Disparities in post-acute rehabilitation care for joint replacement

Abstract

Objective: To determine the extent to which demographic and geographic disparities exist in the use of post-acute rehabilitation care (PARC) for joint replacement.

Methods: We conducted a cross-sectional analysis of 2 years (2005 and 2006) of population-based hospital discharge data from 392 hospitals in 4 states (Arizona, Florida, New Jersey, and Wisconsin). A total of 164,875 individuals who were age ≥ 45 years, admitted to the hospital for a hip or knee joint replacement, and who survived their inpatient stay were identified. Three dichotomous dependent variables were examined: 1) discharge to home versus institution (i.e., skilled nursing facility [SNF] or inpatient rehabilitation facility [IRF]), 2) discharge to home with versus without home health (HH), and 3) discharge to an SNF versus an IRF. Multilevel logistic regression analyses were conducted to identify demographic and geographic disparities in PARC use, controlling for illness severity/comorbidities, hospital characteristics, and PARC supply. Interactions among race, socioeconomic, and geographic variables were explored.

Results: Considering PARC as a continuum from more to less intensive care in regard to hours of rehabilitation per day (e.g., IRF→SNF→HH→no HH), the uninsured received less intensive care in all 3 models. Individuals receiving Medicaid and those of lower socioeconomic status received less intensive care in the HH versus no HH and SNF versus IRF models. Individuals living in rural areas received less intensive care in the institution versus home and HH versus no HH models. The effect of race was modified by insurance and by state. In most instances, minorities received less intensive care. PARC use varied by hospital.

Conclusion: Efforts to further understand the reasons behind these disparities and their effect on outcomes are needed.

Copyright © 2011 by the American College of Rheumatology.

Figures

Figure 1

Creation of Final Sample

Figure 2

Conceptual Model