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Emergency Care Sensitive Conditions in Brazil: A Geographic Information System Approach to Timely Hospital Access
BACKGROUND: The benefits of treatment for many conditions are time dependent. The burden of these emergency care sensitive conditions (ECSCs) is especially high in low- and middle-income countries. Our objective was to analyze geospatial trends in ECSCs and characterize regional disparities in acces...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9903578/ https://www.ncbi.nlm.nih.gov/pubmed/36776707 http://dx.doi.org/10.1016/j.lana.2021.100063 |
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author | Isaacson, Julia Elizabeth Joiner, Anjni Patel Kozhumam, Arthi Shankar Caruzzo, Nayara Malheiros de Andrade, Luciano Iora, Pedro Henrique Costa, Dalton Breno Vissoci, Bianca Maria Sartori, Marcos Luiggi Lemos Rocha, Thiago Augusto Hernandes Vissoci, Joao Ricardo Nickenig |
author_facet | Isaacson, Julia Elizabeth Joiner, Anjni Patel Kozhumam, Arthi Shankar Caruzzo, Nayara Malheiros de Andrade, Luciano Iora, Pedro Henrique Costa, Dalton Breno Vissoci, Bianca Maria Sartori, Marcos Luiggi Lemos Rocha, Thiago Augusto Hernandes Vissoci, Joao Ricardo Nickenig |
author_sort | Isaacson, Julia Elizabeth |
collection | PubMed |
description | BACKGROUND: The benefits of treatment for many conditions are time dependent. The burden of these emergency care sensitive conditions (ECSCs) is especially high in low- and middle-income countries. Our objective was to analyze geospatial trends in ECSCs and characterize regional disparities in access to emergency care in Brazil. METHODS: From publicly available datasets, we extracted data on patients assigned an ECSC-related ICD-10 code and on the country’s emergency facilities from 2015-2019. Using ArcGIS, OpenStreetMap, and WorldPop, we created catchment areas corresponding to 180 minutes of driving distance from each hospital. We then used ArcGIS to characterize space-time trends in ECSC admissions and to complete an Origin-Destination analysis to determine the path from household to closest hospital. FINDINGS: There were 1362 municipalities flagged as “hot spots,” areas with a high volume of ECSCs. Of those, 69.7% were more than 180 minutes (171 km) from the closest emergency facility. These municipalities were primarily located in the states of Minas Gerais, Bahia, Espiríto Santo, Tocantins, and Amapá. In the North region, only 69.1% of the population resided within 180 minutes of an emergency hospital. INTERPRETATIONS: Significant geographical barriers to accessing emergency care exist in certain areas of Brazil, especially in peri-urban areas and the North region. One limitation of this approach is that geolocation was not possible in some areas and thus we are likely underestimating the burden of inadequate access. Subsequent work should evaluate ECSC mortality data. FUNDING: This study was funded by the Duke Global Health Institute Artificial Intelligence Pilot Project. |
format | Online Article Text |
id | pubmed-9903578 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-99035782023-02-10 Emergency Care Sensitive Conditions in Brazil: A Geographic Information System Approach to Timely Hospital Access Isaacson, Julia Elizabeth Joiner, Anjni Patel Kozhumam, Arthi Shankar Caruzzo, Nayara Malheiros de Andrade, Luciano Iora, Pedro Henrique Costa, Dalton Breno Vissoci, Bianca Maria Sartori, Marcos Luiggi Lemos Rocha, Thiago Augusto Hernandes Vissoci, Joao Ricardo Nickenig Lancet Reg Health Am Research Paper BACKGROUND: The benefits of treatment for many conditions are time dependent. The burden of these emergency care sensitive conditions (ECSCs) is especially high in low- and middle-income countries. Our objective was to analyze geospatial trends in ECSCs and characterize regional disparities in access to emergency care in Brazil. METHODS: From publicly available datasets, we extracted data on patients assigned an ECSC-related ICD-10 code and on the country’s emergency facilities from 2015-2019. Using ArcGIS, OpenStreetMap, and WorldPop, we created catchment areas corresponding to 180 minutes of driving distance from each hospital. We then used ArcGIS to characterize space-time trends in ECSC admissions and to complete an Origin-Destination analysis to determine the path from household to closest hospital. FINDINGS: There were 1362 municipalities flagged as “hot spots,” areas with a high volume of ECSCs. Of those, 69.7% were more than 180 minutes (171 km) from the closest emergency facility. These municipalities were primarily located in the states of Minas Gerais, Bahia, Espiríto Santo, Tocantins, and Amapá. In the North region, only 69.1% of the population resided within 180 minutes of an emergency hospital. INTERPRETATIONS: Significant geographical barriers to accessing emergency care exist in certain areas of Brazil, especially in peri-urban areas and the North region. One limitation of this approach is that geolocation was not possible in some areas and thus we are likely underestimating the burden of inadequate access. Subsequent work should evaluate ECSC mortality data. FUNDING: This study was funded by the Duke Global Health Institute Artificial Intelligence Pilot Project. Elsevier 2021-09-10 /pmc/articles/PMC9903578/ /pubmed/36776707 http://dx.doi.org/10.1016/j.lana.2021.100063 Text en © 2021 The Author(s). Published by Elsevier Ltd. https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Research Paper Isaacson, Julia Elizabeth Joiner, Anjni Patel Kozhumam, Arthi Shankar Caruzzo, Nayara Malheiros de Andrade, Luciano Iora, Pedro Henrique Costa, Dalton Breno Vissoci, Bianca Maria Sartori, Marcos Luiggi Lemos Rocha, Thiago Augusto Hernandes Vissoci, Joao Ricardo Nickenig Emergency Care Sensitive Conditions in Brazil: A Geographic Information System Approach to Timely Hospital Access |
title | Emergency Care Sensitive Conditions in Brazil: A Geographic Information System Approach to Timely Hospital Access |
title_full | Emergency Care Sensitive Conditions in Brazil: A Geographic Information System Approach to Timely Hospital Access |
title_fullStr | Emergency Care Sensitive Conditions in Brazil: A Geographic Information System Approach to Timely Hospital Access |
title_full_unstemmed | Emergency Care Sensitive Conditions in Brazil: A Geographic Information System Approach to Timely Hospital Access |
title_short | Emergency Care Sensitive Conditions in Brazil: A Geographic Information System Approach to Timely Hospital Access |
title_sort | emergency care sensitive conditions in brazil: a geographic information system approach to timely hospital access |
topic | Research Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9903578/ https://www.ncbi.nlm.nih.gov/pubmed/36776707 http://dx.doi.org/10.1016/j.lana.2021.100063 |
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