Differences in the determinants of health insurance enrolment among working-age adults in two regions in Ghana

加纳两个地区劳动年龄成年人医疗保险参保决定因素的差异

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Abstract

BACKGROUND: Ghana's National Health Insurance Scheme (NHIS) has achieved varying levels of enrolment within the regions with different rural-urban populations with associated income inequalities. This study sought to investigate the differences in the determinants of enrolment between the Greater Accra (GAR) and Western (WR) regions of Ghana to inform the NHIS reforms. METHOD: Data from 4214 adults, 18 years and above from a household survey conducted in the two regions was analyzed. Bivariate analysis (t-test for continuous and Pearson chi-square for categorical) was performed to examine differences in respondents characteristics (socio-economic and insurance enrolment) between the two regions for the total, urban and rural samples. Logistic regression estimation was performed to establish differences in determinant of enrolment between the regions. RESULTS: Age, sex, educational level, marital status, health status and travel time to nearest health facility were identified as determinants of enrolment in both regions and among the rural and urban residents within the regions. Although the rich and richest in both regions are more likely to enroll than the poor and poorest, the odds of enrolment for the urban richest in the WR is about twice that of GAR whiles the odds of enrolment for the rural richest in the GAR is also about twice that of the WR. Those who visit public facilities in the GAR are more likely to enroll than those in WR for the total and urban samples. However, those who visit private facilities in rural communities in both regions are more likely to enroll. CONCLUSION: Differences in the NHIS enrolment between the regions is as a result of differences in socio-economic factors that are intrinsic in the regions and impact on the inhabitants' ability to afford insurance premium. Policymakers should determine NHIS premium differently at the district level based on socio-economic activities and income levels within the districts.

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