0.6
0.3
0.6
0.5
80%
1.3
0.8
0.9
0.7
1.5
0.6
0.8
1.3
1.1
0.7
0.8
0.9
0.9
0.6
0.9
0.8
90%
2.6
1.5
1.4
1.2
2.3
1.2
1.4
2.2
1.9
1.1
1.3
1.4
1.6
1.2
1.6
1.2
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TABLE 60—IMPACT OF CHANGING MINIMUM REQUIRED SAMPLE SIZE FOR HHCAHPS PERFORMANCE MEASURES ON
AVERAGE TPS AND PAYMENT ADJUSTMENT RANGE 232
Average TPS
HHA
count
State
20
Minimum
40
Minimum
Minimum payment
adjustment
%
Difference
Difference
Maximum payment
adjustment
20
Minimum
(%)
40
Minimum
(%)
20 Minimum
(%)
40 Minimum
(%)
Larger-Volume HHAS
AZ .................................
FL .................................
IA ..................................
MA ................................
MD ................................
NC ................................
NE ................................
TN ................................
WA ...............................
105
723
94
111
50
164
44
121
57
38.393
36.794
41.079
40.074
47.287
43.738
39.714
45.699
49.888
39.254
37.451
41.049
39.927
47.517
44.175
40.581
45.749
49.685
0.86
0.657
¥0.03
¥0.147
0.23
0.437
0.867
0.05
¥0.203
2.2
1.8
¥0.1
¥0.4
0.5
1.0
2.1
0.1
¥0.4
¥2.6
¥2.6
¥2.4
¥2.8
¥1.2
¥2.0
¥1.8
¥2.8
¥1.4
¥2.6
¥2.6
¥2.4
¥2.8
¥1.2
¥2.0
¥1.8
¥2.6
¥1.8
3.0
3.0
2.0
2.6
2.0
2.2
2.9
1.8
1.2
3.0
3.0
3.0
2.6
2.4
2.2
2.7
1.8
1.2
Total ......................
1,469
................
....................
....................
................
................
................
....................
....................
Smaller-Volume HHAS
AZ .................................
FL .................................
IA ..................................
MA ................................
MD ................................
NC ................................
NE ................................
TN ................................
8
103
32
23
1
3
16
3
31.474
37.349
37.741
26.904
55.841
67.1
37.076
48.549
31.474
37.349
37.741
26.904
55.841
67.1
37.076
48.549
0
0
0
0
0
0
0
0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
¥2.4
¥2.6
¥1.9
¥2.7
0.6
¥0.2
¥2.8
¥1.4
¥2.4
¥2.6
¥1.9
¥2.7
0.6
¥0.2
¥2.8
¥1.4
2.1
3.0
2.0
3.0
0.6
3.0
3.0
2.3
2.1
3.0
2.0
3.0
0.6
3.0
3.0
2.3
Total ......................
189
................
....................
....................
................
................
................
....................
....................
Total ......................
1,658
................
....................
....................
................
................
................
....................
....................
4. HH QRP
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Failure to submit data required under
section 1895(b)(3)(B)(v) of the Act will
result in the reduction of the annual
update to the standard federal rate for
discharges occurring during such fiscal
year by 2 percentage points for any HHA
that does not comply with the
requirements established by the
Secretary. At the time that this analysis
was prepared, 513, or approximately 4.3
percent, of the 12,149 active Medicarecertified HHAs, did not receive the full
annual percentage increase for the CY
2017 annual payment update
determination. Information is not
available to determine the precise
number of HHAs that will not meet the
230 Rural beneficiaries identified based on the
CBSA code reported on the claim.
231 Acuity is based on the average case-mx weight
for non-LUPA episodes. Low acuity is defined as
the bottom 25% (among HHVBP model
participants); mid-acuity is the middle 50% and
high acuity is the highest 25%. Note that one HHA
was missing acuity information.
232 OASIS measures run from January 1, 2015 to
December 31, 2016; Claims from September 1, 2015
to September 30, 2016. Payment based on 2015 and
2016 Medicare claims data (2016 is used as the
payment year—in actuality CY 2018 claims
payments would determine actual payment
adjustment amounts).
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requirements to receive the full annual
percentage increase for the CY 2018
payment determination.
As noted in section VII.B. of this
proposed rule, the net effect of our
proposals is an estimated decrease in
cost associated with proposed changes
to the HH QRP on average of $3,700.74
per HHA annually, or $44,952,846.87
for all HHAs annually.
D. Alternatives Considered
1. HH PPS for CY 2018
We did not consider extending the
rural add-on payment as this provision
was statutory. Section 421(a) of the
MMA extended 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, for episodes
and visits ending before January 1, 2018.
Therefore, for episodes and visits that
end on or after January 1, 2018, a rural
add-on payment will not apply.
In the alternatives considered section
for the CY 2016 HH PPS proposed rule
(80 FR 39839), we considered reducing
the 60-day episode rate in CY 2016 only
to account for nominal case-mix growth
between CY 2012 and CY 2014.
However, we instead proposed to
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reduce the 60-day episode rate over a
2-year period (CY 2016 and CY 2017) to
lessen the impact on HHAs in a given
year. In the CY 2016 HH PPS final rule
(80 FR 68624), we finalized a reduction
of 0.97 percent to the 60-day episode
rate in each of the next 3 calendar years
(CY 2016 through CY 2018. Therefore,
the alternatives with regards to the 0.97
percent reduction in the national,
standardized 60-day episode payment
amount for CY 2018 were already
considered in the CY 2016 HH PPS
proposed and final rules and we did not
consider alternatives for implementing
this reduction for CY 2018.
We are not able to consider alternative
values for the home health payment
update percentage. The home health
payment update percentage is based on
the home health market basket update
and section 1895(b)(3)(B) of the Act, as
amended by section 411(d) of the
MACRA, mandates that for home health
payments for CY 2018, the market
basket percentage increase shall be 1
percent.
2. HH PPS for CY 2019 (Proposed
HHGM)
We considered proposing to
implement the HHGM for CY 2018.
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However, implementation of the HHGM
will require provider education and
training, updating and revising relevant
manuals, and changing assessment and
claims processing systems.
Implementation starting in 2019 would
provide an opportunity for CMS and
providers to prepare.
For CY 2019, in addition to
considering whether to implement the
HHGM in a fully non-budget neutral
manner for CY 2019 or implementing
the HHGM with a HHGM partial budget
neutrality adjustment factor that would
have reduced the estimated impact of
the HHGM by 50 percent in CY 2019
and the elimination of such factor in CY
2020, we also considered implementing
the HHGM as fully budget neutral in CY
2019 or as partially budget-neutral with
longer phase-out period (for example
starting with a HHGM partial budget
neutrality adjustment factor that would
have reduced the estimated impact of
the HHGM by 75 percent in CY 2019, a
HHGM partial budget neutrality
adjustment factor that would have
reduced the estimated impact of the
HHGM by 50 percent in CY 2020, a
HHGM partial budget neutrality
adjustment factor that would have
reduced the estimated impact of the
HHGM by 25 percent in CY 2021, and
the elimination of such factor in CY
2022). However, we propose to
implement the change in the unit of
payment under the HHGM in a nonbudget neutral manner as doing so
better aligns home health payments
with the costs of providing care. In
addition, we do not believe a longer
phase-out period is necessary if we were
to implement the HHGM in a nonbudget neutral manner with a HHGM
partial budget neutrality adjustment
factor applied in CY 2019 to be removed
in CY 2020, as this 2-year timeframe
would be sufficient to lessen the
economic impact in the first year of
implementation.
We also considered maintaining
60-day episodes of care as the unit of
payment. As stated in the FY 2001 HH
PPS final rule, ‘‘We believe the 60-day
episode definition is the most
appropriate approach to define the unit
of payment under HHA PPS. Public
support for the 60-day episode as the
unit of payment under PPS centered on
the general consensus that HHAs and
physicians predict home care needs
over a 60-day timeframe due to current
plan of care requirements and required
updates to the comprehensive
assessments that basically follow a 60day timeframe. As discussed in detail in
the proposed rule, research indicated
that the 60-day episode captures the
majority of stays experienced in the
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Phase II per-episode HHA PPS
demonstration (65 FR 41136).’’
However, we further noted that we ‘‘will
continue to monitor the appropriateness
of the 60-day unit of payment and may
consider modifying our approach to the
episode definition in subsequent years
of PPS, if warranted.’’ During
subsequent years, we have identified
variation in average resource use
between the first 30-day period within
a 60-day episode and the second 30-day
period within a 60-day episode. This
difference in resources between the first
and second 30-day periods within a 60day episode led to the development of
30-day periods for the HHGM. In
addition, the accuracy of the HHGM
improves when a shorter, more
constrained time period is examined.
This in turn would improve the
accuracy of the case-mix weights that
are generated using 30-day periods
instead of 60-day episodes. We note that
the frequency of the required updates to
the plan of care and the comprehensive
assessment would remain unchanged
under the proposed HHGM.
We considered whether to continue
using the wage-weighted minutes of
care (WWMC) approach to estimate
resource use under the HHGM, as
described in section III.E.2 of this
proposed rule. Although the
relationship in relative costs between
the WWMC approach and the proposed
cost-per-minute plus non-routine
supplies (CPM+NRS) approach is very
similar (correlation coefficient equal to
0.8016), the WWMC approach does not
as evenly weight skilled nursing costs
relative to therapy costs as evidenced in
the cost report data and would require
us to maintain a separate case-mix
adjustment mechanism for NRS. If we
were to maintain the current WWMC
approach, skilled nursing and therapy
costs would not be as evenly weighted
and a certain level of complexity in
calculating payments under the HH PPS
would persist as we would need to
continue with the current method of
case-mix adjusting NRS payments
separate from service costs (i.e., skilled
nursing, physical therapy, occupational
therapy, speech-language pathology,
home health aide, and medical social
services) under the HH PPS.
Finally, we considered not proposing
the HH PPS case-mix methodology
refinements for CY 2019. However, in
maintaining the current case-mix
methodology, the current payment
system, with its various therapy
thresholds, would continue to provide
financial incentives that detract from a
focus on patient characteristics and care
needs when agencies are setting plans of
care for their patients, and would
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35389
continue to incentivize unnecessary
therapy utilization. The proposed
HHGM removes therapy thresholds from
the case-mix adjustment methodology
thereby eliminating the financial
incentive to provide unnecessary
therapy visits in order to maximize
payment. In addition, we believe the
proposed HHGM is a more simplified,
clinically intuitive, and patient-centered
approach to payment compared to the
existing case-mix adjustment
methodology. We invite comments on
the alternatives discussed in this
analysis.
3. HHVBP Model Proposals
An alternative to our proposal to use
40 completed HHCAHPS surveys
beginning with PY 1 would be to
continue calculating quality scores at 20
completed HHCAHPS surveys as
finalized in the CY 2016 HH PPS final
rule.
Another alternative would be to use
40 completed HHCAHPS surveys
beginning with PY 2 and subsequent
years, but keep the 20 completed
HHCAHPS surveys calculation for PY 1;
however, this would give HHAs a short
amount of time to analyze from year to
year a change in threshold from 20 to 40
completed HHCAHPS surveys.
Rather than removing the Drug
Education on All Medications Provided
to Patient/Caregiver during all Episodes
of Care measure from the set of
applicable measures, an alternative
would be to keep the measure in the set
of applicable measures for the HHVBP
Model. Doing so would continue HHAs’
awareness of the importance of drug
education for patient and caregivers
during all episodes of care.
Nevertheless, there would be a lack of
variability in the measure across the
participating HHAs and the measure
does not address the quality or intensity
of the education provided.
E. Accounting Statement and Table
As required by OMB Circular A–4
(available at https://
www.whitehouse.gov/omb/circulars_
a004_a-4), in Tables 61 and 62, 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 61 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 in CY 2018.
Table 62 provides our estimate as a
result of the changes associated with the
HHGM proposed for CY 2019. Table 63
provides our best estimates of the
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changes associated with the HH QRP
proposals.
TABLE 61—ACCOUNTING STATEMENT:
HH PPS CLASSIFICATION OF ESTIMATED TRANSFERS, FROM CYS
2017 TO 2018
Category
Annualized Monetized
Transfers.
TABLE 61—ACCOUNTING STATEMENT:
HH PPS CLASSIFICATION OF ESTIMATED TRANSFERS, FROM CYS
2017 TO 2018—Continued
Category
Transfers
¥$80 million.
From Whom to
Whom?
Transfers
Federal Government
to HHAs.
TABLE 62—ACCOUNTING STATEMENT: HH PPS CLASSIFICATION OF ESTIMATED TRANSFERS DUE TO IMPLEMENTATION OF
PROPOSED HHGM, FROM CYS 2018 TO 2019
Category
Transfers
Annualized Monetized Transfers (Not Budget Neutral) ...........................
Annualized Monetized Transfers (Partially Budget Neutral) ....................
From Whom to Whom? ............................................................................
¥$950 million.
¥$480 million.
Federal Government to HHAs.
TABLE 63—ACCOUNTING STATEMENT: HH QRP CLASSIFICATION OF ESTIMATED COSTS, FROM CYS 2018 TO 2019
Category
Costs
Annualized Monetized Net Burden for HHAs Submission of the OASIS
F. Reducing Regulation and Controlling
Regulatory Costs
Executive Order 13771, entitled
Reducing Regulation and Controlling
Regulatory Costs (82 FR 9339), was
issued on January 30, 2017. Under E.O.
13771, this rule would be considered
deregulatory if finalized as proposed.
G. Conclusion
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1. HH PPS
In conclusion, we estimate that the
net impact of the HH PPS policies in
this rule is a decrease of 0.4 percent, or
$80 million, in Medicare payments to
HHAs for CY 2018. The ¥$80 million
impact reflects the effects of a 0.5
percent reduction in payments due to
the sunset of the rural add-on provision
($100 million decrease), a 1 percent CY
2018 HH payment update percentage
($190 million increase), and a 0.9
percent decrease in payments due to the
0.97 percent reduction to the national,
standardized 60-day episode payment
rate in CY 2017 to account for nominal
case-mix growth ($170 million
decrease). We estimate that the net
impact of the proposed HHGM is a
decrease of 4.3 percent ($950 million
decrease) in Medicare payments to
HHAs in CY 2019 if the proposed
HHGM is implemented in a fully nonbudget neutral manner. We estimate that
the net impact of the proposed HHGM
is a decrease of 2.2 percent ($480
million decrease) in Medicare payments
to HHAs in CY 2019 if the proposed
HHGM is implemented in a partially
budget-neutral manner in CY 2019 with
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¥$44.9 million.
the removal of the HHGM partial budget
neutrality adjustment factor in CY 2020.
This analysis, together with the
remainder of this preamble, provides an
initial Regulatory Flexibility Analysis.
2. HHVBP Model
In conclusion, we estimate there
would be no net impact (to include
either a net increase or reduction in
payments) in this proposed rule in
Medicare payments to HHAs competing
in the HHVBP Model for CY 2018.
However, the overall economic impact
of the HHVBP Model provision is an
estimated $378 million in total savings
from a reduction in unnecessary
hospitalizations and SNF usage as a
result of greater quality improvements
in the home health industry over the life
of the HHVBP Model.
3. HH QRP
In conclusion, for CY 2019 we
estimate that there will be a total
decrease in costs of $44,952,846.87
associated with the proposed changes to
the HH QRP.
X. 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
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substantial direct effects on the rights,
roles, and responsibilities of states, local
or tribal governments.
In accordance with the provisions of
Executive Order 12866, this regulation
was reviewed by the Office of
Management and Budget.
List of Subjects
42 CFR Part 409
Health facilities, Medicare.
42 CFR Part 484
Health facilities, Health professions,
Medicare, 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 Act
(42 U.S.C. 1302 and 1395hh).
2. Section § 409.43 is amended by—
a. Revising paragraphs (c)(2) and
(c)(3)(ii);
■ b. In paragraph (e)(1)(iii), removing
the phrase ‘‘during the 60-day episode’’
and adding in its place the phrase
‘‘within 60 days after discharge’’.
The revisions read as follows:
■
■
§ 409.43
Plan of care requirements.
*
*
*
*
*
(c) * * *
(2) Reduction or disapproval of
anticipated payment requests. CMS has
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the authority to reduce or disapprove
requests for anticipated payments in
situations when protecting Medicare
program integrity warrants this action.
Since the request for anticipated
payment is based on verbal orders as
specified in paragraph (c)(1)(i) of this
section and/or a prescribing referral as
specified in paragraph (c)(1)(ii) of this
section and is not a Medicare claim for
purposes of the Act (although it is a
‘‘claim’’ for purposes of Federal, civil,
criminal, and administrative law
enforcement authorities, including but
not limited to the Civil Monetary
Penalties Law (as defined in 42 U.S.C.
1320a–7a(i)(2)), the Civil False Claims
Act (as defined in 31 U.S.C. 3729(c)),
and the Criminal False Claims Act (18
U.S.C. 287)), the request for anticipated
payment will be canceled and recovered
unless the claim is submitted within the
greater of one of the following:
(i) 60 days from the end of the episode
(for claims beginning on or before
December 31, 2018);
(ii) 60 days from the end of the 30-day
period of care (for claims beginning on
or after January 1, 2019); or
(iii) 60 days from the issuance of the
request for anticipated payment.
(3) * * *
(ii) Before the claims for each episode
(for a 60-day episode of care beginning
on or before December 31, 2018) or
period (for a 30-day period of care
beginning on or after January 1, 2019)
for services is submitted for the final
percentage prospective payment.
*
*
*
*
*
PART 484—HOME HEALTH SERVICES
3. The authority citation for part 484
continues to read as follows:
■
Authority: Secs. 1102 and 1871 of the Act
(42 U.S.C. 1302 and 1395(hh)) unless
otherwise indicated.
4. Section 484.202 is amended by
revising the definitions of ‘‘Rural area’’
and ‘‘Urban area’’ to read as follows:
■
§ 484.202
Definitions.
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*
*
*
*
*
Rural area means an area defined in
§ 412.64(b)(1)(ii)(C) of this chapter.
Urban area means an area defined in
§ 412.64(b)(1)(ii)(A) and (B) of this
chapter.
■ 5. Section 484.205 is revised to read
as follows:
§ 484.205
Basis of payment.
(a) Method of payment. An HHA
receives a national, standardized
prospective payment amount for home
health services previously paid on a
reasonable cost basis (except the
osteoporosis drug defined in section
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1861(kk) of the Act) as of August 5,
1997. The national, standardized
prospective payment is determined in
accordance with § 484.215.
(b) Unit of payment. For episodes
beginning on or before December 31,
2018, an HHA receives a national,
standardized prospective 60-day
episode payment amount. For periods
beginning on or after January 1, 2019, a
HHA receives a national, standardized
prospective 30-day payment amount.
(c) OASIS data. A HHA must submit
to CMS the OASIS data described at
§ 484.55(b) and (d) in order for CMS to
administer the payment rate
methodologies described in §§ 484.215,
484.220, 484.230, 484.235, and 484.240.
(d) Payment adjustments. The
national, standardized prospective
payment amount is subject to the
following adjustments and additional
payments:
(1) A low-utilization payment
adjustment (LUPA) of a predetermined
per-visit rate as specified in § 484.230.
(2) A partial payment adjustment as
specified in § 484.235.
(3) An outlier payment as specified in
§ 484.240.
(e) Medical review. All payments
under this system may be subject to
medical review with respect to
beneficiary eligibility, medical
necessity, and case-mix group
assignment.
(f) Durable medical equipment (DME)
and disposable devices. DME provided
as a home health service as defined in
section 1861(m) of the Act is paid the
fee schedule amount. Separate payment
is made for ‘‘furnishing NPWT using a
disposable device,’’ as that term is
defined in § 484.202, and is not
included in the national, standardized
prospective payment amount.
(g) Split percentage payments. Split
percentage payments are made in
accordance with requirements at
§ 409.43(c) of this chapter.
(1) Split percentage payments for
episodes beginning on or before
December 31, 2018:
(i) The initial payment for initial
episodes is paid to an HHA at 60
percent of the case-mix and wageadjusted 60-day episode rate. The
residual final payment for initial
episodes is paid at 40 percent of the
case-mix and wage-adjusted 60-day
episode rate.
(ii) The initial payment for
subsequent episodes is paid to an HHA
at 50 percent of the case-mix and wageadjusted 60-day episode rate. The
residual final payment for subsequent
episodes is paid at 50 percent of the
case-mix and wage-adjusted 60-day
episode rate.
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(2) Split percentage payments for
periods beginning on or after January 1,
2019:
(i) The initial payment for initial 30day periods is paid to an HHA at 60
percent of the case-mix and wageadjusted 30-day payment rate. The
residual final payment for initial 30-day
periods is paid at 40 percent of the casemix and wage-adjusted 30-day payment
rate.
(ii) The initial payment for
subsequent 30-day periods is paid to an
HHA at 50 percent of the case-mix and
wage-adjusted 30-day payment rate. The
residual final payment for subsequent
30-day periods is paid at 50 percent of
the case-mix and wage-adjusted 30-day
payment rate.
§ 484.210
[Removed and Reserved]
6. Section 484.210 is removed and
reserved.
■ 7. Section 484.215 is amended by—
■ a. Revising the section heading;
■ b. Revising paragraph (d) introductory
text; and
■ c. Adding paragraph (f).
The revisions and addition read as
follows:
■
§ 484.215 Initial establishment of the
calculation of the national, standardized
prospective 60-day episode payment and
30-day payment rates.
*
*
*
*
*
(d) Calculation of the unadjusted
national average prospective payment
amount for the 60-day episode. For
episodes beginning on or before
December 31, 2018, CMS calculates the
unadjusted national 60-day episode
payment in the following manner:
*
*
*
*
*
(f) For periods beginning on or after
January 1, 2019, a national,
standardized prospective 30-day
payment rate applies. The national,
standardized prospective 30-day
payment rate is an amount determined
by the Secretary, as subsequently
updated pursuant to § 484.225.
■ 8. Section 484.220 is amended by—
■ a. Revising the section heading;
■ b. Revising the introductory text; and
■ c. In paragraph (a) introductory text,
removing the phrase ‘‘national
prospective 60-day episode’’ and adding
in its place the phrase ‘‘national,
standardized prospective’’.
The revisions read as follows:
§ 484.220 Calculation of the case-mix and
wage area adjusted prospective payment
rates.
CMS adjusts the national,
standardized prospective payment rates
as referenced in § 484.215 to account for
the following:
*
*
*
*
*
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9. Section 484.225 is amended by—
a. Revising the section heading;
b. Revising paragraph (a);
c. In paragraphs (b) and (c), removing
the phrase ‘‘national prospective 60-day
episode’’ and adding the phrase
‘‘national standardized prospective’’;
and
■ d. Adding paragraph (d).
The revisions and addition read as
follows:
■
■
■
■
§ 484.225 Annual update of the unadjusted
national, standardized prospective payment
rates.
(a) CMS annually updates the
unadjusted national, standardized
prospective payment rate on a calendar
year basis in accordance with section
1895(b)(3)(B) of the Act.
*
*
*
*
*
(d) For CY 2019, the national,
standardized prospective 30-day
payment amount is an amount
determined by the Secretary. CMS
annually updates this amount on a
calendar year basis in accordance with
paragraphs (a) through (c) of this
section.
■ 10. Section 484.230 is revised to read
as follows:
mstockstill on DSK30JT082PROD with PROPOSALS2
§ 484.230 Low-utilization payment
adjustments.
(a) For episodes beginning on or
before December 31, 2018, an episode
with four or fewer visits is paid the
national per-visit amount by discipline
updated annually by the applicable
market basket for each visit type, in
accordance with § 484.225. The national
per-visit amount is adjusted by the
appropriate wage index based on the
site of service of the beneficiary. An
amount will be added to the lowutilization payment adjustments for
low-utilization episodes that occur as
the beneficiary’s only episode or initial
episode in a sequence of adjacent
episodes. For purposes of the home
health PPS, a sequence of adjacent
episodes for a beneficiary is a series of
claims with no more than 60 days
without home care between the end of
one episode, which is the 60th day
(except for episodes that have been PEPadjusted), and the beginning of the next
episode.
(b) For periods beginning on or after
January 1, 2019, an HHA receives a
national 30-day payment of a
predetermined rate for home health
services, unless CMS determines at the
end of the 30-day period that the HHA
furnished minimal services to a patient
during the 30-day period. For each
payment group used to case-mix adjust
the 30-day payment rate, the 10th
percentile value of total visits during a
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30-day period of care will be used to
create payment group specific
thresholds with a minimum threshold of
at least 2 visits for each case-mix group.
A 30-day period with a total number of
visits less than the threshold is paid the
national per-visit amount by discipline
updated annually by the applicable
market basket for each visit type. The
national per-visit amount is adjusted by
the appropriate wage index based on the
site of service for the beneficiary.
(c) An amount will be added to lowutilization payment adjustments for
low-utilization periods that occur as the
beneficiary’s only 30-day period or
initial 30-day period in a sequence of
adjacent periods of care. For purposes of
the home health PPS, a sequence of
adjacent periods of care for a beneficiary
is a series of claims with no more than
60 days without home care between the
end of one period, which is the 30th day
(except for episodes that have been
partial payment adjusted), and the
beginning of the next episode.
■ 11. Section 484.235 is revised to read
as follows:
§ 484.235
Partial payment adjustments.
(a) Partial episode payments (PEPs)
for episodes beginning on or before
December 31, 2018. (1) An HHA
receives a national, standardized 60-day
payment of a predetermined rate for
home health services unless CMS
determines that an intervening event
has occurred, which warrants a new 60day episode for purposes of payment. A
start of care OASIS assessment and
physician certification of the new plan
of care are required. An intervening
event is defined as either a beneficiary
elected transfer or a discharge with
goals met or no expectation of return to
home health, but the beneficiary
returned to home health during the 60day episode.
(2) The PEP adjustment will not apply
in situations of transfers among HHAs
under 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 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.
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(3) If the intervening event warrants a
new 60-day 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 based on the
first billable visit date through and
including the last billable visit date. The
PEP is calculated by determining the
actual days served as a proportion of 60
multiplied by the initial 60-day
payment amount.
(b) Partial payment adjustments for
periods beginning on or after January 1,
2019. (1) An HHA receives a national,
standardized 30-day payment of a
predetermined rate for home health
services unless CMS determines that an
intervening event has occurred, which
warrants a new 30-day period for
purposes of payment. A start of care
OASIS assessment and physician
certification of the new plan of care are
required. An intervening event is
defined as either a beneficiary elected
transfer or a discharge and return to
home health during the 30-day period.
(2) The partial payment 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
30-day period. The common ownership
exception to the transfer partial
payment adjustment does not apply if
the beneficiary moves to a different
MSA or Non-MSA during the 30-day
period 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 30-day payment and thus a new
physician certification and a new plan
of care, the initial HHA receives a
partial payment adjustment reflecting
the length of time the patient remained
under its care based on the first billable
visit date through and including the last
billable visit date. The partial payment
is calculated by determining the actual
days served as a proportion of 30
multiplied by the initial 30-day
payment amount.
■ 12. Section 484.240 is revised to read
as follows:
§ 484.240
Outlier payments.
(a) For episodes beginning on or
before December 31, 2018, an HHA
receives an outlier payment for an
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episode whose estimated costs exceeds
a threshold amount for each case-mix
group. 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.
(b) For periods beginning on or after
January 1, 2019, an HHA receives an
outlier payment for a 30-day period
whose estimated cost exceeds a
threshold amount for each case-mix
group. The outlier threshold for each
case-mix group is the 30-day payment
amount for that group, or the partial
payment adjustment amount for the 30day period, plus a fixed dollar loss
amount that is the same for all case-mix
groups.
(c) The outlier payment is a
proportion of the amount of estimated
cost beyond the threshold.
(d) CMS estimates the cost for each
episode by multiplying the national per15 minute unit amount of each
discipline by the number of 15 minute
units in the discipline and computing
the total estimated cost for all
disciplines.
■ 13. Section 484.250 is amended by
revising paragraph (a)(1) and adding
paragraphs (d) through (f) to read as
follows:
§ 484.250
Patient assessment data.
mstockstill on DSK30JT082PROD with PROPOSALS2
(a) * * *
(1) The OASIS data described at
§ 484.55(b) and (d) for CMS to
administer the payment rate
methodologies described in §§ 484.215,
484.220, 484. 230, 484.235, and 484.240;
and to meet the quality reporting
requirements of section 1895(b)(3)(B)(v)
of the Act.
*
*
*
*
*
(d) Exceptions and extension
requirements. (1) A HHA may request
and CMS may grant exceptions or
extensions to the reporting requirements
under section 1895(b)(3)(B)(v) of the Act
for one or more quarters, when there are
certain extraordinary circumstances
beyond the control of the HHA.
(2) A HHA may request an exception
or extension within 90 days of the date
that the extraordinary circumstances
occurred by sending an email to CMS
HHAPU reconsiderations at
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HHAPUReconsiderations@cms.hhs.gov
that contains all of the following
information:
(i) HHA CMS Certification Number
(CCN).
(ii) HHA Business Name.
(iii) HHA Business Address.
(iv) CEO or CEO-designated personnel
contact information including name,
telephone number, title, email address,
and mailing address (The address must
be a physical address, not a post office
box).
(v) HHA’s reason for requesting the
exception or extension.
(vi) Evidence of the impact of
extraordinary circumstances, including,
but not limited to, photographs,
newspaper, and other media articles.
(vii) Date when the HHA believes it
will be able to again submit data under
section 1895(b)(3)(B)(v) of the Act and a
justification for the proposed date.
(3) Except as provided in paragraph
(d)(4) of this section, CMS will not
consider an exception or extension
request unless the HHA requesting such
exception or extension has complied
fully with the requirements in this
paragraph (d).
(4) CMS may grant exceptions or
extensions to HHAs without a request if
it is determines that one or more of the
following has occurred:
(i) An extraordinary circumstance
affects an entire region or locale.
(ii) A systemic problem with one of
CMS’s data collection systems directly
affected the ability of a HHA to submit
data under section 1895(b)(3)(B)(v) of
the Act.
(e) Reconsideration. (1) HHAs that do
not meet the quality reporting
requirements under section
1895(b)(3)(B)(v) of the Act for a program
year will receive a letter of noncompliance through the USPS and via
notification in CASPER. An HHA may
request reconsideration no later than 30
calendar days after the date identified
on the letter of non-compliance.
(2) Reconsideration requests may be
submitted to CMS by sending an email
to CMS HHAPU reconsiderations at
HHAPureConsiderations@cms.hhs.gov
containing all of the following
information:
(i) HHA CCN.
(ii) HHA Business Name.
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35393
(iii) HHA Business Address.
(iv) CEO or CEO-designated personnel
contact information including name,
telephone number, title, email address,
and mailing address (The address must
be a physical address, not a post office
box).
(v) CMS identified reason(s) for noncompliance from the non-compliance
letter.
(vi) Reason(s) for requesting
reconsideration, including all
supporting documentation. CMS will
not consider an exception or extension
request unless the HHA has complied
fully with the requirements in
paragraph (e)(2) of this section.
(3) CMS will make a decision on the
request for reconsideration and provide
notice of the decision to the HHA
through CASPER and via letter sent
through the United States Postal
Service.
(f) Appeals. (1) A HHA that is
dissatisfied with CMS’ decision on a
reconsideration request submitted under
paragraph (e) of this section may file an
appeal with the Provider
Reimbursement Review Board (PRRB)
under 42 CFR part 405, subpart R.
(2) [Reserved]
■ 14. Section 484.305 is amended by
revising the definition of ‘‘Applicable
measure’’ to read as follows:
§ 484.305
Definitions.
*
*
*
*
*
Applicable measure means a measure
for which a competing HHA has
provided a minimum of:
(1) 20 home health episodes of care
per year for the OASIS-based measures;
(2) 20 home health episodes of care
per year for the claims-based measures;
or
(3) 40 completed surveys for the
HHCAHPS measures.
*
*
*
*
*
Dated: June 29, 2017.
Seema Verma,
Administrator, Centers for Medicare &
Medicaid Services.
Dated: June 30, 2017.
Thomas E. Price,
Secretary, Department of Health and Human
Services.
[FR Doc. 2017–15825 Filed 7–25–17; 4:15 pm]
BILLING CODE 4120–01–P
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]]>Agencies
[Federal Register Volume 82, Number 144 (Friday, July 28, 2017)]
[Proposed Rules]
[Pages 35270-35393]
From the Federal Register Online via the Government Publishing Office [www.gpo.gov]
[FR Doc No: 2017-15825]
[[Page 35269]]
Vol. 82
Friday,
No. 144
July 28, 2017
Part II
Department of Health and Human Services
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Centers for Medicare & Medicaid Services
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42 CFR Parts 409 and 484
Medicare and Medicaid Programs; CY 2018 Home Health Prospective
Payment System Rate Update and Proposed CY 2019 Case-Mix Adjustment
Methodology Refinements; Home Health Value-Based Purchasing Model; and
Home Health Quality Reporting Requirements; Proposed Rule
Federal Register / Vol. 82 , No. 144 / Friday, July 28, 2017 /
Proposed Rules
[[Page 35270]]
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DEPARTMENT OF HEALTH AND HUMAN SERVICES
Centers for Medicare & Medicaid Services
42 CFR Parts 409 and 484
[CMS-1672-P]
RIN 0938-AT01
Medicare and Medicaid Programs; CY 2018 Home Health Prospective
Payment System Rate Update and Proposed CY 2019 Case-Mix Adjustment
Methodology Refinements; Home Health Value-Based Purchasing Model; and
Home Health Quality Reporting Requirements
AGENCY: Centers for Medicare & Medicaid Services (CMS), HHS.
ACTION: Proposed rule.
-----------------------------------------------------------------------
SUMMARY: This proposed rule updates the home health prospective payment
system (HH PPS) payment rates, including the national, standardized 60-
day episode payment rates, the national per-visit rates, and the non-
routine medical supply (NRS) conversion factor, effective for home
health episodes of care ending on or after January 1, 2018. This rule
also: updates the HH PPS case-mix weights using the most current,
complete data available at the time of rulemaking; implements the 3rd-
year of a 3-year phase-in of a reduction to the national, standardized
60-day episode payment to account for estimated case-mix growth
unrelated to increases in patient acuity (that is, nominal case-mix
growth) between CY 2012 and CY 2014; and discusses our efforts to
monitor the potential impacts of the rebasing adjustments that were
implemented in CY 2014 through CY 2017. This rule proposes case-mix
methodology refinements, as well as a change in the unit of payment
from 60-day episodes of care to 30-day periods of care, to be
implemented for home health services beginning on or after January 1,
2019; and finally, this rule proposes changes to the Home Health Value-
Based Purchasing (HHVBP) Model and to the Home Health Quality Reporting
Program (HH QRP).
DATES: To be assured consideration, comments must be received at one of
the addresses provided below, no later than 5 p.m. on September 25,
2017.
ADDRESSES: In commenting, please refer to file code CMS-1672-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-1672-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-1672-P, Mail
Stop C4-26-05, 7500 Security Boulevard, Baltimore, MD 21244-1850.
4. By hand or courier. If you prefer, you may deliver (by hand or
courier) your written comments before the close of the comment period
to either of the following addresses:
a. For delivery in Washington, DC--Centers for Medicare & Medicaid
Services, Department of Health and Human Services, Room 445-G, Hubert
H. Humphrey Building, 200 Independence Avenue SW., Washington, DC
20201.
(Because access to the interior of the Hubert H. Humphrey Building
is not readily available to persons without federal government
identification, commenters are encouraged to leave their comments in
the CMS drop slots located in the main lobby of the building. A
stamp-in clock is available for persons wishing to retain a proof of
filing by stamping in and retaining an extra copy of the comments
being filed.)
b. For delivery in Baltimore, MD--Centers for Medicare & Medicaid
Services, Department of Health and Human Services, 7500 Security
Boulevard, Baltimore, MD 21244-1850.
If you intend to deliver your comments to the Baltimore address,
please call (410) 786-7195 in advance to schedule your arrival with one
of our staff members.
Comments mailed to the addresses indicated as appropriate for hand
or courier delivery may be delayed and received after the comment
period.
For information on viewing public comments, see the beginning of
the SUPPLEMENTARY INFORMATION section.
FOR FURTHER INFORMATION CONTACT: For general information about the HH
PPS, please send your inquiry via email to:
HomehealthPolicy@cms.hhs.gov.
For information about the HHVBP model, please send your inquiry via
email to: HHVBPquestions@cms.hhs.gov.
Joan Proctor, (410) 786-0949 for information about the home health
quality reporting program.
SUPPLEMENTARY INFORMATION: Inspection of Public Comments: All comments
received before the close of the comment period are available for
viewing by the public, including any personally identifiable or
confidential business information that is included in a comment. We
post all comments received before the close of the comment period on
the following 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. Current System for Payment of Home Health Services
C. Updates to the Home Health Prospective Payment System
D. Report to Congress: Home Health Study on Access to Care for
Vulnerable Patient Populations and Subsequent Research and Analyses
III. Provisions of the Proposed Rule: Payment Under the Home Health
Prospective Payment System (HH PPS)
A. Monitoring for Potential Impacts--Affordable Care Act
Rebasing Adjustments
B. Proposed CY 2018 HH PPS Case-Mix Weights
C. Proposed CY 2018 Home Health Payment Rate Update
D. Payments for High-Cost Outliers under the HH PPS
E. Proposed Implementation of the Home Health Groupings Model
(HHGM) for CY 2019
IV. Proposed Provisions of the Home Health Value-Based Purchasing
(HHVBP) Model
A. Background
B. Quality Measures
C. Quality Measures for Future Consideration
[[Page 35271]]
V. Proposed Updates to the Home Health Care Quality Reporting
Program (HH QRP)
A. Background and Statutory Authority
B. General Considerations Used for the Selection of Quality
Measures for the HH QRP
C. Accounting for Social Risk Factors in the HH QRP
D. Proposed Data Elements for Removal From OASIS
E. Proposed Collection of Standardized Patient Assessment Data
Under the HH QRP
F. HH QRP Quality Measures Proposed Beginning With the CY 2020
HH QRP
G. HH QRP Quality Measures and Measure Concepts Under
Consideration for Future Years
H. Proposed Standardized Patient Assessment Data
I. Proposals Relating to the Form, Manner, and Timing of Data
Submission Under the HH QRP
J. Other Proposals for the CY 2019 HH QRP and Subsequent Years
K. Proposals and Policies Regarding Public Display of Quality
Measure Data for the HH QRP
L. Proposed Mechanism for Providing Confidential Feedback
Reports to HHAs
M. Home Health Care CAHPS[supreg] Survey (HHCAHPS)
VI. Request for Information on CMS Flexibilities and Efficiencies
VII. Collection of Information Requirements
A. Statutory Requirement for Solicitation of Comments
B. Collection of Information Requirements for the HH QRP
C. Submission of PRA-Related Comments
VIII. Response to Public Comments
IX. Regulatory Impact Analysis
A. Statement of Need
B. Overall Impact
C. Detailed Economic Analysis
D. Alternatives Considered
E. Accounting Statement and Table
F. Reducing Regulation and Controlling Regulatory Costs
G. Conclusion
X. Federalism Analysis
Regulation 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
AM-PAC Activity Measure for Post-Acute Care
APU Annual Payment Update
ASPE Assistant Secretary for Planning and Evaluation
BBA Balanced Budget Act of 1997, Public Law 105-33
BBRA Medicare, Medicaid, and SCHIP Balanced Budget Refinement Act of
1999, (Pub. L. 106-113)
BIMS Brief Interview for Mental Status
BLS Bureau of Labor Statistics
CAD Coronary Artery Disease
CAH Critical Access Hospital
CAM Confusion Assessment Method
CARE Continuity Assessment Record and Evaluation
CASPER Certification and Survey Provider Enhanced Reports
CBSA Core-Based Statistical Area
CCN CMS Certification Number
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, Public Law 109-171, enacted
February 8, 2006
DTI Deep Tissue Injury
EOC End of Care
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
HHGM Home Health Groupings Model
HHQRP Home Health Quality Reporting Program
HHRG Home Health Resource Group
HHVBP Home Health Value-Based Purchasing
HIPPS Health Insurance Prospective Payment System
HVBP Hospital Value-Based Purchasing
IADL Instrumental Activities of Daily Living
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 Care Transformation Act of 2014 (Pub.
L. 113-185)
IPR Interim Performance Report
IRF Inpatient Rehabilitation Facility
IRF-PAI IRF Patient Assessment Instrument
IV Intravenous
LCDS LTCH CARE Data Set
LEF Linear Exchange Function
LTCH Long-Term Care Hospital
LUPA Low-Utilization Payment Adjustment
MACRA Medicare Access and CHIP Reauthorization Act of 2015
MAP Measure Applications Partnership
MDS Minimum Data Set
MEPS Medical Expenditures Panel Survey
MFP Multifactor productivity
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
OLS Ordinary Least Squares
OT Occupational Therapy
OMB Office of Management and Budget
PAC Post-Acute Care
PAC-PRD Post-Acute Care Payment Reform Demonstration
PAMA Protecting Access to Medicare Act of 2014
PEP Partial Episode Payment Adjustment
PHQ-2 Patient Health Questionnaire-2
PPOC Primary Point of Contact
PPS Prospective Payment System
PRA Paperwork Reduction Act
PRRB Provider Reimbursement Review Board
PT Physical Therapy
PY Performance Year
QAP Quality Assurance Plan
QIES Quality Improvement Evaluation System
QRP Quality Reporting Program
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
ROC Resumption of Care
SAF Standard Analytic File
SLP Speech-Language Pathology
SN Skilled Nursing
SNF Skilled Nursing Facility
SOC Start of Care
SSI Surgical Site Infection
TEP Technical Expert Panel
TPS Total Performance Score
UMRA Unfunded Mandates Reform Act of 1995.
VAD Vascular Access Device
VBP Value-Based Purchasing
I. Executive Summary
A. Purpose
This proposed rule would update the payment rates for home health
agencies (HHAs) for calendar year (CY) 2018, as required under section
1895(b) of the Social Security Act (the Act). This proposed rule would
update the case-mix weights under section 1895(b)(4)(A)(i) and
(b)(4)(B) of the Act for CY 2018 and implement a 0.97 percent reduction
to the national, standardized 60-day episode payment amount to account
for case-mix growth
[[Page 35272]]
unrelated to increases in patient acuity (that is, nominal case-mix
growth) between CY 2012 and CY 2014, under the authority of section
1895(b)(3)(B)(iv) of the Act. For home health services beginning on or
after January 1, 2019, this rule also proposes case-mix methodology
refinements under the authority set out at sections 1895(b)(4)(A)(i)
and (b)(4)(B) of the Act, and a change in the unit of payment from a
60-day episode of care to a 30-day period of care under the authority
set out at section 1895(b)(2) of the Act. Additionally, this rule
proposes changes to: The Home Health Value Based Purchasing (HHVBP)
model under the authority of section 1115A of the Act; and the Home
Health Quality Reporting Program (HH QRP) requirements under the
authority of section 1895(b)(3)(B)(v) of the Act.
B. Summary of the Major Provisions
Section III.A of this rule discusses our efforts to monitor for
potential impacts due to the rebasing adjustments implemented in CY
2014 through CY 2017, as mandated by section 3131(a) of the Patient
Protection and Affordable Care Act of 2010 (Pub. L. 111-148, enacted
March 23, 2010) as amended by the Health Care and Education
Reconciliation Act of 2010 (Pub. L. 111-152, enacted March 30, 2010),
collectively referred to as the ``Affordable Care Act''. In the CY 2015
HH PPS final rule (79 FR 66072), we finalized our proposal to
recalibrate the case-mix weights every year with the most current and
complete data available at the time of rulemaking. In section III.B 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. Also in section III.B of this rule, as finalized in the CY 2016
HH PPS final rule (80 FR 68624), we are implementing a reduction to the
national, standardized 60-day episode payment rate for CY 2018 of 0.97
percent to account for estimated case-mix growth unrelated to increases
in patient acuity (that is, nominal case-mix growth) between CY 2012
and CY 2014.
In section III.C of this proposed rule, we would update the payment
rates under the HH PPS by 1 percent for CY 2018 in accordance with
section 411(d) of the Medicare Access and CHIP Reauthorization Act of
2015 (MACRA) (Pub. L. 114-10, enacted April 16, 2015) which amended
section 1895(b)(3)(B) of the Act. Additionally, section III.C of this
rule, would update the CY 2018 home health wage index using FY 2014
hospital cost report data. In section III.D of this proposed rule, we
note that the fixed-dollar loss ratio would remain 0.55 for CY 2018 to
pay up to, but no more than, 2.5 percent of total payments as outlier
payments, as required by section 1895(b)(5)(A) of the Act.
In section III.E of this rule we are proposing to implement case-
mix methodology refinements and a change in the unit of payment from a
60-day episode of care to a 30-day period of care, effective for home
health services beginning on or after January 1, 2019. The proposed
home health groupings model (HHGM) relies more heavily on clinical
characteristics and other patient information to place patients into
meaningful payment categories, while eliminating therapy service use
thresholds that are currently used to case-mix adjust payments under
the HH PPS. This includes proposed changes in the episode timing
categories, the addition of an admission source category, the creation
of six clinical groups used to categorize patients based on their
primary reason for home health care, revised functional levels and
corresponding OASIS items, the addition of a comorbidity adjustment,
and a proposed change in the Low-Utilization Payment Adjustment (LUPA)
threshold. The LUPA add-on policy, the partial [episode] payment
adjustment policy, and the methodology used to calculate payments for
high-cost outliers would remain unchanged except for occurring on a 30-
day basis rather than a 60-day basis.
In section IV of this rule, we are proposing changes to the Home
Health Value-Based Purchasing (HHVBP) Model implemented January 1,
2016. We are proposing to amend the definition of ``applicable
measure'' to specify that the HHA would have to submit a minimum of 40
completed surveys for Home Health Care Consumer Assessment of
Healthcare Providers and Systems (HHCAHPS) measures, for purposes of
receiving a performance score for any of the HHCAHPS measures, and for
performance year (PY) 3 and subsequent years, to remove the Outcome and
Assessment Information Set (OASIS)-based measure, Drug Education on All
Medications Provided to Patient/Caregiver during All Episodes of Care,
from the set of applicable measures. We are also soliciting public
comments on composite quality measures for future consideration.
In section V of this rule, we propose updates to the Home Health
Quality Reporting Program, including: The replacement of one quality
measure, the adoption of two new quality measures, the reporting of
standardized patient assessment data in five categories described under
the IMPACT Act, data submission requirements, exception and extension
requirements, and reconsideration and appeals procedures.
C. Summary of Costs and Benefits
Table 1--Summary of Costs and Transfers
------------------------------------------------------------------------
Provision description Costs Transfers
------------------------------------------------------------------------
CY 2018 HH PPS Payment Rate ................. The overall economic
Update. impact of the HH PPS
payment rate update
is an estimated -$80
million (-0.4
percent) in payments
to HHAs.
CY 2018 HHVBP Model........... ................. The overall economic
impact of the HHVBP
Model provision for
CY 2018 through 2022
is an estimated $378
million in total
savings from a
reduction in
unnecessary
hospitalizations and
SNF usage as a
result of greater
quality improvements
in the HH industry
(none of which is
attributable to the
changes proposed in
this proposed rule).
As for payments to
HHAs, there are no
aggregate increases
or decreases
expected to be
applied to the HHAs
competing in the
model.
CY 2019 HH QRP................ The overall .....................
economic impact
of the HH QRP
changes is a
savings to HHAs
of an estimated
$44.9 million,
beginning
January 1, 2019.
[[Page 35273]]
CY 2019 HH PPS Case-Mix ................. The overall impact of
Adjustment Methodology the proposed HH PPS
Refinements. case-mix adjustment
methodology
refinements,
including a change
in the unit of
payment from 60-day
episodes to 30-day
periods of care, is
an estimated -$950
million (-4.3
percent) in payments
to HHAs in CY 2019
if the refinements
are implemented in a
non-budget neutral
manner for 30-day
periods of care
beginning on or
after January 1,
2019. The overall
impact is an
estimated -$480
million (-2.2
percent) in payments
to HHAs in CY 2019
if the refinements
are implemented in a
partially budget-
neutral manner.
------------------------------------------------------------------------
II. Background
A. Statutory Background
The Balanced Budget Act of 1997 (BBA) (Pub. L. 105-33, enacted
August 5, 1997), significantly changed the way Medicare pays for
Medicare HH services. Section 4603 of the BBA mandated the development
of the HH PPS. Until the implementation of the HH PPS on October 1,
2000, HHAs received payment under a retrospective reimbursement system.
Section 4603(a) of the BBA mandated the development of a HH PPS for
all Medicare-covered HH services provided under a plan of care (POC)
that were paid on a reasonable cost basis by adding section 1895 of the
Act, entitled ``Prospective Payment For Home Health Services.'' Section
1895(b)(1) of the Act requires the Secretary to establish a HH PPS for
all costs of HH services paid under Medicare.
Section 1895(b)(3)(A) of the Act requires the following: (1) The
computation of a standard prospective payment amount 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 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 Affordable Care Act
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 for Fiscal
Year 1999 (OCESAA), (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 of 1999, (BBRA) (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 MACRA amended section 421(a) of the MMA to
extend the rural add-on for 2 more years. Section 421(a) of the MMA, as
amended by section 210 of the MACRA, requires that the Secretary
increase, by 3 percent, the payment amount otherwise made under section
1895 of the Act, for HH services
[[Page 35274]]
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. Section 411(d) of MACRA amended
section 1895(b)(3)(B) of the Act such that for home health payments for
CY 2018, the market basket percentage increase shall be 1 percent.
B. Current System for Payment of Home Health Services
Generally, Medicare currently 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 not part of the national, standardized 60-day
episode rate, but is computed by multiplying the relative weight for a
particular NRS severity level by the NRS conversion factor. 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. Therapy service use is measured by the number of
therapy visits provided during the episode and can be categorized into
nine visit level categories (or thresholds): 0-5; 6; 7-9; 10; 11-13;
14-15; 16-17; 18-19; and 20 or more visits.
For episodes with four or fewer visits, Medicare pays national per-
visit rates based on the discipline(s) providing the services. An
episode consisting of four or fewer visits within a 60-day period
receives what is referred to as a low-utilization payment adjustment
(LUPA). Medicare also adjusts the national standardized 60-day episode
payment rate for certain intervening events that are subject to a
partial episode payment adjustment (PEP adjustment). For certain cases
that exceed a specific cost threshold, an outlier adjustment may also
be available.
C. Updates to the Home Health Prospective Payment System
As required by section 1895(b)(3)(B) of the Act, we have
historically updated the HH PPS rates annually in the Federal Register.
The August 29, 2007 final rule with comment period set forth an update
to the 60-day national episode rates and the national per-visit rates
under the HH PPS for CY 2008. The CY 2008 HH PPS final rule included an
analysis performed on CY 2005 HH claims data, which indicated a 12.78
percent increase in the observed case-mix since 2000. Case-mix
represents the variations in conditions of the patient population
served by the HHAs. Subsequently, a more detailed analysis was
performed on the 2005 case-mix data to evaluate if any portion of the
12.78 percent increase was associated with a change in the actual
clinical condition of HH patients. We 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 4-year period in equal
increments, not to exceed 3.5 percent of the amount (or amounts) as of
the date of enactment of the Affordable Care Act, and fully implement
the rebasing adjustments by CY 2017. The statute 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, and a decrease to the NRS conversion factor of 2.82
percent per year. We also finalized three separate LUPA add-on factors
for skilled nursing, physical therapy, and speech-language pathology
and removed 170 diagnosis codes from assignment to diagnosis groups in
the HH PPS Grouper. In the CY 2015 HH PPS final rule (79 FR 66032), we
implemented the 2nd year of the 4 year phase-in of the rebasing
adjustments to the HH PPS payment rates and made changes to the
[[Page 35275]]
HH PPS case-mix weights. In addition, we simplified the face-to-face
encounter regulatory requirements and the therapy reassessment
timeframes.
In the CY 2016 HH PPS final rule (80 FR 68624), we implemented the
3rd year of the 4-year phase-in of the rebasing adjustments to the
national, standardized 60-day episode payment amount, the national per-
visit rates and the NRS conversion factor (as outlined above). In the
CY 2016 HH PPS final rule, we also recalibrated the HH PPS case-mix
weights, using the most current cost and utilization data available, in
a budget neutral manner and finalized reductions to the national,
standardized 60-day episode payment rate in CY 2016, CY 2017, and CY
2018 of 0.97 percent in each year to account for estimated case-mix
growth unrelated to increases in patient acuity (that is, nominal case-
mix growth) between CY 2012 and CY 2014. Finally, section 421(a) of the
MMA, as amended by section 210 of the MACRA, extended the payment
increase of 3 percent for HH services provided in rural areas (as
defined in section 1886(d)(2)(D) of the Act) to episodes or visits
ending before January 1, 2018.
In the CY 2017 HH PPS final rule (81 FR 76702), we implemented the
last year of the 4-year phase-in of the rebasing adjustments to the
national, standardized 60-day episode payment amount, the national per-
visit rates and the NRS conversion factor (as outlined above). We also
finalized changes to the methodology used to calculate outlier payments
under the authority of section 1895(b)(5) of the Act. Lastly, in
accordance with section 1834(s) of the Act, as added by section 504(a)
of the Consolidated Appropriations Act, 2016 (Pub. L. 114-113, enacted
December 18, 2015), we implemented changes in payment for furnishing
Negative Pressure Wound Therapy (NPWT) using a disposable device for
patients under a home health plan of care for which payment would
otherwise be made under section 1895(b) of the Act.
D. Report to Congress: Home Health Study on Access to Care for
Vulnerable Patient Populations and Subsequent Research and Analyses
Section 3131(d) of the Affordable Care Act required CMS to conduct
a study on home health agency costs involved with providing ongoing
access to care to low-income Medicare beneficiaries or beneficiaries in
medically underserved areas, and in treating beneficiaries with varying
levels of severity of illness and submit a report to Congress. As
discussed in the CY 2016 HH PPS proposed rule (80 FR 39840) and the CY
2017 HH PPS proposed rule (81 FR 43744), the findings from the Report
to Congress on the ``Medicare Home Health Study: An Investigation on
Access to Care and Payment for Vulnerable Patient Populations'', found
that payment accuracy could be improved under the current payment
system, particularly for patients with certain clinical characteristics
requiring more nursing care than therapy.\1\
---------------------------------------------------------------------------
\1\ The Report to Congress can be found in its entirety at
https://www.cms.gov/Medicare/Medicare-Fee-for-ServicePayment/HomeHealthPPS/Downloads/HH-Report-to-Congress.pdf.
---------------------------------------------------------------------------
The research for the Report to Congress, released in December 2014,
consisted of extensive analysis of both survey and administrative data.
The CMS-developed surveys were given to physicians who referred
vulnerable patient populations to Medicare home health and to Medicare-
certified HHAs.\2\ The response rates were 72 percent and 59 percent
for the HHA and physician surveys, respectively. The results of the
survey revealed that over 80 percent of respondent HHAs and over 90
percent of respondent 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 (64 percent
of respondent HHAs surveyed) 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. Only 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 results of the CMS-conducted surveys suggested that CMS'
ability to improve access for certain vulnerable patient populations
through payment policy may be limited. However, we are able to revise
the case-mix system to minimize differences in payment that could
potentially be serving as a barrier to receiving care. In this rule, we
propose to better align payment with resource use so that it reduces
HHAs' financial incentives to select certain patients over others.
---------------------------------------------------------------------------
\2\ For the purposes of the surveys, ``vulnerable patient
populations'' were defined as beneficiaries who were either eligible
for the Part D low-income subsidy (LIS) 27 or residing in a health
professional shortage area (HPSA).
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However, we also performed an analysis of Medicare administrative
data (CY 2010 Medicare claims and cost report data) and calculated
margins for episodes of care. This was done because margin differences
associated with patient clinical and social characteristics can
indicate whether financial incentives exist in the current 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, potentially creating access to care issues. The
findings from the data analysis found that certain patient
characteristics appear to be strongly associated with margin levels,
and thus may create financial incentives to select certain patients
over others. Margins were estimated to be lower for patients who
required parenteral nutrition, who had traumatic wounds or ulcers, or
required substantial assistance in bathing. For example, in CY 2010,
episodes for patients with parenteral nutrition were, on average,
associated with a $178.53 lower margin than episodes for patients
without parenteral nutrition. Given that these variables are already
included in the HH PPS case-mix system, the results indicated that
modifications to the way the current case-mix system accounts for
resource use differences may be needed to mitigate any financial
incentives to select certain patients over others. Margins were also
lower for beneficiaries who were admitted after acute or post-acute
stays or who had certain poorly-controlled clinical conditions, such as
poorly-controlled pulmonary disorders, indicating that accounting for
additional patient characteristic variables in the HH PPS case-mix
system may also reduce financial incentives to select certain types of
patients over others. More information on the results from the Home
Health Study required by section 3131(d) of the Affordable Care Act can
be found in the Report to Congress on the ``Medicare Home Health Study:
An Investigation on Access to Care and Payment for Vulnerable Patient
Populations'' available at https://www.cms.gov/center/provider-Type/home-Health-Agency-HHA-Center.html.
Section 3131(d)(5) of the Affordable Care Act allowed for the
Secretary to determine whether a Medicare demonstration project is
appropriate to conduct based on the result of the Home Health Study. If
the Secretary determined it was appropriate to conduct the
demonstration project under this subsection, the Secretary was to
conduct the project for a four year period beginning not later than
January
[[Page 35276]]
1, 2015. We did not determine that it was appropriate to conduct a
demonstration project based on the findings from the Home Health Study.
Rather, the findings from the Home Health Study suggested that follow-
on work should be conducted to better align payments with costs under
the authority of section 1895 of the Act.
In addition to the findings from the Report to Congress on the
``Medicare Home Health Study: An Investigation on Access to Care and
Payment for Vulnerable Patient Populations'', concerns have also been
raised about the use of therapy thresholds in the current payment
system. Under the current payment system, HHAs receive higher payments
for providing more therapy visits once certain thresholds are reached.
As a result, the average number of therapy visits per 60-day episode of
care have increased since the implementation of the HH PPS, while the
number of skilled nursing and home health aide visits have decreased
over the same time period as shown in Figure 3 in section III.A of this
rule. A study examining an option of using predicted, rather than
actual, therapy visits in the HH found that in 2013, 58 percent of home
health episodes included some therapy services, and these episodes
accounted for 72 percent of all Medicare home health payments.\3\
Figure 1 from that study demonstrates that the percentage of episodes,
and the average episode payment by the number of therapy visits for
episodes with at least one therapy visit in 2013 increased sharply in
therapy provision just over payment thresholds at 6, 7, and 16.
According to the study, the presence of sharp increases in the
percentage of episodes just above payment thresholds suggests a
response to financial incentives in the home health payment system.
Similarly, between 2008 and 2013, MedPAC reported a 26 percent increase
in the number of episodes with at least 6 therapy visits, compared with
a 1 percent increase in the number of episodes with five or fewer
therapy visits.\4\ CMS analysis demonstrates that the average share of
therapy visits across all 60-day episodes of care increased from 9
percent of all visits in 1997, prior to the implementation of the HH
PPS (see 64 FR 58151), to 39 percent of all visits in 2015 (see Table 2
in section III.A. of this proposed rule).
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\3\ Fout B, Plotzke M, Christian T. (2016). Using Predicted
Therapy Visits in the Medicare Home Health Prospective Payment
System. Home Health Care Management & Practice, 29(2), 81-90. https://journals.sagepub.com/doi/abs/10.1177/1084822316678384.
\4\ Medicare Payment Advisory Commission (MedPAC). ``Home Health
Care Services.'' Report to Congress: Medicare Payment Policy.
Washington, DC, March 2015. P. 223. Accessed on March 28, 2017 at:
https://www.medpac.gov/docs/default-source/reports/mar2015_entirereport_revised.pdf?sfvrsn=0.
[GRAPHIC] [TIFF OMITTED] TP28JY17.005
Figure 1 suggests that HHAs may be responding to financial
incentives in the home health payment system when making care plan
decisions. Additionally, an investigation into the therapy practices of
the four largest publically-traded home health companies, conducted by
the Senate Committee on Finance in 2010, found that three out of the
four companies investigated ``encouraged therapists to target the most
profitable number of therapy visits, even when patient need alone may
not have justified such patterns''.\5\ The Committee on Finance
[[Page 35277]]
investigation also highlighted the abrupt and dramatic responses the
home health industry has taken to maximize reimbursement under the
therapy threshold models (both the original 10-visit threshold model
and under the revised thresholds implemented in the CY 2008 HH PPS
final rule (72 FR 49762)). Under the HH PPS, the report noted that HHAs
have broad discretion over the number of therapy visits to provide
patients and therefore have control of the single-largest variable in
determining reimbursement and overall margins. The report recommended
that CMS closely examine a future payment approach that focuses on
patient well-being and health characteristics, rather than the
numerical utilization measures.
---------------------------------------------------------------------------
\5\ Committee on Finance, United States Senate. Staff Report on
Home Health and the Medicare Therapy Threshold. Washington, DC,
2011. Accessed on March 28, 2017 at https://www.finance.senate.gov/imo/media/doc/Home_Health_Report_Final4.pdf.
---------------------------------------------------------------------------
MedPAC also continues to recommend the removal of the therapy
thresholds used for determining payment from the HH PPS, as it believes
that such thresholds run counter to the goals of a prospective payment
system, create financial incentives that detract from a focus on
patient characteristics and care needs when agencies are setting plans
of care for their patients, and incentivize unnecessary therapy
utilization. For the average HHA, according to MedPAC, the increase in
payment for therapy visits rises faster than costs resulting in
financial incentives for HHAs to overprovide therapy services.\6\ HHAs
that provide more therapy episodes tend to be more profitable and this
higher profitability and rapid growth in the number of therapy episodes
suggest that financial incentives are causing agencies to favor therapy
services when possible.\7\ Eliminating therapy as a payment factor
would base home health payment solely on patient characteristics, which
is a more patient-focused approach to payment, as recommended by both
MedPAC and previously by the Senate Committee on Finance.
---------------------------------------------------------------------------
\6\ Medicare Payment Advisory Commission (MedPAC). ``Home Health
Services.'' Report to Congress: Medicare Payment Policy. Washington,
DC, March 2011. P. 182-183. Accessed on March 28, 2017 at https://www.medpac.gov/docs/default-source/reports/Mar11_Ch08.pdf?sfvrsn=0.
\7\ Medicare Payment Advisory Commission (MedPAC). ``Home Health
Care Services.'' Report to Congress: Medicare Payment Policy.
Washington, DC, March 2017. P. 243-244. Accessed on March 28, 2017
at https://www.medpac.gov/docs/default-source/reports/mar17_medpac_ch9.pdf?sfvrsn=0.
---------------------------------------------------------------------------
After considering the findings from the Report to Congress and
recommendations from MedPAC and the Senate Committee on Finance, CMS,
along with our contractor, conducted additional research on ways to
improve the payment accuracy under the current payment system.
Exploring all options and different models ultimately led us to further
develop the Home Health Groupings Model (HHGM) proposal. The HHGM
proposal uses 30-day periods, rather than 60-day episodes, and relies
more heavily on clinical characteristics and other patient information
(for example, principal diagnosis, functional level, comorbid
conditions, admission source, and timing) to place patients into
meaningful payment categories, rather than the current therapy driven
system. We believe this patient-centered approach is consistent with
how clinicians differentiate between home health patients and would
improve payment accuracy and access for medically complex cases and not
just cases receiving therapy. The HHGM proposal leverages many of the
same aspects of the current system; however, the major differences
between the current system and the HHGM proposal include a change from
a 60-day to a 30-day billing cycle and the elimination of the therapy
thresholds in the case-mix system.
We shared the analyses and development of the HHGM with both
internal and external stakeholders via technical expert panels,
clinical workgroups, special open door forums, and in the CY 2016 HH
PPS proposed rule (80 FR 39840) and the CY 2017 HH PPS proposed rule
(81 FR 43744). Most recently, we posted a detailed technical report on
the CMS Web site in December of 2016.\8\ After posting the technical
report for the public to review, we also held additional technical
expert panel and clinical workgroup webinars to garner feedback from
the industry and conducted a National Provider call that occurred in
January 2017 to solicit feedback from external stakeholders.\9\ The
feedback we received during the National Provider call on the HHGM was
positive. We discuss the HHGM proposal further below, in section III.E,
and seek public comment on this proposal and the underlying analyses.
---------------------------------------------------------------------------
\8\ Ab Associates. Medicare Home Health Prospective Payment
System: Case-Mix Methodology Refinements. Overview of the Home
Health Groupings Model. Cambridge, MA, November 18, 2016. Accessed
on April 27, 2017 at: https://downloads.cms.gov/files/hhgm%20technical%20report%20120516%20sxf.pdf.
\9\ Centers for Medicare & Medicaid Services (CMS). ``Home
Health Groupings Model Technical Report Call.'' Baltimore, MD,
January 18, 2017. Accessed on April 27, 2017 at: https://www.cms.gov/Outreach-and-Education/Outreach/NPC/National-Provider-Calls-and-Events-Items/2017-01-18-Home-Health.html?DLPage=2&DLEntries=10&DLSort=0&DLSortDir=descending.
---------------------------------------------------------------------------
III. Provisions of the Proposed Rule: Payment Under the Home Health
Prospective Payment System (HH PPS)
A. Monitoring for Potential Impacts--Affordable Care Act Rebasing
Adjustments
1. Analysis of FY 2015 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. Previous years' cost report and claims data analyses
and results can be found in the CY 2017 HH PPS proposed rule (81 FR
43719 through 43720). For this proposed rule, we analyzed 2015 HHA cost
report data and 2015 HHA claims data. To determine the 2015 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 2015 cost reports by size, facility type,
and urban/rural location so the costs per visit were nationally
representative according to 2015 claims data. The 2015 average number
of visits was taken from 2015 claims data. We estimated the cost of a
60-day episode in CY 2015 to be $2,449.01 using 2015 cost report data
as shown in Table 2. However, the national, standardized 60-day episode
payment amount in CY 2015 was $2,961.38. For CY 2015, on average,
payments were 21 percent higher than costs (($2,961.38--$2,449.01)/
$2,449.01).
TABLE 2--2015 Estimated Cost per Episode
----------------------------------------------------------------------------------------------------------------
2015 Average 2015 Average 2015 60-day
Discipline costs per visit number of visits episode costs
----------------------------------------------------------------------------------------------------------------
Skilled Nursing........................................ $132.48 8.93 $1,183.05
Physical Therapy....................................... 156.32 5.39 842.56
[[Page 35278]]
Occupational Therapy................................... 154.64 1.41 218.04
Speech Pathology....................................... 170.96 0.29 49.58
Medical Social Services................................ 220.07 0.14 30.81
Home Health Aides...................................... 62.80 1.99 124.97
--------------------------------------------------------
Total.............................................. ................. 18.15 2,449.01
----------------------------------------------------------------------------------------------------------------
Source: Medicare cost reports pulled in February 2017 and Medicare claims data from 2014 and 2015 for episodes
(excluding low-utilization payment adjusted episodes and partial-episode-payment adjusted episodes), linked to
OASIS assessments for episodes ending in CY 2015.
2. Analysis of CY 2016 HHA Claims Data
In the CY 2014 HH PPS final rule (78 FR 72283), 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 3 years of the 4-year phase-in of the rebasing adjustments (CY
2014, CY 2015, and CY 2016), the first calendar year of the HH PPS (CY
2001), and claims data for 2 years before implementation of the
rebasing adjustments (CY 2012 and CY2013). Analysis of CY 2016 home
health claims data indicates that the number of episodes and the number
of home health users that received at least one episode of care
remained virtually the same (change of less than 1 percent) from 2015
to 2016, while the number of FFS beneficiaries increased 2 percent from
2015 to 2016. 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, a continued decrease of 1.7 percent from 2014 to 2015, and a
decrease of 2.5 percent from 2015 to 2016. The number of home health
users, as a percentage of FFS beneficiaries, appears to have slightly
decreased from 9.0 percent in 2012 to 8.7 percent in 2016, but remains
higher than the 6.9 percent in 2001. In CY 2016, there were 2.9 HHAs
per 10,000 FFS beneficiaries, which is still markedly higher than the
1.9 HHAs per 10,000 FFS beneficiaries observed close to the
implementation of the HH PPS in 2001 (see Table 3). Therefore, the
rebasing adjustments made to the HH PPS payment rates in CYs 2014
through 2016 do not appear to have resulted in significant HHA closures
or otherwise diminished access to home health services.
---------------------------------------------------------------------------
\10\ The data used for this table is not publicly available.
Providers and researchers have access to similar data via the home
health public use files at https://www.cms.gov/Research-Statistics-Data-and-Systems/Statistics-Trends-and-Reports/Medicare-Provider-Charge-Data/HHA.html and through the CMS program statistics Web site
at: https://www.cms.gov/Research-Statistics-Data-and-Systems/Statistics-Trends-and-Reports/CMSProgramStatistics/.
TABLE 3--Home Health Statistics, CY 2001 and CY 2012 Through CY 2016 \10\
--------------------------------------------------------------------------------------------------------------------------------------------------------
2001 2012 2013 2014 2015 2016
--------------------------------------------------------------------------------------------------------------------------------------------------------
Number of episodes...................................... 3,896,502 6,727,875 6,708,923 6,451,283 6,340,932 6,294,234
Beneficiaries receiving at least 1 episode (Home Health 2,412,318 3,446,122 3,484,579 3,381,635 3,365,512 3,350,174
Users).................................................
Part A and/or B FFS beneficiaries....................... 34,899,167 38,224,640 38,505,609 38,506,534 38,506,534 38,555,150
Episodes per Part A and/or B FFS beneficiaries.......... 0.11 0.18 0.17 0.17 0.17 0.16
Home health users as a percentage of Part A and/or B FFS 6.9% 9.0% 9.0% 8.8% 8.8% 8.7%
beneficiaries..........................................
HHAs providing at least 1 episode....................... 6,511 11,746 11,889 11,693 11,381 11,102
HHAs per 10,000 Part A and/or B FFS beneficiaries....... 1.9 3.1 3.1 3.0 3.0 2.9
--------------------------------------------------------------------------------------------------------------------------------------------------------
Source: National claims history (NCH) data obtained from Chronic Condition Warehouse (CCW)--Accessed on May 14, 2014 and August 19, 2014 for CY 2011, CY
2012, and CY 2013 data; accessed on May 7, 2015 for CY 2001 and CY 2014 data; accessed on April 7, 2016 for CY 2015 data; and accessed on March 20,
2017 for CY 2016 data and 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
three years of the implementation of rebasing adjustments required by
the Affordable Care Act, we examined trends in home health utilization
for all years starting in CY 2001 and up through CY 2016. Figure 2,
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 $167 for CY
2016, the average total number of visits per 60-day episode of care has
declined, most notably between CY 2009 (21.7 visits per episode) and CY
2010 (19.8 visits per episode), which was the first year that the 10
percent agency-level cap on HHA outlier payments was implemented. The
average of total visits per episode has steadily decreased from 21.7 in
2009 to 17.9 in 2016.
[[Page 35279]]
[GRAPHIC] [TIFF OMITTED] TP28JY17.000
Figure 3 displays the average number of visits by discipline type
for a 60-day episode of care and shows that the number of therapy
visits per 60-day episode of care has increased steadily. However, the
number of skilled nursing visits has decreased from 10.7 in 2009 to 8.7
in 2016. The number of home health aide visits has decreased from 5.6
average visits in 2009 to 1.5 visits in 2016. The results of the home
health study required by section 3131(d) of the Affordable Care Act
suggest 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.\11\ The home health study results
seem to be consistent with the recent trend in the decreased number of
visits per episode of care driven by decreases in skilled nursing and
home health aide services evident in Figures 2 and 3.
---------------------------------------------------------------------------
\11\ The Report to Congress on the Home Health Study required by
Section 3131(d) is available at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/HomeHealthPPS/Downloads/HH-Report-to-Congress.pdf.
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[[Page 35280]]
[GRAPHIC] [TIFF OMITTED] TP28JY17.001
As part of our monitoring efforts, we also examined the trends in
episode timing and service use over time. The first and second episodes
are considered ``early'' episodes, while third and later episodes are
considered ``late'' episodes. Specifically, we examined the percentage
of early episodes with 0 to 19 therapy visits, late episodes with 0 to
19 therapy visits, and episodes with 20+ therapy visits from CY 2008 to
CY 2016. In CY 2008, we implemented refinements to the HH PPS case-mix
system. As part of those refinements, we added additional therapy
thresholds and differentiated between early and late episodes for those
episodes with less than 20+ therapy visits. When the case-mix system
first differentiated payments between early and late episodes of care,
late episodes of care tended to have higher case-mix weights compared
to early episodes of care. Table 4 shows that while there was a
substantial increase in the number of late episodes between 2008 and
2009 (8 percentage points), since 2011 the number of late episodes as a
percentage of total episodes has decreased over time. In 2015, the
case-mix weights for the third and later episodes of care with 0 to 19
therapy visits decreased as a result of the CY 2015 recalibration of
the case-mix weights. The recalibration of the HH PPS case-mix weights,
beginning in CY 2015, does not seem to have substantially impacted the
percentage of early versus late episodes of care.
The case-mix weights for episodes with 20+ therapy visits are not
determined based on the timing of the episode of care. The percentage
of episodes with 20+ therapy visits increased from 4.6 percent in CY
2008 to 7.0 percent in CY 2016. The increase in the percentage of
episodes with 20+ therapy visits is consistent with the overall
observed increase in therapy visits provided during a 60-day episode of
care (see Figure 3).
[[Page 35281]]
TABLE 4--Home Health Episodes by Episode Timing, CY 2008 Through CY 2016
--------------------------------------------------------------------------------------------------------------------------------------------------------
Number of % of early Number of late % of late
early episodes episodes episodes episodes Number of
(excluding (excluding (excluding (excluding episodes with % of episodes
Year All episodes episodes with episodes with episodes with episodes with 20+ therapy with 20+
20+ therapy 20+ therapy 20+ therapy 20+ therapy visits therapy visits
visits) visits) visits) visits)
--------------------------------------------------------------------------------------------------------------------------------------------------------
2008.................................... 5,423,037 3,571,619 65.9 1,600,587 29.5 250,831 4.6
2009.................................... 6,530,200 3,701,652 56.7 2,456,308 37.6 372,240 5.7
2010.................................... 6,877,598 3,872,504 56.3 2,586,493 37.6 418,601 6.1
2011.................................... 6,857,885 3,912,982 57.1 2,564,859 37.4 380,044 5.5
2012.................................... 6,767,576 3,955,207 58.4 2,458,734 36.3 353,635 5.2
2013.................................... 6,733,146 4,023,486 59.8 2,347,420 34.9 362,240 5.4
2014.................................... 6,616,875 3,980,151 60.2 2,263,638 34.2 373,086 5.6
2015.................................... 6,644,922 4,008,279 60.3 2,205,052 33.2 431,591 6.5
2016.................................... 6,294,232 3,802,254 60.4 2,053,972 32.6 438,006 7.0
--------------------------------------------------------------------------------------------------------------------------------------------------------
Source: National claims history (NCH) data obtained from Chronic Condition Warehouse (CCW)--Accessed on March 21, 2017.
Note(s): Only episodes with a through date in the year specified are included. Episodes with a claim frequency code equal to ``0'' (``Non-payment/zero
claims'') and ``2'' (``Interim--first claim'') are excluded.
We also examined trends in admission source for home health
episodes over time. Specifically, we examined the admission source for
the ``first or only'' episodes of care (first episodes in a sequence of
adjacent episodes of care or the only episode of care) from CY 2008
through CY 2016 (Figure 4). The percentage of first or only episodes
with an acute admission source, defined as episodes with an inpatient
hospital stay within the 14 days prior to a home health episode, has
decreased from 38.6 percent in CY 2008 to 33.9 percent in CY 2016. The
percentage of first or only episodes with a post-acute admission
source, defined as episodes which had a stay at a skilled nursing
facility (SNF), inpatient rehabilitation facility (IRF), or long term
care hospital (LTCH) within 14 days prior to the home health episode,
slightly increased from 16.5 percent in CY 2008 to 17.5 percent in CY
2016. The percentage of first or only episodes with a community
admission source, defined as episodes which did not have an acute or
post-acute stay in the 14 days prior to the home health episode,
increased from 37.4 percent in CY 2008 to 42.6 percent in CY 2016. Our
findings on the trends in admission source are consistent with MedPAC's
as outlined in their 2015 Report to the Congress.\12\ MedPAC examined
admission source trends from 2002 up through 2013 and concluded that
``there has been tremendous growth in the use of home health for
patients residing in the community, episodes not preceded by a prior
hospitalization. The high rates of volume growth for these types of
episodes, which have more than doubled since 2001, suggest there is
significant potential for overuse, particularly since Medicare does not
currently require any cost sharing for home health care.''
---------------------------------------------------------------------------
\12\ Medicare Payment Advisory Commission (MedPAC). ``Home
Health Care Services.'' Report to the Congress: Medicare Payment
Policy. Washington, DC, March 2015. P. 214. Accessed on 3/28/2017 at
https://www.medpac.gov/docs/default-source/reports/chapter-9-home-health-care-services-march-2015-report-.pdf?sfvrsn=0.
---------------------------------------------------------------------------
[[Page 35282]]
[GRAPHIC] [TIFF OMITTED] TP28JY17.002
We will continue to monitor for potential impacts due to the
rebasing adjustments required by section 3131(a) of the Affordable Care
Act and other policy changes in the future. Independent effects of any
one policy may be difficult to discern in years where multiple policy
changes occur in any given year.
B. Proposed CY 2018 HH PPS Case-Mix Weights
In the CY 2015 HH PPS final rule (79 FR 66072), we finalized a
policy to annually recalibrate the HH PPS case-mix weights--adjusting
the weights relative to one another--using the most current, complete
data available. To recalibrate the HH PPS case-mix weights for CY 2018,
we will use the same methodology finalized in the CY 2008 HH PPS final
rule (72 FR 49762), the CY 2012 HH PPS final rule (76 FR 68526), and
the CY 2015 HH PPS final rule (79 FR 66032). Annual recalibration of
the HH PPS case-mix weights ensures that the case-mix weights reflect,
as accurately as possible, current home health resource use and changes
in utilization patterns.
To generate the proposed CY 2018 HH PPS case-mix weights, we used
CY 2016 home health claims data (as of March 17, 2017) with linked
OASIS data. These data are the most current and complete data available
at this time. We will use CY 2016 home health claims data (as of June
30, 2017 or later) with linked OASIS data to generate the CY 2018 HH
PPS case-mix weights in the CY 2018 HH PPS final rule. The process we
used to calculate the HH PPS case-mix weights are outlined below.
Step 1: Re-estimate the four-equation model to determine the
clinical and functional points for an episode using wage-weighted
minutes of care as our dependent variable for resource use. The wage-
weighted minutes of care are determined using the CY 2015 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 2016 home health claims data, are shown in Table 5. 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 5--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 .............. 1 .............. ..............
Diagnosis = Blood
disorders.
3.................... Primary or Other .............. 4 .............. 4
Diagnosis = Cancer,
selected benign
neoplasms.
4.................... Primary Diagnosis = .............. 3 .............. 1
Diabetes.
5.................... Other Diagnosis = 1 .............. .............. ..............
Diabetes.
6.................... Primary or Other 2 16 1 10
Diagnosis = Dysphagia
AND Primary or Other
Diagnosis = Neuro 3--
Stroke.
[[Page 35283]]
7.................... Primary or Other 1 6 .............. 6
Diagnosis = Dysphagia
AND M1030 (Therapy at
home) = 3 (Enteral).
8.................... Primary or Other .............. .............. .............. 2
Diagnosis =
Gastrointestinal
disorders.
9.................... Primary or Other .............. 7 .............. ..............
Diagnosis =
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 1 3 .............. 2
Diagnosis = Heart
Disease OR Hypertension.
12................... Primary Diagnosis = Neuro 2 9 6 9
1--Brain disorders and
paralysis.
13................... Primary or Other .............. 4 .............. 4
Diagnosis = Neuro 1--
Brain disorders and
paralysis AND M1840
(Toilet transfer) = 2 or
more.
14................... Primary or Other 2 4 1 4
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.
15................... Primary or Other 3 9 2 4
Diagnosis = Neuro 3--
Stroke.
16................... Primary or Other .............. 2 .............. ..............
Diagnosis = 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 3 7 5 10
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.
19................... Primary or Other 7 1 7 ..............
Diagnosis = Ortho 1--Leg
Disorders or Gait
Disorders AND M1324
(most problematic
pressure ulcer stage)=
1, 2, 3 or 4.
20................... Primary or Other 3 .............. 3 7
Diagnosis = 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 .............. 2 .............. 1
Diagnosis = Pulmonary
disorders.
24................... Primary or Other .............. .............. .............. ..............
Diagnosis = Pulmonary
disorders AND M1860
(Ambulation) = 1 or more.
25................... Primary Diagnosis = Skin 3 17 6 17
1-Traumatic wounds,
burns, and post-
operative complications.
26................... Other Diagnosis = Skin 1-- 6 13 8 13
Traumatic wounds, burns,
post-operative
complications.
27................... Primary or Other 2 .............. .............. ..............
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).
28................... Primary or Other 2 16 8 17
Diagnosis = Skin 2--
Ulcers and other skin
conditions.
29................... Primary or Other 2 17 .............. 17
Diagnosis = Tracheostomy.
30................... Primary or Other .............. 17 .............. 12
Diagnosis = Urostomy/
Cystostomy.
31................... M1030 (Therapy at home) = .............. 15 5 15
1 (IV/Infusion) or 2
(Parenteral).
32................... M1030 (Therapy at home) = .............. 15 .............. 8
3 (Enteral).
33................... M1200 (Vision) = 1 or .............. .............. .............. ..............
more.
34................... M1242 (Pain)= 3 or 4..... 3 .............. 2 ..............
35................... M1311 = Two or more 4 6 4 6
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 31 10 25
pressure ulcer stage)= 3
or 4.
38................... M1334 (Stasis ulcer 4 13 7 13
status)= 2.
39................... M1334 (Stasis ulcer 7 17 9 17
status)= 3.
40................... M1342 (Surgical wound 2 7 6 13
status)= 2.
41................... M1342 (Surgical wound .............. 6 5 10
status)= 3.
42................... M1400 (Dyspnea) = 2, 3, 1 1 .............. ..............
or 4.
43................... M1620 (Bowel .............. 3 .............. 2
Incontinence) = 2 to 5.
44................... M1630 (Ostomy)= 1 or 2... 4 11 2 8
45 M2030 (Injectable Drug .............. .............. .............. ..............
Use) = 0, 1, 2, or 3.
----------------------------------------------------------------------------------------------------------------
[[Page 35284]]
FUNCTIONAL DIMENSION
----------------------------------------------------------------------------------------------------------------
46................... M1810 or M1820 (Dressing 1 .............. .............. ..............
upper or lower body) =
1, 2, or 3.
47................... M1830 (Bathing) = 2 or 6 5 5 2
more.
48................... M1840 (Toilet .............. 1 .............. ..............
transferring) = 2 or
more.
49................... M1850 (Transferring) = 2 3 1 2 ..............
or more.
50................... M1860 (Ambulation) = 1, 2 7 .............. 4 ..............
or 3.
51................... M1860 (Ambulation) = 4 or 8 9 6 7
more.
----------------------------------------------------------------------------------------------------------------
Source: CY 2016 Medicare claims data for episodes ending on or before December 31, 2016 (as of December 31,
2016) for which we had a linked OASIS assessment. LUPA episodes, outlier episodes, and episodes with 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.gov/Medicare/Medicare-Fee-for-Service-Payment/HomeHealthPPS/coding_billing.html for definitions of primary and secondary diagnoses.
In updating the four-equation model for CY 2018, using 2016 home
health claims data (the last update to the four-equation model for CY
2017 used CY 2015 home health claims data), there were few changes to
the point values for the variables in the four-equation model. These
relatively minor changes reflect the change in the relationship between
the grouper variables and resource use between CY 2015 and CY 2016. The
CY 2018 four-equation model resulted in 120 point-giving variables
being used in the model (as compared to the 124 variables for the CY
2017 recalibration). There were 8 variables that were added to the
model and 12 variables that were dropped from the model due to the
absence of additional resources associated with the variable. Of the
variables that were in both the four-equation model for CY 2017 and the
four-equation model for CY 2018, the points for 14 variables increased
in the CY 2018 four-equation model and the points for 48 variables
decreased in the CY 2018 4-equation model. There were 50 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 2018 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.\13\ Also, we looked at the average resource use associated with
each clinical and functional score and used that as a guide for setting
our thresholds. We grouped scores with similar average resource use
within the same level (even if it meant that more or less than a third
of episodes were placed within a level). The new thresholds, based off
the CY 2018 four-equation model points are shown in Table 6.
---------------------------------------------------------------------------
\13\ For Step 1, 45.4% of episodes were in the medium functional
level (All with score 14).
For Step 2.1, 87.3% of episodes were in the low functional level
(Most with scores 5 to 7).
For Step 2.2, 81.9% of episodes were in the low functional level
(Most with score 1).
