Determinants of enrollment decision in the community-based health insurance, North West Ethiopia: a case-control study

Abstract

OBJECTIVE: To identify the determinants for enrollment decision in the community-based health insurance program among informal economic sector-engaged societies, North West Ethiopia. METHOD: Unmatched case-control study was conducted on 148 cases (member-to-insurance) and 148 controls (not-member-to-insurance program) from September 1 to October 30,2016. To select the villages and households, stratified then simple random sampling method was employed respectively. The data were entered in to Epi-info version 7 and exported to SPSS version 20 for analysis. Descriptive statistics, bi-variable, and multi-variable logistic regression analyses were computed to describe the study objectives and identify the determinants of enrolment decision for the insurance program. Odds ratio at 95% CI was used to describe the association between the independent and outcome variables. RESULTS: A total of 296 respondents (148 cases and 148 controls) were employed. The mean age for both cases and controls were 42 ± 11.73 and 40 ± 11.37 years respectively. Majority of respondents were males (87.2% for cases and 79% for controls). Family size between 4 and 6 (AOR = 2.26; 95% CI: 1.04, 4.89), history of illness by household (AOR = 3.24; 95% CI: 1.68, 6.24), perceived amount of membership contribution was medium (AOR = 2.3; 95% CI: 1.23, 4.26), being married (AOR = 6; 95% CI:1.43, 10.18) and trust on program (AOR = 4.79; 95% CI: 2.40, 9.55) were independent determinants for increased enrollment decision in the community-based health insurance. While, being merchant (AOR = 0.07; 95% CI: 0.09, 0.6) decreased the enrollment decision. CONCLUSION: Societies' enrollment decision to community-based health insurance program was determined by demographic, social, economic and political factors. Households with large family sizes and farmers in the informal sector should be given maximal attention for intensifying enrollment decision in the insurance program.