Continued adherence to community-based health insurance scheme in two districts of northeast Ethiopia: application of accelerated failure time shared frailty models

在埃塞俄比亚东北部两个地区持续坚持社区健康保险计划:加速失效时间共享脆弱性模型的应用

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Abstract

BACKGROUND: The sustainability of a voluntary community-based health insurance scheme depends to a greater extent on its ability to retain members. In low- and middle-income countries, high rate of member dropout has been a great concern for such schemes. Although several studies have investigated the factors influencing dropout decisions, none of these looked into how long and why members adhere to the scheme. The purpose of this study was to determine the factors affecting time to drop out while accounting for the influence of cluster-level variables. METHODS: A community-based cross-sectional study was conducted among 1232 rural households who have ever been enrolled in two community-based health insurance schemes. Data were collected using an interviewer-administered questionnaire via a mobile data collection platform. The Kaplan-Meier estimates were used to compare the time to drop out among subgroups. To identify predictors of time to drop out, a multivariable analysis was done using the accelerated failure time shared frailty models. The degree of association was assessed using the acceleration factor (δ) and statistical significance was determined at 95% confidence interval. RESULTS: Results of the multivariable analysis revealed that marital status of the respondents (δ = 1.610; 95% CI: 1.216, 2.130), household size (δ = 1.168; 95% CI: 1.013, 1.346), presence of chronic illness (δ = 1.424; 95% CI: 1.165, 1.740), hospitalization history (δ = 1.306; 95% CI: 1.118, 1.527), higher perceived quality of care (δ = 1.322; 95% CI: 1.100, 1.587), perceived risk protection (δ = 1.218; 95% CI: 1.027, 1.444), and higher trust in the scheme (δ = 1.731; 95% CI: 1.428, 2.098) were significant predictors of time to drop out. Contrary to the literature, wealth status did not show a significant correlation with the time to drop out. CONCLUSIONS: The fact that larger households and those with chronic illness remained longer in the scheme is suggestive of adverse selection. It is needed to reconsider the premium level in line with household size to attract small size households. Resolving problems related to the quality of health care can be a cross-cutting area of ​​intervention to retain members by building trust in the scheme and enhancing the risk protection ability of the schemes.

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