Multi-criteria decision analysis in priority setting for universal health coverage in Kenya
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The Doctor of Philosophy (DPhil) project and thesis explored the use of quantitative Multi-Criteria Decision Analysis (MCDA) in priority setting for Universal Health Coverage (UHC) in Kenya, using the example of Kenya’s UHC benefit package. The specific objectives of the DPhil project were: 1) to identify and select health interventions for consideration for inclusion in Kenya’s UHC benefit package, 2) to identify and select priority setting criteria, and 3) to determine the relative importance stakeholders place on priority setting criteria and hence prioritise health interventions into the UHC benefit package.
The thesis has six chapters. Chapter one provides the introduction while chapter two outlines a literature review on the application of MCDA in health intervention priority setting in Low- and Middle-Income Countries (LMICs). A total of 28 studies were identified. In the third chapter, an interim list of 14 health interventions to be prioritised were identified and selected using online modified Delphi technique and in person modified nominal group technique. In chapter four, six priority setting criteria (burden of disease, congruence with existing priorities, cost of intervention, effectiveness of intervention, equity, and health systems capacity) and levels were identified using a four-stage process.
Chapter five focused on prioritisation of health interventions using discrete choice modelling, where preferences of 312 stakeholders were elicited. The most important criteria were burden of disease, effectiveness of intervention, equity, congruence with existing priorities, and health systems capacity respectively. The highest ranked health interventions were provision of insecticide treated nets (ITNs) to children and pregnant women, immediate anti-retroviral therapy (ART) initiation, and Covid-19 vaccine. Nonetheless, promotion of proper diet had the lowest cost per value (hence highest ranked) among the 14 interventions when unit costs of the interventions were included in the model. In conclusion, despite the limitations of the project, MCDA is feasible to implement in Kenya.