Area Variation in Rehabilitation Use in Nursing Homes Wen-Chieh Lin, PhD 1 Gregory F. Petroski, PhD 2 David R. Mehr, MD, MS 1 Steven C. Zweig, MD, MSPH 1 Robert L. Kane, MD 3 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 – >= 3-day hospitalization within 30 days prior to admission – requiring skilled nursing or skilled rehabilitation services Coverage – 100 days per benefit period – copayment required for days 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 25 th -percentile 57.5% Median 64.8% 75 th -percentile 68.9% Top 5 statesLowest 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 – Proportion of elderly population, proportion of Medicare and Medicaid dually eligible elderly, proportion of hospice users Needs – 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