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Assessing the feasibility of community health insurance in Uganda: A mixed-methods exploratory analysis
M Biggeri1, M Nannini1, G Putoto2
1Department of Economics and Management, University of Florence, Florence, Italy.
Abstract:
Community health insurance (CHI) aims to provide financial protection and facilitate health care access among poor rural populations. Given common operational challenges that hamper the full development of the scheme, there is need to undertake systematic feasibility studies. These are scarce in the literature and usually they do not provide a comprehensive analysis of the local context. The present research intends to adopt a mixed-methods approach to assess ex-ante the feasibility of CHI. In particular, eight preconditions are proposed to inform the viability of introducing the micro insurance. A case study located in rural northern Uganda is presented to test the effectiveness of the mixed-methods procedure for the feasibility purpose. A household survey covering 180 households, 8 structured focus group discussions, and 40 key informant interviews were performed between October and December 2016 in order to provide a complete and integrated analysis of the feasibility preconditions. Through the data collected at the household level, the population health seeking behaviours and the potential insurance design were examined; econometric analyses were carried out to investigate the perception of health as a priority need and the willingness to pay for the scheme. The latter component, in particular, was analysed through a contingent valuation method. The results validated the relevant feasibility preconditions. Econometric estimates demonstrated that awareness of catastrophic health expenditures and the distance to the hospital play a critical influence on household priorities and willingness to pay. Willingness is also significantly affected by socio-economic status and basic knowledge of insurance principles. Overall, the mixed-methods investigation showed that a comprehensive feasibility analysis can shape a viable CHI model to be implemented in the local context.
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