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Determinants of health insurance enrolment in Ghana: evidence from three national household surveys
Author(s) -
Paola Salari,
Patricia Akweongo,
Moses Aikins,
Fabrizio Tediosi
Publication year - 2019
Publication title -
health policy and planning
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.608
H-Index - 92
eISSN - 1460-2237
pISSN - 0268-1080
DOI - 10.1093/heapol/czz079
Subject(s) - national health interview survey , marital status , subsidy , cluster (spacecraft) , logistic regression , population , socioeconomics , national health insurance , estimation , multilevel model , geography , environmental health , business , medicine , economics , statistics , mathematics , market economy , management , computer science , programming language
In 2003, Ghana implemented a National Health Insurance Scheme (NHIS) to move towards Universal Health Coverage. NHIS enrolment is mandatory for all Ghanaians, but the most recent estimates show that coverage stands under 40%. The evidence on the relationship between socio-economic characteristics and NHIS enrolment is mixed, and comes mainly from studies conducted in a few areas. Therefore, in this study we investigate the socio-economic determinants of NHIS enrolment using three recent national household surveys. We used data from the Ghanaian Demographic and Health Survey conducted in 2014, the Multiple Indicator Cluster Survey conducted in 2011 and the sixth wave of the Ghana Living Standard Survey conducted in 2012-13. Given the multilevel nature of the three databases, we use multilevel logistic regression models to estimate the probability of enrolment for women and men separately. We used three levels of analysis: geographical clusters, household and individual units. We found that education, wealth, marital status-and to some extent-age were positively associated with enrolment. Furthermore, we found that enrolment was correlated with the type of occupation. The analyses of three national household surveys highlight the challenges of understanding the complex dynamics of factors contributing to low NHIS enrolment rates. The results indicate that current policies aimed at identifying and subsidizing underprivileged population groups might insufficiently encourage health insurance enrolment.

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