Financial Implications of Paying for Maternal and Neonatal Healthcare Services for Vulnerable Populations in Tanzania

Despite efforts to reduce barriers and increase the use of key maternal and neonatal health services, the 2015 Tanzania Demographic and Health Survey shows mixed results on the use of these services, with a minimal decline in the maternal mortality ratio over the last decade. The KfW Development Bank is piloting the Tumaini la Mama program in partnership with the National Health Insurance Fund (NHIF), which targets poor pregnant women and offers them the complete NHIF benefits package free of charge throughout their pregnancy and six months postpartum. The pilot has shown promising results, with demand for coverage under this scheme growing. However, sustainability and scalability are not yet clear. Tanzania is exploring the consolidation, improvement, and scale-up of the Community Health Fund, a set of community-based health insurance schemes managed by NHIF, as an intermediary step in promoting access to healthcare alongside NHIF reform and expansion. If the Community Health Fund or National Health Insurance Fund schemes are used as vehicles for expanding access and use, they will need to cover maternal and neonatal health services for the poor. To address the financial implications of paying for maternal and neonatal healthcare services for vulnerable populations in Tanzania, Health Policy Plus (HP+) analyzed the cost of fully subsidizing a defined package of key maternal and neonatal health interventions for poor pregnant women in Tanzania. The analysis used the existing comprehensive costing of the National Road Map Strategic Plan to Improve Reproductive, Maternal, Newborn, Child, & Adolescent Health of the Government of Tanzania, also known as One Plan II, to determine the average unit cost per pregnant woman, including both commodity and labor costs of health workers. The analysis projected total resource needs across several scenarios, taking into account the likelihood that an average woman would access a maternal and neonatal health intervention, using previously-used assumptions on the occurrence of pregnancy-related complications, and indicators for baseline health-seeking behavior across socioeconomic groups. The scenarios are useful to inform policy as future population coverage of the scheme and the change to health-seeking behavior after a demand-side intervention like insurance is launched are both uncertain. To define the population of poor pregnant women a maternal and neonatal health scheme should cover, HP+ used two different methodologies—demographic survey data and community-based identification—to create two potential population scenarios. Based on these populations, the analysis determined the total costs for the current year and projected potential future costs. The results of these scenarios illustrate important drivers of cost to consider in evaluating the scale-up of a Tumaini la Mama-type scheme, particularly for its financial feasibility. The analysis relied on three main sources of data: national poverty estimates, the Tanzania Demographic and Health Survey 2015, and the Tanzania Social Action Fund (TASAF) poverty reduction initiative. TASAF uses a community-based system to identify and target the most poor and vulnerable households, verified by means testing. The analysis used data on beneficiaries available for five regions and extrapolated to the national level. The financial implications of the scale-up of a maternal and neonatal health scheme, like those funded by KfW and NHIF, are dependent on how much of the population the scheme can cover and the likelihood of that population using healthcare services. The analysis shows that expanding coverage of a fully-subsidized package of maternal and neonatal health services is feasible in Tanzania given current resources. Subsidizing such a package through an insurance-type scheme will require a clear understanding of the costs to the payer and how those costs might change depending on how the size of and demand for services from the beneficiary population vary.