Cargando…

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 s...

Descripción completa

Detalles Bibliográficos
Autores principales: Stuart, Robyn M, Fraser-Hurt, Nicole, Shubber, Zara, Vu, Lung, Cheik, Nejma, Kerr, Cliff C, Wilson, David P
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9825717/
https://www.ncbi.nlm.nih.gov/pubmed/36398991
http://dx.doi.org/10.1093/heapol/czac096
_version_ 1784866682883276800
author Stuart, Robyn M
Fraser-Hurt, Nicole
Shubber, Zara
Vu, Lung
Cheik, Nejma
Kerr, Cliff C
Wilson, David P
author_facet Stuart, Robyn M
Fraser-Hurt, Nicole
Shubber, Zara
Vu, Lung
Cheik, Nejma
Kerr, Cliff C
Wilson, David P
author_sort Stuart, Robyn M
collection PubMed
description 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.
format Online
Article
Text
id pubmed-9825717
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher Oxford University Press
record_format MEDLINE/PubMed
spelling pubmed-98257172023-01-10 How to do (or not to do)… health resource allocations using constrained mathematical optimization Stuart, Robyn M Fraser-Hurt, Nicole Shubber, Zara Vu, Lung Cheik, Nejma Kerr, Cliff C Wilson, David P Health Policy Plan How to Do (Or Not to Do) 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. Oxford University Press 2022-11-18 /pmc/articles/PMC9825717/ /pubmed/36398991 http://dx.doi.org/10.1093/heapol/czac096 Text en © The Author(s) 2022. Published by Oxford University Press in association with The London School of Hygiene and Tropical Medicine. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle How to Do (Or Not to Do)
Stuart, Robyn M
Fraser-Hurt, Nicole
Shubber, Zara
Vu, Lung
Cheik, Nejma
Kerr, Cliff C
Wilson, David P
How to do (or not to do)… health resource allocations using constrained mathematical optimization
title How to do (or not to do)… health resource allocations using constrained mathematical optimization
title_full How to do (or not to do)… health resource allocations using constrained mathematical optimization
title_fullStr How to do (or not to do)… health resource allocations using constrained mathematical optimization
title_full_unstemmed How to do (or not to do)… health resource allocations using constrained mathematical optimization
title_short How to do (or not to do)… health resource allocations using constrained mathematical optimization
title_sort how to do (or not to do)… health resource allocations using constrained mathematical optimization
topic How to Do (Or Not to Do)
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9825717/
https://www.ncbi.nlm.nih.gov/pubmed/36398991
http://dx.doi.org/10.1093/heapol/czac096
work_keys_str_mv AT stuartrobynm howtodoornottodohealthresourceallocationsusingconstrainedmathematicaloptimization
AT fraserhurtnicole howtodoornottodohealthresourceallocationsusingconstrainedmathematicaloptimization
AT shubberzara howtodoornottodohealthresourceallocationsusingconstrainedmathematicaloptimization
AT vulung howtodoornottodohealthresourceallocationsusingconstrainedmathematicaloptimization
AT cheiknejma howtodoornottodohealthresourceallocationsusingconstrainedmathematicaloptimization
AT kerrcliffc howtodoornottodohealthresourceallocationsusingconstrainedmathematicaloptimization
AT wilsondavidp howtodoornottodohealthresourceallocationsusingconstrainedmathematicaloptimization