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. 2023 Jan 6;38(1):122-128.
doi: 10.1093/heapol/czac096.

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

Robyn M Stuart  1   2 , Nicole Fraser-Hurt  3 , Zara Shubber  3 , Lung Vu  3 , Nejma Cheik  3 , Cliff C Kerr  4   5 , David P Wilson  2   6
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How to do (or not to do)… health resource allocations using constrained mathematical optimization

Robyn M Stuart et al. Health Policy Plan. .

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.

Keywords: Resource allocation; cost-effectiveness analysis.

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Figures

Figure 1.
Figure 1.
Deciding between two programmes when each one can be implemented at a varying scale
Figure 2.
Figure 2.
Deciding between preventions and treatment programmes when each one can be implemented at a varying scale, and the optimal allocation between them depends on the total budget available
See this image and copyright information in PMC

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