Estimating determinants of healthcare establishment locations with restricted federal administrative data
We model the locational determinants of nine categories of healthcare services in the contiguous United States using restricted access federal establishment data. These data enable close examination of rural health services, which are subject to suppression in publicly published data sources. After...
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| Published in | Health economics Vol. 30; no. 6; pp. 1328 - 1346 |
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| Main Authors | , , , |
| Format | Journal Article |
| Language | English |
| Published |
England
Wiley Periodicals Inc
01.06.2021
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| Subjects | |
| Online Access | Get full text |
| ISSN | 1057-9230 1099-1050 1099-1050 |
| DOI | 10.1002/hec.4242 |
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| Abstract | We model the locational determinants of nine categories of healthcare services in the contiguous United States using restricted access federal establishment data. These data enable close examination of rural health services, which are subject to suppression in publicly published data sources. After reviewing differences in public and unsuppressed restricted data and testing underlying data generation processes for each healthcare industry, including the Poisson, negative binomial, and their zero‐inflated counterparts, we estimate marginal effects for four categories of independent variables: place‐based factors, financial access, characteristics of population, and industry interdependencies. Findings show establishments are less likely to be found with high concentrations of Medicare and Medicaid recipients, while agglomerations are associated with more establishments. Nonemployer establishments serve a broader spectrum of people, but the rural poor still experience less access to health care. |
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| AbstractList | We model the locational determinants of nine categories of healthcare services in the contiguous United States using restricted access federal establishment data. These data enable close examination of rural health services, which are subject to suppression in publicly published data sources. After reviewing differences in public and unsuppressed restricted data and testing underlying data generation processes for each healthcare industry, including the Poisson, negative binomial, and their zero-inflated counterparts, we estimate marginal effects for four categories of independent variables: place-based factors, financial access, characteristics of population, and industry interdependencies. Findings show establishments are less likely to be found with high concentrations of Medicare and Medicaid recipients, while agglomerations are associated with more establishments. Nonemployer establishments serve a broader spectrum of people, but the rural poor still experience less access to health care. We model the locational determinants of nine categories of healthcare services in the contiguous United States using restricted access federal establishment data. These data enable close examination of rural health services, which are subject to suppression in publicly published data sources. After reviewing differences in public and unsuppressed restricted data and testing underlying data generation processes for each healthcare industry, including the Poisson, negative binomial, and their zero-inflated counterparts, we estimate marginal effects for four categories of independent variables: place-based factors, financial access, characteristics of population, and industry interdependencies. Findings show establishments are less likely to be found with high concentrations of Medicare and Medicaid recipients, while agglomerations are associated with more establishments. Nonemployer establishments serve a broader spectrum of people, but the rural poor still experience less access to health care.We model the locational determinants of nine categories of healthcare services in the contiguous United States using restricted access federal establishment data. These data enable close examination of rural health services, which are subject to suppression in publicly published data sources. After reviewing differences in public and unsuppressed restricted data and testing underlying data generation processes for each healthcare industry, including the Poisson, negative binomial, and their zero-inflated counterparts, we estimate marginal effects for four categories of independent variables: place-based factors, financial access, characteristics of population, and industry interdependencies. Findings show establishments are less likely to be found with high concentrations of Medicare and Medicaid recipients, while agglomerations are associated with more establishments. Nonemployer establishments serve a broader spectrum of people, but the rural poor still experience less access to health care. |
| Author | Carpenter, Craig Wesley Loveridge, Scott Van Sandt, Anders Dudensing, Rebekka |
| Author_xml | – sequence: 1 givenname: Anders orcidid: 0000-0001-8665-2357 surname: Van Sandt fullname: Van Sandt, Anders email: avansandt@tamu.edu organization: University of Wyoming – sequence: 2 givenname: Craig Wesley orcidid: 0000-0001-7511-1168 surname: Carpenter fullname: Carpenter, Craig Wesley email: ccarpenter@tamu.edu organization: Texas A&M University – sequence: 3 givenname: Rebekka surname: Dudensing fullname: Dudensing, Rebekka organization: Texas A&M University – sequence: 4 givenname: Scott orcidid: 0000-0002-8067-4819 surname: Loveridge fullname: Loveridge, Scott organization: Michigan State University |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/33745144$$D View this record in MEDLINE/PubMed |
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| SubjectTerms | central place theory demand threshold health care Health care access Health economics Health services hospital industry Medicaid Medicare microdata outpatient physician regional economic development rural health |
| Title | Estimating determinants of healthcare establishment locations with restricted federal administrative data |
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