For Step 3, 46.4% of episodes were in the medium functional
level (Most with score 9).
For Step 4, 48.6% of episodes were in the medium functional
level (Most with score 5 or 6).
Table 6--CY 2018 Clinical and Functional Thresholds
------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
1st and 2nd episodes 3rd+ episodes All Episodes
----------------------------------------------------------------------------------------------------------------------------------------
0 to 13 therapy visits 14 to 19 therapy visits 0 to 13 therapy visits 14 to 19 therapy visits 20+ therapy visits
------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
Grouping Step 1......................... 2......................... 3........................ 4........................ 5
------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
Equations used to calculate points 1......................... 2......................... 3........................ 4........................ (2&4)
(see Table B1)
------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
Dimension Severity Level .......................... .......................... ......................... .........................
------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
Clinical.......................... C1................. 0 to 1.................... 0 to 1.................... 0 to 1................... 0 to 1................... 0 to 3
C2................. 2 to 3.................... 2 to 7.................... 2........................ 2 to 9................... 4 to 16
C3................. 4+........................ 8+........................ 3+....................... 10+...................... 17+
Functional........................ F1................. 0 to 13................... 0 to 7.................... 0 to 6................... 0 to 2................... 0 to 2
F2................. 14........................ 8 to 15................... 7 to 10.................. 3 to 7................... 3 to 6
F3................. 15+....................... 16+....................... 11+...................... 8+....................... 7+
------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
[[Page 35285]]
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 7 shows the regression coefficients for the variables in the
payment regression model updated with CY 2016 home health claims data.
The R-squared value for the payment regression model is 0.5073 (an
increase from 0.4919 for the CY 2017 recalibration).
Table 7--Payment Regression Model
------------------------------------------------------------------------
Payment
regression
from 4-
equation model
for CY2018
------------------------------------------------------------------------
Step 1, Clinical Score Medium........................... $24.35
Step 1, Clinical Score High............................. 54.10
Step 1, Functional Score Medium......................... 71.10
Step 1, Functional Score High........................... 104.74
Step 2.1, Clinical Score Medium......................... 47.79
Step 2.1, Clinical Score High........................... 133.50
Step 2.1, Functional Score Medium....................... 30.46
Step 2.1, Functional Score High......................... 55.93
Step 2.2, Clinical Score Medium......................... 39.93
Step 2.2, Clinical Score High........................... 192.15
Step 2.2, Functional Score Medium....................... 17.99
Step 2.2, Functional Score High......................... 53.34
Step 3, Clinical Score Medium........................... 14.03
Step 3, Clinical Score High............................. 92.83
Step 3, Functional Score Medium......................... 56.27
Step 3, Functional Score High........................... 86.76
Step 4, Clinical Score Medium........................... 78.75
Step 4, Clinical Score High............................. 260.68
Step 4, Functional Score Medium......................... 25.95
Step 4, Functional Score High........................... 58.66
Step 2.1, 1st and 2nd Episodes, 14 to 19 Therapy Visits. 497.79
Step 2.2, 3rd+ Episodes, 14 to 19 Therapy Visits........ 508.40
Step 3, 3rd+ Episodes, 0-13 Therapy Visits.............. -67.30
Step 4, All Episodes, 20+ Therapy Visits................ 883.46
Intercept............................................... 382.25
------------------------------------------------------------------------
Source: CY 2016 Medicare claims data for episodes ending on or before
December 31, 2016 (as of March 17, 2017) for which we had a linked
OASIS assessment.
Step 4: We use the coefficients from the payment regression model
to predict each episode's wage-weighted minutes of care (resource use).
We then divide these predicted values by the mean of the dependent
variable (that is, the average wage-weighted minutes of care across all
episodes used in the payment regression). This division constructs the
weight for each episode, which is simply the ratio of the episode's
predicted wage-weighted minutes of care divided by the average wage-
weighted minutes of care in the sample. Each episode is then aggregated
into one of the 153 home health resource groups (HHRGs) and the ``raw''
weight for each HHRG was calculated as the average of the episode
weights within the HHRG.
Step 5: The raw weights associated with 0 to 5 therapy visits are
then increased by 3.75 percent, the weights associated with 14-15
therapy visits are decreased by 2.5 percent, and the weights associated
with 20+ therapy visits are decreased by 5 percent. These adjustments
to the case-mix weights were finalized in the CY 2012 HH PPS final rule
(76 FR 68557) and were done to address MedPAC's concerns that the HH
PPS overvalues therapy episodes and undervalues non-therapy episodes
and to better align the case-mix weights with episode costs estimated
from cost report data.\14\
---------------------------------------------------------------------------
\14\ Medicare Payment Advisory Commission (MedPAC), Report to
the Congress: Medicare Payment Policy. March 2011, P. 176.
---------------------------------------------------------------------------
Step 6: After the adjustments in Step 5 are applied to the raw
weights, the weights are further adjusted to create an increase in the
payment weights for the therapy visit steps between the therapy
thresholds. Weights with the same clinical severity level, functional
severity level, and early/later episode status were grouped together.
Then within those groups, the weights for each therapy step between
thresholds are gradually increased. We do this by interpolating between
the main thresholds on the model (from 0-5 to 14-15 therapy visits, and
from 14-15 to 20+ therapy visits). We use a linear model to implement
the interpolation so the payment weight increase for each step between
the thresholds (such as the increase between 0-5 therapy visits and 6
therapy visits and the increase between 6 therapy visits and 7-9
therapy visits) are constant. This interpolation is identical to the
process finalized in the CY 2012 HH PPS final rule (76 FR 68555).
Step 7: The interpolated weights are then adjusted so that the
average case-
[[Page 35286]]
mix for the weights is equal to 1.0000.\15\ This last step creates the
proposed CY 2018 case-mix weights shown in Table 8.
---------------------------------------------------------------------------
\15\ 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 8--Proposed CY 2018 Case-Mix Payment Weights
----------------------------------------------------------------------------------------------------------------
Clinical and functional levels Proposed CY
Pay group Description (1 = low; 2 = medium; 3 = high) 2018 weight
----------------------------------------------------------------------------------------------------------------
10111............................ 1st and 2nd Episodes, 0 to 5 C1F1S1 0.5617
Therapy Visits.
10112............................ 1st and 2nd Episodes, 6 C1F1S2 0.6925
Therapy Visits.
10113............................ 1st and 2nd Episodes, 7 to 9 C1F1S3 0.8232
Therapy Visits.
10114............................ 1st and 2nd Episodes, 10 C1F1S4 0.9539
Therapy Visits.
10115............................ 1st and 2nd Episodes, 11 to C1F1S5 1.0846
13 Therapy Visits.
10121............................ 1st and 2nd Episodes, 0 to 5 C1F2S1 0.6662
Therapy Visits.
10122............................ 1st and 2nd Episodes, 6 C1F2S2 0.7845
Therapy Visits.
10123............................ 1st and 2nd Episodes, 7 to 9 C1F2S3 0.9027
Therapy Visits.
10124............................ 1st and 2nd Episodes, 10 C1F2S4 1.0209
Therapy Visits.
10125............................ 1st and 2nd Episodes, 11 to C1F2S5 1.1392
13 Therapy Visits.
10131............................ 1st and 2nd Episodes, 0 to 5 C1F3S1 0.7157
Therapy Visits.
10132............................ 1st and 2nd Episodes, 6 C1F3S2 0.8311
Therapy Visits.
10133............................ 1st and 2nd Episodes, 7 to 9 C1F3S3 0.9464
Therapy Visits.
10134............................ 1st and 2nd Episodes, 10 C1F3S4 1.0618
Therapy Visits.
10135............................ 1st and 2nd Episodes, 11 to C1F3S5 1.1772
13 Therapy Visits.
10211............................ 1st and 2nd Episodes, 0 to 5 C2F1S1 0.5975
Therapy Visits.
10212............................ 1st and 2nd Episodes, 6 C2F1S2 0.7343
Therapy Visits.
10213............................ 1st and 2nd Episodes, 7 to 9 C2F1S3 0.8711
Therapy Visits.
10214............................ 1st and 2nd Episodes, 10 C2F1S4 1.0078
Therapy Visits.
10215............................ 1st and 2nd Episodes, 11 to C2F1S5 1.1446
13 Therapy Visits.
10221............................ 1st and 2nd Episodes, 0 to 5 C2F2S1 0.7020
Therapy Visits.
10222............................ 1st and 2nd Episodes, 6 C2F2S2 0.8263
Therapy Visits.
10223............................ 1st and 2nd Episodes, 7 to 9 C2F2S3 0.9506
Therapy Visits.
10224............................ 1st and 2nd Episodes, 10 C2F2S4 1.0749
Therapy Visits.
10225............................ 1st and 2nd Episodes, 11 to C2F2S5 1.1991
13 Therapy Visits.
10231............................ 1st and 2nd Episodes, 0 to 5 C2F3S1 0.7514
Therapy Visits.
10232............................ 1st and 2nd Episodes, 6 C2F3S2 0.8729
Therapy Visits.
10233............................ 1st and 2nd Episodes, 7 to 9 C2F3S3 0.9943
Therapy Visits.
10234............................ 1st and 2nd Episodes, 10 C2F3S4 1.1157
Therapy Visits.
10235............................ 1st and 2nd Episodes, 11 to C2F3S5 1.2372
13 Therapy Visits.
10311............................ 1st and 2nd Episodes, 0 to 5 C3F1S1 0.6412
Therapy Visits.
10312............................ 1st and 2nd Episodes, 6 C3F1S2 0.7929
Therapy Visits.
10313............................ 1st and 2nd Episodes, 7 to 9 C3F1S3 0.9446
Therapy Visits.
10314............................ 1st and 2nd Episodes, 10 C3F1S4 1.0963
Therapy Visits.
10315............................ 1st and 2nd Episodes, 11 to C3F1S5 1.2480
13 Therapy Visits.
10321............................ 1st and 2nd Episodes, 0 to 5 C3F2S1 0.7457
Therapy Visits.
10322............................ 1st and 2nd Episodes, 6 C3F2S2 0.8850
Therapy Visits.
10323............................ 1st and 2nd Episodes, 7 to 9 C3F2S3 1.0242
Therapy Visits.
10324............................ 1st and 2nd Episodes, 10 C3F2S4 1.1634
Therapy Visits.
10325............................ 1st and 2nd Episodes, 11 to C3F2S5 1.3026
13 Therapy Visits.
10331............................ 1st and 2nd Episodes, 0 to 5 C3F3S1 0.7952
Therapy Visits.
10332............................ 1st and 2nd Episodes, 6 C3F3S2 0.9315
Therapy Visits.
10333............................ 1st and 2nd Episodes, 7 to 9 C3F3S3 1.0679
Therapy Visits.
10334............................ 1st and 2nd Episodes, 10 C3F3S4 1.2043
Therapy Visits.
10335............................ 1st and 2nd Episodes, 11 to C3F3S5 1.3406
13 Therapy Visits.
21111............................ 1st and 2nd Episodes, 14 to C1F1S1 1.2154
15 Therapy Visits.
21112............................ 1st and 2nd Episodes, 16 to C1F1S2 1.3780
17 Therapy Visits.
21113............................ 1st and 2nd Episodes, 18 to C1F1S3 1.5406
19 Therapy Visits.
21121............................ 1st and 2nd Episodes, 14 to C1F2S1 1.2574
15 Therapy Visits.
21122............................ 1st and 2nd Episodes, 16 to C1F2S2 1.4176
17 Therapy Visits.
21123............................ 1st and 2nd Episodes, 18 to C1F2S3 1.5779
19 Therapy Visits.
21131............................ 1st and 2nd Episodes, 14 to C1F3S1 1.2926
15 Therapy Visits.
21132............................ 1st and 2nd Episodes, 16 to C1F3S2 1.4558
17 Therapy Visits.
21133............................ 1st and 2nd Episodes, 18 to C1F3S3 1.6189
19 Therapy Visits.
21211............................ 1st and 2nd Episodes, 14 to C2F1S1 1.2814
15 Therapy Visits.
21212............................ 1st and 2nd Episodes, 16 to C2F1S2 1.4573
17 Therapy Visits.
21213............................ 1st and 2nd Episodes, 18 to C2F1S3 1.6332
19 Therapy Visits.
21221............................ 1st and 2nd Episodes, 14 to C2F2S1 1.3234
15 Therapy Visits.
21222............................ 1st and 2nd Episodes, 16 to C2F2S2 1.4970
17 Therapy Visits.
21223............................ 1st and 2nd Episodes, 18 to C2F2S3 1.6705
19 Therapy Visits.
21231............................ 1st and 2nd Episodes, 14 to C2F3S1 1.3586
15 Therapy Visits.
21232............................ 1st and 2nd Episodes, 16 to C2F3S2 1.5351
17 Therapy Visits.
[[Page 35287]]
21233............................ 1st and 2nd Episodes, 18 to C2F3S3 1.7116
19 Therapy Visits.
21311............................ 1st and 2nd Episodes, 14 to C3F1S1 1.3997
15 Therapy Visits.
21312............................ 1st and 2nd Episodes, 16 to C3F1S2 1.6178
17 Therapy Visits.
21313............................ 1st and 2nd Episodes, 18 to C3F1S3 1.8359
19 Therapy Visits.
21321............................ 1st and 2nd Episodes, 14 to C3F2S1 1.4418
15 Therapy Visits.
21322............................ 1st and 2nd Episodes, 16 to C3F2S2 1.6575
17 Therapy Visits.
21323............................ 1st and 2nd Episodes, 18 to C3F2S3 1.8732
19 Therapy Visits.
21331............................ 1st and 2nd Episodes, 14 to C3F3S1 1.4770
15 Therapy Visits.
21332............................ 1st and 2nd Episodes, 16 to C3F3S2 1.6956
17 Therapy Visits.
21333............................ 1st and 2nd Episodes, 18 to C3F3S3 1.9142
19 Therapy Visits.
22111............................ 3rd+ Episodes, 14 to 15 C1F1S1 1.2300
Therapy Visits.
22112............................ 3rd+ Episodes, 16 to 17 C1F1S2 1.3877
Therapy Visits.
22113............................ 3rd+ Episodes, 18 to 19 C1F1S3 1.5455
Therapy Visits.
22121............................ 3rd+ Episodes, 14 to 15 C1F2S1 1.2549
Therapy Visits.
22122............................ 3rd+ Episodes, 16 to 17 C1F2S2 1.4159
Therapy Visits.
22123............................ 3rd+ Episodes, 18 to 19 C1F2S3 1.5770
Therapy Visits.
22131............................ 3rd+ Episodes, 14 to 15 C1F3S1 1.3037
Therapy Visits.
22132............................ 3rd+ Episodes, 16 to 17 C1F3S2 1.4632
Therapy Visits.
22133............................ 3rd+ Episodes, 18 to 19 C1F3S3 1.6226
Therapy Visits.
22211............................ 3rd+ Episodes, 14 to 15 C2F1S1 1.2852
Therapy Visits.
22212............................ 3rd+ Episodes, 16 to 17 C2F1S2 1.4598
Therapy Visits.
22213............................ 3rd+ Episodes, 18 to 19 C2F1S3 1.6345
Therapy Visits.
22221............................ 3rd+ Episodes, 14 to 15 C2F2S1 1.3100
Therapy Visits.
22222............................ 3rd+ Episodes, 16 to 17 C2F2S2 1.4880
Therapy Visits.
22223............................ 3rd+ Episodes, 18 to 19 C2F2S3 1.6660
Therapy Visits.
22231............................ 3rd+ Episodes, 14 to 15 C2F3S1 1.3588
Therapy Visits.
22232............................ 3rd+ Episodes, 16 to 17 C2F3S2 1.5352
Therapy Visits.
22233............................ 3rd+ Episodes, 18 to 19 C2F3S3 1.7117
Therapy Visits.
22311............................ 3rd+ Episodes, 14 to 15 C3F1S1 1.4954
Therapy Visits.
22312............................ 3rd+ Episodes, 16 to 17 C3F1S2 1.6816
Therapy Visits.
22313............................ 3rd+ Episodes, 18 to 19 C3F1S3 1.8678
Therapy Visits.
22321............................ 3rd+ Episodes, 14 to 15 C3F2S1 1.5202
Therapy Visits.
22322............................ 3rd+ Episodes, 16 to 17 C3F2S2 1.7098
Therapy Visits.
22323............................ 3rd+ Episodes, 18 to 19 C3F2S3 1.8993
Therapy Visits.
22331............................ 3rd+ Episodes, 14 to 15 C3F3S1 1.5690
Therapy Visits.
22332............................ 3rd+ Episodes, 16 to 17 C3F3S2 1.7570
Therapy Visits.
22333............................ 3rd+ Episodes, 18 to 19 C3F3S3 1.9449
Therapy Visits.
30111............................ 3rd+ Episodes, 0 to 5 C1F1S1 0.4628
Therapy Visits.
30112............................ 3rd+ Episodes, 6 Therapy C1F1S2 0.6163
Visits.
30113............................ 3rd+ Episodes, 7 to 9 C1F1S3 0.7697
Therapy Visits.
30114............................ 3rd+ Episodes, 10 Therapy C1F1S4 0.9232
Visits.
30115............................ 3rd+ Episodes, 11 to 13 C1F1S5 1.0766
Therapy Visits.
30121............................ 3rd+ Episodes, 0 to 5 C1F2S1 0.5455
Therapy Visits.
30122............................ 3rd+ Episodes, 6 Therapy C1F2S2 0.6874
Visits.
30123............................ 3rd+ Episodes, 7 to 9 C1F2S3 0.8293
Therapy Visits.
30124............................ 3rd+ Episodes, 10 Therapy C1F2S4 0.9711
Visits.
30125............................ 3rd+ Episodes, 11 to 13 C1F2S5 1.1130
Therapy Visits.
30131............................ 3rd+ Episodes, 0 to 5 C1F3S1 0.5903
Therapy Visits.
30132............................ 3rd+ Episodes, 6 Therapy C1F3S2 0.7330
Visits.
30133............................ 3rd+ Episodes, 7 to 9 C1F3S3 0.8757
Therapy Visits.
30134............................ 3rd+ Episodes, 10 Therapy C1F3S4 1.0183
Visits.
30135............................ 3rd+ Episodes, 11 to 13 C1F3S5 1.1610
Therapy Visits.
30211............................ 3rd+ Episodes, 0 to 5 C2F1S1 0.4835
Therapy Visits.
30212............................ 3rd+ Episodes, 6 Therapy C2F1S2 0.6438
Visits.
30213............................ 3rd+ Episodes, 7 to 9 C2F1S3 0.8041
Therapy Visits.
30214............................ 3rd+ Episodes, 10 Therapy C2F1S4 0.9645
Visits.
30215............................ 3rd+ Episodes, 11 to 13 C2F1S5 1.1248
Therapy Visits.
30221............................ 3rd+ Episodes, 0 to 5 C2F2S1 0.5662
Therapy Visits.
30222............................ 3rd+ Episodes, 6 Therapy C2F2S2 0.7149
Visits.
30223............................ 3rd+ Episodes, 7 to 9 C2F2S3 0.8637
Therapy Visits.
30224............................ 3rd+ Episodes, 10 Therapy C2F2S4 1.0125
Visits.
30225............................ 3rd+ Episodes, 11 to 13 C2F2S5 1.1612
Therapy Visits.
30231............................ 3rd+ Episodes, 0 to 5 C2F3S1 0.6110
Therapy Visits.
30232............................ 3rd+ Episodes, 6 Therapy C2F3S2 0.7605
Visits.
30233............................ 3rd+ Episodes, 7 to 9 C2F3S3 0.9101
Therapy Visits.
30234............................ 3rd+ Episodes, 10 Therapy C2F3S4 1.0597
Visits.
30235............................ 3rd+ Episodes, 11 to 13 C2F3S5 1.2093
Therapy Visits.
30311............................ 3rd+ Episodes, 0 to 5 C3F1S1 0.5993
Therapy Visits.
[[Page 35288]]
30312............................ 3rd+ Episodes, 6 Therapy C3F1S2 0.7785
Visits.
30313............................ 3rd+ Episodes, 7 to 9 C3F1S3 0.9577
Therapy Visits.
30314............................ 3rd+ Episodes, 10 Therapy C3F1S4 1.1369
Visits.
30315............................ 3rd+ Episodes, 11 to 13 C3F1S5 1.3162
Therapy Visits.
30321............................ 3rd+ Episodes, 0 to 5 C3F2S1 0.6820
Therapy Visits.
30322............................ 3rd+ Episodes, 6 Therapy C3F2S2 0.8496
Visits.
30323............................ 3rd+ Episodes, 7 to 9 C3F2S3 1.0173
Therapy Visits.
30324............................ 3rd+ Episodes, 10 Therapy C3F2S4 1.1849
Visits.
30325............................ 3rd+ Episodes, 11 to 13 C3F2S5 1.3526
Therapy Visits.
30331............................ 3rd+ Episodes, 0 to 5 C3F3S1 0.7268
Therapy Visits.
30332............................ 3rd+ Episodes, 6 Therapy C3F3S2 0.8952
Visits.
30333............................ 3rd+ Episodes, 7 to 9 C3F3S3 1.0637
Therapy Visits.
30334............................ 3rd+ Episodes, 10 Therapy C3F3S4 1.2321
Visits.
30335............................ 3rd+ Episodes, 11 to 13 C3F3S5 1.4006
Therapy Visits.
40111............................ All Episodes, 20+ Therapy C1F1S1 1.7032
Visits.
40121............................ All Episodes, 20+ Therapy C1F2S1 1.7381
Visits.
40131............................ All Episodes, 20+ Therapy C1F3S1 1.7821
Visits.
40211............................ All Episodes, 20+ Therapy C2F1S1 1.8091
Visits.
40221............................ All Episodes, 20+ Therapy C2F2S1 1.8440
Visits.
40231............................ All Episodes, 20+ Therapy C2F3S1 1.8881
Visits.
40311............................ All Episodes, 20+ Therapy C3F1S1 2.0539
Visits.
40321............................ All Episodes, 20+ Therapy C3F2S1 2.0889
Visits.
40331............................ All Episodes, 20+ Therapy C3F3S1 2.1329
Visits.
----------------------------------------------------------------------------------------------------------------
To ensure the changes to the HH PPS case-mix weights are
implemented in a budget neutral manner, we then apply a case-mix budget
neutrality factor to the proposed CY 2018 national, standardized 60-day
episode payment rate (see section III.C.3. of this proposed rule). The
case-mix budget neutrality factor is calculated as the ratio of total
payments when the CY 2018 HH PPS case-mix weights (developed using CY
2016 home health claims data) are applied to CY 2016 utilization
(claims) data to total payments when CY 2017 HH PPS case-mix weights
(developed using CY 2015 home health claims data) are applied to CY
2016 utilization data. This produces a case-mix budget neutrality
factor for CY 2018 of 1.0159.
C. Proposed CY 2018 Home Health Payment Rate Update
1. Proposed CY 2018 Home Health Market Basket Update
Section 1895(b)(3)(B) of the Act requires that the standard
prospective payment amounts for CY 2018 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 through 67090).
Section 1895(b)(3)(B)(vi) of the Act, requires that, in CY 2015
(and in subsequent calendar years, except CY 2018 (under section 411(c)
of the Medicare Access and CHIP Reauthorization Act of 2015 (MACRA)
(Pub. L. 114-10, enacted April 16, 2015)), 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. Section 1886(b)(3)(B)(xi)(II) of the Act defines the
productivity adjustment 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.
Prior to the enactment of the MACRA, which amended section
1895(b)(3)(B) of the Act, the proposed home health update percentage
for CY 2018 would have been based on the estimated home health market
basket update of 2.7 percent (based on IHS Global Insight Inc.'s first-
quarter 2017 forecast with historical data through fourth-quarter
2016). Due to the requirements specified at section 1895(b)(3)(B)(vi)
of the Act prior to the enactment of MACRA, the estimated CY 2018 home
health market basket update of 2.7 percent would have been reduced by a
MFP adjustment as mandated by the Affordable Care Act (currently
estimated to be 0.5 percentage point for CY 2018). In effect, the
proposed home health payment update percentage for CY 2018 would have
been 2.2 percent. However, section 411(c) of the MACRA amended section
1895(b)(3)(B) of the Act, such that for home health payments for CY
2018, the market basket percentage increase is required to be 1
percent.
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 2018, the home health payment
update would be -1 percent (1 percent minus 2 percentage points).
2. Proposed CY 2018 Home Health Wage Index
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
[[Page 35289]]
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 2018, 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
2018, the updated wage data are for hospital cost reporting periods
beginning on or after October 1, 2013, and before October 1, 2014 (FY
2014 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).
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 2018 HH PPS wage index, we propose to continue to
use the same methodology discussed in the CY 2007 HH PPS final rule (71
FR 65884) to address those geographic areas in which there are no
inpatient hospitals. For rural areas that do not have inpatient
hospitals, we would use the average wage index from all contiguous Core
Based Statistical Areas (CBSAs) as a reasonable proxy. Currently, the
only rural area without a hospital from which hospital wage data could
be derived is Puerto Rico. However, 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 2018, the
only urban area without inpatient hospital wage data is Hinesville, GA
(CBSA 25980).
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. In
the CY 2015 HH PPS final rule (79 FR 66085 through 66087), we adopted
the OMB's new area delineations using a 1-year transition. The most
recent bulletin (No. 15-01) concerning the revised delineations was
published by the OMB on July 15, 2015.
The proposed CY 2018 wage index is available on the CMS Web site at
https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/HomeHealthPPS/Home-Health-Prospective-Payment-System-Regulations-and-Notices.html.
3. Proposed CY 2018 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 Sec. 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 2018 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.B of this rule. The following are the steps we take to
compute the case-mix and wage-adjusted 60-day episode rate:
(1) Multiply the national 60-day episode rate by the patient's
applicable case-mix weight.
(2) Divide the case-mix adjusted amount into a labor (78.535
percent) and a non-labor portion (21.465 percent).
(3) Multiply the labor portion by the applicable wage index based
on the site of service of the beneficiary.
(4) Add the wage-adjusted portion to the non-labor portion,
yielding the case-mix and wage adjusted 60-day episode rate, subject to
any additional applicable adjustments.
In accordance with section 1895(b)(3)(B) of the Act, this document
proposes 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 2
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. Sec. 484.205(c) and 484.230.
A partial episode payment (PEP) adjustment as set forth in
Sec. Sec. 484.205(d) and 484.235.
An outlier payment as set forth in Sec. Sec. 484.205(e)
and 484.240.
b. Proposed CY 2018 National, Standardized 60-Day Episode Payment Rate
Section 1895(3)(A)(i) of the Act requires 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 2018 national, standardized 60-day episode
payment rate, we would apply a wage
[[Page 35290]]
index budget neutrality factor; a case-mix budget neutrality factor
described in section III.B. of this proposed rule; a reduction of 0.97
percent to account for nominal case-mix growth from 2012 to 2014, as
finalized in the CY 2016 HH PPS final rule (80 FR 68646); and the home
health payment update percentage discussed in section III.C.1 of this
proposed rule.
To calculate the wage index budget neutrality factor, we simulated
total payments for non-LUPA episodes using the proposed CY 2018 wage
index and compared it to our simulation of total payments for non-LUPA
episodes using the CY 2017 wage index. By dividing the total payments
for non-LUPA episodes using the proposed CY 2018 wage index by the
total payments for non-LUPA episodes using the CY 2017 wage index, we
obtain a wage index budget neutrality factor of 1.0001. We would apply
the wage index budget neutrality factor of 1.0001 to the calculation of
the proposed CY 2018 national, standardized 60-day episode rate.
As discussed in section III.B. of this proposed rule, to ensure the
changes to the case-mix weights are implemented in a budget neutral
manner, we would apply a case-mix weight budget neutrality factor to
the CY 2018 national, standardized 60-day episode payment rate. The
case-mix weight budget neutrality factor is calculated as the ratio of
total payments when CY 2018 case-mix weights are applied to CY 2016
utilization (claims) data to total payments when CY 2017 case-mix
weights are applied to CY 2016 utilization data. The case-mix budget
neutrality factor for CY 2018 would be 1.0159 as described in section
III.B of this proposed rule.
Next, we would apply a reduction of 0.97 percent to the national,
standardized 60-day payment rate for CY 2018 to account for nominal
case-mix growth between CY 2012 and CY 2014. Lastly, we would update
the proposed payment rates by the proposed CY 2018 home health payment
update percentage of 1 percent as mandated by section
1895(b)(3)(B)(iii) of the Act. The proposed CY 2018 national,
standardized 60-day episode payment rate is calculated in Table 9.
Table 9--Proposed CY 2018 60-day National, Standardized 60-day Episode Payment Amount
--------------------------------------------------------------------------------------------------------------------------------------------------------
Proposed CY
Wage index Case-mix Nominal case- Proposed CY 2018 national,
CY 2017 national, standardized 60-day episode payment budget weights budget mix growth 2018 HH payment standardized 60-
neutrality neutrality adjustment (1- update day episode
factor factor 0.0097) payment
--------------------------------------------------------------------------------------------------------------------------------------------------------
$2,989.97.......................................................... x 1.0001 x 1.0159 x 0.9903 x 1.01 $3,038.43
--------------------------------------------------------------------------------------------------------------------------------------------------------
The proposed CY 2018 national, standardized 60-day episode payment
rate for an HHA that does not submit the required quality data is
updated by the proposed CY 2018 home health payment update of 1 percent
minus 2 percentage points and is shown in Table 10.
Table 10--Proposed CY 2018 National, Standardized 60-day Episode Payment Amount for HHAs That DO NOT Submit the Quality Data
--------------------------------------------------------------------------------------------------------------------------------------------------------
Proposed CY Proposed CY
Wage index Case-mix Nominal case- 2018 HH payment 2018 national,
CY 2017 national, standardized 60-day episode payment budget weights budget mix growth update minus 2 standardized 60-
neutrality neutrality adjustment (1- percentage day episode
factor factor 0.0097) points payment
--------------------------------------------------------------------------------------------------------------------------------------------------------
$2,989.97.......................................................... x 1.0001 x 1.0159 x 0.9903 x 0.99 $2,978.26
--------------------------------------------------------------------------------------------------------------------------------------------------------
c. Proposed CY 2018 National Per-Visit Rates
The national per-visit rates are used to pay LUPAs (episodes with
four or fewer visits) and are also used to compute imputed costs in
outlier calculations. The per-visit rates are paid by type of visit or
HH discipline. The six HH disciplines are as follows:
Home health aide (HH aide);
Medical Social Services (MSS);
Occupational therapy (OT);
Physical therapy (PT);
Skilled nursing (SN); and
Speech-language pathology (SLP).
To calculate the proposed CY 2018 national per-visit rates, we
start with the CY 2017 national per-visit rates. We then apply a wage
index budget neutrality factor to ensure budget neutrality for LUPA
per-visit payments. We calculate the wage index budget neutrality
factor by simulating total payments for LUPA episodes using the
proposed CY 2018 wage index and comparing it to simulated total
payments for LUPA episodes using the CY 2017 wage index. By dividing
the total payments for LUPA episodes using the proposed CY 2018 wage
index by the total payments for LUPA episodes using the CY 2017 wage
index, we obtain a wage index budget neutrality factor of 1.0005. We
would apply the wage index budget neutrality factor of 1.0005 in order
to calculate the CY 2018 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. Lastly, the per-visit
rates for each discipline are updated by the proposed CY 2018 home
health payment update percentage of 1 percent. The national per-visit
rates are adjusted by the wage index based on the site of service of
the beneficiary. The per-visit payments for LUPAs are separate from the
LUPA add-on payment amount, which is paid for episodes that occur as
the only episode or initial episode in a sequence of adjacent episodes.
The proposed CY 2018 national per-visit rates are shown in Tables 11
and 12.
[[Page 35291]]
Table 11--Proposed CY 2018 National Per-Visit Payment Amounts for HHAs That DO Submit the Required Quality Data
----------------------------------------------------------------------------------------------------------------
Wage index
CY 2017 per- budget Proposed CY Proposed CY
HH discipline type visit payment neutrality 2018 HH 2018 per-visit
factor payment update payment
----------------------------------------------------------------------------------------------------------------
Home Health Aide................................ $64.23 x 1.0005 x 1.01 $64.90
Medical Social Services......................... 227.36 x 1.0005 x 1.01 229.75
Occupational Therapy............................ 156.11 x 1.0005 x 1.01 157.75
Physical Therapy................................ 155.05 x 1.0005 x 1.01 156.68
Skilled Nursing................................. 141.84 x 1.0005 x 1.01 143.33
Speech- Language Pathology...................... 168.52 x 1.0005 x 1.01 170.29
----------------------------------------------------------------------------------------------------------------
The proposed CY 2018 per-visit payment rates for HHAs that do not
submit the required quality data are updated by the proposed CY 2018 HH
payment update percentage of 1 percent minus 2 percentage points and
are shown in Table 12.
Table 12--Proposed CY 2018 National Per-Visit Payment Amounts for HHAs That DO NOT Submit the Required Quality
Data
----------------------------------------------------------------------------------------------------------------
Proposed CY
Wage index 2018 HH
CY 2017 per- budget payment update Proposed CY
HH discipline type visit rates neutrality minus 2 2018 per-visit
factor percentage rates
points
----------------------------------------------------------------------------------------------------------------
Home Health Aide................................ $64.23 x 1.0005 x 0.99 $63.62
Medical Social Services......................... 227.36 x 1.0005 x 0.99 225.20
Occupational Therapy............................ 156.11 x 1.0005 x 0.99 154.63
Physical Therapy................................ 155.05 x 1.0005 x 0.99 153.58
Skilled Nursing................................. 141.84 x 1.0005 x 0.99 140.49
Speech- Language Pathology...................... 168.52 x 1.0005 x 0.99 166.92
----------------------------------------------------------------------------------------------------------------
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, in the case of HHAs that do submit the required quality
data, 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 $264.46 (1.8451 multiplied
by $143.33), subject to area wage adjustment.
e. Proposed CY 2018 Non-Routine Medical Supply (NRS) Payment Rates
Payments for NRS are computed by multiplying the relative weight
for a particular severity level by the NRS conversion factor. To
determine the proposed CY 2018 NRS conversion factor, we update the CY
2017 NRS conversion factor ($52.50) by the proposed CY 2018 home health
payment update percentage of 1 percent. We do not apply a
standardization factor as the NRS payment amount calculated from the
conversion factor is not wage or case-mix adjusted when the final claim
payment amount is computed. The proposed NRS conversion factor for CY
2018 is shown in Table 13.
Table 13--Proposed CY 2018 NRS Conversion Factor for HHAs That DO Submit
the Required Quality Data
------------------------------------------------------------------------
Proposed CY
Proposed CY 2018 NRS
CY 2017 NRS conversion factor 2018 HH conversion
payment update factor
------------------------------------------------------------------------
$52.50................................ x 1.01 $53.03
------------------------------------------------------------------------
Using the CY 2018 NRS conversion factor, the payment amounts for
the six severity levels are shown in Table 14.
Table 14--Proposed CY 2018 NRS Payment Amounts for HHAs That DO Submit the Required Quality Data
----------------------------------------------------------------------------------------------------------------
Proposed CY
Relative 2017 NRS
Severity level Points (scoring) weight payment
amounts
----------------------------------------------------------------------------------------------------------------
1........................................... 0................................. 0.2698 $ 14.31
2........................................... 1 to 14........................... 0.9742 51.66
3........................................... 15 to 27.......................... 2.6712 141.65
4........................................... 28 to 48.......................... 3.9686 210.45
[[Page 35292]]
5........................................... 49 to 98.......................... 6.1198 324.53
6........................................... 99+............................... 10.5254 558.16
----------------------------------------------------------------------------------------------------------------
For HHAs that do not submit the required quality data, we update
the CY 2017 NRS conversion factor ($52.50) by the proposed CY 2018 home
health payment update percentage of 1 percent minus 2 percentage
points. The proposed CY 2018 NRS conversion factor for HHAs that do not
submit quality data is shown in Table 15.
Table 15--Proposed CY 2018 NRS Conversion Factor for HHAs That DO NOT
Submit the Required Quality Data
------------------------------------------------------------------------
Proposed CY
2018 HH payment
update Proposed CY
CY 2017 NRS conversion factor percentage 2018 NRS
minus 2 conversion
percentage factor
points
------------------------------------------------------------------------
$52.50................................ x 0.99 $51.98
------------------------------------------------------------------------
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 16.
Table 16--Proposed CY 2018 NRS Payment Amounts for HHAs That DO NOT Submit the Required Quality Data
----------------------------------------------------------------------------------------------------------------
Proposed CY
Relative 2018 NRS
Severity level Points (scoring) weight payment
amounts
----------------------------------------------------------------------------------------------------------------
1........................................... 0................................. 0.2698 $ 14.02
2........................................... 1 to 14........................... 0.9742 50.64
3........................................... 15 to 27.......................... 2.6712 138.85
4........................................... 28 to 48.......................... 3.9686 206.29
5........................................... 49 to 98.......................... 6.1198 318.11
6........................................... 99+............................... 10.5254 547.11
----------------------------------------------------------------------------------------------------------------
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 MACRA 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.
Therefore, for episodes and visits that end on or after January 1,
2018, a rural add-on payment will not apply.
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 home health payment amount in the case of
outliers because of unusual variations in the type or amount of
medically necessary care. Prior to the enactment of the Affordable Care
Act, section 1895(b)(5) of the Act stipulated that projected total
outlier payments could not exceed 5 percent of total projected or
estimated HH payments in a given year. In the July 3, 2000 Medicare
Program; Prospective Payment System for Home Health Agencies final rule
(65 FR 41188 through 41190), we described the method for determining
outlier payments. Under this system, outlier payments are made for
episodes whose estimated costs exceed a threshold amount for each Home
Health Resource Group (HHRG). The episode's estimated cost was
established as the sum of the national wage-adjusted per-visit payment
amounts 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
[[Page 35293]]
beyond the wage-adjusted threshold. The threshold amount is the sum of
the wage and case-mix adjusted PPS episode amount and wage-adjusted FDL
amount. The proportion of additional costs over the outlier threshold
amount paid as outlier payments is referred to as the loss-sharing
ratio.
In the CY 2010 HH PPS proposed rule (74 FR 40948, 40957), we stated
that outlier payments increased as a percentage of total payments from
4.1 percent in CY 2005, to 5.0 percent in CY 2006, to 6.4 percent in CY
2007 and that this excessive growth in outlier payments was primarily
the result of unusually high outlier payments in a few areas of the
country. In that discussion, we noted that despite program integrity
efforts associated with excessive outlier payments in targeted areas of
the country, we discovered that outlier expenditures still exceeded the
5 percent target in CY 2007 and, in the absence of corrective measures,
would continue do to so. Consequently, we assessed the appropriateness
of taking action to curb outlier abuse. As described in the CY 2010 HH
PPS final rule (74 FR 58080 through 58087), to mitigate possible
billing vulnerabilities associated with excessive outlier payments and
adhere to our statutory limit on outlier payments, we finalized an
outlier policy that included a 10 percent agency-level cap on outlier
payments. This cap was implemented in concert with a reduced FDL ratio
of 0.67. These policies resulted in a projected target outlier pool of
approximately 2.5 percent. (The previous outlier pool was 5 percent of
total home health expenditures). For CY 2010, we first returned the 5
percent held for the previous target outlier pool to the national,
standardized 60-day episode rates, the national per-visit rates, the
LUPA add-on payment amount, and the NRS conversion factor. Then, we
reduced the CY 2010 rates by 2.5 percent to account for the new outlier
pool of 2.5 percent. This outlier policy was adopted for CY 2010 only.
As we noted in the CY 2011 HH PPS final rule (75 FR 70397 through
70399), section 3131(b)(1) of the Affordable Care Act amended section
1895(b)(3)(C) of the Act, and required the Secretary to reduce the HH
PPS payment rates such that aggregate HH PPS payments were reduced by 5
percent. In addition, section 3131(b)(2) of the Affordable Care Act
amended section 1895(b)(5) of the Act by redesignating the existing
language as section 1895(b)(5)(A) of the Act, and revising the language
to state that the total amount of the additional payments or payment
adjustments for outlier episodes may not exceed 2.5 percent of the
estimated total HH PPS payments for that year. Section 3131(b)(2)(C) of
the Affordable Care Act also added section 1895(b)(5)(B) of the Act
which capped outlier payments as a percent of total payments for each
HHA at 10 percent.
As such, beginning in CY 2011, our HH PPS outlier policy is that we
reduce payment rates by 5 percent and target up to 2.5 percent of total
estimated HH PPS payments to be paid as outliers. To do so, we first
returned the 2.5 percent held for the target CY 2010 outlier pool to
the national, standardized 60-day episode rates, the national per visit
rates, the LUPA add-on payment amount, and the NRS conversion factor
for CY 2010. We then reduced the rates by 5 percent as required by
section 1895(b)(3)(C) of the Act, as amended by section 3131(b)(1) of
the Affordable Care Act. For CY 2011 and subsequent calendar years we
target up to 2.5 percent of estimated total payments to be paid as
outlier payments, and apply a 10 percent agency-level outlier cap.
In the CY 2017 HH PPS proposed and final rules (81 FR 43737 through
43742 and 81 FR 76702), we described our concerns regarding patterns
observed in home health outlier episodes. Specifically, we noted that
the methodology for calculating home health outlier payments may have
created a financial incentive for providers to increase the number of
visits during an episode of care to surpass the outlier threshold and
simultaneously created a disincentive for providers to treat medically
complex beneficiaries who require fewer but longer visits. Given these
concerns, in the CY 2017 HH PPS final rule (81 FR 76702), we finalized
changes to the methodology used to calculate outlier payments, using a
cost-per-unit approach rather than a cost-per-visit approach. This
change in methodology allows for more accurate payment for outlier
episodes, accounting for both the number of visits during an episode of
care and also the length of the visits provided. Using this approach,
we now convert the national per-visit rates into per 15-minute unit
rates. These per 15-minute unit rates are used to calculate the
estimated cost of an episode to determine whether the claim will
receive an outlier payment and the amount of payment for an episode of
care. In conjunction with our finalized policy to change to a cost-per-
unit approach to estimate episode costs and determine whether an
outlier episode should receive outlier payments, in the CY 2017 HH PPS
final rule we also finalized the implementation of a cap on the amount
of time per day that would be counted toward the estimation of an
episode's costs for outlier calculation purposes (81 FR 76725).
Specifically, we limit the amount of time per day (summed across the
six disciplines of care) to 8 hours (32 units) per day when estimating
the cost of an episode for outlier calculation purposes.
2. Fixed Dollar Loss (FDL) Ratio
For a given level of outlier payments, there is a trade-off between
the values selected for the FDL ratio and the loss-sharing ratio. A
high FDL ratio reduces the number of episodes that can receive outlier
payments, but makes it possible to select a higher loss-sharing ratio,
and therefore, increase outlier payments for qualifying outlier
episodes. Alternatively, a lower FDL ratio means that more episodes can
qualify for outlier payments, but outlier payments per episode must
then be lower.
The FDL ratio and the loss-sharing ratio must be selected so that
the estimated total outlier payments do not exceed the 2.5 percent
aggregate level (as required by section 1895(b)(5)(A) of the Act).
Historically, we have used a value of 0.80 for the loss-sharing ratio
which, we believe, preserves incentives for agencies to attempt to
provide care efficiently for outlier cases. With a loss-sharing ratio
of 0.80, Medicare pays 80 percent of the additional estimated costs
above the outlier threshold amount.
Simulations based on CY 2015 claims data (as of June 30, 2016)
completed for the CY 2017 HH PPS final rule showed that outlier
payments were estimated to represent approximately 2.84 percent of
total HH PPS payments in CY 2017, and as such, we raised the FDL ratio
from 0.45 to 0.55. We stated that raising the FDL ratio to 0.55, while
maintaining a loss-sharing ratio of 0.80, struck an effective balance
of compensating for high-cost episodes while still meeting the
statutory requirement to target up to, but no more than, 2.5 percent of
total payments as outlier payments (81 FR 76726). 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, using preliminary CY 2016 claims data (as
of March 17, 2017) and the proposed CY 2018 payment rates presented in
section III.C of this proposed rule, we estimate that outlier payments
would constitute
[[Page 35294]]
approximately 2.47 percent of total HH PPS payments in CY 2018 under
the current outlier methodology. Given the statutory requirement to
target up to, but no more than, 2.5 percent of total payments as
outlier payments, we are not proposing a change to the FDL ratio for CY
2018 as we believe that maintaining an FDL ratio of 0.55 with a loss-
sharing ratio of 0.80 is still appropriate given the percentage of
outlier payments projected for CY 2018. Likewise, we are not proposing
a change to the loss-sharing ratio (0.80) for the HH PPS to remain
consistent with payment for high-cost outliers in other Medicare
payment systems (for example, IRF PPS, IPPS, etc.). While we are not
proposing to change the FDL ratio of 0.55 for CY 2018, we note that in
the final rule, we will update our estimate of outlier payments as a
percent of total HH PPS payments using the most current and complete
year of HH PPS data (CY 2016 claims data as of June 30, 2017 or later).
This may result in changes to the FDL ratio in the final rule.
E. Proposed Implementation of the Home Health Groupings Model (HHGM)
for CY 2019
1. Overview, Data, and File Construction
Under the home health prospective payment system (HH PPS), Medicare
pays for home health services provided during a 60-day episode of care.
Episodes are case-mix adjusted based on the timing of the episode
within a sequence of episodes, the patient's clinical status and
functional status as determined using information from the Outcome and
Assessment Information Set (OASIS), and the amount of therapy service
provided during the episode. Therapy service use is measured by the
number of therapy visits provided during the episode and can be
categorized into nine visit level categories (or thresholds): 0-5; 6;
7-9; 10; 11-13; 14-15; 16-17; 18-19; and 20 or more visits. The
combinations of episode timing, clinical and functional levels, and
therapy service use categories result in 153 home health resource
groups (HHRGs) into which home health episodes are categorized. Each
HHRG is assigned a relative weight reflecting the average resource use
of patients in that group compared with average resource use across all
Medicare home health patients; this weight is then used to case mix
adjust the episode's payment (with an additional adjustment for
geographic variation in wages). Additional payment adjustments are made
for very resource intensive (outlier) episodes, episodes with very few
visits, transfers to other HHAs or to hospitals with a return to home
health during the episode, and the expected use of non-routine medical
supplies (NRS).
As discussed in section II.D of this proposed rule, the Report to
Congress, required by section 3131(d) of the Affordable Care Act, found
that payment accuracy could be improved under the current payment
system, particularly for patients with certain clinical
characteristics.\16\ Findings from the report suggest 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 need therapy services, but require skilled nursing care. In
addition, MedPAC believes that the Medicare home health benefit is ill-
defined and the current reliance on therapy service thresholds for
determining payment is counter to the goals of a prospective payment
system. Under the current payment system, HHAs receive higher payments
for providing more therapy visits, which may incentivize unnecessary
utilization. MedPAC reitereated their recommendation in the March 2017
Report to Congress that CMS eliminate the use of the number of therapy
vists as a payment factor in the home health PPS beginning in 2019.\17\
---------------------------------------------------------------------------
\16\ Report to Congress. Medicare Home Health Study: An
Investigation on Access to Care and Payment for Vulnerable Patient
Populations. Available at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/HomeHealthPPS/Downloads/HH-Report-to-Congress.pdf.
\17\ Medicare Payment Advisory Commission (MedPAC). ``Home
Health Care Services.'' Report to Congress: Medicare Payment Policy.
Washington, DC, March 2015. P. 233. Accessed on March 28, 2017 at
https://www.medpac.gov/docs/default-source/reports/mar2015_entirereport_revised.pdf?sfvrsn=0.
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To better align payment with patient care needs and better ensure
that clinically complex and ill beneficiaries have adequate access to
home health care, we are proposing for CY 2019 case-mix methodology
refinements through the implementation of the Home Health Groupings
Model (HHGM). We propose to implement the HHGM for home health periods
of care beginning on or after January 1, 2019. The implementation of
the HHGM will require provider education and training, updating and
revising relevant manuals, and changing claims processing systems.
Implementation starting in CY 2019 would provide an opportunity for
CMS, its contractors, and the agencies themselves to prepare. This
patient-centered model groups periods of care in a manner consistent
with how clinicians differentiate between patients and the primary
reason for needing home health care. The HHGM uses 30-day periods
rather than the 60-day episode used in the current payment system,
eliminates the use of the number of therapy visits provided to
determine payment, and relies more heavily on clinical characteristics
and other patient information (for example, diagnosis, functional
level, comorbid conditions, admission source) to place patients into
clinically meaningful payment categories. In total, there are 144
different payment groups in the HHGM.
Costs during an episode/period of care are estimated based on the
concept of resource use, which measures the costs associated with
visits performed during a home health episode/period. For the current
HH PPS case-mix weights, we use Wage Weighted Minutes of Care (WWMC),
which uses data from the Bureau of Labor Statistics (BLS) reflecting
the Home Health Care Service Industry. For the HHGM, we propose
shifting to a Cost-Per-Minute plus Non-Routine Supplies (CPM + NRS)
approach, which uses information from the Medicare Cost Report. The CPM
+ NRS approach incorporates a wider variety of costs (such as
transportation) compared to the BLS estimates and the costs are
available for individual HHA providers while the BLS costs are
aggregated for the Home Health Care Service industry. The proposed
methodology used to calculate the cost of an episode/period of care is
discussed in detail in section III.E.2. of this proposed rule.
We propose using the 30-day periods rather than the 60-day episodes
in the current payment system. Episodes have more visits, on average,
during the first 30 days compared to the last 30 days.\18\ Costs are
much higher earlier in the episode and lesser later on, therefore we
believe that dividing a single 60-day episode into two 30-day periods
more accurately apportions payments. Overall, we found that the average
length of an episode of care was 47 days, but roughly a quarter of all
60 days episodes lasted 30 days or less. The proposed change from 60-
day billing to 30-day billing under the HHGM is discussed in detail in
section III.E.3. of this proposed rule.
---------------------------------------------------------------------------
\18\ Abt Associates. ``Overview of the Home Health Groupings
Model.'' Medicare Home Health Prospective Payment System: Case-Mix
Methodology Refinements. Cambridge, MA, November 18, 2016. Available
at https://downloads.cms.gov/files/hhgm%20technical%20report%20120516%20sxf.pdf.
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[[Page 35295]]
Similar to the current payment system, 30-day periods under the
HHGM would be classified as ``early'' or ``late'' depending on when
they occur within a sequence of 30-day periods. Under the current HH
PPS, the first two 60-day episodes of a sequence of adjacent 60-day
episodes are considered early, while the third 60-day episode of that
sequence and any subsequent episodes are considered late. Under the
HHGM, the first 30-day period is classified as early. All subsequent
30-day periods in the sequence (second or later) are classified as
late. We propose to adopt this episode timing classification for 30-day
periods with the implementation of the HHGM. Similar to the current
payment system, we propose that a 30-day period could not be considered
early unless there was a gap of more than 60 days between the end of
one period and the start of another. The comprehensive assessment would
still be completed within 5 days of the start of care date and
completed no less frequently than during the last 5 days of every 60
days beginning with the start of care date, as currently required by
Sec. 484.55, Condition of participation: Comprehensive assessment of
patients. The proposed episode timing classification is discussed in
detail in section III.E.4. of this proposed rule.
Under the HHGM, each period would be classified into one of two
admission source categories--community or institutional--depending on
what healthcare setting was utilized in the 14 days prior to home
health. The 30-day period would be categorized as institutional if an
acute or post-acute care stay occurred in the prior 14 days to the
start of the 30-day period of care. The 30-day period would be
categorized as community if there was no acute or post-acute care stay
in the 14 days prior to the start of the 30-day period of care. We
propose to adopt this categorization by admission source with the
implementation of the HHGM. The proposed admission classification
source is discussed in detail in section III.E.5. of this proposed
rule.
The HHGM would group 30-day periods into categories based on a
variety of patient characteristics. Within the HHGM, one of the steps
in case-mix adjusting the 30-day payment amount would include grouping
periods into one of six clinical groups based on the principal
diagnosis listed on the home health claim. We propose grouping periods
into one of six clinical groups based on the principal diagnosis with
the implementation of the HHGM. The principal diagnosis reported would
provide information to describe the primary reason for which patients
are receiving home health services under the Medicare home health
benefit. The proposed six clinical groups, which are discussed in
detail in section III.E.6. of this proposed rule, are as follows:
Musculoskeletal Rehabilitation.
Neuro/Stroke Rehabilitation.
Wounds--Post-Op Wound Aftercare and Skin/Non-Surgical
Wound Care.
Complex Nursing Interventions.
Behavioral Health Care.
Medication Management, Teaching and Assessment (MMTA).
Under the HHGM, each 30-day period would be placed into one of
three functional levels. The level would indicate if, on average, given
its responses on certain functional OASIS items, a 30-day period is
predicted to have higher costs or lower costs. We propose classifying
30-day periods according to functional level. For each of the six
clinical groups, we propose that periods would be further classified
into one of three functional levels with roughly 33 percent of periods
in each level. The creation of this functional level is very similar to
how the functional level is created in the current payment system. The
proposed functional levels and corresponding OASIS items are discussed
in detail in section III.E.7. of this proposed rule.
Exploratory analyses determined that comorbidities--that is,
secondary diagnoses--provide additional information that can further
explain resource use differences across 30-day periods of care even
after controlling for the primary diagnosis. Comorbidities are tied to
poorer health outcomes, more complex medical need and management, and
higher costs. The HHGM would include a comorbidity adjustment category
based on the presence of secondary diagnoses. We propose that 30-day
periods would receive a comorbidity adjustment if any diagnosis codes
listed on the home health claim are included on a list of comorbidities
that occurred in at least 0.1 percent of 30-day periods and associated
with increased average resource use. The proposed comorbidity
adjustment is discussed in detail in section III.E.8. of this proposed
rule.
Currently, if an HHA provides four visits or less in an episode,
they will be paid a standardized per visit payment instead of an
episode payment for a 60-day episode of care. These payment adjustments
are called Low-Utilization Payment Adjustments (LUPAs). While the HHGM
would still include LUPAs, the approach to calculating the LUPA
thresholds would need to change in the HHGM because of the switch to
30-day periods from 60-day episodes. Whereas there is a single LUPA
threshold of 4 visits for all episodes under the current payment
system, we propose the LUPA threshold would vary for a 30-day period
under the HHGM depending on the HHGM payment group to which it was
assigned. To create LUPA thresholds, 30-day periods (including those
that were LUPAs in the current payment system) were grouped into the
144 different HHGM payment groups. For each payment group, we propose
to use the 10th percentile value of visits to create a payment group
specific LUPA threshold with a minimum threshold of at least 2 for each
group. The proposed LUPA thresholds are discussed in more detail in
section III.E.9. of this proposed rule.
Figure 5 represents how each 30-day period of care would be placed
into one of 144 home health resource groups (HHRGs) under the proposed
HHGM.
[[Page 35296]]
[GRAPHIC] [TIFF OMITTED] TP28JY17.003
While the proposed HHGM would reflect a change in the case-mix
adjustment methodology, the conditions for payment would remain the
same for Medicare home health services, meaning all requirements would
still
[[Page 35297]]
need to be met in accordance with Sec. 424.22. This includes physician
certification that: (1) The individual is in need or needed
intermittent skilled nursing care, or physical therapy or speech-
language pathology services, and is confined to the home; (2) a plan of
care has been established and will be periodically reviewed by a
physician who is a doctor of medicine, osteopathy, or podiatric
medicine; (3) the individual was under the care of a physician who is a
doctor of medicine, osteopathy, or podiatric medicine; and, (4) a face-
to-face patient encounter, which is related to the primary reason the
patient requires home health services, occurred no more than 90 days
prior to the home health start of care date or within 30 days of the
start of the home health care and was performed by a physician or
allowed non-physician practitioner. Likewise, under the HHGM, the
Medicare beneficiary would retain all rights that currently exist under
the current HH PPS, including those related to beneficiary liability
for services or any reduction or termination of services. These would
include the issuance of the Advanced Beneficiary Notice (ABN) and the
Home Health Change of Care Notice (HHCCN), when appropriate. Medicare
home health agencies are required to issue an ABN when a HHA believes
Medicare will not pay for some or all of the patient's Medicare home
health care. In these circumstances, if the beneficiary chooses to
receive the items/services in question and Medicare does not cover the
home health care, HHAs may use the ABN to shift liability for the non-
covered home health care to the beneficiary. The HHCCN is a written
notice that the HHA provides a beneficiary when his/her home health
plan of care is changing because the home health agency makes a
business decision to reduce or stop providing the patient some or all
of the home health services or supplies OR the beneficiary's physician
changed orders which may reduce or stop certain Medicare covered home
health services or supplies.
To create the HHGM proposed model and related analyses, a data file
based on home health episodes of care as reported in Medicare home
health claims was utilized. The claims data provide episode-level data
(for example, episode From and Through Dates, total number of visits,
HHRG, diagnoses), as well as visit-level data (visit date, visit length
in 15-minute units, discipline of the staff, etc.). The claims also
provide data on whether NRS was provided during the episode and total
charges for NRS.
The core file for most of the analyses for this proposed rule
includes 100 percent of home health episode claims with Through Dates
in Calendar Year (CY) 2016, processed by March 17, 2017, accessed via
the Chronic Conditions Data Warehouse (CCW). Original or adjustment
claims processed after March 17, 2017, would not be reflected in the
core file. The claims-based file was supplemented with additional
variables that were obtained from the CCW, such as information
regarding other Part A and Part B utilization.
The data were cleaned by processing any remaining adjustments and
by excluding duplicates and claims that were Requests for Anticipated
Payment (RAP). In addition, visit-level variables needed for the
analysis were extracted from the revenue center trailers (that is, the
line items that describe the visits) and downloaded as a separate
visit-level file, with selected episode-level variables merged onto the
records for visits during those episodes. To account for potential data
entry errors, the visit-level variables for visit length were top-
censored at eight hours.\19\
---------------------------------------------------------------------------
\19\ Less than 0.1 percent of all visits were recorded as having
greater than 8 hours of service.
---------------------------------------------------------------------------
A set of data cleaning exclusions were applied to the episode-level
file, which resulted in the exclusion of the following:
Episodes with no covered visits.
Episodes with any missing units or visit data.
Episodes with zero payments.
Episodes with no charges.
Non-LUPA episodes missing an HHRG.
The analysis file also includes data on patient characteristics
obtained from the OASIS assessments conducted by HHA staff at the start
of each episode. The assessment data are electronically submitted by
home health agencies (HHAs) to a central CMS repository. In
constructing the core data file, 100 percent of the OASIS assessments
submitted October 2015, through December 2016 from the CMS repository
were uploaded by CMS to the CCW. A CCW-derived linking key (Bene_ID)
was used to match the OASIS data with CY 2016 episodes of care.
Episodes that could not be linked with an OASIS assessment were
excluded from the analysis file, as they included insufficient patient-
level data to create the HHGM.
To construct measures of resource use, a variety of data sources
were used (see section III.E.2 of this proposed rule for the proposed
methodology used to calculate the cost of care under the HHGM). First,
BLS data on average wages and fringe benefits were used to produce one
version of the wage-weighted cost per minute for each home health
discipline. The wage data are for North American Industry
Classification System (NAICS) 621600--Home Health Care Services. The
wage data are broken down by the following occupations:
Table 17--BLS Standard Occupation Classification (SOC) Codes for Home
Health Providers
------------------------------------------------------------------------
Standard Occupation Code (SOC) No. Occupation title
------------------------------------------------------------------------
29-1141................................... Registered Nurses.
29-2061................................... Licensed Practical and
Licensed Vocational Nurses.
29-1123................................... Physical Therapists.
31-2021................................... Physical Therapist
Assistants.
31-2022................................... Physical Therapist Aides.
29-1122................................... Occupational Therapists.
31-2011................................... Occupational Therapist
Assistants.
31-2012................................... Occupational Therapist
Aides.
29-1127................................... Speech-Language
Pathologists.
21-1022................................... Medical and Public Health
Social Workers.
21-1023................................... Mental Health and Substance
Abuse Social Workers.
31-1011................................... Home Health Aides.
------------------------------------------------------------------------
For visits where the service provided--as indicated by the
Healthcare Common Procedure Coding System (HCPCS) code--can be provided
by only a single standard occupation classification code; for example,
establishment or review of a plan of care by a registered nurse (RN;
HCPCS = G0162), the wage (and fringe) rate for that standard occupation
classification is used to calculate the cost of the minutes for the
visit. For visits where the service provided can potentially be
provided by different standard occupation classification, such as
observation and assessment by an RN or a Licensed Practical Nurse (LPN;
HCPCS = G0163), a blended rate is applied, with the rate for each
standard occupation classification code weighted by the total home
health employment for that standard occupation classification code. The
employment data are available from the same BLS table as the wage data.
Home Health Agency Medicare Cost Report (MCR) data were also used
to construct a measure of resource use after trimming out HHAs whose
costs were outliers. These data are used to provide a representation of
the average costs of visits provided by HHAs in the six Medicare home
health disciplines: Skilled nursing; physical therapy; occupational
therapy; speech-language pathology; medical social services; and home
health aide services. Cost report
[[Page 35298]]
data are publicly available at https://www.cms.gov/Research-Statistics-Data-and-Systems/Downloadable-Public-Use-Files/Cost-Reports/.
The 2016 analytic file included 6,293,442 episodes. Of these,
469,346 (7.5 percent) were excluded because they could not be linked to
OASIS assessments or because of the reasons listed above. This yielded
an analysis file including 5,824,096 episodes. Those episodes are 60-
day episodes under the current payment system, but for the HHGM those
60-day episodes were converted into two 30-day periods. This yielded a
final HHGM analytic file that included 10,231,507, 30-day periods.
Certain 30-day periods were excluded for the following reasons:
Periods missing a diagnosis code or where the diagnosis
code did not link to a clinical group to case-mix adjust the period's
payment (after exclusions, n = 10,177,949).
Inability to merge to certain OASIS items to create the
episode's functional level that is used for risk adjustment. For all
the periods in the analytic file, there was a look-back through CY 2015
for a Start of Care or Resumption of Care assessment that preceded the
period being analyzed and was in the same sequence of periods. If such
an assessment was found, it was used to impute responses for OASIS
items that were not included in the follow-up assessment. Periods which
did not link to a Start of Care or Resumption of Care assessment were
dropped (after exclusions, n = 9,477,856).
No nursing visits or therapy visits (after exclusions, n =
9,290,340).
LUPAs were excluded from the analysis. Periods that are
identified as LUPAs in the current payment system are excluded in the
creation of the functional score. Following the creation of the score
(and the corresponding levels), case-mix group specific LUPA thresholds
were created and episodes/periods were excluded that were below the new
LUPA threshold when computing the case-mix weights.\20\ Therefore, the
final analytic sample included 8,642,107 30-day periods that were used
for the analyses in the HHGM.
---------------------------------------------------------------------------
\20\ The case-mix group specific LUPA thresholds were determined
using episodes that were considered LUPAs under the current payment
system.
---------------------------------------------------------------------------
As noted in section II.D of this proposed rule, the analyses and
the ultimate development of Home Health Groupings Model (HHGM) have
been shared with both internal and external stakeholders via technical
expert panels, clinical workgroups, special open door forums, and in
the CY 2017 HH PPS final rule (81 FR 76702). Technical expert panel and
clinical workgroup webinars on the technical report were held in
December 2016 and a detailed technical report was posted on the CMS
home health agency Web page in December, providing opportunity for
stakeholder feedback.\21\ We also held a National Provider call in
January 2017, to further solicit feedback from the public.\22\
---------------------------------------------------------------------------
\21\ Abt Associates. ``Overview of the Home Health Groupings
Model.'' Medicare Home Health Prospective Payment System: Case-Mix
Methodology Refinements. Cambridge, MA, November 18, 2016. Available
at https://downloads.cms.gov/files/hhgm%20technical%20report%20120516%20sxf.pdf.
\22\ Centers for Medicare & Medicaid Services (CMS).
``Certifying Patients for the Medicare Home Health Benefit.'' MLN
ConnectsTM National Provider Call. Baltimore, MD,
December 16, 2016. Slides, examples, audio recording and transcript
available at https://www.cms.gov/Outreach-and-Education/Outreach/NPC/National-Provider-Calls-and-Events-Items/2017-01-18-Home-Health.html?DLPage=2&DLEntries=10&DLSort=0&DLSortDir=descending.
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2. Methodology Used To Calculate the Cost of Care
To construct the case-mix weights for the HHGM proposal, the costs
of providing care needed to be determined. A Wage-Weighted Minutes of
Care (WWMC) approach is used in the current payment system based on
data from the BLS. However, we are proposing to adopt a Cost-per-Minute
plus Non-Routine Supplies (CPM + NRS) approach, which uses information
from Medicare Cost Reports (MCR). We used the following data sources
and methodology for calculating these measures of resource use:
BLS Wage Estimates: For the WWMC method of calculating
home health resource use, wage and fringe data was obtained from the
BLS by industry code from the NAICS and occupation code from the
Standard Operation Classification. These data provide nationwide
average wage rates and the average value of fringe benefits per hour of
work for specific occupations.
Home Health Medicare Cost Report Data: All Medicare-
certified HHAs must report their own costs through publicly-available
home health cost reports maintained by the Healthcare Cost Report
Information System (HCRIS). Freestanding HHAs report HHA-specific cost
reports while HHAs that are hospital-based report on the HHA component
of the hospital cost reports. These cost reports enable estimation of
the cost per visit by provider and the estimated NRS cost to charge
ratios. To obtain a more robust estimate of cost, a trimming process
was applied to remove cost reports with missing or questionable data
and extreme values.\23\
---------------------------------------------------------------------------
\23\ The trimming methodology is described in the report
``Analyses in Support of Rebasing & Updating Medicare Home Health
Payment Rates'' (Morefield, Christian, and Goldberg 2013). See
https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/HomeHealthPPS/Downloads/Analyses-in-Support-of-Rebasing-and-Updating-the-Medicare-Home-Health-Payment-Rates-Technical-Report.pdf.
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Home Health Claims Data: Medicare home health claims data
are used in both the WWMC and CPM+NRS methods to obtain minutes of care
by discipline of care.
Wage-Weighted Minutes of Care (WWMC) Approach: Used in the
current payment system, this approach determines resource use for each
episode by multiplying utilization (in terms of the number of minutes
of direct patient care provided by each discipline) by the
corresponding opportunity cost of that care (represented by wage and
fringe benefit rates from the BLS).\24\ Table 18 shows the occupational
titles and corresponding mean hourly wage rates from the BLS. The
employer cost per hour worked shown in the fifth column is calculated
by adding together the mean hourly wage rates and the fringe benefit
rates from the BLS (generally around 37 percent of wages). For home
health disciplines that include multiple occupations (such as skilled
nursing), the opportunity cost is generated by weighting the employer
cost by the proportions of the labor mix.\25\ Otherwise, the
opportunity cost is the same as the employer cost per hour.
---------------------------------------------------------------------------
\24\ Opportunity costs represent the foregone resources from
providing each minute of care versus using the resources for another
purpose (the next best alternative). Generally, opportunity costs
represent more than the monetary costs, but in these analyses, they
are proxied using hourly wage rates.
\25\ Labor mix represents the percentage of employees with a
particular occupational title (as obtained from the BLS) within a
home health discipline.
[[Page 35299]]
Table 18--Occupational Employment and Wages Provided by the Federal Bureau of Labor Statistics
------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
Estimated
National Mean hourly Estimate of employer cost Labor Opportunity
Occupation title employment wage benefits as a per hour mix Home health discipline cost
counts % of wages worked
------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
Registered Nurses.............................. 173,590 $32.94 43.76 $47.36 0.68 Skilled Nursing........................................ $42.21
Licensed Practical and Licensed Vocational 82,860 21.86 43.76 31.43 0.32
Nurses.
Physical Therapists............................ 25,700 46.42 39.91 64.95 0.76 Physical Therapy....................................... 59.18
Physical Therapist Assistants.................. 7,460 30.81 35.75 41.83 0.22
Physical Therapist Aides....................... 500 15.85 35.75 21.52 0.01
Occupational Therapists........................ 10,780 44.17 39.91 61.80 0.82 Occupational Therapy................................... 58.46
Occupational Therapist Assistants.............. 2,220 32.03 35.75 43.48 0.17
Occupational Therapist Aides................... 110 25.20 35.75 34.21 0.01
Speech-Language Pathologists................... 5,340 46.83 39.91 65.52 ...... Speech Therapy......................................... 65.52
Medical and Public Health Social Workers....... 17,270 28.16 39.91 39.40 0.97 Medical Social Service................................. 39.35
Mental Health and Substance Abuse Social 450 26.87 39.91 37.59 0.03
Workers.
Home Health Aides.............................. 385,440 10.93 35.75 14.84 ...... Home Health Aide....................................... 14.84
------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
Source: May 2015 National Industry-Specific Occupational Employment and Wage Estimates NAICS 621600--Home Health Care Services.
For each home health period of care, the number of minutes of care
provided (obtained from the home health claims) is weighted by the
corresponding opportunity cost for each discipline providing the
minutes. The resulting wage-weighted minutes of care are summed for the
30-day period to obtain total costs. Table 19 shows these costs overall
for 30-day periods in CY 2016 (n = 8,642,107). On average, total period
costs were $374.52. The distribution ranged from a 5th percentile value
of $73.87 to a 95th percentile value of $912.10.
Table 19--Distribution of Average Resource Use Using WWMC Approach
[30 day periods]
------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
5th 10th 25th 50th 75th 90th 95th
Statistics Mean N Percentile Percentile Percentile Percentile Percentile Percentile Percentile
------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
Average Resource Use (WWMC)....................................... $374.52 8,642,107 $73.87 $94.97 $158.29 $303.19 $517.063 $749.22 $912.10
------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
In the current HH PPS, all episodes without a LUPA payment receive
payment for NRS, regardless of whether or not the HHA provided NRS
during that episode. NRS payment amounts are determined through a
payment model separately from the one used to construct the episode's
case-mix weight. The current payment system determines NRS payment
using the presence of clinical factors associated with NRS provision
from the OASIS. Two-thirds of episodes do not include provision of NRS,
yet those episodes still receive an NRS payment.
We are proposing to calculate resource use under the HHGM using a
Cost-per-Minute plus Non-Routine Supplies (CPM + NRS) approach. It
determines resource use using information from Medicare cost reports.
Under the proposed HHGM, we would group episodes into their case-mix
[[Page 35300]]
groups taking into account admission source, timing, clinical group,
functional level, and comorbidity adjustment. From there, the average
resource use for each case-mix group dictates the group's case-mix
weight. Resource use is the estimated cost of visits recorded on the
home health claim plus the cost of NRS recorded on the claims. The cost
of NRS is generated by taking NRS charges on claims and converting them
to costs using a NRS cost to charge ratio that is specific to each HHA.
When NRS is factored into the average resource use, NRS costs are
reflected in the average resource use that drives the case-mix weights.
CMS would return $53.03 to the base rate (that is, the NRS conversion
factor). If there is a high amount of NRS cost for all episodes in a
particular group (holding all else equal), the resource use will be
higher relative to the average and the case-mix weight will
correspondingly be higher. Similar to the current system, NRS would
still be paid prospectively under the HHGM, but the HHGM eliminates the
separate case-mix adjustment model for NRS. Incorporating the NRS cost
into the measure of overall resource use (that is, the dependent
variable of the payment model) requires adjusting the NRS charges
submitted on claims based on the NRS cost-to-charge ratio from cost
report data.
The following steps would be used to generate the measure of
resource use under this CPM + NRS approach:
(1) From the cost reports, obtain total costs for each of the six
home health disciplines for each HHA.
(2) From the cost reports, obtain the number of visits by each of
the six home health disciplines for each HHA.
(3) Calculate discipline-specific cost per visit values by dividing
total costs [1] by number of visits [2] for each discipline for each
HHA. For HHAs that did not have a cost report available (or a cost
report that was trimmed from the sample), imputed values were used as
follows:
A state-level mean was used if the HHA was not hospital-
based. The state-level mean was computed using all non-hospital based
HHAs in each state.
An urban nationwide mean was used for all hospital-based
HHAs located in a Core-based Statistical Area (CBSA). The urban nation-
wide mean was computed using all hospital-based HHAs located in any
CBSA.
A rural nationwide mean was used for all hospital-based
HHAs not in a CBSA. The rural nation-wide mean was computed using all
hospital-based HHAs not in a CBSA.
(4) From the home health claims data, obtain the average number of
minutes of care provided by each discipline across all episodes for a
HHA.
(5) From the home health claims data, obtain the average number of
visits provided by each discipline across all episodes for each HHA.
(6) Calculate a ratio of average visits to average minutes by
discipline by dividing average visits provided [5] by average minutes
of care [4] by discipline for each HHA.
(7) Calculate costs per minute by multiplying the HHA's cost per
visit [3] by the ratio of average visits to average minutes [6] by
discipline for each HHA.
(8) Obtain 30-day period costs by multiplying costs per minute [7]
by the total number of minutes of care provided during a 30-day period
by discipline. Then, sum these costs across the disciplines for each
period.
This approach accounts for variation in the length of a visit by
discipline. NRS costs are added to the resource use calculated in [8]
in the following way:
(9) From the cost reports, determine the NRS cost-to-charge ratio
for each HHA. The NRS ratio is trimmed if the value falls in the top or
bottom 1 percent of the distribution across all HHAs from the trimmed
sample. Imputation for missing or trimmed values is done in the same
manner as it was done for cost per visit (see [3] above).
(10) From the home health claims data, obtain NRS charges for each
period.
(11) Obtain NRS costs for each period by multiplying charges from
the home health claims data [10] by the cost-to-charge ratio from the
cost reports [9] for each HHA.
Resource use is then obtained by:
(12) Summing costs from [8] with NRS costs from [11] for each 30-
day period.
Table 20 shows these costs overall for 30-day periods in CY 2015 (n
= 8,642,107). On average, total 30-day period costs are $1,585.48. The
distribution ranges from a 5th percentile value of $300.03 to a 95th
percentile value of $3,908.93.
Table 20--Distribution of Average Resource Use Using CPM + NRS Approach
[30 day periods]
--------------------------------------------------------------------------------------------------------------------------------------------------------
5th 10th 25th 50th 75th 90th 95th
Statistics Mean N Percentile Percentile Percentile Percentile Percentile Percentile Percentile
--------------------------------------------------------------------------------------------------------------------------------------------------------
Average Resource Use (CPM + NRS)... $1,585.48 8,642,107 $300.03 $396.82 $671.96 $1262.65 $2,119.49 $3,135.38 $3,908.93
--------------------------------------------------------------------------------------------------------------------------------------------------------
The distributions and magnitude of the estimates of costs for the
two methods are very different. The differences arise because the CPM +
NRS method incorporates HHA-specific costs that represent the total
costs incurred during a 30-day period (including overhead costs), while
the WWMC method provides an estimate of only the labor costs (wage +
fringe) related to direct patient care from patient visits that are
incurred during a 30-day period. Those costs are not HHA-specific and
do not account for any non-labor costs (such as transportation costs)
or the non-direct patient care labor costs (such as, administration and
general labor costs). Because the costs estimated using the two
approaches are measuring different items, they cannot be directly
compared. However, if the true cost of a 30-day period is correlated
with the labor that is provided during visits, the two approaches
should be highly correlated. The correlation coefficient between the
two approaches to calculating resource use is equal to 0.8016 (n =
8,642,107). Therefore, the relationship in relative costs is similar
between the two methods.
Using cost report data to develop case-mix weights more evenly
weights skilled nursing services and therapy services than the BLS
data. Table 21 shows the ratios between the estimated costs per hour
for each of the home health disciplines compared with skilled nursing
resulting from the CPM +NRS versus WWMC methods. Under the CPM+NRS
methodology, the ratio for physical therapy costs per hour to skilled
nursing is 1.14 compared with 1.40 using the WWMC method.
[[Page 35301]]
Table 21--Relative Values in Costs per Hour by Discipline
[Skilled nursing is base]
--------------------------------------------------------------------------------------------------------------------------------------------------------
Skilled Physical Occupational Speech Medical Home health
Estimated cost per hour nursing therapy therapy therapy social service aide
--------------------------------------------------------------------------------------------------------------------------------------------------------
CPM+NRS................................................. 1.00 1.14 1.16 1.24 1.36 0.41
WWMC.................................................... 1.00 1.40 1.39 1.50 0.95 0.36
--------------------------------------------------------------------------------------------------------------------------------------------------------
We believe that using cost report data to calculate the cost of
home health care better aligns the case-mix weights with the total
relative cost for treating various patients. In addition, using cost
report data allows us to incorporate NRS into the case-mix system,
rather than maintaining a separate payment system. Therefore, we are
proposing to calculate the cost of a 30-day period of home health care
under the HHGM using the cost per minute plus non-routine supplies
(CPM+NRS) approach outlined above. We invite comments on the proposed
methodology for calculating the cost of a 30-day period of care under
the HHGM.
3. Change From 60-Day Billing to 30-Day Billing Under the HHGM
a. 30-Day Unit of Payment
Currently, HHAs are paid for each 60-day episode of home health
care provided. We are proposing 30-day periods of payment for the HHGM.
Through examination of the resources used within a 60-day episode of
care, we identified differences in resources used between the first 30-
day period within a 60-day episode and the second 30-day period within
a 60-day episode. Episodes have more visits, on average, during the
first 30 days compared to the last 30 days (see Tables 22 and 23).
Costs are much higher earlier in the episode and lesser later on,
therefore, dividing a single 60-day episode into two 30-day periods
more accurately apportions payments. This difference in resource use
between the first and second 30-day period within a 60-day episode is
one of the main reasons we are proposing 30-day periods of payment for
the HHGM. Another reason for proposing to change the unit of payment
from 60-days to 30-days is the removal of the therapy visit thresholds
from the case-mix adjustment methodology under the HHGM (the current
system accounts for therapy visit variation through the use of these
thresholds). Without thresholds being used to account for resource use
variation, a shorter period of care is needed to reduce the variation
and improve the accuracy of the case-mix weights generated under the
HHGM. The HHGM's goodness of fit statistics (for example, R-squared)
improve due to reduced resource use variation when a shorter, more
constrained time period is examined. Therefore, the case-mix weights
and proposed move to a 30-day period under the HHGM better approximate
relative resource use. Furthermore, by switching to a 30-day period,
the billing cycle for Medicare home health services would be the same
as for other Medicare health care settings, such as hospices and SNFs,
which currently bill on a monthly basis.
Using two segments of the current 60-day episodes, 30-day periods
were constructed as follows for the development of the HHGM:
A 30-day period comprising days 1-30 of a current 60-day
episode where ``day 1'' is the current 60-day episode's From Date.
A second period comprising days 31 and above of a current
60-day episode. This period would be 30-days in length if the current
episode was 60-days (from the From Date of the episode to the Through
Date of the episode) and some lesser length if the current episode were
fewer than 60-days.
A typical 60-day episode was broken down into two portions: A first
30-day period; and a second 30-day period consisting of the remaining
days. For example, if the current episode was 58 days, then the first
period was 30-days, and the second period was comprised of the
remaining 28 days. Resource utilization was calculated for each 30-day
period based on the discipline visits that occur within each respective
30-day time span. The OASIS information that is applied to the two 30-
day periods (for example, OASIS information) is established by the same
OASIS that is linked to the current 60-day episode.
Table 22 shows the average number of visits by discipline and
resource use estimates during 15-day periods in a 60-day episode, and
shows that visit patterns differ over the course of a 60-day episode.
Across all labor categories there is a decline in visits as the episode
proceeds; in total there are 6.8 visits on average in days 1-15 and 2.6
visits on average in days 46-60 which is a 61.8 percent decline from
the first 15 days of care in a 60-day episode to the last 15 days of
care in a 60-day episode.
Table 23 shows the average number of visits and resource use
estimates by discipline during 15-day periods in a 60-day episode, but
for only those episodes that are first in a sequence of episodes and
last a full 60-days. A sequence of episodes contains episodes where no
more than 60-days elapse from the end of one episode to the start of
the next. Therefore, first episodes are those where the beneficiary has
not had home health in the 60-days prior to the start of the first
episode. Even among this subset of episodes, there is a decline in
average visits by quarter as the episode proceeds.
These results show that there is variation in average resource use
across 60-day episodes. By moving to two 30-day periods within a 60-day
episode (or a single 30-day period if the 60-day episode contains 30 or
fewer days), the HH PPS case mix weights better align with the resource
use patterns across the current 60-day episode. Though the analyses are
based on two 30-day periods in a 60-day episode, we are not proposing a
change in the requirements for completing the comprehensive assessment.
Under the HHGM, the comprehensive assessment would still be required,
as outlined in Sec. 484.55 roughly every 60-days as is required under
the current HH PPS. While we examined resource use in 15-day periods in
a 60-day episode of care, as outlined in Tables 22 and 23, in order to
strike an appropriate balance between increasing payment accuracy and
being cognizant of increasing burden for the home health industry, we
are not proposing to adjust payments every 15 days. We expect that
billing on a 30-day basis should not be completely unfamiliar to HHAs
as HHAs billed as such prior to the implementation of the HH PPS.
[[Page 35302]]
Table 22--Average Visits per 15 Days During a 60-Day Episode
----------------------------------------------------------------------------------------------------------------
Days 1-15 Days 16-30 Days 31-45 Days 46-60
----------------------------------------------------------------------------------------------------------------
Average Daily Resource Use...................... $261.97 $162.44 $107.49 $88.67
Average Skilled Nursing Visits.................. 3.3 2.1 1.6 1.4
Average PT Visits............................... 2.2 1.7 1.0 0.6
Average OT Visits............................... 0.6 0.5 0.3 0.2
Average SLP Visits.............................. 0.1 0.1 0.1 0.0
Average Aide Visits............................. 0.5 0.5 0.4 0.3
Average MSS Visits.............................. 0.1 0.0 0.0 0.0
---------------------------------------------------------------
Average Total Visits........................ 6.8 4.9 3.3 2.6
----------------------------------------------------------------------------------------------------------------
Table 23--Average Visits per 15 Days During a 60-Day Episode
[Only First Episodes in a Sequence of Episodes That Last a Full 60-Days]
----------------------------------------------------------------------------------------------------------------
Days 1-15 Days 16-30 Days 31-45 Days 46-60
----------------------------------------------------------------------------------------------------------------
Average Daily Resource Use...................... $326.78 $217.75 $174.82 $167.69
Average Skilled Nursing Visits.................. 3.9 2.5 2.2 2.3
Average PT Visits............................... 2.6 2.4 1.7 1.4
Average OT Visits............................... 0.8 0.8 0.5 0.4
Average SLP Visits.............................. 0.1 0.2 0.1 0.1
Average Aide Visits............................. 0.5 0.5 0.5 0.4
Average MSS Visits.............................. 0.1 0.1 0.0 0.0
---------------------------------------------------------------
Average Total Visits........................ 8.1 6.4 5.1 4.6
----------------------------------------------------------------------------------------------------------------
Overall, approximately 25 percent of episodes are 30 days or less
in length, and therefore, would produce no second 30-day period under
the HHGM. These episodes (with 30 days or fewer) would convert to only
one 30-day period each; any 60-day episode that is 31 days or more
would produce two 30-day periods: A first period comprising 30 days in
length and then a second period with the remaining days in the 60-day
episode.
Overall, after conversion from the 5,110,629 60-day episodes, there
were 8,642,107 30-day periods:
There were 1,197,740 30-day periods that could potentially
be one-to-one conversions from 60-day episodes that were 30-days or
fewer in length.
Additionally, there were 3,912,889 60-day episodes that
were between 31 and 60-days in length in which two 30-day periods could
be produced. That is, those 60-day episodes could produce up to
7,825,778 30-day periods.
However, from the above episodes (which were used to
create the 30-day periods), there were 381,411 periods that had no
visits included or were considered a LUPA under the HHGM and therefore
were excluded. This is shown in Table 24.
[GRAPHIC] [TIFF OMITTED] TP28JY17.004
[[Page 35303]]
Tables 25 and 26 show the frequency of episode length in days and
estimates of resource use among the original, 60-day episodes and the
corresponding distribution of episode length and resource use estimates
among the simulated 30-day periods. Again, these results show
differences by the length of care. By shortening the unit of time that
CMS pays for within the HH PPS (from 60-day episodes to 30-day
periods), payment would more accurately relate to the variation in
costs seen across episodes and periods of care.
