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

LATEST ARTICLES
SEARCH INDEX
SUGGEST ARTICLE
THE OSI COLLECTIONS
ABOUT THE OSI

OSI STATISTICS

Total abstracts indexed:
528
Audio abstracts:
101
Open access articles:
468
Pending review:
107
Annotations added:
2
Countries represented:
90
No. of contributors:
10
Bookmarks made:
12
Specialities covered:
19

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


JournalWorld Journal of Surgery
Publication date – Apr – 2020
Authors – Niclas Rudolfson, Magdalena Gruendl, Theoneste Nkurunziza, Frederick Kateera, Kristin Sonderman, Edison Nihiwacu, Bahati Ramadhan, Robert Riviello & Bethany Hedt-Gauthier
Keywordsemergency obstetric surgery, geographical barriers, global surgery indicators, Rwanda
Open access – Yes
SpecialityEmergency surgery, Obstetrics and Gynaecology
World region Eastern Africa
Country: Rwanda
Language – English
Submitted to the One Surgery Index on May 31, 2020 at 12:41 pm
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.

OSI Number – 20451
PMID – 32274536

Public annotations on this article:
No public annotations yet