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Allocating treatment resources for hepatitis C in the UK: a constrained optimization modelling approach

Background and objective: Although the treatment of chronic hepatitis C (CHC) has significantly evolved with the introduction of direct-acting antivirals, the treatment uptake rates have been low especially among marginalized groups in the UK, such as people who inject drug (PWID) and men who have s...

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Autores principales: Han, Ru, Liang, Shuyao, François, Clément, Aballea, Samuel, Clay, Emilie, Toumi, Mondher
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Routledge 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8008927/
https://www.ncbi.nlm.nih.gov/pubmed/33828822
http://dx.doi.org/10.1080/20016689.2021.1887664
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author Han, Ru
Liang, Shuyao
François, Clément
Aballea, Samuel
Clay, Emilie
Toumi, Mondher
author_facet Han, Ru
Liang, Shuyao
François, Clément
Aballea, Samuel
Clay, Emilie
Toumi, Mondher
author_sort Han, Ru
collection PubMed
description Background and objective: Although the treatment of chronic hepatitis C (CHC) has significantly evolved with the introduction of direct-acting antivirals, the treatment uptake rates have been low especially among marginalized groups in the UK, such as people who inject drug (PWID) and men who have sex with men (MSM). Cutting health inequality is a major focus of healthcare agencies. This study aims to identify the optimal allocation of treatment budget for chronic hepatitis CHC among populations and treatments in the UK so that liver-related mortality in patients with CHC is minimized, given the constraint of treatment budget and equity issue. Methods: A constrained optimization modelling of resource allocation for the treatment of CHC was developed in Excel from the perspective of the UK National Health System over a lifetime horizon. The model was designated with the objective function of minimizing liver-related deaths by varying the decision variables, representing the number of patients receiving each treatment (elbasvir-grazoprevir, ombitasvir-paritaprevir-ritonavir-dasabuvir, sofosbuvir-ledipasvir, and pegylated interferon-ribavirin) in each population (the general population, PWID, and MSM). Two main constraints were formulated including treatment budget and the issue of equity. The model was populated with UK local data applying linear programming and underwent internal and external validation. Scenario analyses were performed to assess the robustness of model results. Results: Within the constraints of no additional funding over original spending in status quo and the consideration of the issue of equity among populations, the optimal allocation from the constrained optimization modelling (treating 13,122 PWID, 160 MSM, and 904 general patients with ombitasvir-paritaprevir-ritonavir-dasabuvir) was found to treat 2,430 more patients (relative change: 20.7%) and avert 78 liver-related deaths (relative change: 0.3%) compared with the current allocation. The number of patients receiving treatment increased 4,928 (relative change: 60.1%) among PWID and 42 (relative change: 35.8%) among MSM. Conclusion: The current allocation of treatment budget for CHC is not optimal in the UK. More patients would be treated, and more liver-related deaths would be avoided using a new allocation from a constrained optimization modelling without incurring additional spending and considering the issue of equity.
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spelling pubmed-80089272021-04-06 Allocating treatment resources for hepatitis C in the UK: a constrained optimization modelling approach Han, Ru Liang, Shuyao François, Clément Aballea, Samuel Clay, Emilie Toumi, Mondher J Mark Access Health Policy Original Research Article Background and objective: Although the treatment of chronic hepatitis C (CHC) has significantly evolved with the introduction of direct-acting antivirals, the treatment uptake rates have been low especially among marginalized groups in the UK, such as people who inject drug (PWID) and men who have sex with men (MSM). Cutting health inequality is a major focus of healthcare agencies. This study aims to identify the optimal allocation of treatment budget for chronic hepatitis CHC among populations and treatments in the UK so that liver-related mortality in patients with CHC is minimized, given the constraint of treatment budget and equity issue. Methods: A constrained optimization modelling of resource allocation for the treatment of CHC was developed in Excel from the perspective of the UK National Health System over a lifetime horizon. The model was designated with the objective function of minimizing liver-related deaths by varying the decision variables, representing the number of patients receiving each treatment (elbasvir-grazoprevir, ombitasvir-paritaprevir-ritonavir-dasabuvir, sofosbuvir-ledipasvir, and pegylated interferon-ribavirin) in each population (the general population, PWID, and MSM). Two main constraints were formulated including treatment budget and the issue of equity. The model was populated with UK local data applying linear programming and underwent internal and external validation. Scenario analyses were performed to assess the robustness of model results. Results: Within the constraints of no additional funding over original spending in status quo and the consideration of the issue of equity among populations, the optimal allocation from the constrained optimization modelling (treating 13,122 PWID, 160 MSM, and 904 general patients with ombitasvir-paritaprevir-ritonavir-dasabuvir) was found to treat 2,430 more patients (relative change: 20.7%) and avert 78 liver-related deaths (relative change: 0.3%) compared with the current allocation. The number of patients receiving treatment increased 4,928 (relative change: 60.1%) among PWID and 42 (relative change: 35.8%) among MSM. Conclusion: The current allocation of treatment budget for CHC is not optimal in the UK. More patients would be treated, and more liver-related deaths would be avoided using a new allocation from a constrained optimization modelling without incurring additional spending and considering the issue of equity. Routledge 2021-03-25 /pmc/articles/PMC8008927/ /pubmed/33828822 http://dx.doi.org/10.1080/20016689.2021.1887664 Text en © 2021 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. https://creativecommons.org/licenses/by-nc/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License (http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) ), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Research Article
Han, Ru
Liang, Shuyao
François, Clément
Aballea, Samuel
Clay, Emilie
Toumi, Mondher
Allocating treatment resources for hepatitis C in the UK: a constrained optimization modelling approach
title Allocating treatment resources for hepatitis C in the UK: a constrained optimization modelling approach
title_full Allocating treatment resources for hepatitis C in the UK: a constrained optimization modelling approach
title_fullStr Allocating treatment resources for hepatitis C in the UK: a constrained optimization modelling approach
title_full_unstemmed Allocating treatment resources for hepatitis C in the UK: a constrained optimization modelling approach
title_short Allocating treatment resources for hepatitis C in the UK: a constrained optimization modelling approach
title_sort allocating treatment resources for hepatitis c in the uk: a constrained optimization modelling approach
topic Original Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8008927/
https://www.ncbi.nlm.nih.gov/pubmed/33828822
http://dx.doi.org/10.1080/20016689.2021.1887664
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