Table 25--Frequency of Length of 60-Day Episodes and Average Resource Use for Episodes of a Certain Length
--------------------------------------------------------------------------------------------------------------------------------------------------------
Standard 25th 75th
Length of episode in days Number of Percent of Average deviation of Percentile of Median Percentile of
episodes episodes resource use resource use resource use resource use resource use
--------------------------------------------------------------------------------------------------------------------------------------------------------
1....................................... 189 0.0 $390.10 $200.87 $348.85 $249.99 $495.03
2....................................... 1,204 0.0 542.52 348.55 453.72 318.34 673.97
3....................................... 3,796 0.1 673.54 418.19 596.78 403.37 846.78
4....................................... 6,051 0.1 751.09 474.35 667.26 447.37 940.19
5....................................... 9,385 0.2 829.89 521.12 730.17 506.40 1,021.84
6....................................... 11,793 0.2 873.31 505.81 785.61 542.35 1,083.79
7....................................... 16,587 0.3 941.17 560.28 838.68 588.23 1,152.63
8....................................... 19,887 0.4 972.38 556.43 875.29 613.68 1,200.88
9....................................... 21,026 0.4 1,024.75 592.64 920.13 641.04 1,272.40
10...................................... 25,724 0.5 1,078.33 623.90 965.80 671.36 1,345.45
11...................................... 29,757 0.6 1,130.59 645.67 1,021.82 708.30 1,418.14
12...................................... 34,725 0.7 1,210.00 661.38 1,094.30 769.13 1,515.79
13...................................... 40,923 0.8 1,264.30 704.44 1,138.39 791.18 1,585.99
14...................................... 49,796 1.0 1,328.34 737.07 1,194.49 829.00 1,667.27
15...................................... 55,035 1.1 1,348.52 744.31 1,210.83 840.75 1,697.71
16...................................... 47,921 0.9 1,386.45 780.24 1,245.80 850.81 1,754.75
17...................................... 48,442 0.9 1,417.42 818.41 1,265.56 865.41 1,796.48
18...................................... 48,802 1.0 1,467.76 851.49 1,311.49 883.41 1,864.69
19...................................... 48,998 1.0 1,538.06 887.62 1,377.47 926.88 1,955.85
20...................................... 53,699 1.1 1,583.97 897.61 1,427.87 954.98 2,014.18
21...................................... 59,071 1.2 1,649.78 939.64 1,482.19 995.89 2,097.03
22...................................... 66,055 1.3 1,678.50 958.48 1,501.48 1,012.61 2,129.05
23...................................... 58,291 1.1 1,743.90 995.17 1,565.59 1,047.09 2,225.60
24...................................... 59,211 1.2 1,797.28 1,026.42 1,605.71 1,085.07 2,292.14
25...................................... 58,481 1.1 1,847.21 1,059.00 1,656.07 1,103.81 2,363.45
26...................................... 58,245 1.1 1,919.71 1,098.44 1,734.72 1,145.08 2,456.08
27...................................... 63,077 1.2 1,976.10 1,115.08 1,799.37 1,188.51 2,534.66
28...................................... 67,228 1.3 2,038.34 1,156.00 1,845.61 1,229.39 2,608.78
29...................................... 73,202 1.4 2,056.06 1,176.25 1,850.93 1,227.68 2,630.45
30...................................... 61,139 1.2 2,131.43 1,219.42 1,925.44 1,266.69 2,748.63
31...................................... 54,481 1.1 2,054.35 1,239.89 1,844.53 1,175.90 2,664.68
32...................................... 48,964 1.0 2,106.57 1,320.10 1,876.72 1,183.96 2,745.18
33...................................... 45,330 0.9 2,162.62 1,347.74 1,940.78 1,206.50 2,828.61
34...................................... 47,568 0.9 2,249.85 1,433.54 2,011.03 1,250.25 2,928.78
35...................................... 50,567 1.0 2,323.60 1,436.69 2,094.77 1,331.92 3,004.86
36...................................... 54,810 1.1 2,355.59 1,436.60 2,133.82 1,372.34 3,017.30
37...................................... 44,844 0.9 2,429.51 1,534.67 2,185.85 1,389.64 3,114.63
38...................................... 43,262 0.8 2,474.67 1,561.76 2,208.94 1,423.02 3,166.09
39...................................... 40,322 0.8 2,521.79 1,611.74 2,258.31 1,429.43 3,244.51
40...................................... 39,193 0.8 2,611.98 1,669.37 2,348.75 1,487.83 3,344.28
41...................................... 42,316 0.8 2,676.84 1,652.00 2,433.86 1,570.54 3,392.77
42...................................... 43,428 0.8 2,717.91 1,713.02 2,433.05 1,570.70 3,486.36
43...................................... 44,866 0.9 2,723.30 1,692.49 2,429.86 1,594.39 3,475.35
44...................................... 36,714 0.7 2,784.62 1,751.30 2,489.70 1,608.51 3,560.94
45...................................... 34,973 0.7 2,825.00 1,800.40 2,498.55 1,617.88 3,621.28
46...................................... 32,604 0.6 2,843.98 1,881.88 2,516.21 1,592.33 3,649.60
47...................................... 31,457 0.6 2,901.93 1,914.85 2,568.74 1,637.72 3,722.24
48...................................... 33,588 0.7 2,967.28 1,890.38 2,637.52 1,692.59 3,802.17
49...................................... 35,758 0.7 2,985.66 1,881.80 2,661.29 1,728.52 3,810.65
50...................................... 38,505 0.8 3,006.91 1,948.18 2,656.75 1,714.03 3,846.70
51...................................... 34,081 0.7 3,069.10 1,987.99 2,711.23 1,754.01 3,911.27
52...................................... 35,200 0.7 3,044.64 1,968.48 2,699.22 1,730.90 3,902.26
53...................................... 37,353 0.7 3,041.44 2,031.19 2,656.68 1,663.20 3,911.30
54...................................... 42,039 0.8 3,050.40 1,995.63 2,691.98 1,681.25 3,935.63
55...................................... 57,053 1.1 3,031.82 1,993.77 2,686.03 1,655.26 3,929.67
56...................................... 133,103 2.6 2,739.54 1,902.85 2,402.36 1,337.71 3,653.27
57...................................... 134,831 2.6 2,910.43 1,957.02 2,568.83 1,506.89 3,835.12
58...................................... 124,027 2.4 2,979.59 2,032.32 2,616.53 1,506.76 3,934.52
59...................................... 131,881 2.6 3,056.59 2,106.81 2,671.40 1,531.18 4,042.43
60...................................... 2,339,771 45.8 3,167.25 2,582.35 2,584.60 1,381.40 4,146.38
---------------------------------------------------------------------------------------------------------------
Total............................... 5,110,629 100.0 2,668.61 2,167.89 2,126.24 1,223.35 3,471.50
--------------------------------------------------------------------------------------------------------------------------------------------------------
[[Page 35304]]
Table 26A--Frequency of Length of 30-Day Periods and Average Resource Use for Episodes of a Certain Length
--------------------------------------------------------------------------------------------------------------------------------------------------------
Standard 25th 75th
Length of period in days Number of Percent of Average deviation of Percentile of Median Percentile of
periods periods resource use resource use resource use resource use resource use
--------------------------------------------------------------------------------------------------------------------------------------------------------
1....................................... 3,524 0.0 $324.24 $263.35 $280.90 $211.49 $370.04
2....................................... 8,369 0.1 388.82 369.29 315.71 239.78 433.16
3....................................... 15,906 0.2 457.10 366.59 362.89 264.75 533.87
4....................................... 23,219 0.3 505.38 421.31 389.49 278.90 600.01
5....................................... 32,751 0.4 548.40 454.32 422.29 293.29 661.01
6....................................... 41,608 0.5 574.07 450.58 448.54 304.63 704.08
7....................................... 43,863 0.5 659.05 534.21 512.49 332.18 825.53
8....................................... 51,527 0.6 701.40 524.40 566.85 362.61 892.13
9....................................... 52,384 0.6 750.57 575.81 606.90 383.81 957.98
10...................................... 57,437 0.7 821.25 612.49 679.85 416.34 1,056.92
11...................................... 64,917 0.8 871.27 626.24 738.18 452.60 1,118.16
12...................................... 71,310 0.8 937.62 667.37 791.38 482.71 1,220.16
13...................................... 79,309 0.9 990.00 697.39 832.05 514.47 1,288.99
14...................................... 81,603 0.9 1,097.23 740.41 943.52 584.53 1,432.03
15...................................... 86,340 1.0 1,154.17 754.00 999.52 634.63 1,495.77
16...................................... 77,411 0.9 1,180.96 793.23 1,017.08 634.79 1,538.93
17...................................... 77,257 0.9 1,217.06 828.31 1,044.18 656.03 1,579.78
18...................................... 79,981 0.9 1,251.95 846.54 1,070.55 665.44 1,632.13
19...................................... 82,356 1.0 1,296.30 881.05 1,109.47 687.23 1,690.54
20...................................... 89,669 1.0 1,336.50 899.78 1,144.26 709.84 1,748.36
21...................................... 91,247 1.1 1,426.72 942.61 1,230.61 773.65 1,859.45
22...................................... 99,530 1.2 1,472.50 956.21 1,274.66 809.29 1,910.76
23...................................... 94,124 1.1 1,494.61 993.71 1,285.28 793.44 1,959.20
24...................................... 99,779 1.2 1,513.58 1,018.60 1,302.00 791.75 1,989.40
25...................................... 113,978 1.3 1,486.39 1,035.65 1,260.53 749.62 1,964.15
26...................................... 188,106 2.2 1,282.22 1,006.44 1,027.40 550.41 1,727.53
27...................................... 195,398 2.3 1,372.37 1,038.05 1,126.05 617.79 1,844.29
28...................................... 189,012 2.2 1,465.50 1,086.75 1,219.26 668.85 1,967.27
29...................................... 202,819 2.3 1,541.39 1,118.11 1,295.04 727.83 2,060.18
30...................................... 6,247,373 72.3 1,719.92 1,375.02 1,396.74 728.43 2,305.59
---------------------------------------------------------------------------------------------------------------
Total............................... 8,642,107 100.0 1,585.48 1,289.23 1,262.65 671.96 2,119.49
--------------------------------------------------------------------------------------------------------------------------------------------------------
The 60-day episode unit of payment was originally implemented on
October 1, 2000, because most episodes in the HHA per-episode PPS
demonstration, which was used to inform the development of the HH PPS,
ended in 60 days or less, the OASIS data would be captured on a 60-day
cycle, and Medicare plan of care/certification requirements continue to
be bimonthly (64 FR 58143). In the FY 2001 HH PPS proposed rule, we
noted that about 60 percent of episodes paid under the HH PPS were
completed within one 60-day episode and 73 percent within two 60-day
episodes. In the FY 2001 HH PPS final rule, we noted that we would
continue to monitor the appropriateness of the 60-day unit of payment,
and would consider modifying our approach to the episode definition in
subsequent years of PPS, if warranted (65 FR 41136).
In CY 2016, 73 percent of episodes were completed within one 60-day
episode and 86 percent within two 60-day episodes. We currently observe
wide variation in the length of care in the current HH PPS. Overall,
the average length of home health care was approximately 46 days, but
roughly a quarter of all 60-day episodes lasted 30 days or less. For
example, those episodes that had a hospital stay in the seven days
prior to the start of the episode where the Diagnosis Related Group
(DRG) was either 469 or 470 (major joint replacement or reattachment of
lower extremity) had an average length equal to 23.7 days. As noted
above, there is a decline in visits as the episode proceeds with a 61.8
percent decline from the first 15 days of care in a 60-day episode to
the last 15 days of care in a 60-day episode.
The wide variation in resource use and trends toward shorter
episodes of care, the difference in resources between the first and
second 30-day period within a 60-day episode, and the removal of the
therapy visit thresholds from the case-mix adjustment methodology
(which currently account for variation in resource use, but create
adverse incentives as outlined in section II.D of this proposed rule)
result in less accurate case-mix weights. When a shorter, more
constrained time period is used for payment, the HHGM's goodness of fit
statistics (for example, R-squared) improve due to reduced resource use
variation. Accordingly, the case-mix weights under the HHGM better
approximate relative resource use. Therefore, we are proposing to
change the unit of payment under section 1895(b)(2) of the Act from a
60-day episode of care to 30-day periods of care. Section 1895(b)(2) of
the Act requires the Secretary to consider potential changes in the mix
of services provided within that unit and their cost. Our analysis
shows evidence of a change in the mix of services under a 60-day
episode of care, as outlined above and in section II.D of this proposed
rule. Therefore, to better account for changes in the mix of services
over time; to ensure that the unit of payment reflects an appropriate
number, type, and duration of visits provided within a unit of payment;
and to provide continued access to quality services, we are proposing
to change the unit of payment from a 60-day episode of care to a 30-day
period of care and to implement case-mix adjustment methodology
refinements, outlined in sections III.E.1 through III.E.12 of this
proposed rule.
[[Page 35305]]
b. National, Standardized 30-Day Payment Amount
We note that we propose to implement the HHGM for 30-day periods of
care beginning on or after January 1, 2019.\26\ As a result, we would
calculate a proposed national, standardized 30-day payment amount in
the CY 2019 HH PPS proposed rule. In calculating a national,
standardized 30-day payment amount for CY 2019, we propose to start
with the CY 2019 national, standardized 60-day episode payment amount
reflecting the HHA market basket update as specified in section
1895(b)(3)(B) of the Act, add back in the CY 2019 non-routine medical
supply (NRS) conversion factor amount reflecting the HHA market basket
update as specified in section 1895(b)(3)(B) of the Act, and then
divide the sum by two.
---------------------------------------------------------------------------
\26\ 60-day episodes of care that begin on or before December
31, 2018 and end on or after January 1, 2019, will be paid using the
current case-mix adjustment methodology (153-group system) and a CY
2019 national, standardized 60-day episode payment amount and/or CY
2019 national per-visit amounts.
---------------------------------------------------------------------------
If we had proposed to implement the HHGM in CY 2018, we would have
calculated a proposed 30-day payment amount for CY 2018 by starting
with the CY 2018 proposed national, standardized 60-day episode payment
amount of $3,038.43, adding back in the CY 2018 proposed NRS conversion
factor amount of $53.03, and dividing the sum by two to produce a 30-
day payment amount of $1,545.73. However, we reiterate that we propose
to implement the HHGM for 30-day periods of care beginning on or after
January 1, 2019; so we propose to calculate a national, standardized
30-day payment amount for CY 2019 using the CY 2019 60-day episode
payment amount, adding back in the CY 2019 NRS conversion factor and
dividing the sum by two to produce a 30-day payment amount. Finally, we
note that the calculation proposed above would only be used to
calculate a national, standardized 30-day payment amount for CY 2019.
To calculate a national, standardized 30-day payment amount for CY 2020
and subsequent years, we would update the national, standardized 30-day
payment amount from the immediate preceding year by the home health
payment update percentage required by the statute, as described in
section III.C.1 of this rule.
In determining the 30-day payment amount, we evaluated whether
starting with the national, standardized 60-day episode payment amount,
adding back in the NRS conversion factor amount and dividing the sum by
two was an appropriate estimate of the cost of a 30-day period of care.
Section 1895(b)(3) of the Act provides a methodology for determining an
initial payment amount for the PPS and for calculating annual
increases. As noted in this proposed rule, the Act at section
1895(b)(2) gives the Secretary the discretion to determine the ``unit
of payment'' (also referred to in the statute as a ``unit of service'')
on which a standard prospective payment amount would be based. Since we
are proposing to change the unit of payment, we believe it is necessary
to calculate a 30-day payment amount that would accurately reflect what
a 30-day payment would be had we chosen to use a 30-day rather than a
60-day unit of payment when we first implemented the PPS.
To do this, we calculated an estimated 30-day payment amount by
taking the average number of visits per discipline per 30-day period of
care in CY 2016 multiplied by the FY 2001 per-visit amounts (including
average NRS costs per visit) initially established under the HH PPS
based on the most recent audited cost report data available to the
Secretary in accordance with section 1895(b)(3)(A)(I) of the Act, as
adjusted for inflation and productivity. The FY 2001 per-visit amounts
were adjusted for inflation by the actual HHA market basket updates
(reflecting historical data from FY 2002 to CY 2016), the regulatory
HHA market basket updates for CY 2017 (which is based on the CY 2017
forecasted data at the time of CY 2017 rulemaking (81 FR 76714)) and CY
2018 (which is based on the CY 2018 forecasted data in this CY 2018
proposed rule), and for productivity (using Economy-wide Multifactor
Productivity as specified in section 1895(b)(3)(B)(vi) to the Act and
described in section 1886(b)(3)(B)(xi)(II) of the Act) beginning in
2015, as reflected in Table 26B.
Table 26B--HHA Market Basket Updates and Productivity Adjustments, FY 2002 Through CY 2018
--------------------------------------------------------------------------------------------------------------------------------------------------------
FY/CY
FY 02 FY 03 04* CY 05 CY 06 CY 07 CY 08 CY 09 CY 10
-------------------------------------------------------------------------------------------------------------------------------------------------
Market Basket Update (Historical Data FY02 to CY16, forecast 3.4 3.2 4.0 3.1 3.1 3.5 3.2 1.7 1.7
CY17 and CY18).................................................
....... ....... ....... ....... ....... ....... ....... ....... .......
CY 11 CY 12 CY 13 CY 14 CY 15 CY 16 CY 17 CY18 .......
Market Basket Update (Historical FY02 to CY16, forecast CY 17 2.0 1.7 1.6 1.6 1.6 2.0 2.8 2.7 .......
and CY 18).....................................................
Multi-Factor Productivity Adjustment (historical CY15, ....... ....... ....... ....... 0.4 0.6 0.3 0.5 .......
preliminary historical CY16, forecast CY17 and CY18)...........
--------------------------------------------------------------------------------------------------------------------------------------------------------
As shown in Table 28, using the FY 2001 per-visit amounts initially
established under the HH PPS results in an estimated 30-day payment
amount of $1,494.64. This value is less than, but similar to half the
sum of the proposed CY 2018 national, standardized 60-day episode
payment amount and proposed CY 2018 NRS conversion factor amount
($1,545.73).
We also calculated an estimated 30-day payment amount by taking the
average number of visits per discipline per 30-day period of care in CY
2016 multiplied by the FY 2015 costs-per-visit, per discipline, based
on the most recent cost report data available at the time of CY 2018 HH
PPS rulemaking (as outlined in Table 2 in section III.A of this
proposed rule) and further adjusted to include average NRS costs per
visit, for outliers in accordance with section 1895(b)(3)(C) of the
Act, and for inflation and productivity. As shown in Table 29, using
2015 costs-per-visit, per discipline, based on the most recent cost
report data available at the time of CY 2018 HH PPS rulemaking, results
in an estimated 30-day payment amount of $1,485.11. This value is also
less than, but similar to half the sum of the proposed CY 2018
national, standardized 60-day episode payment amount and proposed CY
2018 NRS conversion factor amount ($1,545.73).
[[Page 35306]]
Table 27--Average Visits Per Discipline for 30-Day Periods of Care, CY
2016
------------------------------------------------------------------------
CY 2016
Average number
Discipline of visits in
30-day period
------------------------------------------------------------------------
Skilled Nursing......................................... 5.0
Physical Therapy........................................ 3.3
Occupational Therapy.................................... 0.9
Speech-Language Pathology............................... 0.2
Medical Social Services................................. 0.1
Home Health Aides....................................... 1.0
---------------
Total............................................... 10.5
------------------------------------------------------------------------
Source: CY 2016 claims data (as of March 17, 2017), excluding 30-day
periods of care with no visits and those classified as LUPAs as
outlined in section III.E.9 of this proposed rule.
Table 28--Estimated 30-Day Payment Amount in CY 2018 (Using FY 2001 HH PPS Per-Visit Amounts, Per Discipline,
Adjusted for Inflation and for Productivity Beginning in 2015)
----------------------------------------------------------------------------------------------------------------
FY 2001 per-
FY 2001 per- visit amounts CY 2016
Discipline visit amounts trended average number CY 2018 30-day
\1\ forward to of visits in period costs
2018 30-day period
----------------------------------------------------------------------------------------------------------------
Skilled Nursing................................. $95.34 $143.03 5.0 $715.15
Physical Therapy................................ 104.27 156.43 3.3 516.22
Occupational Therapy............................ 104.97 157.48 0.9 141.73
Speech-Language Pathology....................... 113.32 170.01 0.2 34.00
Medical Social Services......................... 152.95 229.47 0.1 22.95
Home Health Aides............................... 43.05 64.59 1.0 64.59
---------------------------------------------------------------
Total....................................... .............. .............. 10.5 1,494.64
----------------------------------------------------------------------------------------------------------------
\1\ The FY 2001 per-visit amounts can be found in 65 FR 41187 through 41188 (Table 6).
Note(s): When the HH PPS was established on October 1, 2000, the original per-visit payment amounts for each
discipline included a one-time adjustment of $0.21 to reflect the costs associated with OASIS assessment
schedule refinements (65 FR 41187). In addition, the resulting per-visit rates were then divided by 1.05 to
account for the estimated percentage of outlier payments, a calculation further refined in the CY 2008 HH PPS
final rule (72 FR 49868) by multiplying by 1.05 and 0.95. The FY 2001 per-visit amounts in the text reflect
removing the $0.21 from the FY 2001 per-visit amounts and include the effects of the CY 2008 outlier
calculation refinement.
Table 29--Estimated 30-Day Payment Amount in CY 2018 (Using FY 2015 Average Costs-Per-Visit, Per Discipline, Adjusted for Inflation and for Productivity
Beginning in 2015)
--------------------------------------------------------------------------------------------------------------------------------------------------------
FY 2015
FY 2015 FY 2015 average costs- CY 2016
FY 2015 average NRS average NRS per-visit plus Outlier average number CY 2018 30-day
Discipline average costs- costs-per- costs-per- NRS trended adjustment of visits in period costs
per-visit visit \1\ visit plus NRS forward to factor 30-day period
2018
--------------------------------------------------------------------------------------------------------------------------------------------------------
Skilled Nursing......................... $132.48 +$3.36 $135.84 $144.29 x 0.95 5.0 $685.38
Physical Therapy........................ 156.32 3.36 159.68 169.61 x 0.95 3.3 531.73
Occupational Therapy.................... 154.64 3.36 158.00 167.83 x 0.95 0.9 143.50
Speech-Language Pathology............... 170.96 3.36 174.32 185.17 x 0.95 0.2 35.18
Medical Social Services................. 220.07 3.36 223.43 237.33 x 0.95 0.1 22.55
Home Health Aides....................... 62.80 3.36 66.16 70.28 x 0.95 1.0 66.77
---------------------------------------------------------------------------------------------------------------
Total............................... .............. .............. .............. .............. .............. 10.5 1,485.11
--------------------------------------------------------------------------------------------------------------------------------------------------------
\1\ Of the 8,032 FY 2015 HHA cost reports used for the analysis presented in Table 2 in section III.A of this proposed rule, NRS costs totaled
$301,207,702. For those same 8,032 HHAs, visits (all visits, all episode types) where the claim through date fell on or between the FY start end date
of the agency's cost report totaled 89,726,272. $301,207,702 divided by 89,726,272 = $3.36 per visit.
We believe our proposal to start with the national, standardized
60-day episode payment amount, add back in NRS conversion factor
amount, and then divide the sum by two is a reasonable estimate of the
cost of a 30-day period of care. We propose to implement the change in
the unit of payment from 60-day episodes of care to 30-day periods of
care in a non-budget neutral manner. We note that in its March 2017
Report to Congress, MedPAC highlighted that home health payments have
consistently and substantially exceeded costs because agencies are able
to reduce the number of visits provided and cost growth is generally
lower than the annual payment updates for home health care.\27\ MedPAC
recommended a 5 percent reduction in the base rate for 2018 and a 2-
year rebasing beginning in 2019.\28\ We invite comments on the proposed
calculations for determining the 30-day payment amount, including our
rationale for proposing to
[[Page 35307]]
implement the HHGM in a non-budget neutral manner.
---------------------------------------------------------------------------
\27\ Medicare Payment Advisory Commission (MedPAC). ``Home
Health Care Services.'' Report to Congress: Medicare Payment Policy.
Washington, DC, March 2017. P. 232. Accessed on July 16, 2017 at:
https://www.medpac.gov/docs/default-source/reports/mar17_medpac_ch9.pdf?sfvrsn=0.
\28\ Ibid.
---------------------------------------------------------------------------
We are further proposing to implement the HHGM in a fully non-
budget neutral manner beginning in CY 2019 or alternatively to use a
phased approach to implementation. We acknowledge that implementing the
HHGM in a partially budget-neutral manner could lessen the economic
impact for HHAs in transitioning to the HHGM. Therefore, we considered
potential alternative implementation approaches for the HHGM,
including, but not limited to, a partially budget-neutral approach with
a phase-out period. Specifically, for the phased approach, we propose
to apply a HHGM partial budget neutrality adjustment factor in CY 2019
that would reduce the estimated impact of the HHGM from an estimated -
4.3 percent to -2.2 percent in the initial year of implementation with
the removal of the HHGM partial budget neutrality adjustment factor in
CY 2020. We invite comments on whether to implement the HHGM in a fully
non-budget neutral manner beginning in CY 2019; whether to
alternatively implement the HHGM in CY 2019 with a HHGM partial budget
neutrality adjustment factor applied and then subsequently removed in
CY 2020; or whether a HHGM partial budget neutrality adjustment factor
should be applied and then phased-out over a longer period of time.
c. Split Percentage Payment Approach for 30-Day Periods of Care
In the current HH PPS there is a split percentage payment approach
to the 60-day episode. The first bill, a Request for Anticipated
Payment (RAP), is submitted at the beginning of the episode. The
second, final bill is submitted at the end of the 60-day episode of
care. An initial percentage payment of 60 percent of the anticipated
final claim payment amount is paid at the beginning of the episode and
a final percent payment of 40 percent is paid at the end of the
episode. For all subsequent episodes for beneficiaries who receive
continuous home health care, the episodes are paid at a 50/50
percentage payment split. A new initial and final bill must be
submitted for each 60-day episode period. HHAs are encouraged to submit
the RAP as soon as possible after care begins to assure being
established as the primary HHA for the beneficiary and so that the
claims processing system is alerted that a beneficiary is under a HH
episode of care to enforce the consolidating billing edits required by
law.
We are not proposing a change to the split percentage payment
approach in conjunction with proposing to change the unit of payment
from a 60-day episode to a 30-day period of care. Under the proposed
HHGM, we propose that the initial payment for initial 30-day periods
would be paid at 60 percent of the case-mix and wage-adjusted 30-day
payment rate. The residual final payment for initial 30-day periods
would be paid at 40 percent of the case-mix and wage-adjusted 30-day
payment rate. We propose the initial payment for subsequent 30-day
periods would be paid at 50 percent of the case-mix and wage-adjusted
30-day payment rate. The residual final payment for subsequent 30-day
periods would be paid at 50 percent of the case-mix and wage-adjusted
30-day payment rate.
However, we note the length of time HHAs currently take to submit
the RAP indicates that the RAP payment might not be necessary for the
majority of HHAs to maintain an adequate cash flow (see Table 30).
Approximately 5 percent of RAPs (95th percentile) are not submitted
until the end of an episode of care and the median length of days for
RAP submission is 12 days from the start of the episode. In addition,
eliminating RAP payments would address existing program integrity
vulnerabilities. For example, $1.8 billion in RAP payments (July 1,
2015 through July 31, 2016) were auto-cancelled, and of that amount, a
final claim was never submitted for $321 million worth of RAP
payments.\29\
---------------------------------------------------------------------------
\29\ A RAP is auto-cancelled and recouped on the next
disbursement if the final claim is not received within 4 months of
the start of care or within 2 months of when the RAP was paid
(whichever is greater).
Table 30--Number of Days From the Start of Care to Initial RAP
Submission
------------------------------------------------------------------------
Number of days
from the start
Percentile of care to
initial RAP
submission
------------------------------------------------------------------------
1....................................................... 1
10...................................................... 5
25...................................................... 8
50...................................................... 12
75...................................................... 21
90...................................................... 36
95...................................................... 57
99...................................................... 169
------------------------------------------------------------------------
Source: Analysis of CWF data from July 1, 2015 through July 31, 2016 and
HIGLAS payments and recoupments.
We are soliciting comments as to whether the split payment approach
would still be needed for HHAs to maintain adequate cash flow if the
unit of payment changes from 60-day episodes to 30-day periods of care
under our proposal. In addition, we are soliciting comments on ways to
phase-out the split percentage payment approach in the future if the
proposed HHGM is finalized with the split percentage payment approach
being initially maintained. Specifically, we are soliciting comments on
reducing the percentage of the upfront payment over a period of time.
We believe that payment based on 30-day periods would reduce, if not
eliminate, the need for these partial, up-front payments that occur in
the current payment system. Home health agencies would bill on a
monthly basis, similar to hospices and SNFs, and thus receive final
payment sooner.
If in the future the split percentage approach was eliminated, we
are also soliciting comments on the need for HHAs to submit a notice of
admission within 5 days of the start of care to assure being
established as the primary HHA for the beneficiary and so that the
claims processing system is alerted that a beneficiary is under a HH
period of care to enforce the consolidating billing edits required by
law.
We invite comments on the proposed change in the unit of payment
from a 60-day episode of care to a 30-day period of care under the
HHGM; the calculation of the national, standardized 30-day payment
amount, initially maintaining the split percentage payment approach and
applying such policy to 30-day periods of care; and the associated
regulations text changes outlined in section III.E.13. of this proposed
rule. We are also soliciting comments on ways the split percentage
payment approach could be phased-out and whether to implement a notice
of admission process if the split percentage payment approach is
eliminated in the future.
4. Episode Timing Categories
To advance the goals of better aligning payment with patient needs,
as well as addressing payment incentives and vulnerabilities within the
current system, we investigated the impact of episode timing on home
health resource use. In the current payment system, 60-day episodes are
classified as ``early'' if they are the first or second in a sequence
of episodes and ``late'' if they are the third or later in the
sequence. Episodes are defined as being in the same sequence if there
are no more than 60 days between the end of one episode and the start
of the next. In the development of the proposed HHGM, we sought to
evaluate whether payments to providers appropriately reflect the
varying resource needs of
[[Page 35308]]
home health beneficiaries during various portions of the home health
stay, accounting for contrasting patient characteristics.
We endeavored to evaluate whether beneficiaries in their first 30-
day period of care have different needs and patterns of resource use
than those in later 30-day periods, thus possibly resulting in the
potential need for differentiated payment amounts. We reviewed related
research, held technical and clinical expert panels, and performed our
own investigative analyses. In particular, we were interested in
whether home health patients utilize more resources at the beginning of
home health than in later periods of the home health stay, and, if so,
does the current payment structure sufficiently account for this
elevated need. In a review of research related to episode timing,
studies show that more frequent skilled visits in the first few weeks
of a home health stay can prove beneficial for certain diagnoses by
reducing the likelihood of readmission to an institutional setting and
easing the transition from hospital to home, which can be challenging
for patients.
The Visiting Nurse Associations of America defines ``frontloading''
as the practice of providing an increase in intensity of visits during
the first two to three weeks of the home health care episode for
patients that have been determined to be at high risk for
hospitalization.\30\ A 2014 literature review titled ``Frontloading and
Intensity of Skilled Home Health Visits: A State of the Science'' found
that Medicare patients benefited from an intensified level of care
through a ``frontloading'' approach, which reduced the need for re-
hospitalization among skilled home health patients, and especially for
those with heart failure.\31\ For the purposes of this particular
study, frontloading was defined as providing 60 percent of planned
visits within the first 2 weeks of the home health episode of care.
Furthermore, frontloading was also found by the Briggs[supreg] National
Quality Improvement/Hospitalization Reduction Study,\32\ to be one of
15 best practices routinely employed by 64 percent of the HHAs who were
most successful at reducing hospitalizations. Similarly, in an article
titled ``The Effect of Frontloading Visits on Patient Outcomes,'' \33\
the authors assessed the impact of frontloading on patients with
insulin-dependent diabetes and with heart failure. In their research,
the authors found that frontloading was effective for patients with
heart failure, decreasing re-hospitalization by more than half (39.4
percent vs. 16 percent), with fewer visits overall (15.5 vs. 9.5) and
equal clinical outcomes and patient satisfaction. These improvements in
overall outcomes were presumably due to the timing of the services,
where more visits were provided in the beginning portion of the
episode, even when fewer visits were provided overall. However, we note
that there was no significant impact for those patients with diabetes.
No specific effect for patients with mental health or behavioral health
conditions was noted. Given the potential positive outcomes of the
practice of frontloading, specifically for those beneficiaries with
heart disease, we expect that HHAs would provide more frequent skilled
services in the beginning portion of a home health stay to educate
patients in medication management, coordinate the instruction of both
the patient and family, and support patients in navigating their
clinical situation, especially in cases of heart disease. The first and
fourth reported top primary reasons for home health care in CY 2016
were hypertension and heart failure, respectively, and we therefore
believe an opportunity exists for HHAs to improve the outcomes for
these high-volume home health beneficiaries by providing more resources
in the early period of a home health stay.
---------------------------------------------------------------------------
\30\ Care-Initiation-Frontloading. (n.d.). Retrieved March 20,
2017, from https://vnaablueprint.org/Care-Initiation-Frontloading.html.
\31\ O'Connor, M., Bowles, K.H., Feldman, P. H., Pierre, M. S.,
Jarr[iacute]n, O., Shah, S., & Murtaugh, C. M. (2014). Frontloading
and Intensity of Skilled Home Health Visits: A State of the Science.
Retrieved March 02, 2017, from https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4532304/.
\32\ Briggs National Quality Improvement/Hospitalization * * *
(n.d.). Retrieved March 2, 2017, from https://www.briggscorp.com/ACHstrategies/BriggsStudy.pdf.
\33\ Rogers, J., Perlic, M., & Madigan, E. A. (2007). The Effect
of Frontloading Visits on Patient Outcomes. Home Healthcare Nurse:
The Journal for the Home Care and Hospice Professional, 25(2), 103-
109. doi:10.1097/00004045-200702000-00011; https://www.ncbi.nlm.nih.gov/pubmed/17285038.
---------------------------------------------------------------------------
For many patients admitted to home health, the transition from
hospital or other institutional settings back to the home environment
can be very challenging and lead to adverse effects for the
beneficiary, such as medication errors, harmful drug events, and
additional complications. The provision of intensified home health
services early in a home health stay can potentially help to mitigate
any negative events that could result from this time of transition from
the institutional setting to the home. As such, we would expect that
beneficiaries would require more resources, particularly from skilled
disciplines providing teaching and medication management, during the
first 30 days of a home health admission.
As described in section III.E.3 of this proposed rule, analysis of
home health data demonstrates that HHAs provide more services in the
first 30-day period of home health than in later periods of care. The
differences in the resource utilization during home health episodes are
presented in Table 22, which shows the average resource use of home
health episodes divided into 15-day segments. The first two 15-day
periods in a home health episode have significantly higher average
resource use at $261.97 and $162.44, respectively, as compared with the
third and fourth 15-day segments in a 60-day period, at $107.49 and
$88.67, respectively. Additionally, the average number of visits by the
six disciplines is also significantly higher in the first two 15-day
segments, at 6.8 and 4.9 visits per segment, respectively as compared
to the third and fourth 15-day segments of a 60-day episode, at 3.3 and
2.6, respectively.
Further analysis of home health data demonstrates that under the
current payment system, when analyzed by 30-day periods, HHAs provide
more resources in the first 30-day period of home health (``early'')
than in later periods of care. The differences in the average resource
use during early and late home health episodes when divided into 30-day
periods are presented in Table 28, and shows the first 30-day periods
in a home health sequence have significantly higher average resource
use at $2,102.29 as compared with subsequent 30-day periods.
Specifically, the later 30-day periods showed an average resource use
of $1,348.18, a difference of more than $700 or a 36 percent decrease.
Table 31 also shows a significant difference between the early and late
episode median values of resource use. The median for the first 30-day
period is $1,848.12, while the median for subsequent 30-day periods is
$987.54, a difference of more than $850 or an approximately 47 percent
decrease.
[[Page 35309]]
Table 31--Average Resource Use by Timing (30 Day Periods)
--------------------------------------------------------------------------------------------------------------------------------------------------------
Standard 25th 75th
Average Number of Percent of deviation of percentile of Median percentile of
Timing resource use episodes episodes (%) resource use resource use resource use resource use
($) ($) ($) ($) ($)
--------------------------------------------------------------------------------------------------------------------------------------------------------
Early Episodes.......................... 2,102.29 2,719,495 31.47 1,265.68 1,213.51 1,848.12 2,681.90
Late Episodes........................... 1,348.18 5,922,612 68.53 1,229.14 537.85 987.54 1,760.20
Total............................... 1,585.48 8,642,107 100.00 1,289.23 671.96 1,262.65 2,119.49
--------------------------------------------------------------------------------------------------------------------------------------------------------
There is significant difference in the resource utilization between
early and late 30-day periods as demonstrated in Table 31. Moreover,
the predictive power of the HHGM in terms of estimating resource
utilization improved when separating episodes into 30-day periods
rather than 60-day periods (that is, the first and second 30-day
periods). We believe that an HHGM that accounts for the demonstrated
increase in resource utilization in the first 30-day period better
captures the variations in resource utilization and further promotes
the goal of payment accuracy within the HH PPS. We are proposing to
classify the 30-day periods under the proposed HHGM as ``early'' or
``late'' depending on when they occur within a sequence of 30-day
periods. For the purposes of defining ``early'' and ``late'' periods
for the proposed HHGM, we are proposing that only the first 30-day
period in a sequence of periods be defined as ``early'' and all other
subsequent 30-day periods would be considered ``late''. Additionally,
we are proposing that the definition of a ``home health sequence'' (as
currently described in Sec. 484.230) will remain unchanged relative to
the current system, that is, 30-day periods are considered to be in the
same sequence as long as no more than 60 days pass between the end of
one period and the start of the next, which is consistent with the
definition of a ``home health spell of illness'' described at section
1861(tt)(2) of the Act. We note that because section 1861(tt)(2) of the
Act is a definition related to eligibility for home health services as
described at section 1812(a)(3) of the Act, it does not affect or
restrict our ability to propose a 30-day prospective payment period.
To identify the first 30-day period within a sequence, the Medicare
claims processing system would verify that the claim ``From date'' and
``Admission date'' match. If this condition were to be met, our systems
would send the ``early'' indicator to the HH Grouper for the 30-day
period of care. When the claim is received by CMS's Common Working
File, the system would look back 60 days to ensure there is not a
prior, related episode. If not, the claim would continue to be paid as
``early.'' If another related episode were to be identified, that is an
earlier 30-day period in the sequence, the claim would be returned to
the shared systems for subsequent regrouping and re-pricing. Those
periods that are not the first 30-day period in a sequence of adjacent
periods, separated by no more than a 60 day gap, would be categorized
as ``late'' periods and placed in corresponding HHGM categories.
We invite public comments on the timing categories in the proposed
HHGM and the associated regulations text changes outlined in section
III.E.13 of this proposed rule.
5. Admission Source Category
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)
implementing the HH PPS. In that final rule, we discussed and finalized
the use of a methodology that included variables identifying pre-
admission location (that is, whether certain inpatient and other stays
occurred in the 14-day period immediately preceding the home health
episode) as part of our case-mix adjustment methodology. We stated that
not only were pre-admission inpatient stays a traditional indication of
need in clinical practice, but also that such variables were useful
correlates of resource cost in our evaluation of the home health case-
mix data (65 FR 41146). This pre-admission information was submitted by
HHAs via OASIS assessments.
In the CY 2008 HH PPS final rule, we removed elements from the
case-mix adjustment methodology that were based upon the source of
admission (72 FR 49766). In the CY 2008 HH PPS proposed and final
rules, we assessed variables for policy and payment appropriateness and
ultimately decided to remove the variable that had been used to
identify the patient's pre-admission location from the case-mix
adjustment methodology (72 FR 25361 and 72 FR 49766, respectively).
This decision was based, in part, upon concerns that some agencies were
encountering challenges in obtaining concrete information regarding the
patient's preadmission location while performing the initial home
health assessment and thus the OASIS item used to indicate the
preadmission location of the patient was not always reliable. Moreover,
the pre-admission information did not perform well in terms of the
four-equation model used for payment estimation and also had a small
impact in terms of payment accuracy within the model. In the CY 2008 HH
PPS final rule, we further noted that the item's results across the
four equation model created difficulties in terms of interpretation and
the explanatory power (for example, its contribution to the R-squared
value) was minimal (72 FR 49766).
For the purposes of constructing the HHGM, which would not use a 4-
equation model or otherwise adjust payments based on therapy visit
thresholds; we reexamined the impact of beneficiary admission source,
either from the community or from an institutional setting, on home
health resource use. In our review of related scholarly research, we
found that beneficiaries admitted directly or recently from an
institutional setting (acute or post-acute care (PAC)) tend to have
different care needs and higher resource use than those admitted from
the community, thus indicating the need for differentiated payment
amounts. For instance, a literature review of 25 research studies
published between 2002 and 2011, titled ``Hospitalization Among
Medicare-Reimbursed Skilled Home Health Recipients,'' found that
Medicare beneficiaries discharged from PAC and acute facilities differ
significantly in resource need when compared to community-admitted
beneficiaries.\34\ Patients discharged from acute and PAC settings tend
to be sicker upon admission and are being discharged rapidly back to
the community. Additionally, they are more likely to be
[[Page 35310]]
re-hospitalized after discharge due to the acute nature of their
illness. One study discussed in this literature review determined that
patients being discharged from an inpatient hospitalization typically
present with multiple comorbidities, suggesting that initially-
hospitalized patients subsequently transferred to home care were more
likely to have four or more secondary diagnoses, as well as a pressure
or stasis ulcer, urinary incontinence, a urinary catheter, depression,
or dyspnea.\35\ They generally had more than five medications than
their non-hospitalized counterparts and required assistance with
medication management.\36\ As such, patients referred to home health
after an institutional stay tend to be more infirm, requiring
significant resources upon admission to home health. Additionally, the
same literature review also highlighted a study titled ``Unplanned
hospital readmissions: A home care perspective'' that demonstrated that
patients referred from acute and PAC settings are at a high risk of
hospitalization within 14 to 21 days of admission to home health.\37\
Given that the first few weeks after an institutional stay represent a
critical window in terms of providing beneficiaries with appropriately
intensive supports and services, as well as preventing re-
hospitalization, we would expect that providing care for those
beneficiaries admitted from institutional settings would require more
resource use compared to patients admitted to home health from the
community. Comprehensive and deliberate interventions in this timeframe
could also potentially reduce re-hospitalization rates.
---------------------------------------------------------------------------
\34\ O'Connor, M. (2012, February). Hospitalization Among
Medicare-Reimbursed Skilled Home Health Recipients. Retrieved March
02, 2017, from https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4690459.
\35\ Rosati, R. J., Huang, L., Navaie-Waliser, M., & Feldman, P.
H. (2003). Risk Factors for Repeated Hospitalizations Among Home
Healthcare Recipients. Journal For Healthcare Quality, 25(2), 4-11.
doi:10.1111/j.1945-1474.2003.tb01038.x.
\36\ Rosati, R. J., Huang, L., Navaie-Waliser, M., & Feldman, P.
H. (2003). Risk Factors for Repeated Hospitalizations Among Home
Healthcare Recipients. Journal For Healthcare Quality, 25(2), 4-11.
doi:10.1111/j.1945-1474.2003.tb01038.x.
\37\ Anderson, M. A., Helms, L. B., Hanson, K. S., & Devilder,
N. W. (1999). Unplanned Hospital Readmissions: A Home Care
Perspective. Nursing Research, 48(6), 299-307. doi:10.1097/00006199-
199911000-00005.
---------------------------------------------------------------------------
Research studies also demonstrate that patients admitted to home
health from institutional settings are more vulnerable to adverse
effects and injury because of the functional decline that occurs as a
result of their institutional stay, indicating that this patient
population requires more concentrated resources and supports to account
for and mitigate this functional decline. In the article titled ``The
Incidence and Severity of Adverse Events Affecting Patients after
Discharge from the Hospital,'' \38\ Alan J. Forster, MD noted that
beneficiaries are susceptible to harm post-hospitalization: ``Patients
may be especially vulnerable to injuries during this [post-discharge]
period because they may still have functional impairments and because
discontinuities may occur at the interface of acute and ambulatory
care.'' The author also notes that the current health care environment
encourages potentially expedited discharges from hospital stays, ``in
which patients are leaving the hospital `quicker and sicker.' ''
Patients may be leaving the hospital environment in a tenuous and
fragile state, leaving them vulnerable to further harm once returned to
the home environment. Additionally, the change from constant monitoring
in the inpatient facility to less frequent monitoring in the home
environment can potentially cause gaps in care and consequently
increased risk for adverse events for the newly-admitted home health
beneficiary. The article notes that many of the negative impacts of the
transition can be reduced by an appropriate increase in care for the
beneficiary in the home setting, notably with more frequent assessment
of their condition and ongoing monitoring. Therefore, we believe that
an opportunity may exist for the HHGM to account for this increased
need and accordingly provide a differentiated payment to facilitate the
provision of more frequent assessments and monitoring for beneficiaries
admitted to home health from acute and PAC settings, which could in
turn help prevent re-hospitalizations and adverse events. We expect
that HHAs would provide more resource-intensive services after
discharge from an institutional setting to educate patients in new
medication management, facilitate discharge education for the patient
and family, and provide support in the recovery from the illness that
caused the originating hospitalization or institutional stay.
---------------------------------------------------------------------------
\38\ Forster, A.J. (2003). The Incidence and Severity of Adverse
Events Affecting Patients after Discharge from the Hospital. Annals
of Internal Medicine, 138(3), 161. doi:10.7326/0003-4819-138-3-
200302040-00007.
---------------------------------------------------------------------------
In the guidebook ``Patient Safety and Quality: An Evidence-based
Handbook for Nurses,'' authors Ruth M. Kleinpell, Kathy Fletcher, of
and Bonnie M. Jennings note in chapter 11 that deconditioning, a status
characterized by a ``decrease in muscle mass and the other physiologic
changes related to bed rest, contributes to overall weakness,'' has
become commonplace in the post-institutional beneficiary
population.\39\ This physiological weakening of the institutionalized
beneficiary can then, in turn, lead to significant functional decline,
resulting in reduction in ability to perform Activities of Daily Living
(ADLs), and ultimately in increased home health resource utilization.
The article notes that hospitalization of the elderly is usually marked
by decreased levels of mobility and increased levels of bed rest, with
deterioration from their baseline levels as soon as day two of the
hospitalization. Hence, a hospitalization itself leads to declines in
mobility, which consequently yields reduced functionality in patients
relative to their status before their inpatient stay. This decline in
functional ability likewise merits appropriate skilled services to
support the patient's increased needs after a hospital stay.
---------------------------------------------------------------------------
\39\ Hughes, R. (2008). Patient safety and quality: An evidence-
based handbook for nurses. Rockville, MD: Agency for Healthcare
Research and Quality, U.S. Dept. of Health and Human Services.
https://archive.ahrq.gov/professionals/clinicians-providers/resources/nursing/resources/nurseshdbk/nurseshdbk.pdf, 259-274.
---------------------------------------------------------------------------
In the article ``Determinants of health after hospital discharge:
Rationale and design of the Vanderbilt Inpatient Cohort Study (VICS),''
the authors describe the period after a hospitalization as a
``vulnerable time'' for patients.\40\ This vulnerability is due to a
number of factors, including the need to manage new health care issues,
major modifications to medication interventions, and the coordination
of follow-up appointments, all while a beneficiary strives to
recuperate after a hospital stay for an acute medical event. Of
particular concern are the risks for adverse drug events, for errors in
a beneficiary's medication regimen, and for the need to readmit to the
hospital due to deterioration of the patient's condition. Given the
risks during this intense, challenging, and potentially costly period
after discharge, we would expect that beneficiaries would require more
visits from skilled disciplines, particularly for the purpose of
teaching and medication management. This increased utilization of
resources would, in turn, warrant a differentiated, potentially higher
payment for such services, and the proposed HHGM payment system
refinement could account for this difference with varying
[[Page 35311]]
payment amounts based upon admission source. We note that we do not
expect the source of the patient's admission would lead to an HHA
furnishing home health services that would replace any orders made by
the referring physician regarding the type or frequency of services the
patient might need during the home health stay. The admission source
variable in the proposed HHGM is meant to serve as a meaningful
indicator of resource utilization, which determines Medicare payment.
The HHA, in consultation with the physician and ordered by the
physician, will continue to articulate, in the plan of care, what
services are required to meet the needs of the patient, as well as the
frequency of such services.
---------------------------------------------------------------------------
\40\ Meyers, A.G., Salanitro, A., Wallston, K.A., Cawthon, C.,
Vasilevskis, E.E., Goggins, K. M., . . . Kripalani, S. (2014).
Determinants of health after hospital discharge: Rationale and
design of the Vanderbilt Inpatient Cohort Study (VICS). BMC Health
Services Research, 14(1). doi:10.1186/1472-6963-14-10.
---------------------------------------------------------------------------
With regard to beneficiaries admitted to home health from the
community, research related to home health admission source
demonstrates that community-admitted beneficiaries tend to receive care
from the less-costly disciplines. In its 2016 Report to Congress,
MedPAC noted that, in their analysis of CY 2013 HH claims,
beneficiaries admitted from the community tend to receive more visits
from home health aides than their non-community counterparts, stating
that ``aide services were the majority of services provided in 14
percent of the episodes for community-admitted users compared with 5
percent for PAC users.'' \41\ However, these same community entrants
averaged 2.6, 60-day episodes, while the institutional admits averaged
only 1.4, 60-day episodes, demonstrating longer lengths of stay for the
community-admitted beneficiaries than those entering from institutional
settings. These findings suggest that beneficiaries admitted to home
health from the community typically require less resources but for
longer periods of time when compared to the beneficiaries admitted from
an institutional stay. Additionally, a 2001 Department of Health and
Human Services Office of Inspector General study found Medicare home
health referrals coming from the community (in this case defined as a
referral for a beneficiary who had not been admitted to an overnight
stay in a hospital or skilled nursing facility for 15 days prior to
beginning a home health care episode) were more likely to have chronic
conditions than those referred from hospitals, and therefore, were more
likely to require ongoing but less resource-intensive care.\42\
---------------------------------------------------------------------------
\41\ Medicare Payment Advisory Commission (MedPAC). ``Home
Health Care Services.'' Report to Congress: Medicare Payment Policy.
Washington, DC, March 2016. P. XX. Accessed on March 28, 2017 at
https://www.medpac.gov/docs/default-source/reports/chapter-8-home-health-care-services-march-2016-report-.pdf?sfvrsn=0.
\42\ https://oig.hhs.gov/oei/reports/oei-02-01-00070.pdf;
``Medicare Home Health Care Community Beneficiaries 2001''; HHSM-
500-2010-00072C 12.
---------------------------------------------------------------------------
In addition to our review of related research, we also evaluated
home health utilization and patient assessment data as described in
section III.E.1 of this proposed rule, and our findings demonstrate
that those beneficiaries admitted from PAC, as well as acute care
settings demonstrate higher resource utilization than their community-
admitted counterparts.
The differences in care needs during home health based on admission
source are illustrated in the resource utilization figures presented in
Table 32, which shows the distribution of admission sources as well as
average resource use for 30-day periods by admission source.
Institutional admissions have significantly higher average resource use
at $2,165.06 compared with community admissions at $1,393.10, a
difference of $771.96. Median values of resource use also show a
significant difference between sources of admission, with institutional
resource use at $1,899.41 while community resource use is at $1,060.51,
a difference of nearly $840. The pattern of higher resource use for
institutional admissions as compared to community admissions continues
for the 25th and 75th percentiles, with a difference of approximately
$700 and $900, respectively.
Table 32--Average Resource Use by Admission Source (14 Day Look-Back) Admission Source
--------------------------------------------------------------------------------------------------------------------------------------------------------
Standard 25th 75th
Average Number of 30- Percent of 30- deviation of percentile of Median percentile of
resource use day periods day periods resource use resource use resource use resource use
--------------------------------------------------------------------------------------------------------------------------------------------------------
Institutional........................... $2,165.06 $2,153,712 24.92 $1,350.43 $1,224.83 $1,899.41 $2,772.04
Community............................... 1,393.10 6,488,395 75.08 1,208.29 571.97 1,060.51 1,838.39
---------------------------------------------------------------------------------------------------------------
Total............................... 1,585.48 8,642,107 100.00 1,289.23 671.96 1,262.65 2,119.49
--------------------------------------------------------------------------------------------------------------------------------------------------------
Source: CY 2016 Medicare Home Health Claims Data (as of March 17, 2017).
For all of these reasons, we are proposing to establish two
admission source categories for grouping 30-day periods of care under
the HHGM--institutional and community--as determined by the healthcare
setting utilized in the 14 days prior to home health admission. We are
proposing the institutional category would include 30-day periods of
care for patients admitted from either acute care or PAC settings.
Thirty-day periods for beneficiaries with any inpatient acute care
hospitalizations, skilled nursing facility stays, inpatient
rehabilitation facility stays, or long term care hospital stays within
the 14 days prior to a home health admission would be designated as
institutional admissions. Similarly, we are proposing that the
institutional admission source category would also include patients
that had an acute care hospital stay during a previous 30-day period of
care and within 14 days prior to the subsequent, contiguous 30-day
period of care and for which the patient was not discharged from home
health and readmitted (that is, the admission date and from date for
the subsequent 30-day period of care do not match) as we acknowledge
that HHAs have discretion as to whether they discharge the patient due
to a hospitalization and then readmit the patient after hospital
discharge. However, we would not categorize post-acute care stays that
occur during a previous 30-day period and within 14 days of a
subsequent, contiguous 30-day period of care (that is, the admission
date and from date for the subsequent 30-day period of care do not
match) as institutional as we would expect the HHA to discharge the
patient if the patient requires post-acute care in a different setting
(for example, a SNF or IRF) and then readmit the patient, if necessary,
after discharge from such setting. If the patient is discharged and
then readmitted to home health, the admission date and from date on the
30-day claim will match and the claims
[[Page 35312]]
processing system will look for an acute or a post-acute care stay
within 14 days of the home health admission date. This admission source
designation process would be applicable to institutional stays paid by
Medicare or any other payer. All other 30-day periods would be
designated as community admissions.
We initially investigated maintaining two separate institutional
categories, one for PAC and another for acute care settings, to
identify any meaningful differences in resource use. However, we
observed similar resource use in those cases where the patient was
admitted from both PAC and acute care settings. Furthermore, in our
analysis of the data from CY 2013, we found that the volume of home
health cases with an admission from PAC settings across all 30-day
periods of care was a low value at 736,112 cases (approximately 8
percent) out of a total of 8,539,996 cases as compared with cases
admitted from acute settings at 1,376,567 cases (approximately 16
percent). The number of cases admitted from acute settings was
approximately double the number of cases admitted from PAC settings.
Moreover, in the creation of case-mix groups that differentiated
between community, acute, and PAC admission sources, there were some
case-mix groups with a very low number of 30-day periods of care, which
in turn can result in substantial variability in the average resource
use from year- to- year. We were concerned that this variability could
introduce unnecessary instability in the case-mix weights under the
proposed HHGM. As such, we are proposing to group 30-day periods of
care for patients admitted from acute care and PAC settings together as
``institutional'' admissions.
We also considered the employment of a ``look-back'' period for
determining the admission source that was longer than 14 days and thus
examined data for a longer 30-day ``look-back'' period to assess the
resource utilization for patients admitted to home health from
institutional and community settings; however, our findings indicated
that there is only a slight difference in resource use, as well as
volume of beneficiaries utilizing PAC or acute services before home
health between the two timeframes. Table 33 shows the distribution of
30-day periods and average resource utilization with admission source
categories now defined by service use for beneficiaries in the 30 days
prior instead of 14 days prior. In general, results are similar to
those for the 14-day look-back period when compared to the 30-day
``look-back'' window. Average resource use under a 14-day ``look-back''
period for institutional entrants is at $2,165.06 while the 30-day
entrants show an average resource use of $2,140.40. The same similarity
holds true for community entrants, who show an average resource use of
$1,393.10 for the 14-day ``look-back'' period versus $1,382.38 under
the 30-day window. We note that the 30-day ``look-back'' period only
produces a slightly higher proportion of institutional periods of care,
at 2,315,557 periods as compared with the 14-day period value of
2,153,712, a difference of approximately 10 percent.
Table 33--Average Resource Use by Admission Source
[30 Day look-back]
--------------------------------------------------------------------------------------------------------------------------------------------------------
Standard 25th 75th
Admission source Average Number of 30- Percent of 30- deviation of Percentile of Median Percentile of
resource use day periods day periods resource use resource use resource use resource use
--------------------------------------------------------------------------------------------------------------------------------------------------------
Institutional........................... $2,140.40 2,315,557 26.79% $1,354.34 $1,197.39 $1,873.71 $2,748.79
Community............................... 1,382.38 6,326,550 73.21 1,202.14 567.05 1,049.66 1,823.04
---------------------------------------------------------------------------------------------------------------
Total............................... 1,585.48 8,642,107 100.00 1,289.23 671.96 1,262.65 2,119.49
--------------------------------------------------------------------------------------------------------------------------------------------------------
Source: CY2016 Medicare Home Health Claims Data (as of March 17, 2017).
We believe that a 14-day ``look-back'' period is more likely to be
directly related to the patients' need for home health care than a 30-
day ``look-back'' period. This would also be more intuitive for HHAs,
as the OASIS item M1000 specifically assesses whether a beneficiary was
discharged from an institutional setting within the past 14 days. Thus,
we ultimately are proposing to use the 14-day ``look-back'' period as
we believe it will better categorize those beneficiaries with a
relatively short transition between institutional care and home health
care. Given that beneficiary admission source has previously been
utilized for the purposes of Medicare home health payment, HHAs will be
familiar with this concept. Moreover, the proposed 14-day ``look-back''
period simplifies the structure of the proposed model and limits burden
on claims systems and related processing. Additionally, a ``look-back''
period of 14 days is consistent with section 1861(tt)(1) of the Act,
which defines the term ``post-institutional home health services''.
To differentiate between an institutional and community admission
source, we would establish an evaluation process whereby the Medicare
claims processing system would check for the presence of an acute/post-
acute Medicare claim occurring within 14 days of the home health
admission on an ongoing basis. In the past, HHAs stated that they had
encountered challenges in terms of identifying the source of admission
for home health beneficiaries, and we believe that an automated systems
approach where Medicare systems evaluate for the presence of an
institutional claim within the 14-day ``look-back'' window will serve
to overcome this earlier challenge. Under this approach, the Medicare
systems would only evaluate for whether an acute/post-acute Medicare
claim occurring within 14 days of the home health admission was
processed by Medicare, not whether it was paid.
Moreover, we propose that newly-created occurrence codes would also
be established that would allow HHAs to manually indicate on Medicare
home health claims an institutional admission source prior to an acute/
post-acute Medicare claim, if any, being processed by Medicare systems.
We note that the use of these occurrence codes would not be limited to
home health beneficiaries for whom the acute/post-acute claims were
paid by Medicare. HHAs would also use the occurrence codes for
beneficiaries with acute/post-acute care stays paid by other payers,
such as the Veterans Administration. Although a home health claim with
a non-Medicare institutional admission source can be categorized by the
HHA as an institutional admission and paid accordingly, we may conduct
medical review as discussed below. We expect
[[Page 35313]]
home health agencies would utilize discharge summaries from
institutional providers to inform the usage of these occurrence codes.
We note that these discharge documents should already be part of the
beneficiary's home health medical record used to support the
certification of patient eligibility as outlined in Sec. 424.22(c).
If an occurrence code is submitted on the home health claim, the
home health claim would be categorized as an institutional admission.
However, if a home health claim is submitted without an institutional
admission occurrence code, thereby categorizing it with a community
admission source, and later an acute/post-acute Medicare claim for an
institutional stay occurring within 14 days of the home health
admission is submitted within the timely filing deadline and processed
by the Medicare systems, the home health claim would be automatically
adjusted and re-categorized as an institutional admission and
appropriate payment modifications would be made. Our systems would
adjust community-admitted home health claims on a claim-by-claim, flow
basis if an acute/post-acute Medicare claim for an institutional stay
occurring within 14 days of the home health admission is received.
Given that our systems can only evaluate for the presence of a Medicare
acute/post-acute claim, if there was a non-Medicare institutional stay
occurring within 14 days of the home health admission but the HHA was
not aware of such a stay, upon learning of the institutional stay, the
HHA would be able to resubmit a home health claim that included an
occurrence code, subject to the timely filing deadline, and payment
adjustments would be made accordingly.
Conversely, if an occurrence code is submitted on the home health
claim along with dates of the institutional stay, and an acute/post-
acute Medicare claim for an institutional stay occurring within 14 days
of the home health admission is not subsequently submitted within the
timely filing deadline and processed by the Medicare systems, or an
acute/post-acute Medicare claim for an institutional stay occurring
within 14 days of the home health admission was submitted but later
denied for payment, we may conduct post-payment medical review of the
home health claim to determine whether the admission was in fact
preceded by an institutional stay occurring within 14 days of the home
health admission. If upon medical review a determination is made that
the admission was not from an institutional setting, we would take
appropriate administrative action, including correcting any improper
payments and potentially referring the provider to another CMS review
contractor for further review or investigation. In summary, we believe
that allowing HHAs to submit a claim with an institutional admission
occurrence code for a beneficiary with either a Medicare or non-
Medicare institutional admission source would enable HHAs to receive
appropriate payment for the home health services, while also allowing
us the opportunity and flexibility to verify the source of the
admission and correct any improper payments as deemed appropriate.
For the purposes of a RAP, we would only adjust the final home
health claim submitted for source of admission. For example, if a RAP
for a community admission was submitted and paid, and then an acute/
post-acute Medicare claim was submitted for that patient before the
final home health claim was submitted, we would not adjust the RAP and
would only adjust the final home health claim so that it reflected an
institutional admission. Additionally, HHAs would only indicate
admission source occurrence codes on the final claim and not on any
RAPs submitted.
We invite public comments on the admission source component of the
proposed HHGM payment system.
6. Proposed Clinical Groupings
a. Background
As discussed in section II.D of this proposed rule, the Home Health
Study Report to Congress found that the current payment system may
encourage HHAs to select certain types of patients over others, as some
clinical sub-groups within the current case mix system are associated
with lower margins.\43\ These sub-groups include patients with a higher
severity of illness, including those receiving a greater level of
skilled nursing care; for example, patients with wounds, with ostomies,
or who are receiving total parenteral nutrition or mechanical
ventilation. Additionally, the Medicare Payment Advisory Commission
(MedPAC) has expressed concerns that the HH PPS disincentivizes care
for patients needing skilled nursing visits, thereby limiting access of
care to the most clinically vulnerable patient populations.\44\
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\43\ Report to Congress. Medicare Home Health Study: An
Investigation on Access to Care and Payment for Vulnerable Patient
Populations. Available at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/HomeHealthPPS/Downloads/HH-Report-to-Congress.pdf.
\44\ Report to the Congress: Medicare Payment Policy. (2015)
Home health care services: Assessing payment adequacy and updating
payments. Ch.9 https://www.medpac.gov/docs/default-source/reports/chapter-9-home-health-care-services-march-2015-report-.pdf?sfvrsn=0.
---------------------------------------------------------------------------
Although the clinical domain of the current case-mix system
accounts for whether or not the patient has one or more certain
clinical conditions, there could be improvements in clarity regarding
patient needs to clearly explain resource use and cost. Given that
payment should be predicated on resource use, providing additional
clinical groups in the case-mix system and adjusting payment based on
identified clinical characteristics and associated services, along with
other patient variables, should better align payment with resource use.
As such, under the HHGM, we propose grouping 30-day periods of care
into six clinical groups designed to capture the most common types of
care that HHAs provide. The proposed groups mirror how clinicians
differentiate between patients as to what types of care they are
receiving. To inform the development of the clinical groups, Abt
Associates and CMS conducted an extensive review of diagnosis codes to
identify the primary reasons for home health services under the
Medicare home health benefit. The workgroup developed six clinical
groups reflecting the reported principal diagnosis, clinical relevance,
and coding guidelines and conventions, see Table 34.
Table 34--Clinical Groups Used in the Home Health Groupings Model
------------------------------------------------------------------------
The primary reason for the home
Clinical groups health encounter is to provide:
------------------------------------------------------------------------
Musculoskeletal Rehabilitation.... Therapy (physical, occupational or
speech) for a musculoskeletal
condition.
Neuro/Stroke Rehabilitation....... Therapy (physical, occupational or
speech) for a neurological
condition or stroke.
[[Page 35314]]
Wounds--Post-Op Wound Aftercare Assessment, treatment & evaluation
and Skin/Non-Surgical Wound Care. of a surgical wound(s); assessment,
treatment & evaluation of non-
surgical wounds, ulcers, burns, and
other lesions.
Behavioral Health Care............ Assessment, treatment & evaluation
of psychiatric conditions.
Complex Nursing Interventions..... Assessment, treatment & evaluation
of complex medical & surgical
conditions including IV, TPN,
enteral nutrition, ventilator, and
ostomies.
Medication Management, Teaching Assessment, evaluation, teaching,
and Assessment (MMTA). and medication management for a
variety of medical and surgical
conditions not classified in one of
the above listed groups.
------------------------------------------------------------------------
The 30-day periods of care were assigned to one of the six clinical
groups based on the reported principal diagnosis. However, roughly 19
percent of 30-day periods could not be assigned to a clinical group
based on principal diagnosis alone. Reasons for the inability to group
30-day periods based on primary diagnoses included codes that were too
vague, meaning the code did not provide adequate information to support
the need for home health services (for example, T14.90 Injury,
unspecified); codes that would not be Medicare covered services in
other settings (for example, dental codes); codes that would be
unlikely to require skilled home health services (for example, R68.89
Other general symptoms and signs); codes that indicate death as the
outcome (for example, G93.82, Brain death); manifestation codes, where
coding guidelines require an etiology code to be reported as a
principal diagnosis (for example, I39 Endocarditis and heart valve
disorders in diseases classified elsewhere); or code first, meaning the
diagnosis is subject to sequencing conventions under ICD-10-CM, where
the underlying condition must be sequenced first (for example, dementia
in Parkinson's disease, in which Parkinson's disease must be sequenced
first). In these instances, 30-day periods were considered
``questionable encounters'' and secondary diagnosis codes were examined
to group the 30-day period of care. An ICD-10-CM list with all of the
codes that would assign 30-day periods into the six clinical groupings
can be found on CMS's HHA Center Web page at https://www.cms.gov/center/provider-Type/home-Health-Agency-HHA-Center.html. More
information on the analysis and development of the groupings can be
found in the HHGM technical report, also available on the HHA Center
Web page. Table 35 shows the distribution of episodes and associated
resource use across the six clinical groups.
Table 35--Frequency and Associated Resource Use of Clinical Groups
--------------------------------------------------------------------------------------------------------------------------------------------------------
Standard 25th 75th
Average deviation Percentile Median Percentile
Clinical group resource N Percent of resource of resource resource of resource
use use use use use
--------------------------------------------------------------------------------------------------------------------------------------------------------
Musculoskeletal Rehabilitation............................... $1,713.10 1,430,813 16.56 $1,149.61 $1,495.09 $878.95 $2,276.98
Neuro/Stroke Rehabilitation.................................. 1,811.74 772,579 8.94 1,319.45 1,511.06 851.12 2,434.60
Wound........................................................ 2,055.47 906,782 10.49 1,666.59 1,609.16 955.17 2,623.31
Behavioral Health............................................ 1,252.08 289,513 3.35 1,019.25 954.32 505.15 1,704.72
Complex Nursing Interventions................................ 1,703.24 336,249 3.89 1,573.15 1,240.74 675.88 2,206.54
MMTA......................................................... 1,437.37 4,906,171 56.77 1,200.35 1,105.63 589.92 1,936.81
------------------------------------------------------------------------------------------
Total.................................................... 1,585.48 8,642,107 100.00 1,289.23 1,262.65 671.96 2,119.49
--------------------------------------------------------------------------------------------------------------------------------------------------------
Table 35 illustrates the differences in average resource use
between 30-day periods with similar care needs. Under the HHGM, we
propose that each 30-day period would be assigned to a clinical group
according to the primary reason the patient was receiving home health,
which would be derived from the principal diagnosis code reported on
the home health claims. If a 30-day period of care could not be grouped
based on the home health reported principal diagnosis due to the
reasons listed above, we propose that the claim for that 30-day period
would remain a questionable encounter and be returned to the provider
for more accurate or definitive coding. Upon publication of this
proposed rule, we will post a complete list of ICD-10 codes and their
assigned clinical groupings on the CMS HHA Center Web page (https://www.cms.gov/center/provider-Type/home-Health-Agency-HHA-Center.html) to
allow ample time for HHAs to understand those codes which would be
considered a ``questionable encounter.'' We believe this will help to
minimize any returned claims for more definitive coding. Each code
should be reported to the level of certainty and specificity known for
the home health admission. Under our proposal, secondary diagnosis
codes would not be used to assign the clinical group, as the intent of
the HHGM is to increase clarity by classifying the 30-day period based
on the primary reason for home health services. Although the principal
diagnosis code is the basis for the home health period, secondary
diagnosis codes would then be used to case-mix adjust the period
further through additional elements of the model, such as the
comorbidity adjustment. Using principal diagnoses as the core of the
model would create a clinically intuitive payment system that more
clearly identifies the types of patients that are treated in home
health. Diagnosis codes would also provide clarity and transparency
since they are clearly described and reported on claims and other care
tools. Additionally, they would support medical necessity for services
furnished, and provide information for establishing the home health
plan of care. Ultimately, developing clinically similar groups based on
the reported principal
[[Page 35315]]
diagnosis as part of the larger structure of the model would allow for
more meaningful analysis of home health resource use, ensure that
patients are receiving care commiserate with their level of need, and
more accurately align payment with cost.
b. Musculoskeletal and Neuro/Stroke Rehabilitation
Rehabilitation is an integral part of recovery following an
illness, injury, or surgical procedure, whether due to a neurological
or a musculoskeletal condition. Given that different care goals and
expected outcomes of neuro-rehabilitation and musculoskeletal
rehabilitation affect resource use, the clinical groups in the HHGM
would differentiate between the two. Patient characteristics between
the two groups determine whether resources are directed towards
preventing the loss of function or slowing the rate of loss of
function; improvement or restoration of function; compensation for lost
function; and maintenance of current function.\45\ Musculoskeletal
rehabilitation focuses on individuals with impairments or disabilities
due to disease, disorders, or trauma to the muscles or bones, whereas
neurological rehabilitation is designed for individuals with disease,
trauma, or disorders of the nervous system.\46\ Rehabilitation
following a stroke, for instance, is primarily initiated early and
intensively with the most recovery of function occurring within the
first 3 months; \47\ however, reacquiring the skills to perform ADLs
may be an on-going process depending on the extent and area of injury.
However, if improvement or recovery are not expected or achieved, the
focus of therapy may shift to maintenance to prevent further decline.
Therefore, the VA Clinical Practice Guidelines for Management of Stroke
Rehabilitation ``strongly recommend that rehabilitation therapy should
start as early as possible, once medical stability is reached'' and
``recommend that the patient receive as much therapy as needed and
tolerated to adapt, recover, and/or reestablish the premorbid or
optimal level of functional independence.'' \48\ Neuro-rehabilitation
resource use can encompass evaluation and treatment of impairments in
cognitive and spatial functioning, swallowing, communication, and
psychological or emotional deficit; whereas musculoskeletal
rehabilitation generally focuses on evaluation and treatment of the
impaired muscle, bone, or joint. Musculoskeletal rehabilitation is more
targeted toward proprioception, strength, imbalances, orthopedic
surgeries, and abnormal functional movement patterns, and generally
streamlines resources following a surgery or injury. Because of these
clinical differences and associated resource use differences based on
variables in length and intensity of rehabilitation, the HHGM would
adjust payment between musculoskeletal and neuro/stroke rehabilitation
accordingly.
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\45\ World Health Organization. (2011). Rehabilitation. World
Report on Disability. Chapter 4. Retrieved from https://www.who.int/disabilities/world_report/2011/chapter4.pdf.
\46\ Johns Hopkins Online Health Library. Neurological
Rehabilitation. Retrieved from https://www.hopkinsmedicine.org/healthlibrary/conditions/adult/physical_medicine_and_rehabilitation/neurological_rehabilitation_85,P01163/.
\47\ Stinear,C., Ackerley,S., Byblow, W. (2013) Rehabilitation
is Initiated Early After Stroke, but Most Motor Rehabilitation
Trials Are Not. Stroke. 2013; 44:2039-2045. https://doi.org/10.1161/STROKEAHA.113.000968.
\48\ https://www.healthquality.va.gov/guidelines/Rehab/stroke/Mgmt_of_Stroke_Rehab_03151.pdf.
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c. Wounds
Wound care is provided in a variety of settings, including in the
home. Advances in wound care treatments have increasingly allowed for a
wide range of wound therapies to be provided in the home.\49\ According
to the article ``Wound Care Outcomes and Associated Cost Among Patients
Treated in US Outpatient Wound Centers: Data From the US Wound
Registry,'' a ``rough population prevalence rate for chronic non-
healing wounds in the United States is 2 percent of the general
population,'' with an estimated cost of caring for these wounds
exceeding $50 billion a year.\50\ Non-healing, chronic wounds are often
found in home health patients considering ``prolonged and non-healing
connective tissue injuries are often associated with common diseases,
such as metabolic disorders, obesity, hypertension, arteriosclerosis,
neuropathy, and diabetes mellitus,'' \51\ which are among the top home
health diagnoses.
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\49\ Rhee, S., Valle, M., Wilson, L., Lazarus, G., Zenilman, J.,
Robinson, K. (2015). Negative pressure wound therapy technologies
for chronic wound care in the home setting: A systematic review.
Wound Repair and Regeneration. 23, 506-517.
\50\ https://www.woundsresearch.com/article/wound-care-outcomes-and-associated-cost-among-patients-treated-us-outpatient-wound-centers-d.
\51\ Ackermann, P., Hart, D. Influence of Comorbidities:
Neuropathy, Vasculopathy, and Diabetes on Healing Response Quality.
(2013) Adv Wound Care (New Rochelle), 2(8): 410-421. doi: 10.1089/
wound.2012.0437.
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Surgical wound care is essential at preventing post-operative
complications such as surgical site infections (SSIs) and dehiscence.
Research has shown that post-discharge SSIs occur in 3 to 5 percent of
all surgical patients, and up to 33 percent of patients undergoing
abdominal surgery, and that ``more than half of patients who develop
post-discharge SSIs are readmitted to the hospital, making SSIs the
overall costliest healthcare-associated infection.'' \52\ Home care
management of burns requires a variety of resources as ``burn patients
are unique, representing the most severe model of trauma.'' \53\ The
management of burn injury involves a multidisciplinary approach which
may include nurses, occupational and physical therapists, dieticians,
and psychosocial experts. Pressure ulcers are associated with an
increased risk of morbidity and mortality and have a variety of
intrinsic and external factors affecting their incidence and treatment.
The incidence of pressure ulcers in home health is projected to rise
due to the aging population, increasingly fragmented care, and nursing
shortage.\54\ Ultimately, wound care depends on a multitude of
characteristics driving resource utilization. By highlighting them as a
clinical group, the HHGM would recognize the variety of resources and
skills that necessitate careful treatment and healing of different
types of wounds, and more accurately ascribe resource use to payment.
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\52\ Sanger, P., Hartzler, A., Han,S., et al. (2014) Patient
Perspectives on Post-Discharge Surgical Site Infections: Towards a
Patient-Centered Mobile Health Solution. PLoS One. 2014; 9(12):
e114016.Published online 2014 Dec 1. doi: 10.1371/
journal.pone.0114016.
\53\ Al-Mousawi, A. MD, Mecott-Rivera, G. MD, Jeschke, M. MD,
Ph.D., et al. (2009). Burn Teams and Burn Centers: The Importance of
a Comprehensive Team Approach to Burn Care: Clin Plast Surg. 2009
Oct; 36(4): 547-554: doi: 10.1016/j.cps.2009.05.015.
\54\ Lyder, C., Ayello, Elizabeth. (2008). Pressure Ulcers: A
Patient Safety Issue. Patient Safety and Quality: An Evidence-based
Handbook for Nurses. Chapter 12.
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d. Behavioral Health Care
The World Health Organization (WHO) defines health as ``a state of
complete physical, mental and social well-being and not merely the
absence of disease or infirmity.'' \55\ As such, behavioral and mental
home health is an important clinical group of the HHGM. If all
eligibility and coverage criteria are met according to Sec. 409.42,
then a patient may receive skilled nursing services for the assessment,
treatment, and evaluation of psychiatric conditions. The Home Health
Benefit Policy Manual states that ``the evaluation, psychotherapy, and
teaching needed by a patient suffering from a diagnosed psychiatric
disorder that requires active treatment by a
[[Page 35316]]
psychiatrically trained nurse, and the costs of the psychiatric nurse's
services may be covered as a skilled nursing service.'' \56\ However,
the psychiatric care must be furnished by an agency that does not
primarily provide care and treatment of mental diseases. Older adults
may be more susceptible to psychiatric and behavioral health issues due
to limited mobility, bereavement, loss of ability to live
independently, or drop in socioeconomic status due to retirement.\57\
Although psychiatric and behavioral conditions have different signs,
symptoms, and treatment options than physical illness, mental health
can have major consequences on physical health. Behavioral health
research suggests that ``a model of care including solely hospital
based provision (usually inpatient and outpatient care) will be
insufficient to provide access for people facing barriers to care.''
\58\ Additionally, the length of stay among Medicare beneficiaries who
have been hospitalized for mental illness has declined over the last
decade, with patients being discharged to home health rather than
extending a hospitalization.\59\ For these reasons, behavioral home
health remains a crucial aspect of keeping beneficiaries out of the
hospital. Distinguishing it as a clinical group delineates the
resources associated with the unique care needs of these patients and
would more accurately assign payment based on patient characteristics.
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\55\ Constitution of WHO: principles: https://www.who.int/about/mission/en/.
\56\ https://www.cms.gov/Regulations-and-Guidance/Guidance/Manuals/Downloads/bp102c07.pdf.
\57\ World Health Organization: Mental Health and Older Adults.
Retrieved from https://www.who.int/mediacentre/factsheets/fs381/en/.
\58\ Thornicroft, G., Deb, T., Henderson, C. (2016) Community
mental health care worldwide: current status and further
developments. World Psychiatry, 15(3): 276-286.Published online 2016
Sep 22. doi: 10.1002/wps.20349.
\59\ Banta, J., Belk, I., Newton, K., Sherzai, A. (2010)
Inpatient Charges and Mental Illness: Findings from the Inpatient
Sample 1999-2007. Clinicoecon Outcomes Res2010; 2: 149-158.
Published online 2010 Oct 11. doi: 10.2147/CEOR.S7560.
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e. Complex Nursing Interventions
Understandably, the growing trend toward providing more healthcare
services in the community shifts an increasing number of complex
nursing interventions to home health. Providing complex nursing
interventions in the home reflects a patient population with ``more
complex health care needs who require more intensive medical services
coordinated across multiple providers, as well as a wide range of
social supports to maintain health and functioning.'' \60\ Because of
the range and intensity of services needed, these patients tend to
generate high resource utilization and associated costs due to the need
for a higher level of knowledge and expertise.\61\ Additionally,
readmission rates can be high in this vulnerable population as patients
adjust to their home with therapies generally administered in the
hospital or post-acute environment.\62\
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\60\ Rich, E., Lipson, D., Libersky, J., Parchman, M. (2012).
Coordinating Care for Adults With Complex Care Needs in the Patient-
Centered Medical Home: Challenges and Solutions WHITE PAPER,
prepared by Mathematica Policy Research AHRQ Publication No. 12-0010
January 2012: https://www.mathematica-mpr.com/our-publications-and-findings/publications/coordinating-care-for-adults-with-complex-care-needs-in-the-patientcentered-medical-home-challenges-and-solutions.
\61\ Huisman-de Waal G., van Achterberg, T., Jansen, J., Wanten,
G., Schoonhoven, L. (2011) High-tech home care: overview of
professional care in patients on home parenteral nutrition and
implications for nursing care: J Clin Nurs. 2011 Aug;20(15-16):2125-
34. doi: 10.1111/j.1365-2702.2010.03682.x. Epub 2011 May 25.
\62\ Vallab, H., Konrad, D., DeChicco, R., et al (2016). Thirty-
Day Readmission Rate Is High for Hospitalized Patients Discharged
With Home Parenteral Nutrition or Intravenous Fluids, JPEN J
Parenter Enteral Nutr. 2016 Aug 18. doi: 0148607116664785.
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For instance, the introduction of home mechanical ventilation is a
technological advancement that not only keeps healthcare costs down but
also allows patients, whose condition would otherwise necessitate an
institutional environment, a maximum quality of life. For example, the
results from one study found that long-term mechanical ventilation on
average costs $14,500 less per patient, per month when administered at
home rather than in an acute or post-acute facility.\63\ However, it
does not come without challenges. Caregiver competency, evolving
technology, changes in patient medical status, and safety of home
environment can lead to higher home health resource utilization.
Likewise, management of ostomies and vascular access devices (VADs) are
associated with higher resource use in the home. The impact on patients
living with VADs and ostomies is significant, with research identifying
physical, psychological, and social effects.\64\ Ostomy and VAD
specific challenges or complications may occur initially and persist
and change daily as patients learn to troubleshoot and manage life with
an ostomy or VAD. Care often requires resources aimed at education and
support in addition to physical care. This can be made more challenging
by the social and psychological effects that many new patients
experience. Under the HHGM, ICD-10-CM codes on the home health claim
that identify complex nursing interventions as the principal reason for
home health would generate higher payment to account for these inherent
challenges requiring additional resource utilization.
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\63\ King, A. Long-Term Home Mechanical Ventilation in the
United States. (2012). Respiratory Care June 2012, 57 (6) 921-932;
doi: https://doi.org/10.4187/respcare.01741.
\64\ Grant, M. RN, DNS, FAAN, McCorkle, R. Ph.D., FAAN,
Hornbrook, M. Ph.D., et al. (2013). Development of a Chronic Care
Ostomy Self-Management Program. J Cancer Educ. 2013 Mar; 28(1): 70-
78. doi: 10.1007/s13187-012-0433-1.
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f. Medication Management, Teaching, and Assessment (MMTA)
Based on our analysis, the majority of 30-day periods of care in
the HHGM would likely be classified under the MMTA clinical group.
These 30-day periods would be characterized by codes that identify
direct services related to the management and evaluation of the care
plan, observation and assessment of the patient's condition, and
training and/or education of a patient or family member that are not
classified into one of the other clinical groups. The numerous and
diverse conditions found in home health, and their associated
medications and interventions, influence the principal diagnosis that
would classify a 30-day period as under the MMTA clinical group.
Research on home health patient characteristics, home health
nursing interventions, and outcomes of care show that there are four
broad categories of interventions most frequently provided in the home:
(1) Health teaching, guidance and counseling;
(2) Treatments and procedures;
(3) Case management; and,
(4) Surveillance \65\
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\65\ Martin, K., Scheet, N., Stegman, M.R. (1993). Home Health
Clients: Characteristics, Outcomes of Care, and Nursing
Interventions. American Journal of Public Health. 83(12), 1730-1734.
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Of these interventions, surveillance is the most frequently
occurring intervention, closely followed by health teaching, guidance
and counseling.\66\ Specific patient problems most frequently
identified in the home health setting are related to medication
regimens, especially with polypharmacy, and health-related
behaviors.\67\ The majority of home health care patients routinely take
more than five prescription drugs, and many likely deviate from their
prescribed medication regimen.\68\ This increases
[[Page 35317]]
the potential for medication errors or adverse effects in home health,
highlighting the substantial need for education and medication
management regardless of whether the patient needs wound care,
rehabilitation, or complex nursing interventions.
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\66\ Ibid.
\67\ Ibid.
\68\ Ellenbecker, C., Samia, L., Cushman, M., Alster, K. (2008).
Patient Safety and Quality in Home Health Care. Patient Safety and
Quality: An Evidence-based Handbook for Nurses. Chapter 13.
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Additionally, patients with comorbidities tend to be high users of
home health,\69\ making education and assessment of disease diagnosis,
medication interactions, lifestyle changes, and avoidance of adverse
events a considerable portion of home health care. In an elderly
patient population, the number of chronic conditions increases with
age. Medications used to treat or prevent blood clots (anticoagulants),
diabetes (insulin), and pain (opioid analgesics) are some of the most
commonly implicated drugs in emergency room visits and emergent
hospitalizations for adverse drug events in older adults.\70\ These
adverse events can potentially be reduced by improving dosing and
monitoring of these drugs in high risk populations and settings like
older adults in home health programs.\71\ Anticoagulants are
challenging to manage in home health settings and have been identified
as targets for improvements in monitoring and care coordination by HHS.
Also, as the number of medications being taken increases, so does the
risk of adverse drug reactions, and the risk of drug reaction related
emergency room visits and hospital admissions, especially in patients
who are in poor health.\72\ Elderly patients are especially at risk for
adverse drug reactions as the organs that metabolize drugs have reduced
functional ability which can lead to increased toxicity.\73\ Similarly,
roughly 31 percent of younger Medicare beneficiaries with disabilities
report having five or more chronic conditions.\74\ Polypharmacy can
lead to reduced compliance with medication regimens, thus putting the
patient at risk for adverse events resulting from poorly managed
conditions. In the home healthcare setting, management of polypharmacy
is a primary focus of nursing interventions.\75\ These interventions
include assessment of the patient's chronic conditions and medications
used to treat those conditions; assessment of the patient's
understanding of and compliance with his or her medication regimen; and
teaching and reinforcing treatment and medication regimens. The
medication review by the home health nurse can help reduce duplicate
medications, medications that are contraindicated for older adults, and
provide ways to ensure patients are being appropriately monitored and
understand why they are taking the medications as well as how to take
them correctly.\76\
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\69\ Center for Healthcare and Transformation. (2010). Health
Care Cost drivers: Chronic Disease, Comorbidity and Health Risk
Factors in the U.S. and Michigan. Center for Healthcare and
Transformation.
