Did Saving Mothers, Giving Life Expand Timely Access to Lifesaving Care in Uganda? A Spatial District-Level Analysis of Travel Time to Emergency Obstetric and Newborn Care

Abstract

A spatial analysis of facility accessibility, taking into account road networks and environmental constraints on travel, suggests that the Saving Mothers, Giving Life (SMGL) initiative increased access to emergency obstetric and neonatal care in SMGL-supported districts in Uganda. Spatial travel-time analyses can inform policy and program efforts targeting underserved populations in conjunction with the geographic distribution of maternity services.

Modeling the Impact of Traveling Time on the Utilization of Maternity Services Using Routine Health Facility Data in Siaya County, Western Kenya

“…In terms of traveling scenario, the current findings suggest that walking had the greatest negative impact on the ability of a pregnant woman to access the nearest facility offering maternity services. Although this finding was consistent with both previous and most recent studies (Ebener et al, 2015;Makanga et al, 2016;Schmitz et al, 2019), further analysis across higher level facility types like health centres and hospitals contrasted this finding that walking distance alone was enough to determine whether or not a pregnant woman reached, and thus utilized, a nearby health facility offering maternity services. A case in point is from a previous study of the correlates of utilization of skilled maternal health services in Siaya County, which revealed that poverty, low education, husband/ partners education and walking or using a bicycle to hospital were significantly associated with low utilization of skilled maternal health services (Omondi & Amolo, 2015), even if a comparable study reaffirmed that in the event high accessibility ratios overlap with low levels of utilization, it could suggest that physical accessibility may not be the main determinant of maternity services utilization and that other barriers might exist in areas like Siaya county with poor maternal health outcomes (Colston & Burgert, 2014).…”

“…between countries) than distances (Munoz & Källestål, 2012;Ray & Ebener, 2008; WHO, 2016a). AccessMod platform for instance, is a free and open source WHO developed spatial model which estimates the most efficient travel time to a health facility along established roads, walking paths and landscape barriers and has emerged as one of the most robust analytical spatial techniques applied in maternal health towards universal health coverage (UHC) (Ebener et al, 2015;Roth et al, 2016;Schmitz et al, 2019). Hence, in examining physical access to maternity health services or predicting skilled birth attendance, the application of geographic approaches and GIS to measure inequities in maternal health outcomes is critical to assess the situation and needs and guide policy decisions (Ebener et al, 2015).…”

“…In summary, the wider use of routine health facility data within the Kenyan context via robust and open source platforms like DHIS 2, may indeed provide an unprecedented opportunity for local decision makers to employ the power of existing GIS able to combine information on theoretical physical accessibility to maternity services, with more accurate and timely reporting on the numerators of the coverage for safe delivery indicators-to locate, measure and address the needs of most vulnerable pregnant women. Therefore, based on current GIS best practices from literature (Ebener & Stenberg, 2016a;Makanga, Schuurman, von Dadelszen, & Firoz, 2016;Schmitz et al, 2019), in combination with data on the actual use of available maternity services from DHIS2, the current study estimated how different transportation modes (walking and/or motorized) affected women's ability to utilize maternity health services at the ward administrative level. Thus, the urban areas population were spatially excluded and facilities were disaggregated by level of care (hospitals, health centres and dispensaries), towards a more realistic representation of the magnitude of the relationship between physical accessibility and utilization of existing maternity health services in rural Siaya County.…”

Spatial access inequities and childhood immunisation uptake in Kenya

“…The mean travel time to health facilities offering immunisation services was 40 min, with 7 % of the total population in Kenya living more than one-hour away from an immunising health facility assuming that populations use a combination of walking and motorized/cycling transport. Previous studies [ 58 , 60 , 61 ] show that using the optimistic travel scenario provides a robust analytical spatial technique to estimating travel times. However, estimates from the walking scenario are useful for highlighting limitations due to inadequacies of the road infrastructure and availability of public transport as well as evaluating travel time targets in Kenya [ 28 , 62 ].…”

Geographical Accessibility and Spatial Coverage Modelling of Public Health Care Network in Rural and Remote India.

“…However, healthcare accessibility can be augmented by systems approach embodying synergistic interventions at the community, facility and health systems level designed to decrease travel time to care and increase access to motorized transportation. (Schmitz et. al, 2019).…”