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Predictors of Community-Based Health Insurance in Ethiopia via Multilevel Mixed-Effects Modelling: Evidence from the 2019 Ethiopia Mini Demography and Health Survey

BACKGROUND: The World Health Organization has endorsed a community-based health insurance scheme (CBHIS) as a shared financing plan to improve access to health services and ensure universal coverage of the healthcare delivery system. Such a contributory scheme is the most likely option to provide he...

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Detalles Bibliográficos
Autor principal: Teshome Bekele, Wondesen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Dove 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9391937/
https://www.ncbi.nlm.nih.gov/pubmed/35996638
http://dx.doi.org/10.2147/CEOR.S368925
Descripción
Sumario:BACKGROUND: The World Health Organization has endorsed a community-based health insurance scheme (CBHIS) as a shared financing plan to improve access to health services and ensure universal coverage of the healthcare delivery system. Such a contributory scheme is the most likely option to provide health insurance coverage when governments cannot offer direct health care support. Despite improvements in access to current healthcare services, Ethiopia’s healthcare delivery remained low, owing to the country’s underdeveloped healthcare finance system. As a result, the present study assessed CBHIS coverage and its predictors in Ethiopia at the individual and community level. METHODS: The availability of CBHIS was checked via a criterion: at least one of the cluster respondents had to be enrolled in CBHIS. This study was based on secondary data from the Ethiopia Mini Demography and Health Survey (EMDHS) 2019 and included 7724 respondents. The study population was described using percentage and frequency. Four multilevel mixed-effects logistic regression modelling stages were performed to control for variations due to heterogeneity across clusters, and determinant predictors of CBHIS enrollment were outplayed. RESULTS: The prevalence of CBHIS enrollment in Ethiopia was 33.13%. Rural residents were 3.218 times (AOR = 3.218; 95% CI: 1.521, 6.809), male household heads were 1.574 times (AOR = 1.574, 95% CI: 1.105, 2.241), getting funds from the safety net program were times 2.062 (AOR = 2.062, 95% CI: 1.297, 3.279), attending the primary educational level was 1.686 times (AOR = 1.686, 95% CI: 1.007, 2.821), bank accounts were 1.373 times (AOR = 1.373, 95% CI: 1.052, 1.792), and wealth index was 1.356 times (AOR = 1.356, 95% CI: 1.001, 1.838) more likely associated with CBHIS coverage, whereas the regions, the other religions, and women aged 20–24 had lower odds of CBHIS coverage. CONCLUSION: In Ethiopia, regional healthcare expenditure per capital, religious affiliation, women age range, residents, sex of household head, funds from the safety net program, formal educational level, and having bank accounts were associated with community-based health insurance scheme coverage.