\70\ Budnitz DS, Lovegrove MC, Shehab N, Richards CL. Emergency
hospitalizations for adverse drug events among older Americans. N
Engl J Med 2011;365:2002-2012.
\71\ U.S. Department of Health and Human Services, Office of
Disease Prevention and Health Promotion. (2014). National Action
Plan for Adverse Drug Event Prevention. Washington, DC.
\72\ Alpert, P., Gatlin, T. (2015). Polypharmacy in Older
Adults. Homehealth Care Now. 33(10), 524-529.
\73\ Ibid.
\74\ Cubanski, J., Neuman, T., Damico, A. (2010, August)
Medicare's Role for People Under Age 65 with Disabilities. Retrieved
from https://kff.org/medicare/issue-brief/medicares-role-for-people-under-age-65-with-disabilities/.
\75\ Ibid.
\76\ Ibid.
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Other studies show that primary functions of home health care
skilled nursing interventions include providing disease-specific and
general health information; helping patients to practice and refine
disease management skills; assessing efficacy of treatment; and,
advocating for any needed changes to established treatment and drug
regimens.\77\ The interventions encompassed under the MMTA clinical
group are shown extensively in research literature to be the most
prevalent services provided by home health clinicians. Analysis of home
health episodes for the HHGM suggests that the MMTA services would be
the most frequent home health service being provided to Medicare home
health beneficiaries.
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\77\ Liebel, D., Powers, B.A., Friedman, B., Watson, N. (2011).
Barriers and Facilitators to Optimize Function and Prevent
Disability Worsening: A Content Analysis of a Nurse Home
Intervention. Journal of Advanced Nursing. 68(1), 80-93.
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We believe that the proposed clinical groupings add a needed level
of clarity in identifying and meeting the needs of home health
patients; particularly the patient populations addressed in the Home
Health Study Report to Congress as outlined in section II.D. of this
proposed rule. Recognizing that all 30-day periods of home health care
cannot be defined by the principal diagnosis alone, the clinical
groupings would only be one step in the case-mix adjustment under the
HHGM. We invite comments on the proposed clinical groups, which are
designed to capture the most common types of care that HHAs provide.
7. Functional Levels and Corresponding OASIS Items
Research has shown a relationship exists between functional status,
rates of hospital readmission, and the overall costs of health care
services.\78\ Functional status is defined in a number of ways, but
generally, functional status reflects an individual's ability to carry
out activities of daily living (ADLs) and to participate in various
life situations and in society.\79\ The assessment of functional status
is often called ``the sixth vital sign'', which reflects its clinical
relevance in the plan of care. CMS requires the collection of data on
functional status in home health through a standardized assessment
instrument: The Outcome and Assessment Information Set (OASIS).\80\
Under the current HH PPS, functional status is assessed through the
following OASIS items:
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\78\ Burke, R. MD, MS, Whitfield, E. Ph.D., Hittle, D. Ph.D.,
Min, S. Ph.D., Levy, C. MD, Ph.D., Prochazka, A. MD, MS, Coleman, E.
MD, MPH, Schwartz, R. MD, Ginde, A. (2016). ``Hospital Readmission
From Post-Acute Care Facilities: Risk Factors, Timing, and
Outcomes''. The Journal of Post-Acute Care and Long Term Care
Medicine. (17), 249-255.
\79\ Clauser, S. Ph.D., and Arlene S. Bierman, M.D., M.S.
(2003). ``Significance of Functional Status Data for Payment and
Quality''. Health Care Financing Review. 24(3), 1-12.
\80\ Bierman, A. (2001). ``Functional Status: The Sixth Vital
Sign''. Journal of Internal Medicine. 16(11), 785-786.
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M1810: Dressing Upper Body.
M1820: Dressing Lower Body.
M1830: Bathing.
M1840: Toileting.
M1850: Transferring.
M1860: Ambulation/Locomotion.
For each of these OASIS items, the clinician or therapist
conducting the assessment selects a numbered checkbox that best
describes the patient's functional status in terms of ability to
perform certain tasks. These numbered checkboxes typically range from
zero, meaning independent with the task or no functional deficits, to
higher numbers, meaning decreasing independence and/or increasing
deficits. Responses to these OASIS items result in ``points'' to
calculate an overall functional score which conveys the functional
status of the patient. This means that patients with a higher
functional score (that is, reduced functional status) have, on average,
higher resource use compared to patients with a lower functional score
(that is, higher functional status). As such, the functional status of
the patient is a useful case-mix adjuster. Including functional status
in the case-mix adjustment methodology allows for higher payment for
those patients with
[[Page 35318]]
higher service needs. As functional status is commonly used for risk
adjustment in various payment systems, including in the current HH PPS,
the proposed HHGM would also adjust payments to account for differences
in resource use associated with functional status.
During the development of the HHGM, each OASIS-C item was evaluated
using clinical review and analytical methods. Because the current case-
mix adjustment methodology already utilizes OASIS items associated with
functional status to adjust the home health payment, utilizing these
OASIS items for inclusion in the HHGM was a primary focus. All OASIS
items, including items not used in the current case-mix adjustment
methodology, were evaluated for potential inclusion in the HHGM. OASIS
items were eliminated for inclusion based on statistical factors (for
example, the relationship of the item with resource use), clinical
factors (for example, clinical appropriateness of using the item for
payment purposes) and incentive factors (for example, potential for
unintended consequences such as overutilization solely for increased
reimbursement).
We presented our analysis of the OASIS items to a clinical
workgroup that included physicians, nurses, and therapists with
substantial home health clinical expertise, to obtain input regarding
which OASIS items to include in the HHGM. Based on the clinical
workgroup feedback and additional analyses by the research team, the
following decisions were made regarding the narrowed list of OASIS
items being considered for a functional status payment adjustment under
the HHGM: \81\
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\81\ Version OASIS C items were used for this initial analysis.
---------------------------------------------------------------------------
M066, M0110: Age, Episode timing--Both age and episode
timing were determined to be appropriate for the HHGM, but both items
can be accurately obtained directly from the home health claims data,
rather than the OASIS. As such, responses on these OASIS items would
not be used for this functional status adjustment under the HHGM.
M1018, M1030: Selected prior conditions and types of
therapies a patient receives--These OASIS items would not be used for
functional status adjustment in the HHGM because the clinical groups,
specifically Complex Nursing Interventions, (described in section
III.E.6. of this proposed rule) account for most of the conditions
described in these OASIS items (for example, IV therapy, TPN) so using
these OASIS items would be duplicative.
M1200: Vision--The clinical workgroup believed this OASIS
item to be clinically significant. However, while this item is used in
the current HH PPS, there are no longer ``points'' associated with this
item for the clinical domain because there is no additional resource
use related to this item beyond the average across all periods of care.
Additionally, analysis of this vision impairment OASIS item showed
decreased resource use in the HHGM and; therefore, was determined to
have a counterintuitive relationship. As a result, this OASIS item
would not be used for functional status adjustment in the HHGM.
Analysis of this item is found in the ``Overview of the Home Health
Groupings Model'' technical report found on the HHA Center Web
page.\82\
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\82\ ``Overview of the Home Health Groupings Model'' technical
report, Appendix Exhibit A7-1 on the HHA Center Web page (https://
www.cms.gov/center/provider-type/home-health-agency-hha-
center.html).
---------------------------------------------------------------------------
M1220, M1230: Understanding of verbal content, speech and
oral--These items were determined to be subjective in nature and may
not provide information that is an accurate reflection of the patient's
cognitive status. As with other OASIS items in this analysis, these
items showed that there was decreased resource costs associated with
worsening status. As a result, these OASIS items would not be used for
functional status adjustment in the HHGM.
M1242: Pain--While this item is used in the current HH
PPS, this is shown to have only a minimal relationship with resource
use in the current payment model. Although the clinical workgroup
believed this item to be clinically significant, CMS clinicians agreed
this one item alone may not be robust enough to fully capture the pain
presentation of the patient and its impact on resource utilization.
Therefore, this OASIS item would not be used for functional status
adjustment in the HHGM.
M1302, M1308, M1320, M1322, M1324, M1332, M1334, and
M1340: Ulcers and wounds--These OASIS items would not be used for
functional status adjustment in the HHGM because the Wound clinical
group (described in section III.E.6.of this proposed rule) already
adjusts the period payment for these conditions and using these OASIS
items would be duplicative.
M1400: Shortness of breath--Although the clinical
workgroup believed this item to be clinically significant, this OASIS
item would not be used for functional status adjustment in the HHGM
because the analysis showed decreased resource costs with worsening
dyspnea which appears to be clinically counterintuitive.\83\
---------------------------------------------------------------------------
\83\ Ibid.
---------------------------------------------------------------------------
M1700--M1750: Cognitive items--These items were initially
determined to be clinically appropriate for inclusion in the HHGM but
were later removed due to analysis that showed a counterintuitive
relationship, meaning costs decreased as cognitive status worsened.
This negative relationship with resource use was consistent with most
of the OASIS cognitive items. This analysis is discussed more in depth
in this section below and the full analysis of all of the cognitive
items is found in the technical report.
M1800--M1890: Functional items--These OASIS items include
both ADLs and Instrumental Activities of Daily Living (IADLs). ADLs are
routine activities that people tend to do every day without needing
assistance. There are six basic ADLs: Eating, bathing, dressing,
toileting, transferring (walking) and continence. IADLs are activities
related to independent living and include preparing meals, managing
money, shopping for groceries or personal items, performing light or
heavy housework, doing laundry, and using a telephone. While most of
these items were determined to be clinically appropriate for inclusion
in the HHGM, M1870-M1890 (IADLs) would not be used for functional
status adjustment in the HHGM due to responses having a negative
relationship with resource use (for example, worsening status in
performing IADLs was associated with decreased resource use).
M2030: Management of injectable medications--This OASIS
item would not be used for functional status adjustment in the HHGM
because most of the responses associated with this item reflected less
resource use when the patient increasingly had issues with preparing
and taking injectable medications. We believe that clinically
counterintuitive relationships resulting from responses to OASIS items,
where the expectation would be to see increased resource costs
associated with decreased function or ability, should not be included
in the case mix adjustment.
In addition to the OASIS items listed above, the clinical workgroup
also discussed M2100 (types and sources of assistance-specifically non-
HHA caregiver assistance). Workgroup members agreed that the
availability of non-agency caregiver assistance can be an important
determinant of home health care needs. Caregiver availability
[[Page 35319]]
and assistance was a focus in the Report to Congress ``Medicare Home
Health Study: An Investigation on Access to Care and Payment for
Vulnerable Patient Populations''. Vulnerable patient populations
examined in this study included those patients with minimal or no
caregiver support. Results from this study revealed that HHAs and
physicians stated that family or caregiver issues are an important
contributing factor in the inability to admit or place patients in home
health.\84\ However, 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 alone may be limited.\85\ OASIS-C item M2100 identifies the
ability and willingness of the caregiver(s) (other than home health
agency staff) to provide categories of assistance needed by the
patient, including ADL/IADL assistance, medication administration, and
management of equipment. This particular OASIS item is multi-faceted,
meaning this items requires one of six responses for seven different
types of caregiver assistance. Because the responses to this item
generally are not based on direct observation by the clinician
conducting the assessment, this presents a limitation for use in a case
mix adjustment as the accuracy of the responses cannot be easily
validated. Patients or caregivers may overestimate or underestimate
their ability or willingness to assist in the patient's care. Analysis
of the resource use associated with this item showed ambiguous results
where the same response (``assistance needed, but no caregiver(s)
available'') would be associated with increased resource costs for
certain types of assistance but decreased resource costs for other
types of assistance. We believe this is clinically counterintuitive as
it would be expected that if a need for caregiver assistance exists but
there are no available caregivers, then the result would be an
increased need for resources for all of the types of caregiver
assistance listed on this OASIS item. Analysis of OASIS-C item M2110,
frequency of ADL/IADL assistance, which identifies the frequency of
assistance provided by non-agency caregiver(s), also showed a
counterintuitive and contradicting relationship with M2100. Therefore,
these OASIS items would not be included as part of the functional
status payment adjustment under the HHGM.
---------------------------------------------------------------------------
\84\ Report to Congress Medicare Home Health Study: An
Investigation on Access to Care and Payment for Vulnerable Patient
Populations. Available at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/HomeHealthPPS/Downloads/HH-Report-to-Congress.pdf.
\85\ Ibid.
---------------------------------------------------------------------------
During the analysis of functional case mix adjustment under the
HHGM, a review of the literature revealed growing evidence suggesting
that cognitive dysfunction is an important risk factor in the
development of functional disability and loss of independence.\86\ The
research team analyzed the responses to the OASIS items associated with
cognitive status, but found there was decreased resource use associated
with worsening cognitive status. We decided to further evaluate OASIS
cognitive items (M1700-1750) in addition to functional items (M1800-
1860), as well as other possible OASIS items that may contribute to
overall function status. The following OASIS items were determined to
be indicators of cognitive and functional status that potentially could
be used as case mix adjusters:
---------------------------------------------------------------------------
\86\ Njegovan, V., Man-Song-Hing, M., Mitchell, S., Molnar,
F.(2001). ``The Hierarchy of Functional Loss Associated with
Cognitive Decline in Older Persons''. Journal of Gerontology.
56A(10), M638-643.
---------------------------------------------------------------------------
M066: Age.
M1032: Risk of Hospitalization.
M1220: Understanding of Verbal Content.
M1230: Speech and Oral (Verbal) Expression of Language.
M1700: Cognitive functioning.
M1710: Confusion indicator.
M1720: Anxiety indicator.
M1740: Cognitive, behavioral, and psychiatric symptoms.
M1745: Frequency of disruptive behavior symptoms.
M1750: Receipt of psychiatric nursing services.
M1800: Grooming.
M1810: Current ability to dress upper body safely.
M1820: Current ability to dress lower body safely.
M1830: Bathing.
M1840: Toilet transferring.
M1845: Toilet hygiene.
M1850: Transferring.
M1860: Ambulation/locomotion.
One difficulty in using certain OASIS items (for example, M1700) to
examine relationships with resource use is that they are only
questioned on the Start of Care and Resumption of Care assessments, and
not on follow-up assessments. Therefore, for this analysis, as outlined
in the technical report, we looked back for the most recent period in
the same sequence of periods that was linked to a Start of Care or
Resumption of Care assessment, and carried forward the information from
that assessment to the subsequent periods of care linked to follow-up
(recertification) assessments. Analysis of these items, including
looking at interactions between certain items, continued to show
decreased resource use associated with worsening severity. The research
team believed that clinically counterintuitive relationships to
resource use may have the unintended consequence of discouraging HHAs
to provide the appropriate amount of care to the patients who are
clinically complex and need home health services the most.
For several of the OASIS items listed above, particularly the
functional items, worsening status is associated with higher resource
use, indicating that these items may be useful as adjustors to
construct case-mix weights for the HHGM. However, several responses
within other individual OASIS items had very similar average resource
use. Due to the lack of variation in resource use across certain
responses and because certain responses were infrequently chosen, some
responses were combined into larger response categories to better
capture the relationship between worsening status and resource use.
Responses on these OASIS items were combined using the following
methodology:
Responses that corresponded to a small number of periods
were combined with responses that corresponded to a larger number of
periods and;
Responses that had similar average resource use were
combined together.
The resulting combinations of responses for these OASIS items are
found at Exhibit 7-2 in the HHGM technical report.\87\
---------------------------------------------------------------------------
\87\ https://www.cms.gov/center/provider-type/home-health-agency-hha-center.html?redirect=/center/hha.asp; https://downloads.cms.gov/files/hhgm%20technical%20report%20120516%20sxf.pdf.
---------------------------------------------------------------------------
After making these combinations, the newly combined OASIS items and
resource use were analyzed again to determine if those OASIS items
could be used to help case-mix adjust periods within the HHGM. Results
showed that decreasing functional status, increasing age, and
increasing risk of hospitalization tended to be associated with higher
resource use, while worsening cognitive status tended to be associated
with lower resource use. The relationship between worsening cognitive
status but lower resource use is counterintuitive to existing research
regarding cognitive status and health
[[Page 35320]]
care costs.\88\ To further explore the relationship between the
functional and cognitive OASIS items and resource use, additional
analyses were conducted where the coefficients (that is, resource
costs) associated with the functional and cognitive items were
converted into a table of points to calculate the functional score for
home health periods of care. However, even after controlling for each
OASIS variable (as well as other components of the HHGM), the general
trends between the cognitive and functional items from the other
analyses remained the same. That is, worsening cognitive status was
generally associated with less resource use; worsening functional
status was generally associated with increased resource use; increased
risk of hospitalization was associated with increased resource use; and
age was not associated with either increased or decreased resource use.
The summary statistics of these analyses are found at Exhibit 7-3 of
the technical report, ``Overview of the Home Health Groupings
Model''.\89\ Therefore, we decided not to include those OASIS items
with these types of inverse relationships to resource costs as part of
the adjustment to the HHGM period payment. However, given the research
support and clinical input from home health clinicians, we will
continue to analyze the inclusion of cognitive items into the HHGM case
mix adjustment. The analyses of the complete list of all OASIS items
analyzed can be found in the Appendix Exhibits A7-1 and A7-2 of the
technical report mentioned above.
---------------------------------------------------------------------------
\88\ P.P. Pandharipande, T.D. Girard, J.C. Jackson, A. Morandi,
J.L. Thompson, B.T. Pun, N.E. Brummel, C.G. Hughes, E.E.
Vasilevskis, A.K. Shintani, K.G. Moons, S.K. Geevarghese, A.
Canonico, R.O. Hopkins, G.R. Bernard, R.S. Dittus, and E.W. Ely.
(2013). ``Long-Term Cognitive Impairment after Critical Illness''.
The New England Journal of Medicine. 369(14), 1306-14.
\89\ Abt Associates. ``Overview of the Home Health Groupings
Model.'' Medicare Home Health Prospective Payment System: Case-Mix
Methodology Refinements. Cambridge, MA, November 18, 2016. Accessed
on April 27, 2017 at https://www.cms.gov/center/provider-type/home-health-agency-hha-center.html?redirect=/center/hha.asp; https://downloads.cms.gov/files/hhgm%20technical%20report%20120516%20sxf.pdf.
---------------------------------------------------------------------------
On the basis of input from the clinical workgroup and these
analytic results, all cognitive items, functional items with a negative
relationship with resource use, and age were removed and the model was
re-estimated. Each OASIS item included in the final model has a
positive relationship with resource use, meaning as functional status
declines (as measured by a higher response category), periods have more
resource use on average. Additionally, periods with a higher risk of
hospitalization (meaning four or more items checked on M1033) are
associated with higher resource use compared with periods with a lower
risk of hospitalization. This indicates that these items could be used
to help risk adjust a period's payment and help determine case-mix
weights for the HHGM. As such, we are proposing that the following
OASIS items be included as part of the functional payment adjustment
under the proposed HHGM:
M1800: Grooming.
M1810: Current Ability to Dress Upper Body.
M1820: Current Ability to Dress Lower Body.
M1830: Bathing.
M1840: Toilet Transferring.
M1850: Transferring.
M1860: Ambulation/Locomotion.
M1032 (M1033 in OASIS-C1): Risk of Hospitalization.\90\
---------------------------------------------------------------------------
\90\ In Version OASIS C-1, two responses were excluded:
``currently reports exhaustion'' and ``other risks not listed in 1-
8''.
---------------------------------------------------------------------------
While the original analyses of these OASIS functional items were
conducted using CY 2013 data from the OASIS-C version (as presented in
the technical report), the updated analyses for CY 2016 reported in
Tables 36, 37, and 38 are based on data obtained from OASIS C-1. While
the OASIS item number for ``Risk of Hospitalization'' changed from
M1032 (in OASIS C) to M1033 (in OASIS C-1), the remaining OASIS items
(and item numbers) used for this functional adjustment analysis are the
same. As discussed earlier in this section, to facilitate the
interpretation of this analysis of the functional items used to
construct the case mix weights, the results of this analysis were
converted into a table of points that can be used to calculate the
functional score for a home health period. Table 36 shows the points
for 2013 and 2016 for those items associated with increased resource
use using a reduced set of OASIS C-1 items:
Table 36--OASIS Points Table for Those Items Associated With Increased Resource Use Using a Reduced Set of OASIS
Items, CY 2013 and CY 2016
----------------------------------------------------------------------------------------------------------------
Percent of Percent of
periods in periods in
Variable Response Points (2013) Points (2016) 2013 with 2016 with
category this response this response
category (%) category (%)
----------------------------------------------------------------------------------------------------------------
M1800: Grooming................. 1 3 4 41.5 51.9
M1810: Current Ability to Dress 1 4 6 46.6 55.6
Upper Body.....................
M1820: Current Ability to Dress 1 7 6 52.1 57.5
Lower Body.....................
2 10 12 16.4 19.6
M1830: Bathing.................. 1 6 4 24.4 20.3
2 17 14 46.1 51.6
3 25 22 19.1 21.9
M1840: Toilet Transferring...... 1 4 5 20.3 28.2
M1850: Transferring............. 1 7 4 61.6 47.7
2 13 9 29.2 48.0
M1860: Ambulation/Locomotion.... 1 13 12 37.7 29.0
2 17 15 33.0 47.8
3 27 27 12.7 14.2
M1032 (M1033 for OASIS C-1): 4 or more 12 11 12.6 16.3
Risk of Hospitalization........ items checked
----------------------------------------------------------------------------------------------------------------
[[Page 35321]]
Similar to the current case-mix adjustment methodology, the points
generated in Table 36 were then used to create a functional score for
each home health period of care in the HHGM. That is, a home health
period of care receives points based on each of the responses
associated with the OASIS items listed above. The sum of all of these
points results in a functional score which is used in the HHGM to group
home health periods into a functional level. As part of the HHGM case-
mix adjustment, we are proposing to assign points for each of the
responses to the proposed OASIS functional items and to sum up the
points to create a functional score for the period of care. Whereas the
results presented in the technical report showed that the number of
functional levels varied by clinical group, continued analysis
ultimately established three functional levels for each of the clinical
groups--low, medium and high, with approximately one third of home
health periods from each of the clinical groups within each level. This
means home health periods in the low level have responses for the above
OASIS items that are associated with the lowest resource use on
average. Home health periods in the high level have responses on the
above OASIS items that are associated with the highest resource use on
average. We are proposing to use the three functional levels of low,
medium, and high, based on the CY 2016 data for each of the clinical
groups. Table 37 shows the functional thresholds for each functional
level by clinical group for CYs 2013 and 2016.
Table 37--Thresholds for Functional Levels by Clinical Group, CY 2013 and CY 2016
----------------------------------------------------------------------------------------------------------------
Points (2013 Points (2016
Clinical group Level data) data)
----------------------------------------------------------------------------------------------------------------
MMTA........................................... Low............................ 0-36 0-36
Medium......................... 37-55 37-54
High........................... 56+ 55+
Behavioral Health.............................. Low............................ 0-30 0-38
Medium......................... 31-55 39-57
High........................... 56+ 58+
Complex Nursing Interventions.................. Low............................ 0-33 0-36
Medium......................... 34-60 37-59
High........................... 61+ 60+
Musculoskeletal Rehabilitation................. Low............................ 0-37 0-39
Medium......................... 38-55 40-55
High........................... 56+ 56+
Neuro Rehabilitation........................... Low............................ 0-48 0-49
Medium......................... 49-67 50-66
High........................... 68+ 67+
Wound.......................................... Low............................ 0-41 0-42
Medium......................... 42-65 43-65
High........................... 66+ 66+
----------------------------------------------------------------------------------------------------------------
Table 38 shows the average resource use by clinical group and
functional level for CY 2016:
TABLE 38--Average Resource Use by Clinical Group and Functional Level, CY 2016
--------------------------------------------------------------------------------------------------------------------------------------------------------
Standard 25th 75th
Mean resource Frequency of Percent of deviation of Percentile of Median Percentile of
use periods periods resource use resource use resource use resource use
--------------------------------------------------------------------------------------------------------------------------------------------------------
MMTA--Low............................... $1,216.76 1,683,279 19.48 $1,091.11 $880.56 $507.63 $1,589.76
MMTA--Medium............................ 1,466.19 1,594,451 18.45 1,182.78 1,163.49 617.07 1,979.71
MMTA--High.............................. 1,637.21 1,628,441 18.84 1,284.34 1,334.00 695.10 2,216.12
Behavioral Health--Low.................. 963.97 100,572 1.16 847.72 679.14 407.74 1,255.47
Behavioral Health--Medium............... 1,308.10 94,030 1.09 1,018.11 1,040.79 543.96 1,780.03
Behavioral Health--High................. 1,501.87 94,911 1.10 1,107.73 1,237.97 662.86 2,047.39
Complex--Low............................ 1,425.30 120,528 1.39 1,356.53 1,019.77 582.12 1,795.04
Complex--Medium......................... 1,797.33 106,056 1.23 1,593.76 1,354.89 739.39 2,340.46
Complex--High........................... 1,917.72 109,665 1.27 1,723.31 1,430.70 756.59 2,536.16
MS Rehab--Low........................... 1,519.02 478,059 5.53 1,048.29 1,298.20 753.88 2,025.52
MS Rehab--Medium........................ 1,730.99 480,676 5.56 1,121.66 1,534.42 921.87 2,296.70
MS Rehab--High.......................... 1,891.42 472,078 5.46 1,241.57 1,671.24 1,004.59 2,501.81
Neuro--Low.............................. 1,594.59 283,573 3.28 1,169.30 1,327.08 739.60 2,137.34
Neuro--Medium........................... 1,847.36 233,398 2.70 1,271.54 1,581.08 914.70 2,487.14
Neuro--High............................. 2,020.14 255,608 2.96 1,473.75 1,682.68 947.61 2,715.74
Wound--Low.............................. 1,860.42 305,556 3.54 1,550.96 1,436.36 861.98 2,345.97
Wound--Medium........................... 2,052.45 303,435 3.51 1,603.05 1,646.76 980.27 2,634.01
Wound--High............................. 2,258.66 297,791 3.45 1,814.01 1,771.12 1,043.72 2,897.54
---------------------------------------------------------------------------------------------------------------
Total............................... 1,585.48 8,642,107 100.00 1,289.23 1,262.65 671.96 2,119.49
--------------------------------------------------------------------------------------------------------------------------------------------------------
[[Page 35322]]
Like the annual recalibration of the case-mix weights under the
current HH PPS, we expect that annual recalibrations would also be made
to the HHGM case-mix weights. If the HHGM is finalized, we will
continue to analyze all of the components of the case-mix adjustment,
including adjustment for functional status, and would make refinements
as necessary to ensure that payment for home health periods are in
alignment with costs. We invite comments on the proposed OASIS items
and the associated points and thresholds used to group patients into
three functional levels under the HHGM, as outlined above.
8. Comorbidity Adjustment
The HHGM groups home health periods based on the primary reason for
home health care (principal diagnosis), functional level, admission
source, and timing. To further account for differences in resource use
based on patient characteristics in the development of the HHGM, we
analyzed the presence of comorbidities as another factor that could
impact resource utilization and costs. We conducted a comprehensive
literature review examining published, peer-reviewed research regarding
the relationship between comorbidity and resource use.\91\ This review
also included findings on those conditions that impact health care
resource utilization. Based on this review and findings, we propose a
comorbidity adjustment to account for higher costs associated with
comorbidities.
---------------------------------------------------------------------------
\91\ Appendix Exhibit A9-1, ``Overview of the Home Health
Groupings Model'', 2016. 12-23-12-26. https://www.cms.gov/center/
provider-type/home-health-agency-hha-center.html.
---------------------------------------------------------------------------
A comorbidity is most often defined as two or more coexisting
medical conditions or disease processes that are in addition to an
initial diagnosis.\92\ Typically, a comorbidity is a condition(s) in
which there is no direct correlation in the treatment of the principal
diagnosis, but the presence of that condition(s) may impact the home
health plan of care in terms of resource utilization and costs. With
aging, the presence of comorbidity increases markedly because the
frequency of individual conditions arises with age. While the elderly
are far more likely to have multiple comorbidities, comorbidities also
are prevalent in Medicare beneficiaries under the age of 65 who have
intellectual and physical disabilities.\93\ Research has repeatedly
shown that comorbidity is associated with high health care utilization
and expenditures.\94\ Additionally, comorbidity is tied to worse health
outcomes and the need for more complex treatment and disease
management, which in turn results in higher health care costs.\95\
Patients with comorbidities tend to be high users of home health visits
and overall Medicare spending increases with the number of chronic
conditions.\96\
---------------------------------------------------------------------------
\92\ Mosby's Medical Dictionary, 9th edition. (copyright)2009,
Elsevier.
\93\ Cooper, S., McLean, G., Guthrie, B., McConnachie, A.,
Mercer, S., Sullivan, F., Morrison, J. (2015). ``Multiple physical
and mental health comorbidity in adults with intellectual
disabilities''. BMC Family Practice. 16(110), 1-11. doi 10.1186/
s12875-015-0329-3.
\94\ Fried, L., Ferrucci, L., Darer, J., Williamson, J.,
Anderson, G. (2004). ``Untangling the Concepts of Disability,
Frailty, and Comorbidity: Implications for Improved Targeting and
Care''. Journal of Gerontology. 59(3), 255-263.
\95\ Starfield, B., Lemke, K., Bernhardt, T., Foldes, S.,
Forrest, C., Weiner, J. (2003). ``Comorbidity: Implications for the
Importance of Primary Care in Case Management''. Annals of Family
Medicine. 1(1), 8-14.
\96\ https://www.cdc.gov/chronicdisease/about/multiple-chronic.html.
---------------------------------------------------------------------------
In the home health setting, information regarding the patient's
health conditions for which home health services are provided are
assessed and documented by skilled clinicians on the OASIS. These
conditions would include secondary diagnoses in addition to the
principal diagnosis supporting the need for home health services. As
such, exploratory analyses for the HHGM determined that secondary
diagnoses (that is, comorbidities) provide additional information that
can predict resource use even after controlling for the period's
clinical group. We examined multiple approaches for a comorbidity
adjustment in the HHGM and the analyses on these approaches is found in
the ``Overview of the Home Health Groupings Model'' technical report
found on the HHA Center Web page. Based on the results of these
analyses, we moved towards the development of a home health specific
comorbidity list for the HHGM comorbidity adjustment.
For the analysis of a comorbidity adjustment in the HHGM, some
diagnosis exclusions were made. Under the HHGM, certain reported
principal diagnosis codes, including some ICD-10-CM ``R-codes'' (R00-
R99) which identify symptoms and abnormal clinical findings, would be
considered a ``questionable encounter'', meaning these codes may be too
vague to group the home health period, subject to sequencing or other
ICD-10-CM coding conventions, not a Medicare-covered diagnosis, or a
condition unlikely to require home health services. For these
``questionable encounters'', more information was needed to assign the
period to a clinical group. This meant, for analysis purposes only, we
looked at the secondary diagnoses to assign the home health period to
one of the six clinical groups. As such, those periods with a principal
diagnosis that was determined to be a ``questionable encounter'' code
were excluded from our comorbidity adjustment analysis. However, if the
HHGM is finalized, we are proposing that claims submitted with
principal reported diagnosis codes that are considered ``questionable
encounters'' would be returned to the provider for more definitive
coding. Once the claim is resubmitted without a principal diagnosis
that is considered a ``questionable encounter'', the home health period
would be grouped into one of the six clinical groups. The secondary
diagnoses on those resubmitted claims would then be eligible for the
comorbidity adjustment.
Another exclusion from this comorbidity analysis included those
secondary diagnoses that had the same three character ICD-10-CM code as
the diagnosis used to assign a case to a particular clinical group
(that is, musculoskeletal rehab, neuro/stroke rehab, wounds, behavioral
health, complex nursing interventions, and MMTA). An additional
exclusion was added that applied to diagnoses that identify an
unspecified site or side (meaning the code is defined by laterality or
site specificity). There are ICD-10-CM codes that are specific to site,
laterality, and proximal versus distal parts of the body. For example,
L89.004, Pressure ulcer of unspecified elbow, stage 4, can be coded to
identify whether the pressure ulcer is on the left or right elbow. ICD-
10 CM coding guidelines state to report diagnoses to the greatest level
of specificity. The home health clinician should be able to identify
the specific side or body part involved through either direct
assessment or of a query of the certifying physician.
Finally, an exclusion was added for some secondary diagnoses that
would not be considered a comorbidity if reported with certain Z codes.
For example, if Z96.651, presence of right artificial knee joint, is
reported as secondary, it would not be considered a comorbidity if
Z47.1, aftercare following joint replacement surgery, was reported as
the principal diagnosis. The secondary diagnosis in this scenario is
not a comorbidity because this secondary diagnosis explains the reason
for the aftercare. We are utilizing this approach to minimize the
unintended consequence of providers reporting comorbidities that are
duplicative of the
[[Page 35323]]
principal diagnosis, or are a further description of the principal
diagnosis, which could potentially overestimate the actual resources
needed for a home health period and could result in inaccurate payment.
Using the research from the comprehensive literature review, we
identified common chronic comorbid conditions frequently cited as
drivers of increased health care resource utilization, including
coronary artery disease, congestive heart failure, diabetes, COPD,
asthma, chronic wounds, and depression.\97\ In addition to chronic
comorbid conditions, other acute comorbid conditions have been shown to
affect overall resource utilization as well. These conditions include
pneumonia, Clostridium difficile (c-diff), and Methicillin-resistant
Staphylococcus aureus (MRSA).\98\ After compiling a list of both acute
and chronic comorbid diagnoses that could affect home health resource
utilization, we conducted initial analyses looking at controlling for
the presence of the individual diagnoses. However, these analyses
showed some counterintuitive relationships with resource use, meaning
the presence of certain comorbidities showed that there would be less
resource use than if the comorbidity was not present.
---------------------------------------------------------------------------
\97\ Center for Healthcare Research and Transformation. (2010)
``Healthcare Cost Drivers: Chronic Disease, Comorbidity, and Health
Risk Factors in the U.S. and Michigan.'' https://www.chrt.org/publication/health-care-cost-drivers-chronic-disease-comorbidity-health-risk-factors-u-s-michigan/.
\98\ Drikoningen, J., Rohde, G., (2010). ``Pneumococcal
Infection in Adults: Burden of Disease''. Clinical Microbiology and
Infection. 45-51. Kyne, L., Hamel, M.B., Polavaram, R., Kelly, C.
(2002). ``Health Care Costs and Mortality Associated with Nosocomial
Diarrhea due to Clostridium difficile''. Clinical Infectious
Diseases. 346-353.
---------------------------------------------------------------------------
Because the core of the HHGM is a clinical one, CMS clinicians
utilized the principles of patient assessment by body systems and their
associated diseases, conditions, and injuries as a way to examine
potential clinically relevant relationships. Next, we combined those
individual diagnoses into larger categories utilizing the body systems
as a clinically intuitive way to consider what diagnoses potentially
could impact the home health plan of care and resource utilization.
When combining the individual diagnoses into larger comorbidity
categories, the counterintuitive relationships decreased. These broad
body system categories include conditions, diseases, and injuries that
affect each of the individual body systems (for example, heart
disease). Neoplasms and infectious diseases were given their own
discrete categories because of their potential to affect more than one
body system. The broad categories used to group comorbidities within
the HHGM were further refined by grouping similar diagnoses within the
broad categories into subcategories. The subcategories allowed for
additional refinement of diagnoses to include as part of the home
health specific list. Subcategories were distinguished primarily (but
not exclusively) by the first three characters of the ICD-10-CM
diagnosis code to represent related conditions within the same body
system. For example, subcategory Heart 10 includes diagnoses associated
with various cardiac arrhythmias. The home health specific comorbidity
list includes 13 broad body system based categories and 116 total
subcategories using ICD-10-CM diagnosis codes. The broad categories
used to group comorbidities within the HHGM include the following:
Heart Disease (11 subcategories).
Respiratory Disease (9 subcategories).
Circulatory Disease and Blood Disorders (12
subcategories).
Cerebral Vascular Disease (4 subcategories).
Gastrointestinal Disease (9 subcategories).
Neurological Disease and Associated Conditions (11
subcategories).
Endocrine Disease (6 subcategories).
Neoplasm (24 subcategories).
Genitourinary and Renal Disease (5 subcategories).
Skin Disease (5 subcategories).
Musculoskeletal Disease or Injury (5 subcategories).
Behavioral Health (11 subcategories).
Infectious Disease (4 subcategories).
The secondary diagnoses listed on the OASIS that are attributed to
any one of the listed subcategories were used to identify whether a
period fell into one or more comorbidity categories and subcategories.
For the purpose of evaluating these identified comorbidities for
inclusion in the HHGM, we assigned the CY 2016 home health periods that
reported a secondary diagnosis included on this home health specific
list to a comorbidity subcategory and subsequently dropped any
subcategories that were in less than 0.1 percent of periods. This was
done because low volume leads to instability in our estimates of how
resource use is related to the comorbidity. A regression model was used
to determine the relationship between the remaining subcategories and
resource use. After this analysis, we dropped comorbidity subcategories
that were not statistically significant with regards to their
relationship to resource use (a coefficient with a p-value greater than
0.05). After these exclusions, we kept the subcategories associated
with increased resource use that was at least as high as the median
resource use, as they indicated a direct relationship between the
comorbidity subcategories and resource utilization. These remaining
subcategories would receive a comorbidity adjustment. As such, there
are 15 subcategories that meet the current criteria for the comorbidity
adjustment in the HHGM. This is a decreased number of subcategories
that were presented in the technical report where 29 subcategories met
the criteria to qualify for the comorbidity adjustment. The comorbidity
analysis presented in the technical report was based on CY 2013 data
and used ICD-9-CM diagnosis codes. There are several potential reasons
for this decrease including that the analysis exclusions for the 2016
analysis were slightly different than were used in the technical
report. Another potential reason for the decrease in subcategories may
be due to diagnosis exclusions based on changes from ICD-9-CM to ICD-
10-CM with regards to specificity. Some of this decrease could be
related to the changes in case-mix weights from 2013 to 2016 where
secondary conditions that received clinical points in 2013 may not have
had any associated points in 2016 and hence, there would be no
incentive to report those conditions. The analysis on the CY 2013 and
CY 2016 data, including all of the diagnoses and their assigned
subcategories is posted on the HHA Center Web page.\99\ The 15
subcategories included in the comorbidity adjustment in the HHGM are as
follows:
---------------------------------------------------------------------------
\99\ https://www.cms.gov/center/provider-type/home-health-
agency-hha-center.html.
---------------------------------------------------------------------------
Heart Disease 1: Includes hypertensive heart disease.
Cerebral Vascular Disease 4: Includes sequelae of
cerebrovascular disease.
Circulatory Disease and Blood Disorders 9: Includes venous
embolisms and thrombosis.
Circulatory Disease and Blood Disorders 10: Includes
varicose veins of lower extremities with ulcers and inflammation, and
esophageal varices.
Circulatory Disease and Blood Disorders 11: Includes
lymphedema.
Endocrine Disease 2: Includes diabetes with complications
due to an underlying condition.
Neoplasm 18: Includes secondary malignant neoplasms.
[[Page 35324]]
Neurological Disease and Associated Conditions 5: Includes
secondary parkinsonism.
Neurological Disease and Associated Conditions 7: Includes
encephalitis, myelitis, encephalomyelitis, and hemiplegia, paraplegia,
and quadriplegia.
Neurological Disease and Associated Conditions 10:
Includes diabetes with neurological complications.
Respiratory Disease 7: Includes pneumonia, pneumonitis,
and pulmonary edema.
Skin Disease 1: Includes cutaneous abscesses, and
cellulitis.
Skin Disease 2: Includes stage one pressure ulcers.
Skin Disease 3: Includes atherosclerosis with gangrene.
Skin Disease 4: Includes unstageable and stages two
through four pressure ulcers.
We propose that if a period had at least one secondary diagnosis
reported on the home health claim that fell into one of the 15
subcategories, that period would receive a comorbidity adjustment to
account for higher costs associated with the comorbidity. The
comorbidity adjustment amount would be the same across all of the
subcategories. A period would receive only one comorbidity adjustment
regardless of the number of secondary diagnoses reported on the home
health claim that fell into one of the 15 subcategories. Table 39 shows
information on resource use for periods with and without the
comorbidity adjustment.
TABLE 39--Frequency of Comorbidity Groups and Distribution of Average Resource Use
--------------------------------------------------------------------------------------------------------------------------------------------------------
Standard 25th 75th
Comorbidity group Mean resource Frequency of Percent of deviation of Percentile of Median Percentile of
use periods periods resource use resource use resource use resource use
--------------------------------------------------------------------------------------------------------------------------------------------------------
No Comorbidity Adjustment............... $1,534.17 7,365,806 85.23 $1,228.43 $1,227.35 $653.57 $2,061.88
Comorbidity Adjustment.................. 1,881.60 1,276,301 14.77 1,562.89 1,484.39 803.15 2,475.20
---------------------------------------------------------------------------------------------------------------
Total............................... 1,585.48 8,642,107 100.00 1,289.23 1,262.65 671.96 2,119.49
--------------------------------------------------------------------------------------------------------------------------------------------------------
The HHGM payment adjustment for comorbidities is predicated on the
presence of one of the identified diagnoses within the subcategories
associated with increased resource use at or above the median. If there
is no reported diagnosis that meets the comorbidity adjustment
criteria, the period would not qualify for the payment adjustment. We
consider this comorbidity adjustment component of the proposed HHGM to
be fluid, where OASIS-reported secondary diagnoses may be removed from,
or added to the home health specific comorbidity list dependent upon
the relationship between the comorbidity and resource costs. If the
HHGM is finalized and implemented, we anticipate there may be
behavioral shifts in secondary diagnosis reporting and the proposed
comorbidity list and its associated subcategories may change to capture
resource utilization associated with these or other conditions. We
invite comments on the proposed comorbidity diagnoses, including
additions or subtractions to the proposed home health specific list,
and this comorbidity adjustment approach under the HHGM.
9. Change in the Low-Utilization Payment Adjustment (LUPA) Threshold
An episode with four or fewer visits is paid the national per visit
amount by discipline, adjusted by the appropriate wage index based on
the site of service of the beneficiary, instead of the full episode
amount. Such payment adjustments are called Low Utilization Payment
Adjustments (LUPAs). While the proposed HHGM system would still include
LUPA payments, we are proposing that the approach to calculating the
LUPA thresholds would change in the HHGM because of the proposed change
in the unit of payment to 30-day periods from 60-day episodes. Whereas
LUPAS are paid for all episodes consisting of four or fewer visits
under the current payment system, in order to receive full episode
amount under the HHGM (rather than receive a LUPA where the episode
would be paid the national per visit amount by discipline) we propose
to vary the LUPA threshold for a 30-day period under the HHGM depending
on the HHGM payment group to which it is assigned. The 30-day periods
have substantially more instances of four or fewer visits than 60-day
episodes. To create LUPA thresholds, 30-day periods (including those
that were LUPAs in the current payment system) were grouped into the
144 different HHGM payment groups. For each payment group, we propose
to set the LUPA threshold at the 10th percentile value of visits or 2
visits, whichever is higher. In the current payment system
approximately 8 percent of episodes are LUPAs. Under the HHGM, we
propose the 10th percentile value of visits or 2 visits, whichever is
higher, to target approximately the same percentage of LUPAs
(approximately 7 percent of 30-day periods would be LUPAs (assuming no
behavior change)).
For example, for 30-day periods of care in the payment group
corresponding to ``MMTA- Functional Level Medium--Early Timing--
Institutional Admission--No Comorbidity Adjustment'', the threshold is
four visits. If 30-day periods assigned to that particular payment
group had three or fewer visits they would be paid using the national
per-visit rates in section III.C.3 of this proposed rule instead of the
case-mix adjusted 30-day payment amount. We propose that the LUPA
thresholds for each HHGM payment group would be re-evaluated every year
based on the most current, complete utilization data available. The
LUPA thresholds, based on the most current utilization data available
(CY 2016 data as of March 17, 2017), for each corresponding HIPPS code,
are listed in Table 40. We would propose updated LUPA thresholds using
the most current, complete utilization data available at the time of
rulemaking.
[[Page 35325]]
Table 40--Proposed LUPA Thresholds for the Proposed HHGM Payment Groups Based on CY 2016 Utilization Data
----------------------------------------------------------------------------------------------------------------
Threshold
(10th
HIPPS Clinical group and Timing and admission Comorbidity adjustment percentile or
functional level source 2--whichever
is higher)
----------------------------------------------------------------------------------------------------------------
1AAN..................... MMTA--Low........... Early--Community.... No....................... 4
1AAY..................... MMTA--Low........... Early--Community.... Yes...................... 4
1ABN..................... MMTA--Medium........ Early--Community.... No....................... 4
1ABY..................... MMTA--Medium........ Early--Community.... Yes...................... 4
1ACN..................... MMTA--High.......... Early--Community.... No....................... 4
1ACY..................... MMTA--High.......... Early--Community.... Yes...................... 4
1BAN..................... Neuro--Low.......... Early--Community.... No....................... 4
1BAY..................... Neuro--Low.......... Early--Community.... Yes...................... 5
1BBN..................... Neuro--Medium....... Early--Community.... No....................... 5
1BBY..................... Neuro--Medium....... Early--Community.... Yes...................... 5
1BCN..................... Neuro--High......... Early--Community.... No....................... 5
1BCY..................... Neuro--High......... Early--Community.... Yes...................... 5
1CAN..................... Wound--Low.......... Early--Community.... No....................... 5
1CAY..................... Wound--Low.......... Early--Community.... Yes...................... 4
1CBN..................... Wound--Medium....... Early--Community.... No....................... 5
1CBY..................... Wound--Medium....... Early--Community.... Yes...................... 5
1CCN..................... Wound--High......... Early--Community.... No....................... 5
1CCY..................... Wound--High......... Early--Community.... Yes...................... 5
1DAN..................... Complex--Low........ Early--Community.... No....................... 3
1DAY..................... Complex--Low........ Early--Community.... Yes...................... 3
1DBN..................... Complex--Medium..... Early--Community.... No....................... 3
1DBY..................... Complex--Medium..... Early--Community.... Yes...................... 3
1DCN..................... Complex--High....... Early--Community.... No....................... 3
1DCY..................... Complex--High....... Early--Community.... Yes...................... 3
1EAN..................... MS Rehab--Low....... Early--Community.... No....................... 5
1EAY..................... MS Rehab--Low....... Early--Community.... Yes...................... 5
1EBN..................... MS Rehab--Medium.... Early--Community.... No....................... 5
1EBY..................... MS Rehab--Medium.... Early--Community.... Yes...................... 5
1ECN..................... MS Rehab--High...... Early--Community.... No....................... 5
1ECY..................... MS Rehab--High...... Early--Community.... Yes...................... 5
1FAN..................... Behavioral Health-- Early--Community.... No....................... 3
Low.
1FAY..................... Behavioral Health-- Early--Community.... Yes...................... 3
Low.
1FBN..................... Behavioral Health-- Early--Community.... No....................... 4
Medium.
1FBY..................... Behavioral Health-- Early--Community.... Yes...................... 4
Medium.
1FCN..................... Behavioral Health-- Early--Community.... No....................... 4
High.
1FCY..................... Behavioral Health-- Early--Community.... Yes...................... 4
High.
2AAN..................... MMTA--Low........... Early--Institutional No....................... 3
2AAY..................... MMTA--Low........... Early--Institutional Yes...................... 4
2ABN..................... MMTA--Medium........ Early--Institutional No....................... 4
2ABY..................... MMTA--Medium........ Early--Institutional Yes...................... 5
2ACN..................... MMTA--High.......... Early--Institutional No....................... 4
2ACY..................... MMTA--High.......... Early--Institutional Yes...................... 4
2BAN..................... Neuro--Low.......... Early--Institutional No....................... 5
2BAY..................... Neuro--Low.......... Early--Institutional Yes...................... 5
2BBN..................... Neuro--Medium....... Early--Institutional No....................... 6
2BBY..................... Neuro--Medium....... Early--Institutional Yes...................... 6
2BCN..................... Neuro--High......... Early--Institutional No....................... 5
2BCY..................... Neuro--High......... Early--Institutional Yes...................... 5
2CAN..................... Wound--Low.......... Early--Institutional No....................... 4
2CAY..................... Wound--Low.......... Early--Institutional Yes...................... 4
2CBN..................... Wound--Medium....... Early--Institutional No....................... 5
2CBY..................... Wound--Medium....... Early--Institutional Yes...................... 5
2CCN..................... Wound--High......... Early--Institutional No....................... 4
2CCY..................... Wound--High......... Early--Institutional Yes...................... 5
2DAN..................... Complex--Low........ Early--Institutional No....................... 3
2DAY..................... Complex--Low........ Early--Institutional Yes...................... 4
2DBN..................... Complex--Medium..... Early--Institutional No....................... 4
2DBY..................... Complex--Medium..... Early--Institutional Yes...................... 4
2DCN..................... Complex--High....... Early--Institutional No....................... 4
2DCY..................... Complex--High....... Early--Institutional Yes...................... 4
2EAN..................... MS Rehab--Low....... Early--Institutional No....................... 5
2EAY..................... MS Rehab--Low....... Early--Institutional Yes...................... 5
2EBN..................... MS Rehab--Medium.... Early--Institutional No....................... 6
2EBY..................... MS Rehab--Medium.... Early--Institutional Yes...................... 6
2ECN..................... MS Rehab--High...... Early--Institutional No....................... 6
2ECY..................... MS Rehab--High...... Early--Institutional Yes...................... 7
2FAN..................... Behavioral Health-- Early--Institutional No....................... 3
Low.
[[Page 35326]]
2FAY..................... Behavioral Health-- Early--Institutional Yes...................... 3
Low.
2FBN..................... Behavioral Health-- Early--Institutional No....................... 4
Medium.
2FBY..................... Behavioral Health-- Early--Institutional Yes...................... 5
Medium.
2FCN..................... Behavioral Health-- Early--Institutional No....................... 4
High.
2FCY..................... Behavioral Health-- Early--Institutional Yes...................... 4
High.
3AAN..................... MMTA--Low........... Late--Community..... No....................... 2
3AAY..................... MMTA--Low........... Late--Community..... Yes...................... 2
3ABN..................... MMTA--Medium........ Late--Community..... No....................... 2
3ABY..................... MMTA--Medium........ Late--Community..... Yes...................... 2
3ACN..................... MMTA--High.......... Late--Community..... No....................... 2
3ACY..................... MMTA--High.......... Late--Community..... Yes...................... 2
3BAN..................... Neuro--Low.......... Late--Community..... No....................... 2
3BAY..................... Neuro--Low.......... Late--Community..... Yes...................... 2
3BBN..................... Neuro--Medium....... Late--Community..... No....................... 2
3BBY..................... Neuro--Medium....... Late--Community..... Yes...................... 3
3BCN..................... Neuro--High......... Late--Community..... No....................... 2
3BCY..................... Neuro--High......... Late--Community..... Yes...................... 3
3CAN..................... Wound--Low.......... Late--Community..... No....................... 3
3CAY..................... Wound--Low.......... Late--Community..... Yes...................... 3
3CBN..................... Wound--Medium....... Late--Community..... No....................... 3
3CBY..................... Wound--Medium....... Late--Community..... Yes...................... 3
3CCN..................... Wound--High......... Late--Community..... No....................... 3
3CCY..................... Wound--High......... Late--Community..... Yes...................... 3
3DAN..................... Complex--Low........ Late--Community..... No....................... 2
3DAY..................... Complex--Low........ Late--Community..... Yes...................... 2
3DBN..................... Complex--Medium..... Late--Community..... No....................... 2
3DBY..................... Complex--Medium..... Late--Community..... Yes...................... 2
3DCN..................... Complex--High....... Late--Community..... No....................... 2
3DCY..................... Complex--High....... Late--Community..... Yes...................... 2
3EAN..................... MS Rehab--Low....... Late--Community..... No....................... 2
3EAY..................... MS Rehab--Low....... Late--Community..... Yes...................... 2
3EBN..................... MS Rehab--Medium.... Late--Community..... No....................... 2
3EBY..................... MS Rehab--Medium.... Late--Community..... Yes...................... 2
3ECN..................... MS Rehab--High...... Late--Community..... No....................... 2
3ECY..................... MS Rehab--High...... Late--Community..... Yes...................... 3
3FAN..................... Behavioral Health-- Late--Community..... No....................... 2
Low.
3FAY..................... Behavioral Health-- Late--Community..... Yes...................... 2
Low.
3FBN..................... Behavioral Health-- Late--Community..... No....................... 2
Medium.
3FBY..................... Behavioral Health-- Late--Community..... Yes...................... 2
Medium.
3FCN..................... Behavioral Health-- Late--Community..... No....................... 2
High.
3FCY..................... Behavioral Health-- Late--Community..... Yes...................... 3
High.
4AAN..................... MMTA--Low........... Late--Institutional. No....................... 3
4AAY..................... MMTA--Low........... Late--Institutional. Yes...................... 3
4ABN..................... MMTA--Medium........ Late--Institutional. No....................... 3
4ABY..................... MMTA--Medium........ Late--Institutional. Yes...................... 3
4ACN..................... MMTA--High.......... Late--Institutional. No....................... 3
4ACY..................... MMTA--High.......... Late--Institutional. Yes...................... 3
4BAN..................... Neuro--Low.......... Late--Institutional. No....................... 4
4BAY..................... Neuro--Low.......... Late--Institutional. Yes...................... 4
4BBN..................... Neuro--Medium....... Late--Institutional. No....................... 4
4BBY..................... Neuro--Medium....... Late--Institutional. Yes...................... 4
4BCN..................... Neuro--High......... Late--Institutional. No....................... 4
4BCY..................... Neuro--High......... Late--Institutional. Yes...................... 4
4CAN..................... Wound--Low.......... Late--Institutional. No....................... 3
4CAY..................... Wound--Low.......... Late--Institutional. Yes...................... 3
4CBN..................... Wound--Medium....... Late--Institutional. No....................... 4
4CBY..................... Wound--Medium....... Late--Institutional. Yes...................... 4
4CCN..................... Wound--High......... Late--Institutional. No....................... 4
4CCY..................... Wound--High......... Late--Institutional. Yes...................... 4
4DAN..................... Complex--Low........ Late--Institutional. No....................... 2
4DAY..................... Complex--Low........ Late--Institutional. Yes...................... 3
4DBN..................... Complex--Medium..... Late--Institutional. No....................... 3
4DBY..................... Complex--Medium..... Late--Institutional. Yes...................... 3
4DCN..................... Complex--High....... Late--Institutional. No....................... 3
4DCY..................... Complex--High....... Late--Institutional. Yes...................... 3
4EAN..................... MS Rehab--Low....... Late--Institutional. No....................... 4
4EAY..................... MS Rehab--Low....... Late--Institutional. Yes...................... 4
[[Page 35327]]
4EBN..................... MS Rehab--Medium.... Late--Institutional. No....................... 4
4EBY..................... MS Rehab--Medium.... Late--Institutional. Yes...................... 4
4ECN..................... MS Rehab--High...... Late--Institutional. No....................... 4
4ECY..................... MS Rehab--High...... Late--Institutional. Yes...................... 5
4FAN..................... Behavioral Health-- Late--Institutional. No....................... 2
Low.
4FAY..................... Behavioral Health-- Late--Institutional. Yes...................... 3
Low.
4FBN..................... Behavioral Health-- Late--Institutional. No....................... 3
Medium.
4FBY..................... Behavioral Health-- Late--Institutional. Yes...................... 3
Medium.
4FCN..................... Behavioral Health-- Late--Institutional. No....................... 3
High.
4FCY..................... Behavioral Health-- Late--Institutional. Yes...................... 3
High.
----------------------------------------------------------------------------------------------------------------
We invite public comments on the LUPA threshold methodology
proposed for the HHGM and the associated regulations text changes in
section VIII. of this proposed rule.
10. HH PPS Case-Mix Weights Under the HHGM
Section 1895(b)(4)(B) of the Act requires the Secretary to
establish appropriate case mix adjustment factors for home health
services in a manner that explains a significant amount of the
variation in cost among different units of services. We are proposing
the HHGM case-mix adjustment methodology, which sorts 30-day periods of
care into different payment groups based on five categories (admission
source, timing, clinical group, functional level, and comorbidity
group), for 30-day periods of care that begin on or after January 1,
2019. In combination, this would yield a total of 144 HHGM payment
groups, which we would still refer to as Home Health Resource Groups
(HHRGs) under the HHGM. To generate HHGM case-mix weights, we utilized
a data file based on home health episodes of care, as reported in
Medicare home health claims, as well as OASIS assessment data. The
claims data provide episode-level data, as well as visit-level data.
The claims also provide data on whether NRS was provided during the
episode and the total charges for NRS. We determined the case-mix
weight for each of the different HHGM payment groups by regressing
resource use on a series of indicator variables for each of the five
categories listed above using a fixed effects model. The regression
measures resource use with the proposed Cost per Minute (CPS) + NRS
approach outlined in section III.E.2 of this proposed rule.
To normalize the results from the fixed effects regression model,
we divided the predicted resource use for each 30-day period by the
overall average resource use for all 30-day periods used to estimate
the model to calculate the case mix weight of all 30-day periods within
a particular payment group, where each payment group is defined as the
unique combination of the subgroups within the five HHGM categories
(admission source, timing of the episode, clinical grouping, functional
level, and comorbidity adjustment). The case-mix weight is then used to
adjust the 30-day payment rate to determine each 30-day period payment.
Table 41 shows the coefficients of the payment regression used to
generate the weights, and the coefficients divided by average resource
use. Information can be found in section III.E.6 of this proposed rule
for the clinical groups, section III.E.7 of this proposed rule for the
functional levels, section III.E.5 of this proposed rule for admission
source, section III.E.4 of this proposed rule for episode timing, and
section III.E.8 of this proposed rule for the comorbidity adjustment.
Table 41--Coefficient of Payment Regression and Coefficient Divided by
Average Resource Use for HHGM Payment Group
------------------------------------------------------------------------
Coefficient
divided by
Coefficient average
resource use
------------------------------------------------------------------------
Clinical Group and Functional Level (MMTA--Low is excluded)
------------------------------------------------------------------------
MMTA--Medium............................ $238.93 0.151
MMTA--High.............................. 434.36 0.274
Behavioral Health--Low.................. -116.43 -0.073
Behavioral Health--Medium............... 177.47 0.112
Behavioral Health--High................. 350.98 0.221
Complex--Low............................ 99.82 0.063
Complex--Medium......................... 472.79 0.298
Complex--High........................... 638.62 0.403
MS Rehab--Low........................... 154.72 0.098
MS Rehab--Medium........................ 353.44 0.223
MS Rehab--High.......................... 597.31 0.377
Neuro--Low.............................. 356.33 0.225
Neuro--Medium........................... 636.52 0.401
Neuro--High............................. 804.50 0.507
Wound--Low.............................. 582.68 0.368
[[Page 35328]]
Wound--Medium........................... 812.76 0.513
Wound--High............................. 1,048.55 0.661
------------------------------------------------------------------------
Referral Source With Timing (Community Early excluded)
------------------------------------------------------------------------
Community Late.......................... -618.74 -0.390
Institutional Early..................... 271.07 0.171
Institutional Late...................... 83.61 0.053
------------------------------------------------------------------------
Comorbidity Adjustment (No Comorbidity Adjustment Group is excluded)
------------------------------------------------------------------------
Comorbidity Adjustment Group............ 244.01 0.154
------------------------------------------------------------------------
------------------------------------------------------------------------
Constant................................ 1,533.33 0.967
N....................................... 8,642,107 ..............
Adjusted R2............................. 0.2704 ..............
Average Resource Use.................... 1,585.48 ..............
------------------------------------------------------------------------
Source: CY 2016 Medicare claims data for episodes ending on or before
December 31, 2016 (as of March 17, 2017) for which we had a linked
OASIS assessment. LUPA episodes, outlier episodes, and episodes with
PEP adjustments were excluded.
Table 42 presents the case-mix weight for each HHRG in the
regression model (from Table 46's coefficients). LUPA episodes, outlier
episodes, and episodes with PEP adjustments were excluded. These are
the case-mix weights for the HHGM based on the most current, complete
data available (CY 2016 data as of March 17, 2017). We would propose
updated case-mix weights using the latest CY 2017 data in the CY 2019
HH PPS proposed rule. LUPA information can be found in section III.E.9
of this proposed rule. Weights are determined by first calculating the
predicted resource use for episodes with a particular combination of
admission source, episode timing, clinical grouping, functional level,
and comorbidity adjustment. This combination specific calculation is
then divided by the average resource use of all the episodes that were
used to estimate, which is $1,585.48. The resulting ratio represents
the case-mix weight for that particular combination of a HHRG payment
group. The adjusted R-squared value for this model is 0.2704. The
adjusted R-squared value provides a measure of how well observed
outcomes are replicated by the model, based on the proportion of total
variation of outcomes explained by the model. In this instance, the
fixed effects regression model used to generate the case-mix weight
under the HHGM predicts about 27 percent of the variation in resource
use in a given 30-day period of home health care.
As noted above, there are 144 different HHRG payment groups under
the HHGM. There are 9 HHRG payment groups that represent roughly 50.5
percent of the total episodes. There are 33 HHRG payment groups that
represent roughly 1.0 percent of total episodes. The HHRG payment group
with the smallest weight has a weight of 0.5034 (community, late,
behavioral health, low functional level, with no comorbidity
adjustment). The HHRG payment group with the largest weight has a
weight of 1.9533 (institutional admission, early, wound, high
functional level, with comorbidity adjustment).
Table 42--Case-Mix Weights for Each HHRG Payment Group, Based on 2016 Data
----------------------------------------------------------------------------------------------------------------
Weight based
HIPPS Clinical group and Timing and admission Comorbidity adjustment on CY 2016
functional level source data
----------------------------------------------------------------------------------------------------------------
1AAN..................... MMTA--Low........... Early--Community.... No....................... 0.9671
1AAY..................... MMTA--Low........... Early--Community.... Yes...................... 1.1210
1ABN..................... MMTA--Medium........ Early--Community.... No....................... 1.1178
1ABY..................... MMTA--Medium........ Early--Community.... Yes...................... 1.2717
1ACN..................... MMTA--High.......... Early--Community.... No....................... 1.2411
1ACY..................... MMTA--High.......... Early--Community.... Yes...................... 1.3950
1BAN..................... Neuro--Low.......... Early--Community.... No....................... 1.1919
1BAY..................... Neuro--Low.......... Early--Community.... Yes...................... 1.3458
1BBN..................... Neuro--Medium....... Early--Community.... No....................... 1.3686
1BBY..................... Neuro--Medium....... Early--Community.... Yes...................... 1.5225
1BCN..................... Neuro--High......... Early--Community.... No....................... 1.4745
1BCY..................... Neuro--High......... Early--Community.... Yes...................... 1.6284
1CAN..................... Wound--Low.......... Early--Community.... No....................... 1.3346
1CAY..................... Wound--Low.......... Early--Community.... Yes...................... 1.4885
1CBN..................... Wound--Medium....... Early--Community.... No....................... 1.4797
1CBY..................... Wound--Medium....... Early--Community.... Yes...................... 1.6336
1CCN..................... Wound--High......... Early--Community.... No....................... 1.6284
[[Page 35329]]
1CCY..................... Wound--High......... Early--Community.... Yes...................... 1.7823
1DAN..................... Complex--Low........ Early--Community.... No....................... 1.0301
1DAY..................... Complex--Low........ Early--Community.... Yes...................... 1.1840
1DBN..................... Complex--Medium..... Early--Community.... No....................... 1.2653
1DBY..................... Complex--Medium..... Early--Community.... Yes...................... 1.4192
1DCN..................... Complex--High....... Early--Community.... No....................... 1.3699
1DCY..................... Complex--High....... Early--Community.... Yes...................... 1.5238
1EAN..................... MS Rehab--Low....... Early--Community.... No....................... 1.0647
1EAY..................... MS Rehab--Low....... Early--Community.... Yes...................... 1.2186
1EBN..................... MS Rehab--Medium.... Early--Community.... No....................... 1.1900
1EBY..................... MS Rehab--Medium.... Early--Community.... Yes...................... 1.3439
1ECN..................... MS Rehab--High...... Early--Community.... No....................... 1.3438
1ECY..................... MS Rehab--High...... Early--Community.... Yes...................... 1.4977
1FAN..................... Behavioral Health-- Early--Community.... No....................... 0.8937
Low.
1FAY..................... Behavioral Health-- Early--Community.... Yes...................... 1.0476
Low.
1FBN..................... Behavioral Health-- Early--Community.... No....................... 1.0790
Medium.
1FBY..................... Behavioral Health-- Early--Community.... Yes...................... 1.2329
Medium.
1FCN..................... Behavioral Health-- Early--Community.... No....................... 1.1885
High.
1FCY..................... Behavioral Health-- Early--Community.... Yes...................... 1.3424
High.
2AAN..................... MMTA--Low........... Early--Institutional No....................... 1.1381
2AAY..................... MMTA--Low........... Early--Institutional Yes...................... 1.2920
2ABN..................... MMTA--Medium........ Early--Institutional No....................... 1.2888
2ABY..................... MMTA--Medium........ Early--Institutional Yes...................... 1.4427
2ACN..................... MMTA--High.......... Early--Institutional No....................... 1.4120
2ACY..................... MMTA--High.......... Early--Institutional Yes...................... 1.5659
2BAN..................... Neuro--Low.......... Early--Institutional No....................... 1.3628
2BAY..................... Neuro--Low.......... Early--Institutional Yes...................... 1.5167
2BBN..................... Neuro--Medium....... Early--Institutional No....................... 1.5395
2BBY..................... Neuro--Medium....... Early--Institutional Yes...................... 1.6934
2BCN..................... Neuro--High......... Early--Institutional No....................... 1.6455
2BCY..................... Neuro--High......... Early--Institutional Yes...................... 1.7994
2CAN..................... Wound--Low.......... Early--Institutional No....................... 1.5056
2CAY..................... Wound--Low.......... Early--Institutional Yes...................... 1.6595
2CBN..................... Wound--Medium....... Early--Institutional No....................... 1.6507
2CBY..................... Wound--Medium....... Early--Institutional Yes...................... 1.8046
2CCN..................... Wound--High......... Early--Institutional No....................... 1.7994
2CCY..................... Wound--High......... Early--Institutional Yes...................... 1.9533
2DAN..................... Complex--Low........ Early--Institutional No....................... 1.2010
2DAY..................... Complex--Low........ Early--Institutional Yes...................... 1.3549
2DBN..................... Complex--Medium..... Early--Institutional No....................... 1.4363
2DBY..................... Complex--Medium..... Early--Institutional Yes...................... 1.5902
2DCN..................... Complex--High....... Early--Institutional No....................... 1.5409
2DCY..................... Complex--High....... Early--Institutional Yes...................... 1.6948
2EAN..................... MS Rehab--Low....... Early--Institutional No....................... 1.2357
2EAY..................... MS Rehab--Low....... Early--Institutional Yes...................... 1.3896
2EBN..................... MS Rehab--Medium.... Early--Institutional No....................... 1.3610
2EBY..................... MS Rehab--Medium.... Early--Institutional Yes...................... 1.5149
2ECN..................... MS Rehab--High...... Early--Institutional No....................... 1.5148
2ECY..................... MS Rehab--High...... Early--Institutional Yes...................... 1.6687
2FAN..................... Behavioral Health-- Early--Institutional No....................... 1.0646
Low.
2FAY..................... Behavioral Health-- Early--Institutional Yes...................... 1.2185
Low.
2FBN..................... Behavioral Health-- Early--Institutional No....................... 1.2500
Medium.
2FBY..................... Behavioral Health-- Early--Institutional Yes...................... 1.4039
Medium.
2FCN..................... Behavioral Health-- Early--Institutional No....................... 1.3594
High.
2FCY..................... Behavioral Health-- Early--Institutional Yes...................... 1.5133
High.
3AAN..................... MMTA--Low........... Late--Community..... No....................... 0.5769
3AAY..................... MMTA--Low........... Late--Community..... Yes...................... 0.7308
3ABN..................... MMTA--Medium........ Late--Community..... No....................... 0.7276
3ABY..................... MMTA--Medium........ Late--Community..... Yes...................... 0.8815
3ACN..................... MMTA--High.......... Late--Community..... No....................... 0.8508
3ACY..................... MMTA--High.......... Late--Community..... Yes...................... 1.0047
3BAN..................... Neuro--Low.......... Late--Community..... No....................... 0.8016
3BAY..................... Neuro--Low.......... Late--Community..... Yes...................... 0.9555
3BBN..................... Neuro--Medium....... Late--Community..... No....................... 0.9783
3BBY..................... Neuro--Medium....... Late--Community..... Yes...................... 1.1322
3BCN..................... Neuro--High......... Late--Community..... No....................... 1.0843
3BCY..................... Neuro--High......... Late--Community..... Yes...................... 1.2382
3CAN..................... Wound--Low.......... Late--Community..... No....................... 0.9444
3CAY..................... Wound--Low.......... Late--Community..... Yes...................... 1.0983
3CBN..................... Wound--Medium....... Late--Community..... No....................... 1.0895
[[Page 35330]]
3CBY..................... Wound--Medium....... Late--Community..... Yes...................... 1.2434
3CCN..................... Wound--High......... Late--Community..... No....................... 1.2382
3CCY..................... Wound--High......... Late--Community..... Yes...................... 1.3921
3DAN..................... Complex--Low........ Late--Community..... No....................... 0.6398
3DAY..................... Complex--Low........ Late--Community..... Yes...................... 0.7937
3DBN..................... Complex--Medium..... Late--Community..... No....................... 0.8751
3DBY..................... Complex--Medium..... Late--Community..... Yes...................... 1.0290
3DCN..................... Complex--High....... Late--Community..... No....................... 0.9796
3DCY..................... Complex--High....... Late--Community..... Yes...................... 1.1335
3EAN..................... MS Rehab--Low....... Late--Community..... No....................... 0.6744
3EAY..................... MS Rehab--Low....... Late--Community..... Yes...................... 0.8283
3EBN..................... MS Rehab--Medium.... Late--Community..... No....................... 0.7998
3EBY..................... MS Rehab--Medium.... Late--Community..... Yes...................... 0.9537
3ECN..................... MS Rehab--High...... Late--Community..... No....................... 0.9536
3ECY..................... MS Rehab--High...... Late--Community..... Yes...................... 1.1075
3FAN..................... Behavioral Health-- Late--Community..... No....................... 0.5034
Low.
3FAY..................... Behavioral Health-- Late--Community..... Yes...................... 0.6573
Low.
3FBN..................... Behavioral Health-- Late--Community..... No....................... 0.6888
Medium.
3FBY..................... Behavioral Health-- Late--Community..... Yes...................... 0.8427
Medium.
3FCN..................... Behavioral Health-- Late--Community..... No....................... 0.7982
High.
3FCY..................... Behavioral Health-- Late--Community..... Yes...................... 0.9521
High.
4AAN..................... MMTA--Low........... Late--Institutional. No....................... 1.0198
4AAY..................... MMTA--Low........... Late--Institutional. Yes...................... 1.1737
4ABN..................... MMTA--Medium........ Late--Institutional. No....................... 1.1705
4ABY..................... MMTA--Medium........ Late--Institutional. Yes...................... 1.3244
4ACN..................... MMTA--High.......... Late--Institutional. No....................... 1.2938
4ACY..................... MMTA--High.......... Late--Institutional. Yes...................... 1.4477
4BAN..................... Neuro--Low.......... Late--Institutional. No....................... 1.2446
4BAY..................... Neuro--Low.......... Late--Institutional. Yes...................... 1.3985
4BBN..................... Neuro--Medium....... Late--Institutional. No....................... 1.4213
4BBY..................... Neuro--Medium....... Late--Institutional. Yes...................... 1.5752
4BCN..................... Neuro--High......... Late--Institutional. No....................... 1.5273
4BCY..................... Neuro--High......... Late--Institutional. Yes...................... 1.6812
4CAN..................... Wound--Low.......... Late--Institutional. No....................... 1.3874
4CAY..................... Wound--Low.......... Late--Institutional. Yes...................... 1.5413
4CBN..................... Wound--Medium....... Late--Institutional. No....................... 1.5325
4CBY..................... Wound--Medium....... Late--Institutional. Yes...................... 1.6864
4CCN..................... Wound--High......... Late--Institutional. No....................... 1.6812
4CCY..................... Wound--High......... Late--Institutional. Yes...................... 1.8351
4DAN..................... Complex--Low........ Late--Institutional. No....................... 1.0828
4DAY..................... Complex--Low........ Late--Institutional. Yes...................... 1.2367
4DBN..................... Complex--Medium..... Late--Institutional. No....................... 1.3180
4DBY..................... Complex--Medium..... Late--Institutional. Yes...................... 1.4719
4DCN..................... Complex--High....... Late--Institutional. No....................... 1.4226
4DCY..................... Complex--High....... Late--Institutional. Yes...................... 1.5765
4EAN..................... MS Rehab--Low....... Late--Institutional. No....................... 1.1174
4EAY..................... MS Rehab--Low....... Late--Institutional. Yes...................... 1.2713
4EBN..................... MS Rehab--Medium.... Late--Institutional. No....................... 1.2428
4EBY..................... MS Rehab--Medium.... Late--Institutional. Yes...................... 1.3967
4ECN..................... MS Rehab--High...... Late--Institutional. No....................... 1.3966
4ECY..................... MS Rehab--High...... Late--Institutional. Yes...................... 1.5505
4FAN..................... Behavioral Health-- Late--Institutional. No....................... 0.9464
Low.
4FAY..................... Behavioral Health-- Late--Institutional. Yes...................... 1.1003
Low.
4FBN..................... Behavioral Health-- Late--Institutional. No....................... 1.1318
Medium.
4FBY..................... Behavioral Health-- Late--Institutional. Yes...................... 1.2857
Medium.
4FCN..................... Behavioral Health-- Late--Institutional. No....................... 1.2412
High.
4FCY..................... Behavioral Health-- Late--Institutional. Yes...................... 1.3951
High.
----------------------------------------------------------------------------------------------------------------
Source: CY 2016 Medicare claims data for episodes ending on or before December 31, 2016 for which we had a
linked OASIS assessment. LUPA episodes, outlier episodes, and episodes with PEP adjustments were excluded.
We invite comments on the proposed case-mix weight methodology
under the HHGM.
11. Low-Utilization Payment Adjustment (LUPA) Add-On Payments and
Partial Payment Adjustments Under the HHGM
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. Under the HHGM, we propose the LUPA add-on factors will
remain the same as the current payment system, described in section
III.C.3. of this
[[Page 35331]]
proposed rule. We propose to 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 (1.8451 for SN, 1.6700 for PT, and 1.6266 for SLP)
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 in CY 2019, if the first skilled visit is
SN, the payment for that visit would be the CY 2019 per-visit rate for
SN, multiplied by 1.8451, subject to area wage adjustment.
The current partial episode payment (PEP) adjustment is a
proportion of the episode payment and is based on the span of days
including the start-of-care date or first billable service date through
and including the last billable service date under the original plan of
care before the intervening event in a home health beneficiary's care
defined as:
A beneficiary elected transfer, or
A discharge and return to home health that would warrant,
for purposes of payment, a new OASIS assessment, physician
certification of eligibility, and a new plan of care.
For 30-day periods of care, we propose the process for partial
payment adjustments would remain the same as the existing policies
pertaining to partial episode payments. When a new 30-day period begins
due to the intervening event of the beneficiary elected transfer or
there was a discharge and return to home health during the 30-day
period, we propose the original 30-day period would be proportionally
adjusted to reflect the length of time the beneficiary remained under
the agency's care prior to the intervening event. The proportional
payment is the partial payment adjustment. The partial payment
adjustment is calculated by using the span of days (first billable
service date through and including the last billable service date)
under the original plan of care as a proportion of 30. The proportion
is multiplied by the original case-mix and wage index to produce the
30-day payment.
12. Payments for High-Cost Outliers Under the HHGM
As described in section III.D. of this proposed rule, section
1895(b)(5) of the Act allows for the provision of an addition or
adjustment to the home health payment amount in the case of outliers
because of unusual variations in the type or amount of medically
necessary care. The history of and current methodology for payment of
high-cost outliers under the HH PPS is described in detail in section
III.D. of this proposed rule. We are proposing to maintain the current
methodology for payment of high-cost outliers upon implementation of
the HHGM in CY 2019 and we would calculate payment for high-cost
outliers on 30-day periods of care.
Simulating payments using preliminary CY 2016 claims data and the
CY 2018 payment rates, we estimate that outlier payments under the
proposed HHGM with 30-day periods of care would comprise approximately
4.50 percent of total HH PPS payments in CY 2018. Given the statutory
requirement to target up to, but no more than, 2.5 percent of total
payments as outlier payments, we currently estimate that the FDL ratio
under the HHGM would need to change from 0.55 to 0.93. However, given
the proposed implementation of the HHGM for 30-day periods of care
beginning on or after January 1, 2019, we will update our estimate of
outlier payments as a percent of total HH PPS payments using the most
current and complete utilization data available at the time of CY 2019
rate-setting. We would propose a change in the FDL ratio for CY 2019,
if needed.
We invite public comments on maintaining the current outlier
payment methodology outlined in section III.D. of this proposed rule
for the proposed HHGM and the associated changes in the regulations
text as described in section III.E.13 of this proposed rule.
13. Conforming Regulations Text Revisions for the Implementation of the
HHGM in CY 2019
We are proposing to make a number of revisions to the regulations
to implement the HHGM for periods beginning on or after January 1,
2019, as outlined in sections III.E.1. through III.E.12. of this
proposed rule. We propose to make conforming changes in Sec. 409.43
and part 484 subpart E to revise the unit of service from a 60-day
episode to a 30-day period. In addition, we are proposing to
restructure Sec. 484.205. These revisions would be effective on
January 1, 2019. We are not proposing any revisions to the regulations
for CY 2018. These revisions and others are discussed below.
Specifically, we propose to:
Revise Sec. 409.43, which outlines plan of care
requirements. We propose to revise several paragraphs to phase out the
unit of service from a 60-day episode for episodes beginning on or
before December 31, 2018, and to implement a 30-day period as the new
unit of service for periods beginning on or after January 1, 2019 under
the HHGM.
Revise the definitions of rural area and urban area in
Sec. 484.202 to remove ``with respect to home health episodes ending
on or after January 1, 2006'' from each definition, as this verbiage is
no longer necessary.
Restructure Sec. 484.205 to provide more logical
organization. Specifically, we propose to add paragraphs to paragraph
(b) to define the unit of payment. We propose to move language which
addresses the requirement for OASIS submission from Sec. 484.210 and
insert it into Sec. 484.205 as new paragraph (c). We also propose to
add paragraph (f) to discuss split percentage payments under the
current model and the proposed HHGM. In addition, we propose to revise
Sec. 484.205 to remove references to ``60-day episode'' and to refer
more generally to the ``national, standardized prospective payment''.
While we are proposing to revise Sec. 484.205 to account for the
change in the unit of payment under the HH PPS for CY 2019, we are not
proposing to change the requirements or policies relating to durable
medical equipment or furnishing negative pressure wound therapy using a
disposable device.
Remove Sec. 484.210 which discusses data used for the
calculation of the national prospective 60-day episode payment as we
believe that this information is incorporated in other sections of part
484 subpart E, such as Sec. 484.205(c), Sec. 484.215(a) and (b),
Sec. 484.220 and Sec. 484.215.
Revise the section heading of Sec. 484.215 from ``Initial
establishment of the calculation of the national 60-day episode
payment'' to ``Initial establishment of the calculation of the
national, standardized prospective 60-day episode payment and 30-day
payment rates.'' Also, we propose to add paragraph (f) to this section
to describe how the national, standardized prospective 60-day episode
payment rate is converted into a national, standardized prospective 30-
day period payment and when it applies.
Revise the section heading of Sec. 484.220 from
``Calculation of the adjusted national prospective 60-day episode
payment rate for case-mix and area wage levels'' to ``Calculation of
the case-mix and wage area adjusted prospective payment rates.'' We
propose to remove the reference to ``national 60-day episode payment
rate'' and replace it with ``national, standardized prospective
payment''.
Revise the section heading in Sec. 484.225 from ``Annual
update of the unadjusted national prospective 60-day episode payment
rate'' to ``Annual update of the unadjusted national, standardized
prospective 60-day
[[Page 35332]]
episode and 30-day payment rates''. Also, we propose to revise Sec.
484.225 to remove references to ``60-day episode'' and to refer more
generally to the ``national, standardized prospective payment''. In
addition, we propose to add paragraph (d) to describe the annual update
for CY 2019.
Revise the section heading of Sec. 484.230 from
``Methodology used for the calculation of low-utilization payment
adjustment'' to ``Low utilization payment adjustment''. Also, we
propose to designate the current text to paragraph (a) and insert
language such that proposed paragraph (a) applies to episodes beginning
on or before December 31, 2018, using the current payment system. We
propose to add paragraph (b) to describe how low utilization payment
adjustments are determined for periods beginning on or after January 1,
2019, using the proposed HHGM.
Revise the section heading of Sec. 484.235 from
``Methodology used for the calculation of partial episode payment
adjustments'' to ``Partial payment adjustments''. We propose to remove
paragraphs (a), (b), and (c). We propose to remove paragraphs (1), (2),
and (3) which describe partial payment adjustments from paragraph (d)
in Sec. 484.205 and incorporate them into Sec. 484.235. We propose to
add paragraph (a) to describe partial payment adjustments under the
current system, that is, for episodes beginning on or before December
31, 2018, and paragraph (b) to describe partial payment adjustments
under the proposed HHGM, that is, for periods beginning on or after
January 1, 2019.
Revise the section heading for Sec. 484.240 from
``Methodology used for the calculation of the outlier payment'' to
``Outlier payments.'' In addition, we propose to remove language at
paragraph (b) and append it to paragraph (a). We propose to add
language to proposed revised paragraph (a) such that paragraph (a) will
apply to payments under the current system, that is, for episodes
beginning on or before December 31, 2018. We propose to revise
paragraph (b) to describe payments under the proposed HHGM, that is,
for periods beginning on or after January 1, 2019. In paragraph (c), we
propose to replace the ``estimated'' cost with ``imputed'' cost.
Lastly, we propose to revise paragraph (d) to reflect the per-15 minute
unit approach to imputing the cost for each claim.
We are soliciting comments on the proposed HHGM as outlined in
sections III.E.1. through III.E.12. and the associated regulations text
changes described above and in the regulations text of this proposed
rule.
IV. Proposed Provisions of the Home Health Value-Based Purchasing
(HHVBP) Model
A. Background
As authorized by section 1115A of the Act and finalized in the CY
2016 HH PPS final rule (80 FR 68624), we began testing the HHVBP Model
on January 1, 2016. The HHVBP Model has an overall purpose of improving
the quality and delivery of home health care services to Medicare
beneficiaries. The specific goals of the Model are to: (1) Provide
incentives for better quality care with greater efficiency; (2) study
new potential quality and efficiency measures for appropriateness in
the home health setting; and (3) enhance the current public reporting
process.
Using the randomized selection methodology finalized in the CY 2016
HH PPS final rule, nine states were selected for inclusion in the HHVBP
Model, representing each geographic area across the nation. All
Medicare-certified HHAs providing services in Arizona, Florida, Iowa,
Maryland, Massachusetts, Nebraska, North Carolina, Tennessee, and
Washington (competing HHAs) are required to compete in the Model.
Requiring all Medicare-certified HHAs providing services in the
selected states to participate in the Model ensures that: (1) there is
no selection bias; (2) participating HHAs are representative of HHAs
nationally; and, (3) there is sufficient participation to generate
meaningful results.
As finalized in the CY 2016 HH PPS final rule, the HHVBP Model will
utilize the waiver authority under section 1115A(d)(1) of the Act to
adjust Medicare payment rates under section 1895(b) of the Act
beginning in CY 2018 based on performance on applicable measures.
Payment adjustments will be increased incrementally over the course of
the HHVBP Model in the following manner: (1) A maximum payment
adjustment of 3 percent (upward or downward) in CY 2018; (2) a maximum
payment adjustment of 5 percent (upward or downward) in CY 2019; (3) a
maximum payment adjustment of 6 percent (upward or downward) in CY
2020; (4) a maximum payment adjustment of 7 percent (upward or
downward) in CY 2021; and (5) a maximum payment adjustment of 8 percent
(upward or downward) in CY 2022. Payment adjustments will be based on
each HHA's Total Performance Score (TPS) in a given performance year
(PY) on (1) a set of measures already reported via OASIS and HHCAHPS
for all patients serviced by the HHA and select claims data elements,
and (2) three New Measures where points are achieved for reporting
data.
