Influence of Service Provision Readiness and Livelihood on Maternal Health Services Utilization Patterns in Kenya

Abstract

This is a study report on the relationship between Maternal Service Provision Readiness and Maternal Skilled Delivery Services Utilization using Kenya’s county level data. The report also contains the results of investigation of the relationship between nomadic livelihood and skilled delivery coverage. The broad objective was to determine if the current Maternal Services Utilization patterns across Kenya’s counties could be explained by Maternal Services Provision Readiness and Nomadic livelihoods. The study was anchored on the theories of Health Seeking Behaviour (Rebhan, 2010) and Resource Based View (Barney, 1991). Service Provision Readiness is a measure of the supply side capacity to provide quality services (WHO, 2014) while utilization is used as a measure of access. The concept of Superior Utilization was introduced to benchmark the country’s performance against sub- Saharan Africa’s MDG achievement (United Nation, 2015) using the knowledge anchored on RBT. Benchmarking has become a standard management practice. The northern Counties of Kenya, predominantly nomadic, did not register improved health outcomes generally (KHSSP II). The study sought to answer the following questions: is there regional disparity in the production and consumption of maternal health services in Kenya? Is nomadic livelihood a constraint to access? Does investment in the supply side (readiness to provide maternal services) explain maternal skilled delivery differentials across counties of Kenya? The study focused on Readiness, Livelihood and Utilization of maternal skilled delivery services. A descriptive, cross-sectional design was used. County was the unit of analysis and both multiple linear regression and binary choice methods were employed in the analysis using STATA 12 statistical software. Data source on utilization was obtained from Kenya Demographic Health Survey (2014) while Readiness data was obtained from SARAM report (Government of Kenya, 2014). These data were linked and analysed according to the study objectives to answer the above research questions. The following were the findings of the study: disparities in preparedness exist at all levels of KEPH; disparity was least in health centre preparedness (CV, 18%) and highest in hospitals (CV, 23%); Health centres readiness was the only supply side factor which could explain maternal delivery pattern(r= 0.307, p<0.05); improving health centre maternal service provision readiness increases maternal skilled delivery coverage. Changing a county from nomadic improves maternal delivery coverage and increases its predictive probability for better performance. Nomadic livelihood reduces the likelihood of a county realizing acceptable utilization levels of maternal delivery services. Achieving Secondary education level for women significantly increases the likelihood of a county realizing acceptable skilled delivery coverage by 4.9%. Demand-side factors have the most influence on maternal skilled deliveries compared to the supply-side.