Improving Maternal Care through a State-Wide Health Insurance Program: A Cost and Cost-Effectiveness Study in Rural Nigeria.

BACKGROUND: While the Nigerian government has made progress towards the Millennium Development Goals, further investments are needed to achieve the targets of post-2015 Sustainable Development Goals, including Universal Health Coverage. Economic evaluations of innovative interventions can help inform investment decisions in resource-constrained settings. We aim to assess the cost and cost-effectiveness of maternal care provided within the new Kwara State Health Insurance program (KSHI) in rural Nigeria. METHODS AND FINDINGS: We used a decision analytic model to simulate a cohort of pregnant women. The primary outcome is the incremental cost effectiveness ratio (ICER) of the KSHI scenario compared to the current standard of care. Intervention cost from a healthcare provider perspective included service delivery costs and above-service level costs; these were evaluated in a participating hospital and using financial records from the managing organisations, respectively. Standard of care costs from a provider perspective were derived from the literature using an ingredient approach. We generated 95% credibility intervals around the primary outcome through probabilistic sensitivity analysis (PSA) based on a Monte Carlo simulation. We conducted one-way sensitivity analyses across key model parameters and assessed the sensitivity of our results to the performance of the base case separately through a scenario analysis. Finally, we assessed the sustainability and feasibility of this program's scale up within the State's healthcare financing structure through a budget impact analysis. The KSHI scenario results in a health benefit to patients at a higher cost compared to the base case. The mean ICER (US$46.4/disability-adjusted life year averted) is considered very cost-effective compared to a willingness-to-pay threshold of one gross domestic product per capita (Nigeria, US$ 2012, 2,730). Our conclusion was robust to uncertainty in parameters estimates (PSA: median US$49.1, 95% credible interval 21.9-152.3), during one-way sensitivity analyses, and when cost, quality, cost and utilization parameters of the base case scenario were changed. The sustainability of this program's scale up by the State is dependent on further investments in healthcare. CONCLUSIONS: This study provides evidence that the investment made by the KSHI program in rural Nigeria is likely to have been cost-effective; however, further healthcare investments are needed for this program to be successfully expanded within Kwara State. Policy makers should consider supporting financial initiatives to reduce maternal mortality tackling both supply and demand issues in the access to care.

Costs of cardiovascular disease prevention care and scenarios for cost saving: a micro-costing study from rural Nigeria.

OBJECTIVE: To assess the costs of cardiovascular disease (CVD) prevention care according to international guidelines, in a primary healthcare clinic in rural Nigeria, participating in a health insurance programme. METHODS: A micro-costing study was conducted from a healthcare provider perspective. Activities per patient per year (e.g., consultations, diagnostic tests) were based on clinical practice in the study clinic. Direct (e.g., staff, drugs) and indirect cost items (overheads) for each activity were measured. A cohort study, patient and staff observations, and interviews in the study clinic provided patient resource utilization data. Univariate sensitivity analyses were performed. Scenario analyses evaluated cost-saving options. The main outcome was the costs of CVD prevention care per patient per year. RESULTS: The costs of CVD prevention care were United States dollars (USD) 144 (range 130-158) per patient per year. Direct costs were USD 82 and indirect costs were USD 62. The main cost drivers were drugs (USD 39) and diagnostic tests (USD 36). The costs of hypertension care were USD 118 (107-132) and that of diabetes care USD 263 (236-289) per patient per year. A combination of task-shifting from doctors to nurses, reduction of appointment frequencies, and minimal organ damage screening would result in a direct cost reduction of 42%. CONCLUSION: This is the first study to report the costs of CVD prevention care in sub-Saharan Africa, based on prospectively collected operational data. The costs observed in our study are unaffordable in many countries in sub-Saharan Africa, highlighting the need for innovative financing mechanisms to fund CVD prevention care.

Step-by-step guideline for disease-specific costing studies in low- and middle-income countries: a mixed methodology.

BACKGROUND: Disease-specific costing studies can be used as input into cost-effectiveness analyses and provide important information for efficient resource allocation. However, limited data availability and limited expertise constrain such studies in low- and middle-income countries (LMICs). OBJECTIVE: To describe a step-by-step guideline for conducting disease-specific costing studies in LMICs where data availability is limited and to illustrate how the guideline was applied in a costing study of cardiovascular disease prevention care in rural Nigeria. DESIGN: The step-by-step guideline provides practical recommendations on methods and data requirements for six sequential steps: 1) definition of the study perspective, 2) characterization of the unit of analysis, 3) identification of cost items, 4) measurement of cost items, 5) valuation of cost items, and 6) uncertainty analyses.Please provide the significance of asterisk given in table body. RESULTS: We discuss the necessary tradeoffs between the accuracy of estimates and data availability constraints at each step and illustrate how a mixed methodology of accurate bottom-up micro-costing and more feasible approaches can be used to make optimal use of all available data. An illustrative example from Nigeria is provided. CONCLUSIONS: An innovative, user-friendly guideline for disease-specific costing in LMICs is presented, using a mixed methodology to account for limited data availability. The illustrative example showed that the step-by-step guideline can be used by healthcare professionals in LMICs to conduct feasible and accurate disease-specific cost analyses.