Area Variation in Rehabilitation
Use in Nursing Homes
Wen-Chieh Lin, PhD1
Gregory F. Petroski, PhD2
David R. Mehr, MD, MS1
Steven C. Zweig, MD, MSPH1
Robert L. Kane, MD3
1.
Department of Family and Community Medicine,
University of Missouri-Columbia
2.
Biostatistics Group, Office of Medical Research,
University of Missouri-Columbia
3.
Division of Health Policy and Management,
University of Minnesota
Funding Sources: Agency for
Healthcare Research and Quality
Nursing Home (NH) Residents
Long-stay vs. short-stay
–
–
Long-stay: Medicaid or private pay
Short-stay: Medicare covered skilled nursing
facility (SNF) care
Provides services to patients after being discharged
from acute care hospitals
Replaces a portion of hospital care
Facilitates recovery and/or rehabilitation
Medicare Skilled Nursing Facility Service
Eligibility
–
–
Coverage
–
–
>= 3-day hospitalization within 30 days prior to admission
requiring skilled nursing or skilled rehabilitation services
100 days per benefit period
copayment required for days 21-100
Payment
–
Case-mix adjusted per-diem prospective payment
Resource Utilization Groups (RUGs)
Case-mix adjustment for the SNF prospective
payment system
Based on services provided
10 major RUG-III groups with 5 rehabilitation
groups
–
–
Ultra high, very high, high, medium, and low
rehabilitation groups
Strong financial incentives for providing
rehabilitation services
Area Variation in Rehabilitation RUGs
Classification
The proportion of
SNF stays classified
into rehabilitation
RUGs in calendar
year 2000
–
–
Nationally 64.9%
Among states
25th-percentile 57.5%
Median 64.8%
75th-percentile 68.9%
Top 5 states
Lowest 5 states
MI 73.5%
MT 52.0%
FL 73.1%
AR 50.7%
OH 71.3%
LA 48.1%
VA 70.9%
SD 43.9%
CO 70.8%
ND 40.7%
Research Question
What factors are associated with the area
variation in NH rehabilitation use, i.e. the
proportion of rehabilitation RUGs?
Population differences
Substitution between SNFs and inpatient
rehabilitation facilities (IRFs) under Medicare’s
post-acute care services
Varied levels of treatment and “aggressiveness”
Methods
Data
–
Medicare covered SNF stays by state of provider
and major RUG-III groups in calendar year 2000
Logit regression on grouped data
Independent Variables Considered
Population
–
Needs
–
Proportion of elderly population, proportion of Medicare and
Medicaid dually eligible elderly, proportion of hospice users
The ratio of SNF use to IRF use in patients discharged from
hospital for stroke, hip and knee procedures, and hip fracture
Supply
–
The number of SNF beds per 1,000 elderly, the number of IRF
beds per 1,000 elderly, the proportion of for-profit SNFs
Note: Considering the small sample size, variables in the Italic font were
excluded from the final model.
Results
Negative association with % of SNF stays being classified into
rehabilitation RUGs (** p-value < 0.01, * p-value < 0.05)
–
–
–
The number of IRF beds per 1,000 elderly (β = -0.26**)
The ratio of SNF use to IRF use (β = -0.03*)
The proportion of dually eligible elderly (β = -0.04**)
An example – holding other covariates at their median values
# of IRF beds per
1,000 elderly
Adjusted % of SNF stays being
classified into rehabilitation RUGs
0.32 (OR)
70.7%
0.75 (VT)
68.4%
0.96 (VA)
67.2%
1.29 (MO)
65.2%
2.69 (LA)
56.6%
Conclusions
Substitution between SNF and IRF use
–
Increased IRF beds supply was associated with
decreased likelihood of receiving rehabilitation
services during SNF stays
Limitations
State-level data
–
Patient and facility characteristics uncontrolled for
in the model
Lack of assessment data upon admission
and discharge
Discussion
Heterogeneous groups of SNF residents
Case-mix adjustment based on services
provided, but not clinical needs
Financial incentives for rehabilitation
Appropriateness and outcomes of
rehabilitation use in SNFs
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