Optimizing health, financial risk protection, and equity in health benefits package design toward universal health...

Health policymakers are often challenged with balancing multiple objectives within the constraints of a limited budget. These objectives typically include enhancing (i) population health, (ii) providing financial risk protection, and (iii) improving health equity. We introduce quantitative methods to guide the design of essential benefits packages (EBPs) that explicitly account for trade-offs across these three critical objectives under budgetary limitations. We develop a mathematical optimization model that evaluates the fulfillment of these objectives for a spectrum of potential candidate health interventions under various options of public funding. Utilizing tri-criterion integer programming, our model identifies an optimal set of interventions for inclusion. We illustrate the approach with a case study of EBP design in Ethiopia. We found that the optimal EBP's intervention mix is sensitive to the comparative prioritization of the three objectives and the available budget; and that the number of Pareto-optimal intervention combinations changes nonlinearly with the available budget. When all three objectives are integrated, the composition of the optimal EBP is strongly influenced by the relative preferences placed on each objective. The mathematical optimization framework proposed can empower policymakers to design health policies that synergistically address multiple efficiency and equity objectives within defined financial limits.