As finalized in the CY 2017 HH PPS final rule (81 FR 76741 through
76752), in addition to providing an update on the progress towards
developing public reporting of performance under the HHVBP Model, we
finalized the following changes related to the HHVBP Model:
Calculating benchmarks and achievement thresholds at the
state level rather than the level of the size-cohort and revising the
definition for benchmark to state that benchmark refers to the mean of
the top decile of Medicare-certified HHA performance on the specified
quality measure during the baseline period, calculated for each state;
Requiring a minimum of eight HHAs in a size-cohort;
Increasing the timeframe for submitting New Measure data
from seven calendar days to 15 calendar days following the end of each
reporting period to account for weekends and holidays;
Removing four measures (Care Management: Types and Sources
of Assistance, Prior Functioning Activities of Daily Living (ADL)/
Instrumental ADL (IADL), Influenza Vaccine Data Collection Period, and
Reason Pneumococcal Vaccine Not Received) from the set of applicable
measures;
Adjusting the reporting period and submission date for the
Influenza Vaccination Coverage for Home Health Personnel measure from a
quarterly submission to an annual submission; and
Allowing for an appeals process that includes the
recalculation process finalized in the CY 2016 HH PPS final rule (80 FR
68688 through 68689), as modified, and adds a reconsideration process.
B. Quality Measures
1. Proposed Adjustment to the Minimum Number of Completed Home Health
Care Consumer Assessment of Healthcare Providers and System (HHCAHPS)
Surveys
The 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. The survey is designed to
measure the experiences of people receiving home health care from
Medicare-certified home health care agencies and meet the following
three broad goals to: (1)
[[Page 35333]]
Produce comparable data on the patient's perspective that allows
objective and meaningful comparisons between home health agencies on
domains that are important to consumers; (2) create incentives through
public reporting of survey results for agencies to improve their
quality of care; and (3) enhance public accountability in health care
by increasing the transparency of the quality of care provided in
return for public investment through public reporting.
As finalized in the CY 2016 HH PPS final rule (80 FR 68685 through
68686), if a HHA does not have a minimum of 20 episodes of care during
a performance year to generate a performance score on at least five
measures, that HHA would not be included in the Linear Exchange
Function (LEF) and would not have a payment adjustment percentage
calculated. The LEF is used to translate an HHA's Total Performance
Score (TPS) into a percentage of the value-based payment adjustment
earned by each HHA under the HHVBP Model. For the HHCAHPS measures, a
minimum of 20 HHCAHPS completed surveys would be necessary in order for
scores to be generated for the HHCAHPS quality measures that can be
included in the calculation of the TPS.
We believe, however, that using a minimum of 40 completed HHCAHPS
surveys, rather than a minimum of 20 completed HHCAHPS surveys, would
better align the Model with HHCAHPS policy for the Patient Survey Star
Ratings on Home Health Compare.\100\ The decision to use a minimum of
40 completed surveys for these star ratings was a result of balancing
two competing goals. One goal was to provide star ratings that were
meaningful and minimized random variations. This goal was best served
by calculating star ratings for large numbers of cases by having a
larger minimum of completed HHCAHPS surveys (for example, 50 or 100
completed HHCAHPS surveys). At the same time, we also wanted to be able
to provide star ratings for as many HHAs as possible. This goal was
best served by using a lower minimum of completed HHCAHPS surveys (for
example, 20 completed HHCAHPS surveys). We chose to balance these
opposing and necessary goals by using 40 completed HHCAHPS surveys for
the Patient Survey Star Ratings. Because we believe that aligning the
Patient Survey Star Ratings system and the HHVBP model provides
uniformity, consistency, and standard transformability for different
healthcare platforms, we therefore propose using a minimum of 40
instead of 20 completed HHCAHPS surveys under the HHVBP.
---------------------------------------------------------------------------
\100\ Patient Survey Star Ratings https://www.medicare.gov/HomeHealthCompare/Data/Patient-Survey-Star-Ratings.html.
---------------------------------------------------------------------------
We note that we received a comment in response to the CY 2016 HH
PPS proposed rule in support of using a higher minimum threshold for
HHCAHPS completed surveys for the Patient Survey Star Ratings if the
data are going to be used in HHVBP or any other quality assessment
program (80 FR 68709). We also note that we received public comment in
response to the CY 2017 HH PPS proposed rule in support of using a
higher minimum threshold for HHCAHPS completed surveys in the HHVBP
Model, including a recommendation to use a minimum of 100 HHCAHPS
rather than a sample size of 20 surveys (81 FR 76747). We believe that
proposing a minimum of 40 completed HHCAHPS surveys for the Model would
be more appropriate than the higher minimums previously recommended by
some commenters because it represents a balance between providing
meaningful data and having sufficient numbers of HHAs with performance
scores for at least 5 measures in the cohorts. Moreover, as we noted,
it aligns with the Patient Survey Star Ratings on Home Health Compare.
To understand the possible impact of our proposal to use a minimum
of 40 HHCAHPS completed surveys, we note that HHAs may refer to the
Interim Performance Reports (IPRs) issued in October 2016, January 2017
and April 2017, which analyzed 40 or more completed HHCAHPS surveys
across both small and large cohorts in determining each HHA's HHCAHPS
quality measure scores. As a point of comparison to the minimum of 40
HHCAHPS completed surveys, we note that these IPRs will be reissued
using 20 or more completed HHCAHPS surveys and include quality measure
scores, for these same time periods, calculated with HHAs that qualify
for the LEF by having sufficient data for at least five measures. HHAs
will have the opportunity to submit a request for recalculation of the
revised interim performance scores.
HHAs have an opportunity to evaluate these IPRs in light of our
proposal to change to a minimum of 40 HHCAHPS completed surveys, as
well as seek clarification on the difference in their reports. The
participating HHAs will receive concurrent IPRs in July 2017 and
concurrent Annual Total Performance Score and Payment Adjustment
Reports, which we plan to make available in the last week of August
2017. The concurrent reports will show one report with HHCAHPS quality
measure scores calculated based on a minimum of 40 completed surveys
and one report with HHCAHPS quality measure scores calculated based on
a minimum of 20 completed surveys. Because this proposed rule will not
be finalized before the timeline for submission of recalculation and
reconsideration requests, HHAs will have the opportunity to submit
recalculation requests for the interim performance scores based on both
a minimum of 40 and 20 completed surveys, and recalculation and
reconsideration requests, as applicable, for the annual total
performance scores included in these reports for these thresholds in
accordance with the appeals process set forth at Sec. 484.335, which
was finalized in the CY 2017 HH PPS final rule.
We analyzed the effects on participating HHAs of using the proposed
40 or more completed HHCAHPS surveys as compared to using 20 or more
completed HHCAHPS surveys by examining OASIS measures submitted from
January 1, 2015 through December 31, 2016, claims measures submitted
from September 1, 2015 through September 30, 2016, and 12 months ending
June 30, 2016 for HHCAHPS-based measures. We also found that
achievement thresholds, which are calculated as the median of all HHAs'
performance on the specified quality measures during the 2015 baseline
year for each state, would not change by more than 1.1
percent, with the largest changes occurring in the statewide
achievement thresholds for the HHCAHPS Willingness to Recommend the
Agency measure in Arizona (+1.1 percent) and Nebraska (-1.1 percent).
Benchmarks (the mean of the top decile of Medicare-certified HHA
performance on the specified quality measures during the 2015 baseline
year, calculated for each state) had greater potential for change,
ranging down to -3.2 percent. For instance, we found that when
calculated using a minimum of 40 surveys rather than a minimum of 20
surveys, there was a -2.0 percent reduction in the benchmark for the
HHCAHPS Willingness to Recommend the Agency measure for Arizona and a -
1.7 percent reduction in the benchmark for Nebraska. We also found that
when calculated using a minimum of 40 surveys rather than a minimum of
20 surveys, there was a -1.7 percent reduction in the benchmark for the
HHCAHPS Communications between
[[Page 35334]]
Providers and Patients measure for Arizona, a -1.7 percent reduction in
the benchmark for Florida, and a -3.2 percent reduction in the
benchmark for Nebraska.
Overall, the proposed change in the HHCAHPS minimum of 40 completed
surveys is estimated to result in a limited percent change in the
average statewide TPS for larger-volume HHAs, ranging from -0.4 through
+2.2 percent. Because the underlying data does not cover the full 2016
calendar year, the data limitation may impact the final total
performance scores and corresponding payment adjustment percentages. We
provide estimates of the expected payment adjustment distribution based
on the proposed minimum of 40 completed HHCAHPS surveys in the impact
analysis of this proposed rule.
We are inviting public comments on our proposal to use 40 or more
completed HHCAHPS surveys as the minimum to generate a quality measure
score on the HHCAHPS measures, as is currently used in Home Health
Compare and the Patient Survey Star Ratings. Therefore, we propose to
revise the definition of ``applicable measure'' at Sec. 484.305 to
reflect this proposal, from a measure for which the competing HHA has
provided 20 home health episodes of care per year to a measure for
which a competing HHA has provided a minimum of 20 home health episodes
of care per year for the OASIS-based measures, 20 home health episodes
of care per year for the claims-based measures, or 40 completed surveys
for the HHCAHPS measures. This proposal, if finalized, would apply to
the calculation of the benchmark and achievement thresholds and the
calculation of performance scores for all Model years, beginning with
Performance Year (PY) One.
2. Proposal To Remove One OASIS-Based Measure Beginning With
Performance Year 3
In the CY 2016 HH PPS final rule, we finalized a set of quality
measures in Figure 4a: Final PY1 Measures and Figure 4b: Final PY1 New
Measures (80 FR 68671 through 68673) for the HHVBP Model to be used in
the first performance year (PY1), referred to as the starter set.
The measures were selected for the Model using the following
guiding principles: (1) Use a broad measure set that captures the
complexity of the services HHAs provide; (2) Incorporate the
flexibility for future inclusion of the Improving Medicare Post-Acute
Care Transformation Act of 2014 (IMPACT) measures that cut across post-
acute care settings; (3) Develop `second generation' (of the HHVBP
Model) measures of patient outcomes, health and functional status,
shared decision making, and patient activation; (4) Include a balance
of process, outcome and patient experience measures; (5) Advance the
ability to measure cost and value; (6) Add measures for appropriateness
or overuse; and (7) Promote infrastructure investments. This set of
quality measures encompasses the multiple National Quality Strategy
(NQS) domains \101\ (80 FR 68668). The NQS domains include six priority
areas identified in the CY 2016 HH PPS final rule (80 FR 68668) as the
CMS Framework for Quality Measurement Mapping. These areas are: (1)
Clinical quality of care; (2) Care coordination; (3) Population &
community health; (4) Person- and Caregiver-centered experience and
outcomes; (5) Safety; and (6) Efficiency and cost reduction. Figures 4a
and 4b of the CY 2016 HH PPS final rule identified 15 outcome measures
(five from the HHCAHPS, eight from Outcome and Assessment Information
Set (OASIS), and two from the Chronic Care Warehouse (claims)), and
nine process measures (six from OASIS, and three New Measures, which
were not previously reported in the home health setting).
---------------------------------------------------------------------------
\101\ 2015 Annual Report to Congress, https://www.ahrq.gov/workingforquality/reports/annual-reports/nqs2015annlrpt.htm.
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In the CY 2017 HH PPS final rule, we removed the following four
measures from the measure set for PY 1 and subsequent performance
years: (1) Care Management: Types and Sources of Assistance; (2) Prior
Functioning ADL/IADL; (3) Influenza Vaccine Data Collection Period:
Does this episode of care include any dates on or between October 1 and
March 31?; and (4) Reason Pneumococcal Vaccine Not Received, for the
reasons discussed in that final rule (81 FR 76743 through 76747).
For Performance Year 3 (PY 3), we are proposing to remove one
OASIS-based measure, Drug Education on All Medications Provided to
Patient/Caregiver during All Episodes of Care, from the set of
applicable measures. As part of our ongoing monitoring efforts, we
found that based on the standard metrics of measure performance, many
providers have achieved full performance on the Drug Education measure.
For example, for the January 2017 IPRs (which covered the 12-month
period of October 1, 2015 through September 30, 2016), the average
value for this measure across all participating HHAs was 95.69 percent
from October 2015 through September 2016. When looking at just
September 2016, the mean value on this measure across all participating
HHAs had increased to 97.8 percent. Also, there are few HHAs with poor
performance on the measure. Based on the January 2017 IPRs, across all
participating HHAs, the 10th percentile was 89 percent and the 5th
percentile was 81.8 percent, but only 1.8 percent of HHAs had a value
below 70 percent on the measure. We believe that removing this measure
would be consistent with our policy, as noted in the CY 2017 HH PPS
final rule (81 FR 76746), that when a measure has achieved full
performance, we may propose the removal of the measure in future
rulemaking. In addition, our contractor's Technical Expert Panel (TEP),
which consists of 11 panelists with expertise in home health care and
quality measures, expressed concern that the Drug Education measure
does not capture whether the education provided by the HHA was
meaningful.
The revised set of applicable measures, if our proposal to remove
the OASIS-based measure, Drug Education on All Medications Provided to
Patient/Caregiver during All Episodes of Care, is finalized, is
presented in Table 43. This measure set would be applicable to PY3 and
each subsequent performance year until such time that another set of
applicable measures, or changes to this measure set, are proposed and
finalized in future rulemaking.
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\102\ 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.
[[Page 35335]]
Table 43--Measure Set for the HHVBP Model \102\ Beginning PY 3
--------------------------------------------------------------------------------------------------------------------------------------------------------
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[dash] 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
ambulation/ or measure-specific
locomotion at exclusions.
discharge than at
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
transferring at or measure-specific
discharge than at exclusions.
the 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 covered by generic
bathing at discharge or measure-specific
than at the start exclusions.
(or 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 covered by generic
resumption) of care. or measure-specific
exclusions.
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
at the discharge discharge or
indicates the transfer to
patient remained in inpatient facility
the community after during the reporting
discharge. period, other than
those covered by
generic or measure-
specific exclusions.
Efficiency & Cost Reduction... Acute Care Outcome.......... NQF0171.......... CCW (Claims)..... Number of home health Number of home health
Hospitalization: stays for patients stays that begin
Unplanned who have a Medicare during the 12-month
Hospitalization claim for an observation period.
during first 60 unplanned admission A home health stay is
days of Home to an acute care a sequence of home
Health. hospital in the 60 health payment
days following the episodes separated
start of the home from other home
health stay. health payment
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 a sequence of home
for acute care health payment
hospitalization in episodes separated
the 60 days from other home
following the start health payment
of the home health episodes by at least
stay. 60 days.
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
discharge than at or measure-specific
the start (or exclusions.
resumption) of care.
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
oral medications or measure-specific
correctly at exclusions.
discharge than at
start (or
resumption) of care.
Population/Community Health... Influenza Process.......... NQF0522.......... OASIS (M1046).... Number of home health Number of home health
Immunization episodes during episodes of care
Received for which patients (a) ending with
Current Flu received vaccination discharge, or
Season. from the HHA or (b) transfer to
had received inpatient facility
vaccination from HHA during the reporting
during earlier period, other than
episode of care, or those covered by
(c) was determined generic or measure-
to have received specific exclusions.
vaccination from
another provider.
Population/Community Health... Pneumococcal Process.......... NQF0525.......... OASIS (M1051).... Number of home health Number of home health
Polysaccharide episodes during episodes of care
Vaccine Ever which patients were ending with
Received. determined to have discharge or
ever received transfer to
Pneumococcal inpatient facility
Polysaccharide during the reporting
Vaccine (PPV). period, other than
those covered by
generic or measure-
specific exclusions.
Patient & Caregiver-Centered Care of Patients. Outcome.......... ................. CAHPS............ NA................... NA.
Experience.
Patient & Caregiver-Centered Communications Outcome.......... ................. CAHPS............ NA................... NA.
Experience. between
Providers and
Patients.
[[Page 35336]]
Patient & Caregiver-Centered Specific Care Outcome.......... ................. CAHPS............ NA................... NA.
Experience. Issues.
Patient & Caregiver-Centered Overall rating of Outcome.......... ................. CAHPS............ NA................... NA.
Experience. home health care.
Patient & Caregiver-Centered Willingness to Outcome.......... ................. CAHPS............ NA................... NA.
Experience. recommend the
agency.
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 working in the
Home Health Care Home Health). during the time from healthcare facility
Personnel. October 1 (or when for at least 1
the 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 clinical
influenza responsibility or
vaccination patient contact.
administered at the
healthcare facility,
or reported in
writing or provided
documentation that
influenza
vaccination was
received elsewhere:
or (b) were
determined to have a
medical
contraindication/
condition of severe
allergic reaction to
eggs or to other
components of the
vaccine or history
of Guillain-Barre
Syndrome within 6
weeks after a
previous influenza
vaccination; or (c)
declined influenza
vaccination; or (d)
persons with unknown
vaccination status
or who do not
otherwise meet any
of the definitions
of the above-
mentioned numerator
categories.
Population/Community Health... Herpes zoster Process.......... NA............... Reported by HHAs Total number of Total number of
(Shingles) through Web Medicare Medicare
vaccination: Has Portal. beneficiaries aged beneficiaries aged
the patient ever 60 years and over 60 years and over
received the who report having receiving services
shingles ever received zoster from the HHA.
vaccination? vaccine (shingles
vaccine).
Communication & Care Advance Care Plan Process.......... NQF0326.......... Reported by HHAs Patients who have an All patients aged 65
Coordination. 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.
--------------------------------------------------------------------------------------------------------------------------------------------------------
We invite public comment on the proposal to remove one OASIS-based
measure, Drug Education on All Medications Provided to Patient/
Caregiver during All Episodes of Care, from the set of applicable
measures for PY3 and subsequent performance years and Table 43.
C. Quality Measures for Future Consideration
The CY 2016 HH PPS final rule discusses the HHVBP Model design, the
guiding principles to select measures, and the six priority areas of
the National Quality Strategy (NQS) we considered for the Model (80 FR
68656 through 68678). Under the HHVBP Model, any measures we determine
to be good indicators of quality will be considered for use in the
HHVBP Model in future years, and may be added or removed through the
rulemaking process. To further our commitment to objectively assess
HHVBP quality measures, we are utilizing an implementation contractor
that invited a group of measure experts to provide advice on the
adjustment of the current measure set for consideration. The contractor
convened a technical expert panel (TEP) consisting of 11 panelists with
expertise in home health care and quality measures that met on
September 7, 2016, in Baltimore, Maryland and via conference call on
December 2, 2016. The TEP discussed developing a composite total change
in ADL/IADL measure; a composite functional decline measure; a measure
to capture when an HHA correctly identifies the patient's need for
mental and behavioral health supervision; and a measure to identify if
a caregiver is able to provide the patient's mental or behavioral
health supervision, to align with Sec. 409.45(b)(3)(iii) and the
Medicare Benefit Policy Manual (Pub. 100-02), Chapter 7, Section 20.2.
We discuss each of these potential measures in further detail in this
section of the proposed rule. While any new measures would be proposed
for use in future rulemaking, we are inviting comment on these
potential measures now to inform measure development and selection.
As noted in the CY 2017 HH PPS final rule (81 FR 76747), we
received several comments expressing concern that the measures under
the Model do not reflect the patient population served under the
Medicare Home Health benefit as the outcome measures focus on a
patient's clinical improvement and do not address patients with chronic
illnesses; deteriorating neurological, pulmonary, cardiac, and other
conditions; and some with terminal illness. These commenters opined
that the value of
[[Page 35337]]
including stabilization measures in the HHVBP Model is readily apparent
as it aligns the Model with the Medicare Home Health benefit.
Commenters also expressed concerns that improvement is not always the
goal for each patient and that stabilization is a reasonable clinical
goal for some patients. Commenters suggested the addition of
stabilization or maintenance measures be considered for the HHVBP
Model. Many commenters objected to the use of improvement measures in
the HHVBP Model. We did not receive any specific measures for future
consideration. In the subsections that follow, we are identifying
measures that we are considering for possible inclusion under the Model
in future rulemaking and are seeking input from the public on the
measures mentioned, as well as any input about the development or
construction of the measures and their features or methodologies.
1. Total Change in ADL/IADL Performance by HHA Patients
The measure set finalized in the CY 2016 HH PPS final rule included
Change in Daily Activity Function as Measured by the Activity Measure
for Post-Acute Care (AM-PAC) (NQF #0430). However, the measure was
removed in the CY 2017 HH PPS final rule and never used in the HHVBP
Model because the measure required use of a proprietary data collection
instrument in the home health environment. We are considering replacing
Change in Daily Activity Function as Measured by AM-PAC (NQF #0430)
with a composite total ADL/IADL change performance measure. During the
September 2016 TEP meeting, an alternative to the Change in Daily
Activity Function measure was presented. The TEP requested that a
composite Total ADL/IADL Change measure be investigated empirically.
This measure was discussed as part of the follow-up conference call,
and the TEP supported continued development of the measure in the HHVBP
Model as a way of including a measure that captures all three potential
outcomes for home health patients: Stabilization; decline; and
improvement. They provided input on the technical specifications of the
potential composite measure, including the feasibility of implementing
the measure and the overall measure reliability and validity. We have
reviewed this suggested alternative and believe this measure would
provide actionable and transparent information that would support HHA
efforts to improve care and prevent functional decline for all patients
across a broad range of patient functional outcomes. The measure would
also improve accountability during an episode of care when the patient
is directly under the HHA's care.
The name of this potential composite measure could be Total Change
in ADL/IADL Performance by HHA Patients. The measure would report the
average, normalized, total improved functioning across the 11 ADL/IADL
items on the current OASIS-C2 instrument. The measure is calculated by
comparing scores from the start-of-care/resumption of care to scores at
discharge. For each item the patient's discharge assessed performance
score is subtracted from the patient's start of care/resumption of care
assessed performance score, and then divided by the maximum improvement
value based on the number of response options for that item. These
values are summed into a total normalized change score that can range
from -11 (that is, for an episode where there is maximum decline on all
11 items used in the measure) to +11 (that is, for an episode where
there is the maximum improvement on all 11 items). An HHA's score on
the measure is based on its average across all eligible episodes.
Patients who are independent on all 11 ADL/IADL items at Start of Care
(SOC)/Resumption of Care (ROC) would also be included in the measure.
The HHA's observed score on the measure is the average of the
normalized total scores for all eligible episodes for its patients
during the reporting period.
The following 11 ADLs/IADL-related items from OASIS-C2 items were
included in developing a composite measure:
ADL OASIS-C2 items related to Self-Care:
M1800 (Grooming).
M1810 (Upper body dressing).
M1820 (Lower body dressing).
M1845 (Toileting hygiene).
M1870 (Eating).
ADL OASIS-C2 items related to Mobility:
M1840 (Toilet transferring).
M1840 (Bed transferring).
M1860 (Ambulation).
Other IADLs OASIS items:
M1880 (Light meal preparation).
M1890 (Telephone use).
M2020 (Oral medication management).
Based on the measures identified above, we would risk-adjust using
OASIS-C2 items to account for case-mix variation and other factors that
affect functional decline but are beyond the influence of the HHA. The
risk-adjustment model uses an ordinary least squares (OLS)
103 104 regression framework because the outcome measure
(normalized change in ADL/IADL performance) is a continuous variable.
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\103\ Fox, John (1997). Applied Regression Analysis, Linear
Models, and Related Methods/Edition 1, 1997, SAGE.
\104\ Green, William H. (2017). Econometric analysis (8th ed.).
New Jersey: Pearson. ISBN 978-0134461366.
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The prediction model for this outcome measure was derived using the
predicted values from the 11 individual outcomes that are currently
used to risk adjust these 11 individual quality measures. Of the 11
values tested, the 8 identified in this proposed rule were found to be
statistically related to the Total Change in ADL/IADL Performance by
HHA Patients measure at p <0.0001 level and would be used in the
prediction model that we are considering proposing to use to risk
adjust the HHA's observed value with respect to this potential future
measure. The prediction model for this outcome measure uses predicted
values from the following individual outcomes (Note: The primary source
OASIS item is listed in parenthesis after the name of the quality
measure):
Improvement in Upper Body Dressing (M1810).
Improvement in Management of Oral Medications (M2020).
Improvement in Bed Transferring (M1850).
Improvement in Ambulation/Locomotion (M1860).
Improvement in Grooming (M1800).
Improvement in Toileting Hygiene (M1845).
Discharged to the Community (M2420).
Improvement in Toileting Transfer (M1840).
Two predictive models, one based on predicted values from CY2014
and one from CY2015, were computed. The correlations at the episode
level between observed and predicted values for the target outcome
measure Total Change in ADL/IADL Performance by HHA Patients are shown
in Table 44.
[[Page 35338]]
Table 44--Correlations at the Episode Level Between Observed and Predicted Values for the Target Outcome Measure
Total Change in ADL/IADL Performance by HHA Patients
----------------------------------------------------------------------------------------------------------------
r\2\ (Coeff.
Data group Correlation Significance Determination)
(p < ) (%)
----------------------------------------------------------------------------------------------------------------
CY2014, National.............................................. 0.5022 0.0001 25.22
CY2014, HHVBP states.......................................... 0.5094 0.0001 25.95
CY2015, National.............................................. 0.5011 0.0001 25.11
CY2015, HHVBP states.......................................... 0.5076 0.0001 25.76
----------------------------------------------------------------------------------------------------------------
The results in Table 44 suggest that either model would account for
25 percent or more of the variability in the outcome measure. These
models could be considered very strong predictive models for the target
outcome measure. Although the analysis supports developing a composite
measure, the analysis assumes that the OASIS-C2 items identified to be
used in the composite measure do not change; however, we recognize that
OASIS-C2 items could be removed or added in any given year. We expect
to conduct an additional analysis, in advance of any future proposal,
to assess whether changes to OASIS-C2 items that are removed or added
could significantly impact a HHA's ability to address several measures
to improve its overall score in the composite measure. We are
soliciting public comments on whether or not to include a composite
total ADL/IADL change performance measure in the set of applicable
measures, the name of any such measure, the risk adjustment method, and
whether we should conduct an analysis of the impact of removal/addition
of OASIS-C2 items.
2. Composite Functional Decline Measure
The second measure we are considering for possible inclusion under
the Model in future rulemaking is a Composite Functional Decline
Measure that could be the percentage of episodes where there was
decline on one or more of the eight ADL items used in the measure. As
noted in this proposed rule, we received comments on the CY 2017 HH PPS
proposed rule suggesting that we consider the addition of stabilization
or maintenance measures. To address this suggestion, we are considering
a composite functional decline measure because the existing functional
stabilization measures, taken individually, are topped out, with HHA
level means of 95 percent or higher. This type of composite functional
decline measure is similar to the composite ADL decline measure that is
used in the Skilled Nursing Facility (SNF) Quality Reporting program
(QRP).\105\ The SNF QRP measure is constructed from four ADL items: Bed
mobility; transfer; eating; and toileting.
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\105\ ``Long-stay Nursing Home Care: Percent of Residents Whose
Need for help with Activities of Daily Living has Increased.''
https://www.qualitymeasures.ahrq.gov/summaries/summary/50060.
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An HHVBP composite functional decline measure could provide
actionable and transparent information that could support HHA efforts
to improve care and prevent functional decline for all patients,
including those for whom improvement in functional status is not a
realistic care goal. This concept was discussed during the TEP meeting
on September 7, 2016, with a follow-up conference call held on December
2, 2016. The TEP supported the inclusion of measures of stabilization
and decline in the HHVBP Model, as well as further development of the
composite functional decline measure. They provided input on the
technical specifications of the potential composite measure, including
the feasibility of implementing the measure and the overall measure
reliability and validity.
When calculating the composite functional decline measure, we could
use the following 8 existing OASIS-C2 items identified below:
Ambulation/Locomotion (M1860).
Bed Transferring (M1840).
Toilet Transferring (M1840).
Bathing (M1830).
Toilet Hygiene (M1845).
Lower Body Dressing (M1820).
Upper Body Dressing (M1810).
Grooming (M1800).
The measure could be defined as 1 if there is decline reported in
one or more of these items between the Start of Care and the Discharge
assessments and zero if no decline is reported on any of these items.
As with other OASIS-based measures, a performance score for the measure
would only be calculated for HHAs that have 20 or more episodes of care
during a performance year.
The measure could be risk-adjusted using OASIS-C2 items to account
for case-mix variation and other factors that affect functional decline
but are beyond the influence of the HHA. The risk-adjustment model uses
a logistic regression framework. The model includes a large number of
patient clinical conditions and other characteristics measured at start
of care. A logistic regression model is estimated to predict whether
the patient will have length of stay of greater than 60 days. The
predicted probability of length of stay of greater than 60 days is
used, along with other patient characteristics, to construct a logistic
regression model to predict the probability of decline in any of eight
ADLs. This model is used to estimate the predicted percent of ADL
decline at the HHA level. To calculate case-mix adjusted values, the
observed value of the measure is adjusted by the difference between the
HHA predicted percent and the national predicted percent. The risk-
adjustment model reduces the adjusted difference between HHAs that
serve a disproportionate number of longer-stay patients and those that
serve patients with more typical lengths of stay of one episode.
Across all participating HHAs in the HHVBP Model, for HHAs that had
less than 20 percent of episodes lasting more than 60 days, the average
on the functional decline measure was 8.08 percent. This increased to
11.08 percent for HHAs with 20 percent to 40 percent of episodes
lasting more than 60 days, 14.23 percent for HHAs with 40 percent to 60
percent of episodes lasting more than 60 days, and 20.59 percent for
HHAs with more than 60 percent of episodes lasting more than 60 days.
This finding suggests that, in addition to focusing on prevention of
functional decline, we should also attempt to better predict a
patient's functional trajectory and potentially stratify the population
to exclude those on a likely downward trajectory. However, in spite of
this finding, the inclusion of a measure that rewards providers for
avoiding functional decline has the advantage of diversifying the set
of measures for the HHVBP model. We are soliciting public comments on
whether or not to include
[[Page 35339]]
a composite functional decline measure in the set of applicable
measures, the name of any such measure, the risk adjustment method, and
whether we should conduct an analysis of the impact of removal/addition
of OASIS-C2 items.
3. Behavioral Health Measures
Although we did not receive comments or suggestions through the
rulemaking process for the HHVBP Model regarding behavioral or mental
health measures, we recognize that the Model does not include such
measures. The OASIS-C2 collects several items related to behavioral and
mental health (M1700 Cognitive Functioning; M1710 Confusion Frequency;
M1720 Anxiety; M1730 Depression Screening; M1740 Cognitive, Behavioral,
and Psychiatric Symptoms; M1745 Frequency of Disruptive Behavior
Symptoms; and M1750 Psychiatric Nursing Services). These items are used
to compute both Improvement and Process measures as well as Potentially
Avoidable Events. The inclusion of behavioral health measures is
important for care transformation and improvement activities as many
persons served by the Home Health program may have behavioral health
needs.
The TEP made several suggestions during the December 2016
conference call as to whether the focus of a behavioral or mental
health measure could be identifying whether a patient needed mental or
behavioral health assistance compared to the supervision of the patient
or advocacy assistance. The TEP supports the supervision type measure
due to its opportunity for potential improvement. In further analyses,
we identified two underlying components to outcomes for providing
assistance. We developed a method, described below, to identify
patients who have or do not have needs for mental or behavioral health
supervision. We are considering further refining this method by
identifying the involvement of the caregiver in addressing the
patient's mental or behavioral health supervision needs as an important
outcome measure, and we seek comment on whether this is an appropriate
factor or feature that we should consider in developing such a measure
in future rulemaking.
a. HHA Correctly Identifies Patient's Need for Mental or Behavioral
Health Supervision
We are considering adding a HHA Correctly Identifies Patient's Need
for Mental or Behavioral Health Supervision measure to the HHVBP Model
in the future to capture a patient's need for mental or behavioral
health supervision based on an identifier. This identifier is based on
information from existing Neuro/Emotional/Behavioral Status OASIS
items, along with other indicators of mental/behavioral health problems
to identify a patient in need of supervisory assistance. The outcome
measure assesses whether the HHA correctly identifies whether or not
the patient needs mental or behavioral health supervision based on the
OASIS SOC/ROC assessment item M2102f, Types and Sources of Assistance:
Supervision and Safety.
A composite Mental/Behavioral Health measure could be a dichotomous
measure that reports the percentage of episodes of care where the HHA
correctly identifies: (a) Patients who need mental or behavioral health
supervision; and (b) patients who don't need mental or behavioral
health supervision. The numerator could be a combination of two values:
(1) The number of episodes of care where the HHA correctly identifies
patients who need mental or behavioral health supervision; plus (2) the
number of episodes of care where the HHA correctly identifies patients
who don't need mental or behavioral health supervision. The denominator
is all episodes of care.
The composite measure requires that a patient's need for mental or
behavioral health supervision be identified. The following algorithm
was designed to identify if a patient was in need of mental or
behavioral health supervision. If the patient met any of the following
conditions, the patient was identified by the algorithm as in need of
mental or behavioral health supervision:
Was discharged from a psychiatric hospital prior to
entering home health care (M1000 = 6);
Is diagnosed as having chronic mental behavioral problems
(M1021 and M1023);
Is diagnosed with a mental illness (M1021 and M1023);
Is cognitively impaired (M1700 > = 2);
Is confused (M1710 > = 2);
Is identified as having a memory deficit (M1740 = 1);
Is identified as having impaired decision-making (M1740 =
2);
Is identified as being verbally disruptive (M1740 = 3);
Is identified as being physically aggressive (M1740 = 4);
Is identified as exhibiting disruptive, infantile, or
inappropriate behaviors (M1740 = 5);
Is identified as being delusional (M1740 = 6); or
Has a frequency of disruptive symptoms (M1745 >= 2.
The measure also requires that the HHA identify if the patient is
in need of mental or behavioral health supervision. This requirement is
based on the SOC/ROC code for M2102f, Types and Sources of Assistance:
Supervision and Safety. If the HHA codes a value of 0, then the HHA has
identified this patient as not needing mental or behavioral health
supervision. If the HHA codes another value for M2102f, Types and
Sources of Assistance: Supervision and Safety, then the HHA has
identified this patient as needing mental or behavioral health
supervision. The outcome measure is defined as the agreement between
the algorithm's identification of a patient's need for mental or
behavioral health supervision and the HHA's coding of this need. That
is, if--
The algorithm identifies the patient as not in need of
mental or behavioral health supervision and the HHA identifies the
patient as not in need of mental or behavioral health supervision, or
The algorithm identifies the patient as in need of mental
or behavioral health supervision and the HHA identifies the patient as
in need of mental or behavioral health supervision, then
The outcome is coded as 1, successful.
As with other OASIS-based measures, a performance score for the
measure would only be calculated for HHAs that have 20 or more episodes
of care during a performance year.
The measure is risk-adjusted using OASIS-C2 items to account for
case-mix variation and other factors that affect functional decline but
are beyond the influence of the HHA. The risk-adjustment model uses a
logistic regression framework. The model includes a large number of
patient clinical conditions and other characteristics measured at the
start of care. To calculate case-mix adjusted values, the observed
value of the measure is adjusted by the difference between the HHA
predicted percent and the national predicted percent.
The prediction model for this outcome measure uses 39 risk factors
\106\ with each risk factor statistically significant at <0.0001. The
correlation for the model between observed and predicted values as
estimated by
[[Page 35340]]
Somers' D \107\ is 0.427, that yields an estimated coefficient of
determination (r2) value based on the Tau-a \108\ of 0.201. This
suggests that the variability in the model accounts for (predicts)
approximately 20 percent of the variability in the outcome measure. The
best statistic for evaluating the power of a prediction model that is
derived using logistic regression is the c-statistic.\109\ This
statistic identifies the overall accuracy of prediction by comparing
observed and predicted value pairs to the proportion of the time that
both predict the outcome in the same direction with 0.500 being a coin-
flip. The discussed prediction model has a c-statistic equal to 0.713,
which is considered to be strong. Using data from CY 2015, the episode-
level mean for the HHA Correctly Identifies Patient's Need for Mental
or Behavioral Health Supervision measure is 61.98 percent, nationally,
and 62.98 percent for the HHVBP states.
---------------------------------------------------------------------------
\106\ ``Home Health Quality Initiative: Quality Measures''
https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HomeHealthQualityInits/HHQIQualityMeasures.html.
\107\ Somers' D is a statistic that is based on the concept of
concordant vs. discordant pairs for two related values. In this
case, if both the observed and predicted values are higher than the
average or if both values are less than the average, then the pair
of numbers is considered concordant. However, if one value is higher
than average and the other is lower than average--or vice versa,
then the pair of values is considered discordant. The Somer's D is
(# of concordant pairs - # of discordant pairs)/total # of pairs.
The higher the ratio, the stronger the concordance between the two
set of values.
\108\ The Kendall Tau-a assumes that if there is a correlation
between two variables, then sorting the variables based on one of
the values will result in ordering the second variable. It uses the
same concept of concordant pairs in Somers' D but a different
formula: t = [(4P)/[(n) (n-1)]-1 where p = # of concordant pairs and
n = # of pairs. This correlation method reduces the effect of
outlier values as the values are essentially ranked.
\109\ The C-statistic (sometimes called the ``concordance''
statistic or C-index) is a measure of goodness of fit for binary
outcomes in a logistic regression model. In clinical studies, the C-
statistic gives the probability a randomly selected patient who
experienced an event (for example, a disease or condition) had a
higher risk score than a patient who had not experienced the event.
It is equal to the area under the Receiver Operating Characteristic
(ROC) curve and ranges from 0.5 to 1.
A value below 0.5 indicates a very poor model.
A value of 0.5 means that the model is no better than
predicting an outcome than random chance.
Values over 0.7 indicate a good model.
Values over 0.8 indicate a strong model.
---------------------------------------------------------------------------
b. Caregiver Can/Does Provide for Patient's Mental or Behavioral Health
Supervision Need
We are considering including under the Model in future rulemaking a
Caregiver Can/Does Provide for Patient's Mental or Behavioral Health
Supervision Need measure that would encourage HHAs to ensure that
patients who need mental or behavioral health supervision are receiving
such care from the patient's caregivers, and would be a realistic care
goal.
When considering how to develop a measure to determine whether or
not the caregiver can/does provide the patient's mental or behavioral
health supervision, we would create an identifier of a patient's need
for mental or behavioral health supervision. This identifier is based
on the same algorithm described in the previous section from existing
Neuro/Emotional/Behavioral Status OASIS items along with other
indicators of mental/behavioral health problems to identify a patient
in need of supervisory assistance. The outcome measure is whether the
HHA correctly identifies this patient as having the need for mental or
behavioral health supervision based on the OASIS SOC/ROC assessment
item M2102f, Types and Sources of Assistance: Supervision and Safety.
The measure could be a dichotomous measure that reports the
percentage of episodes where patients with identified mental or
behavioral health supervision needs have their needs met or could have
their needs met by the patient's caregiver with additional training (if
needed) and support by the HHA. The numerator is the intersection of:
(1) The number of episodes of care where the patient needs mental or
behavioral health supervision; and (2) the number of episodes of care
where these patients have their needs met or could have their needs met
by the patient's caregiver with additional training (if needed) and
support by the HHA. By intersection, we mean that, for the numerator to
equal one, a patient has to need mental or behavioral health
supervision and has to have these needs met by his or her caregiver, or
could have their needs met by the caregiver with additional training
and/or support by the HHA. The denominator is all episodes of care. The
algorithm discussed above for HHA Correctly Identifies Patient's Need
for Mental or Behavioral Health Supervision could also be used to first
identify if a patient was in need of mental or behavioral health
supervision.
To identify whether caregivers are able to provide supervisory care
or, with training, could be able to provide supervisory care for these
patients, we could use the SOC/ROC code for M2102f, Types and Sources
of Assistance: Supervision and Safety. If the HHA codes a value of 1
(Non-agency caregiver(s) currently provide assistance) or 2 (Non-agency
caregiver(s) need training/supportive services to provide assistance),
then the measure identifies that a caregiver does or could provide
supervision to a patient who has been identified as needing mental or
behavioral health supervision.
The outcome measure is defined as the agreement between the
algorithm's identification of a patient's need for mental or behavioral
health supervision and the availability of supervision from the
patient's caregiver(s). That is, if--
The algorithm identifies the patient as in need of mental
or behavioral health supervision and there is documentation that the
patient's caregiver(s) do or could provide this supervision; then
The outcome is coded as 1, successful.
As with other OASIS-based measures, a performance score for the
measure would only be calculated for HHAs that have 20 or more episodes
during a performance year. We would use the same methodology to risk-
adjust by using OASIS-C2 items and the prediction model described
above. The prediction model for this outcome measure uses 55 risk
factors with each risk factor significant at p < 0.0001. The
correlation for the model between observed and predicted values as
estimated by Somers' D is 0.672, that yields an estimated coefficient
of determination (r\2\) value based on the Tau-a of 0.205. This
suggests that the variability in the model accounts for (predicts)
approximately 20 percent of the variability in the outcome measure. The
best statistic for evaluating the power of a prediction model that is
derived using logistic regression is the c-statistic. This statistic
identifies the overall accuracy of prediction by comparing observed and
predicted value pairs to the proportion of the time that both predict
the outcome in the same direction with 0.500 being a coin-flip. The
prediction model has a c-statistic equal to 0.836, which is considered
to be extremely strong.
We are considering whether the HHA Correctly Identifies Patient's
Need for Mental or Behavioral Health Supervision measure or the
Caregiver Can/Does Provide for Patient's Mental or Behavioral Health
Supervision Need measure would be most meaningful to include in the
Model. We are also considering the interactions between the Home Health
Grouping Model (HHGM) proposal on quality measures discussed in section
III of this proposed rule and the HHVBP Model for the quality measures
discussed in section IV.B of this proposed rule. We are soliciting
public comments on the methodologies, analyses used to test the quality
measure, and issues described in this section for future measure
considerations. We will continue to share analyses as they become
available with participating HHAs during future webinars.
[[Page 35341]]
V. Proposed Updates to the Home Health Care Quality Reporting Program
(HH QRP)
A. Background and Statutory Authority
Section 1895(b)(3)(B)(v)(II) of the Act requires that for 2007 and
subsequent years, each HHA submit to the Secretary in a form and
manner, and at a time, specified by the Secretary, such data that the
Secretary determines are appropriate for the measurement of health care
quality. To the extent that an HHA does not submit data in accordance
with this clause, the Secretary is directed to reduce the home health
market basket percentage increase applicable to the HHA for such year
by 2 percentage points. As provided at section 1895(b)(3)(B)(vi) of the
Act, depending on the market basket percentage increase applicable for
a particular year, the reduction of that increase by 2 percentage
points for failure to comply with the requirements of the HH QRP, and
further reduction of the increase by the productivity adjustment
described in section 1886(b)(3)(B)(xi)(II) of the Act, may result in
the home health market basket percentage increase 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.
We use the terminology ``CY [year] HH QRP'' to refer to the
calendar year for which the HH QRP requirements applicable to that
calendar year must be met in order for an HHA to avoid a 2 percentage
point reduction to its market basket percentage increase under section
1895(b)(3)(B)(v)(I) of the Act when calculating the payment rates
applicable to it for that calendar year.
The Improving Medicare Post-Acute Care Transformation Act of 2014
(Pub. L. 113-185, enacted on October 6, 2014) (IMPACT Act) amended
Title XVIII of the Act, in part, by adding new section 1899B of the
Act, entitled ``Standardized Post-Acute Care Assessment Data for
Quality, Payment, and Discharge Planning,'' and by enacting new data
reporting requirements for certain post-acute care (PAC) providers,
including Home Health Agencies (HHAs). Specifically, new sections
1899B(a)(1)(A)(ii) and (iii) of the Act require HHAs, Inpatient
Rehabilitation Facilities (IRFs), Long Term Care Hospitals (LTCHs) and
Skilled Nursing Facilities (SNFs), under each of their respective
quality reporting program (which, for HHAs, is found at section
1895(b)(3)(B)(v) of the Act), to report data on quality measures
specified under section 1899B(c)(1) of the Act for at least five
domains, and data on resource use and other measures specified under
section 1899B(d)(1) of the Act for at least three domains. Section
1899B(a)(1)(A)(i) of the Act further requires each of these PAC
providers to report under their respective quality reporting program
standardized patient assessment data in accordance with subsection (b)
for at least the quality measures specified under subsection (c)(1) and
that is for five specific categories: Functional status; cognitive
function and mental status; special services, treatments, and
interventions; medical conditions and co-morbidities; and impairments.
All of the data that must be reported in accordance with section
1899B(a)(1)(A) of the Act must be standardized and interoperable, so as
to allow for the exchange of the information among PAC providers and
other providers, as well as for the use of such data to enable access
to longitudinal information and to facilitate coordinated care. We
refer readers to the CY 2016 HH PPS final rule (80 FR 68690 through
68692) for additional information on the IMPACT Act and its
applicability to HHAs.
B. General Considerations Used for the Selection of Quality Measures
for the HH QRP
We refer readers to the CY 2016 HH PPS final rule (80 FR 68695
through 68698) for a detailed discussion of the considerations we apply
in measure selection for the HH QRP, such as alignment with the CMS
Quality Strategy,\110\ which incorporates the three broad aims of the
National Quality Strategy.\111\ As part of our consideration for
measures for use in the HH QRP, we review and evaluate measures that
have been implemented in other programs and take into account measures
that have been endorsed by NQF for provider settings other than the HH
setting. We have previously adopted measures with the term
``Application of'' in the names of those measures. We have received
questions pertaining to the term ``application'' and want to clarify
that when we refer to a measure as an ``Application of'' the measure,
we mean that the measure would be used in a setting other than the
setting for which it was endorsed by the NQF. For example, in the FY
2016 SNF PPS Rule (80 FR 46440 through 46444 we adopted an Application
of Percent of Residents with Experiencing Falls with Major Injury (Long
Stay) (NQF #0674), which is endorsed for the Nursing Home setting but
not the SNF setting. For such measures, we intend to seek NQF
endorsement for the HH setting, and if the NQF endorses one or more of
them, we will update the title of the measure to remove the reference
to ``Application of.''
---------------------------------------------------------------------------
\110\ https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/QualityInitiativesGenInfo/CMS-Quality-Strategy.html.
\111\ https://www.ahrq.gov/workingforquality/nqs/nqs2011annlrpt.htm.
---------------------------------------------------------------------------
C. Accounting for Social Risk Factors in the HH QRP
We consider related factors that may affect measures in the HH QRP.
We understand that social risk factors such as income, education, race
and ethnicity, employment, disability, community resources, and social
support (certain factors of which are also sometimes referred to as
socioeconomic status (SES) factors or socio-demographic status (SDS)
factors) play a major role in health. One of our core objectives is to
improve beneficiary outcomes including reducing health disparities, and
we want to ensure that all beneficiaries, including those with social
risk factors, receive high quality care. In addition, we seek to ensure
that the quality of care furnished by providers and suppliers is
assessed as fairly as possible under our programs while ensuring that
beneficiaries have adequate access to excellent care.
We have been reviewing reports prepared by the Office of the
Assistant Secretary for Planning and Evaluation (ASPE \112\) and the
National Academies of Sciences, Engineering, and Medicine on the issue
of measuring and accounting for social risk factors in CMS' value-based
purchasing and quality reporting programs, and considering options on
how to address the issue in these programs. On December 21, 2016, ASPE
submitted a Report to Congress on a study it was required to conduct
under section 2(d) of the Improving Medicare Post-Acute Care
Transformation (IMPACT) Act of 2014. The study analyzed the effects of
certain social risk factors of Medicare beneficiaries on quality
measures and measures of resource use used in one or more of nine
Medicare value-based purchasing programs.\113\ The report also included
considerations for strategies to account for social risk factors in
these programs. In a January 10, 2017 report released by The National
Academies of Sciences, Engineering, and Medicine, that body provided
various potential
[[Page 35342]]
methods for measuring and accounting for social risk factors, including
stratified public reporting.\114\
---------------------------------------------------------------------------
\112\ https://aspe.hhs.gov/pdf-report/report-congress-social-risk-factors-and-performance-under-medicares-value-based-purchasing-programs.
\113\ https://aspe.hhs.gov/pdf-report/report-congress-social-risk-factors-and-performance-under-medicares-value-based-purchasing-programs.
\114\ National Academies of Sciences, Engineering, and Medicine.
2017. Accounting for social risk factors in Medicare payment.
Washington, DC: The National Academies Press.
---------------------------------------------------------------------------
As discussed in the CY 2017 HH PPS final rule, the NQF has
undertaken a 2-year trial period in which new measures, measures
undergoing maintenance review, and measures endorsed with the condition
that they enter the trial period can be assessed to determine whether
risk adjustment for selected social risk factors is appropriate for
these measures. Measures from the HH QRP, Rehospitalization During the
First 30 Days of Home Health (NQF #2380), and Emergency Department Use
without Hospital Readmission During the First 30 Days of Home Health
(NQF #2505) are being addressed in this trial. This trial entails
temporarily allowing inclusion of social risk factors in the risk-
adjustment approach for these measures. At the conclusion of the trial,
NQF will issue recommendations on the future inclusion of social risk
factors in risk adjustment for quality measures.
As we continue to consider the analyses and recommendations from
these reports and await the results of the NQF trial on risk adjustment
for quality measures, we are continuing to work with stakeholders in
this process. As we have previously communicated, we are concerned
about holding providers to different standards for the outcomes of
their patients with social risk factors because we do not want to mask
potential disparities or minimize incentives to improve the outcomes
for disadvantaged populations. Keeping this concern in mind, while we
sought input on this topic previously, we continue to seek public
comment on whether we should account for social risk factors in
measures in the HH QRP, and if so, what method or combination of
methods would be most appropriate for accounting for social risk
factors. Examples of methods include: Confidential reporting to
providers of measure rates stratified by social risk factors, public
reporting of stratified measure rates, and potential risk adjustment of
a particular measure as appropriate based on data and evidence.
In addition, we are seeking public comment on which social risk
factors might be most appropriate for reporting stratified measure
scores and potential risk adjustment of a particular measure. Examples
of social risk factors include, but are not limited to, dual
eligibility/low-income subsidy, race and ethnicity, and geographic area
of residence. We are seeking comments on which of these factors,
including current data sources where this information would be
available, could be used alone or in combination, and whether other
data should be collected to better capture the effects of social risk.
We will take commenters' input into consideration as we continue to
assess the appropriateness and feasibility of accounting for social
risk factors in the HH QRP. We note that any such changes would be
proposed through future notice and comment rulemaking.
We look forward to working with stakeholders as we consider the
issue of accounting for social risk factors and reducing health
disparities in CMS programs. Of note, implementing any of the above
methods would be taken into consideration in the context of how this
and other CMS programs operate (for example, data submission methods,
availability of data, statistical considerations relating to
reliability of data calculations, among others), so we also welcome
comment on operational considerations. We are committed to ensuring
that beneficiaries have access to and receive excellent care, and that
the quality of care furnished by providers and suppliers is assessed
fairly in CMS programs.
D. Proposed Data Elements for Removal From OASIS
We are proposing to remove 247 data elements from 35 OASIS items
collected at specific time points during a home health episode. These
data elements are not used in the calculation of quality measures
already adopted in the HH QRP, nor are they being used for previously
established purposes unrelated to the HH QRP, including payment,
survey, the HH VBP Model or care planning. A list of the proposed 35
OASIS items and data elements are listed in Table 45 and also at
https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HomeHealthQualityInits/OASIS-Data-Sets.html.
Table 45--Proposed Data Elements To Be Removed From OASIS on January 1, 2019
--------------------------------------------------------------------------------------------------------------------------------------------------------
Specific time point
-----------------------------------------------------------------------------------------------
OASIS item Transfer to an
Start of care Resumption of Follow-up inpatient Death at home Discharge from
care facility agency
--------------------------------------------------------------------------------------------------------------------------------------------------------
M0903................................................... .............. .............. .............. 1 1 1
M1011................................................... 6 6 6 .............. .............. ..............
M1017................................................... 6 6 .............. .............. .............. ..............
M1018................................................... 6 6 .............. .............. .............. ..............
M1025................................................... 12 12 12 .............. .............. ..............
M1034................................................... 1 1 .............. .............. .............. ..............
M1036................................................... 4 4 .............. .............. .............. ..............
M1200................................................... 1 1 1 .............. .............. ..............
M1210................................................... 1 1 .............. .............. .............. ..............
M1220................................................... 1 1 .............. .............. .............. ..............
M1230................................................... 1 1 .............. .............. .............. 1
M1240................................................... 1 1 .............. .............. .............. ..............
M1300................................................... 1 1 .............. .............. .............. ..............
M1302................................................... 1 1 .............. .............. .............. ..............
M1320................................................... 1 1 .............. .............. .............. 1
M1322................................................... .............. .............. .............. .............. .............. 1
M1332................................................... .............. .............. .............. .............. .............. 1
M1350................................................... 1 1 .............. .............. .............. ..............
M1410................................................... 3 3 .............. .............. .............. ..............
M1501................................................... .............. .............. .............. 1 .............. 1
[[Page 35343]]
M1511................................................... .............. .............. .............. 5 .............. 5
M1610................................................... .............. .............. .............. .............. .............. 1
M1615................................................... 1 1 .............. .............. .............. 1
M1730................................................... 3 3 .............. .............. .............. ..............
M1750................................................... 1 1 .............. .............. .............. ..............
M1880................................................... 1 1 .............. .............. .............. 1
M1890................................................... 1 1 .............. .............. .............. 1
M1900................................................... 4 4 .............. .............. .............. ..............
M2030................................................... 1 1 1 .............. .............. 1
M2040................................................... 2 2 .............. .............. .............. ..............
M2102 *................................................. 6 6 .............. .............. .............. \**\ 3
M2110................................................... 1 1 .............. .............. .............. ..............
M2250................................................... 7 7 .............. .............. .............. ..............
M2310................................................... .............. .............. .............. \***\ 15 .............. \***\ 15
M2430................................................... .............. .............. .............. 20 .............. ..............
-----------------------------------------------------------------------------------------------
Total............................................... 75 75 20 42 1 34
--------------------------------------------------------------------------------------------------------------------------------------------------------
* M2102 row f to remain collected at Start of Care, Resumption of Care and Discharge from Agency as part of the HH VBP program.
** M2102 rows a,c,d to remain collected at Discharge from Agency for survey purposes.
*** M2310 responses 1,10,OTH,UK to remain collected at Transfer to an Inpatient Facility and Discharge from Agency for survey purposes.
We are inviting public comment on this proposal.
E. Proposed Collection of Standardized Patient Assessment Data Under
the HH QRP
1. Proposed Definition of Standardized Patient Assessment Data
Section 1895(b)(3)(B)(v)(IV)(bb) of the Act requires that beginning
with the CY 2019 HH QRP, HHAs report standardized patient assessment
data required under section 1899B(b)(1) of the Act. For purposes of
meeting this requirement, section 1895(b)(3)(B)(v)(IV)(cc) of the Act
requires that a HHA submit the standardized patient assessment data
required under section 1899B(b)(1) of the Act in the form and manner,
and at the time, as specified by the Secretary.
Section 1899B(b)(1)(B) of the Act describes standardized patient
assessment data as data required for at least the quality measures
described in sections 1899B(c)(1) of the Act and regarding the
following categories:
Functional status, such as mobility and self-care at
admission to a PAC provider and before discharge from a PAC provider;
Cognitive function, such as ability to express and
understand ideas, and mental status, such as depression and dementia;
Special services, treatments and interventions such as the
need for ventilator use, dialysis, chemotherapy, central line
placement, and total parenteral nutrition;
Medical conditions and comorbidities such as diabetes,
congestive heart failure and pressure ulcers;
Impairments, such as incontinence and an impaired ability
to hear, see or swallow; and
Other categories deemed necessary and appropriate by the
Secretary.
As required under section 1899B(b)(1)(A) of the Act, the
standardized patient assessment data must be reported at least for the
beginning of the home health episode (for example, HH start of care/
resumption of care) and end of episode (discharge), but the Secretary
may require the data to be reported more frequently.
In this proposed rule, we are proposing to define the standardized
patient assessment data that HHAs must report under the HH QRP, as well
as the requirements for the reporting of these data. The collection of
standardized patient assessment data is critical to our efforts to
drive improvement in healthcare quality across the four post-acute care
(PAC) settings to which the IMPACT Act applies. We intend to use these
data for a number of purposes, including facilitating their exchange
and longitudinal use among healthcare providers to enable high quality
care and outcomes through care coordination, as well as for quality
measure calculation, and identifying comorbidities that might increase
the medical complexity of a particular admission.
HHAs are currently required to report patient assessment data
through the Outcome and Assessment Information Set (OASIS) by
responding to an identical set of assessment questions using an
identical set of response options (we refer to a solitary question/
response option as a data element and we refer to a group of questions/
responses as data elements), both of which incorporate an identical set
of definitions and standards. The primary purpose of the identical
questions and response options is to ensure that we collect a set of
standardized data elements across HHAs, which we can then use for a
number purposes, including HH payment and measure calculation for the
HH QRP.
LTCHs, IRFs, and SNFs are also required to report patient
assessment data through their applicable PAC assessment instruments,
and they do so by responding to identical assessment questions
developed for their respective settings using an identical set of
response options (which incorporate an identical set of definitions and
standards). Like the OASIS, the questions and response options for each
of these other PAC assessment instruments are standardized across the
PAC provider type to which the PAC assessment instrument applies.
However, the assessment questions and response options in the four PAC
assessment instruments are not currently standardized with each other.
As a result, questions and response options that appear on the OASIS
[[Page 35344]]
cannot be readily compared with questions and response options that
appear, for example, on the Inpatient Rehabilitation Facility-Patient
Assessment Instrument (IRF-PAI) the PAC assessment instrument used by
IRFs. This is true even when the questions and response options are
similar. This lack of standardization across the four PAC provider
types has limited our ability to compare one PAC provider type with
another for purposes such as care coordination and quality improvement.
To achieve a level of standardization across HHAs, LTCHs, IRFs, and
SNFs that enables us to make comparisons between them, we are proposing
to define ``standardized patient assessment data'' as patient or
resident assessment questions and response options that are identical
in all four PAC assessment instruments, and to which identical
standards and definitions apply. Standardizing the questions and
response options across the four PAC assessment instruments is an
essential step in making that data interoperable, allowing it to be
shared electronically, or otherwise, between PAC provider types. It
will enable the data to be comparable for various purposes, including
the development of cross-setting quality measures and to inform payment
models that take into account patient characteristics rather than
setting, as described in the IMPACT Act.
We are inviting public comment on this proposed definition.
2. General Considerations Used for the Selection of Proposed
Standardized Patient Assessment Data
As part of our effort to identify appropriate standardized patient
assessment data for purposes of collecting under the HH QRP, we sought
input from the general public, stakeholder community, and subject
matter experts on items that would enable person-centered, high quality
health care, as well as access to longitudinal information to
facilitate coordinated care and improved beneficiary outcomes.
To identify optimal data elements for standardization, our data
element contractor organized teams of researchers for each category,
with each team working with a group of advisors made up of clinicians
and academic researchers with expertise in PAC. Information-gathering
activities were used to identify data elements, as well as key themes
related to the categories described in section 1899B(b)(1)(B) of the
Act. In January and February 2016, our data element contractor also
conducted provider focus groups for each of the four PAC provider
types, and a focus group for consumers that included current or former
PAC patients and residents, caregivers, ombudsmen, and patient advocacy
group representatives. The Development and Maintenance of Post-Acute
Care Cross-Setting Standardized Patient Assessment Data Focus Group
Summary Report is available at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
Our data element contractor also assembled a 16-member TEP that met
on April 7 and 8, 2016, and January 5 and 6, 2017, in Baltimore,
Maryland, to provide expert input on data elements that are currently
in each PAC assessment instrument, as well as data elements that could
be standardized. The Development and Maintenance of Post-Acute Care
Cross-Setting Standardized Patient Assessment Data TEP Summary Reports
are available at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
As part of the environmental scan, data elements currently in the
four existing PAC assessment instruments were examined to see if any
could be considered for proposal as standardized patient assessment
data. Specifically, this evaluation included consideration of data
elements in OASIS-C2 (effective January 2017); IRF-PAI, v1.4 (effective
October 2016); LCDS, v3.00 (effective April 2016); and MDS 3.0, v1.14
(effective October 2016). Data elements in the standardized assessment
instrument that we tested in the Post-Acute Care Payment Reform
Demonstration (PAC PRD)--the Continuity Assessment Record and public
reporting Evaluation (CARE)--were also considered. A literature search
was also conducted to determine whether additional data elements to
propose as standardized patient assessment data could be identified.
Additionally, we held four Special Open Door Forums (SODFs) on
October 27, 2015; May 12, 2016; September 15, 2016; and December 8,
2016, to present data elements we were considering and to solicit
input. At each SODF, some stakeholders provided immediate input, and
all were invited to submit additional comments via the CMS IMPACT
Mailbox: PACQualityInitiative@cms.hhs.gov.
We also convened a meeting with federal agency subject matter
experts (SMEs) on May 13, 2016. In addition, a public comment period
was open from August 12 to September 12, 2016 to solicit comments on
detailed candidate data element descriptions, data collection methods,
and coding methods. The IMPACT Act Public Comment Summary Report
containing the public comments (summarized and verbatim) and our
responses is available at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
We specifically sought to identify standardized patient assessment
data that we could feasibly incorporate into the LTCH, IRF, SNF, and
HHA assessment instruments and that have the following attributes: (1)
Being supported by current science; (2) testing well in terms of their
reliability and validity, consistent with findings from the Post-Acute
Care Payment Reform Demonstration (PAC PRD); (3) the potential to be
shared (for example, through interoperable means) among PAC and other
provider types to facilitate efficient care coordination and improved
beneficiary outcomes; (4) the potential to inform the development of
quality, resource use and other measures, as well as future payment
methodologies that could more directly take into account individual
beneficiary health characteristics; and (5) the ability to be used by
practitioners to inform their clinical decision and care planning
activities. We also applied the same considerations that we apply with
quality measures, including the CMS Quality Strategy which is framed
using the three broad aims of the National Quality Strategy.
3. Policy for Retaining HH QRP Measures and Proposal To Apply That
Policy to Standardized Patient Assessment Data
In the CY 2017 HH PPS final rule (81 FR 76702), we adopted a policy
that would allow for any quality measure adopted for use in the HH QRP
to remain in effect until the measure is removed, suspended, or
replaced. For further information on how measures are considered for
removal, suspension or replacement, we refer readers to the CY 2017 HH
PPS final rule (81 FR 76702). We propose to apply this same policy to
the standardized patient assessment data that we adopt for the HH QRP.
We are inviting public comment on our proposal.
[[Page 35345]]
4. Policy for Adopting Changes to HH QRP Measures and Proposal To Apply
That Policy to Standardized Patient Assessment Data
In the CY 2017 HH PPS final rule (81 FR 76702), we adopted a
subregulatory process to incorporate updates to HH quality measure
specifications that do not substantively change the nature of the
measure. Substantive changes will be proposed and finalized through
rulemaking. For further information on what constitutes a substantive
versus a nonsubstantive change and the subregulatory process for
nonsubstantive changes, we refer readers to the CY 2017 HH PPS final
rule (81 FR 76702). We propose to apply this policy to the standardized
patient assessment data that we adopt for HH QRP.
We are inviting public comment on our proposal.
5. Quality Measures Previously Finalized for the HH QRP
The HH QRP currently has 23 measures, as outlined in Table 47.
Table 47--Measures Currently Adopted for the HH QRP
------------------------------------------------------------------------
Short name Measure name & data source
------------------------------------------------------------------------
OASIS-based
------------------------------------------------------------------------
Pressure Ulcers.............. Percent of Patients or Residents with
Pressure Ulcers that are New or Worsened
(NQF #0678).* \+\
DRR.......................... Drug Regimen Review Conducted with Follow-
Up for Identified Issues-Post Acute Care
(PAC) Home Health Quality Reporting
Program.\+\
Ambulation................... Improvement in Ambulation/Locomotion (NQF
#0167).
Bathing...................... Improvement in Bathing (NQF #0174).
Dyspnea...................... Improvement in Dyspnea.
Oral Medications............. Improvement in Management of Oral
Medication (NQF #0176).
Pain......................... Improvement in Pain Interfering with
Activity (NQF #0177).
Surgical Wounds.............. Improvement in Status of Surgical Wounds
(NQF #0178).
Bed Transferring............. Improvement in Bed Transferring (NQF
#0175).
Timely Care.................. Timely Initiation Of Care (NQF #0526).
Depression Assessment........ Depression Assessment Conducted.
Influenza.................... Influenza Immunization Received for
Current Flu Season (NQF #0522).
PPV.......................... Pneumococcal Polysaccharide Vaccine Ever
Received (NQF #0525).
Falls Risk................... Multifactor Fall Risk Assessment
Conducted For All Patients Who Can
Ambulate (NQF #0537).
Diabetic Foot Care........... Diabetic Foot Care and Patient/Caregiver
Education Implemented during All
Episodes of Care (NQF #0519).
Drug Education............... Drug Education on All Medications
Provided to Patient/Caregiver during All
Episodes of Care.
------------------------------------------------------------------------
Claims-based
------------------------------------------------------------------------
MSPB......................... Total Estimated Medicare Spending Per
Beneficiary (MSPB)--Post Acute Care
(PAC) Home Health (HH) Quality Reporting
Program (QRP).\+\
DTC.......................... Discharge to Community-Post Acute Care
(PAC) Home Health (HH) Quality Reporting
Program (QRP).\+\
PPR.......................... Potentially Preventable 30-Day Post-
Discharge Readmission Measure for Home
Health Quality Reporting Program.\+\
ACH.......................... Acute Care Hospitalization During the
First 60 Days of Home Health (NQF
#0171).
ED Use....................... Emergency Department Use without
Hospitalization During the First 60 Days
of Home Health (NQF #0173).
Rehospitalization............ Rehospitalization During the First 30
Days of Home Health (NQF #2380).
ED Use without Readmission... Emergency Department Use without Hospital
Readmission During the First 30 Days of
Home Health (NQF #2505).
------------------------------------------------------------------------
HHCAHPs-based
------------------------------------------------------------------------
Professional Care............ How often the home health team gave care
in a professional way.
Communication................ How well did the home health team
communicate with patients.
Team Discussion.............. Did the home health team discuss
medicines, pain, and home safety with
patients.
Overall Rating............... How do patients rate the overall care
from the home health agency.
Willing to Recommend......... Would patients recommend the home health
agency to friends and family.
------------------------------------------------------------------------
* Not currently NQF-endorsed for the HH Setting.
\+\ The data collection period will begin with CY 2017 Q1&2 reporting
for CY 2018 APU determination, followed by the previously established
HH QRP use of 12 months (July 1, 2017-June 30, 2018) of CY 2017
reporting for CY 2019 APU determination. Subsequent years will be
based on the HH July 1-June 30 timeframe for APU purposes. For claims
data, the performance period will use rolling CY claims for subsequent
reporting purposes.
F. HH QRP Quality Measures Proposed Beginning With the CY 2020 HH QRP
Beginning with the CY 2020 HH QRP, in addition to the quality
measures we are retaining under our policy described in section V.B. of
the preamble of this proposed rule, we are proposing to replace the
current pressure ulcer measure entitled Percent of Residents or
Patients with Pressure Ulcers That Are New or Worsened (Short Stay)
(NQF #0678) with a modified version of the measure and to adopt one
measure on patient falls and one measure on assessment of patient
functional status. We are also proposing to characterize the data
elements described below, as standardized patient assessment data under
section 1899B(b)(1)(B) of the Act that must be reported by HHAs under
the HH QRP through the OASIS, under section 1895(b)(3)(B)(v) of the
Act. The proposed measures are as follows:
Changes in Skin Integrity Post-Acute Care: Pressure Ulcer/
Injury.
Application of Percent of Residents Experiencing One or
More Falls with Major Injury (NQF #0674).
Application of Percent of Long-Term Care Hospital Patients
with an Admission and Discharge Functional
[[Page 35346]]
Assessment and a Care Plan That Addresses Function (NQF #2631).
The measures are described in more detail below.
1. Proposal To Replace the Current Pressure Ulcer Quality Measure,
Entitled Percent of Residents or Patients With Pressure Ulcers That Are
New or Worsened (Short Stay) (NQF #0678), With a Modified Pressure
Ulcer Measure, Entitled Changes in Skin Integrity Post-Acute Care:
Pressure Ulcer/Injury
a. Measure Background
In this rule, we are proposing to remove the current pressure ulcer
measure, Percent of Residents or Patients with Pressure Ulcers That Are
New or Worsened (Short Stay) (NQF #0678), from the HH QRP measure set
and to replace it with a modified version of that measure, Changes in
Skin Integrity Post-Acute Care: Pressure Ulcer/Injury, beginning with
the CY 2020 HH QRP. The change in the measure name is to reduce
confusion about the new modified measure. The modified version differs
from the current version of the measure because it includes new or
worsened unstageable pressure ulcers, including deep tissue injuries
(DTIs), in the measure numerator. The proposed modified version of the
measure also contains updated specifications intended to eliminate
redundancies in the assessment items needed for its calculation and to
reduce the potential for underestimating the frequency of pressure
ulcers. The modified version of the measure would satisfy the IMPACT
Act domain of ``Skin integrity and changes in skin integrity.''
b. Measure Importance
As described in the CY 2016 HH PPS final rule (80 FR 68697),
pressure ulcers are high-cost adverse events and are an important
measure of quality. For information on the history and rationale for
the relevance, importance, and applicability of having a pressure ulcer
measure in the HH QRP, we refer readers to the CY 2016 HH PPS final
rule (80 FR 68623).
We are proposing to adopt a modified version of the current
pressure ulcer measure because unstageable pressure ulcers, including
DTIs, are similar to Stage 2, Stage 3, and Stage 4 pressure ulcers in
that they represent poor outcomes, are a serious medical condition that
can result in death and disability, are debilitating and painful and
are often an avoidable outcome of medical
care.115 116 117 118 119 120 Studies show that most pressure
ulcers can be avoided and can also be healed in acute, post-acute, and
long term care settings with appropriate medical care.\121\
Furthermore, some studies indicate that DTIs, if managed using
appropriate care, can be resolved without deteriorating into a worsened
pressure ulcer.122 123
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\115\ Casey, G. (2013). ``Pressure ulcers reflect quality of
nursing care.'' Nurs N Z 19(10): 20-24.
\116\ Gorzoni, M.L. and S.L. Pires (2011). ``Deaths in nursing
homes.'' Rev Assoc Med Bras 57(3): 327-331.
\117\ 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.
\118\ White-Chu, E.F., et al. (2011). ``Pressure ulcers in long-
term care.'' Clin Geriatr Med 27(2): 241-258.
\119\ 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.
\120\ Bennet, G, Dealy, C, Posnett, J (2004). The cost of
pressure ulcers in the UK, Age and Aging, 33(3):230-235.
\121\ Black, Joyce M., et al. ``Pressure ulcers: avoidable or
unavoidable? Results of the national pressure ulcer advisory panel
consensus conference.'' Ostomy-Wound Management 57.2 (2011): 24.
\122\ Sullivan, R. (2013). A Two-year Retrospective Review of
Suspected Deep Tissue Injury Evolution in Adult Acute Care Patients.
Ostomy Wound Management 59(9) https://www.o-wm.com/article/two-year-retrospective-review-suspected-deep-tissue-injury-evolution-adult-acute-care-patien.
\123\ Posthauer, ME, Zulkowski, K. (2005). Special to OWM: The
NPUAP Dual Mission Conference: Reaching Consensus on Staging and
Deep Tissue Injury. Ostomy Wound Management 51(4) https://www.o-wm.com/content/the-npuap-dual-mission-conference-reaching-consensus-staging-and-deep-tissue-injury.
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While there are few studies that provide information regarding the
incidence of unstageable pressure ulcers in PAC settings, an analysis
conducted by our measure development contractor indicated that adding
unstageable pressure ulcers to the quality measure numerator would
result in a higher percentage of patients with new or worsened pressure
ulcers in HHA settings and increase the variability of measure scores.
A higher percentage indicates lower quality. This increased variability
serves to improve the measure by improving the ability of the measure
to distinguish between high and low quality home health agencies.
Given the low prevalence of pressure ulcers in the home health
setting, the addition of unstageable ulcers to this measure should
enhance variability. Analysis of 2015 OASIS data found that in
approximately 1.2 percent, or more than 70,000 episodes, the patient
had an unstageable ulcer upon admission. Patients in more than 13,000
episodes were discharged with an unstageable ulcer. In addition,
unstageable ulcers due to slough/eschar worsened between admission and
discharge in approximately 5,000 episodes of care. In conclusion, the
inclusion of unstageable pressure ulcers, including DTIs, in the
numerator of this measure is expected to increase measure scores and
variability in measure scores, thereby improving the ability to
discriminate among poor- and high-performing HHAs.
Testing shows similar results in other PAC settings. For example,
in SNFs, using data from Quarter 4 2015 through Quarter 3 2016, the
mean score on the currently implemented pressure ulcer measure is 1.75
percent, compared with 2.58 percent in the proposed measure. In the
proposed measure, the SNF mean score is 2.58 percent; the 25th and 75th
percentiles are 0.65 percent and 3.70 percent, respectively; and 20.32
percent of facilities have perfect scores. In LTCHs, using data from
Quarter 1 through Quarter 4 2015, the mean score on the currently
implemented pressure ulcer measure is 1.95 percent, compared with 3.73
percent in the proposed measure. In the proposed measure, the LTCH mean
score is 3.73 percent; the 25th and 75th percentiles are 1.53 percent
and 4.89 percent, respectively; and 5.46 percent of facilities have
perfect scores. In IRFs, using data from Quarter 4 2016, the mean score
on the currently implemented pressure ulcer measure is 0.64 percent,
compared with 1.46 percent in the proposed measure. In the proposed
measure, the IRF mean score is 1.46 percent and the 25th and 75th
percentiles are 0 percent and 2.27 percent, respectively. The inclusion
of unstageable pressure ulcers, including DTIs, in the numerator of
this measure is expected to increase measure scores and variability in
measure scores, thereby improving the ability to distinguish between
poor and high performing HHAs.
This increased variability of scores across quarters and deciles
may improve the ability of the measure to distinguish between high and
low performing providers across PAC settings.
c. Stakeholder Feedback
Our measure development contractor sought input from subject matter
experts, including Technical Expert Panels (TEPs), over the course of
several years on various skin integrity topics and specifically those
associated with the inclusion of unstageable pressure ulcers including
DTIs. Most recently, on July 18, 2016, a TEP convened by our measure
development contractor provided input on the technical specifications
of this proposed quality measure, including the feasibility of
implementing the proposed measure's
[[Page 35347]]
updates across PAC settings. The TEP supported the use of the proposed
measure across PAC settings, including the use of different data
elements for measure calculation. The TEP supported the updates to the
measure across PAC settings, including the inclusion in the numerator
of unstageable pressure ulcers due to slough and/or eschar that are new
or worsened, new unstageable pressure ulcers due to a non-removable
dressing or device, and new DTIs. The TEP recommended supplying
additional guidance to providers regarding each type of unstageable
pressure ulcer. This support was in agreement with earlier TEP
meetings, held on June 13, and November 15, 2013, which had recommended
that CMS update the specifications for the pressure ulcer measure to
include unstageable pressure ulcers in the numerator.124 125
Exploratory data analysis conducted by our measure development
contractor suggests that the addition of unstageable pressure ulcers,
including DTIs, will increase the observed incidence of new or worsened
pressure ulcers at the facility level and may improve the ability of
the proposed quality measure to discriminate between poor- and high-
performing agencies.
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\124\ 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.
\125\ 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.
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We solicited stakeholder feedback on this proposed measure by means
of a public comment period held from October 17, through November 17,
2016. In general, we received considerable support for the proposed
measure. A few commenters supported all of the changes to the current
pressure ulcer measure that resulted in the proposed measure, with one
commenter noting the significance of the work to align the pressure
ulcer quality measure specifications across the PAC settings. Many
commenters supported the inclusion of unstageable pressure ulcers due
to slough/eschar, due to non-removable dressing/device, and DTIs in the
proposed quality measure. Other commenters did not support the
inclusion of DTIs in the proposed quality measure because they stated
that there is no universally accepted definition for this type of skin
injury.
Some commenters provided feedback on the data elements used to
calculate the proposed quality measure. We believe that these data
elements will promote facilitation of cross-setting quality comparison
as mandated by the IMPACT Act, alignment between quality measures and
payment, reduction in redundancies in assessment items, and prevention
of inappropriate underestimation of pressure ulcers. The currently
implemented pressure ulcer measure is calculated using retrospective
data elements that assess the number of new or worsened pressure ulcers
at each stage, while the proposed measure is calculated using data
elements that assess the current number of unhealed pressure ulcers at
each stage, and the number of these that were present upon admission,
which are subtracted from the current number at that stage. Some
commenters did not support the data elements that would be used to
calculate the proposed measure, and requested further testing of these
data elements. Other commenters supported the use of these data
elements stating that these data elements simplified the measure
calculation process.
The public comment summary report for the proposed measure is
available on the CMS Web site at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
The NQF-convened Measures Application Partnership (MAP) Post-Acute
Care/Long-Term Care (PAC/LTC) Workgroup met on December 14 and 15,
2016, and provided input to us about this proposed measure. The MAP
provided a recommendation of ``support for rulemaking'' for use of the
proposed measure in the HH QRP. The MAP Coordinating Committee met on
January 24 and 25, 2017, and provided a recommendation of ``conditional
support for rulemaking'' for use of the proposed measure in the HH QRP.
The MAP's conditions of support include that, as a part of measure
implementation, we provide guidance on the correct collection and
calculation of the measure result, as well as guidance on public
reporting Web sites explaining the impact of the specification changes
on the measure result. The MAP's conditions also specify that CMS
continue analyzing the proposed measure to investigate unexpected
results reported in public comment. We intend to fulfill these
conditions by offering additional training opportunities and
educational materials in advance of public reporting, and by continuing
to monitor and analyze the proposed measure. We provide private
provider feedback reports as well as a Quarterly Quality Measure report
that allow HHAs to track their measure outcomes for QI purposes. Aside
from those reports, we conduct internal monitoring and evaluation of
our measures to ensure that the measures are performing as they were
intended to perform during the development of the measure. More
information about the MAP's recommendations for this measure is
available at https://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=84452.
We reviewed the NQF's consensus endorsed measures and were unable
to identify any home health measures that address changes in skin
integrity related to pressure ulcers. Therefore, based on the evidence
previously discussed, we are proposing to adopt the quality measure
entitled, Changes in Skin Integrity Post-Acute Care: Pressure Ulcer/
Injury, for the HH QRP beginning with the CY 2020 HH QRP. We plan to
submit the proposed measure to the NQF for endorsement consideration as
soon as feasible.
d. Data Collection
The data for this quality measure would be collected using the
OASIS data set, which is currently submitted by HHAs through the
Quality Improvement and Evaluation System (QIES) Assessment Submission
and Processing (ASAP) System. The required items applicable to this
measure are already reported by HHAs for patients and episodes of care
meeting statutorily-defined criteria. While the inclusion of
unstageable wounds in the proposed measure results in a measure
calculation methodology that is different from the methodology used to
calculate the current pressure ulcer measure, the data elements needed
to calculate the proposed measure are already included on the OASIS
data set. In addition, our proposal to eliminate duplicative data
elements that were used in calculation of the current pressure ulcer
measure will result in an overall reduced reporting burden for HHAs for
the proposed measure. For more information on OASIS data set submission
using the QIES ASAP System, we refer readers to https://www.qtso.com/.
[[Page 35348]]
For technical information about this proposed measure, including
information about the measure calculation and the standardized patient
assessment data elements used to calculate this measure, we refer
readers to the document titled, Proposed Measure Specifications and
Standardized Data Elements for CY 2018 HH QRP Notice of Proposed
Rulemaking, available at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HomeHealthQualityInits/HHQIQualityMeasures.html.
We are proposing that HHAs would begin reporting the proposed
pressure ulcer measure, Changes in Skin Integrity Post-Acute Care:
Pressure Ulcer/Injury, which will replace the current pressure ulcer
measure, with data collection beginning with respect to admissions and
discharges occurring on or after January 1, 2019.
We are inviting public comment on our proposal to remove the
current pressure ulcer measure, Percent of Residents or Patients with
Pressure Ulcers That Are New or Worsened (Short Stay) (NQF #0678), and
replace it with a modified version of that measure, entitled, Changes
in Skin Integrity Post-Acute Care: Pressure Ulcer/Injury, beginning
with the CY 2020 HH QRP.
2. Proposal To Address the IMPACT Act Domain of Functional Status,
Cognitive Function, and Changes in Function and Cognitive Function:
Application of Percent of Long-Term Care Hospital Patients With an
Admission and Discharge Functional Assessment and a Care Plan That
Addresses Function (NQF #2631)
a. Measure Background
Sections 1899B(d)(1)(B) of the Act requires that no later than the
specified application date (which under section 1899B(a)(1)(E)(ii) is
January 1, 2019 for HHAs, and October 1, 2016 for SNFs, IRFs and
LTCHs), the Secretary specify a quality measure to address the domain
of ``Functional status, cognitive function, and changes in function and
cognitive function.'' We propose to adopt the measure, Application of
Percent of Long-Term Care Hospital Patients with an Admission and
Discharge Functional Assessment and a Care Plan That Addresses Function
(NQF #2631) for the HH QRP, beginning with the CY 2020 program year.
This is a process measure that reports the percentage of patients with
an admission and discharge functional assessment and treatment goal
that addresses function. The treatment goal provides evidence that a
care plan with a goal has been established for the HH patient.
The National Committee on Vital and Health Statistics' Subcommittee
on Health,\126\ noted that ``information on functional status is
becoming increasingly essential for fostering healthy people and a
healthy population. Achieving optimal health and well-being for
Americans requires an understanding across the life span of the effects
of people's health conditions on their ability to do basic activities
and participate in life situations in other words, their functional
status.'' This is supported by research showing that patient and
resident functioning is associated with important outcomes such as
discharge destination and length of stay in inpatient settings,\127\ as
well as the risk of nursing home placement and hospitalization of older
adults living in the community.\128\ For example, many patients who
utilize HH services may be at risk for a decline in function due to
limited mobility and ambulation.\129\ Thus, impairment in function
activities such as self-care and mobility is highly prevalent in HH
patients. For example, in 98 percent of the over six million HH
episodes in 2015, the patient had at least one limitation or was not
completely independent in self-care activities such as grooming, upper
and lower body dressing, bathing, toilet hygiene, and/or feeding/
eating.\130\
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\126\ Subcommittee on Health National Committee on Vital and
Health Statistics, ``Classifying and Reporting Functional Status''
(2001).
\127\ Reistetter TA, Graham JE, Granger CV, Deutsch A,
Ottenbacher KJ. Utility of Functional Status for Classifying
Community Versus Institutional Discharges after Inpatient
Rehabilitation for Stroke. Archives of Physical Medicine and
Rehabilitation, 2010; 91:345-350.
\128\ Miller EA, Weissert WG. Predicting Elderly People's Risk
for Nursing Home Placement, Hospitalization, Functional Impairment,
and Mortality: A Synthesis. Medical Care Research and Review, 57; 3:
259-297.
\129\ Kortebein, P., Ferrando, A., Lombebeida, J., Wolfe, R., &
Evans, W.J. (2007). Effect of 10 days of bed rest on skeletal muscle
in health adults. JAMA; 297(16):1772-4.
\130\ Kortebein, P., Ferrando, A., Lombebeida, J., Wolfe, R., &
Evans, W.J. (2007). Effect of 10 days of bed rest on skeletal muscle
in health adults. JAMA; 297(16):1772-4.
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The primary goal of home health care is to provide restorative care
when improvement is expected, maintain function and health status if
improvement is not expected, slow the rate of functional decline to
avoid institutionalization in an acute or post-acute setting, and/or
facilitate transition to end-of-life care as
appropriate.131 132 Home health care can positively impact
functional outcomes. In stroke patients, home-based rehabilitation
programs administered by home health clinicians significantly improved
ADL function and gait performance.\133\ Home health services, delivered
by a registered nurse, positively impacted patient Quality of Life
(QOL) and clinical outcomes, including significant improvement in
dressing lower body, bathing, meal preparation, shopping, and
housekeeping. For some home health patients, achieving independence
within the living environment and improved community mobility might be
the goal of care. For others, the goal of care might be to slow the
rate of functional decline to avoid institutionalization.\134\
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\131\ Riggs, J. S. & Madigan, E. A. (2012). Describing variation
in home health care episodes for patients with heart failure. Home
Health Care Management and Practice, 24(3): 146-152.
\132\ Ellenbecker, C.H., Samia, L., Cushman, M.J., & Alster, K
(2008). Patient safety and quality: an evidence-based handbook for
nurses. Rockville (MD): agency for healthcare research and quality
(US); 2008 Apr. Chapter 13.
\133\ Asiri, F. Y., Marchetti, G. F., Ellis, J. L., Otis, L.,
Sparto, P. J., Watzlaf, V., & Whitney, S. L. (2014). Predictors of
functional and gait outcomes for persons poststroke undergoing home-
based rehabilitation. Journal of Stroke and Cerebrovascular
Diseases: The Official Journal of National Stroke Association,
23(7), 1856-1864. https://doi.org/10.1016/j.jstrokecerebrovasdis.2014.02.025.
