How to do (or not to do)… health resource allocations using constrained mathematical optimization. Issue 1 (18th November 2022)

• Record Type: Journal Article
• Authors: Stuart, Robyn M; Fraser-Hurt, Nicole; Shubber, Zara; Vu, Lung; Cheik, Nejma; Kerr, Cliff C; Wilson, David P
• Is Part Of: Health policy and planning. Volume 38:Issue 1(2023)
• Page Start: 122
• Page End: 128
• Publication Date: 2022-11-18
• Subjects: Resource allocation -- cost-effectiveness analysis; Medical policy -- Developing countries -- Periodicals; Public health -- Developing countries -- Periodicals; Health planning -- Developing countries -- Periodicals; 362.1091724
• DOI: 10.1093/heapol/czac096
• Languages: English
• ISSNs: 0268-1080

Abstract

Abstract: 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 policymakers 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 or league tables. In this paper, we describe how such methods work, how policymakers and programme managers can access them and implement their recommendations and how they have changed health spending in the world to date.