Rural-urban disparities in post-acute therapy utilization: identifying hot spots of low utilization among fee-for-service Medicare beneficiaries toward informing policy and public health interventions
Principal Investigator(s): View help for Principal Investigator(s) Tiago Jesus, The Ohio State University
Version: View help for Version V1
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Project Citation:
Jesus, Tiago. Rural-urban disparities in post-acute therapy utilization: identifying hot spots of low utilization among fee-for-service Medicare beneficiaries toward informing policy and public health interventions. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2025-06-19. https://doi.org/10.3886/E233575V1
Project Description
Summary:
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This project has two aims, each one described below.
Aim 1: To quantify rural-urban disparities in rehabilitation therapy utilization (IRFs/ SNFs/ HHAs) among FFS Medicare beneficiaries (2021) and evaluate their change over time (2013-2021). Hypothesis 1: Rural Fee For Service (FFS) Medicare beneficiaries had lower therapy utilization than urban counterparts in 2021. Hypothesis 2: Rural disparities have been stagnant or increased as opposed to significantly reduced over time (2013-2021), stratified for the pre- (2013-2019) and post-pandemic (2020-2021) times. We will use hierarchical linear multiple regressions. Dependent variable: counties’ therapy utilization rate for IRFs, SNFs, and HHAs combined. Independent variable: rural area, per two indicators: a) rural residency of FFS beneficiaries b) rural county gradient. Covariates: 1) FFS beneficiaries’ characteristics; 2) FFS Medicare expenditures; 3) counties’ disability statistics, e.g., poverty; 4) community-level health, health access and social determinants of health; and 6) regions and states. The significance of the interaction between years and rurality will be tested.
Aim 2: To build interactive, user-centered maps of rehabilitation therapy utilization (IRFs / SNFs / HHAs), identifying hot spots of low utilization (in 2021) and their evolving trends (2013-2021). A GIS (ArcGIS Pro) will be used to spatiotemporally analyze the data used in the Aim 1. First, we will develop choropleth maps: gradients of county-level utilization rates, intersected with rural areas. Second, hot spot analyses (statistical spatial clustering) will map clusters of counties with low utilization. Third, a spatiotemporal, emerging hot spot analysis (2013-2021) will map areas with up to eight types of time-trends such as those showing an intensifying or persistent low utilization. The spatiotemporal analysis will be also stratified for the pre- (2013-2019) and post-pandemic (2020-2021) time periods. All the maps, with customizable options, will be shared online for public access. An Advisory Group of target end-users (e.g., disability advocates, public health agents) will provide input throughout to design the maps’ attributes and refine them after beta testing
Aim 1: To quantify rural-urban disparities in rehabilitation therapy utilization (IRFs/ SNFs/ HHAs) among FFS Medicare beneficiaries (2021) and evaluate their change over time (2013-2021). Hypothesis 1: Rural Fee For Service (FFS) Medicare beneficiaries had lower therapy utilization than urban counterparts in 2021. Hypothesis 2: Rural disparities have been stagnant or increased as opposed to significantly reduced over time (2013-2021), stratified for the pre- (2013-2019) and post-pandemic (2020-2021) times. We will use hierarchical linear multiple regressions. Dependent variable: counties’ therapy utilization rate for IRFs, SNFs, and HHAs combined. Independent variable: rural area, per two indicators: a) rural residency of FFS beneficiaries b) rural county gradient. Covariates: 1) FFS beneficiaries’ characteristics; 2) FFS Medicare expenditures; 3) counties’ disability statistics, e.g., poverty; 4) community-level health, health access and social determinants of health; and 6) regions and states. The significance of the interaction between years and rurality will be tested.
Aim 2: To build interactive, user-centered maps of rehabilitation therapy utilization (IRFs / SNFs / HHAs), identifying hot spots of low utilization (in 2021) and their evolving trends (2013-2021). A GIS (ArcGIS Pro) will be used to spatiotemporally analyze the data used in the Aim 1. First, we will develop choropleth maps: gradients of county-level utilization rates, intersected with rural areas. Second, hot spot analyses (statistical spatial clustering) will map clusters of counties with low utilization. Third, a spatiotemporal, emerging hot spot analysis (2013-2021) will map areas with up to eight types of time-trends such as those showing an intensifying or persistent low utilization. The spatiotemporal analysis will be also stratified for the pre- (2013-2019) and post-pandemic (2020-2021) time periods. All the maps, with customizable options, will be shared online for public access. An Advisory Group of target end-users (e.g., disability advocates, public health agents) will provide input throughout to design the maps’ attributes and refine them after beta testing
Funding Sources:
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National Institute on Disability, Independent Living, and Rehabilitation Research (90SFGE0046)
Scope of Project
Subject Terms:
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Rural;
Rehabilitation;
Utilization;
Post-acute care;
geographic information systems
Geographic Coverage:
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USA, nationwide
Time Period(s):
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1/1/2013 – 12/31/2022
Collection Date(s):
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8/1/2023 – 9/1/2024
Universe:
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Public domain Part A postacute therapy minutes for Medicare Fee-For-Service Beneficiaries.
Data Type(s):
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aggregate data
Collection Notes:
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All the data here used and aggregated at the county and state level are derived from public domain data.
Methodology
Response Rate:
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NA
Sampling:
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NA
Data Source:
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Source for the main variable: Post-Acute Care Public Use Files (PAC PUFs) from the Centers for Medicare & Medicaid Services (CMS)
Collection Mode(s):
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other
Scales:
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NA
Weights:
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The utilization data was adjusted for the Hierarchical Condition Category (HCC) that CMS uses to predict patient healthcare costs
Unit(s) of Observation:
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Minutes per fee for service beneficiary
Geographic Unit:
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County and State
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