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

Author:

Stuart Robyn M12ORCID,Fraser-Hurt Nicole3,Shubber Zara3,Vu Lung3,Cheik Nejma3,Kerr Cliff C45,Wilson David P26

Affiliation:

1. Department of Mathematical Sciences, University of Copenhagen , Universitetsparken 5, Copenhagen 2100, Denmark

2. Burnet Institute , 85 Commercial Road, Melbourne 3004, Australia

3. The World Bank Group , 2121 Pennsylvania Avenue NW, Washington, DC 20433, USA

4. Institute for Disease Modeling at the Bill & Melinda Gates Foundation , 500 Fifth Avenue North, Seattle, WA 98109, USA

5. School of Physics, University of Sydney , Physics Road, Sydney, New South Wales, Camperdown 2006, Australia

6. Bill & Melinda Gates Foundation , 500 Fifth Avenue North, Seattle, WA 98109, USA

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.

Funder

World Bank Group

Publisher

Oxford University Press (OUP)

Subject

Health Policy

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