Estimating Catchment Populations of Global Health Radiology Outreach Using Geographic Information Systems Analysis.

J Am Coll Radiol

Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins Hospital, Baltimore, Maryland; Manager, GIS Research and Medical Hybrid Airship Programs, RAD-AID International, Chevy Chase, Maryland. Electronic address:

Published: January 2022

AI Article Synopsis

  • - The study aimed to create and test GIS methods for analyzing and quantifying patient populations served by a global health organization, RAD-AID International, across 78 medical facilities in 32 countries.
  • - Using constraints like driving and walking time along with a circular radius, GIS analyzed population data combined with demographic statistics from the World Health Organization, revealing significant findings about served populations' size and health metrics.
  • - The results indicated that the total populations served varied significantly under different constraints, with median life expectancy and child mortality rates provided, suggesting the GIS method is valuable for global health outreach planning and resource allocation.

Article Abstract

Purpose: The purpose of this study was to design, develop, and test geographic information systems (GIS) analytic methods for quantifying and characterizing catchment populations across all sites served by a radiology global health organization.

Methods: The analysis included populations served by 78 low-resource medical facilities in 32 countries partnered with radiology nonprofit organization, RAD-AID International. Three constraints were used to approximate patient catchment areas: (1) 1-hour driving time, (2) 1-hour walking time, and (3) 10-mile circular radius. GIS calculated populations within each constraint using publicly available geospatial input databases, including a global digital elevation model, population and land cover data, and road locations from OpenStreetMap. Demographic and health data from the World Health Organization were incorporated to provide further characteristics of covered populations.

Results: The total populations served by all RAD-AID sites as measured by driving time, walking time, and 10-mile radius were 189,241,193 (47.8% female), 26,190,117 (48.7% female), and 110,884,095 (48.1% female), respectively. For individual locations, median population within 1-hour driving time was 1,795,977 (range: 8,742-30,630,800), with an average life expectancy of 68.4 ± 5.8 years. Median child mortality before age 5 was 3.8% (range: 0.9%-8.3%), and median prevalence of human immunodeficiency virus infection was 3.1% (range: 0.7%-10.9%).

Conclusion: In this study, GIS provided a robust multisite analysis for estimating the potential global population reached by an international radiology outreach organization with targeted individual site measurements. Given heightened needs to accurately characterize global outreach populations, this GIS-based approach may be useful for analysis, outreach planning, and resource allocation among global health organizations.

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Source
http://dx.doi.org/10.1016/j.jacr.2021.09.024DOI Listing

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