Cold spot s of postacute rehabilitation therapy delivery among Original Medicare beneficiaries across the United States: Statistical spatial clustering analysis

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Abstract This study aims to map significant cold spots of postacute rehabilitation therapy delivery rates for Original Medicare beneficiaries in the U.S. and determine the prevalence of those cold spots in rural areas. Statistical spatial clustering of postacute therapy delivery rates was conducted in ArcGIS Pro using hot and cold spot analyses (Getis-Ord Gi*). County-level therapy delivery volume was defined as the total minutes of physical, occupational, and speech therapy provided by skilled nursing facilities (SNFs), home health agencies (HHAs), and inpatient rehabilitation facilities (IRFs). Therapy delivery rates were then computed as minutes per Original Medicare beneficiary at the county level and adjusted using a county-level Hierarchical Condition Category risk score. Spatial clustering identified cold spots (statistically significant clusters of low rates) and hot spots (clusters of high rates). We also computed the proportion of cold spots in rural counties and the relative percentage difference compared to the national rural county baseline, using two rural classification systems. Identified cold spots varied by provider type. For SNFs, they were notably identified in the Mountain and West North Central US divisions. For HHAs, cold spots appeared across more U.S. Census Divisions, including areas (e.g., Kentucky, Indiana, southern Illinois) where SNFs showed hot spots . Cold spots were more prevalent in rural —and especially in small rural —counties across all provider types. In rural counties, cold spot rates were 42.8% to 71.5% higher than the rural county baseline. In small rural counties, differences were larger, at 69.1% to 95.5% higher. Concluding, cold spots of postacute therapy delivery varied across the continental U.S. by provider type but were more prevalent in rural and especially in rural counties with smaller population size ─ across provider types. Identifying these cold-spot locations may support geographically targeted policy responses and the development of alternative service-delivery models in underserved areas.

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