The Lancet Regional Health. Americas (Dec 2021)

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

  • 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

Journal volume & issue
Vol. 4
p. 100063

Abstract

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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.

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