Validating the Global Surgery Geographical Accessibility Indicator: Differences in Modeled Versus Patient-Reported Travel Times

Research output: Contribution to journalArticle

Abstract

Background: Since long travel times to reach health facilities are associated with worse outcomes, geographic accessibility is one of the six core global surgery indicators; this corresponds to the second of the “Three Delays Framework,” namely “delay in reaching a health facility.” Most attempts to estimate this indicator have been based on geographical information systems (GIS) algorithms. The aim of our study was to compare GIS derived estimates to self-reported travel times for patients traveling to a district hospital in rural Rwanda for emergency obstetric care. Methods: Our study includes 664 women who traveled to undergo a Cesarean delivery in Kirehe, Rwanda. We compared self-reported travel time from home to the hospital (excluding waiting time) with GIS estimated travel times, which were computed using the World Health Organization tool AccessMod, using linear regression. Results: The majority of patients used multiple modes of transportation (walking = 48.5%, public transport = 74.2%, private transport = 2.9%, and ambulance 70.6%). Self-reported times were longer than GIS estimates by a factor of 1.49 (95% CI 1.40–1.57). Concordance was higher when the GIS model took into account that all patients in Rwanda are referred via their health center (β = 1.12; 95% CI 1.05–1.18). Conclusions: To our knowledge, in this largest to date GIS validation study for geographical access to healthcare in low- and middle-income countries, a standard GIS model was found to significantly underestimate real travel time, which likely is in part because it does not model the actual route patients are travelling. Therefore, previous studies of 2-h access to surgery will need to be interpreted with caution, and future studies should take local travelling conditions into account.

Details

Authors
  • Niclas Rudolfson
  • Magdalena Gruendl
  • Theoneste Nkurunziza
  • Frederick Kateera
  • Kristin Sonderman
  • Edison Nihiwacu
  • Bahati Ramadhan
  • Robert Riviello
  • Bethany Hedt-Gauthier
Organisations
External organisations
  • Harvard Medical School
  • Technical University of Munich
  • Partners In Health (PIH), Rwanda
Research areas and keywords

Subject classification (UKÄ) – MANDATORY

  • Public Health, Global Health, Social Medicine and Epidemiology
  • Transport Systems and Logistics
Original languageEnglish
JournalWorld Journal of Surgery
Publication statusE-pub ahead of print - 2020 Mar 31
Publication categoryResearch
Peer-reviewedYes