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Trop Med Int Health ; 18(1): 18-26, 2013 Jan.
Article in English | MEDLINE | ID: mdl-23279379

ABSTRACT

OBJECTIVES: To show the utility of combining routinely collected data with geographic location using a Geographic Information System (GIS) in order to facilitate a data-driven approach to identifying potential gaps in access to emergency obstetric care within a rural Rwandan health district. METHODS: Total expected births in 2009 at sub-district levels were estimated using community health worker collected population data. Clinical data were extracted from birth registries at eight health centres (HCs) and the district hospital (DH). C-section rates as a proportion of total expected births were mapped by cell. Peri-partum foetal mortality rates per facility-based births, as well as the rate of uterine rupture as an indication for C-section, were compared between areas of low and high C-section rates. RESULTS: The lowest C-section rates were found in the more remote part of the hospital catchment area. The sector with significantly lower C-section rates had significantly higher facility-based peri-partum foetal mortality and incidence of uterine rupture than the sector with the highest C-section rates (P < 0.034). CONCLUSIONS: This simple approach for geographic monitoring and evaluation leveraging existing health service and GIS data facilitated evidence-based decision making and represents a feasible approach to further strengthen local data-driven decisions for resource allocation and quality improvement.


Subject(s)
Cesarean Section/statistics & numerical data , Emergency Medical Services/standards , Geographic Information Systems/statistics & numerical data , Health Services Accessibility , Health Services Research/methods , Maternal Health Services/standards , Pregnancy Complications/epidemiology , Adult , Emergency Medical Services/statistics & numerical data , Female , Fetal Mortality , Health Services Needs and Demand , Hospitals , Humans , Incidence , Maternal Health Services/statistics & numerical data , Pregnancy , Quality Improvement , Research Design , Resource Allocation , Rural Health Services/standards , Rural Health Services/statistics & numerical data , Rural Population , Rwanda/epidemiology , Uterine Rupture/epidemiology
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