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Use of Fine-scale Geospatial Units and Population Data to Evaluate Access to Emergency Care

INTRODUCTION: Time to facility is a crucial element in emergency medicine (EM). Fine-scale geospatial units such as census block groups (CBG) and publicly available population datasets offer a low-cost and accurate approach to modeling geographic access to and utilization of emergency departments (E...

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Autores principales: Joyce, Katherine M., Burke, Ryan C., Veldman, Thomas J., Beeson, Michelle M., Simon, Erin L.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Department of Emergency Medicine, University of California, Irvine School of Medicine 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6225952/
https://www.ncbi.nlm.nih.gov/pubmed/30429940
http://dx.doi.org/10.5811/westjem.2018.9.38957
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author Joyce, Katherine M.
Burke, Ryan C.
Veldman, Thomas J.
Beeson, Michelle M.
Simon, Erin L.
author_facet Joyce, Katherine M.
Burke, Ryan C.
Veldman, Thomas J.
Beeson, Michelle M.
Simon, Erin L.
author_sort Joyce, Katherine M.
collection PubMed
description INTRODUCTION: Time to facility is a crucial element in emergency medicine (EM). Fine-scale geospatial units such as census block groups (CBG) and publicly available population datasets offer a low-cost and accurate approach to modeling geographic access to and utilization of emergency departments (ED). These methods are relevant to the emergency physician in evaluating patient utilization patterns, emergency medical services protocols, and opportunities for improved patient outcomes and cost utilization. We describe the practical application of geographic information system (GIS) and fine-scale analysis for EM using Ohio ED access as a case study. METHODS: Ohio ED locations (n=198), CBGs (n=9,238) and 2015 United States Census five-year American Community Survey (ACS) socioeconomic data were collected July—August 2016. We estimated drive time and distance between population-weighted CBGs and nearest ED using ArcGIS and 2010 CBG shapefiles. We examined drive times vs. ACS characteristics using multinomial regression and mapping. RESULTS: We categorized CBGs by centroid-ED travel time in minutes: <10 (73.4%; n=6,774), 10–30 (25.1%; n=2,315), and >30 (1.5%; n=141). CBGs with increased median age, Hispanic and non-Hispanic Black population, and college graduation rates had significantly decreased travel time. CBGs with increased low-income populations (adjusted odds ratio [AOR] [1.03], 95% confidence interval [CI] [1.01–1.04]) and vacant housing (AOR [1.06], 95% CI [1.05–1.08]) had increased odds of >30 minute travel time. CONCLUSION: Use of fine-scale geographic analysis and population data can be used to evaluate geographic accessibility and utilization of EDs. Methods described offer guidance to approaching questions of geographic accessibility and have numerous ED and pre-hospital applications.
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spelling pubmed-62259522018-11-14 Use of Fine-scale Geospatial Units and Population Data to Evaluate Access to Emergency Care Joyce, Katherine M. Burke, Ryan C. Veldman, Thomas J. Beeson, Michelle M. Simon, Erin L. West J Emerg Med Public Health INTRODUCTION: Time to facility is a crucial element in emergency medicine (EM). Fine-scale geospatial units such as census block groups (CBG) and publicly available population datasets offer a low-cost and accurate approach to modeling geographic access to and utilization of emergency departments (ED). These methods are relevant to the emergency physician in evaluating patient utilization patterns, emergency medical services protocols, and opportunities for improved patient outcomes and cost utilization. We describe the practical application of geographic information system (GIS) and fine-scale analysis for EM using Ohio ED access as a case study. METHODS: Ohio ED locations (n=198), CBGs (n=9,238) and 2015 United States Census five-year American Community Survey (ACS) socioeconomic data were collected July—August 2016. We estimated drive time and distance between population-weighted CBGs and nearest ED using ArcGIS and 2010 CBG shapefiles. We examined drive times vs. ACS characteristics using multinomial regression and mapping. RESULTS: We categorized CBGs by centroid-ED travel time in minutes: <10 (73.4%; n=6,774), 10–30 (25.1%; n=2,315), and >30 (1.5%; n=141). CBGs with increased median age, Hispanic and non-Hispanic Black population, and college graduation rates had significantly decreased travel time. CBGs with increased low-income populations (adjusted odds ratio [AOR] [1.03], 95% confidence interval [CI] [1.01–1.04]) and vacant housing (AOR [1.06], 95% CI [1.05–1.08]) had increased odds of >30 minute travel time. CONCLUSION: Use of fine-scale geographic analysis and population data can be used to evaluate geographic accessibility and utilization of EDs. Methods described offer guidance to approaching questions of geographic accessibility and have numerous ED and pre-hospital applications. Department of Emergency Medicine, University of California, Irvine School of Medicine 2018-11 2018-10-18 /pmc/articles/PMC6225952/ /pubmed/30429940 http://dx.doi.org/10.5811/westjem.2018.9.38957 Text en Copyright: © 2018 Joyce et al. http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed in accordance with the terms of the Creative Commons Attribution (CC BY 4.0) License. See: http://creativecommons.org/licenses/by/4.0/
spellingShingle Public Health
Joyce, Katherine M.
Burke, Ryan C.
Veldman, Thomas J.
Beeson, Michelle M.
Simon, Erin L.
Use of Fine-scale Geospatial Units and Population Data to Evaluate Access to Emergency Care
title Use of Fine-scale Geospatial Units and Population Data to Evaluate Access to Emergency Care
title_full Use of Fine-scale Geospatial Units and Population Data to Evaluate Access to Emergency Care
title_fullStr Use of Fine-scale Geospatial Units and Population Data to Evaluate Access to Emergency Care
title_full_unstemmed Use of Fine-scale Geospatial Units and Population Data to Evaluate Access to Emergency Care
title_short Use of Fine-scale Geospatial Units and Population Data to Evaluate Access to Emergency Care
title_sort use of fine-scale geospatial units and population data to evaluate access to emergency care
topic Public Health
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6225952/
https://www.ncbi.nlm.nih.gov/pubmed/30429940
http://dx.doi.org/10.5811/westjem.2018.9.38957
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