Does health insurance solve health care utilization puzzle in Tanzania?

OBJECTIVES: The global target of achieving universal health coverage by 2030 is a nightmare in most developing countries. To seek in-depth reasons, this study examines the effects of health insurance on healthcare utilization in Tanzania. STUDY DESIGN: This study used a non-experimental research design. METHODS: Probit model, negative binomial regression, and instrumental variable Poisson with generalized method of moments were used to solve the healthcare utilization puzzle by the use of Andersen Health Care Utilization Model by using the Tanzania Panel Survey data of 2020/21. RESULTS: The findings showed that education level, income, age, residence, household size, insurance, and distance from homestead to health facilities are significant policy intervention factors for improving households' healthcare utilization behavior among households in Tanzania. CONCLUSION: Prioritize should be made on interventions that ensure the affordability of health services without compromising the quality of services offered and expanding the share of the government budget on health sector.

Equity in the public social healthcare protection in Tanzania: does it matter on household healthcare financing?

Efforts to promote equity in healthcare involve implementing policies and programs that address the root causes of healthcare disparities and promote equal access to care. One such program is the public social healthcare protection schemes. However, like many other developing countries, Tanzania has low health insurance coverage, hindering its efforts to achieve universal health coverage. This study examines the role of equity in public social healthcare protection and its effects on household healthcare financing in Tanzania. The study used secondary data collected from the National Bureau of Statistics' National Panel Survey 2020/21 and stratified households based on their place of residence (rural vs. urban). Moreover, the logit regression model, ordered logit, and the endogenous switching regression model were used to provide counterfactual estimates without selection bias and endogeneity problems. The results showed greater variations in social health protection across rural and urban households, increasing disparities in health outcomes between these areas. Rural residents are the most vulnerable groups. Furthermore, education, income, and direct healthcare costs significantly influence equity in healthcare financing and the ability of households to benefit from public social healthcare protection schemes. To achieve equity in healthcare in rural and urban areas, developing countries need to increase investment in health sector by reducing the cost of healthcare, which will significantly reduce household healthcare financing. Furthermore, the study recommends that social health protection is an essential strategy for improving fair access to quality healthcare by removing differences across households and promoting equality in utilizing healthcare services.

Analysis on the equity differential on household healthcare financing in developing countries: empirical evidence from Tanzania, East Africa.

BACKGROUND: Achieving equity in healthcare services has been a global priority. According to the literature, a slew of initiatives aimed at increasing household equity in healthcare financing have exacerbated the problem, making it hard for most developing countries to understand the real cause of the problem. METHOD: The non-experimental research design has been used to explore the Tanzania Panel Survey (NPS) data 2019/2020, to investigate equity differential in household healthcare financing in Tanzania by the use of conventional instrumental variable methods of Two-stage and Three-stage least square methods RESULTS: Despite the global agenda of universal health coverage, this paper reveals that 86 percent of Tanzania lacks health insurance with a high degree of inequitable distribution of health facilities as 71.54 percent of the population is in rural areas, yet these areas have poor health systems compared to urban ones. These disparities increase pressure on household healthcare financing and widen the inequity and equality gaps simultaneously. Additionally, a household's income, education, health care waivers, out-of-pocket expenditure, and user fees have been found to have a significant impact on household equity in healthcare financing. CONCLUSION: To reverse the situation and increase equity in household healthcare financing in most developing countries, this paper suggests that an adequate pooling system should be used to allow more people to be covered by medical prepayment programs, and the donor-funded programs in developing countries should focus on health sector infrastructure development and not the capacity building.