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...
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2021-01-01
|
| Series: | Journal of Market Access & Health Policy |
| Subjects: | |
| Online Access: | http://dx.doi.org/10.1080/20016689.2021.1887664 |
| _version_ | 1827265250524659712 |
|---|---|
| author | Ru Han Shuyao Liang Clément François Samuel Aballea Emilie Clay Mondher Toumi |
| author_facet | Ru Han Shuyao Liang Clément François Samuel Aballea Emilie Clay Mondher Toumi |
| author_sort | Ru Han |
| collection | DOAJ |
| 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. |
| first_indexed | 2024-04-24T15:37:38Z |
| format | Article |
| id | doaj.art-afccf73769e5442bbe5e7ffed50faa3f |
| institution | Directory Open Access Journal |
| issn | 2001-6689 |
| language | English |
| last_indexed | 2025-03-22T03:58:58Z |
| publishDate | 2021-01-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | Journal of Market Access & Health Policy |
| spelling | doaj.art-afccf73769e5442bbe5e7ffed50faa3f2024-04-28T10:46:23ZengTaylor & Francis GroupJournal of Market Access & Health Policy2001-66892021-01-019110.1080/20016689.2021.18876641887664Allocating treatment resources for hepatitis C in the UK: a constrained optimization modelling approachRu Han0Shuyao Liang1Clément François2Samuel Aballea3Emilie Clay4Mondher Toumi5University of Aix-MarseilleUniversity of Aix-MarseilleUniversity of Aix-MarseilleUniversity of Aix-MarseilleUniversity of Aix-MarseilleUniversity of Aix-MarseilleBackground 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.http://dx.doi.org/10.1080/20016689.2021.1887664constrained optimization modellinghepatitis cresource allocation |
| spellingShingle | Ru Han Shuyao Liang Clément François Samuel Aballea Emilie Clay Mondher Toumi Allocating treatment resources for hepatitis C in the UK: a constrained optimization modelling approach Journal of Market Access & Health Policy constrained optimization modelling hepatitis c resource allocation |
| 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 | constrained optimization modelling hepatitis c resource allocation |
| url | http://dx.doi.org/10.1080/20016689.2021.1887664 |
| work_keys_str_mv | AT ruhan allocatingtreatmentresourcesforhepatitiscintheukaconstrainedoptimizationmodellingapproach AT shuyaoliang allocatingtreatmentresourcesforhepatitiscintheukaconstrainedoptimizationmodellingapproach AT clementfrancois allocatingtreatmentresourcesforhepatitiscintheukaconstrainedoptimizationmodellingapproach AT samuelaballea allocatingtreatmentresourcesforhepatitiscintheukaconstrainedoptimizationmodellingapproach AT emilieclay allocatingtreatmentresourcesforhepatitiscintheukaconstrainedoptimizationmodellingapproach AT mondhertoumi allocatingtreatmentresourcesforhepatitiscintheukaconstrainedoptimizationmodellingapproach |