How to do (or not to do)… health resource allocations using constrained mathematical optimization.

Despite the push towards evidence-based health policy, decisions about how to allocate health resources are all too often made on the basis of political forces or a continuation of the status quo. This results in wastage in health systems and loss of potential population health. However, if health systems are to serve people best, then they must operate efficiently and equitably, and appropriate valuation methods are needed to determine how to do this. With the advances in computing power over the past few decades, advanced mathematical optimization algorithms can now be run on personal computers, and can be used to provide comprehensive, evidence-based recommendations for policy makers on how to prioritize health spending considering policy objectives, interactions of interventions, real-world system constraints, and budget envelopes. Such methods provide an invaluable complement to traditional or extended cost-effectiveness analyses (CEA or ECEA) or league tables. In this paper, we describe how such methods work, how policy makers and program managers can access them and implement their recommendations, and how they have changed health spending in the world to date. [ABSTRACT FROM AUTHOR]