Cargando…
Teaming up census and patient data to delineate fine-scale hospital service areas and identify geographic disparities in hospital accessibility
The number of hospital beds per capita, an important measure of equity in healthcare availability and resource allocation, was found to vary across geographic areas in many countries, including the USA. The hospital service areas (HSAs) have proven to be more meaningful spatial units for studying he...
Autores principales: | , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6598966/ https://www.ncbi.nlm.nih.gov/pubmed/31254122 http://dx.doi.org/10.1007/s10661-019-7413-4 |
_version_ | 1783430863500869632 |
---|---|
author | Jia, Peng Shi, Xinyu Xierali, Imam M. |
author_facet | Jia, Peng Shi, Xinyu Xierali, Imam M. |
author_sort | Jia, Peng |
collection | PubMed |
description | The number of hospital beds per capita, an important measure of equity in healthcare availability and resource allocation, was found to vary across geographic areas in many countries, including the USA. The hospital service areas (HSAs) have proven to be more meaningful spatial units for studying health-seeking behaviors and health resource allocation and service utilization. However, when evaluating the geographical balance in ratios of hospital beds to population (HBtP), no existing HSA delineation methods directly consider the underlying population distribution. Using Geographic Information Systems (GIS), this study incorporated the State Inpatient Database with census data to develop a population-based HSA delineation method. The census-derived HSAs were produced for Florida and were validated by aggregating and comparing with the traditional flow-based HSAs. The difference in current ratios of HBtP between the most over- and under-served HSAs was approximately 60 times. Significant clusters of high and low ratios were found in Miami and Jacksonville metropolitan areas, respectively. Such results may be of interest to relevant stakeholders and contribute to planning and optimization of hospital resource allocation and healthcare policy-making. Furthermore, the discovery of a strong correlation between the numbers of hospital discharges and the population at ZIP code level holds a remarkable potential for affordable population estimation, especially in non-census years. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s10661-019-7413-4) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-6598966 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Springer International Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-65989662019-07-23 Teaming up census and patient data to delineate fine-scale hospital service areas and identify geographic disparities in hospital accessibility Jia, Peng Shi, Xinyu Xierali, Imam M. Environ Monit Assess Article The number of hospital beds per capita, an important measure of equity in healthcare availability and resource allocation, was found to vary across geographic areas in many countries, including the USA. The hospital service areas (HSAs) have proven to be more meaningful spatial units for studying health-seeking behaviors and health resource allocation and service utilization. However, when evaluating the geographical balance in ratios of hospital beds to population (HBtP), no existing HSA delineation methods directly consider the underlying population distribution. Using Geographic Information Systems (GIS), this study incorporated the State Inpatient Database with census data to develop a population-based HSA delineation method. The census-derived HSAs were produced for Florida and were validated by aggregating and comparing with the traditional flow-based HSAs. The difference in current ratios of HBtP between the most over- and under-served HSAs was approximately 60 times. Significant clusters of high and low ratios were found in Miami and Jacksonville metropolitan areas, respectively. Such results may be of interest to relevant stakeholders and contribute to planning and optimization of hospital resource allocation and healthcare policy-making. Furthermore, the discovery of a strong correlation between the numbers of hospital discharges and the population at ZIP code level holds a remarkable potential for affordable population estimation, especially in non-census years. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s10661-019-7413-4) contains supplementary material, which is available to authorized users. Springer International Publishing 2019-06-28 2019 /pmc/articles/PMC6598966/ /pubmed/31254122 http://dx.doi.org/10.1007/s10661-019-7413-4 Text en © The Author(s) 2019 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. |
spellingShingle | Article Jia, Peng Shi, Xinyu Xierali, Imam M. Teaming up census and patient data to delineate fine-scale hospital service areas and identify geographic disparities in hospital accessibility |
title | Teaming up census and patient data to delineate fine-scale hospital service areas and identify geographic disparities in hospital accessibility |
title_full | Teaming up census and patient data to delineate fine-scale hospital service areas and identify geographic disparities in hospital accessibility |
title_fullStr | Teaming up census and patient data to delineate fine-scale hospital service areas and identify geographic disparities in hospital accessibility |
title_full_unstemmed | Teaming up census and patient data to delineate fine-scale hospital service areas and identify geographic disparities in hospital accessibility |
title_short | Teaming up census and patient data to delineate fine-scale hospital service areas and identify geographic disparities in hospital accessibility |
title_sort | teaming up census and patient data to delineate fine-scale hospital service areas and identify geographic disparities in hospital accessibility |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6598966/ https://www.ncbi.nlm.nih.gov/pubmed/31254122 http://dx.doi.org/10.1007/s10661-019-7413-4 |
work_keys_str_mv | AT jiapeng teamingupcensusandpatientdatatodelineatefinescalehospitalserviceareasandidentifygeographicdisparitiesinhospitalaccessibility AT shixinyu teamingupcensusandpatientdatatodelineatefinescalehospitalserviceareasandidentifygeographicdisparitiesinhospitalaccessibility AT xieraliimamm teamingupcensusandpatientdatatodelineatefinescalehospitalserviceareasandidentifygeographicdisparitiesinhospitalaccessibility |