\134\ Ellenbecker, C.H., Samia, L., Cushman, M.J., & Alster, K
(2008). Patient safety and quality: an evidence-based handbook for
nurses. Rockville (MD): agency for healthcare research and quality
(US); 2008 Apr. Chapter 13.
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Patients' functional status is associated with important patient
outcomes, so measuring and monitoring the patients' extent of engaging
in self-care and mobility is valuable. Functional decline among the
elderly;\135\ and chronic illness comorbidities, such as chronic pain
among the older adult population 136 137 are associated with
decreases in self-sufficiency and patient activation (defined as the
patient's knowledge and confidence in self-managing their health).
Impaired mobility, frailty, and low physical activity are associated
with institutionalization,\138\ higher risk of
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falls and falls-related hip fracture and death,139 140
greater risk of undernutrition,\141\ higher rates of inpatient
admission from the emergency department,\142\ and higher prevalence of
hypertension and diabetes.\143\
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\135\ Gleason, K. T., Tanner, E. K., Boyd, C. M., Saczynski, J.
S., & Szanton, S. L. (2016). Factors associated with patient
activation in an older adult population with functional
difficulties. Patient Education and Counseling, 99(8), 1421-1426.
https://doi.org/10.1016/j.pec.2016.03.011.
\136\ Roberts AR, Betts Adams K, Beckette & Warner C. (2016).
Effects of chronic illness on daily life and barriers to self-care
for older women: a mixed-methods exploration. J Women Aging, Jul
25:1-11.
\137\ Wu, J.-R., Lennie, T. A., & Moser, D. K. (2016). A
prospective, observational study to explore health disparities in
patients with heart failure-ethnicity and financial status. European
Journal of Cardiovascular Nursing: Journal of the Working Group on
Cardiovascular Nursing of the European Society of Cardiology.
https://doi.org/10.1177/1474515116641296.
\138\ Hajek, A., Brettschneider, C., Lange, C., Posselt, T.,
Wiese, B., Steinmann, S., Weyerer, S., Werle, J., Pentzek, M.,
Fuchs, A., Stein, J., Luck, T., Bickel, H., M[ouml]sch, E., Wagner,
M., Jessen, F., Maier, W., Scherer, M., Riedel-Heller, S.G.,
K[ouml]nig, H.H., & AgeCoDe Study Group. (2015). Longitudinal
Predictors of Institutionalization in Old Age. PLoS One,
10(12):e0144203.
\139\ Akahane, M., Maeyashiki, A., Yoshihara, S., Tanaka, Y., &
Imamura, T. (2016). Relationship between difficulties in daily
activities and falling: loco-check as a self-assessment of fall
risk. Interactive Journal of Medical Research, 5(2), e20. https://doi.org/10.2196/ijmr.5590.
\140\ Zaslavsky, O., Zelber-Sagi, S., Gray, S. L., LaCroix, A.
Z., Brunner, R. L., Wallace, R. B., . . . Woods, N. F. (2016).
Comparison of Frailty Phenotypes for Prediction of Mortality,
Incident Falls, and Hip Fracture in Older Women. Journal of the
American Geriatrics Society, 64(9), 1858--1862. https://doi.org/10.1111/jgs.14233.
\141\ van der Pols-Vijlbrief, R., Wijnhoven, H. A. H., Bosmans,
J. E., Twisk, J. W. R., & Visser, M. (2016). Targeting the
underlying causes of undernutrition. Cost-effectiveness of a
multifactorial personalized intervention in community-dwelling older
adults: A randomized controlled trial. Clinical Nutrition
(Edinburgh, Scotland). https://doi.org/10.1016/j.clnu.2016.09.030.
\142\ Hominick, K., McLeod, V., & Rockwood, K. (2016).
Characteristics of older adults admitted to hospital versus those
discharged home, in emergency department patients referred to
internal medicine. Canadian Geriatrics Journal: CGJ, 19(1), 9-14.
https://doi.org/10.5770/cgj.19.195.
\143\ Halaweh, H., Willen, C., Grimby-Ekman, A., & Svantesson,
U. (2015). Physical activity and health-related quality of life
among community dwelling elderly. J Clin Med Res, 7(11), 845-52.
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In addition, the assessment of functional ability and provision of
treatment plans directed toward improving or maintaining functional
ability could impact health care costs. Providing comprehensive home
health care, which includes improving or maintaining functional ability
for frail elderly adults, can reduce the likelihood of hospital
readmissions or emergency department visits, leading to reduced health
care service expenditures.144 145 146 Reducing preventable
rehospitalizations, which made up approximately 17 percent of
Medicare's $102.6 billion in 2004 hospital payments, creates the
potential for large health care cost savings.147 148
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\144\ Hirth, V., Baskins, J., & Dever-Bumba, M. (2009). Program
of all-inclusive care (PACE): Past, present, and future. Journal of
the American Medical Directors Association, 10, 155-160.
\145\ Mukamel, D. B., Fortinsky, R. H., White, A., Harrington,
C., White, L. M., & Ngo-Metzger, Q. (2014). The policy implications
of the cost structure of home health agencies. Medicare & Medicaid
Research Review, 4(1). https://doi.org/10.5600/mmrr2014-004-01-a03.
\146\ Meunier, M. J., Brant, J. M., Audet, S., Dickerson, D.,
Gransbery, K., & Ciemins, E. L. (2016). Life after PACE (Program of
All-Inclusive Care for the Elderly): A retrospective/prospective,
qualitative analysis of the impact of closing a nurse practitioner
centered PACE site. Journal of the American Association of Nurse
Practitioners. https://doi.org/10.1002/2327-6924.12379.
\147\ Jencks, S.F., Williams, M.V., and Coleman, E.A. (2009).
Rehospitalizations among patients in the Medicare fee-for-service
program. New England Journal of Medicine; 360(14):1418-28.
\148\ Tao, H., Ellenbecker, C. H., Chen, J., Zhan, L., & Dalton,
J. (2012). The influence of social environmental factors on
rehospitalization among patients receiving home health care
services. ANS. Advances in Nursing Science, 35(4), 346-358. https://doi.org/10.1097/ANS.0b013e318271d2ad.
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Further, improving and maintaining functional ability in
individuals with high needs, defined as those with three or more
chronic conditions, may also account for an increase in healthcare
savings. Adults with three or more chronic conditions have nearly four
times the average annual per-person spending for health care services
and prescription medications than the average for all U.S. adults, and
high needs adults with limitations in their ability to perform ADLs,
have even higher average annual health care expenditures.\149\ High
needs individuals with functional limitations spend, on average,
$21,021 on annual health care services, whereas the average annual
health care expenditures for all U.S. adults are approximately
$4,845.\45\
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\149\ Hayes, S.L., Salzberg, C.A., McCarthy, D., Radley, DC,
Abrams, M.K., Shah, T., and Anderson, G.F. (2016). High-Need, High-
Cost Patients: Who are they and how do they use health care--A
population-based comparison of demographics, health care use, and
expenditures. The Commonwealth Fund.
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b. Measure Importance
The majority of individuals who receive PAC services, including
care provided by HHAs, SNFs, IRFs, and LTCHs, have functional
limitations, and many of these individuals are at risk for further
decline in function due to limited mobility and ambulation.\150\ The
patient populations treated by HHAs, SNFs, IRFs, and LTCHs vary in
terms of their functional abilities. For example, for home health
patients, achieving independence within the home environment and
promoting community mobility may be the goal of care. For other home
health patients, the goal of care may be to slow the rate of functional
decline in order to allow the person to remain at home and avoid
institutionalization.\151\ The clinical practice guideline Assessment
of Physical Function \152\ recommends that clinicians document
functional status at baseline and over time to validate capacity,
decline, or progress. Therefore, assessment of functional status at
admission and discharge, as well as establishing a functional goal for
discharge as part of the care plan is an important aspect of patient or
resident care across PAC settings.
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\150\ Kortebein P, Ferrando A, Lombebeida J, Wolfe R, Evans WJ.
Effect of 10 days of bed rest on skeletal muscle in health adults.
JAMA; 297(16):1772-4.
\151\ Ellenbecker CH, Samia L, Cushman MJ, Alster K. Patient
safety and quality in home health care. Patient Safety and Quality:
An Evidence-Based Handbook for Nurses. Vol 1.
\152\ Kresevic DM. Assessment of physical function. In: Boltz M,
Capezuti E, Fulmer T, Zwicker D, editor(s). Evidence-based geriatric
nursing protocols for best practice. 4th ed. New York (NY): Springer
Publishing Company; 2012. p. 89-103.
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Currently, functional assessment data are collected by all four PAC
providers, yet data collection has employed different assessment
instruments, scales, and item definitions. The data cover similar
topics, but are not standardized across PAC settings. The different
sets of functional assessment items coupled with different rating
scales makes communication about patient and resident functioning
challenging when patients and residents transition from one type of
setting to another. Collection of standardized functional assessment
data across HHAs, SNFs, IRFs, and LTCHs using common data items would
establish a common language for patient and resident functioning, which
may facilitate communication and care coordination as patients and
residents transition from one type of provider to another. The
collection of standardized functional status data may also help improve
patient functioning during an episode of care by ensuring that basic
daily activities are assessed for all PAC residents at the start and
end of care, and that at least one functional goal is established.
The functional assessment items included in the proposed functional
status quality measure were originally developed and tested as part of
the Post-Acute Care Payment Reform Demonstration version of the
Continuity Assessment Record and Evaluation (CARE) Item Set, which was
designed to standardize the assessment of a person's status, including
functional status, across acute and post-acute settings (HHAs, SNFs,
IRFs, and LTCHs). The functional status items on the CARE Item Set are
daily activities that clinicians typically assess at the time of
admission and/or discharge to determine patient or resident needs,
evaluate patient or resident progress, and prepare patients, residents,
and their families for a transition to home or to another setting. The
development of the CARE Item Set and a description and rationale for
each item is described in a report entitled ``The Development and
Testing of the Continuity Assessment Record and Evaluation (CARE) Item
Set: Final Report on the Development of the CARE Item Set:
[[Page 35350]]
Volume 1 of 3.'' \153\ Reliability and validity testing were conducted
as part of CMS's Post-Acute Care Payment Reform Demonstration (PAC-
PRD), and we concluded that the functional status items have acceptable
reliability and validity. Testing for the functional assessment items
concluded that the items were able to evaluate all patients on basic
self-care and mobility activities, regardless of functional level or
PAC setting. A description of the testing methodology and results are
available in several reports, including the report entitled ``The
Development and Testing of the Continuity Assessment Record And
Evaluation (CARE) Item Set: Final Report On Reliability Testing: Volume
2 of 3'' \154\ and the report entitled ``The Development and Testing of
The Continuity Assessment Record And Evaluation (CARE) Item Set: Final
Report on Care Item Set and Current Assessment Comparisons: Volume 3 of
3.'' \155\ These reports are available on our Post-Acute Care Quality
Initiatives Web page at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/CARE-Item-Set-and-B-CARE.html.
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\153\ Barbara Gage et al., ``The Development and Testing of the
Continuity Assessment Record and Evaluation (CARE) Item Set: Final
Report on the Development of the CARE Item Set'' (RTI International,
2012).
\154\ Ibid.
\155\ Ibid.
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Additional testing of these functional assessment items was
conducted in a small field test occurring in 2016-2017, capturing data
from 12 HHAs. Preliminary data results yielded moderate to substantial
reliability for the self-care and mobility data items. More information
about testing design and results can be found at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HomeHealthQualityInits/OASIS-Data-Sets.html. The functional status
quality measure we are proposing to adopt beginning with the CY 2020 HH
QRP is a process quality measure that is an application of the NQF-
endorsed quality measure, the Percent of Long-Term Care Hospital
Patients with an Admission and Discharge Functional Assessment and a
Care Plan that Addresses Function (NQF #2631). This quality measure
reports the percent of patients with both an admission and a discharge
functional assessment and a functional treatment goal.
This process measure requires the collection of admission and
discharge functional status data by clinicians using standardized
patient assessment data elements, which assess specific functional
activities, such as self-care and mobility activities. The self-care
and mobility function activities are coded using a 6-level rating scale
that indicates the resident's level of independence with the activity
at both admission and discharge. A higher score indicates more
independence. These functional assessment data elements will be
collected at Start or Resumption of Care (SOC/ROC) and discharge.
For this quality measure, there must be documentation at the time
of admission (SOC) that at least one activity performance (function)
goal is recorded for at least one of the standardized self-care or
mobility function items using the 6-level rating scale. This indicates
that an activity goal(s) has been established. Following this initial
assessment, the clinical best practice would be to ensure that the
patient's care plan reflected and included a plan to achieve such
activity goal(s). At the time of discharge, goal setting and
establishment of a care plan to achieve the goal, is reassessed using
the same 6-level rating scale, allowing for the ability to evaluate
success in achieving the patient's activity performance goals.
To the extent that a patient has an unplanned discharge, for
example, transfer to an acute care facility, the collection of
discharge functional status data may not be feasible. Therefore, for
patients with unplanned discharges, admission functional status data
and at least one treatment goal must be reported, but discharge
functional status data are not required to be reported.
c. Stakeholder Feedback
Our measures contractor convened a TEP on October 17, and October
18, 2016. The TEP was composed of a diverse group of stakeholders with
HH, PAC, and functional assessment expertise. The panel provided input
on the technical specifications of this proposed measure, including the
feasibility of implementing the measure, as well as the overall measure
of reliability and validity. The TEP additionally provided feedback on
the clinical assessment items used to calculate the measure. The TEP
reviewed the measure ``Percent of Long-Term Care Patients with an
Admission and Discharge Functional Assessment and a Care Plan That
Addresses Function (NQF 2631)'' for potential application to the home
health setting. Overall they were supportive of a functional process
measure, noting it could have the positive effect of focusing clinician
attention on functional status and goals. A summary of the TEP
proceedings is available on the PAC Quality Initiatives Downloads and
Videos Web page at https://www.cms.gov/medicare/quality-initiatives-
patient-assessment-instruments/post-acute-care-quality-initiatives/
impact-act-of-2014/impact-act-downloads-and-videos.html.
We also solicited stakeholder feedback on the development of this
measure through a public comment period held from November 4, 2016
through December 5, 2016. Several stakeholders and organizations
supported this measure for implementation and for measure
standardization. Some commenters also provided feedback on the
standardized patient assessment data elements used to calculate the
proposed quality measure. Commenters offered suggestions, including
providing education regarding the difference in measure scales for the
standardized items relative to current OASIS functional items, and
guidance on the type of clinical staff input needed to appropriately
complete new functional assessment items. Commenters also addressed the
feasibility of collecting data for the individual standardized self-
care and mobility items in the home health setting. Finally, commenters
noted the importance of appropriate goal setting when functional
improvement for a patient may not be feasible. The public comment
summary report for the proposed measure is available on the CMS Web
site at https://www.cms.gov/medicare/quality-initiatives-patient-
assessment-instruments/post-acute-care-quality-initiatives/impact-act-
of-2014/impact-act-downloads-and-videos.html.
The NQF-convened MAP met on December 14 and 15, 2016, and provided
input on the use of this proposed measure in the HH QRP. The MAP
recommended ``conditional support for rulemaking'' for this measure.
MAP members noted the measure would drive care coordination and improve
transitions by encouraging the use of standardized functional
assessment items across PAC settings, but recommended submission to the
NQF for endorsement to include the home health setting. More
information about the MAP's recommendations for this measure is
available at https://www.qualityforum.org/Publications/2017/02/MAP_2017_Considerations_for_Implementing_Measures_in_Federal_Programs_-_PAC-LTC.aspx.
We reviewed the NQF's consensus endorsed measures and were unable
to identify any home health measures that address functional
assessment, and treatment goals that address function.
[[Page 35351]]
There are five functional measures in home health that assess
functional activities: (1) Improvement in Ambulation/Locomotion (NQF
#0167); (2) Improvement in Bathing (NQF #0174); (3) Improvement in Bed
Transfer (NQF #0175); (4) Improvement in Management of Oral Medications
(NQF # 0176); and (5) Improvement in Pain Interfering with Activity
(NQF #0177). Our review determined that these setting-specific measures
are not appropriate to meet the specified IMPACT Act domain as they do
not include standardized items or are not included for various other
PAC populations. Specifically:
The items used to collect data for the current home health
measures are less specific, leading to broader measure results, whereas
the standardized patient assessment data items used for the proposed
measure assess core activities such as rolling in bed, walking a
specified distance, or wheelchair capability.
The item coding responses are more detailed when compared
to the non-standardized OASIS item responses, allowing for more
granular data for the measure.
The proposed functional measure will capture a patient's
discharge goal at admission into home health; this detail is not
captured in the existing endorsed HH function measures.
Therefore, based on the evidence discussed above, we are proposing
to adopt the quality measure entitled, Application of Percent of Long-
Term Care Hospital Patients with an Admission and Discharge Functional
Assessment and a Care Plan That Addresses Function (NQF #2631), for the
HH QRP beginning with the CY 2020 HH QRP. We plan to submit the
proposed measure to the NQF for endorsement consideration as soon as is
feasible.
For technical information about this proposed measure, including
information about the measure calculation and the standardized patient
assessment data elements used to calculate this measure, we refer
readers to the document titled, Proposed Measure Specifications and
Standardized Data Elements for CY 2018 HH QRP Notice of Proposed
Rulemaking, available at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HomeHealthQualityInits/HHQIQualityMeasures.html.
d. Data Collection
For purposes of assessment data collection, we propose to add new
functional status items to the OASIS, to be collected at SOC/ROC and
discharge. These items would assess specific self-care and mobility
activities, and would be based on functional items included in the PAC-
PRD version of the CARE Item Set. More information pertaining to item
testing is available on our Post-Acute Care Quality Initiatives Web
page at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/CARE-Item-Set-and-B-CARE.html.
To allow HHAs to fulfill the requirements of the Home Health Agency
Conditions of Participation (HHA CoPs) (82 FR 4504), we are proposing
to add a subset of the functional assessment items to the OASIS, with
collection of these items at Follow-Up (FU). The collection of these
assessment items at FU by HHAs will allow them to fulfill the
requirements outlined in the HHA CoPs that suggest that the collection
of a patient's current health, including functional status, be
collected on the comprehensive assessment.
These new functional status items are standardized across PAC
settings and support the proposed standardized measure. They are
organized into two functional domains: Self-Care and Mobility. Each
domain includes dimensions of these functional constructs that are
relevant for home health patients. The proposed function items that we
would add to the OASIS for purposes of the calculation of this proposed
quality measure do not duplicate existing items currently collected in
that assessment instrument for other purposes. The current OASIS
function items evaluate current ability, whereas the proposed
functional items would evaluate an individual's usual performance at
the time of admission and at the time of discharge for goal setting
purposes. Additionally, there are several key differences between the
existing and new proposed function items that may result in variation
in the patient assessment results including: (1) The data collection
and associated data collection instructions; (2) the rating scales used
to score a resident's level of independence; and (3) the item
definitions. A description of these differences is provided with the
measure specifications available at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HomeHealthQualityInits/HHQIQualityMeasures.html.
Because of the differences between the current function assessment
items (OASIS C-2) and the proposed function assessment items that we
would collect for purposes of calculating the proposed measure, we
would require that HHAs submit data on both sets of items. Data
collection for the new proposed function items do not substitute for
the data collection under the current OASIS ADL and IADL items.
Although providers will collect on the proposed function assessment
items as well as the current assessment items, for reasons previously
described, we believe these items are not duplicative. However, we
request comment on opportunities to streamline reporting to avoid
duplication and minimize burden.
We are proposing that data for the proposed quality measure would
be collected through the OASIS, which HHAs currently submit through the
QIES ASAP system. We refer readers to section V.F.2 of this proposed
rule for more information on the proposed data collection and
submission timeline for this proposed quality measure. If this measure
is finalized, we intend to provide initial confidential feedback to
home health agencies, prior to the public reporting of this measure.
We invite public comment on our proposal to adopt the measure,
Application of Percent of Long-Term Care Hospital Patients with an
Admission and Discharge Functional Assessment and a Care Plan That
Addresses Function (NQF #2631).
3. Proposal To Address the IMPACT Act Domain of ``Incidence of Major
Falls'' Measure: Percent of Residents Experiencing One or More Falls
With Major Injury
a. Measure Background
Sections 1899B(c)(1)(D) of the Act requires that no later than the
specified application date (which under section 1899B(a)(1)(E)(i)(IV)
is January 1, 2019 for HHAs, and October 1, 2016 for SNFs, IRFs and
LTCHs), the Secretary specify a measure to address the domain of
incidence of major falls, including falls with major injury. We propose
to adopt the measure, Application of Percent of Residents Experiencing
One or More Falls with Major Injury (NQF #0674), for which we would
begin to collect data on January 1, 2019 for the CY 2020 HH QRP to meet
this requirement. This proposed outcome measure reports the percentage
of residents who have experienced falls with major injury during
episodes ending in a 3-month period.
b. Measure Importance
Falls affect an estimated 6 to 12 million older adults each year
and are the leading cause of both fatal injury
[[Page 35352]]
and nonfatal hospital admissions.\156\ \157\ Within the home health
population, the risk of falling is significant as approximately one
third of individuals over the age of 65 experienced at least one fall
annually.\158\ Major fall-related injuries among older community-
dwelling adults are a growing health concern within the United
States159 160 because they can have high medical and cost
implications for the Medicare community.\161\ In 2013, the direct
medical cost for falls in older adults was $34 billion \162\ and is
projected to increase to over $101 billion by 2030 due to the aging
population.\163\
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\156\ Bohl, A. A., Phelan, E. A., Fishman, P. A., & Harris, J.
R. (2012). How are the costs of care for medical falls distributed?
The costs of medical falls by component of cost, timing, and injury
severity. The Gerontologist, 52(5): 664-675.
\157\ National Council on Aging (2015). Falls Prevention Fact
Sheet. Retrieved from https://www.ncoa.org/wp-content/uploads/Fact-Sheet_Falls-Prevention.pdf.
\158\ Avin G., K., Hanke A., T., Kirk-Sanche, N., McDonough M.,
C., Shubert E., T., Hardage, J., & Hartley, G. (2015). Management of
Falls in Community-Dwelling Older Adults: Clinical Guidance
Statement From the Academy of Geriatric Physical Therapy of the
American Physical Therapy Association. Physical Therapy, 95(6), 815-
834. doi:10.2522/ptj.20140415.
\159\ Hester, A. L. & Wei, F. (2013). Falls in the community:
state of the science. Clinical Interventions in Aging, 8:675-679.
\160\ Orces, C. H. & Alamgir, H. (2014). Trends in fall-related
injuries among older adults treated in emergency departments in the
USA. Injury Prevention, 20: 421-423.
\161\ Liu, S. W., Obermeyer, Z., Chang, Y., & Shankar, K. N.
(2015). Frequency of ED revisits and death among older adults after
a fall. American Journal of Emergency Medicine, 33(8), 1012-1018.
doi:10.1016/j.ajem.2015.04.023.
\162\ Centers for Disease Control and Prevention (2015b).
Important facts about falls. https://www.cdc.gov/homeandrecreationalsafety/falls/adultfalls.html. Accessed April 19,
2016.
\163\ Houry, D., Florence, C. Bladwin, G., Stevens, J., &
McClure, R. (2015). The CDC Injury Center's response to the growing
public health problem of falls among older adults. American Journal
of Lifestyle Medicine, 10(1), 74-77.
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Evidence from various studies indicates that implementing effective
fall prevention interventions and minimizing the impact of falls that
do occur reduces overall costs, emergency department visits, hospital
readmissions, and overall Medicare resource
utilization.164 165 166 167 In the 2006 Home Assessments and
Modification study, a home visit by an occupational therapist or home
care worker to identify and mitigate potential home hazards and risky
behavior, resulted in a 46 percent reduction in fall rates for those
receiving the intervention compared to controls.\168\ Overall, patients
participating in interventions experienced improved quality of life due
to reduced morbidity, improved functional ability and mobility, reduced
number of falls and injurious falls, and a decrease in the fear of
falling. 169 170 Falls also represent a significant cost
burden to Medicare. Each year, 2.8 million older people are treated in
Emergency Departments for fall related injuries and over 800,000
require hospitalization.\171\ Adjusted to 2015 dollars, nationally,
direct medical costs for non-fatal fall related injuries in older
adults were over $31.3 billion.\172\ Additional health care costs (in
2010 dollars) can range from $3,500 for a fall without serious injury
to $27,000 for a fall with a serious injury.\173\ Between 1988 and
2005, fractures accounted for 84 percent of hospitalizations for fall-
related injuries among older adults.\174\ Researchers evaluated the
cost of fall-related hospitalizations among older adults using the 2011
Texas Hospital Inpatient Discharge Data and determined that the average
cost for fall-related hip fractures was $61,715 for individuals 50 and
older living in metropolitan areas and $55,366 for those living
nonmetropolitan areas.\175\
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\164\ Bamgbade, S., & Dearmon, V. (2016). Fall prevention for
older adults receiving home healthcare. Home Healthcare Now, 34(2),
68-75.
\165\ Carande-Kulis, V., Stevens, J. A., Florence, C. S.,
Beattie, B. L., & Arias, I. (2015). A cost-benefit analysis of three
older adult fall prevention interventions. Journal of Safety
Research, 52, 65-70. doi:10.1016/j.jsr.2014.12.007.
\166\ Cohen, A. M., Miller, J., Shi, X., Sandhu, J., & Lipsitz,
A. (2015). Prevention program lowered the risk of falls and
decreased claims for long-term care services among elder
participants. Health Affairs, 34(6), 971-977.
\167\ Howland, J., Shankar, K. N., Peterson, E. W., & Taylor, A.
A. (2015). Savings in acute care costs if all older adults treated
for fall-related injuries completed matter of balance. Injury
Epidemiology, 2(25), 1-7.
\168\ Pighills AC, Torgerson DJ, Sheldon TA, Drummond AE, Bland
JM. Environmental assessment and modification to prevent falls in
older people. Journal of the American Geriatrics Society.
2011;59(1):26-33.
\169\ Chase, C. A., Mann, K., Wasek, S., & Arbesman, M. (2012).
Systematic review of the effect of home modification and fall
prevention programs on falls and the performance of community-
dwelling older adults. American Journal of Occupational Therapy,
66(3), 284-291.
\170\ Patil, R., Uusi-Rasi, K., Tokola, K., Karinkanta, S.,
Kannus, P., & Sievanen, H. (2015). Effects of a Multimodal Exercise
Program on Physical Function, Falls, and Injuries in Older Women: A
2-Year Community-Based, Randomized Controlled Trial. Journal of the
American Geriatrics Society, 63(7), 1306-1313.
\171\ Centers for Disease Control and Prevention, National
Center for Injury Prevention and Control. Web-based Injury
Statistics Query and Reporting System (WISQARS) [online]. Accessed
August 5, 2016.
\172\ Burns ER, Stevens JA, Lee R. The direct costs of fatal and
non-fatal falls among older adults--United States. J Safety Res
2016;58:99-103.
\173\ Wu S, Keeler EB, Rubenstein LZ, Maglione MA, Shekelle PG.
A cost-effectiveness analysis of a proposed national falls
prevention program. Clin Geriatr Med. 2010;26(4): 751-66.
\174\ Orces, C. H. & Alamgir, H. (2014). Trends in fall-related
injuries among older adults treated in emergency departments in the
USA. Injury Prevention, 20: 421-423.
\175\ Towne, S. D., Ory, M. G., & Smith, M. L. (2014). Cost of
fall-related hospitalizations among older adults: environmental
comparisons from the 2011 Texas hospital inpatient discharge data.
Population Health Management, 17(6), 351-356.
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To meet the IMPACT Act provision requiring the development of a
standardized quality measure for the domain of Incidence of Major Falls
(sections 1899B(c)(1)(D) of the Act), we developed the proposed
standardized measure, The Percent of Residents Experiencing One or More
Falls with Major Injury (Long Stay) (NQF #0674). This quality measure
is NQF-endorsed and has been successfully implemented in the Nursing
Home Quality Initiative for nursing facility long-stay residents since
2011, demonstrating the measure is feasible, appropriate for assessing
PAC quality of care, and could be used as a platform for standardized
quality measure development. This quality measure is standardized
across PAC settings and contains items that are collected uniformly in
each setting's assessment instruments (that is, MDS, IRF-PAI, and
LCDS). Further, an application of the quality measure was adopted for
use in the LTCH QRP in the FY 2014 IPPS/LTCH PPS final rule (78 FR
50874 through 50877), revised in the FY 2015 IPPS/LTCH PPS final rule
(79 FR 50290), and adopted to fulfill IMPACT Act requirements in the FY
2016 IPPS/LTCH PPS final rule (80 FR 49736 through 49739). Data
collection began in April 1, 2016 for LTCHs, and October 1, 2016 for
SNFs and IRFs.
More information on the NQF-endorsed quality measure, the Percent
of Residents Experiencing One or More Falls with Major Injury (Long
Stay) (NQF #0674) is available at https://www.qualityforum.org/QPS/0674.
c. Stakeholder Feedback
A TEP convened by our measure development contractor provided input
on the technical specifications of an application of the quality
measure, the Percent of Residents Experiencing One or More Falls with
Major Injury (Long Stay) (NQF #0674), including the feasibility of
implementing the measure across PAC settings. The TEP was supportive of
the implementation of this measure across PAC settings and was also
supportive of our efforts to standardize this measure for cross-setting
development. More information about this TEP can be found at https://
www.cms.gov/medicare/quality-initiatives-patient-assessment-
instruments/post-acute-care-quality-initiatives/impact-act-of-2014/
impact-act-downloads-and-videos.html.
[[Page 35353]]
In addition, we solicited public comment on this measure from
September 19, 2016 through October 14, 2016. Overall, commenters were
generally supportive of the measure, but raised concerns about the
attribution given that home health clinicians are not present in the
home at all times and recommended risk-adjusting the measure. The
summary of this public comment period can be found at https://
www.cms.gov/medicare/quality-initiatives-patient-assessment-
instruments/post-acute-care-quality-initiatives/impact-act-of-2014/
impact-act-downloads-and-videos.html.
Finally, we presented this measure to the NQF-convened MAP on
December 14, 2016. The MAP conditionally supported the use of an
application of the quality measure, the Percent of Residents
Experiencing One or More Falls with Major Injury (Long Stay) (NQF
#0674) in the HH QRP as a cross-setting quality measure. The MAP
highlighted the clinical significance of falls with major injury, while
noting potential difficulties in collecting falls data and more limited
actionability in the HH setting. The MAP suggested that CMS explore
stratification of measure rates by referral origin when public
reporting. More information about the MAP's recommendations for this
measure is available at https://www.qualityforum.org/Publications/2017/02/MAP_2017_Considerations_for_Implementing_Measures_in_Federal_Programs_-_PAC-LTC.aspx. We are inviting public comment on the stratification of
the proposed measure, specifically on the measure rates for public
reporting. The quality measure, the Percent of Residents Experiencing
One or More Falls with Major Injury (Long Stay) (NQF #0674) is not
currently endorsed for the HH setting. We reviewed the NQF's consensus
endorsed measures and were unable to identify any NQF-endorsed cross-
setting quality measures for that setting that are focused on falls
with major injury. We found one falls-related measure in home health
titled, Multifactor Fall Risk Assessment Conducted for All Patients Who
Can Ambulate (NQF #0537).
We are also aware of one NQF-endorsed measure, Falls with Injury
(NQF #0202), which is a measure designed for adult acute inpatient and
rehabilitation patients capturing ``all documented patient falls with
an injury level of minor or greater on eligible unit types in a
calendar quarter, reported as injury falls per 100 days.'' \176\ After
careful review, we have determined that these measures are not
appropriate to meet the IMPACT Act domain of incidence of major falls.
Specifically:
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\176\ American Nurses Association (2014, April 9). Falls with
injury. Retrieved from https://www.qualityforum.org/QPS/0202.
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NQF #0202 includes minor injuries in the numerator
definition. Including all falls in an outcome measure could result in
providers limiting activity for individuals at higher risk for falls.
NQF #0537 is a process-based measure of HHAs' efforts to
assess the risk for any fall, but not actual falls.
Neither measure is standardized across PAC settings.
We are unaware of any other cross-setting quality measures for
falls with major injury that have been endorsed or adopted by another
consensus organization for the HH setting. Therefore, based on the
evidence discussed above, we are proposing to adopt the quality measure
entitled, An Application of the Measure Percent of Residents
Experiencing One or More Falls with Major Injury (Long Stay) (NQF
#0674), for the HH QRP beginning with the CY 2020 HH QRP. We plan to
submit the proposed measure to the NQF for endorsement consideration as
soon as it is feasible.
d. Data Collection
For purposes of assessment data collection, we propose to add two
new falls-related items to the OASIS. The proposed falls with major
injury item used to calculate the proposed quality measure does not
duplicate existing items currently collected in the OASIS. We propose
to add two standardized items to the OASIS for collection at End of
Care (EOC), which comprises the Discharge from Agency, Death at Home,
and Transfer to an Inpatient Facility time points: J1800 and J1900. The
first item (J1800) is a gateway item that asks whether the patient has
experienced any falls since admission/resumption of care (prior
assessment). If the answer to J1800 is yes, the next item (J1900) asks
for the number of falls with: (a) No injury, (b) injury (except major),
and (c) major injury. The measure is calculated using data reported for
J1900C (number of falls with major injury). This measure would be
calculated at the time of discharge (see Section V.F.3 of this proposed
rule). For technical information about this proposed measure, including
information pertaining to measure calculation and the standardized
patient assessment data element used to calculate this measure, we
refer readers to the document titled, Proposed Measure Specifications
and Standardized Data Elements for CY 2018 HH QRP Notice of Proposed
Rulemaking, available at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HomeHealthQualityInits/HHQIQualityMeasures.html.
We are proposing that data for the proposed quality measure would
be collected through the OASIS, which HHAs currently submit through the
QIES ASAP system. We refer readers to section V.I.4 of this proposed
rule for more information on the proposed data collection and
submission timeline for this proposed quality measure.
We are inviting public comments on our proposal to adopt an
application of the quality measure, the Percent of Residents
Experiencing One or More Falls with Major Injury (Long Stay) (NQF
#0674) for the CY 2020 HH QRP.
G. HH QRP Quality Measures and Measure Concepts Under Consideration for
Future Years
We are inviting public comment on the importance, relevance,
appropriateness, and applicability of each of the quality measures
listed in Table 48 for use in future years in the HH QRP.
Table 48--HH QRP Quality Measures Under Consideration for Future Years
------------------------------------------------------------------------
Functional status, cognitive function,
IMPACT Act domain and changes in function and cognitive
function
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Measures..................... A. Application of NQF #2633--Change in
Self-Care Score for Medical
Rehabilitation Patients.
B. Application of NQF #2634--Change in
Mobility Score for Medical
Rehabilitation Patients.
C. Application of NQF #2635--Discharge
Self-Care Score for Medical
Rehabilitation Patients.
D. Application of NQF #2636--Discharge
Mobility Score for Medical
Rehabilitation Patients.
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[[Page 35354]]
We are considering four measures that would assess a change in
functional outcomes such as self-care and mobility across a HH episode.
These measures would be standardized to measures finalized in other PAC
quality reporting programs, such as the IRF QRP. We invite feedback on
the importance, relevance, appropriateness, and applicability of these
measure constructs.
Based on input from stakeholders, we have identified additional
concept areas for potential future measure development for the HH QRP.
These include claims-based within stay potentially preventable
hospitalization measures. The potentially preventable within-stay
hospitalization measures would look at the percentage of HH episodes in
which patients were admitted to an acute care hospital or seen in an
emergency department for a potentially preventable condition during an
HH episode. We invite feedback on the importance, relevance,
appropriateness, and applicability of these measure constructs.
In alignment with the requirements of the IMPACT Act to develop
quality measures and standardize data for comparative purposes, we
believe that evaluating outcomes across the post-acute settings using
standardized data is an important priority. Therefore, in addition to
proposing a process-based measure for the domain of ``Functional
status, cognitive function, and changes in function and cognitive
function'', included in this year's proposed rule, we also intend to
develop outcomes-based quality measures, including functional status
and other quality outcome measures to further satisfy this domain.
1. IMPACT Act Implementation Update
As a result of the input and suggestions provided by technical
experts at the TEPs held by our measure developer, and through public
comment, we are engaging in additional development work for two
measures that would satisfy 1899B(c)(1)(E) of the Act, including
performing additional testing. We intend to specify these measures
under section 1899B(c)(1)(E) of the Act no later than January 1, 2019
and we intend to propose to adopt them for the CY 2021 HH QRP, with
data collection beginning on or about January 1, 2020.
H. Proposed Standardized Patient Assessment Data
1. Proposed Standardized Patient Assessment Data Reporting for the CY
2019 HH QRP
Section 1895(b)(3)(B)(v)(IV)(bb) of the Act requires that for
calendar years beginning on or after January 1, 2019, HHAs submit to
the Secretary standardized patient assessment data required under
section 1899B(b)(1) of the Act.
As we describe in more detail above, we are proposing that the
current pressure ulcer measure, Application of Percent of Residents or
Patients with Pressure Ulcers That Are New or Worsened (Short Stay)
(NQF #0678), be replaced with the proposed pressure ulcer measure,
Changes in Skin Integrity Post-Acute Care: Pressure Ulcer/Injury,
beginning with the CY 2020 HH QRP. The current pressure ulcer measure
will remain in the HH QRP until that time. Accordingly, for the
requirement that HHAs report standardized patient assessment data for
the CY 2019 HH QRP, we are proposing that the data elements used to
calculate that measure meet the definition of standardized patient
assessment data for medical conditions and co-morbidities under section
1899B(b)(1)(B)(iv) of the Act, and that the successful reporting of
that data under section 1895(b)(3)(b)(v)(IV)(aa) of the Act for the
beginning of the HH episode (for example, HH start of care/resumption
of care), as well as the end of the HH episode (discharges) occurring
during the first two quarters of CY 2018 would also satisfy the
requirement to report standardized patient assessment data beginning
with the CY 2019 HH QRP.
The collection of assessment data pertaining to skin integrity,
specifically pressure related wounds, is important for multiple
reasons. Clinical decision making, care planning, and quality
improvement all depend on reliable assessment data collection. Pressure
related wounds represent poor outcomes, are a serious medical condition
that can result in death and disability, are debilitating and painful,
and are often avoidable. 177 178 179 180 181 182 Pressure
related wounds are considered healthcare acquired conditions.
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\177\ Casey, G. (2013). ``Pressure ulcers reflect quality of
nursing care.'' Nurs N Z 19(10): 20-24.
\178\ Gorzoni, M.L. and S.L. Pires (2011). ``Deaths in nursing
homes.'' Rev Assoc Med Bras 57(3): 327-331.
\179\ 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.
\180\ White-Chu, E.F., et al. (2011). ``Pressure ulcers in long-
term care.'' Clin Geriatr Med 27(2): 241-258.
\181\ 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.
\182\ Bennet, G, Dealy, C Posnett, J (2004). The cost of
pressure ulcers in the UK, Age and Aging, 33(3):230-235.
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As we note above, the data elements needed to calculate the current
pressure ulcer measure are already included on the OASIS data set and
reported by HHAs, and exhibit validity and reliability for use across
PAC providers. Item reliability for these data elements was also tested
for the nursing home setting during implementation of MDS 3.0. Testing
results are from the RAND Development and Validation of MDS 3.0
project.\183\ The RAND pilot test of the MDS 3.0 data elements showed
good reliability and are applicable to the OASIS because the data
elements tested are the same as those used in the OASIS Data Set.
Across the pressure ulcer data elements, the average gold-standard
nurse to gold-standard nurse kappa statistic was 0.905. The average
gold-standard nurse to facility-nurse kappa statistic was 0.937. Data
elements used to risk adjust this quality measure were also tested
under this same pilot test, and the gold-standard to gold-standard
kappa statistic, or percent agreement (where kappa statistic not
available), ranged from 0.91 to 0.99 for these data elements. These
kappa scores indicate ``almost perfect'' agreement using the Landis and
Koch standard for strength of agreement.\184\
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\183\ Saliba, D., & Buchanan, J. (2008, April). Development and
validation of a revised nursing home assessment tool: MDS 3.0.
Contract No. 500-00-0027/Task Order #2. Santa Monica, CA: Rand
Corporation. Retrieved from https://www.cms.hhs.gov/NursingHomeQualityInits/Downloads/MDS30FinalReport.pdf.
\184\ Landis, R., & Koch, G. (1977, March). The measurement of
observer agreement for categorical data. Biometrics 33(1), 159-174.
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The data elements used to calculate the current pressure ulcer
measure received public comment on several occasions, including when
that measure was proposed in the CY 2016 HH PPS (80 FR 68623). Further,
they were discussed in the past by TEPs held by our measure development
contractor on June 13 and November 15, 2013, and recently by a TEP on
July 18, 2016. TEP members supported the measure and its cross-setting
use in PAC. The report, Technical Expert Panel Summary Report:
Refinement of the Percent of Patients or Residents with Pressure Ulcers
that are New or Worsened (Short-Stay) (NQF #0678) Quality Measure for
Skilled Nursing Facilities (SNFs), Inpatient Rehabilitation Facilities
(HHAs), Long-Term Care Hospitals
[[Page 35355]]
(LTCHs), and Home Health Agencies (HHAs), is available at and https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
We are inviting public comment on this proposal.
2. Proposed Standardized Patient Assessment Data Reporting Beginning
With the CY 2020 HH QRP
We describe below our proposals for the reporting of standardized
patient assessment data by HHAs beginning with the CY 2020 HH QRP.
LTCHs, IRFs, and SNFs are also required to report standardized patient
assessment data through their applicable PAC assessment instruments,
and they do so by responding to identical assessment questions
developed for their respective settings using an identical set of
response options (which incorporate an identical set of definitions and
standards). HHAs would be required to report these data at admission
(SOC/ROC) and discharge beginning on January 1, 2019, with the
exception of three data elements (Brief Interview of Mental Status
(BIMS), Hearing, and Vision) that will be required at SOC/ROC only, as
described below. The BIMS, Hearing and Vision data elements would be
assessed at SOC/ROC only due to the relatively stable nature of the
types of cognitive function, hearing impairment, and vision impairment,
making it unlikely that these assessments would change between the
start and end of the HHA episode of care. Assessment of the BIMS,
Hearing, and Vision data elements at EOC would introduce additional
burden without improving the quality or usefulness of the data, and is
deemed unnecessary. Following the initial reporting year (which would
be based on 6 months of data) for the CY 2020 HH QRP, subsequent years
for the HH QRP would be based on a full calendar year of such data
reporting.
In selecting the data elements described below, we carefully
weighed the balance of burden in assessment-based data collection and
aimed to minimize additional burden through the utilization of existing
data in the assessment instruments. We also note that the patient and
resident assessment instruments are considered part of the medical
record and sought the inclusion of data elements relevant to patient
care.
We also took into consideration the following factors for each data
element: overall clinical relevance; ability to support clinical
decisions, care planning, and interoperable exchange to facilitate care
coordination during transitions in care; and the ability to capture
medical complexity and risk factors that can inform both payment and
quality. In addition, the data elements had to have strong scientific
reliability and validity; be meaningful enough to inform longitudinal
analysis by providers; had to have received general consensus agreement
for its usability; and had to have the ability to collect such data
once but support multiple uses. Further, to inform the final set of
data elements for proposal, we took into account technical and clinical
subject matter expert review, public comment, and consensus input in
which such principles were applied.
3. Proposed Standardized Patient Assessment Data by Category
a. Functional Status Data
We are proposing that the data elements that would be reported by
HHAs to calculate the measure, Application of Percent of Long-Term Care
Hospital Patients with an Admission and Discharge Functional Assessment
and a Care Plan That Addresses Function (NQF #2631), as described in
section V.F.2 would also meet the definition of standardized patient
assessment data for functional status under section 1899B(b)(1)(B)(i)
of the Act, and that the successful reporting of that data under
section 1895(b)(3)(B)(v)(IV)(aa) of the Act would also satisfy the
requirement to report standardized patient assessment data under
section 1895(b)(3)(B)(v)(IV)(bb) of the Act. Details on the data used
to calculate this measure is discussed in section V.F.2.
To further satisfy the requirements under section 1899B(b)(1)(B)(i)
of the Act and specifically our efforts to achieve standardized patient
assessment data pertaining to functional status, such as mobility and
self-care at admission to a PAC provider and before discharge from a
PAC provider, we are also proposing to adopt the functional status data
elements that specifically address mobility and self-care as provided
in the Act. These data elements are also used to calculate the function
outcome measures implemented and/or proposed for implementation in
three other post-acute quality reporting programs to which the IMPACT
Act applies (Application of NQF #2633--Change in Self-Care Score for
Medical Rehabilitation Patients; Application of NQF #2634--Change in
Mobility Score for Medical Rehabilitation Patients; Application of NQF
#2635--Discharge Self-Care Score for Medical Rehabilitation Patients;
and Application of NQF #2636--Discharge Mobility Score for Medical
Rehabilitation Patients). To achieve standardization, we have
implemented such data elements, or sub-sets of the items, into the
other post-acute care patient/resident assessment instruments and we
are proposing that they also meet the definition of standardized
patient assessment data for functional status under section
1899B(b)(1)(B)(i) of the Act, and that the successful reporting of such
data under section 1895(b)(3)(B)(v)(IV)(aa) of the Act would also
satisfy the requirement to report standardized patient assessment data
under section 1895(b)(3)(B)(v)(IV)(bb) of the Act. These data elements
currently are collected in the Section GG: Functional Abilities and
Goals located in current versions of the MDS and the IRF-PAI assessment
instruments.
As previously described, these patient assessment data that assess
for functional status are from the CARE Item Set. They were
specifically developed for cross-setting application and are the result
of consensus building and public input. Further, we received public
comment and input. Their reliability and validity testing were
conducted as part of CMS' Post-Acute Care Payment Reform Demonstration,
and we concluded that the functional status items have acceptable
reliability and validity. We refer the reader to section V.F.2 for a
full description of the CARE Item Set and description of the testing
methodology and results that are available in several reports. For more
information about this quality measure and the data elements used to
calculate it, we refer readers to the FY 2016 IPPS/LTCH PPS final rule
(80 FR 49739 through 49747), the FY 2016 IRF PPS final rule (80 FR
47100 through 47111), and the FY 2016 SNF PPS final rule (80 FR 46444
through 46453).
Therefore, we are proposing to adopt the functional status data
elements that as for the CY 2020 HH QRP, HHAs would be required to
report these data at SOC/ROC or discharge starting on January 1, 2019.
This aligns with the required reporting timeframe for the CY 2020 HH
QRP. Following the initial two quarters of reporting for the CY 2020 HH
QRP, subsequent years for the HH QRP would be based on 12 months of
data reporting beginning with July 1, 2019, through June 30, 2020 for
the CY 2021 HH QRP.
We seek comment on this proposal.
[[Page 35356]]
b. Cognitive Function and Mental Status Data
Cognitive function and mental status in PAC patient and resident
populations can be affected by a number of underlying conditions,
including dementia, stroke, traumatic brain injury, side effects of
medication, metabolic and/or endocrine imbalances, delirium, and
depression.\185\ The assessment of cognitive function and mental status
by PAC providers is important because of the high percentage of
patients and residents with these conditions,\186\ and to improve
quality of care. Symptoms of dementia may improve with pharmacotherapy,
occupational therapy, or physical activity,187 188 189 and
promising treatments for severe traumatic brain injury are currently
being tested.\190\ For older patients and residents diagnosed with
depression, treatment options to reduce symptoms and improve quality of
life include antidepressant medication and
psychotherapy,191 192 193 194 and targeted services, such as
therapeutic recreation, exercise, and restorative nursing, to increase
opportunities for psychosocial interaction.\195\
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\185\ National Institute on Aging. (2014). Assessing Cognitive
Impairment in Older Patients. A Quick Guide for Primary Care
Physicians. Retrieved from https://www.nia.nih.gov/alzheimers/publication/assessing-cognitive-impairment-older-patients.
\186\ Gage B., Morley M., Smith L., et al. (2012). Post-Acute
Care Payment Reform Demonstration (Final report, Volume 4 of 4).
Research Triangle Park, NC: RTI International.
\187\ Casey D.A., Antimisiaris D., O'Brien J. (2010). Drugs for
Alzheimer's Disease: Are They Effective? Pharmacology &
Therapeutics, 35, 208-11.
\188\ Graff M.J., Vernooij-Dassen M.J., Thijssen M., Dekker J.,
Hoefnagels W.H., Rikkert M.G.O. (2006). Community Based Occupational
Therapy for Patients with Dementia and their Care Givers: Randomised
Controlled Trial. BMJ, 333(7580): 1196.
\189\ Bherer L., Erickson K.I., Liu-Ambrose T. (2013). A Review
of the Effects of Physical Activity and Exercise on Cognitive and
Brain Functions in Older Adults. Journal of Aging Research, 657508.
\190\ Giacino J.T., Whyte J., Bagiella E., et al. (2012).
Placebo-controlled trial of amantadine for severe traumatic brain
injury. New England Journal of Medicine, 366(9), 819-826.
\191\ Alexopoulos G.S., Katz I.R., Reynolds C.F. 3rd, Carpenter
D., Docherty J.P., Ross R.W. (2001). Pharmacotherapy of depression
in older patients: a summary of the expert consensus guidelines.
Journal of Psychiatric Practice, 7(6), 361-376.
\192\ Arean P.A., Cook B.L. (2002). Psychotherapy and combined
psychotherapy/pharmacotherapy for late life depression. Biological
Psychiatry, 52(3), 293-303.
\193\ Hollon S.D., Jarrett R.B., Nierenberg A.A., Thase M.E.,
Trivedi M., Rush A.J. (2005). Psychotherapy and medication in the
treatment of adult and geriatric depression: which monotherapy or
combined treatment? Journal of Clinical Psychiatry, 66(4), 455-468.
\194\ Wagenaar D., Colenda C.C., Kreft M., Sawade J., Gardiner
J., Poverejan E. (2003). Treating depression in nursing homes:
practice guidelines in the real world. J Am Osteopath Assoc.
103(10), 465-469.
\195\ Crespy S.D., Van Haitsma K., Kleban M., Hann C.J. Reducing
Depressive Symptoms in Nursing Home Residents: Evaluation of the
Pennsylvania Depression Collaborative Quality Improvement Program. J
Healthc Qual. 2016. Vol. 38, No. 6, pp. e76-e88.
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Accurate assessment of cognitive function and mental status of
patients and residents in PAC would be expected to have a positive
impact on the National Quality Strategy's domains of patient and family
engagement, patient safety, care coordination, clinical process/
effectiveness, and efficient use of health care resources. For example,
standardized assessment of cognitive function and mental status of
patients and residents in PAC will support establishing a baseline for
identifying changes in cognitive function and mental status (for
example, delirium), anticipating the patient or resident's ability to
understand and participate in treatments during a PAC stay, ensuring
patient and resident safety (for example, risk of falls), and
identifying appropriate support needs at the time of discharge or
transfer. Standardized assessment data elements will enable or support
clinical decision-making, early clinical intervention, as well as
person-centered, high quality care through: Facilitating better care
continuity and coordination; better data exchange and interoperability
between settings; and longitudinal outcome analysis. Hence, reliable
data elements assessing cognitive impairment and mental status are
needed to initiate a care plan that can best manage a patient or
resident's prognosis and reduce the possibility of adverse events.
i. Brief Interview for Mental Status (BIMS)
We are proposing that the data elements that comprise the Brief
Interview for Mental Status meet the definition of standardized patient
assessment data for cognitive function and mental status under section
1899B(b)(1)(B)(ii) of the Act. The proposed data elements consist of
seven BIMS questions that result in a cognitive function score. For
more information on the BIMS, we refer readers to the document titled,
Proposed Measure Specifications and Standardized Data Elements for CY
2018 HH QRP Notice of Proposed Rulemaking, available at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HomeHealthQualityInits/HHQIQualityMeasures.html.
The BIMS is a performance-based cognitive assessment that assesses
repetition, recall with and without prompting, and temporal
orientation. It was developed to be a brief screener to assess
cognition, with a focus on learning and memory. Dementia and cognitive
impairment are associated with long-term functional dependence and,
consequently, poor quality of life, increased health care costs, and
mortality.\196\ This makes assessment of mental status and early
detection of cognitive decline or impairment critical in the PAC
setting. The intensity of routine nursing care is higher for patients
and residents with cognitive impairment than for those without, and
dementia is a significant variable in predicting readmission after
discharge to the community from PAC providers.\197\
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\196\ Ag[uuml]ero-Torres, H., Fratiglioni, L., Guo, Z.,
Viitanen, M., von Strauss, E., & Winblad, B. (1998). ``Dementia is
the major cause of functional dependence in the elderly: 3-year
follow-up data from a population-based study.'' Am J of Public
Health 88(10): 1452-1456.
\197\ RTI International. Proposed Measure Specifications for
Measures Proposed in the FY 2017 LTCH QRP NPRM. Research Triangle
Park, NC. 2016.
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The BIMS data elements are currently in use in two of the PAC
assessments: The MDS 3.0 in SNFs and the IRF-PAI in IRFs. The BIMS was
tested in the PAC PRD where it was found to have substantial to almost
perfect agreement for inter-rater reliability (kappa range of 0.71 to
0.91) when tested in all four PAC settings.\198\ Clinical and subject
matter expert advisors working with our data element contractor agreed
that the BIMS is feasible for use by PAC providers. Additionally,
discussions during a TEP convened on April 6 and 7, 2016, demonstrated
support for the BIMS. The Development and Maintenance of Post-Acute
Care Cross-Setting Standardized Patient Assessment Data Technical
Expert Panel Summary Report is available at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
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\198\ Gage B., Morley M., Smith L., et al. (2012). Post-Acute
Care Payment Reform Demonstration (Final report, Volume 2 of 4).
Research Triangle Park, NC: RTI International.
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To solicit additional feedback on the BIMS, we requested public
comment from August 12 to September 12, 2016. Many commenters expressed
support for use of the BIMS, noting that it is reliable, feasible to
use across settings, and will provide useful information about patients
and residents. These comments noted that the data collected through the
BIMS will provide a clearer picture of patient or resident complexity,
help with the care planning
[[Page 35357]]
process, and be useful during care transitions and when coordinating
across providers. A full report of the comments is available at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
Therefore, we are proposing to adopt the BIMS for use in the HH
QRP. We are proposing to add the data elements that comprise the BIMS
to the OASIS, and that HHAs would be required to report these data at
SOC/ROC between January 1, 2019 and June 30, 2019. Following the
initial two quarters of reporting for the CY 2020 HH QRP, subsequent
years for the HH QRP would be based on 12 months of such data reporting
beginning with July 1, 2019 through June 30, 2020 for the CY 2021 HH
QRP. The BIMS data elements would be assessed at SOC/ROC only due to
the relatively stable nature of the types of cognitive function
assessed by the BIMS, making it unlikely that a patient's score on this
assessment would change between the start and end of care. Assessment
at discharge would introduce additional burden without improving the
quality or usefulness of the data, and we believe it is unnecessary.
We are inviting public comment on these proposals.
ii. Confusion Assessment Method (CAM)
We are proposing that the data elements that comprise the Confusion
Assessment Method (CAM) meet the definition of standardized patient
assessment data for cognitive function and mental status under section
1899B(b)(1)(B)(ii) of the Act. The CAM is a six-question instrument
that screens for overall cognitive impairment, as well as distinguishes
delirium or reversible confusion from other types of cognitive
impairment. For more information on the CAM, we refer readers to the
document titled, Proposed Measure Specifications and Standardized Data
Elements for CY 2018 HH QRP Notice of Proposed Rulemakings, available
at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HomeHealthQualityInits/HHQIQualityMeasures.html.
The CAM was developed to identify the signs and symptoms of
delirium. It results in a score that suggests whether the patient or
resident should be assigned a diagnosis of delirium. Because patients
and residents with multiple comorbidities receive services from PAC
providers, it is important to assess delirium, as it is associated with
a high mortality rate and prolonged duration of stay in hospitalized
older adults with dementia.\199\ Assessing for signs and symptoms of
delirium is clinically relevant for care planning by PAC providers.
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\199\ Fick, D.M., Steis, M.R., Waller, J.L., & Inouye, S.K.
(2013). ``Delirium superimposed on dementia is associated with
prolonged length of stay and poor outcomes in hospitalized older
adults.'' J of Hospital Med 8(9): 500-505.
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The CAM is currently in use in two of the PAC assessments: The MDS
3.0 in SNFs and the LCDS in LTCHs. The CAM was tested in the PAC PRD
where it was found to have substantial agreement for inter-rater
reliability for the ``Inattention and Disorganized Thinking'' questions
(kappa range of 0.70 to 0.73); and moderate agreement for the ``Altered
Level of Consciousness'' question (kappa of 0.58).\200\
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\200\ Gage B., Morley M., Smith L., et al. (2012). Post-Acute
Care Payment Reform Demonstration (Final report, Volume 2 of 4).
Research Triangle Park, NC: RTI International.
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Clinical and subject matter expert advisors working with our data
element contractor agreed that the CAM is feasible for use by PAC
providers, that it assesses key aspects of cognition, and that this
information about patient or resident cognition would be clinically
useful both within and across PAC provider types. The CAM was also
supported by a TEP that discussed and rated candidate data elements
during a meeting on April 6 and 7, 2016. The Development and
Maintenance of Post-Acute Care Cross-Setting Standardized Patient
Assessment Data Technical Expert Panel Summary Report is available at
https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html. We requested public comment on
the CAM from August 12 to September 12, 2016. Many commenters expressed
support for use of the CAM, noting that it would provide important
information for care planning and care coordination, and therefore,
contribute to quality improvement. The commenters noted it is
particularly helpful in distinguishing delirium and reversible
confusion from other types of cognitive impairment. A full report of
the comments is available at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
Therefore, we are proposing to add the CAM data elements to the
OASIS, and that HHAs would be required to report these data for the CY
2020 HH QRP at SOC/ROC and discharge between January 1, 2019 and June
30, 2019. Following the initial two quarters of reporting for the CY
2020 HH QRP, subsequent years for the HH QRP would be based on 12
months of such data reporting beginning with July 1, 2019 through June
30, 2020 for the CY 2021 HH QRP.
We are inviting public comment on these proposals.
iii. Behavioral Signs and Symptoms
We are proposing that the Behavioral Signs and Symptoms data
elements meet the definition of standardized patient assessment data
for cognitive function and mental status under section
1899B(b)(1)(B)(ii) of the Act. The proposed data elements consist of
three Behavioral Signs and Symptoms questions and result in three
scores that categorize patients as having or not having certain types
of behavioral signs and symptoms. For more information on the
Behavioral Signs and Symptoms data elements, we refer readers to the
document titled, Proposed Measure Specifications and Standardized Data
Elements for CY 2018 HH QRP Notice of Proposed Rulemaking, available at
https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HomeHealthQualityInits/HHQIQualityMeasures.html.
The questions included in the Behavioral Signs and Symptoms group
assess whether the patient or resident has exhibited any behavioral
symptoms that may indicate cognitive impairment or other mental health
issues during the assessment period, including physical, verbal, and
other disruptive or dangerous behavioral symptoms, but excluding
patient wandering. Such behaviors can indicate unrecognized needs and
care preferences and are associated most commonly with dementia and
other cognitive impairment, and less commonly with adverse drug events,
mood disorders, and other conditions.\201\ Assessing behavioral
disturbances can lead to early intervention, patient- and resident-
centered care planning, clinical decision support, and improved staff
and patient or resident safety. Assessment and documentation of these
behaviors can help inform care planning and patient transitions, and
provide important information about resource use.
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\201\ Desai A, Grossbert G. Recognition and management of
behavioral disturbances in dementia. The Primary Care Companion to
the Journal of Clinical Psychiatry. 2001; 3(3):93-109.
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Data elements that capture behavioral symptoms are currently
included in two
[[Page 35358]]
of the PAC assessments: The MDS 3.0 in SNFs and the OASIS-C2 in HHAs.
In the MDS, each question includes four response options ranging from
``behavior not exhibited'' (0) to behavior ``occurred daily'' (3). The
OASIS-C2 includes some similar data elements which record the frequency
of disruptive behaviors on a 6-point scale ranging from ``never'' (0)
to ``at least daily'' (5). Data elements that mirror those used in the
MDS and serve the same assessment purpose were tested in post-acute
providers in the PAC PRD and found to be clinically relevant,
meaningful for care planning, and feasible for use in each of the four
PAC settings.\202\
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\202\ Gage B., Morley M., Smith L., et al. (2012). Post-Acute
Care Payment Reform Demonstration (Final report, Volume 2 of 4).
Research Triangle Park, NC: RTI International.
---------------------------------------------------------------------------
The proposed data elements were supported by comments from the
Standardized Patient Assessment Data TEP held by our data element
contractor. The TEP identified patient and resident behaviors as an
important consideration for resource intensity and care planning, and
affirmed the importance of the standardized assessment of patient
behaviors through data elements such as those in use in the MDS. The
Development and Maintenance of Post-Acute Care Cross-Setting
Standardized Patient Assessment Data Technical Expert Panel Summary
Report is available at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
Because the PAC PRD version of the Behavioral Signs and Symptoms
data elements were previously tested across PAC providers, we solicited
additional feedback on this version of the data elements by including
these data elements in a call for public comment that was open from
August 12 to September 12, 2016. Consistent with the TEP discussion on
the importance of patient and resident behaviors, many commenters
expressed support for use of the Behavioral Signs and Symptoms data
elements, noting that they would provide useful information about
patient and resident behavior at both admission and discharge, and
contribute to care planning regarding the most appropriate treatment
and resource use for the patient or resident. Public comment also
supported the use of a highly similar MDS version of the data elements
to provide continuity with existing assessment processes in SNFs. A
full report of the comments is available at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
Therefore, we are proposing the MDS version of the Behavioral Signs
and Symptoms data elements because they focus more closely on
behavioral symptoms than the OASIS data elements, and include more
detailed response categories than those used in the PAC PRD version,
capturing more information about the frequency of behaviors. We are
proposing that HHAs would be required to report these data for the CY
2020 HH QRP at SOC/ROC and discharge between January 1, 2019 and June
30, 2019. Following the initial two quarters of reporting for the CY
2020 HH QRP, subsequent years for the HH QRP would be based on 12
months of such data reporting beginning with July 1, 2019 through June
30, 2020 for the CY 2021 HH QRP.
We are inviting public comment on these proposals.
iv. Patient Health Questionnaire-2 (PHQ-2)
We are proposing that the PHQ-2 data elements meet the definition
of standardized patient assessment data for cognitive function and
mental status under section 1899B(b)(1)(B)(ii) of the Act. The proposed
data elements consist of the PHQ-2 two-item questionnaire that assesses
the cardinal criteria for depression: depressed mood and anhedonia
(inability to feel pleasure). For more information on the PHQ-2, we
refer readers to the document titled, Proposed Measure Specifications
and Standardized Data Elements for CY 2018 HH QRP Notice of Proposed
Rulemaking, available at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HomeHealthQualityInits/HHQIQualityMeasures.html.
Depression is a common mental health condition that is often missed
and under-recognized. Assessing depression helps PAC providers better
understand the needs of their patients and residents by: Prompting
further evaluation (that is, to establish a diagnosis of depression);
elucidating the patient's or resident's ability to participate in
therapies for conditions other than depression during their stay; and
identifying appropriate ongoing treatment and support needs at the time
of discharge. A PHQ-2 score beyond a predetermined threshold signals
the need for additional clinical assessment to determine a depression
diagnosis.
The proposed data elements that comprise the PHQ-2 are currently
used in the OASIS-C2 for HHAs and the MDS 3.0 for SNFs (as part of the
PHQ-9). The PHQ-2 data elements were tested in the PAC PRD, where they
were found to have almost perfect agreement for inter-rater reliability
(kappa range of 0.84 to 0.91) when tested by all four PAC
providers.\203\
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\203\ Gage B., Smith L., Ross J. et al. (2012). The Development
and Testing of the Continuity Assessment Record and Evaluation
(CARE) Item Set (Final Report on Reliability Testing, Volume 2 of
3). Research Triangle Park, NC: RTI International.
---------------------------------------------------------------------------
Clinical and subject matter expert advisors working with our data
element contractor agreed that the PHQ-2 is feasible for use in PAC,
that it assesses key aspects of mental status, and that this
information about patient or resident mood would be clinically useful
both within and across PAC settings. We note that both the PHQ-9 and
the PHQ-2 were supported by TEP members who discussed and rated
candidate data elements during a meeting on April 6 and 7, 2016. They
particularly noted that the brevity of the PHQ-2 made it feasible with
low burden for both assessors and PAC patients or residents. The
Development and Maintenance of Post-Acute Care Cross-Setting
Standardized Patient Assessment Data Technical Expert Panel Summary
Report is available at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
To solicit additional feedback on the PHQ-2, we requested public
comment from August 12 to September 12, 2016. Many commenters provided
feedback on using the PHQ-2 for the assessment of mood. Overall,
commenters believed that collecting these data elements across PAC
settings was appropriate, given the role that depression plays in well-
being. Several commenters expressed support for an approach that would
use PHQ-2 as a gateway to the longer PHQ-9 and would maintain the
reduced burden on most patients and residents, as well as test
administrators, which is a benefit of the PHQ-2, while ensuring that
the PHQ-9, which exhibits higher specificity,\204\ would be
administered for patients and residents who showed signs and symptoms
of depression on the PHQ-2. Specific
[[Page 35359]]
comments are described in a full report available at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
---------------------------------------------------------------------------
\204\ Arroll B, Goodyear-Smith F, Crengle S, Gunn J, Kerse N,
Fishman T, et al. Validation of PHQ-2 and PHQ-9 to screen for major
depression in the primary care population. Annals of family
medicine. 2010;8(4):348-53. doi: 10.1370/afm.1139 pmid:20644190;
PubMed Central PMCID: PMC2906530.
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Therefore, we are proposing to adopt the PHQ-2 data elements for
use in the HH QRP as standardized patient assessment data. As noted
above in this section, the PHQ-2 is already included on the OASIS. HHAs
would be required to report these data for the CY 2020 HH QRP at SOC/
ROC and discharge between January 1, 2019 and June 30, 2019. Following
the initial two quarters of reporting for the CY 2020 HH QRP,
subsequent years for the HH QRP would be based on 12 months of such
data reporting beginning with July 1, 2019 through June 30, 2020 for
the CY 2021 HH QRP.
We are inviting public comment on these proposals.
c. Special Services, Treatments, and Interventions Data
Special services, treatments, and interventions performed in PAC
can have a major effect on an individual's health status, self-image,
and quality of life. The assessment of these special services,
treatments, and interventions in PAC is important to ensure the
continuing appropriateness of care for the patients and residents
receiving them, and to support care transitions from one PAC setting to
another, an acute care hospital, or discharge. Accurate assessment of
special services, treatments, and interventions of patients and
residents served by PAC providers are expected to have a positive
impact on the National Quality Strategy's domains of patient and family
engagement, patient safety, care coordination, clinical process/
effectiveness, and efficient use of healthcare resources.
For example, standardized assessment of special services,
treatments, and interventions used in PAC can promote patient and
resident safety through appropriate care planning (for example,
mitigating risks such as infection or pulmonary embolism associated
with central intravenous access), and identifying life-sustaining
treatments that must be continued, such as mechanical ventilation,
dialysis, suctioning, and chemotherapy, at the time of discharge or
transfer. Standardized assessment of these data elements will enable or
support: Clinical decision-making and early clinical intervention;
person-centered, high quality care through, for example, facilitating
better care continuity and coordination; better data exchange and
interoperability between settings; and longitudinal outcome analysis.
Hence, reliable data elements assessing special services, treatments,
and interventions are needed to initiate a care plan that can improve,
maintain, or best manage a patient or resident's condition and reduce
the possibility of adverse events.
We are proposing 15 special services, treatments, and interventions
as presented below in this section grouped by cancer treatments,
respiratory treatments, other treatments, and nutritional approaches. A
TEP convened by our data element contractor provided input on the 15
data elements for Special Services, Treatments, and Interventions. This
TEP, held on January 5 and 6, 2017, opined that these data elements are
appropriate for standardization because they would provide useful
clinical information to inform care planning and care coordination. The
TEP affirmed that assessment of these services and interventions is
standard clinical practice, and that the collection of these data by
means of a list and checkbox format would conform with common workflow
for PAC providers. A full report of the TEP discussion is available at
https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
i. Cancer Treatment: Chemotherapy (IV, Oral, Other)
We are proposing that the Chemotherapy (IV, Oral, Other) data
elements meet the definition of standardized patient assessment data
for special services, treatments, and interventions under section
1899B(b)(1)(B)(iii) of the Act. The proposed data elements consist of
the principal Chemotherapy data element and three sub-elements: IV
Chemotherapy, Oral Chemotherapy, and Other. For more information on the
Chemotherapy (IV, Oral, Other) data elements, we refer readers to the
document titled, https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HomeHealthQualityInits/HHQIQualityMeasures.html.
Chemotherapy is a type of cancer treatment that uses drugs to
destroy cancer cells. It is typically used when a patient has a
malignancy (cancer), which is a serious, often life-threatening or
life-limiting condition. Both intravenous (IV) and oral chemotherapy
can have serious side effects, including nausea/vomiting, extreme
fatigue, risk of infection due to a suppressed immune system, anemia,
and an increased risk of bleeding due to low platelet counts. Oral
chemotherapy can have as many side effects as IV chemotherapy, but can
also be significantly more convenient and less resource-intensive to
administer. Because of the toxicity of these agents, special care must
be exercised in handling and transporting chemotherapy drugs. IV
chemotherapy may be given by peripheral IV, but is more commonly given
via an indwelling central line, which raises the risk of bloodstream
infections. Given the significant burden of malignancy, the resource
intensity of administering chemotherapy, and the side effects and
potential complications of these highly-toxic medications, assessing
the receipt of chemotherapy is important in the PAC setting for care
planning and determining resource use.
The need for chemotherapy predicts resource intensity, both because
of the complexity of administering these potent, toxic drug
combinations under specific protocols, and because of what the need for
chemotherapy signals about the patient's underlying medical condition.
Furthermore, the resource intensity of IV chemotherapy is higher than
for oral chemotherapy, as the protocols for administration and the care
of the central line (if present) require significant resources.
The Chemotherapy (IV, Oral, Other) data elements consist of a
principal data element and three sub-elements: IV chemotherapy, which
is generally resource-intensive; oral chemotherapy, which is less
invasive and generally less intensive with regard to administration
protocols; and a third category provided to enable the capture of other
less common chemotherapeutic approaches. This third category is
potentially associated with higher risks and is more resource intensive
due to delivery by other routes (for example, intraventricular or
intrathecal).
The principal Chemotherapy data element is currently in use in the
MDS 3.0. One proposed sub-element, IV Chemotherapy, was tested in the
PAC PRD and found feasible for use in each of the four PAC settings. We
solicited public comment on IV Chemotherapy from August 12 to September
12, 2016. Several commenters provided support for the data element and
suggested it be included as standardized patient assessment data.
Commenters stated that assessing the use of chemotherapy services is
relevant to share across the care continuum to facilitate care
coordination and care transitions and noted the validity of the data
element.
[[Page 35360]]
Commenters also noted the importance of capturing all types of
chemotherapy, regardless of route, and stated that collecting data only
on patients and residents who received chemotherapy by IV would limit
the usefulness of this standardized data element. A full report of the
comments is available at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
Therefore, we are proposing that the Chemotherapy (IV, Oral, Other)
data elements with a principal data element and three sub-elements meet
the definition of standardized patient assessment data for special
services, treatments, and interventions under section
1899B(b)(1)(B)(iii) of the Act. We are proposing to add the
Chemotherapy (IV, Oral, Other) data elements to the OASIS, and that
HHAs would be required to report these data for the CY 2020 HH QRP at
SOC/ROC and discharge between January 1, 2019 and June 30, 2019.
Following the initial two quarters of reporting for the CY 2020 HH QRP,
subsequent years for the HH QRP would be based on 12 months of such
data reporting beginning with July 1, 2019, through June 30, 2020 for
the CY 2021 HH QRP.
We are inviting public comment on these proposals.
ii. Cancer Treatment: Radiation
We are proposing that the Radiation data element meets the
definition of standardized patient assessment data for special
services, treatments, and interventions under section
1899B(b)(1)(B)(iii) of the Act. The proposed data element consists of
the single Radiation data element. For more information on the
Radiation data element, we refer readers to the document titled,
Proposed Measure Specifications and Standardized Data Elements for CY
2018 HH QRP Notice of Proposed Rulemaking, available at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HomeHealthQualityInits/HHQIQualityMeasures.html.
Radiation is a type of cancer treatment that uses high-energy
radioactivity to stop cancer by damaging cancer cell DNA, but it can
also damage normal cells. Radiation is an important therapy for
particular types of cancer, and the resource utilization is high, with
frequent radiation sessions required, often daily for a period of
several weeks. Assessing whether a patient or resident is receiving
radiation therapy is important to determine resource utilization, as
PAC patients and residents will need to be transported to and from
radiation treatments, and monitored and treated for side effects after
receiving this intervention. Therefore, assessing the receipt of
radiation therapy, which would compete with other care processes given
the time burden, would be important for care planning and care
coordination by PAC providers.
The Radiation data element is currently in use in the MDS 3.0. This
data element was not tested in the PAC PRD. However, public comment and
other expert input on the Radiation data element supported its
importance and clinical usefulness for patients in PAC settings, due to
the side effects and consequences of radiation treatment on patients
that need to be considered in care planning and care transitions. To
solicit additional feedback on the Radiation data element we are
proposing, we requested public comment from August 12 to September 12,
2016. Several commenters provided support for the data element, noting
the relevance of this data element in facilitating care coordination
and supporting care transitions, the feasibility of the item, and the
potential for quality improvement. A full report of the comments is
available at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
The proposed data element was presented to and supported by the TEP
held by our data element contractor on January 5 and 6, 2017, which
opined that Radiation provided important corollary information about
cancer treatment in addition to Chemotherapy (IV, Oral, Other), and
that, because capturing this information is a customary part of
clinical practice, the proposed data element would be feasible,
reliable, and easily incorporated into existing workflow.
Therefore, we are proposing that the Radiation data element meets
the definition of standardized patient assessment data for special
services, treatments, and interventions under section
1899B(b)(1)(B)(iii) of the Act. We are proposing to add the Radiation
data element to the OASIS, and that HHAs would be required to report
these data for the CY 2020 HH QRP at SOC/ROC and discharge between
January 1, 2019 and June 30, 2019. Following the initial two quarters
of reporting for the CY 2020 HH QRP, subsequent years for the HH QRP
would be based on 12 months of such data reporting beginning with July
1, 2019 through June 30, 2020 for the CY 2021 HH QRP.
We are inviting public comment on these proposals.
iii. Respiratory Treatment: Oxygen Therapy (Continuous, Intermittent)
We are proposing that the Oxygen Therapy (Continuous, Intermittent)
data elements meet the definition of standardized patient assessment
data for special services, treatments, and interventions under section
1899B(b)(1)(B)(iii) of the Act. The proposed data elements consist of
the principal Oxygen data element and two sub-elements, ``Continuous''
(whether the oxygen was delivered continuously, typically defined as
>=14 hours per day), or ``Intermittent.'' For more information on the
Oxygen Therapy (Continuous, Intermittent) data elements, we refer
readers to the document titled, Proposed Measure Specifications and
Standardized Data Elements for CY 2018 HH QRP Notice of Proposed
Rulemaking, available at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HomeHealthQualityInits/HHQIQualityMeasures.html.
Oxygen therapy provides a patient or resident with extra oxygen
when medical conditions such as chronic obstructive pulmonary disease,
pneumonia, or severe asthma prevent the patient or resident from
getting enough oxygen from room air. Oxygen administration is a
resource-intensive intervention, as it requires specialized equipment
such as the source of oxygen, delivery systems (for example, oxygen
concentrator, liquid oxygen containers, and high-pressure systems), the
patient interface (for example, nasal cannula or mask), and other
accessories (for example, regulators, filters, tubing). These data
elements capture patient or resident use of two types of oxygen therapy
(continuous and intermittent) which are reflective of intensity of care
needs, including the level of monitoring and direct patient care
required. Assessing the receipt of this service is important for care
planning and resource use for PAC providers.
The proposed data elements were developed based on similar data
elements that assess oxygen therapy, currently in use in the MDS 3.0
(``Oxygen Therapy'') and OASIS-C2 (``Oxygen (intermittent or
continuous)''), and a data element tested in the PAC PRD that focused
on intensive oxygen therapy (``High O2 Concentration Delivery System
with FiO2 > 40%'').
As a result of input from expert advisors, we solicited public
comment on the single data element, Oxygen
[[Page 35361]]
(inclusive of intermittent and continuous oxygen use), from August 12
to September 12, 2016. Several commenters supported the importance of
the Oxygen data element, noting feasibility of this item in PAC, and
the relevance in facilitating care coordination and supporting care
transitions, but suggesting that the extent of oxygen use be
documented. A full report of the comments is available at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
As a result of public comment and input from expert advisors about
the importance and clinical usefulness of documenting the extent of
oxygen use, we expanded the single data element to include two sub-
elements, intermittent and continuous.
Therefore, we are proposing that the Oxygen Therapy (Continuous,
Intermittent) data elements with a principal data element and two sub-
elements meet the definition of standardized patient assessment data
for special services, treatments, and interventions under section
1899B(b)(1)(B)(iii) of the Act. We are proposing to expand the existing
Oxygen (intermittent or continuous)- data element in the OASIS to
include sub-elements for Continuous and Intermittent, and that HHAs
would be required to report these data for the CY 2020 HH QRP at SOC/
ROC and discharge between January 1, 2019 and June 30, 2019. Following
the initial two quarters of reporting for the CY 2020 HH QRP,
subsequent years for the HH QRP would be based on 12 months of such
data reporting beginning with July 1, 2019 through June 30, 2020 for
the CY 2021 HH QRP.
We are inviting public comment on these proposals.
iv. Respiratory Treatment: Suctioning (Scheduled, As needed)
We are proposing that the Suctioning (Scheduled, As needed) data
elements meet the definition of standardized patient assessment data
for special services, treatments, and interventions under section
1899B(b)(1)(B)(iii) of the Act. The proposed data elements consist of
the principal Suctioning data element, and two sub-elements,
``Scheduled'' and ``As needed.'' These sub-elements capture two types
of suctioning. ``Scheduled'' indicates suctioning based on a specific
frequency, such as every hour. ``As needed'' means suctioning only when
indicated. For more information on the Suctioning (Scheduled, As
needed) data elements, we refer readers to the document titled,
Proposed Measure Specifications and Standardized Data Elements for CY
2018 HH QRP Notice of Proposed Rulemaking, available at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HomeHealthQualityInits/HHQIQualityMeasures.html.
Suctioning is an intervention used to clear secretions from the
airway when a person cannot clear those secretions on his or her own.
It is done by aspirating secretions through a catheter connected to a
suction source. Types of suctioning include oropharyngeal and
nasopharyngeal suctioning, nasotracheal suctioning, and suctioning
through an artificial airway such as a tracheostomy tube. Oropharyngeal
and nasopharyngeal suctioning are a key part of many patients' care
plans, both to prevent the accumulation of secretions that can lead to
aspiration pneumonia (a common condition in patients with inadequate
gag reflexes), and to relieve obstructions from mucus plugging during
an acute or chronic respiratory infection, which can often lead to
desaturation and increased respiratory effort. Suctioning can be done
on a scheduled basis if the patient is judged to clinically benefit
from regular interventions; or can be done as needed, such as when
secretions become so copious that gurgling or choking is noted, or a
sudden desaturation occurs from a mucus plug. As suctioning is
generally performed by a care provider rather than independently, this
intervention can be quite resource-intensive if it occurs every hour,
for example, rather than once a shift. It also signifies an underlying
medical condition that prevents the patient from clearing his/her
secretions effectively (such as after a stroke, or during an acute
respiratory infection). Generally, suctioning is necessary to ensure
that the airway is clear of secretions which, if left, can inhibit
successful oxygenation of the individual and/or lead to infection. The
intent of suctioning is to maintain a patent airway, the loss of which
can lead to death, or complications associated with hypoxia.
The proposed data elements are based on an item currently in use in
the MDS 3.0 (``Suctioning'' without the two sub-elements), and data
elements tested in the PAC PRD that focused on the frequency of
suctioning required for patients with tracheostomies (``Trach Tube with
Suctioning: Specify most intensive frequency of suctioning during stay
[Every __ hours]'').
Clinical and subject matter expert advisors working with our data
element contractor agreed that the proposed Suctioning (Scheduled, As
needed) data elements are feasible for use in PAC, and that they
indicate important treatment that would be clinically useful to capture
both within and across PAC providers. We solicited public comment on
the suctioning data element currently included in the MDS 3.0 from
August 12 to September 12, 2016. Several commenters wrote in support of
this data element, noting feasibility of this item in PAC, and the
relevance of this data element to facilitating care coordination and
supporting care transitions. We also received comments suggesting that
we examine the frequency of suctioning to better understand the use of
staff time, the impact on a patient or resident's capacity to speak and
swallow, and intensity of care required. Based on these comments, we
decided to add two sub-elements (scheduled and as needed) to the
suctioning element. The proposed data elements, Suctioning (Scheduled,
As needed) includes both the principal suctioning data element that is
included on the MDS 3.0 and two sub-elements, ``scheduled'' and ``as
needed.'' A full report of the comments is available at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
A TEP convened by the data element contractor provided input on the
proposed data elements. This TEP, held on January 5 and 6, 2017, opined
that these data elements are appropriate for standardization because
they would provide useful clinical information to inform care planning
and care coordination. The TEP affirmed that assessment of these
services and interventions is standard clinical practice. A full report
of the TEP discussion is available at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
Therefore, we are proposing that the Suctioning (Scheduled, As
needed) data elements with a principal data element and two sub-
elements meet the definition of standardized patient assessment data
for special services, treatments, and interventions under section
1899B(b)(1)(B)(iii) of the Act. We are proposing to add the Suctioning
(Scheduled, As needed) data elements to the OASIS, and that HHAs would
be
[[Page 35362]]
required to report these data for the CY 2020 HH QRP at SOC/ROC and
discharge between January 1, 2019, and June 30, 2019. Following the
initial two quarters of reporting for the CY 2020 HH QRP, subsequent
years for the HH QRP would be based on 12 months of such data reporting
beginning with July 1, 2019, through June 30, 2020 for the CY 2021 HH
QRP.
We are inviting public comment on these proposals.
v. Respiratory Treatment: Tracheostomy Care
We are proposing that the Tracheostomy Care data element meets the
definition of standardized patient assessment data for special
services, treatments, and interventions under section
1899B(b)(1)(B)(iii) of the Act. The proposed data element consists of
the single Tracheostomy Care data element. For more information on the
Tracheostomy Care data element, we refer readers to the document
titled, Proposed Measure Specifications and Standardized Data Elements
for CY 2018 HH QRP Notice of Proposed Rulemaking, available at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HomeHealthQualityInits/HHQIQualityMeasures.html.
A tracheostomy provides an airway to help a patient or resident
breathe when the usual route for breathing is obstructed or impaired.
Generally, in all of these cases, suctioning is necessary to ensure
that the tracheostomy tube is clear of secretions which can inhibit
successful oxygenation of the individual, or accumulate and cause
infection. Often, individuals with tracheostomies are also receiving
supplemental oxygenation. The presence of a tracheostomy, whether
permanent or temporary, warrants careful monitoring and immediate
intervention if the tracheostomy tube becomes occluded or dislodged.
While in rare cases the presence of a tracheostomy is not associated
with increased care demands (and in some of those instances, the care
of the ostomy is performed by the patient), in general the presence of
such a device is associated with increased patient risk and resource
use. Tracheostomy care should include close monitoring to prevent
occlusion or decannulation, skin infection or necrosis, and other
complications to ensure adequate air flow and oxygenation. In addition
to suctioning, skin care, dressing changes, and replacement or cleaning
of the tracheostomy cannula (tube), is also a critical part of the
tracheostomy care plan. Regular cleaning and suctioning is important in
preventing infections such as pneumonia, preventing skin breakdown, and
preventing any occlusions leading to inadequate oxygenation.
The proposed data element is currently in use in the MDS 3.0
(``Tracheostomy care''). Data elements (``Trach Tube with Suctioning'')
that were tested in the PAC PRD included an equivalent principal data
element on the presence of a tracheostomy. This data element was found
feasible for use in each of the four PAC settings as the data
collection aligned with usual work flow.
Clinical and subject matter expert advisors working with our data
element contractor agreed that the Tracheostomy Care data element is
feasible for use in PAC and that it assesses an important treatment
that would be clinically useful both within and across PAC provider
types.
