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Abstract Background Over 150 million people, mostly from low and middle-income countries (LMICs) suffer from catastrophic health expenditure (CHE) every year because of high out-of-pocket (OOP) payments. In Tanzania, OOP payments account for about a quarter of the total health expenditure. This paper compares healthcare utilization and the incidence of CHE among improved Community Health Fund (iCHF) members and non-members in central Tanzania. Methods A survey was conducted in 722 households in Bahi and Chamwino districts in Dodoma region. CHE was defined as a household health expenditure exceeding 40% of total non-food expenditure (capacity to pay). Concentration index (CI) and logistic regression were used to assess the socioeconomic inequalities in the distribution of healthcare utilization and the association between CHE and iCHF enrollment status, respectively. Results 50% of the members and 29% of the non-members utilized outpatient care in the previous month, while 19% (members) and 15% (non-members) utilized inpatient care in the previous twelve months. The degree of inequality for utilization of inpatient care was higher (insured, CI = 0.38; noninsured CI = 0.29) than for outpatient care (insured, CI = 0.09; noninsured CI = 0.16). Overall, 15% of the households experienced CHE, however, when disaggregated by enrollment status, the incidence of CHE was 13% and 15% among members and non-members, respectively. The odds of iCHF-members incurring CHE were 0.4 times less compared to non-members (OR = 0.41, 95%CI: 0.27–0.63). The key determinants of CHE were iCHF enrollment status, health status, socioeconomic status, chronic illness, and the utilization of inpatient and outpatient care. Conclusion The utilization of healthcare services was higher while the incidence of CHE was lower among households enrolled in the iCHF insurance scheme relative to those not enrolled. More studies are needed to establish the reasons for the relatively high incidence of CHE among iCHF members and the low degree of healthcare utilization among households with low socioeconomic status.

Lower-middle income countries (LMICs) have invested significant effort into expanding insurance coverage as a means of improving access to health care. However, it has proven challenging to fulfill these ambitions. This study investigates to what extent variables associated with the enrollment decision (stay never-insured or enroll) differ from variables associated with the dropout decision (stay insured or drop out). A cross-sectional survey that included 722 households from rural districts in Tanzania was conducted and multinomial logistic regressions were performed to determine the associations between independent variables and membership status (never-insured, dropouts, or currently insured). Both the decision to enrollment and the decision to drop out were significantly associated with the presence of chronic disease and perceptions about the quality of services provided, insurance scheme management, and traditional healers. The effect of other variables, such as age, gender and educational level of the household head, household income, and perceptions about premium affordability and benefit-premium ratios, varied across the two groups. To improve voluntary health insurance coverage, policymakers must simultaneously increase the enrollment rate among the never-insured and reduce the dropout rate among the insured. Our conclusions suggest that policies to increase insurance scheme enrollment rates should differ for the two uninsured groups.

Abstract Background Several countries including Tanzania, have established voluntary non-profit insurance schemes, commonly known as community-based health insurance schemes (CBHIs), that typically target rural populations and the informal sector. This paper considers the importance of household perceptions towards CBHIs in Tanzania and their role in explaining the enrolment decision of households. Methods This was a cross-sectional household survey that involved 722 households located in Bahi and Chamwino districts in the Dodoma region. A three-stage sampling procedure was used, and the data were analyzed using both factor analysis (FA) and principal component analysis (PCA). Statistical tests such as Bartlett’s test of sphericity, Kaiser-Meyer-Olkin (KMO) for sampling adequacy, and Cronbach’s alpha test for internal consistency and scale reliability were performed to examine the suitability of the data for PCA and FA. Finally, multivariate logistic regressions were run to determine the associations between the identified factors and the insurance enrolment status. Results The PCA identified seven perception factors while FA identified four factors. The quality of healthcare services, preferences (social beliefs), and accessibility to insurance scheme administration (convenience) were the most important factors identified by the two methods. Multivariate logistic regressions showed that the factors identified from the two methods differed somewhat in importance when considered as independent predictors of the enrollment status. The most important perception factors in terms of strength of association (odds ratio) and statistical significance were accessibility to insurance scheme administration (convenience), preferences (beliefs), and the quality of health care services. However, age and income were the only socio-demographic characteristics that were statistically significant. Conclusion Household perceptions were found to influence households’ decisions to enroll in CBHIs. Policymakers should recognize and consider these perceptions when designing policies and programs that aim to increase the enrolment into CBHIs.