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Emergency Care Sensitive Conditions in Brazil: A Geographic Information System Approach to Timely Hospital Access

Authors :
Julia Elizabeth Isaacson
Anjni Patel Joiner
Arthi Shankar Kozhumam
Nayara Malheiros Caruzzo
Luciano de Andrade
Pedro Henrique Iora
Dalton Breno Costa
Bianca Maria Vissoci
Marcos Luiggi Lemos Sartori
Thiago Augusto Hernandes Rocha
Joao Ricardo Nickenig Vissoci
Source :
The Lancet Regional Health. Americas, Vol 4, Iss , Pp 100063- (2021)
Publication Year :
2021
Publisher :
Elsevier, 2021.

Abstract

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.

Details

Language :
English
ISSN :
2667193X
Volume :
4
Issue :
100063-
Database :
Directory of Open Access Journals
Journal :
The Lancet Regional Health. Americas
Publication Type :
Academic Journal
Accession number :
edsdoj.99c467f6663446da88e6285dcc3bdefa
Document Type :
article
Full Text :
https://doi.org/10.1016/j.lana.2021.100063