We solicited public comment on this data element from August 12 to
September 12, 2016. Several commenters wrote in support of this data
element, noting the feasibility of this item in PAC, and the relevance
of this data element to facilitating care coordination and supporting
care transitions. A full report of the comments is available at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
A TEP convened by the data element contractor provided input on the
proposed data elements. This TEP, held on January 5 and 6, 2017, opined
that these data elements are appropriate for standardization because
they would provide useful clinical information to inform care planning
and care coordination. The TEP affirmed that assessment of these
services and interventions is standard clinical practice. A full report
of the TEP discussion is available at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
Therefore, we are proposing that the Tracheostomy Care data element
meets the definition of standardized patient assessment data for
special services, treatments, and interventions under section
1899B(b)(1)(B)(iii) of the Act. We are proposing to add the
Tracheostomy Care data element to the OASIS, and that HHAs would be
required to report these data for the CY 2020 HH QRP at SOC/ROC and
discharge between January 1, 2019 and June 30, 2019. Following the
initial two quarters of reporting for the CY 2020 HH QRP, subsequent
years for the HH QRP would be based on 12 months of such data reporting
beginning with July 1, 2019, through June 30, 2020 for the CY 2021 HH
QRP.
We are inviting public comment on these proposals.
vi. Respiratory Treatment: Non-Invasive Mechanical Ventilator (BiPAP,
CPAP)
We are proposing that the Non-invasive Mechanical Ventilator
(Bilevel Positive Airway Pressure [BiPAP], Continuous Positive Airway
Pressure [CPAP]) data elements meet the definition of standardized
patient assessment data for special services, treatments, and
interventions under section 1899B(b)(1)(B)(iii) of the Act. The
proposed data elements consist of the principal Non-invasive Mechanical
Ventilator data element and two sub-elements, BiPAP and CPAP. For more
information on the Non-invasive Mechanical Ventilator (BiPAP, CPAP)
data elements, we refer readers to the document titled, Proposed
Measure Specifications and Standardized Data Elements for CY 2018 HH
QRP Notice of Proposed Rulemaking, available at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HomeHealthQualityInits/HHQIQualityMeasures.html.
BiPAP and CPAP are respiratory support devices that prevent the
airways from closing by delivering slightly pressurized air via
electronic cycling throughout the breathing cycle (Bilevel Positive
Airway Pressure, referred to as BiPAP) or through a mask continuously
(Continuous PAP, referred to as CPAP). Assessment of non-invasive
mechanical ventilation is important in care planning, as both CPAP and
BiPAP are resource-intensive (although less so than invasive mechanical
ventilation) and signify a more complex or underlying medical
condition. Particularly when used in the context of acute illness or
progressive respiratory decline, additional staff (for example,
respiratory therapists) are required to monitor and adjust the CPAP and
BiPAP settings. Additionally the patient or resident may require more
nursing assessment, education, and interventions, such as pulse
oximetry or venipuncture for blood gas evaluation.
Data elements that assess BiPAP and CPAP are currently included on
the OASIS-C2 for HHAs (``Continuous/Bi-level positive airway
pressure''), LCDS for the LTCH setting (``Non-invasive Ventilator
(BIPAP, CPAP)''), and the MDS 3.0 for the SNF setting (``BiPAP/
[[Page 35363]]
CPAP''). A data element that focused on CPAP was tested across the four
PAC providers in the PAC PRD study and found to be feasible for
standardization. All of these data elements assess BiPAP or CPAP with a
single check box, not separately.
Clinical and subject matter expert advisors working with our data
element contractor agreed that the standardized assessment of Non-
invasive Mechanical Ventilator (BiPAP, CPAP) data elements would be
feasible for use in PAC, and assess an important treatment that would
be clinically useful both within and across PAC provider types.
To solicit additional feedback on the form of the Non-invasive
Mechanical Ventilator (BiPAP, CPAP) data elements best suited for
standardization, we requested public comment on a single data element,
BiPAP/CPAP, equivalent (but for labeling) to what is currently in use
on the MDS, OASIS, and LCDS, from August 12 to September 12, 2016.
Several commenters wrote in support of this data element, noting the
feasibility of these items in PAC, and the relevance of these data
elements for facilitating care coordination and supporting care
transitions. In addition, there was support in the public comment
responses for separating out BiPAP and CPAP as distinct sub-elements,
as they are therapies used for different types of patients and
residents. A full report of the comments is available at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
A TEP convened by the data element contractor provided input on the
proposed data elements. This TEP, held on January 5 and 6, 2017, opined
that these data elements are appropriate for standardization because
they would provide useful clinical information to inform care planning
and care coordination. The TEP affirmed that assessment of these
services and interventions is standard clinical practice. A full report
of the TEP discussion is available at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
Therefore, we are proposing that the Non-invasive Mechanical
Ventilator (BiPAP, CPAP) data elements with a principal data element
and two sub-elements meet the definition of standardized patient
assessment data for special services, treatments, and interventions
under section 1899B(b)(1)(B)(iii) of the Act. We are proposing that the
existing ``Continuous/Bi-level positive airway pressure'' data element
in the OASIS be expanded and relabeled as the Non-invasive Mechanical
Ventilator (BiPAP, CPAP) data elements, and that HHAs would be required
to report these data for the CY 2020 HH QRP at SOC/ROC and discharge
between January 1, 2019 and June 30, 2019. Following the initial two
quarters of reporting for the CY 2020 HH QRP, subsequent years for the
HH QRP would be based on 12 months of such data reporting beginning
with July 1, 2019, through June 30, 2020 for the CY 2021 HH QRP.
We are inviting public comment on these proposals.
vii. Respiratory Treatment: Invasive Mechanical Ventilator
We are proposing that the Invasive Mechanical Ventilator data
element meets the definition of standardized patient assessment data
for special services, treatments, and interventions under section
1899B(b)(1)(B)(iii) of the Act. The proposed data element consists of a
single Invasive Mechanical Ventilator data element. For more
information on the Invasive Mechanical Ventilator data element, we
refer readers to the document titled, Proposed Measure Specifications
and Standardized Data Elements for CY 2018 HH QRP Notice of Proposed
Rulemaking, available at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HomeHealthQualityInits/HHQIQualityMeasures.html.
Invasive mechanical ventilation includes ventilators and
respirators that ventilate the patient through a tube that extends via
the oral airway into the pulmonary region (intubation), or through a
surgical opening directly into the trachea (tracheostomy). Thus,
assessment of invasive mechanical ventilation is important in care
planning and risk mitigation. Ventilation in this manner is a resource-
intensive therapy associated with life-threatening conditions without
which the patient or resident would not survive. However, ventilator
use has inherent risks requiring close monitoring. Failure to
adequately care for the patient or resident who is ventilator dependent
can lead to iatrogenic events such as death, pneumonia and sepsis.
Mechanical ventilation further signifies the complexity of the
patient's underlying medical or surgical condition. Of note, invasive
mechanical ventilation is associated with high daily and aggregate
costs.\205\
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\205\ Wunsch, H., Linde-Zwirble, W.T., Angus, D. C., Hartman,
M.E., Milbrandt, E.B., & Kahn, J.M. (2010). ``The epidemiology of
mechanical ventilation use in the United States.'' Critical Care Med
38(10): 1947-1953.
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Data elements that capture invasive mechanical ventilation, but
vary in their level of specificity, are currently in use in the MDS 3.0
(``Ventilator or respirator''), LCDS (``Invasive Mechanical Ventilator:
weaning'' and ``Invasive Mechanical Ventilator: non-weaning''), and
related data elements that assess invasive ventilator use and weaning
status were tested in the PAC PRD (``Ventilator--Weaning'' and
``Ventilator--Non-Weaning'') and found feasible for use in each of the
four PAC settings.
Clinical and subject matter expert advisors working with our data
element contractor agreed that assessing Invasive Mechanical Ventilator
use is feasible in PAC, and would be clinically useful both within and
across PAC providers.
To solicit additional feedback on the form of a data element on
this topic that would be appropriate for standardization, data elements
that assess invasive ventilator use and weaning status that were tested
in the PAC PRD (``Ventilator--Weaning'' and ``Ventilator--Non-
Weaning'') were included in a call for public comment that was open
from August 12 to September 12, 2016 because they were being considered
for standardization. Several commenters wrote in support of these data
elements, highlighting the importance of this information in supporting
care coordination and care transitions. Some commenters expressed
concern about the appropriateness for standardization, given the
prevalence of ventilator weaning across PAC providers; the timing of
administration; how weaning is defined; and how weaning status in
particular relates to quality of care. These comments guided the
decision to propose a single data element focused on current use of
invasive mechanical ventilation only, and does not attempt to capture
weaning status. A full report of the comments is available at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
A TEP convened by the data element contractor provided input on the
proposed data elements. This TEP, held on January 5 and 6, 2017, opined
that these data elements are appropriate for standardization because
they would
[[Page 35364]]
provide useful clinical information to inform care planning and care
coordination. The TEP affirmed that assessment of these services and
interventions is standard clinical practice. A full report of the TEP
discussion is available at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
Therefore, we are proposing that the Invasive Mechanical Ventilator
data element that assesses the use of an invasive mechanical
ventilator, but does not assess weaning status, meets the definition of
standardized patient assessment data for special services, treatments,
and interventions under section 1899B(b)(1)(B)(iii) of the Act. We are
proposing to add the Invasive Mechanical Ventilator data element to the
OASIS, and that HHAs would be required to report these data for the CY
2020 HH QRP at SOC/ROC and discharge between January 1, 2019 and June
30, 2019. Following the initial two quarters of reporting for the CY
2020 HH QRP, subsequent years for the HH QRP would be based on 12
months of such data reporting beginning with July 1, 2019 through June
30, 2020 for the CY 2021 HH QRP.
We are inviting public comment on these proposals.
viii. Other Treatment: Intravenous (IV) Medications (Antibiotics,
Anticoagulation, Other)
We are proposing that the IV Medications (Antibiotics,
Anticoagulation, Other) data elements meet the definition of
standardized patient assessment data for special services, treatments,
and interventions under section 1899B(b)(1)(B)(iii) of the Act. The
proposed data elements consist of the principal IV Medications data
element and three sub-elements, Antibiotics, Anticoagulation, and
Other. For more information on the IV Medications (Antibiotics,
Anticoagulation, Other) data elements, we refer readers to the document
titled, Proposed Measure Specifications and Standardized Data Elements
for CY 2018 HH QRP Notice of Proposed Rulemaking, available at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HomeHealthQualityInits/HHQIQualityMeasures.html.
IV medications are solutions of a specific medication (for example,
antibiotics, anticoagulants) administered directly into the venous
circulation via a port or intravenous tubing. IV medications are
administered via intravenous push (bolus), single, intermittent, or
continuous infusion through a catheter placed into the vein (for
example, through central, midline, or peripheral ports). Further, IV
medications are more resource intensive to administer than oral
medications, and signify a higher patient complexity (and often higher
severity of illness).
The clinical indications for each of the sub-elements of the IV
Medication data element (Antibiotics, Anticoagulants, and Other) are
very different. IV antibiotics are used for severe infections when: (1)
The bioavailability of the oral form of the medication would be
inadequate to kill the pathogen; (2) an oral form of the medication
does not exist; or (3) the patient is unable to take the medication by
mouth. IV anticoagulants refer to anti-clotting medications (that is,
``blood thinners''), often used for the prevention and treatment of
deep vein thrombosis and other thromboembolic complications. IV
anticoagulants are commonly used in patients with limited mobility
(either chronically or acutely, in the post-operative setting), who are
at risk of deep vein thrombosis, or patients with certain cardiac
arrhythmias such as atrial fibrillation. The indications, risks, and
benefits of each of these classes of IV medications are distinct,
making it important to assess and monitor each separately in PAC.
Knowing whether or not patients are receiving IV medication and the
type of medication provided by each PAC provider will improve quality
of care.
The principal IV Medication data element is currently in use on the
MDS 3.0 and there is a related data element in OASIS-C2 that collects
information on Intravenous and Infusion Therapies. One sub-element of
the proposed data elements, IV Anti-coagulants, and two other data
elements related to IV therapy (IV Vasoactive Medications and IV
Chemotherapy), were tested in the PAC PRD and found feasible for use in
that the data collection aligned with usual work flow in each of the
four PAC settings, demonstrating the feasibility of collecting IV
medication information, including type of IV medication, through
similar data elements in these settings.
Clinical and subject matter expert advisors working with our data
element contractor agreed that standardized collection of information
on medications, including IV medications, would be feasible in PAC, and
assess an important treatment that would be clinically useful both
within and across PAC provider types.
We solicited public comment on a related data element, Vasoactive
Medications, from August 12 to September 12, 2016. While commenters
supported this data element with one noting the importance of this data
element in supporting care transitions, others criticized the need for
collecting specifically on Vasoactive Medications, giving feedback that
the data element was too narrowly focused. Additionally, comments
received indicated that the clinical significance of vasoactive
medications administration alone was not high enough in PAC to merit
mandated assessment, noting that related and more useful information
could be captured in an item that assessed all IV medication use.
Overall, public comment indicated the importance of including the
additional check box data elements to distinguish particular classes of
medications. A full report of the comments is available at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
A TEP convened by the data element contractor provided input on the
proposed data elements. This TEP, held on January 5 and 6, 2017, opined
that these data elements are appropriate for standardization because
they would provide useful clinical information to inform care planning
and care coordination. The TEP affirmed that assessment of these
services and interventions is standard clinical practice. A full report
of the TEP discussion is available at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
Therefore, we are proposing that the IV Medications (Antibiotics,
Anticoagulation, Other) data elements with a principal data element and
three sub-elements meet the definition of standardized patient
assessment data for special services, treatments, and interventions
under section 1899B(b)(1)(B)(iii) of the Act. We are proposing to add
the IV Medications (Antibiotics, Anticoagulation, Other) data elements
to the OASIS, and that HHAs would be required to report these data for
the CY 2020 HH QRP at SOC/ROC and discharge between January 1, 2019 and
June 30, 2019. Following the initial two quarters of reporting for the
CY 2020 HH QRP, subsequent years for the HH QRP would be based on 12
[[Page 35365]]
months of such data reporting beginning with July 1, 2019 through June
30, 2020 for the CY 2021 HH QRP.
We are inviting public comment on these proposals.
ix. Other Treatment: Transfusions
We are proposing that the Transfusions data element meets the
definition of standardized patient assessment data for special
services, treatments, and interventions under section
1899B(b)(1)(B)(iii) of the Act. The proposed data element consists of
the single Transfusions data element. For more information on the
Transfusions data element, we refer readers to the document titled,
Proposed Measure Specifications and Standardized Data Elements for CY
2018 HH QRP Notice of Proposed Rulemaking, available at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HomeHealthQualityInits/HHQIQualityMeasures.html.
Transfusion refers to introducing blood, blood products, or other
fluid into the circulatory system of a person. Blood transfusions are
based on specific protocols, with multiple safety checks and monitoring
required before, during, and after the infusion to prevent errors and
adverse events. Coordination with the provider's blood bank is
necessary, as well as documentation by clinical staff to ensure
compliance with regulatory requirements. In addition, the need for
transfusions signifies underlying patient complexity that is likely to
require care coordination and patient monitoring, and impacts planning
for transitions of care, as transfusions are not performed by all PAC
providers.
The proposed data element was selected from three existing
assessment items on transfusions and related services, currently in use
in the MDS 3.0 (``Transfusions'') and OASIS-C2 (``Intravenous or
Infusion Therapy''), and a data element tested in the PAC PRD (``Blood
Transfusions''), that was found feasible for use in each of the four
PAC settings. We chose to propose the MDS version because of its
greater level of specificity over the OASIS-C2 data element. This
selection was informed by expert advisors and reviewed and supported in
the proposed form by the Standardized Patient Assessment Data TEP held
by our data element contractor on January 5 and 6, 2017. A full report
of the TEP discussion is available at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
Therefore, we are proposing that the Transfusions data element that
is currently in use in the MDS meets the definition of standardized
patient assessment data for special services, treatments, and
interventions under section 1899B(b)(1)(B)(iii) of the Act. We are
proposing to add the Transfusions data element to the OASIS, and that
HHAs would be required to report these data for the CY 2020 HH QRP at
SOC/ROC and discharge between January 1, 2019 and June 30, 2019.
Following the initial two quarters of reporting for the CY 2020 HH QRP,
subsequent years for the HH QRP would be based on 12 months of such
data reporting beginning with July 1, 2019 through June 30, 2020 for
the CY 2021 HH QRP.
We are inviting public comment on these proposals.
x. Other Treatment: Dialysis (Hemodialysis, Peritoneal Dialysis)
We are proposing that the Dialysis (Hemodialysis, Peritoneal
dialysis) data elements meet the definition of standardized patient
assessment data for special services, treatments, and interventions
under section 1899B(b)(1)(B)(iii) of the Act. The proposed data
elements consist of the principal Dialysis data element and two sub-
elements, Hemodialysis and Peritoneal dialysis. For more information on
the Dialysis (Hemodialysis, Peritoneal dialysis) data elements, we
refer readers to the document titled, Proposed Measure Specifications
and Standardized Data Elements for CY 2018 HH QRP Notice of Proposed
Rulemaking, available at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HomeHealthQualityInits/HHQIQualityMeasures.html.
Dialysis is a treatment primarily used to provide replacement for
lost kidney function. Both forms of dialysis (hemodialysis and
peritoneal dialysis) are resource intensive, not only during the actual
dialysis process but before, during, and after treatment. Patients and
residents who need and undergo dialysis procedures are at high risk for
physiologic and hemodynamic instability from fluid shifts and
electrolyte disturbances, as well as infections that can lead to
sepsis. Further, patients or residents receiving hemodialysis are often
transported to a different facility, or at a minimum, to a different
location in the same facility. Close monitoring for fluid shifts, blood
pressure abnormalities, and other adverse effects is required prior to,
during and following each dialysis session. Nursing staff typically
perform peritoneal dialysis at the bedside, and as with hemodialysis,
close monitoring is required.
The principal Dialysis data element is currently included on the
MDS 3.0 and the LCDS v3.0 and assesses the overall use of dialysis. The
sub-elements for Hemodialysis and Peritoneal dialysis were tested
across the four PAC providers in the PAC PRD study, and found to be
feasible for standardization. Clinical and subject matter expert
advisors working with our data element contractor opined that the
standardized assessment of dialysis is feasible in PAC, and that it
assesses an important treatment that would be clinically useful both
within and across PAC providers. As the result of expert and public
feedback, described below, we decided to propose data elements that
include both the principal Dialysis data element and the two sub-
elements (hemodialysis and peritoneal dialysis).
The Hemodialysis data element, which was tested in the PAC PRD, was
included in a call for public comment that was open from August 12 to
September 12, 2016. Commenters supported the assessment of hemodialysis
and recommended that the data element be expanded to include peritoneal
dialysis. Several commenters supported the Hemodialysis data element,
noting the relevance of this information for sharing across the care
continuum to facilitate care coordination and care transitions, the
potential for this data element to be used to improve quality, and the
feasibility for use in PAC. In addition, we received comment that the
item would be useful in improving patient and resident transitions of
care. Several commenters also stated that peritoneal dialysis should be
included in a standardized data element on dialysis and recommended
collecting information on peritoneal dialysis in addition to
hemodialysis. The rationale for including peritoneal dialysis from
commenters included the fact that patients and residents receiving
peritoneal dialysis will have different needs at post-acute discharge
compared to those receiving hemodialysis or not having any dialysis.
Based on these comments, the Hemodialysis data element was expanded to
include a principal Dialysis data element and two sub-elements,
hemodialysis and peritoneal dialysis; these are the same two data
elements that were tested in the PAC PRD. This expanded version,
Dialysis (Hemodialysis, Peritoneal dialysis), are the data elements
being proposed. A full report of the comments
[[Page 35366]]
is available at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
We note that the Dialysis (Hemodialysis, Peritoneal dialysis) data
elements were also supported by the TEP that discussed candidate data
elements for Special Services, Treatments, and Interventions during a
meeting on January 5 and 6, 2017. A full report of the TEP discussion
is available at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
Therefore, we are proposing that the Dialysis (Hemodialysis,
Peritoneal dialysis) data elements with a principal data element and
two sub-elements meet the definition of standardized patient assessment
data for special services, treatments, and interventions under section
1899B(b)(1)(B)(iii) of the Act. We are proposing to add the Dialysis
(Hemodialysis, Peritoneal dialysis) data elements to the OASIS, and
that HHAs would be required to report these data for the CY 2020 HH QRP
at SOC/ROC and discharge between January 1, 2019 and June 30, 2019.
Following the initial two quarters of reporting for the CY 2020 HH QRP,
subsequent years for the HH QRP would be based on 12 months of such
data reporting beginning with July 1, 2019 through June 30, 2020 for
the CY 2021 HH QRP.
We are inviting public comment on these proposals.
xi. Other Treatment: Intravenous (IV) Access (Peripheral IV, Midline,
Central Line, Other)
We are proposing that the IV Access (Peripheral IV, Midline,
Central line, Other) data elements meet the definition of standardized
patient assessment data for special services, treatments, and
interventions under section 1899B(b)(1)(B)(iii) of the Act. The
proposed data elements consist of the principal IV Access data element
and four sub-elements, Peripheral IV, Midline, Central line, and Other.
For more information on the IV Access (Peripheral IV, Midline, Central
line, Other) data elements, we refer readers to the document titled,
Proposed Measure Specifications and Standardized Data Elements for CY
2018 HH QRP Notice of Proposed Rulemaking, available at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HomeHealthQualityInits/HHQIQualityMeasures.html.
Patients or residents with central lines, including those
peripherally inserted or who have subcutaneous central line ``port''
access, always require vigilant nursing care to ensure patency of the
lines and prevent any potentially life-threatening events such as
infection, air embolism, or bleeding from an open lumen. Clinically
complex patients and residents are likely to be receiving medications
or nutrition intravenously. The sub-elements included in the IV Access
data elements distinguish between peripheral access and different types
of central access. The rationale for distinguishing between a
peripheral IV and central IV access is that central lines confer higher
risks associated with life-threatening events such as pulmonary
embolism, infection, and bleeding.
The proposed IV Access (Peripheral IV, Midline, Central line,
Other) data elements are not currently included on any of the mandated
PAC assessment instruments. However, related data elements (for
example, IV Medication in MDS 3.0 for SNF, Intravenous or infusion
therapy in OASIS-C2 for HHAs) currently assess types of IV infusions or
service. Several related data elements that describe types of IV
infusions and services (for example, Central Line Management, IV
Vasoactive Medications) were tested across the four PAC providers in
the PAC PRD study, and found to be feasible for standardization.
Clinical and subject matter expert advisors working with our data
element contractor agreed that assessing type of IV access would be
feasible for use in PAC and that it assesses an important treatment
that would be clinically useful both within and across PAC provider
types.
We requested public comment on one of the PAC PRD data elements,
Central Line Management, from August 12 to September 12, 2016. A
central line is one type of IV access. Commenters supported the
assessment of central line management and recommended that the data
element be broadened to also include other types of IV access. Several
commenters supported the data element, noting feasibility and
importance for facilitating care coordination and care transitions.
However, a few commenters recommended that the definition of this data
element be broadened to include peripherally inserted central catheters
(``PICC lines'') and midline IVs. Based on public comment feedback and
in consultation with clinical and subject matter experts, we expanded
the Central Line Management data element to include more types of IV
access (Peripheral IV, Midline, Central line, Other). This expanded
version, IV Access (Peripheral IV, Midline, Central line, Other), are
the data elements being proposed. A full report of the comments is
available at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
We note that the IV Access (Peripheral IV, Midline, Central line,
Other) data elements were supported by the TEP that discussed candidate
data elements for Special Services, Treatments, and Interventions
during a meeting on January 5 and 6, 2017. A full report of the TEP
discussion is available at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
Therefore, we are proposing that the IV access (Peripheral IV,
Midline, Central line, Other) data elements with a principal data
element and four sub-elements meet the definition of standardized
patient assessment data for special services, treatments, and
interventions under section 1899B(b)(1)(B)(iii) of the Act. We are
proposing to add the IV Access (Peripheral IV, Midline, Central line,
Other) data elements to the OASIS and that HHAs would be required to
report these data for the CY 2020 HH QRP at SOC/ROC and discharge
between January 1, 2019 and June 30, 2019. Following the initial two
quarters of reporting for the CY 2020 HH QRP, subsequent years for the
HH QRP would be based on 12 months of such data reporting beginning
with July 1, 2019 through June 30, 2020 for the CY 2021 HH QRP.
We are inviting public comment on these proposals.
xii. Nutritional Approach: Parenteral/IV Feeding
We are proposing that the Parenteral/IV Feeding data element meets
the definition of standardized patient assessment data for special
services, treatments, and interventions under section
1899B(b)(1)(B)(iii) of the Act. The proposed data element consists of
the single Parenteral/IV Feeding data element. For more information on
the Parenteral/IV Feeding data element, we refer readers to the
document titled, Proposed Measure Specifications and Standardized Data
Elements for CY 2018 HH QRP Notice of Proposed
[[Page 35367]]
Rulemaking, available at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HomeHealthQualityInits/HHQIQualityMeasures.html.
Parenteral/IV Feeding refers to a patient or resident being fed
intravenously using an infusion pump, bypassing the usual process of
eating and digestion. The need for IV/parenteral feeding indicates a
clinical complexity that prevents the patient or resident from meeting
his/her nutritional needs enterally, and is more resource intensive
than other forms of nutrition, as it often requires monitoring of blood
chemistries, and maintenance of a central line. Therefore, assessing a
patient or resident's need for parenteral feeding is important for care
planning and resource use. In addition to the risks associated with
central and peripheral intravenous access, total parenteral nutrition
is associated with significant risks such as embolism, sepsis, and
glucose abnormalities.
The Parenteral/IV Feeding data element is currently in use in the
MDS 3.0, and equivalent or related data elements are in use in the
LCDS, IRF-PAI, and the OASIS-C2. An equivalent data element was tested
in the PAC PRD (``Total Parenteral Nutrition'') and found feasible for
use in each of the four PAC settings, demonstrating the feasibility of
collecting information about this nutritional service in these
settings.
Total Parenteral Nutrition (an item with the same meaning as the
proposed data element, but with the label used in the PAC PRD) was
included in a call for public comment that was open from August 12 to
September 12, 2016. Several commenters supported this data element,
noting its relevance to facilitating care coordination and supporting
care transitions. After the public comment period, the Total Parenteral
Nutrition data element was re-named Parenteral/IV Feeding, to be
consistent with how this data element is referred to in the MDS. A full
report of the comments is available at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
A TEP convened by the data element contractor provided input on the
proposed data elements. This TEP, held on January 5 and 6, 2017, opined
that these data elements are appropriate for standardization because
they would provide useful clinical information to inform care planning
and care coordination. The TEP affirmed that assessment of these
services and interventions is standard clinical practice. A full report
of the TEP discussion is available at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
Therefore, we are proposing that the Parenteral/IV Feeding data
element meets the definition of standardized patient assessment data
for special services, treatments, and interventions under section
1899B(b)(1)(B)(iii) of the Act. We are proposing to rename the existing
``Parenteral nutrition (TPN or lipids)'' data element in the OASIS to
the Parenteral/IV Feeding data element, and that HHAs would be required
to report these data for the CY 2020 HH QRP at SOC/ROC and discharge
between January 1, 2019, and June 30, 2019. Following the initial two
quarters of reporting for the CY 2020 HH QRP, subsequent years for the
HH QRP would be based on 12 months of such data reporting beginning
with July 1, 2019, through June 30, 2020 for the CY 2021 HH QRP.
We are inviting public comment on these proposals.
xiv. Nutritional Approach: Feeding Tube
We are proposing that the Feeding Tube data element meets the
definition of standardized patient assessment data for special
services, treatments, and interventions under section
1899B(b)(1)(B)(iii) of the Act. The proposed data element consists of
the single Feeding Tube data element. For more information on the
Feeding Tube data element, we refer readers to the document titled,
Proposed Measure Specifications and Standardized Data Elements for CY
2018 HH QRP Notice of Proposed Rulemaking, available at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HomeHealthQualityInits/HHQIQualityMeasures.html.
The majority of patients admitted to acute care hospitals
experience deterioration of their nutritional status during their
hospital stay, making assessment of nutritional status and method of
feeding, if unable to eat orally, very important in PAC. A feeding tube
can be inserted through the nose or the skin on the abdomen to deliver
liquid nutrition into the stomach or small intestine. Feeding tubes are
resource intensive and are therefore important to assess for care
planning and resource use. Patients with severe malnutrition are at
higher risk for a variety of complications.\206\ In PAC settings, there
are a variety of reasons that patients and residents may not be able to
eat orally (including clinical or cognitive status).
---------------------------------------------------------------------------
\206\ Dempsey, D.T., Mullen, J.L., & Buzby, G.P. (1988). ``The
link between nutritional status and clinical outcome: can
nutritional intervention modify it?'' Am J of Clinical Nutrition
47(2): 352-356.
---------------------------------------------------------------------------
The Feeding Tube data element is currently included in the MDS 3.0
for SNFs, and in the OASIS-C2 for HHAs, where it is labeled Enteral
Nutrition. A related data element is collected in the IRF-PAI for IRFs
(Tube/Parenteral Feeding). The testing of similar nutrition-focused
data elements in the PAC PRD, and the current assessment of feeding
tubes and related nutritional services and devices, demonstrates the
feasibility of collecting information about this nutritional service in
these settings.
Clinical and subject matter expert advisors working with our data
element contractor opined that the Feeding Tube data element is
feasible for use in PAC, and supported its importance and clinical
usefulness for patients in PAC settings, due to the increased level of
nursing care and patient monitoring required for patients who received
enteral nutrition with this device.
We solicited additional feedback on an Enteral Nutrition data
element (an item with the same meaning as the proposed data element,
but with the label used in the OASIS) in a call for public comment that
was open from August 12 to September 12, 2016. Several commenters
supported the data element, noting the importance of assessing enteral
nutrition status for facilitating care coordination and care
transitions. After the public comment period, the Enteral Nutrition
data element used in public comment was re-named Feeding Tube,
indicating the presence of an assistive device. A full report of the
comments is available at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
We note that the Feeding Tube data element was also supported by
the TEP that discussed candidate data elements for Special Services,
Treatments, and Interventions during a meeting on January 5 and 6,
2017. A full report of the TEP discussion is available at https://
www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-
Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/
[[Page 35368]]
IMPACT-Act-Downloads-and-Videos.html.
Therefore, we are proposing that the Feeding Tube data element
meets the definition of standardized patient assessment data for
special services, treatments, and interventions under section
1899B(b)(1)(B)(iii) of the Act. We are proposing to rename the existing
``Enteral nutrition (nasogastric, gastrostomy, jejunostomy, or any
other artificial entry into the alimentary canal)'' data element in the
OASIS to the Feeding Tube data element and that HHAs would be required
to report these data for the CY 2020 HH QRP at SOC/ROC and discharge
between January 1, 2019, and June 30, 2019. Following the initial two
quarters of reporting for the CY 2020 HH QRP, subsequent years for the
HH QRP would be based on 12 months of such data reporting beginning
with July 1, 2019 through June 30, 2020 for the CY 2021 HH QRP.
We are inviting public comment on these proposals.
xv. Nutritional Approach: Mechanically Altered Diet
We are proposing that the Mechanically Altered Diet data element
meets the definition of standardized patient assessment data for
special services, treatments, and interventions under section
1899B(b)(1)(B)(iii) of the Act. The proposed data element consists of
the single Mechanically Altered Diet data element. For more information
on the Mechanically Altered Diet data element, we refer readers to the
document titled, Proposed Measure Specifications and Standardized Data
Elements for CY 2018 HH QRP Notice of Proposed Rulemaking, available at
https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HomeHealthQualityInits/HHQIQualityMeasures.html.
The Mechanically Altered Diet data element refers to food that has
been altered to make it easier for the patient or resident to chew and
swallow, and this type of diet is used for patients and residents who
have difficulty performing these functions. Patients with severe
malnutrition are at higher risk for a variety of complications.\207\ In
PAC settings, there are a variety of reasons that patients and
residents may have impairments related to oral feedings, including
clinical or cognitive status. The provision of a mechanically altered
diet may be resource intensive, and can signal difficulties associated
with swallowing/eating safety, including dysphagia. In other cases, it
signifies the type of altered food source, such as ground or puree,
which will enable the safe and thorough ingestion of nutritional
substances and ensure safe and adequate delivery of nourishment to the
patient. Often, patients on mechanically altered diets also require
additional nursing supports such as individual feeding, or direct
observation, to ensure the safe consumption of the food product.
Assessing whether a patient or resident requires a mechanically altered
diet is therefore important for care planning and resource
identification.
---------------------------------------------------------------------------
\207\ Dempsey, D.T., Mullen, J.L., & Buzby, G.P. (1988). ``The
link between nutritional status and clinical outcome: can
nutritional intervention modify it?'' Am J of Clinical Nutrition
47(2): 352-356.
---------------------------------------------------------------------------
The proposed data element for a mechanically altered diet is
currently included on the MDS 3.0 for SNFs. A related data element for
modified food consistency/supervision is currently included on the IRF-
PAI for IRFs. A related data element is included in the OASIS-C2 for
HHAs that collects information about independent eating that requires
``a liquid, pureed or ground meat diet.'' The testing of similar
nutrition-focused data elements in the PAC PRD, and the current
assessment of various nutritional services across the four PAC
settings, demonstrates the feasibility of collecting information about
this nutritional service in these settings.
Clinical and subject matter expert advisors working with our data
element contractor agreed that the proposed Mechanically Altered Diet
data element is feasible for use in PAC, and it assesses an important
treatment that would be clinically useful both within and across PAC
settings. Expert input on the Mechanically Altered Diet data element
highlighted its importance and clinical usefulness for patients in PAC
settings, due to the increased monitoring and resource use required for
patients on special diets. We note that the Mechanically Altered Diet
data element was also supported by the TEP that discussed candidate
data elements for Special Services, Treatments, and Interventions
during a meeting on January 5 and 6, 2017. A full report of the TEP
discussion is available at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
Therefore, we are proposing that the Mechanically Altered Diet data
element meets the definition of standardized patient assessment data
for special services, treatments, and interventions under section
1899B(b)(1)(B)(iii) of the Act. We are proposing to add the
Mechanically Altered Diet data element to the OASIS, and that HHAs
would be required to report these data for the CY 2020 HH QRP at SOC/
ROC and discharge between January 1, 2019 and June 30, 2019. Following
the initial two quarters of reporting for the CY 2020 HH QRP,
subsequent years for the HH QRP would be based on 12 months of such
data reporting beginning with July 1, 2019, through June 30, 2020 for
the CY 2021 HH QRP.
We are inviting public comment on these proposals.
xvi. Nutritional Approach: Therapeutic Diet
We are proposing that the Therapeutic Diet data element meets the
definition of standardized patient assessment data for special
services, treatments, and interventions under section
1899B(b)(1)(B)(iii) of the Act. The proposed data element consists of
the single Therapeutic Diet data element. For more information on the
Therapeutic Diet data element, we refer readers to the document titled,
Proposed Measure Specifications and Standardized Data Elements for CY
2018 HH QRP Notice of Proposed Rulemaking, available at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HomeHealthQualityInits/HHQIQualityMeasures.html.
Therapeutic Diet refers to meals planned to increase, decrease, or
eliminate specific foods or nutrients in a patient or resident's diet,
such as a low-salt diet, for the purpose of treating a medical
condition. The use of therapeutic diets among patients in PAC provides
insight on the clinical complexity of these patients and their multiple
comorbidities. Therapeutic diets are less resource intensive from the
bedside nursing perspective, but can signify one or more underlying
clinical conditions that preclude the patient from eating a regular
diet. They also often require more education and lifestyle modification
training. The communication among PAC providers about whether a patient
is receiving a particular therapeutic diet is critical to ensure safe
transitions of care.
The Therapeutic Diet data element is currently in use in the MDS
3.0. The testing of similar nutrition-focused data elements in the PAC
PRD, and the current assessment of various nutritional services across
the four PAC settings, demonstrates the feasibility of collecting
information about this nutritional service in these settings.
Clinical and subject matter expert advisors working with our data
element contractor supported the importance
[[Page 35369]]
and clinical usefulness of the proposed Therapeutic Diet data element
for patients in PAC settings, due to the increased monitoring and
resource use required for patients on special diets, and agreed that it
is feasible for use in PAC and that it assesses an important treatment
that would be clinically useful both within and across PAC settings. We
note that the Therapeutic Diet data element was also supported by the
TEP that discussed candidate data elements for Special Services,
Treatments, and Interventions during a meeting on January 5 and 6,
2017.
Therefore, we are proposing that the Therapeutic Diet data element
meets the definition of standardized patient assessment data for
special services, treatments, and interventions under section
1899B(b)(1)(B)(iii) of the Act. We are proposing to add the Therapeutic
Diet data element to the OASIS, and that HHAs would be required to
report these data for the CY 2020 HH QRP at SOC/ROC and discharge
between January 1, 2019 and June 30, 2019. Following the initial two
quarters of reporting for the CY 2020 HH QRP, subsequent years for the
HH QRP would be based on 12 months of such data reporting beginning
with July 1, 2019, through June 30, 2020 for the CY 2021 HH QRP.
We are inviting public comment on these proposals.
d. Medical Condition and Comorbidity Data
We are proposing that the data elements needed to calculate the
current measure, Percent of Residents or Patients with Pressure Ulcers
That Are New or Worsened (Short Stay) (NQF #0678), and that the
proposed measure, Changes in Skin Integrity Post-Acute Care: Pressure
Ulcer/Injury, meet the definition of standardized patient assessment
data with respect to medical conditions and co-morbidities under
section 1899B(b)(1)(B)(iv) of the Act, and that the successful
reporting of that data under section 1895(b)(3)(B)(v)(IV)(aa) of the
Act would also satisfy the requirement to report standardized patient
assessment data under section 1895(b)(3)(B)(v)(IV)(bb) of the Act.
``Medical conditions and co-morbidities'' and the conditions
addressed in the standardized data elements used in the calculation and
risk adjustment of these measures, that is, the presence of pressure
ulcers, diabetes, incontinence, peripheral vascular disease or
peripheral arterial disease, mobility, as well as low body mass index
(BMI), are all health-related conditions that indicate medical
complexity that can be indicative of underlying disease severity and
other comorbidities.
Specifically, the data elements used in the measure are important
for care planning and provide information pertaining to medical
complexity. Pressure ulcers are serious wounds representing poor
outcomes, and can result in sepsis and death. Assessing skin condition,
care planning for pressure ulcer prevention and healing, and informing
providers about their presence in patient transitions of care is
imperative a customary and best practice. Venous and arterial disease
and diabetes are associated with insufficient low blood flow, which may
increase the risk of tissue damage. These diseases commonly are
indicators of factors that may place individuals at risk for pressure
ulcer development and are therefore important for care planning. Low
BMI, which may be an indicator of underlying disease severity, may be
associated with loss of fat and muscle, resulting in potential risk for
pressure ulcers due to shearing. Bowel incontinence, and the possible
maceration to the skin associated, can lead to higher risk for pressure
ulcers. In addition, the bacteria associated with bowel incontinence
can complicate current wounds and cause local infection. Mobility is an
indicator of impairment or reduction in mobility and movement which is
a major risk factor for the development of pressure ulcers. Taken
separately and together, these data elements are important for care
planning, transitions in services and identifying medical complexities.
e. Impairment Data
Hearing and vision impairments are conditions that, if unaddressed,
affect activities of daily living, communication, physical functioning,
rehabilitation outcomes, and overall quality of life. Sensory
limitations can lead to confusion in new settings, increase isolation,
contribute to mood disorders, and impede accurate assessment of other
medical conditions. Failure to appropriately assess, accommodate, and
treat these conditions increases the likelihood that patients will
require more intensive and prolonged treatment. Onset of these
conditions can be gradual, so individualized assessment with accurate
screening tools and regular follow-up evaluations are essential to
determining which patients need hearing- or vision-specific medical
attention or assistive devices, and accommodations, including auxiliary
aids and/or services, and to ensure that person-directed care plans are
developed to accommodate a patient's needs. Accurate diagnosis and
management of hearing or vision impairment would likely improve
rehabilitation outcomes and care transitions, including transition from
institutional-based care to the community. Accurate assessment of
hearing and vision impairment would be expected to lead to appropriate
treatment, accommodations, including the provision of auxiliary aids
and services during the stay, and ensure that patients continue to have
their vision and hearing needs met when they leave the facility.
Accurate individualized assessment, treatment, and accommodation of
hearing and vision impairments of patients and residents in PAC would
be expected to have a positive impact on the National Quality
Strategy's domains of patient and family engagement, patient safety,
care coordination, clinical process/effectiveness, and efficient use of
healthcare resources. For example, standardized assessment of hearing
and vision impairments used in PAC will support ensuring patient safety
(for example, risk of falls) identifying accommodations needed during
the stay, and appropriate support needs at the time of discharge or
transfer. Standardized assessment of these data elements will enable or
support clinical decision-making and early clinical intervention;
person-centered, high quality care (for example, facilitating better
care continuity and coordination); better data exchange and
interoperability between settings; and longitudinal outcome analysis.
Hence, reliable data elements assessing hearing and vision impairments
are needed to initiate a management program that can optimize a patient
or resident's prognosis and reduce the possibility of adverse events.
i. Hearing
We are proposing that the Hearing data element meets the definition
of standardized patient assessment data for impairments under section
1899B(b)(1)(B)(v) of the Act. The proposed data element consists of the
single Hearing data element. This data element assesses level of
hearing impairment, and consists of one question. For more information
on the Hearing data element, we refer readers to the document titled,
Proposed Measure Specifications and Standardized Data Elements for CY
2018 HH QRP Notice of Proposed Rulemaking, available at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HomeHealthQualityInits/HHQIQualityMeasures.html.
[[Page 35370]]
Accurate assessment of hearing impairment is important in the PAC
setting for care planning and resource use. Hearing impairment has been
associated with lower quality of life, including poorer physical,
mental, and social functioning, and emotional health.208 209
Treatment and accommodation of hearing impairment led to improved
health outcomes, including but not limited to increased quality of
life.\210\ For example, hearing loss in elderly individuals has been
associated with depression and cognitive
impairment,211 212 213 higher rates of incident cognitive
impairment and cognitive decline,\214\ and less time in occupational
therapy.\215\ Accurate assessment of hearing impairment is important in
the PAC setting for care planning and defining resource use.
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\208\ Dalton DS, Cruickshanks KJ, Klein BE, Klein R, Wiley TL,
Nondahl DM. The impact of hearing loss on quality of life in older
adults. Gerontologist. 2003;43(5):661-668.
\209\ Hawkins K, Bottone FG, Jr., Ozminkowski RJ, et al. The
prevalence of hearing impairment and its burden on the quality of
life among adults with Medicare Supplement Insurance. Qual Life Res.
2012;21(7):1135-1147.
\210\ Horn KL, McMahon NB, McMahon DC, Lewis JS, Barker M,
Gherini S. Functional use of the Nucleus 22-channel cochlear implant
in the elderly. The Laryngoscope. 1991;101(3):284-288.
\211\ Sprinzl GM, Riechelmann H. Current trends in treating
hearing loss in elderly people: a review of the technology and
treatment options--a mini-review. Gerontology. 2010;56(3):351-358.
\212\ Lin FR, Thorpe R, Gordon-Salant S, Ferrucci L. Hearing
Loss Prevalence and Risk Factors Among Older Adults in the United
States. The Journals of Gerontology Series A: Biological Sciences
and Medical Sciences. 2011;66A(5):582-590.
\213\ Hawkins K, Bottone FG, Jr., Ozminkowski RJ, et al. The
prevalence of hearing impairment and its burden on the quality of
life among adults with Medicare Supplement Insurance. Qual Life Res.
2012;21(7):1135-1147.
\214\ Lin FR, Metter EJ, O'Brien RJ, Resnick SM, Zonderman AB,
Ferrucci L. Hearing Loss and Incident Dementia. Arch Neurol.
2011;68(2):214-220.
\215\ Cimarolli VR, Jung S. Intensity of Occupational Therapy
Utilization in Nursing Home Residents: The Role of Sensory
Impairments. J Am Med Dir Assoc. 2016;17(10):939-942.
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The proposed data element was selected from two forms of the
Hearing data element based on expert and stakeholder feedback. We
considered the two forms of the Hearing data element, one of which is
currently in use in the MDS 3.0 (Hearing) and another data element with
different wording and fewer response option categories that is
currently in use in the OASIS-C2 (Ability to Hear). Ability to Hear was
also tested in the PAC PRD and found to have substantial agreement for
inter-rater reliability across PAC settings (kappa of 0.78).\216\
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\216\ Gage B., Smith L., Ross J. et al. (2012). The Development
and Testing of the Continuity Assessment Record and Evaluation
(CARE) Item Set (Final Report on Reliability Testing, Volume 2 of
3). Research Triangle Park, NC: RTI International.
---------------------------------------------------------------------------
Several data elements that assess hearing impairment were presented
to the Standardized Patient Assessment Data TEP held by our data
element contractor. The TEP did not reach consensus on the ideal number
of response categories or phrasing of response options, which are the
primary differences between the current MDS (Hearing) and OASIS
(Ability to Hear) items. The Development and Maintenance of Post-Acute
Care Cross-Setting Standardized Patient Assessment Data Technical
Expert Panel Summary Report is available at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
The PAC PRD form of the data element (Ability to Hear) was included
in a call for public comment that was open from August 12 to September
12, 2016. This data element includes three response choices, in
contrast to the Hearing data element (in use in the MDS 3.0 and being
proposed for standardization), which includes four response choices.
Several commenters supported the use of the Ability to Hear data
element, although some commenters raised concerns that the three-level
response choice was not compatible with the current, four-level
response used in the MDS, and favored the use of the MDS version of the
Hearing data element. In addition, we received comments stating that
standardized assessment related to hearing impairment has the ability
to improve quality of care if information on hearing is included in
medical records of patients and residents, which would improve care
coordination and facilitate the development of patient- and resident-
centered treatment plans. Based on comments that the three-level
response choice (Ability to Hear) was not congruent with the current,
four-level response used in the MDS (Hearing), and support for the use
of the MDS version of the Hearing data element received in the public
comment, we are proposing the Hearing data element from the MDS. A full
report of the comments is available at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
Therefore, we are proposing the Hearing data element currently in
use in the MDS. We are proposing to add the Hearing data element to the
OASIS, and that HHAs would be required to report these data for the CY
2020 HH QRP at SOC/ROC between January 1, 2019 and June 30, 2019.
Following the initial two quarters of reporting for the CY 2020 HH QRP,
subsequent years for the HH QRP would be based on 12 months of such
data reporting beginning with July 1, 2019, through June 30, 2020 for
the CY 2021 HH QRP. The Hearing data element would be assessed at SOC/
ROC only due to the relatively stable nature of hearing impairment,
making it unlikely that this assessment would change between the start
and end of care. Assessment at discharge would introduce additional
burden without improving the quality or usefulness of the data, and we
believe it is unnecessary.
We are inviting public comment on these proposals.
ii. Vision
We are proposing that the Vision data element meets the definition
of standardized patient assessment data for impairments under section
1899B(b)(1)(B)(v) of the Act. The proposed data element consists of the
single Vision (Ability To See in Adequate Light) data element that
consists of one question with five response categories. For more
information on the Vision data element, we refer readers to the
document titled, Proposed Measure Specifications and Standardized Data
Elements for CY 2018 HH QRP Notice of Proposed Rulemaking, available at
https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HomeHealthQualityInits/HHQIQualityMeasures.html.
Evaluation of an individual's ability to see is important for
assessing for risks such as falls and provides opportunities for
improvement through treatment and the provision of accommodations,
including auxiliary aids and services, which can safeguard patients and
improve their overall quality of life. Further, vision impairment is
often a treatable risk factor associated with adverse events and poor
quality of life. For example, individuals with visual impairment are
more likely to experience falls and hip fracture, have less mobility,
and report depressive symptoms.217 218 219 220 221 222 223
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\217\ Colon-Emeric CS, Biggs DP, Schenck AP, Lyles KW. Risk
factors for hip fracture in skilled nursing facilities: who should
be evaluated? Osteoporos Int. 2003;14(6):484-489.
\218\ Freeman EE, Munoz B, Rubin G, West SK. Visual field loss
increases the risk of falls in older adults: the Salisbury eye
evaluation. Invest Ophthalmol Vis Sci. 2007;48(10):4445-4450.
\219\ Keepnews D, Capitman JA, Rosati RJ. Measuring patient-
level clinical outcomes of home health care. J Nurs Scholarsh.
2004;36(1):79-85.
\220\ Nguyen HT, Black SA, Ray LA, Espino DV, Markides KS.
Predictors of decline in MMSE scores among older Mexican Americans.
J Gerontol A Biol Sci Med Sci. 2002;57(3):M181-185.
\221\ Prager AJ, Liebmann JM, Cioffi GA, Blumberg DM. Self-
reported Function, Health Resource Use, and Total Health Care Costs
Among Medicare Beneficiaries With Glaucoma. JAMA ophthalmology.
2016;134(4):357-365.
\222\ Rovner BW, Ganguli M. Depression and disability associated
with impaired vision: the MoVies Project. J Am Geriatr Soc.
1998;46(5):617-619.
\223\ Tinetti ME, Ginter SF. The nursing home life-space
diameter. A measure of extent and frequency of mobility among
nursing home residents. J Am Geriatr Soc. 1990;38(12):1311-1315.
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[[Page 35371]]
Individualized initial screening can lead to life-improving
interventions such as accommodations, including the provision of
auxiliary aids and services, during the stay and/or treatments that can
improve vision and prevent or slow further vision loss. For patients
with some types of visual impairment, use of glasses and contact lenses
can be effective in restoring vision.\224\ Other conditions, including
glaucoma\225\ and age-related macular degeneration,226 227
have responded well to treatment. Accurate assessment of vision
impairment is important in the PAC setting for care planning and
defining resource use.
---------------------------------------------------------------------------
\224\ Rein DB, Wittenborn JS, Zhang X, et al. The Cost-
effectiveness of Welcome to Medicare Visual Acuity Screening and a
Possible Alternative Welcome to Medicare Eye Evaluation Among
Persons Without Diagnosed Diabetes Mellitus. Archives of
ophthalmology. 2012;130(5):607-614.
\225\ Leske M, Heijl A, Hussein M, et al. Factors for glaucoma
progression and the effect of treatment: The early manifest glaucoma
trial. Archives of Ophthalmology. 2003;121(1):48-56.
\226\ Age-Related Eye Disease Study Research G. A randomized,
placebo-controlled, clinical trial of high-dose supplementation with
vitamins c and e, beta carotene, and zinc for age-related macular
degeneration and vision loss: AREDS report no. 8. Archives of
Ophthalmology. 2001;119(10):1417-1436.
\227\ Takeda AL, Colquitt J, Clegg AJ, Jones J. Pegaptanib and
ranibizumab for neovascular age[hyphen]related macular degeneration:
a systematic review. The British Journal of Ophthalmology.
2007;91(9):1177-1182.
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The Vision data element that we are proposing for standardization
was tested as part of the development of the MDS 3.0 and is currently
in use in that assessment. Similar data elements, but with different
wording and fewer response option categories, are in use in the OASIS-
C2 and were tested in post-acute providers in the PAC PRD and found to
be clinically relevant, meaningful for care planning, reliable (kappa
of 0.74),\228\ and feasible for use in each of the four PAC settings.
---------------------------------------------------------------------------
\228\ Gage B., Smith L., Ross J. et al. (2012). The Development
and Testing of the Continuity Assessment Record and Evaluation
(CARE) Item Set (Final Report on Reliability Testing, Volume 2 of
3). Research Triangle Park, NC: RTI International.
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Several data elements that assess vision were presented to the TEP
held by our data element contractor. The TEP did not reach consensus on
the ideal number of response categories or phrasing of response
options, which are the primary differences between the current MDS and
OASIS items; some members preferring more granular response options
(for example, mild impairment and moderate impairment) while others
were comfortable with collapsed response options (that is, mild/
moderate impairment). The Development and Maintenance of Post-Acute
Care Cross-Setting Standardized Patient Assessment Data Technical
Expert Panel Summary Report is available at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
We solicited public comment from August 12 to September 12, 2016,
on the Ability to See in Adequate Light data element (version tested in
the PAC PRD with three response categories). The data element in public
comment differed from the proposed data element, but the comments
supported the assessment of vision in PAC settings and the useful
information a vision data element would provide. The commenters stated
that the Ability to See item would provide important information that
would facilitate care coordination and care planning, and consequently
improve the quality of care. Other commenters suggested it would be
helpful as an indicator of resource use and noted that the item would
provide useful information about the abilities of patients and
residents to care for themselves. Additional commenters noted that the
item could feasibly be implemented across PAC providers and that its
kappa scores from the PAC PRD support its validity. Some commenters
noted a preference for MDS version of the Vision data element over the
form put forward in public comment, citing the widespread use of this
data element. A full report of the comments is available at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
Clinical and subject matter expert advisors working with our data
element contractor agreed that assessing vision impairment of patients
and residents with a standardized data element is feasible in PAC, that
it can reliably and accurately identify adults with objective impaired
vision, and that this information about impaired vision would be
clinically useful to identify needed accommodations and/or treatment
both within and across PAC settings.
Therefore, we are proposing the Vision data element from the MDS.
We are proposing to add the Vision data element to the OASIS, and that
HHAs would be required to report these data for the CY 2020 HH QRP at
the start of care between January 1, 2019 and June 30, 2019. Following
the initial two quarters of reporting for the CY 2020 HH QRP,
subsequent years for the HH QRP would be based on 12 months of such
data reporting beginning with July 1, 2019 through June 30, 2020 for
the CY 2021 HH QRP. The Vision data element would be assessed at start
of care only due to the relatively stable nature of vision impairment,
making it unlikely that this assessment would change between the start
and end of care. Assessment at the end of care would introduce
additional burden without improving the quality or usefulness of the
data, and we believe it is unnecessary.
We are inviting public comment on these proposals.
I. Proposals Relating to the Form, Manner, and Timing of Data
Submission Under the HH QRP
1. Proposed Start Date for Reporting Standardized Patient Assessment
Data by New HHAs
In the CY 2016 HH PPS final rule (80 FR 68624), we adopted timing
for new HHAs to begin reporting standardized quality data under the HH
QRP. We are proposing in this proposed rule that new HHAs will be
required to begin reporting standardized patient assessment data on the
same schedule. We are inviting public comment on this proposal.
2. Proposed Mechanism for Reporting Standardized Patient Assessment
Data Beginning With the CY 2019 HH QRP
Under our current policy, HHAs report data by completing applicable
sections of the OASIS, and submitting the OASIS to CMS through the
QIES, ASAP system. For more information on HH QRP reporting through the
QIES ASAP system, refer to https://www.qtso.com/index.php. In addition
to the data currently submitted on quality measures as previously
finalized and described in Table 49 of this proposed
[[Page 35372]]
rule, we are proposing that HHAs would be required to begin submitting
the proposed standardized patient assessment data for HHA Medicare and
Medicaid quality episodes that begin or end on or after January 1, 2019
using the OASIS, as described here.
Further, the proposed standardized patient assessment data elements
described above would be added to the OASIS, so the new reporting
requirements regarding those elements would result in no changes to the
mechanism by which HHAs report data under the HH QRP. All standardized
patient assessment data elements would be collected at SOC/ROC using
the OASIS item set, and all except the Brief Interview for Mental
Status (BIMS), Hearing, and Vision data elements are or would be
collected at discharge using the OASIS item set. Details on the
modifications and assessment collection for the OASIS for the proposed
standardized data are available at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HomeHealthQualityInits/HHQIQualityMeasures.html.
We are inviting public comments on these proposals.
3. Proposed Schedule for Reporting Standardized Patient Assessment Data
Beginning With the CY 2019 HH QRP
Starting with the CY 2019 HH QRP, we are proposing to apply our
current schedule for the reporting of measure data to the reporting of
standardized patient assessment data. Under that policy, except for the
first program year for which a measure is adopted, HHAs must report
data on measures for HHA Medicare and Medicaid quality episodes that
occur during the 12-month period (between July 1 and June 30) that
applies to the program year. For the first program year for which a
measure is adopted, HHAs are only required to report data on HHA
Medicare and Medicaid quality episodes that begin on or after January 1
and end up to and including June 30 of the calendar year that applies
to that program year. For example, for the CY 2019 HH QRP, data on
measures adopted for earlier program years must be reported for all HHA
Medicare and Medicaid quality episodes that begin on or after July 1,
2017 and end on or before June 30, 2018. However, data on new measures
adopted for the first time for the CY 2019 HH QRP program year must
only be reported for HHA Medicare and Medicaid quality episodes that
begin or end during the first two quarters of CY 2018. Tables 49 and 50
illustrate this policy.
Table 49--Summary Illustration of Initial Reporting for Newly Adopted
Measures and Standardized Patient Assessment Data Reporting Using CY Q1
and Q2 Data for the HH QRP *:
------------------------------------------------------------------------
Proposed data submission
Proposed data collection/submission deadlines beginning with CY
reporting period * 2019 HH QRP *
------------------------------------------------------------------------
January 1, 2018-June 30, 2018.......... July 31, 2018.
------------------------------------------------------------------------
\*\We note that submission of the OASIS must also adhere to the HH PPS
deadlines.
[supcaret] The term ``CY 2019 HH QRP'' means the calendar year for which
the HH QRP requirements applicable to that calendar year must be met
in order for a HHA to avoid a two percentage point reduction to its
market basket percentage when calculating the payment rates applicable
to it for that calendar year.
Table 50--Summary Illustration of OASIS 12 Month Data Reporting for
Measures and Standardized Patient Assessment Data Reporting for the HH
QRP *
------------------------------------------------------------------------
Proposed data submission
Proposed data collection/submission deadlines beginning with CY
reporting period * 2020 HH QRP * [caret]
------------------------------------------------------------------------
July 1, 2018--June 30, 2019............ July 31, 2019.
------------------------------------------------------------------------
\*\ We note that submission of the OASIS must also adhere to the HH PPS
deadlines.
[supcaret] The term ``CY 2020 HH QRP'' means the calendar year for which
the HH QRP requirements applicable to that calendar year must be met
in order for a HHA to avoid a two percentage point reduction to its
market basket percentage when calculating the payment rates applicable
to it for that calendar year.
We are inviting comment on our proposal to extend our current
policy governing the schedule for reporting the quality measure data to
the reporting of standardized patient assessment data for the HH QRP
beginning with the CY 2019 HH QRP.
4. Proposed Schedule for Reporting the Proposed Quality Measures
Beginning With the CY 2020 HH QRP
As discussed in section V.I. of this proposed rule, we are
proposing to adopt three quality measures beginning with the CY 2020 HH
QRP: Changes in Skin Integrity Post-Acute Care: Pressure Ulcer/Injury;
Application of The Percent of Residents Experiencing One or More Falls
with Major Injury (NQF # 0674); and Application of Percent of Long-Term
Care Hospital Patients with an Admission and Discharge Functional
Assessment and a Care Plan That Addresses Function (NQF #2631). We are
proposing that HHAs would report data on these measures using OASIS
reporting that is submitted through the QIES ASAP system. More
information on OASIS reporting using the QIES ASAP system is located at
https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/OASIS/DataSpecifications.html.
For the CY 2020 HH QRP, HHAs would be required to report these data
for HHA Medicare and Medicaid quality episodes that begin or end during
the period from January 1, 2019 to June 30, 2019. Beginning with the CY
2021 HH QRP, HHAs would be required to submit data for the entire 12-
month period from July 1 to June 30. Further, for the purposes of
measure calculation, our policy was established in the CY 2017 HH PPS
final rule (81 FR 76702) that data are utilized using calendar year
timeframes with review and correction periods.
We are inviting public comment on this proposal.
5. Input Sought for Data Reporting Related to Assessment Based Measures
Through various means of public input, including through previous
rules, public comment on measures, and the MAP, we have received input
suggesting that we expand the population for quality measurement to
include all patients regardless of payer. Approximately 75 percent of
home health expenditures in 2014 were made
[[Page 35373]]
by either Medicare or Medicaid and currently both Medicare and Medicaid
collect and report data for OASIS. We believe that expanding the
patient population for which OASIS collects data will allow us to
ensure data that is representative of quality provided to all patients
in the HHA setting and therefore allow us to better determine whether
HH Medicare beneficiaries receive the same quality of care that other
patients receive. We also appreciate that collecting quality data on
all patients regardless of payer source may create additional burden.
However, we also received input that the effort to separate out
Medicare and Medicaid beneficiaries, who are currently reported through
OASIS, from other patients creates clinical and work flow implications
with an associated burden too, and we further appreciate that it is
common practice for HHAs to collect OASIS data on all patients,
regardless of payer source. Thus, we are seeking input on whether we
should require quality data reporting on all HH patients, regardless of
payer, where feasible--noting that because Medicare Part A claims data
are submitted only with respect to Medicare beneficiaries, claims-based
measures rates would continue to be calculated only for Medicare
beneficiaries.
We are inviting public comments on this topic.
J. Other Proposals for the CY 2019 HH QRP and Subsequent Years
1. Proposal To Apply the HH QRP Data Completion Thresholds to the
Submission of Standardized Patient Assessment Data Beginning With the
CY 2019 HH QRP
In the CY 2016 HH PPS final rule (80 FR 68703 through 68705), we
defined the pay-for-reporting performance system model that could
accurately measure the level of an HHA's submission of OASIS data 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. EOC assessments comprise the Discharge from Agency, Death
at Home and Transfer to an Inpatient Facility time points. For further
information on successful submission of OASIS assessments, types of
assessments submitted by an HHA that fit the definition of a quality
assessment, defining the ``Quality Assessments Only'' (QAO) formula,
and implementing a pay-for-reporting performance requirement over a 3-
year period, please see the CY 2016 HH PPS final rule (80 FR 68704 to
68705).
Additionally, we finalized the pay-for-reporting threshold
requirements in the CY 2016 HH PPS rule. We finalized a policy through
which HHAs must score at least 70 percent on the QAO metric of pay-for-
reporting performance requirement for CY 2017 (reporting period July 1,
2015 to June 30, 2016), 80 percent for CY 2018 (reporting period July
1, 2016 to June 30, 2017) and 90 percent for CY 2019 (reporting period
July 1, 2017 to June 30, 2018). An HHA that does not meet this
requirement for a calendar year will be subject to a two percentage
point reduction to the market basket percentage increase that would
otherwise apply for that calendar year. We are now proposing to apply
the threshold requirements established in the CY 2016 HH PPS rule to
the submission of standardized patient assessment data beginning with
the CY 2019 HH QRP.
We are inviting public comment on our proposal to extend our
current HH QRP data completion requirements to the submission of
standardized patient assessment data.
2. Proposal for the HH QRP Submission Exception and Extension
Requirements
Our experience with other QRPs has shown that there are times when
providers are unable to submit quality data due to extraordinary
circumstances beyond their control (for example, natural, or man-made
disasters). Other extenuating circumstances are reviewed on a case-by-
case basis. We propose to define a ``disaster'' as any natural or man-
made catastrophe which causes damages of sufficient severity and
magnitude to partially or completely destroy or delay access to medical
records and associated documentation. Natural disasters could include
events such as hurricanes, tornadoes, earthquakes, volcanic eruptions,
fires, mudslides, snowstorms, and tsunamis. Man-made disasters could
include such events as terrorist attacks, bombings, floods caused by
man-made actions, civil disorders, and explosions. A disaster may be
widespread and impact multiple structures or be isolated and impact a
single site only.
In certain instances of either natural or man-made disasters, an
HHA may have the ability to conduct a full patient assessment, and
record and save the associated data either during or before the
occurrence of the extraordinary event. In this case, the extraordinary
event has not caused the agency's data files to be destroyed, but it
could hinder the HHA's ability to meet the QRP's data submission
deadlines. In this scenario, the HHA would potentially have the ability
to report the data at a later date, after the emergency has passed. In
such cases, a temporary extension of the deadlines for reporting might
be appropriate.
In other circumstances of natural or man-made disaster, an HHA may
not have had the ability to conduct a full patient assessment, or to
record and save the associated data before the occurrence of the
extraordinary event. In such a scenario, the agency may not have
complete data to submit to CMS. We believe that it may be appropriate,
in these situations, to grant a full exception to the reporting
requirements for a specific period of time.
We do not wish to penalize HHAs in these circumstances or to unduly
increase their burden during these times. Therefore, we propose a
process for HHAs to request and for us to grant exceptions and
extensions for the reporting requirements of the HH QRP for one or more
quarters, beginning with the CY 2019 HH QRP, when there are certain
extraordinary circumstances beyond the control of the HHA. When an
exception or extension is granted, we would not reduce the HHA's PPS
payment for failure to comply with the requirements of the HH QRP.
We propose that if an HHA seeks to request an exception or
extension for the HH QRP, the HHA should request an exception or
extension within 90 days of the date that the extraordinary
circumstances occurred. The HHA may request an exception or extension
for one or more quarters by submitting a written request to CMS that
contains the information noted below, via email to the HHA Exception
and Extension mailbox at HHAPureConsiderations@cms.hhs.gov. Requests
sent to CMS through any other channel would not be considered as valid
requests for an exception or extension from the HH QRP's reporting
requirements for any payment determination.
The subject of the email must read ``HH QRP Exception or Extension
Request'' and the email must contain the following information:
HHA CCN;
HHA name;
CEO or CEO-designated personnel contact information
including name, telephone number, email address, and mailing address
(the address must be a physical address, not a post office box);
HHA's reason for requesting an exception or extension;
Evidence of the impact of extraordinary circumstances,
including
[[Page 35374]]
but not limited to photographs, newspaper and other media articles; and
A date when the HHA believes it will be able to again
submit HH QRP data and a justification for the proposed date.
We propose that exception and extension requests be signed by the
HHA's CEO or CEO-designated personnel, and that if the CEO designates
an individual to sign the request, the CEO-designated individual has
the appropriate authority to submit such a request on behalf of the
HHA. Following receipt of the email, we would: (1) Provide a written
acknowledgement, using the contact information provided in the email,
to the CEO or CEO-designated contact notifying them that the request
has been received; and (2) provide a formal response to the CEO or any
CEO-designated HHA personnel, using the contact information provided in
the email, indicating our decision.
This proposal does not preclude us from granting exceptions or
extensions to HHAs that have not requested them when we determine that
an extraordinary circumstance, such as an act of nature, affects an
entire region or locale. If we make the determination to grant an
exception or extension to all HHAs in a region or locale, we propose to
communicate this decision through routine communication channels to
HHAs and vendors, including, but not limited to, issuing memos, emails,
and notices on our HH QRP Web site once it is available at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HomeHealthQualityInits/HomeHealthQualityReporting-Reconsideration-and-Exception-and-Extension.html.
We also propose that we may grant an exception or extension to HHAs
if we determine that a systemic problem with one of our data collection
systems directly affected the ability of the HHA to submit data.
Because we do not anticipate that these types of systemic errors will
happen often, we do not anticipate granting an exception or extension
on this basis frequently.
If an HHA is granted an exception, we would not require that the
HHA submit any measure data for the period of time specified in the
exception request decision. If we grant an extension to the original
submission deadline, the HHA would still remain responsible for
submitting quality data collected during the timeframe in question,
although we would specify a revised deadline by which the HHA must
submit this quality data.
We also propose that any exception or extension requests submitted
for purposes of the HH QRP would apply to that program only, and not to
any other program we administer for HHAs such as survey and
certification. OASIS requirements, including electronic submission,
during Declared Public Health Emergencies can be found at FAQs I-5, I-
6, I-7, I-8 at https://www.cms.gov/Medicare/Provider-Enrollment-and-Certification/SurveyCertEmergPrep/downloads/AllHazardsFAQs.pdf.
We intend to provide additional information pertaining to
exceptions and extensions for the HH QRP, including any additional
guidance, on the HH QRP Web site at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HomeHealthQualityInits/HomeHealthQualityReporting-Reconsideration-and-Exception-and-Extension.html.
We propose to add the HH QRP Submission Exception and Extension
Requirements at Sec. 484.250(d). We welcome comment on these
proposals.
3. Proposed HH QRP Submission Reconsideration and Appeals Procedures
The HH QRP reconsiderations and appeals process was finalized in
the CY 2013 HH PPS final rule (77 FR 67096) and has been used for prior
all periods cited in the previous rules, and utilized in the CY 2012 to
CY 2017 APU determinations. At the conclusion of the required quality
data reporting and submission period, we review the data received from
each HHA during that reporting period to determine if the HHA met the
HH QRP reporting requirements. HHAs that are found to be noncompliant
with the HH QRP reporting requirements for the applicable calendar year
will receive a 2 percentage point reduction to its market basket
percentage update for that calendar year.
Similar to our other quality reporting programs, such as the SNF
QRP, the LTCH QRP, and the IRF QRP, we include an opportunity for the
providers to request a reconsideration of our initial noncompliance
determination. To be consistent with other established quality
reporting programs and to provide an opportunity for HHAs to seek
reconsideration of our initial noncompliance decision, we are proposing
a process that enables an HHA to request reconsideration of our initial
non-compliance decision in the event that it believes that it was
incorrectly identified as being non-compliant with the HH QRP reporting
requirements for a particular calendar year. These proposals clarify
the HH QRP reconsiderations and appeals process that we have finalized
in previous rules.
For the CY 2019 HH QRP, and subsequent years, we are proposing that
a HHA would receive a notification of noncompliance if we determine
that the HHA did not submit data in accordance with the HH QRP
reporting requirements for the applicable CY. The purpose of this
notification is to put the HHA on notice that the HHA: (1) Has been
identified as being non-compliant with the HH QRP's reporting
requirements for the applicable calendar year; (2) will be scheduled to
receive a reduction in the amount of two percentage points to its
market basket percentage update for the applicable calendar year; (3)
may file a request for reconsideration if it believes that the finding
of noncompliance is erroneous, has submitted a request for an extension
or exception that has not yet been decided, or has been granted an
extension or exception; and (4) must follow a defined process on how to
file a request for reconsideration, which will be described in the
notification. We would only consider requests for reconsideration after
an HHA has been found to be noncompliant.
Notifications of noncompliance and any subsequent notifications
from CMS would be sent via a traceable delivery method, such as
certified U.S. mail or registered U.S. mail, or through other
practicable notification processes, such as a report from CMS to the
provider as a Certification and Survey Provider Enhanced Reports
(CASPER) report, that will provide information pertaining to their
compliance with the reporting requirements for the given reporting
cycle or from the Medicare Administrative Contractors assigned to
process the provider's claims. To obtain the compliance reports,
providers should access the CASPER Reporting Application. HHA providers
access the CASPER Reporting application via their CMS OASIS System
Welcome page by selecting the CASPER Reporting link. The ``CASPER
Reports'' link will connect an HHA to the QIES National System Login
page for CASPER Reporting.
We propose to disseminate communications regarding the availability
of compliance reports through routine channels to HHAs and vendors,
including, but not limited to issuing memos, emails, Medicare Learning
Network (MLN) announcements, and notices on our HH QRP Web site once it
is available at https://www.cms.gov/Medicare/Quality-Initiatives-
Patient-Assessment-Instruments/HomeHealthQualityInits/
[[Page 35375]]
HomeHealthQualityReporting-Reconsideration-and-Exception-and-
Extension.html.
An HHA would have 30 days from the date of the letter of
noncompliance to submit to us a request for reconsideration. This
proposed time frame allows us to balance our desire to ensure that HHA
s have the opportunity to request reconsideration with our need to
complete the process and provide HHAs with our reconsideration decision
in a timely manner. We are proposing that an HHA may withdraw its
request at any time and may file an updated request within the proposed
30-day deadline. We are also proposing that, in very limited
circumstances, we may grant a request by an HHA to extend the proposed
deadline for reconsideration requests. It would be the responsibility
of an HHA to request an extension and demonstrate that extenuating
circumstances existed that prevented the filing of the reconsideration
request by the proposed deadline.
We also are proposing that as part of the HHA's request for
reconsideration, the HHA would be required to submit all supporting
documentation and evidence demonstrating full compliance with all HH
QRP reporting requirements for the applicable calendar year, that the
HHA has requested an extension or exception for which a decision has
not yet been made, that the HHA has been granted an extension or
exception, or has experienced an extenuating circumstance as defined in
section V.I.2 of this rule but failed to file a timely request of
exception. We propose that we would not review any reconsideration
request that fails to provide the necessary documentation and evidence
along with the request.
The documentation and evidence may include copies of any
communications that demonstrate the HHA's compliance with the HH QRP,
as well as any other records that support the HHA's rationale for
seeking reconsideration, but should not include any protected health
information (PHI). We intend to provide a sample list of acceptable
supporting documentation and evidence, as well as instructions for HHAs
on how to retrieve copies of the data submitted to CMS for the
appropriate program year in the future on our HH QRP Web site at
https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HomeHealthQualityInits/HomeHealthQualityReporting-Reconsideration-and-Exception-and-Extension.html.
We are proposing that an HHA wishing to request a reconsideration
of our initial noncompliance determination would be required to do so
by submitting an email to the following email address:
HHAPureConsiderations@cms.hhs.gov. Any request for reconsideration
submitted to us by an HHA would be required to follow the guidelines
outlined on our HH QRP Web site once it is available at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HomeHealthQualityInits/HomeHealthQualityReporting-Reconsideration-and-Exception-and-Extension.html.
All emails must contain a subject line that reads ``HH QRP
Reconsideration Request.'' Electronic email submission is the only form
of reconsideration request submission that will be accepted by us. Any
reconsideration requests communicated through another channel
including, but not limited to, U.S. Postal Service or phone, will not
be considered as a valid reconsideration request.
We are proposing that a reconsideration request include the
following information:
HHA CMS Certification Number (CCN);
HHA Business Name;
HHA Business Address;
The CEO contact information including name, email address,
telephone number and physical mailing address; or The CEO-designated
representative contact information including name, title, email
address, telephone number and physical mailing address; and
CMS identified reason(s) for noncompliance from the non-
compliance notification; and
The reason(s) for requesting reconsideration.
The request for reconsideration must be accompanied by supporting
documentation demonstrating compliance. Following receipt of a request
for reconsideration, we would provide an email acknowledgment, using
the contact information provided in the reconsideration request, to the
CEO or CEO-designated representative that the request has been
received. Once we have reached a decision regarding the reconsideration
request, an email would be sent to the HHA CEO or CEO designated
representative, using the contact information provided in the
reconsideration request, notifying the HHA of our decision.
We also propose that the notifications of our decision regarding
reconsideration requests may be made available through a traceable
delivery method, such as certified U.S. mail or registered U.S. mail or
through the use of CASPER reports. If the HHA is dissatisfied with the
decision rendered at the reconsideration level, the HHA may appeal the
decision to the PRRB under 42 CFR 405.1835. We believe this proposed
process is more efficient and less costly for CMS and for HHAs because
it decreases the number of PRRB appeals by resolving issues earlier in
the process. Additional information about the reconsideration process
including details for submitting a reconsideration request will be
posted in the future to our HH QRP Web site at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HomeHealthQualityInits/HomeHealthQualityReporting-Reconsideration-and-Exception-and-Extension.html.
We propose to add the HH QRP Submission Reconsideration and Appeals
Procedures at Sec. 484.250(e) and (f). We welcome comment on these
proposals.
K. Proposals and Policies Regarding Public Display of Quality Measure
Data for the HH QRP
Our home health regulations, at Sec. 484.250(a), require HHAs to
submit OASIS assessments and Home Health Care Consumer Assessment of
Healthcare Providers and Systems Survey[supreg] (HHCAHPS) data to meet
the quality reporting requirements of section 1895(b)(3)(B)(v) of the
Act. Section 1899B(g) of the Act requires that data and information of
provider performance on quality measures and resource use and other
measures be made publicly available beginning not later than two years
after the applicable specified ``application date''. In addition,
sections 1895(b)(3)(B)(v)(III) requires the Secretary to establish
procedures for making data submitted under section 1895(b)(3)(B)(v)(II)
available to the public, and section 1899B(g)(1) of the Act requires
the Secretary to do the same with respect to HHA performance on
measures specified under sections 1899B(c)(1) and (d)(1) of the Act.
Section 1895(b)(3)(B)(v)(III) of the Act requires that the public
reporting procedures for data submitted under subclause (II) ensure
that a HHA has the opportunity to review the data that is to be made
public with respect to it prior to such data being made public. Under
section 1899B(g)(2) of the Act, the public reporting procedures for
performance on measures under sections 1899B(c)(1) and (d)(1) of the
Act must ensure, including through a process consistent with the
process applied under section 1886(b)(3)(B)(viii)(VII) of the Act,
(which refers to public display and review requirements in the Hospital
Inpatient Quality Reporting (Hospital IQR) Program), that a HHA has the
[[Page 35376]]
opportunity to review and submit corrections to its data and
information that are to be made public for the agency prior to such
data being made public. We recognize that public reporting of quality
data is a vital component of a robust quality reporting program and are
fully committed to ensuring that the data made available to the public
are meaningful. Further, we agree that measures for comparing
performance across home health agencies should be constructed from data
collected in a standardized and uniform manner.
In the CY 2017 HH PPS final rule (81 FR 76785 through 76786), we
finalized procedures that allow individual HHAs to review and correct
their data and information on IMPACT Act measures that are to be made
public before those measure data are made public. Information on how to
review and correct data on IMPACT Act measures that are to be made
public before those measure data are made public can be found on the HH
QRP Web site at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HomeHealthQualityInits/Home-Health-Quality-Reporting-Requirements.html. We are not proposing any changes
to these policies.
In this CY 2018 HH PPS proposed rule, pending the availability of
data, we are proposing to publicly report data beginning in CY 2019 for
the following two assessment-based measures: (1) Percent of Patients or
Residents with Pressure Ulcers that are New or Worsened (NQF #0678);
and (2) Drug Regimen Review Conducted with Follow-Up for Identified
Issues-PAC HH QRP. Data collection for these two assessment-based
measures began on OASIS on January 1, 2017. We propose to publicly
report data beginning in CY 2019 for these assessment-based measures
based on four rolling quarters of data, beginning with data collected
for discharges in 2017.
In addition, we are proposing to publicly report data beginning in
CY 2019 for the following 3 claims-based measures: (1) Medicare
Spending Per Beneficiary-PAC HH QRP; (2) Discharge to Community-PAC HH
QRP; and (3) Potentially Preventable 30-Day Post-Discharge Readmission
Measure for HH QRP. As adopted in the CY 2017 HH PPS final rule (81 FR
43773), for the MSPB-PAC HH QRP measure, we will use one year of claims
data beginning with CY 2016 claims data to inform confidential feedback
reports for HHAs, and CY 2017 claims data for public reporting for the
HH QRP. For the Discharge to Community--PAC HH QRP measure we will use
2 years of claims data, beginning with CYs 2015 and 2016 claims data to
inform confidential feedback and CYs 2016 and 2017 claims data for
public reporting. For the Potentially Preventable 30-Day Post-Discharge
Readmission Measure for HH QRP, we will use 3 years of claims data,
beginning with CY 2014, 2015 and 2016 claims data to inform
confidential feedback reports for HHAs, and CY 2015, 2016 and 2017
claims data for public reporting.
Finally, we are proposing to assign HHAs with fewer than 20
eligible cases during a performance period to a separate category:
``The number of patient episodes for this measure is too small to
report,'' \229\ to ensure the statistical reliability of the measures.
If a HHA had fewer than 20 eligible cases, the HHA's performance would
not be publicly reported for the measure for that performance period.
---------------------------------------------------------------------------
\229\ This language is currently available as Footnote #4 on
Home Health Compare (https://www.medicare.gov/HomeHealthCompare/Data/Footnotes.html).
Table 51--Summary of Proposed New HH QRP Measures for CY 2019 Public
Display
------------------------------------------------------------------------
-------------------------------------------------------------------------
Proposed Measures:
Percent of Residents or Patients with Pressure Ulcers that Are New
or Worsened (Short Stay) (NQF #0678).
Drug Regimen Review Conducted with Follow-Up for Identified Issues-
PAC HH QRP.
Potentially Preventable 30-Day Post-Discharge Readmission Measure
for HH QRP.
Discharge to Community--(PAC) HH QRP.
Medicare Spending Per Beneficiary (PAC) HH QRP.
------------------------------------------------------------------------
We are inviting public comment on these proposals for the public
display of quality data, as described in this proposed rule.
L. Proposed Mechanism for Providing Confidential Feedback Reports to
HHAs
Section 1899B(f) of the Act requires the Secretary to provide
confidential feedback reports to post-acute care (PAC) providers on
their performance on the measures specified under subsections (c)(1)
and (d)(1) of section 1899B of the Act, beginning one year after the
specified application date that applies to such measures and PAC
providers. In the CY 2017 HH PPS final rule (81 FR 76702), we finalized
processes to allow HH providers the opportunity to review their data
and information using confidential feedback reports that will enable
HHAs to review their performance on the measures required under the HH
QRP. Information on how to obtain these and other reports available to
the HH QRP can be found at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HomeHealthQualityInits/Home-Health-Quality-Reporting-Requirements.html. We are not proposing any
changes to this policy.
M. Home Health Care CAHPS[supreg] Survey (HHCAHPS)
In the CY 2017 HH PPS final rule (81 FR 76787), we stated that the
home health quality measures reporting requirements for Medicare-
certified agencies includes the Home Health Care CAHPS[supreg]
(HHCAHPS) Survey for the Home Health Quality Reporting Program and
along with OASIS measures, HHCAHPS participation is required for the
Annual Payment Update (APU). In the CY 2017 HH PPS final rule, we
finalized the reporting requirements and the data submission dates for
the CY 2017-CY 2020 APU periods. We proposed to continue the HHCAHPS
requirements in future years for the continuous monthly data collection
and quarterly data submission of HHCAHPS data.
1. Background and Description of HHCAHPS
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. For more details about the HH CAHPS Survey please see 81 FR 76787
through 76788.
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 are required to
provide a monthly list of their HHCAHPS-eligible patients to their
respective HHCAHPS
[[Page 35377]]
survey vendors. Home health agencies are not allowed to influence their
patients about how the HHCAHPS survey.
As previously required, new HHCAHPS survey vendors are required to
attend Introduction training, and current HHCAHPS vendors are required
to attend Update training conducted by CMS and the HHCAHPS Survey
Coordination Team. New HHCAHPS vendors need to pass a post-training
certification test. We have approximately 30 approved HHCAHPS survey
vendors. The list of approved HHCAHPS survey vendors is available at
https://homehealthcahps.org.
2. HHCAHPS Oversight Activities
We stated in prior final rules that all approved HHCAHPS survey
vendors are required to participate in HHCAHPS oversight activities to
ensure compliance with HHCAHPS protocols, guidelines, and survey
requirements. The purpose of the oversight activities is to ensure that
approved HHCAHPS survey vendors follow the HHCAHPS Protocols and
Guidelines Manual.
In the CY 2013 HH PPS final rule (77 FR 67094, 67164), we codified
the current guideline that all approved HHCAHPS survey vendors fully
comply with all HHCAHPS oversight activities. We included this survey
requirement at Sec. 484.250(c)(3).
For the sake of continuity with this proposed rule, we are
reiterating the HHCAHPS requirements for CY 2019, because participation
occurs in the period of the publication of the proposed and final rules
for CY 2018. We are additionally presenting the HHCAHPS requirements
for CY 2020 for the sake of continuity. We are proposing the HHCAHPS
requirements for the CY 2021 Annual Payment Update.
3. HHCAHPS Requirements for the CY 2019 HH QRP
In the CY 2017 HH PPS final rule, we finalized the requirements for
the CY 2019 HH QRP. For the CY 2019 HH QRP, we require continuous
monthly HHCAHPS data collection and reporting for four quarters. The
data collection period for the CY 2018 HH QRP includes the second
quarter 2017 through the first quarter 2018 (the months of April 2017
through March 2018). HHAs will be required to submit their HHCAHPS data
files to the HHCAHPS Data Center for the second quarter 2017 by 11:59
p.m., eastern daylight time (e.d.t.) on October 19, 2017; for the third
quarter 2017 by 11:59 p.m., eastern standard time (e.s.t.) on January
18, 2018; for the fourth quarter 2017 by 11:59 p.m., e.d.t. on April
19, 2018; and for the first quarter 2018 by 11:59 p.m., e.d.t. on July
19, 2018. These deadlines are firm; no exceptions will be permitted.
For more details on the CY 2019 HH QRP, we refer readers to 81 FR
76789.
4. HHCAHPS Requirements for the CY 2020 HH QRP
In the CY 2017 HH PPS final rule, we finalized the requirements for
the CY 2020 HH QRP. For the CY 2020 HH QRP, we require continued
monthly HHCAHPS data collection and reporting for four quarters. The
data collection period for the CY 2020 HH QRP includes the second
quarter 2018 through the first quarter 2019 (the months of April 2018
through March 2019). HHAs will be required to submit their HHCAHPS data
files to the HHCAHPS Data Center for the second quarter 2018 by 11:59
p.m., e.d.t. on October 18, 2018; for the third quarter 2018 by 11:59
p.m., e.s.t. on January 17, 2019; for the fourth quarter 2018 by 11:59
p.m., e.d.t. on April 18, 2019; and for the first quarter 2019 by 11:59
p.m., e.d.t. on July 18, 2019. These deadlines are firm; no exceptions
will be permitted.
For more details about the CY 2020 HH QRP, we refer readers to 81
FR 76789.
