Validating the Global Surgery Geographical Accessibility Indicator : Differences in Modeled Versus Patient-Reported Travel Times
(2020) In World Journal of Surgery 44(7). p.2123-2130- 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... (More)
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.
(Less)
- author
- Rudolfson, Niclas LU ; Gruendl, Magdalena ; Nkurunziza, Theoneste ; Kateera, Frederick ; Sonderman, Kristin ; Nihiwacu, Edison ; Ramadhan, Bahati ; Riviello, Robert and Hedt-Gauthier, Bethany
- organization
- publishing date
- 2020-07
- type
- Contribution to journal
- publication status
- published
- subject
- in
- World Journal of Surgery
- volume
- 44
- issue
- 7
- pages
- 8 pages
- publisher
- Springer
- external identifiers
-
- scopus:85083423489
- pmid:32274536
- ISSN
- 0364-2313
- DOI
- 10.1007/s00268-020-05480-8
- language
- English
- LU publication?
- yes
- id
- 418ef894-7973-4f24-ae51-73b6be29aa6a
- date added to LUP
- 2020-05-08 14:20:37
- date last changed
- 2024-06-13 15:59:03
@article{418ef894-7973-4f24-ae51-73b6be29aa6a,
abstract = {{<p>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.</p>}},
author = {{Rudolfson, Niclas and Gruendl, Magdalena and Nkurunziza, Theoneste and Kateera, Frederick and Sonderman, Kristin and Nihiwacu, Edison and Ramadhan, Bahati and Riviello, Robert and Hedt-Gauthier, Bethany}},
issn = {{0364-2313}},
language = {{eng}},
number = {{7}},
pages = {{2123--2130}},
publisher = {{Springer}},
series = {{World Journal of Surgery}},
title = {{Validating the Global Surgery Geographical Accessibility Indicator : Differences in Modeled Versus Patient-Reported Travel Times}},
url = {{http://dx.doi.org/10.1007/s00268-020-05480-8}},
doi = {{10.1007/s00268-020-05480-8}},
volume = {{44}},
year = {{2020}},
}