Determinants of community-based health insurance implementation in west Gojjam zone, Northwest Ethiopia: a community based cross sectional study design

Abstract

Background In most developing countries, healthcare cost is mainly paid at the time of sickness and out-of-pocket at the point of service delivery which potentially could inhibit access . The total economic cost of illness for households is also estimated to be frequently above 10% of household income which is categorized as catastrophic. The purpose of this study was to assess factors that determine decisions to join the community based health insurance in West Gojjam zone. Methods A community based cross sectional survey was conducted to collect data from 690 household heads using a multistage sampling technique. A binary logistic regression was used to identify the determinants of household decisions for CBHI enrollment. Results Out of the participants, 58% were CBHI members. Besides, family size (AOR = 1.17; CI = 1.02–1.35), average health status (AOR = .380; CI = .179–.805), chronic disease (AOR = 3.42; CI = 1.89–6.19); scheme benefit package adequacy (AOR = 2.17; CI = 1.20–3.93), perceived health service quality (AOR = 3.69; CI = 1.77–7.69), CBHI awareness (AOR = 4.90; CI = 1.65–14.4); community solidarity (AOR = 3.77; CI = 2.05–6.92) and wealth (AOR = 3.62; CI = 1.67–7.83) were significant determinant factors for enrolment in the community based health insurance scheme. Conclusion CBHI awareness, family health status, community solidarity, quality of service of health institutions, and wealth were major factors that most determine the household decisions to enroll in the system. Therefore, in-depth and sustainable awareness creation programs on the scheme; stratified premium- based on economic status of households; incorporation of social capital factors, particularly building community solidarity in the scheme implementation are vital to enhance sustainable enrollment. As perceived family health status and the existence of chronic disease were also found significant determinants of enrollment, the Government might have to look for options to make the scheme mandatory.

Factors Associated with Non-Enrollment in National Health Insurance Scheme in Kaski District, Nepal

“…This study finding showed that the odds of non-enrollment was higher among those household who perceived their family health status as a good. This result is consistent with the finding of Kenya and Ethiopia (Mirach et al, 2019;Otieno et al, 2019). This is obvious that if household members do not have any health problems, they would never prefer to be enrolled until and unless they have severe health problems and may have a thinking that they should no waste money unnecessarily.…”

“…Facts from various studies have shown the positive association between socio-economic status and non-enrollment (Ghimire et al, 2019;Jehu-Appiah et al, 2011;Mirach et al, 2019;Paudel, 2019). The present study also showed that non-enrollment increases with the decreasing socio-economic status in the society.…”

“…However present study reveals contrast result. Correspondingly previous literatures showed having no chronic illness in the family increases non-enrollment (Ghimire et al, 2019;Mirach et al, 2019;Paudel, 2019). But this study didn't found any significant association.…”

<p>Community-Based Health Insurance Membership Dropout Rate and Associated Factors in Dera District, Northwest Ethiopia</p>

“…A structured pretested questionnaire was used prepared by reviewing different pieces of literature. 21,[27][28][29][30] Data were collected through face-to-face interviews. The questionnaire was initially prepared in English, and it was translated into Amharic and then translated back to English to check for any inconsistencies or distortions in the meaning of words and concepts through language experts.…”

Health insurance awareness and its uptake in India: a systematic review protocol

“…1 People living in the LMICs rely majorly on out-of-pocket payments as the prime source for managing healthcare expenses, that results in a massive demand for services and financial burden of households (usually catastrophic), which in turn leads to impoverishment. [1][2][3][4][5] It is projected that every year approximately 150 million people experience financial catastrophe, by spending more than 40% on health expenses other than food. 6 Families generally spend more than 10% of the household income on illness-related expenses, due to which other household expenses are affected.…”