5. HHCAHPS Requirements for the CY 2021 HH QRP
For the CY 2021 HH QRP, we propose to require the continued monthly
HHCAHPS data collection and reporting for four quarters. The data
collection period for the CY 2021 HH QRP includes the second quarter
2019 through the first quarter 2020 (the months of April 2019 through
March 2020). HHAs will be required to submit their HHCAHPS data files
to the HHCAHPS Data Center for the second quarter 2019 by 11:59 p.m.,
e.d.t. on October 17, 2019; for the third quarter 2019 by 11:59 p.m.,
e.s.t. on January 16, 2020; for the fourth quarter 2019 by 11:59 p.m.,
e.d.t. on April 16, 2020; and for the first quarter 2020 by 11:59 p.m.,
e.d.t. on July 16, 2020. These deadlines are firm; no exceptions will
be permitted.
For the CY 2021 HH QRP, we propose to require that all HHAs with
fewer than 60 HHCAHPS-eligible unduplicated or unique patients in the
period of April 1, 2018 through March 31, 2019 are exempt from the
HHCAHPS data collection and submission requirements for the CY 2021 HH
QRP, upon completion of the CY 2021 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, 2018 through March 31, 2019 are
proposed to be required to submit their patient counts on the CY 2021
HHCAHPS Participation Exemption Request form posted on https://homehealthcahps.org from April 1, 2019 to 11:59 p.m., e.d.t. to March
31, 2020. This deadline is firm, as are all of the quarterly data
submission deadlines for the HHAs that participate in HHCAHPS.
We propose to automatically exempt HHAs receiving Medicare
certification on or after the start of the period in which HHAs do
their patient count for a particular year's HHCAHPS data submission
from the HHCAHPS reporting requirement for the year. We propose that
HHAs receiving Medicare-certification on or after April 1, 2019 would
be exempt from the HHCAHPS reporting requirement for the CY 2021 HH
QRP. As we have finalized in previous years, we propose that these
newly-certified HHAs do not need to complete the HHCAHPS Participation
Exemption Request Form for the CY 2021 HH QRP.
6. HHCAHPS Reconsiderations and Appeals Process
As finalized in previous rules, we propose that HHAs should monitor
their respective HHCAHPS survey vendors to ensure that vendors submit
their HHCAHPS data on time, by accessing their HHCAHPS Data Submission
Reports on https://homehealthcahps.org. This helps HHAs ensure that
their data are submitted in the proper format for data processing to
the HHCAHPS Data Center.
We propose to continue HHCAHPS oversight activities as finalized in
the previous rules. In the CY 2013 HH PPS final rule (77 FR 67068,
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).
For further information on the HH QRP reconsiderations and appeals
process, please see Section V.J.3. of this proposed rule.
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 for future HH QRP years. We again strongly
encourage HHAs to keep up-to-date about the HHCAHPS by regularly
viewing the official Web site for the
[[Page 35378]]
HHCAHPS at https://homehealthcahps.org. HHAs can also send an email to
the HHCAHPS Survey Coordination Team at hhcahps@rti.org or to CMS at
homehealthcahps@cms.hhs.gov, or telephone toll-free (1-866-354-0985)
for more information about the HHCAHPS Survey.
VI. Request for Information on CMS Flexibilities and Efficiencies
CMS is committed to transforming the health care delivery system--
and the Medicare program--by putting an additional focus on patient-
centered care and working with providers, physicians, and patients to
improve outcomes. We seek to reduce burdens for hospitals, physicians,
and patients, improve the quality of care, decrease costs, and ensure
that patients and their providers and physicians are making the best
health care choices possible. These are the reasons we are including
this Request for Information in this proposed rule.
As we work to maintain flexibility and efficiency throughout the
Medicare program, we would like to start a national conversation about
improvements that can be made to the health care delivery system that
reduce unnecessary burdens for clinicians, other providers, and
patients and their families. We aim to increase quality of care, lower
costs improve program integrity, and make the health care system more
effective, simple and accessible.
We would like to take this opportunity to invite the public to
submit their ideas for regulatory, subregulatory, policy, practice, and
procedural changes to better accomplish these goals. Ideas could
include payment system redesign, elimination or streamlining of
reporting, monitoring and documentation requirements, aligning Medicare
requirements and processes with those from Medicaid and other payers,
operational flexibility, feedback mechanisms and data sharing that
would enhance patient care, support of the physician-patient
relationship in care delivery, and facilitation of individual
preferences. Responses to this Request for Information could also
include recommendations regarding when and how CMS issues regulations
and policies and how CMS can simplify rules and policies for
beneficiaries, clinicians, physicians, providers, and suppliers. Where
practicable, data and specific examples would be helpful. If the
proposals involve novel legal questions, analysis regarding CMS'
authority is welcome for CMS' consideration. We are particularly
interested in ideas for incentivizing organizations and the full range
of relevant professionals and paraprofessionals to provide screening,
assessment and evidence-based treatment for individuals with opioid use
disorder and other substance use disorders, including reimbursement
methodologies, care coordination, systems and services integration, use
of paraprofessionals including community paramedics and other
strategies. We are requesting commenters to provide clear and concise
proposals that include data and specific examples that could be
implemented within the law.
We note that this is a Request for Information only. Respondents
are encouraged to provide complete but concise responses. This Request
for Information is issued solely for information and planning purposes;
it does not constitute a Request for Proposal (RFP), applications,
proposal abstracts, or quotations. This Request for Information does
not commit the U.S. Government to contract for any supplies or services
or make a grant award. Further, CMS is not seeking proposals through
this Request for Information and will not accept unsolicited proposals.
Responders are advised that the U.S. Government will not pay for any
information or administrative costs incurred in response to this
Request for Information; all costs associated with responding to this
Request for Information will be solely at the interested party's
expense. We note that not responding to this Request for Information
does not preclude participation in any future procurement, if
conducted. It is the responsibility of the potential responders to
monitor this Request for Information announcement for additional
information pertaining to this request. In addition, we note that CMS
will not respond to questions about the policy issues raised in this
Request for Information. CMS will not respond to comment submissions in
response to this Request for Information in the FY 2018 HH PPS final
rule. Rather, CMS will actively consider all input as we develop future
regulatory proposals or future subregulatory policy guidance. CMS may
or may not choose to contact individual responders. Such communications
would be for the sole purpose of clarifying statements in the
responders' written responses. Contractor support personnel may be used
to review responses to this Request for Information. Responses to this
notice are not offers and cannot be accepted by the Government to form
a binding contract or issue a grant. Information obtained as a result
of this Request for Information may be used by the Government for
program planning on a nonattribution basis. Respondents should not
include any information that might be considered proprietary or
confidential. This Request for Information should not be construed as a
commitment or authorization to incur cost for which reimbursement would
be required or sought. All submissions become U.S. Government property
and will not be returned. CMS may publically post the public comments
received, or a summary of those public comments.
VII. Collection of Information Requirements
A. Statutory Requirement for Solicitation of Comments
Under the Paperwork Reduction Act of 1995 (PRA), we are required to
provide 60-day notice in the Federal Register and solicit public
comment before a collection of information requirement is submitted to
the OMB for review and approval. We note that we will submit a revised
information collection request (OMB control number 0938-1279) to OMB
for review. This will also extend the information collection request
which expires December 30, 2019. To fairly evaluate whether an
information collection should be approved by OMB, section 3506(c)(2)(A)
of the PRA requires that we solicit comment on the following issues:
The need for the information collection and its usefulness
in carrying out the proper functions of our agency.
The accuracy of our estimate of the information collection
burden.
The quality, utility, and clarity of the information to be
collected.
Recommendations to minimize the information collection
burden on the affected public, including automated collection
techniques.
This proposed rule makes reference to associated information
collections that are not discussed in the regulation text contained in
this document.
B. Collection of Information Requirements for the HH QRP
We believe that the burden associated with the HH QRP is the time
and effort associated with data collection and reporting. As of April
1, 2017, there are approximately 12,149 HHAs currently reporting
quality data to CMS. For the purposes of calculating the costs
associated with the collection of information requirements, we obtained
mean hourly wages for these staff from the U.S. Bureau of Labor
Statistics' May 2016 National Occupational
[[Page 35379]]
Employment and Wage Estimates (https://www.bls.gov/oes/current/oes_nat.htm). To account for overhead and fringe benefits (100
percent), we have doubled the hourly wage. These amounts are detailed
in Table 52.
Table 52--U.S. Bureau of Labor Statistics' May 2016 National Occupational Employment and Wage Estimates
----------------------------------------------------------------------------------------------------------------
Fringe Adjusted
Occupation title Occupation Mean hourly benefit hourly wage
code wage ($/hr) (100%) ($/hr) ($/hr)
----------------------------------------------------------------------------------------------------------------
Registered Nurse (RN)........................... 29-1141 $34.70 $34.70 $69.40
Physical therapists HHAs........................ 29-1123 46.42 46.42 92.84
Speech-Language Pathologists (SLP).............. 29-1127 37.60 37.60 75.20
Occupational Therapists (OT).................... 29-1122 40.25 40.25 80.50
----------------------------------------------------------------------------------------------------------------
The OASIS changes proposed in section V.D of this proposed rule
will result in the removal of 75 data elements from the OASIS at the
time point of Start of Care (SOC), 75 data elements at the time point
of Resumption of Care (ROC), 20 data elements at the time point of
Follow-up (FU), 42 data elements at the time point of Transfer to an
Inpatient Facility (TOC), 1 data element at the time point of Death at
Home (Death), and 34 data elements at the time point of Discharge from
Agency (Discharge). These data items will not be used in the
calculation of quality measures adopted in the HH QRP nor are they used
for previously established purposes that are non-related to our HH QRP.
More detail on these OASIS data elements proposed for removal can be
found at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HomeHealthQualityInits/OASIS-Data-Sets.html.
Section V.F.1 of this rule proposes to adopt a new pressure ulcer
measure to replace the current pressure ulcer measure that has been
specified under section 1899B(c)(1)(B) of the Act beginning with the CY
2020 HH QRP. The proposed replacement measure is entitled, ``Changes in
Skin Integrity Post-Acute Care: Pressure Ulcer/Injury.'' The new
measure will be calculated using data elements that are currently
collected and reported using the OASIS-C2 (version effective January 1,
2017). Adoption of the Changes in Skin Integrity Post-Acute Care:
Pressure Ulcer/Injury measure would result in the removal of item
M1313, related to pressure ulcer assessment that we believe is
duplicative and no longer necessary. Specifically, with adoption of
Changes in Skin Integrity Post-Acute Care: Pressure Ulcer/Injury
measure, we would remove 6 data elements at Discharge.
In sections V.F.2 of this proposed rule, we are proposing a new
quality measure to meet requirements of the IMPACT Act under section
1899B(c)(1)(A) of the Act beginning with the CY 2020 HH QRP titled
``Application of Percent of Long-Term Care Hospital Patients with an
Admission and Discharge Functional Assessment and a Care Plan That
Addresses Function (NQF #2631).'' Specifically, we are proposing to add
13 standardized patient assessment data elements at SOC, 13 data
elements at ROC, 15 standardized patient assessment data elements at
FU, and 13 standardized patient assessment data elements at Discharge.
In sections V.F.3 of this proposed rule, we are proposing a new
quality measure to meet requirements of the IMPACT Act under section
1899B(c)(1)(D) of the Act beginning with the CY 2020 HH QRP titled
``Application of Percent of Residents Experiencing One or More Falls
with Major Injury (NQF# 0674).'' The new measure will be calculated
using new standardized data elements added to the OASIS. Specifically,
we are proposing to add 4 data elements at TOC, 4 data elements at
Death, and 4 data elements at Discharge.
In sections V.H.2 and V.H.3 of this proposed rule, we are proposing
requirements related to the reporting of standardized patient
assessment data beginning with the CY 2019 HH QRP. We are proposing to
define the term ``standardized patient assessment data'' as patient
assessment questions and response options that are identical in all
four PAC assessment instruments, and to which identical standards and
definitions apply. The standardized patient assessment data is intended
to be shared electronically among PAC providers and will otherwise
enable the data to be comparable for various purposes, including the
development of cross-setting quality measures and to inform payment
models that take into account patient characteristics rather than
setting. Specifically, we are proposing to add 53 standardized patient
assessment data elements at SOC, 53 standardized patient assessment
data elements at ROC, and 36 standardized patient assessment data
elements at Discharge.
The OASIS instrument is used for both the HH QRP and the HH PPS. As
outlined in section III.E of this proposed rule, to calculate the case-
mix adjusted payment amount (specifically the functional level
assignment), we are proposing to add collection of two current OASIS-C2
items (10 data elements) at the FU time point:
M1033: Risk for Hospitalization (9 data elements)
M1800: Grooming (1 data element).
As outlined in section III.E of this proposed rule, OASIS
integumentary status items would not be needed in case-mix adjusting
the period payment; therefore, we are proposing to remove collection of
eight current OASIS-C2 items (19 data elements) at the FU time point:
M1311: Current Number of Unhealed Pressure Ulcers at Each
Stage (12 data elements)
M1322: Current Number of Stage 1 Pressure Ulcers (1 data
element)
M1324: Stage of Most Problematic Unhealed Pressure Ulcer that
is Stageable (1 data element)
M1330: Does this patient have a Stasis Ulcer? (1 data element)
M1332: Current Number of Stasis Ulcer(s) that are Observable
(1 data element)
M1334: Status of Most Problematic Stasis Ulcer that is
Observable (1 data element)
M1340: Does this patient have a Surgical Wound? (1 data
element)
M1342: Status of Most Problematic Surgical Wound that is
Observable (1 data element).
Therefore, we are proposing the net removal associated with the
HHGM of 9 data elements at FU.
In summary, there is a net reduction of 9 data elements at SOC, 9
data elements at ROC,14 data elements at FU
[[Page 35380]]
and 38 data elements at TOC. There is a net increase of 3 data elements
at Death and 13 data elements at Discharge.
Under section 1899B(m) of the Act, the Paperwork Reduction Act does
not apply to section 1899B, or to the sections of the OASIS that
require modification to achieve the standardization of patient
assessment data. We are, however, setting out the burden as a courtesy
to advise interested parties of the proposed actions' time and costs
and for reference in the regulatory impact analysis (RIA) section IX.
The requirement and burden will be submitted to OMB for review and
approval when the modifications to the OASIS have achieved
standardization and are no longer exempt from the requirements under
section 1899B(m) of the Act.
We assume that each data element requires 0.3 minutes of clinician
time to complete. Therefore, there is a reduction in clinician burden
per OASIS assessment of 2.7 minutes at SOC, 2.7 minutes at ROC, 4.2
minutes at FU and 11.4 minutes at TOC. There is an increase in
clinician burden per assessment of 0.9 minutes at Death and 3.9 minutes
at Discharge.
The OASIS is completed by RNs or PTs, or very occasionally by
occupational therapists (OT) or speech language pathologists (SLP/ST).
Data from 2016 show that the SOC/ROC OASIS is completed by RNs
(approximately 87 percent of the time), PTs (approximately 12.7 percent
of the time), and other therapists, including OTs and SLP/STs
(approximately 0.3 percent of the time). Based on this analysis we
estimated a weighted clinician average hourly wage of $72.40, inclusive
of fringe benefits, using the hourly wage data in Table 52. Individual
providers determine the staffing resources necessary.
Table 53 shows the total number of assessments submitted in CY 2016
and estimated burden at each time point.
Table 53--CY 2016 OASIS Submissions and Estimated Burden, by Time Point
------------------------------------------------------------------------
CY 2016
Time point assessments Estimated burden
completed ($)
------------------------------------------------------------------------
Start of Care..................... 6,261,934 -$20,401,380.97
Resumption of Care................ 1,049,247 -3,418,446.73
Follow-up......................... 3,797,410 -19,245,273.88
Transfer to an inpatient facility. 1,892,099 -26,027,713.84
Death at Home..................... 41,128 44,665.01
Discharge from agency............. 5,120,124 24,095,303.54
-------------------------------------
Total......................... 18,161,942 -44,952,846.87
------------------------------------------------------------------------
* Estimated Burden ($) at each Time-Point = (# CY 2016 Assessments
Completed) x (clinician burden [min]/60) x ($72.40 [weighted clinician
average hourly wage]).
Based on the data in Table 53, for the 12,149 active Medicare-
certified HHAs in April 2017, we estimate the total average decrease in
cost associated with proposed changes to the HH QRP at $3,700,74 per
HHA annually, or $44,952,846.87 for all HHAs annually. This decrease in
burden will be accounted for in the information collection under OMB
control number 0938-1279.
C. Submission of PRA-Related Comments
We have submitted a copy of this proposed rule to OMB for its
review of the rule's information collection and recordkeeping
requirements. The requirements are not effective until they have been
approved by OMB.
We invite public comments on these information collection
requirements. If you wish to comment, please identify the rule (CMS-
1672-P) and, where applicable, the ICR's CFR citation, CMS ID number,
and OMB control number.
To obtain copies of a supporting statement and any related forms
for the proposed collection(s) summarized in this notice, you may make
your request using one of following:
1. Access CMS' Web site address at https://www.cms.gov/Regulations-and-Guidance/Legislation/PaperworkReductionActof1995/PRA-Listing.html.
2. Email your request, including your address, phone number, OMB
number, and CMS document identifier, to Paperwork@cms.hhs.gov.
3. Call the Reports Clearance Office at (410) 786-1326.
See this rule's DATES and ADDRESSES sections for the comment due
date and for additional instructions.
VIII. Response to Public Comments
Because of the large number of public comments we normally receive
on Federal Register documents, we are not able to acknowledge or
respond to them individually. We will consider all comments we receive
by the date and time specified in the DATES section of this preamble,
and, when we proceed with a subsequent document, we will respond to the
comments in the preamble to that document.
IX. 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) 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; (2) the prospective payment amount under the HH PPS
to be an appropriate unit of service based on the number, type, and
duration of visits provided within that unit; and (3) 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
[[Page 35381]]
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.
The HHVBP Model will apply a payment adjustment based on an HHA's
performance on quality measures to test the effects on quality and
costs of care.
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), the
Congressional Review Act (5 U.S.C. 804(2) and Executive Order 13771 on
Reducing Regulation and Controlling Regulatory Costs (January 30,
2017).
Executive Orders 12866 and 13563 direct agencies to assess all
costs and benefits of available regulatory alternatives and, if
regulation is necessary, to select regulatory approaches that maximize
net benefits (including potential economic, environmental, public
health and safety effects, distributive impacts, and equity).
Section 3(f) of Executive Order 12866 defines a ``significant
regulatory action'' as an action that is likely to result in a rule:
(1) Having an annual effect on the economy of $100 million or more in
any 1 year, or adversely and materially affecting a sector of the
economy, productivity, competition, jobs, the environment, public
health or safety, or state, local or tribal governments or communities
(also referred to as ``economically significant''); (2) creating a
serious inconsistency or otherwise interfering with an action taken or
planned by another agency; (3) materially altering the budgetary
impacts of entitlement grants, user fees, or loan programs or the
rights and obligations of recipients thereof; or (4) raising novel
legal or policy issues arising out of legal mandates, the President's
priorities, or the principles set forth in the Executive Order.
A regulatory impact analysis (RIA) must be prepared for major rules
with economically significant effects ($100 million or more in any 1
year). The net transfer impact related to the changes in payments under
the HH PPS for CY 2018 is estimated to be -$80 million (-0.4 percent).
The net transfer impact in CY 2019 related to the change in the unit of
payment under the proposed HHGM is estimated to be -$950 million (-4.3
percent) if the HHGM is implemented in a fully non-budget neutral
manner in CY 2019. The net transfer impact in CY 2019 related to the
change in the unit of payment under the proposed HHGM is estimated to
be -$480 million (-2.2 percent) if the HHGM is implemented in a
partially budget-neutral manner in CY 2019 with the removal of the HHGM
partial budget neutrality adjustment factor in CY 2020. The savings
impacts related to the HHVBP model as a whole are estimated at a total
projected 5-year gross savings of $378 million assuming a savings
estimate of a 6 percent annual reduction in hospitalizations and a 1.0
percent annual reduction in SNF admissions; the portion attributable to
this proposed rule is negligible. In the CY 2018 HH PPS proposed rule,
we have identified a reduction in our regulatory reporting burden of
$44,952,846.87. We estimate that this rulemaking is ``economically
significant'' as measured by the $100 million threshold, and hence also
a major rule under the Congressional Review Act. Accordingly, we have
prepared a Regulatory Impact Analysis that, to the best of our ability,
presents the costs and benefits of the rulemaking.
In addition, section 1102(b) of the Act requires us to prepare a
RIA if a rule may have a significant impact on the operations of a
substantial number of small rural hospitals. This analysis must conform
to the provisions of section 603 of RFA. For purposes of section
1102(b) of the Act, we define a small rural hospital as a hospital that
is located outside of a metropolitan statistical area and has fewer
than 100 beds. This proposed rule is applicable exclusively to HHAs.
Therefore, the Secretary has determined this rule would not have a
significant economic impact on the operations of small rural hospitals.
Section 202 of the Unfunded Mandates Reform Act of 1995 (UMRA) also
requires that agencies assess anticipated costs and benefits before
issuing any rule whose mandates require spending in any 1 year of $100
million in 1995 dollars, updated annually for inflation. In 2017, that
threshold is approximately $148 million. This proposed rule is not
anticipated to have an effect on State, local, or tribal governments,
in the aggregate, or on the private sector of $148 million or more.
If regulations impose administrative costs on private entities,
such as the time needed to read and interpret this proposed rule, we
should estimate the cost associated with regulatory review. Due to the
uncertainty involved with accurately quantifying the number of entities
that will review the rule, we assume that the total number of unique
commenters on last year's proposed rule will be the number of reviewers
of this proposed rule. We acknowledge that this assumption may
understate or overstate the costs of reviewing this rule. It is
possible that not all commenters reviewed last year's rule in detail,
and it is also possible that some reviewers chose not to comment on the
proposed rule. For these reasons we thought that the number of past
commenters would be a fair estimate of the number of reviewers of this
rule. We welcome any comments on the approach in estimating the number
of entities that will review this proposed rule.
We also recognize that different types of entities are in many
cases affected by mutually exclusive sections of this proposed rule,
and therefore for the purposes of our estimate we assume that each
reviewer reads approximately 50 percent of the rule. We seek comments
on this assumption.
Using the wage information from the BLS for medical and health
service managers (Code 11-9111), we estimate that the cost of reviewing
this rule is $105.16 per hour, including overhead and fringe benefits
(https://www.bls.gov/oes/2016/may/naics4_621100.htm). Assuming an
average reading speed, we estimate that it would take approximately 3.8
hours for the staff to review half of this proposed rule. For each HHA
that reviews the rule, the estimated cost is $399.61 (3.8 hours x
$105.16). Therefore, we estimate that the total cost of reviewing this
regulation is $33,966.85 ($399.61 x 85 reviewers).
[[Page 35382]]
1. HH PPS for CY 2018
The update set forth in this rule applies to Medicare payments
under HH PPS in CY 2018. Accordingly, the following analysis describes
the impact in CY 2018 only. We estimate that the net impact of the
policies in this rule is approximately $80 million in decreased
payments to HHAs in CY 2018. 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 2018 wage index and the recalibration of the
case-mix weights for 2018 is zero. The -$80 million impact reflects the
distributional effects of a 0.5 percent reduction in payments due to
the sunset of the rural add-on provision ($100 million decrease), a 1
percent home health payment update percentage ($190 million increase),
and a -0.97 percent adjustment to the national, standardized 60-day
episode payment rate to account for nominal case-mix growth for an
impact of -0.9 percent ($170 million decrease). The $80 million in
decreased payments is reflected in the last column of the first row in
Table 54 as a 0.4 percent decrease in expenditures when comparing CY
2017 payments to estimated CY 2018 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 would
result in an estimated total impact of 3 to 5 percent or more on
Medicare revenue for greater than 5 percent of HHAs. Therefore, the
Secretary has determined that this HH PPS proposed rule would have a
significant economic impact on a substantial number of small entities.
Further detail is presented in Table 54, by HHA type and location.
With regards to options for regulatory relief, the sunset of rural
add-on payments for CY 2018 is statutory and we do not have the
authority to authorize rural add-on payments past December 31, 2017. We
believe it is appropriate to reduce the national, standardized 60-day
episode payment amount by 0.97 percent in CY 2018 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.
2. HH PPS for CY 2019 (Proposed HHGM)
The net transfer impacts in CY 2019 related to the proposed change
in the unit of payment under the HHGM are estimated to be -$950 million
(-4.3 percent) if implemented in a fully non-budget neutral manner in
CY 2019. The net transfer impact in CY 2019 related to the change in
the unit of payment under the proposed HHGM is estimated to be -$480
million (-2.2 percent) if the HHGM is implemented in a partially
budget-neutral manner in CY 2019 with the removal of the HHGM partial
budget neutrality adjustment factor in CY 2020. Based on our analysis,
we conclude that the implementation of the HHGM in CY 2019 would result
in an estimated total impact of 3 to 5 percent or more on Medicare
revenue for greater than 5 percent of HHAs, and therefore, would have a
significant economic impact on a substantial number of small entities.
Further detail is presented in Table 55, by HHA type and location.
With regards to options for regulatory relief, changing the unit of
payment from a 60-day episode to a 30-day period is not subject to the
budget neutrality requirements under section 1895 of the Act and would
result in an estimated 4.3 percent decrease (-$950 million) in total HH
PPS payments in CY 2019. As outlined in section III.E.3, we are
proposing to implement the change in the unit of payment from 60-day
episodes of care to 30-day periods care in a non-budget neutral manner
as doing so would better align home health payments with the costs of
providing care. However, as noted in section III.E.3, we are
considering potential alternative implementation approaches for the
HHGM, including, but not limited to, a partially budget-neutral
approach with a phase-out period. Specifically, we are considering
applying a HHGM partial budget neutrality adjustment factor that would
reduce the estimated impact of the HHGM from an estimated -4.3 percent
to -2.2 percent in CY 2019, to be eliminated as soon as CY 2020. We
invite comments on whether to implement the HHGM in a fully non-budget
neutral manner beginning in CY 2019, as proposed; whether to implement
the HHGM in CY 2019 with a HHGM partial budget neutrality adjustment
factor applied and then subsequently removed in CY 2020; or whether a
HHGM partial budget neutrality adjustment factor should be applied and
then phased-out over a longer period of time.
HHAs that provide a larger percentage of overall visits as therapy
visits compared to skilled nursing visits may experience larger
decreases in payments under the HHGM. We do not believe it would be
appropriate to offer regulatory relief, or otherwise mitigate the
impact of the proposed HHGM, for HHAs that provide a preponderance of
their visits as therapy visits compared to nursing visits. The HHGM
would still provide adequate reimbursement for therapy services and was
developed, in part, to eliminate the current therapy thresholds that
encourage the provision of the most profitable number of therapy
visits, even when patient need may not justify such services. We
anticipate that HHAs currently providing excess therapy visits solely
to maximize reimbursement, as outlined in section II.D of this proposed
rule, will no longer do so under the HHGM. We note that therapy
continues to be a valued home health service, as two of the six
clinical groups (neuro/stroke rehabilitation and musculoskeletal
rehabilitation) under the HHGM reflect instances where therapy would be
the primary focus of home health care.
3. HHVBP Model
Under the HHVBP Model, the first payment adjustment will apply in
CY 2018 based on PY1 (2016) data and the final payment adjustment will
apply in CY 2022 based on PY5 (2020) data. In the CY 2016 HH PPS final
rule, we estimated that the overall impact of HHVBP Model from CY 2018
through CY 2022 was a reduction of approximately $380 million (80 FR
68716). In the CY 2017 HH PPS final rule, we estimated that the overall
impact of the HHVBP Model from CY 2018 through CY 2022 was a reduction
of approximately $378 million (81 FR 76795). We do not believe the
proposed
[[Page 35383]]
changes in this rule would affect the prior estimates.
C. Detailed Economic Analysis
This rule proposes updates for CY 2018 to the HH PPS rates
contained in the CY 2017 HH PPS final rule (81 FR 76702 through 76797).
The impact analysis of this proposed rule presents the estimated
expenditure effects of policy changes proposed in this rule. We use the
latest data and best analysis available, but we do not make adjustments
for future changes in such variables as number of visits or case-mix.
This analysis incorporates the latest estimates of growth in
service use and payments under the Medicare HH benefit, based primarily
on Medicare claims data from 2016. 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.
1. HH PPS for CY 2018
Table 54 represents how HHA revenues are likely to be affected by
the policy changes proposed in this rule for CY 2018. For this
analysis, we used an analytic file with linked CY 2016 OASIS
assessments and HH claims data for dates of service that ended on or
before December 31, 2016. The first column of Table 54 classifies HHAs
according to a number of characteristics including provider type,
geographic region, and urban and rural locations. The second column
shows the number of facilities in the impact analysis. The third column
shows the payment effects of the CY 2018 wage index. The fourth column
shows the payment effects of the CY 2018 case-mix weights. The fifth
column shows the effects the 0.97 percent reduction to the national,
standardized 60-day episode payment amount to account for nominal case-
mix growth. The sixth column shows the payment effects from the sunset
of the rural add-on payment provision in statute. The seventh column
shows the effects of the CY 2018 home health payment update percentage.
The last column shows the combined effects of all the policies
proposed in this rule. Overall, it is projected that aggregate payments
in CY 2018 would decrease by 0.4 percent. As illustrated in Table 54,
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 2018 wage index, the extent to
which HHAs had episodes in case-mix groups where the case-mix weight
decreased for CY 2018 relative to CY 2017, 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. In addition, we clarify that there are negative
estimated impacts attributed to the sunset of the rural add-on
provision for HHAs located in urban areas as well as rural areas. This
is due to the fact that HHAs located in urban areas provide services to
patients located in rural areas and payments are based on the location
of the beneficiary.
Table 54--Estimated HHA Impacts by Facility Type and Area of the Country, CY 2018
--------------------------------------------------------------------------------------------------------------------------------------------------------
60-day
episode
CY 2018 CY 2018 rate Sunset of HH payment
Number of wage index case-mix nominal rural add- update Total (%)
agencies \1\ (%) weights \2\ case-mix on (%) percentage
(%) reduction \4\ (%)
\3\ (%)
--------------------------------------------------------------------------------------------------------------------------------------------------------
All Agencies................................................. 10,930 0.0 0.0 -0.9 -0.5 1.0 -0.4
--------------------------------------------------------------------------------------------------------------------------------------------------------
Facility Type and Control
--------------------------------------------------------------------------------------------------------------------------------------------------------
Free-Standing/Other Vol/NP................................... 1,089 0.0 0.1 -0.8 -0.4 1.0 -0.1
Free-Standing/Other Proprietary.............................. 8,588 0.0 0.0 -0.9 -0.4 1.0 -0.3
Free-Standing/Other Government............................... 322 -0.2 0.2 -0.9 -1.4 1.0 -1.3
Facility-Based Vol/NP........................................ 646 0.0 0.3 -0.8 -0.7 1.0 -0.2
Facility-Based Proprietary................................... 92 -0.2 0.2 -0.9 -1.3 1.0 -1.2
Facility-Based Government.................................... 193 -0.2 0.2 -0.9 -1.4 1.0 -1.3
------------------------------------------------------------------------------------------
Subtotal: Freestanding................................... 9,999 0.0 0.0 -0.9 -0.4 1.0 -0.3
Subtotal: Facility-based................................. 931 -0.1 0.3 -0.8 -0.8 1.0 -0.4
Subtotal: Vol/NP......................................... 1,735 0.0 0.2 -0.8 -0.5 1.0 -0.1
Subtotal: Proprietary.................................... 8,680 0.0 0.0 -0.9 -0.5 1.0 -0.4
Subtotal: Government..................................... 515 -0.2 0.2 -0.9 -1.4 1.0 -1.3
--------------------------------------------------------------------------------------------------------------------------------------------------------
Facility Type and Control: Rural
--------------------------------------------------------------------------------------------------------------------------------------------------------
Free-Standing/Other Vol/NP................................... 267 0.2 0.2 -0.9 -2.5 1.0 -2.0
Free-Standing/Other Proprietary.............................. 814 -0.2 -0.1 -0.9 -2.3 1.0 -2.5
Free-Standing/Other Government............................... 229 -0.4 0.1 -0.9 -2.6 1.0 -2.8
Facility-Based Vol/NP........................................ 291 -0.4 0.2 -0.9 -2.7 1.0 -2.8
Facility-Based Proprietary................................... 47 -0.1 0.2 -0.9 -2.7 1.0 -2.5
Facility-Based Government.................................... 142 -0.2 0.2 -0.9 -2.6 1.0 -2.5
--------------------------------------------------------------------------------------------------------------------------------------------------------
Facility Type and Control: Urban
--------------------------------------------------------------------------------------------------------------------------------------------------------
Free-Standing/Other Vol/NP................................... 822 -1.0 0.1 -0.8 -0.1 1.0 -0.8
[[Page 35384]]
Free-Standing/Other Proprietary.............................. 7,774 0.0 0.0 -0.9 -0.2 1.0 -0.1
Free-Standing/Other Government............................... 93 0.0 0.2 -0.9 -0.1 1.0 0.2
Facility-Based Vol/NP........................................ 355 0.1 0.3 -0.8 -0.1 1.0 0.5
Facility-Based Proprietary................................... 45 -0.3 0.2 -0.9 -0.2 1.0 -0.2
Facility-Based Government.................................... 51 -0.2 0.3 -0.9 -0.3 1.0 -0.1
--------------------------------------------------------------------------------------------------------------------------------------------------------
Facility Location: Urban or Rural
--------------------------------------------------------------------------------------------------------------------------------------------------------
Rural........................................................ 1,790 -0.1 0.0 -0.9 -2.4 1.0 -2.4
Urban........................................................ 9,140 0.0 0.0 -0.9 -0.2 1.0 -0.1
--------------------------------------------------------------------------------------------------------------------------------------------------------
Location: Region of the Country (Census Region)
--------------------------------------------------------------------------------------------------------------------------------------------------------
New England.................................................. 346 0.1 0.1 -0.8 -0.3 1.0 0.1
Mid Atlantic................................................. 488 0.0 0.0 -0.8 -0.2 1.0 0.0
East North Central........................................... 2,216 0.0 0.2 -0.9 -0.4 1.0 -0.1
West North Central........................................... 706 0.3 0.2 -0.9 -0.8 1.0 -0.2
South Atlantic............................................... 1,721 -0.1 -0.1 -0.9 -0.3 1.0 -0.4
East South Central........................................... 423 -0.2 -0.2 -0.9 -1.3 1.0 -1.6
West South Central........................................... 2,972 0.2 -0.2 -0.9 -0.7 1.0 -0.6
Mountain..................................................... 668 -0.3 0.1 -0.9 -0.4 1.0 -0.5
Pacific...................................................... 1,343 0.1 0.5 -0.9 -0.1 1.0 0.6
Other........................................................ 47 0.2 -1.0 -0.8 -0.6 1.0 -1.2
--------------------------------------------------------------------------------------------------------------------------------------------------------
Facility Size (Number of 1st Episodes)
--------------------------------------------------------------------------------------------------------------------------------------------------------
<100 episodes................................................ 3,109 0.1 0.2 -0.9 -0.4 1.0 0.0
100 to 249................................................... 2,478 0.1 0.2 -0.9 -0.5 1.0 -0.1
250 to 499................................................... 2,203 0.1 0.2 -0.9 -0.5 1.0 -0.1
500 to 999................................................... 1,646 0.0 0.1 -0.9 -0.5 1.0 -0.3
1,000 or More................................................ 1,494 0.0 -0.1 -0.9 -0.5 1.0 -0.5
--------------------------------------------------------------------------------------------------------------------------------------------------------
Source: CY 2016 Medicare claims data for episodes ending on or before December 31, 2016 for which we had a linked OASIS assessment.
\1\ The impact of the CY 2018 home health wage index is offset by the wage index budget neutrality factor described in section III.C.3 of this proposed
rule.
\2\ The impact of the CY 2018 home health case-mix weights reflects the recalibration of the case-mix weights offset by the case-mix weights budget
neutrality factor described in section III.B of this proposed rule.
\3\ The 0.97 percent reduction to the national, standardized 60-day episode payment amount in CY 2018 is estimated to have a 0.9 percent impact on
overall HH PPS expenditures.
\4\ The CY 2018 home health payment update percentage reflects the home health payment update of 1 percent 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. HH PPS for CY 2019 (Proposed HHGM)
Table 55 represents how HHA revenues are likely to be affected by
the policy changes proposed in this rule for CY 2019. For this
analysis, we used an analytic file with linked CY 2016 OASIS
assessments and CY 2016 HH claims data (as of March 17, 2017) for dates
of service that ended on or before December 31, 2016. The first column
of Table 55 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 and fourth columns shows the impact of the
proposed HHGM as outlined in section III.E of this proposed rule.
Overall, before application of the home health payment update
percentage for CY 2019, it is projected that aggregate payments in CY
2019 would decrease by $950 million (-4.3 percent) if implemented in a
fully non-budget neutral manner and by -$480 million (-2.2 percent) if
the HHGM is implemented in a partially budget-neutral manner in CY 2019
with the removal of the HHGM partial budget neutrality adjustment
factor in CY 2020. As illustrated in Table 55, the effect of the
proposed HHGM varies 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. This is due to
distributional differences among HHAs with regards to the percentage of
total HH PPS payments that were subject to the low-utilization payment
adjustment (LUPA) or paid as outlier payments, the degree of Medicare
utilization, and the ratio of overall visits that were provided as
therapy versus skilled nursing.
[[Page 35385]]
Table 55--Estimated HHA Impacts by Facility Type and Area of the Country, CY 2019
----------------------------------------------------------------------------------------------------------------
Implementation
Implementation of the HHGM
Number of of the HHGM (partially
agencies (not budget budget
neutral) (%) neutral) (%)
----------------------------------------------------------------------------------------------------------------
All Agencies.................................................... 10,860 -4.3 -2.2
----------------------------------------------------------------------------------------------------------------
Facility Type and Control
----------------------------------------------------------------------------------------------------------------
Free-Standing/Other Vol/NP...................................... 1,085 -1.3 0.9
Free-Standing/Other Proprietary................................. 8,525 -5.7 -3.6
Free-Standing/Other Government.................................. 319 -2.9 -0.7
Facility-Based Vol/NP........................................... 646 -0.2 2.0
Facility-Based Proprietary...................................... 92 0.4 2.6
Facility-Based Government....................................... 193 1.3 3.6
-----------------------------------------------
Subtotal: Freestanding...................................... 9,929 -4.7 -2.6
Subtotal: Facility-based.................................... 931 0.0 2.2
Subtotal: Vol/NP............................................ 1,731 -1.0 1.2
Subtotal: Proprietary....................................... 8,617 -5.7 -3.6
Subtotal: Government........................................ 512 -0.7 1.5
----------------------------------------------------------------------------------------------------------------
Facility Type and Control: Rural
----------------------------------------------------------------------------------------------------------------
Free-Standing/Other Vol/NP...................................... 267 0.2 2.5
Free-Standing/Other Proprietary................................. 808 -0.6 1.7
Free-Standing/Other Government.................................. 226 -1.7 0.6
Facility-Based Vol/NP........................................... 291 0.3 2.5
Facility-Based Proprietary...................................... 47 5.0 7.3
Facility-Based Government....................................... 142 1.8 4.1
----------------------------------------------------------------------------------------------------------------
Facility Type and Control: Urban
----------------------------------------------------------------------------------------------------------------
Free-Standing/Other Vol/NP...................................... 818 -1.5 0.7
Free-Standing/Other Proprietary................................. 7,717 -6.3 -4.3
Free-Standing/Other Government.................................. 93 -4.2 -2.0
Facility-Based Vol/NP........................................... 355 -0.3 1.9
Facility-Based Proprietary...................................... 45 -3.1 -1.0
Facility-Based Government....................................... 51 0.9 3.1
----------------------------------------------------------------------------------------------------------------
Facility Location: Urban or Rural
----------------------------------------------------------------------------------------------------------------
Rural........................................................... 1,781 -0.2 2.1
Urban........................................................... 9,079 -4.9 -2.8
----------------------------------------------------------------------------------------------------------------
Facility Location: Region of the Country (Census Region)
----------------------------------------------------------------------------------------------------------------
New England..................................................... 339 -2.3 -0.2
Mid Atlantic.................................................... 485 -0.6 1.5
East North Central.............................................. 2,199 -5.2 -3.1
West North Central.............................................. 705 -7.9 -5.9
South Atlantic.................................................. 1,713 -10.2 -8.2
East South Central.............................................. 423 -3.2 -1.0
West South Central.............................................. 2,947 -0.3 1.9
Mountain........................................................ 662 -9.7 -7.8
Pacific......................................................... 1,340 0.1 2.3
Other........................................................... 47 6.0 8.4
----------------------------------------------------------------------------------------------------------------
Facility Size (Number of 1st Episodes)
----------------------------------------------------------------------------------------------------------------
< 100 episodes.................................................. 3,040 -2.9 -0.8
100 to 249...................................................... 2,478 -3.8 -1.7
250 to 499...................................................... 2,203 -3.9 -1.8
500 to 999...................................................... 1,645 -4.6 -2.5
1,000 or More................................................... 1,494 -4.4 -2.3
----------------------------------------------------------------------------------------------------------------
Nursing/Therapy Visits Ratio
----------------------------------------------------------------------------------------------------------------
1st Quartile (Lowest 25 Nursing)................................ 2,715 -14.4 -12.6
2nd Quartile.................................................... 2,715 -4.6 -2.5
3rd Quartile.................................................... 2,715 2.6 4.9
[[Page 35386]]
4th Quartile (Top 25 Nursing)................................... 2,715 12.9 15.5
----------------------------------------------------------------------------------------------------------------
Source: CY 2016 Medicare claims data (as of March 17, 2017) for episodes ending on or before December 31, 2016
for which we had a linked OASIS assessment.
Notes: This analysis includes assumptions on behavioral responses as a result of the new case-mix adjustment
methodology and omits 360,683 individuals not grouped under the HHGM (either due to a missing OASIS, because
they could be assigned to a clinical grouping, or had missing therapy/nursing visits). After converting 60-day
episodes to 30-day periods for the HHGM, a further 28 periods were excluded with missing wage index
information, 17 periods with missing NRS weights, and 2,376 periods with a missing urban/rural indicator.
These excluded episodes results overall in 70 fewer HHAs being represented than in Table 54.
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.
3. HHVBP Model
Table 57 displays our analysis of the distribution of possible
payment adjustments at the 3-percent, 5-percent, 6-percent, 7-percent,
and 8-percent rates that are being used in the Model using the 2015 and
2016 OASIS-based measures, claims-based hospitalization and Emergency
Department (ED) measures, and HHCAHPS data. Full 2016 data are not yet
available for claims-based and HHCAHPS-based measures. For these
measures, we used the available data--12 months of episodes ending
September 30, 2016 for claims-based measures and 12 months ending June
30, 2016 for HHCAHPS-based measures. The estimated impacts account for
the minimum 40 HHCAHPS completed surveys proposal and the proposal to
remove the OASIS-based measure, Drug Education on All Medications
Provided to Patient/Caregiver during all Episodes of Care beginning in
PY 3. We simulated the impacts based on nine (9) OASIS quality
measures, two (2) claims-based measures in QIES, and the three (3) New
Measures (using the October 2016 and January 2017 submission data),
using the QIES Roll Up File data in the same manner as they will be in
the Model. HHAs were classified as being in the smaller or larger
volume cohort using the 2015 Quality Episode File, which is created
using OASIS assessments. The basis of the payment adjustment was
derived from complete 2015 claims data. We note that this impact
analysis is based on the aggregate value of all nine (9) states.
Table 58 displays our analysis of the distribution of possible
payment adjustments based on the same 2015-2016 data used to calculate
Table 57, providing information on the estimated impact of the
proposals in this rule. We note that this impact analysis is based on
the aggregate value across all nine (9) Model states. Note that all
Medicare-certified HHAs that provide services in Massachusetts,
Maryland, North Carolina, Florida, Washington, Arizona, Iowa, Nebraska,
and Tennessee are required to compete in this Model. This analysis
reflects that under our proposal, only HHAs that have data for at least
five measures that meet the requirements of proposed Sec. 484.305
would be included in the LEF and would have a payment adjustment
calculated. Value-based incentive payment adjustments for the estimated
1,600 plus HHAs in the selected states that will compete in the HHVBP
Model are stratified by size as described in section IV.B. of the CY
2017 HH PPS final rule. As finalized in section IV.B. of the CY 2017
final rule, there must be a minimum of eight (8) HHAs in any cohort.
Those HHAs that are in states that do not have at least eight
smaller-volume HHAs will not have a separate smaller-volume cohort and
thus there will only be one cohort that will include all the HHAs in
that state. As indicated in Table 58, Maryland, North Carolina,
Tennessee and Washington will only have one cohort while Arizona,
Florida, Iowa, Massachusetts, and Nebraska will have both a smaller-
volume cohort and a larger-volume cohort. For example, Iowa has 32 HHAs
eligible to be exempt from being required to have their beneficiaries
complete HHCAHPS surveys because they provided HHA services to less
than 60 beneficiaries. Therefore, those 32 HHAs would be competing in
Iowa's smaller-volume cohort for the 2016 performance year under the
Model.
Using 2015-2016 data and the maximum payment adjustment for
performance year 1 of 3-percent (as applied in CY 2018), based on the
nine (9) OASIS quality measures, two (2) claims-based measures in QIES,
the five (5) HHCAHPS measures, and the three (3) New Measures, the
smaller-volume HHAs in Iowa would have a mean payment adjustment of 0.0
percent (Table 58). Only 10-percent of HHAs in the smaller-volume
cohort would be subject to downward payment adjustments of more than
minus 1.4 percent (-1.4 percent). The next columns provide the
distribution of scores by percentile; we see that the cohort payment
adjustment distribution for HHAs in Iowa in the smaller-volume cohort
ranges from -1.4 percent at the 10th percentile to +1.3 percent at the
90th percentile, while the cohort payment adjustment distribution
median is -0.2 percent.
Table 59 provides the payment adjustment distribution based on
agency size, proportion of dually-eligible beneficiaries, average case
mix (using the average case-mix for non-LUPA episodes), the proportion
of the HHA's beneficiaries that reside in rural areas and HHA
organizational status. HHAs with a higher proportion of dually-eligible
beneficiaries and HHAs whose beneficiaries have higher acuity tend to
have better performance.
The payment adjustment percentages were calculated at the state and
size cohort level. Hence, the values of each separate analysis in the
tables are representative of the baseline year of 2015 and the
performance year of 2016 (though full 2016 data are not yet available
for claims- and HHCAHPS-based measures). There were 1,674 HHAs in the
nine selected states out of
[[Page 35387]]
1,894 HHAs that had a sufficient number of measures to receive a
payment adjustment in the Model. It is expected that a certain number
of HHAs will not have a payment adjustment because they may be
servicing too small of a population to report on an adequate number of
measures to calculate a TPS.
Additional analysis (see Table 60) was conducted to illustrate the
effect of our proposal to require 40 or more completed HHCAHPS surveys
versus 20 or more completed HHCAHPS surveys. The percentage difference
in the average TPS across all larger-volume HHAs for each state ranged
from -0.4 percent through 2.2 percent and the majority of states were
close to zero. We include information on average statewide TPS (by size
cohort) because this is what is used to determine payment adjustment
amounts in HHVBP. The relative ranking of one HHA's TPS to the average
TPS will directly affect the HHA's payment adjustment amount. The
reporting of TPS also shows that this change has no impact on the TPS
for the smaller volume cohort, for which the HHCAHPS measures are not
used (regardless of the minimum sample size).
Table 57--Adjustment Distribution by Percentile Level of Quality Total Performance Score at Different Model Payment Adjustment Rates
[Percentage]
--------------------------------------------------------------------------------------------------------------------------------------------------------
Range Median
Payment adjustment distribution (%) 10% 20% 30% 40% (%) 60% 70% 80% 90%
--------------------------------------------------------------------------------------------------------------------------------------------------------
3% Payment Adjustment For Performance Year 1 of the Model..... 3.0 -1.5 -1.0 -0.7 -0.4 -0.1 0.2 0.6 0.9 1.5
5% Payment Adjustment For Performance Year 2 of the Model..... 5.0 -2.5 -1.6 -1.1 -0.7 -0.1 0.4 0.9 1.5 2.6
6% Payment Adjustment For Performance Year 3 of the Model..... 6.0 -2.9 -2.0 -1.3 -0.8 -0.2 0.4 1.1 1.8 3.1
7% Payment Adjustment For Performance Year 4 of the Model..... 7.0 -3.4 -2.3 -1.5 -0.9 -0.2 0.5 1.3 2.1 3.6
8% Payment Adjustment For Performance Year 5 of the Model..... 8.0 -3.9 -2.6 -1.8 -1.1 -0.2 0.6 1.5 2.4 4.1
--------------------------------------------------------------------------------------------------------------------------------------------------------
Table 58--HHA Cohort Payment Adjustment Distributions by State/Cohort
[Based on a 3-percent payment adjustment]
--------------------------------------------------------------------------------------------------------------------------------------------------------
Average
Cohort # of payment adj. 10% 20% 30% 40% 50% 60% 70% 80% 90%
HHAs %
--------------------------------------------------------------------------------------------------------------------------------------------------------
HHA Cohort in States with no small cohorts (percent)
--------------------------------------------------------------------------------------------------------------------------------------------------------
MD............................................ 51 0.0 -1.0 -0.8 -0.6 -0.4 0.1 0.3 0.5 0.6 1.1
NC............................................ 167 -0.1 -1.3 -0.9 -0.6 -0.3 -0.1 0.1 0.4 0.7 0.9
TN............................................ 124 -0.2 -1.4 -0.9 -0.7 -0.5 -0.1 0.1 0.5 0.7 1.0
WA............................................ 57 -0.2 -1.1 -0.9 -0.6 -0.3 0.0 0.2 0.3 0.4 0.7
--------------------------------------------------------------------------------------------------------------------------------------------------------
Smaller-volume HHA Cohort in states with small cohort (percent)
--------------------------------------------------------------------------------------------------------------------------------------------------------
AZ............................................ 8 -0.4 -2.4 -1.7 -1.3 -1.1 -1.0 -0.9 0.4 1.4 2.1
FL............................................ 103 0.2 -1.7 -1.3 -0.8 -0.5 -0.2 0.6 1.1 1.6 2.9
IA............................................ 32 0.0 -1.4 -1.0 -0.7 -0.5 -0.2 0.2 0.6 1.1 1.3
MA............................................ 23 -0.7 -2.6 -2.0 -1.7 -1.5 -1.3 -0.9 0.1 1.2 1.2
NE............................................ 16 0.4 -1.8 -1.3 -1.2 -0.7 0.5 1.0 1.8 2.4 3.1
--------------------------------------------------------------------------------------------------------------------------------------------------------
Large-volume HHA Cohort in states with small cohorts (percent)
--------------------------------------------------------------------------------------------------------------------------------------------------------
AZ............................................ 105 -0.1 -1.5 -1.0 -0.7 -0.5 -0.3 0.2 0.6 0.7 1.2
FL............................................ 723 0.1 -1.4 -0.9 -0.6 -0.3 0.0 0.3 0.7 1.1 1.8
IA............................................ 94 -0.1 -1.5 -1.1 -0.7 -0.4 -0.2 0.1 0.5 0.9 1.4
MA............................................ 111 -0.2 -1.6 -1.2 -0.8 -0.5 -0.3 0.1 0.3 0.7 1.1
NE............................................ 44 0.1 -1.3 -0.9 -0.5 -0.1 0.2 0.3 0.7 0.9 1.1
--------------------------------------------------------------------------------------------------------------------------------------------------------
Table 59--Payment Adjustment Distributions by Characteristics
[Based on a 3-percent payment adjustment] \230\ \231\
--------------------------------------------------------------------------------------------------------------------------------------------------------
Average
Cohort # of payment adj. 10% 20% 30% 40% 50% 60% 70% 80% 90%
HHAs %
--------------------------------------------------------------------------------------------------------------------------------------------------------
Small HHA (<60 patients in CY 2015)........... 189 0.1 -1.8 -1.4 -1.0 -0.6 -0.2 0.5 1.1 1.3 2.6
Large HHA (>=60 patients in CY 2015).......... 1,469 0.0 -1.4 -1.0 -0.6 -0.4 -0.1 0.2 0.5 0.8 1.5
Low % Dually--Eligible........................ 414 0.1 -1.1 -0.8 -0.5 -0.2 0.1 0.4 0.6 0.9 1.4
Medium % Dually--Eligible..................... 830 -0.1 -1.4 -1.0 -0.7 -0.4 -0.2 0.1 0.4 0.7 1.2
High % Dually--Eligible....................... 414 0.1 -1.7 -1.3 -0.8 -0.5 0.0 0.4 0.9 1.5 2.3
Low Acuity.................................... 415 -0.3 -1.8 -1.4 -1.0 -0.7 -0.5 -0.1 0.2 0.6 1.2
Mid Acuity.................................... 828 0.0 -1.3 -0.9 -0.6 -0.4 -0.1 0.2 0.5 0.8 1.4
High Acuity................................... 414 0.4 -1.1 -0.6 -0.3 0.0 0.3 0.6 0.9 1.3 2.2
All non-rural beneficiaries................... 989 0.1 -1.5 -1.0 -0.7 -0.4 0.0 0.3 0.7 1.1 1.9
Up to 35% rural beneficiaries................. 389 -0.1 -1.5 -1.0 -0.6 -0.4 -0.1 0.1 0.4 0.7 1.1
Over 35% rural beneficiaries.................. 280 -0.1 -1.4 -1.0 -0.7 -0.5 -0.2 0.0 0.4 0.8 1.3
Non-Profit HHAs............................... 304 0.1 -1.2 -0.8 -0.6 -0.3 0.0 0.3 0.6 0.9 1.4
For-Profit HHAs............................... 1,238 0.0 -1.5 -1.0 -0.7 -0.4 -0.1 0.2 0.6 0.9 1.6
Government HHAs............................... 116 -0.1 -1.3 -1.0 -0.7 -0.5 -0.3 0.0 0.3 0.6 1.2
Freestanding.................................. 1,494 0.0 -1.5 -1.0 -0.7 -0.4 -0.1 0.2 0.6 0.9 1.6
Facility-based................................ 164 0.0 -1.2 -0.9 -0.5 -0.3 0.0 0.3 0.5 0.8 1.2
--------------------------------------------------------------------------------------------------------------------------------------------------------
[[Page 35388]]
Table 60--Impact of Changing Minimum Required Sample Size for HHCAHPS Performance Measures on Average TPS and Payment Adjustment Range \232\
--------------------------------------------------------------------------------------------------------------------------------------------------------
Average TPS Minimum payment Maximum payment
------------------------------------------------- adjustment adjustment
-----------------------------------------------
State HHA count 20 % 20 40
Minimum 40 Minimum Difference Difference Minimum Minimum 20 Minimum 40 Minimum
(%) (%) (%) (%)
--------------------------------------------------------------------------------------------------------------------------------------------------------
Larger-Volume HHAS
--------------------------------------------------------------------------------------------------------------------------------------------------------
AZ.......................................... 105 38.393 39.254 0.86 2.2 -2.6 -2.6 3.0 3.0
FL.......................................... 723 36.794 37.451 0.657 1.8 -2.6 -2.6 3.0 3.0
IA.......................................... 94 41.079 41.049 -0.03 -0.1 -2.4 -2.4 2.0 3.0
MA.......................................... 111 40.074 39.927 -0.147 -0.4 -2.8 -2.8 2.6 2.6
MD.......................................... 50 47.287 47.517 0.23 0.5 -1.2 -1.2 2.0 2.4
NC.......................................... 164 43.738 44.175 0.437 1.0 -2.0 -2.0 2.2 2.2
NE.......................................... 44 39.714 40.581 0.867 2.1 -1.8 -1.8 2.9 2.7
TN.......................................... 121 45.699 45.749 0.05 0.1 -2.8 -2.6 1.8 1.8
WA.......................................... 57 49.888 49.685 -0.203 -0.4 -1.4 -1.8 1.2 1.2
-----------------------------------------------------------------------------------------------------------
Total................................... 1,469 ......... ........... ........... .......... ......... ......... ........... ...........
--------------------------------------------------------------------------------------------------------------------------------------------------------
Smaller-Volume HHAS
--------------------------------------------------------------------------------------------------------------------------------------------------------
AZ.......................................... 8 31.474 31.474 0 0.0 -2.4 -2.4 2.1 2.1
FL.......................................... 103 37.349 37.349 0 0.0 -2.6 -2.6 3.0 3.0
IA.......................................... 32 37.741 37.741 0 0.0 -1.9 -1.9 2.0 2.0
MA.......................................... 23 26.904 26.904 0 0.0 -2.7 -2.7 3.0 3.0
MD.......................................... 1 55.841 55.841 0 0.0 0.6 0.6 0.6 0.6
NC.......................................... 3 67.1 67.1 0 0.0 -0.2 -0.2 3.0 3.0
NE.......................................... 16 37.076 37.076 0 0.0 -2.8 -2.8 3.0 3.0
TN.......................................... 3 48.549 48.549 0 0.0 -1.4 -1.4 2.3 2.3
-----------------------------------------------------------------------------------------------------------
Total................................... 189 ......... ........... ........... .......... ......... ......... ........... ...........
-----------------------------------------------------------------------------------------------------------
Total................................... 1,658 ......... ........... ........... .......... ......... ......... ........... ...........
--------------------------------------------------------------------------------------------------------------------------------------------------------
4. HH QRP
Failure to submit data required under section 1895(b)(3)(B)(v) of
the Act will result in the reduction of the annual update to the
standard federal rate for discharges occurring during such fiscal year
by 2 percentage points for any HHA that does not comply with the
requirements established by the Secretary. At the time that this
analysis was prepared, 513, or approximately 4.3 percent, of the 12,149
active Medicare-certified HHAs, did not receive the full annual
percentage increase for the CY 2017 annual payment update
determination. Information is not available to determine the precise
number of HHAs that will not meet the requirements to receive the full
annual percentage increase for the CY 2018 payment determination.
---------------------------------------------------------------------------
\230\ Rural beneficiaries identified based on the CBSA code
reported on the claim.
\231\ Acuity is based on the average case-mx weight for non-LUPA
episodes. Low acuity is defined as the bottom 25% (among HHVBP model
participants); mid-acuity is the middle 50% and high acuity is the
highest 25%. Note that one HHA was missing acuity information.
\232\ OASIS measures run from January 1, 2015 to December 31,
2016; Claims from September 1, 2015 to September 30, 2016. Payment
based on 2015 and 2016 Medicare claims data (2016 is used as the
payment year--in actuality CY 2018 claims payments would determine
actual payment adjustment amounts).
---------------------------------------------------------------------------
As noted in section VII.B. of this proposed rule, the net effect of
our proposals is an estimated decrease in cost associated with proposed
changes to the HH QRP on average of $3,700.74 per HHA annually, or
$44,952,846.87 for all HHAs annually.
D. Alternatives Considered
1. HH PPS for CY 2018
We did not consider extending the rural add-on payment as this
provision was statutory. Section 421(a) of the MMA extended 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, for episodes and visits ending before January 1, 2018.
Therefore, for episodes and visits that end on or after January 1,
2018, a rural add-on payment will not apply.
In the alternatives considered section for the CY 2016 HH PPS
proposed rule (80 FR 39839), we considered reducing the 60-day episode
rate in CY 2016 only to account for nominal case-mix growth between CY
2012 and CY 2014. However, we instead proposed to reduce the 60-day
episode rate over a 2-year period (CY 2016 and CY 2017) to lessen the
impact on HHAs in a given year. In the CY 2016 HH PPS final rule (80 FR
68624), we finalized a reduction of 0.97 percent to the 60-day episode
rate in each of the next 3 calendar years (CY 2016 through CY 2018.
Therefore, the alternatives with regards to the 0.97 percent reduction
in the national, standardized 60-day episode payment amount for CY 2018
were already considered in the CY 2016 HH PPS proposed and final rules
and we did not consider alternatives for implementing this reduction
for CY 2018.
We are not able to consider alternative values for the home health
payment update percentage. The home health payment update percentage is
based on the home health market basket update and section 1895(b)(3)(B)
of the Act, as amended by section 411(d) of the MACRA, mandates that
for home health payments for CY 2018, the market basket percentage
increase shall be 1 percent.
2. HH PPS for CY 2019 (Proposed HHGM)
We considered proposing to implement the HHGM for CY 2018.
[[Page 35389]]
However, implementation of the HHGM will require provider education and
training, updating and revising relevant manuals, and changing
assessment and claims processing systems. Implementation starting in
2019 would provide an opportunity for CMS and providers to prepare.
For CY 2019, in addition to considering whether to implement the
HHGM in a fully non-budget neutral manner for CY 2019 or implementing
the HHGM with a HHGM partial budget neutrality adjustment factor that
would have reduced the estimated impact of the HHGM by 50 percent in CY
2019 and the elimination of such factor in CY 2020, we also considered
implementing the HHGM as fully budget neutral in CY 2019 or as
partially budget-neutral with longer phase-out period (for example
starting with a HHGM partial budget neutrality adjustment factor that
would have reduced the estimated impact of the HHGM by 75 percent in CY
2019, a HHGM partial budget neutrality adjustment factor that would
have reduced the estimated impact of the HHGM by 50 percent in CY 2020,
a HHGM partial budget neutrality adjustment factor that would have
reduced the estimated impact of the HHGM by 25 percent in CY 2021, and
the elimination of such factor in CY 2022). However, we propose to
implement the change in the unit of payment under the HHGM in a non-
budget neutral manner as doing so better aligns home health payments
with the costs of providing care. In addition, we do not believe a
longer phase-out period is necessary if we were to implement the HHGM
in a non-budget neutral manner with a HHGM partial budget neutrality
adjustment factor applied in CY 2019 to be removed in CY 2020, as this
2-year timeframe would be sufficient to lessen the economic impact in
the first year of implementation.
We also considered maintaining 60-day episodes of care as the unit
of payment. As stated in the FY 2001 HH PPS final rule, ``We believe
the 60-day episode definition is the most appropriate approach to
define the unit of payment under HHA PPS. Public support for the 60-day
episode as the unit of payment under PPS centered on the general
consensus that HHAs and physicians predict home care needs over a 60-
day timeframe due to current plan of care requirements and required
updates to the comprehensive assessments that basically follow a 60-day
timeframe. As discussed in detail in the proposed rule, research
indicated that the 60-day episode captures the majority of stays
experienced in the Phase II per-episode HHA PPS demonstration (65 FR
41136).'' However, we further noted that we ``will continue to monitor
the appropriateness of the 60-day unit of payment and may consider
modifying our approach to the episode definition in subsequent years of
PPS, if warranted.'' During subsequent years, we have identified
variation in average resource use between the first 30-day period
within a 60-day episode and the second 30-day period within a 60-day
episode. This difference in resources between the first and second 30-
day periods within a 60-day episode led to the development of 30-day
periods for the HHGM. In addition, the accuracy of the HHGM improves
when a shorter, more constrained time period is examined. This in turn
would improve the accuracy of the case-mix weights that are generated
using 30-day periods instead of 60-day episodes. We note that the
frequency of the required updates to the plan of care and the
comprehensive assessment would remain unchanged under the proposed
HHGM.
We considered whether to continue using the wage-weighted minutes
of care (WWMC) approach to estimate resource use under the HHGM, as
described in section III.E.2 of this proposed rule. Although the
relationship in relative costs between the WWMC approach and the
proposed cost-per-minute plus non-routine supplies (CPM+NRS) approach
is very similar (correlation coefficient equal to 0.8016), the WWMC
approach does not as evenly weight skilled nursing costs relative to
therapy costs as evidenced in the cost report data and would require us
to maintain a separate case-mix adjustment mechanism for NRS. If we
were to maintain the current WWMC approach, skilled nursing and therapy
costs would not be as evenly weighted and a certain level of complexity
in calculating payments under the HH PPS would persist as we would need
to continue with the current method of case-mix adjusting NRS payments
separate from service costs (i.e., skilled nursing, physical therapy,
occupational therapy, speech-language pathology, home health aide, and
medical social services) under the HH PPS.
Finally, we considered not proposing the HH PPS case-mix
methodology refinements for CY 2019. However, in maintaining the
current case-mix methodology, the current payment system, with its
various therapy thresholds, would continue to provide financial
incentives that detract from a focus on patient characteristics and
care needs when agencies are setting plans of care for their patients,
and would continue to incentivize unnecessary therapy utilization. The
proposed HHGM removes therapy thresholds from the case-mix adjustment
methodology thereby eliminating the financial incentive to provide
unnecessary therapy visits in order to maximize payment. In addition,
we believe the proposed HHGM is a more simplified, clinically
intuitive, and patient-centered approach to payment compared to the
existing case-mix adjustment methodology. We invite comments on the
alternatives discussed in this analysis.
3. HHVBP Model Proposals
An alternative to our proposal to use 40 completed HHCAHPS surveys
beginning with PY 1 would be to continue calculating quality scores at
20 completed HHCAHPS surveys as finalized in the CY 2016 HH PPS final
rule.
Another alternative would be to use 40 completed HHCAHPS surveys
beginning with PY 2 and subsequent years, but keep the 20 completed
HHCAHPS surveys calculation for PY 1; however, this would give HHAs a
short amount of time to analyze from year to year a change in threshold
from 20 to 40 completed HHCAHPS surveys.
Rather than removing the Drug Education on All Medications Provided
to Patient/Caregiver during all Episodes of Care measure from the set
of applicable measures, an alternative would be to keep the measure in
the set of applicable measures for the HHVBP Model. Doing so would
continue HHAs' awareness of the importance of drug education for
patient and caregivers during all episodes of care. Nevertheless, there
would be a lack of variability in the measure across the participating
HHAs and the measure does not address the quality or intensity of the
education provided.
E. Accounting Statement and Table
As required by OMB Circular A-4 (available at https://www.whitehouse.gov/omb/circulars_a004_a-4), in Tables 61 and 62, 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 61 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 in CY 2018. Table 62
provides our estimate as a result of the changes associated with the
HHGM proposed for CY 2019. Table 63 provides our best estimates of the
[[Page 35390]]
changes associated with the HH QRP proposals.
Table 61--Accounting Statement: HH PPS Classification of Estimated
Transfers, From CYs 2017 to 2018
------------------------------------------------------------------------
Category Transfers
------------------------------------------------------------------------
Annualized Monetized Transfers............ -$80 million.
From Whom to Whom? Federal Government to HHAs.
------------------------------------------------------------------------
Table 62--Accounting Statement: HH PPS Classification of Estimated
Transfers due to Implementation of Proposed HHGM, From CYs 2018 to 2019
------------------------------------------------------------------------
Category Transfers
------------------------------------------------------------------------
Annualized Monetized Transfers (Not -$950 million.
Budget Neutral).
Annualized Monetized Transfers -$480 million.
(Partially Budget Neutral).
From Whom to Whom?..................... Federal Government to HHAs.
------------------------------------------------------------------------
Table 63--Accounting Statement: HH QRP Classification of Estimated
Costs, From CYs 2018 to 2019
------------------------------------------------------------------------
Category Costs
------------------------------------------------------------------------
Annualized Monetized Net Burden for -$44.9 million.
HHAs Submission of the OASIS.
------------------------------------------------------------------------
F. Reducing Regulation and Controlling Regulatory Costs
Executive Order 13771, entitled Reducing Regulation and Controlling
Regulatory Costs (82 FR 9339), was issued on January 30, 2017. Under
E.O. 13771, this rule would be considered deregulatory if finalized as
proposed.
G. Conclusion
1. HH PPS
In conclusion, we estimate that the net impact of the HH PPS
policies in this rule is a decrease of 0.4 percent, or $80 million, in
Medicare payments to HHAs for CY 2018. The -$80 million impact reflects
the effects of a 0.5 percent reduction in payments due to the sunset of
the rural add-on provision ($100 million decrease), a 1 percent CY 2018
HH payment update percentage ($190 million increase), and a 0.9 percent
decrease in payments due to the 0.97 percent reduction to the national,
standardized 60-day episode payment rate in CY 2017 to account for
nominal case-mix growth ($170 million decrease). We estimate that the
net impact of the proposed HHGM is a decrease of 4.3 percent ($950
million decrease) in Medicare payments to HHAs in CY 2019 if the
proposed HHGM is implemented in a fully non-budget neutral manner. We
estimate that the net impact of the proposed HHGM is a decrease of 2.2
percent ($480 million decrease) in Medicare payments to HHAs in CY 2019
if the proposed HHGM is implemented in a partially budget-neutral
manner in CY 2019 with the removal of the HHGM partial budget
neutrality adjustment factor in CY 2020.
This analysis, together with the remainder of this preamble,
provides an initial Regulatory Flexibility Analysis.
2. HHVBP Model
In conclusion, we estimate there would be no net impact (to include
either a net increase or reduction in payments) in this proposed rule
in Medicare payments to HHAs competing in the HHVBP Model for CY 2018.
However, the overall economic impact of the HHVBP Model provision is an
estimated $378 million in total savings from a reduction in unnecessary
hospitalizations and SNF usage as a result of greater quality
improvements in the home health industry over the life of the HHVBP
Model.
3. HH QRP
In conclusion, for CY 2019 we estimate that there will be a total
decrease in costs of $44,952,846.87 associated with the proposed
changes to the HH QRP.
X. 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.
In accordance with the provisions of Executive Order 12866, this
regulation was reviewed by the Office of Management and Budget.
List of Subjects
42 CFR Part 409
Health facilities, Medicare.
42 CFR Part 484
Health facilities, Health professions, Medicare, 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 Act (42 U.S.C. 1302 and
1395hh).
0
2. Section Sec. 409.43 is amended by--
0
a. Revising paragraphs (c)(2) and (c)(3)(ii);
0
b. In paragraph (e)(1)(iii), removing the phrase ``during the 60-day
episode'' and adding in its place the phrase ``within 60 days after
discharge''.
The revisions read as follows:
Sec. 409.43 Plan of care requirements.
* * * * *
(c) * * *
(2) Reduction or disapproval of anticipated payment requests. CMS
has
[[Page 35391]]
the authority to reduce or disapprove requests for anticipated payments
in situations when protecting Medicare program integrity warrants this
action. Since the request for anticipated payment is based on verbal
orders as specified in paragraph (c)(1)(i) of this section and/or a
prescribing referral as specified in paragraph (c)(1)(ii) of this
section and is not a Medicare claim for purposes of the Act (although
it is a ``claim'' for purposes of Federal, civil, criminal, and
administrative law enforcement authorities, including but not limited
to the Civil Monetary Penalties Law (as defined in 42 U.S.C. 1320a-
7a(i)(2)), the Civil False Claims Act (as defined in 31 U.S.C.
3729(c)), and the Criminal False Claims Act (18 U.S.C. 287)), the
request for anticipated payment will be canceled and recovered unless
the claim is submitted within the greater of one of the following:
(i) 60 days from the end of the episode (for claims beginning on or
before December 31, 2018);
(ii) 60 days from the end of the 30-day period of care (for claims
beginning on or after January 1, 2019); or
(iii) 60 days from the issuance of the request for anticipated
payment.
(3) * * *
(ii) Before the claims for each episode (for a 60-day episode of
care beginning on or before December 31, 2018) or period (for a 30-day
period of care beginning on or after January 1, 2019) for services is
submitted for the final percentage prospective payment.
* * * * *
PART 484--HOME HEALTH SERVICES
0
3. The authority citation for part 484 continues to read as follows:
Authority: Secs. 1102 and 1871 of the Act (42 U.S.C. 1302 and
1395(hh)) unless otherwise indicated.
0
4. Section 484.202 is amended by revising the definitions of ``Rural
area'' and ``Urban area'' to read as follows:
Sec. 484.202 Definitions.
* * * * *
Rural area means an area defined in Sec. 412.64(b)(1)(ii)(C) of
this chapter.
Urban area means an area defined in Sec. 412.64(b)(1)(ii)(A) and
(B) of this chapter.
0
5. Section 484.205 is revised to read as follows:
Sec. 484.205 Basis of payment.
(a) Method of payment. An HHA receives a national, standardized
prospective payment amount for home health services previously paid on
a reasonable cost basis (except the osteoporosis drug defined in
section 1861(kk) of the Act) as of August 5, 1997. The national,
standardized prospective payment is determined in accordance with Sec.
484.215.
(b) Unit of payment. For episodes beginning on or before December
31, 2018, an HHA receives a national, standardized prospective 60-day
episode payment amount. For periods beginning on or after January 1,
2019, a HHA receives a national, standardized prospective 30-day
payment amount.
(c) OASIS data. A HHA must submit to CMS the OASIS data described
at Sec. 484.55(b) and (d) in order for CMS to administer the payment
rate methodologies described in Sec. Sec. 484.215, 484.220, 484.230,
484.235, and 484.240.
(d) Payment adjustments. The national, standardized prospective
payment amount is subject to the following adjustments and additional
payments:
(1) A low-utilization payment adjustment (LUPA) of a predetermined
per-visit rate as specified in Sec. 484.230.
(2) A partial payment adjustment as specified in Sec. 484.235.
(3) An outlier payment as specified in Sec. 484.240.
(e) Medical review. All payments under this system may be subject
to medical review with respect to beneficiary eligibility, medical
necessity, and case-mix group assignment.
(f) Durable medical equipment (DME) and disposable devices. DME
provided as a home health service as defined in section 1861(m) of the
Act is paid the fee schedule amount. Separate payment is made for
``furnishing NPWT using a disposable device,'' as that term is defined
in Sec. 484.202, and is not included in the national, standardized
prospective payment amount.
(g) Split percentage payments. Split percentage payments are made
in accordance with requirements at Sec. 409.43(c) of this chapter.
(1) Split percentage payments for episodes beginning on or before
December 31, 2018:
(i) The initial payment for initial episodes is paid to an HHA at
60 percent of the case-mix and wage-adjusted 60-day episode rate. The
residual final payment for initial episodes is paid at 40 percent of
the case-mix and wage-adjusted 60-day episode rate.
(ii) The initial payment for subsequent episodes is paid to an HHA
at 50 percent of the case-mix and wage-adjusted 60-day episode rate.
The residual final payment for subsequent episodes is paid at 50
percent of the case-mix and wage-adjusted 60-day episode rate.
(2) Split percentage payments for periods beginning on or after
January 1, 2019:
(i) The initial payment for initial 30-day periods is paid to an
HHA at 60 percent of the case-mix and wage-adjusted 30-day payment
rate. The residual final payment for initial 30-day periods is paid at
40 percent of the case-mix and wage-adjusted 30-day payment rate.
(ii) The initial payment for subsequent 30-day periods is paid to
an HHA at 50 percent of the case-mix and wage-adjusted 30-day payment
rate. The residual final payment for subsequent 30-day periods is paid
at 50 percent of the case-mix and wage-adjusted 30-day payment rate.
Sec. 484.210 [Removed and Reserved]
0
6. Section 484.210 is removed and reserved.
0
7. Section 484.215 is amended by--
0
a. Revising the section heading;
0
b. Revising paragraph (d) introductory text; and
0
c. Adding paragraph (f).
The revisions and addition read as follows:
Sec. 484.215 Initial establishment of the calculation of the
national, standardized prospective 60-day episode payment and 30-day
payment rates.
* * * * *
(d) Calculation of the unadjusted national average prospective
payment amount for the 60-day episode. For episodes beginning on or
before December 31, 2018, CMS calculates the unadjusted national 60-day
episode payment in the following manner:
* * * * *
(f) For periods beginning on or after January 1, 2019, a national,
standardized prospective 30-day payment rate applies. The national,
standardized prospective 30-day payment rate is an amount determined by
the Secretary, as subsequently updated pursuant to Sec. 484.225.
0
8. Section 484.220 is amended by--
0
a. Revising the section heading;
0
b. Revising the introductory text; and
0
c. In paragraph (a) introductory text, removing the phrase ``national
prospective 60-day episode'' and adding in its place the phrase
``national, standardized prospective''.
The revisions read as follows:
Sec. 484.220 Calculation of the case-mix and wage area adjusted
prospective payment rates.
CMS adjusts the national, standardized prospective payment rates as
referenced in Sec. 484.215 to account for the following:
* * * * *
[[Page 35392]]
0
9. Section 484.225 is amended by--
0
a. Revising the section heading;
0
b. Revising paragraph (a);
0
c. In paragraphs (b) and (c), removing the phrase ``national
prospective 60-day episode'' and adding the phrase ``national
standardized prospective''; and
0
d. Adding paragraph (d).
The revisions and addition read as follows:
Sec. 484.225 Annual update of the unadjusted national, standardized
prospective payment rates.
(a) CMS annually updates the unadjusted national, standardized
prospective payment rate on a calendar year basis in accordance with
section 1895(b)(3)(B) of the Act.
* * * * *
(d) For CY 2019, the national, standardized prospective 30-day
payment amount is an amount determined by the Secretary. CMS annually
updates this amount on a calendar year basis in accordance with
paragraphs (a) through (c) of this section.
0
10. Section 484.230 is revised to read as follows:
Sec. 484.230 Low-utilization payment adjustments.
(a) For episodes beginning on or before December 31, 2018, an
episode with four or fewer visits is paid the national per-visit amount
by discipline updated annually by the applicable market basket for each
visit type, in accordance with Sec. 484.225. The national per-visit
amount is adjusted by the appropriate wage index based on the site of
service of the beneficiary. An amount will be added to the low-
utilization payment adjustments for low-utilization episodes that occur
as the beneficiary's only episode or initial episode in a sequence of
adjacent episodes. For purposes of the home health PPS, a sequence of
adjacent episodes for a beneficiary is a series of claims with no more
than 60 days without home care between the end of one episode, which is
the 60th day (except for episodes that have been PEP-adjusted), and the
beginning of the next episode.
(b) For periods beginning on or after January 1, 2019, an HHA
receives a national 30-day payment of a predetermined rate for home
health services, unless CMS determines at the end of the 30-day period
that the HHA furnished minimal services to a patient during the 30-day
period. For each payment group used to case-mix adjust the 30-day
payment rate, the 10th percentile value of total visits during a 30-day
period of care will be used to create payment group specific thresholds
with a minimum threshold of at least 2 visits for each case-mix group.
A 30-day period with a total number of visits less than the threshold
is paid the national per-visit amount by discipline updated annually by
the applicable market basket for each visit type. The national per-
visit amount is adjusted by the appropriate wage index based on the
site of service for the beneficiary.
(c) An amount will be added to low-utilization payment adjustments
for low-utilization periods that occur as the beneficiary's only 30-day
period or initial 30-day period in a sequence of adjacent periods of
care. For purposes of the home health PPS, a sequence of adjacent
periods of care for a beneficiary is a series of claims with no more
than 60 days without home care between the end of one period, which is
the 30th day (except for episodes that have been partial payment
adjusted), and the beginning of the next episode.
0
11. Section 484.235 is revised to read as follows:
Sec. 484.235 Partial payment adjustments.
(a) Partial episode payments (PEPs) for episodes beginning on or
before December 31, 2018. (1) An HHA receives a national, standardized
60-day payment of a predetermined rate for home health services unless
CMS determines that an intervening event has occurred, which 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. An intervening event is defined as either a beneficiary
elected transfer or a discharge with goals met or no expectation of
return to home health, but the beneficiary returned to home health
during the 60-day episode.
(2) The PEP adjustment will not apply in situations of transfers
among HHAs under 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 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 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 based on the first billable
visit date through and including the last billable visit date. The PEP
is calculated by determining the actual days served as a proportion of
60 multiplied by the initial 60-day payment amount.
(b) Partial payment adjustments for periods beginning on or after
January 1, 2019. (1) An HHA receives a national, standardized 30-day
payment of a predetermined rate for home health services unless CMS
determines that an intervening event has occurred, which warrants a new
30-day period for purposes of payment. A start of care OASIS assessment
and physician certification of the new plan of care are required. An
intervening event is defined as either a beneficiary elected transfer
or a discharge and return to home health during the 30-day period.
(2) The partial payment 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 30-day period. The common ownership exception to
the transfer partial payment adjustment does not apply if the
beneficiary moves to a different MSA or Non-MSA during the 30-day
period 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 30-day payment and thus
a new physician certification and a new plan of care, the initial HHA
receives a partial payment adjustment reflecting the length of time the
patient remained under its care based on the first billable visit date
through and including the last billable visit date. The partial payment
is calculated by determining the actual days served as a proportion of
30 multiplied by the initial 30-day payment amount.
0
12. Section 484.240 is revised to read as follows:
Sec. [thinsp]484.240 Outlier payments.
(a) For episodes beginning on or before December 31, 2018, an HHA
receives an outlier payment for an
[[Page 35393]]
episode whose estimated costs exceeds a threshold amount for each case-
mix group. 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.
(b) For periods beginning on or after January 1, 2019, an HHA
receives an outlier payment for a 30-day period whose estimated cost
exceeds a threshold amount for each case-mix group. The outlier
threshold for each case-mix group is the 30-day payment amount for that
group, or the partial payment adjustment amount for the 30-day period,
plus a fixed dollar loss amount that is the same for all case-mix
groups.
(c) The outlier payment is a proportion of the amount of estimated
cost beyond the threshold.
(d) CMS estimates the cost for each episode by multiplying the
national per-15 minute unit amount of each discipline by the number of
15 minute units in the discipline and computing the total estimated
cost for all disciplines.
0
13. Section 484.250 is amended by revising paragraph (a)(1) and adding
paragraphs (d) through (f) to read as follows:
Sec. 484.250 Patient assessment data.
(a) * * *
(1) The OASIS data described at Sec. 484.55(b) and (d) for CMS to
administer the payment rate methodologies described in Sec. Sec.
484.215, 484.220, 484. 230, 484.235, and 484.240; and to meet the
quality reporting requirements of section 1895(b)(3)(B)(v) of the Act.
* * * * *
(d) Exceptions and extension requirements. (1) A HHA may request
and CMS may grant exceptions or extensions to the reporting
requirements under section 1895(b)(3)(B)(v) of the Act for one or more
quarters, when there are certain extraordinary circumstances beyond the
control of the HHA.
(2) A HHA may request an exception or extension within 90 days of
the date that the extraordinary circumstances occurred by sending an
email to CMS HHAPU reconsiderations at
HHAPUReconsiderations@cms.hhs.gov that contains all of the following
information:
(i) HHA CMS Certification Number (CCN).
(ii) HHA Business Name.
(iii) HHA Business Address.
(iv) CEO or CEO-designated personnel contact information including
name, telephone number, title, email address, and mailing address (The
address must be a physical address, not a post office box).
(v) HHA's reason for requesting the exception or extension.
(vi) Evidence of the impact of extraordinary circumstances,
including, but not limited to, photographs, newspaper, and other media
articles.
(vii) Date when the HHA believes it will be able to again submit
data under section 1895(b)(3)(B)(v) of the Act and a justification for
the proposed date.
(3) Except as provided in paragraph (d)(4) of this section, CMS
will not consider an exception or extension request unless the HHA
requesting such exception or extension has complied fully with the
requirements in this paragraph (d).
(4) CMS may grant exceptions or extensions to HHAs without a
request if it is determines that one or more of the following has
occurred:
(i) An extraordinary circumstance affects an entire region or
locale.
(ii) A systemic problem with one of CMS's data collection systems
directly affected the ability of a HHA to submit data under section
1895(b)(3)(B)(v) of the Act.
(e) Reconsideration. (1) HHAs that do not meet the quality
reporting requirements under section 1895(b)(3)(B)(v) of the Act for a
program year will receive a letter of non-compliance through the USPS
and via notification in CASPER. An HHA may request reconsideration no
later than 30 calendar days after the date identified on the letter of
non-compliance.
(2) Reconsideration requests may be submitted to CMS by sending an
email to CMS HHAPU reconsiderations at
HHAPureConsiderations@cms.hhs.gov containing all of the following
information:
(i) HHA CCN.
(ii) HHA Business Name.
(iii) HHA Business Address.
(iv) CEO or CEO-designated personnel contact information including
name, telephone number, title, email address, and mailing address (The
address must be a physical address, not a post office box).
(v) CMS identified reason(s) for non-compliance from the non-
compliance letter.
(vi) Reason(s) for requesting reconsideration, including all
supporting documentation. CMS will not consider an exception or
extension request unless the HHA has complied fully with the
requirements in paragraph (e)(2) of this section.
(3) CMS will make a decision on the request for reconsideration and
provide notice of the decision to the HHA through CASPER and via letter
sent through the United States Postal Service.
(f) Appeals. (1) A HHA that is dissatisfied with CMS' decision on a
reconsideration request submitted under paragraph (e) of this section
may file an appeal with the Provider Reimbursement Review Board (PRRB)
under 42 CFR part 405, subpart R.
(2) [Reserved]
0
14. Section 484.305 is amended by revising the definition of
``Applicable measure'' to read as follows:
Sec. 484.305 Definitions.
* * * * *
Applicable measure means a measure for which a competing HHA has
provided a minimum of:
(1) 20 home health episodes of care per year for the OASIS-based
measures;
(2) 20 home health episodes of care per year for the claims-based
measures; or
(3) 40 completed surveys for the HHCAHPS measures.
* * * * *
Dated: June 29, 2017.
Seema Verma,
Administrator, Centers for Medicare & Medicaid Services.
Dated: June 30, 2017.
Thomas E. Price,
Secretary, Department of Health and Human Services.
[FR Doc. 2017-15825 Filed 7-25-17; 4:15 pm]
BILLING CODE 4120-01-P
