Cargando…
Health and economic benefits of public financing of epilepsy treatment in India: An agent‐based simulation model
OBJECTIVE: An estimated 6–10 million people in India live with active epilepsy, and less than half are treated. We analyze the health and economic benefits of three scenarios of publicly financed national epilepsy programs that provide: (1) first‐line antiepilepsy drugs (AEDs), (2) first‐ and second...
Autores principales: | , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2016
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5019268/ https://www.ncbi.nlm.nih.gov/pubmed/26765291 http://dx.doi.org/10.1111/epi.13294 |
_version_ | 1782453025879621632 |
---|---|
author | Megiddo, Itamar Colson, Abigail Chisholm, Dan Dua, Tarun Nandi, Arindam Laxminarayan, Ramanan |
author_facet | Megiddo, Itamar Colson, Abigail Chisholm, Dan Dua, Tarun Nandi, Arindam Laxminarayan, Ramanan |
author_sort | Megiddo, Itamar |
collection | PubMed |
description | OBJECTIVE: An estimated 6–10 million people in India live with active epilepsy, and less than half are treated. We analyze the health and economic benefits of three scenarios of publicly financed national epilepsy programs that provide: (1) first‐line antiepilepsy drugs (AEDs), (2) first‐ and second‐line AEDs, and (3) first‐ and second‐line AEDs and surgery. METHODS: We model the prevalence and distribution of epilepsy in India using IndiaSim, an agent‐based, simulation model of the Indian population. Agents in the model are disease‐free or in one of three disease states: untreated with seizures, treated with seizures, and treated without seizures. Outcome measures include the proportion of the population that has epilepsy and is untreated, disability‐adjusted life years (DALYs) averted, and cost per DALY averted. Economic benefit measures estimated include out‐of‐pocket (OOP) expenditure averted and money‐metric value of insurance. RESULTS: All three scenarios represent a cost‐effective use of resources and would avert 800,000–1 million DALYs per year in India relative to the current scenario. However, especially in poor regions and populations, scenario 1 (which publicly finances only first‐line therapy) does not decrease the OOP expenditure or provide financial risk protection if we include care‐seeking costs. The OOP expenditure averted increases from scenarios 1 through 3, and the money‐metric value of insurance follows a similar trend between scenarios and typically decreases with wealth. In the first 10 years of scenarios 2 and 3, households avert on average over US$80 million per year in medical expenditure. SIGNIFICANCE: Expanding and publicly financing epilepsy treatment in India averts substantial disease burden. A universal public finance policy that covers only first‐line AEDs may not provide significant financial risk protection. Covering costs for both first‐ and second‐line therapy and other medical costs alleviates the financial burden from epilepsy and is cost‐effective across wealth quintiles and in all Indian states. |
format | Online Article Text |
id | pubmed-5019268 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-50192682016-09-23 Health and economic benefits of public financing of epilepsy treatment in India: An agent‐based simulation model Megiddo, Itamar Colson, Abigail Chisholm, Dan Dua, Tarun Nandi, Arindam Laxminarayan, Ramanan Epilepsia Full‐length Original Research OBJECTIVE: An estimated 6–10 million people in India live with active epilepsy, and less than half are treated. We analyze the health and economic benefits of three scenarios of publicly financed national epilepsy programs that provide: (1) first‐line antiepilepsy drugs (AEDs), (2) first‐ and second‐line AEDs, and (3) first‐ and second‐line AEDs and surgery. METHODS: We model the prevalence and distribution of epilepsy in India using IndiaSim, an agent‐based, simulation model of the Indian population. Agents in the model are disease‐free or in one of three disease states: untreated with seizures, treated with seizures, and treated without seizures. Outcome measures include the proportion of the population that has epilepsy and is untreated, disability‐adjusted life years (DALYs) averted, and cost per DALY averted. Economic benefit measures estimated include out‐of‐pocket (OOP) expenditure averted and money‐metric value of insurance. RESULTS: All three scenarios represent a cost‐effective use of resources and would avert 800,000–1 million DALYs per year in India relative to the current scenario. However, especially in poor regions and populations, scenario 1 (which publicly finances only first‐line therapy) does not decrease the OOP expenditure or provide financial risk protection if we include care‐seeking costs. The OOP expenditure averted increases from scenarios 1 through 3, and the money‐metric value of insurance follows a similar trend between scenarios and typically decreases with wealth. In the first 10 years of scenarios 2 and 3, households avert on average over US$80 million per year in medical expenditure. SIGNIFICANCE: Expanding and publicly financing epilepsy treatment in India averts substantial disease burden. A universal public finance policy that covers only first‐line AEDs may not provide significant financial risk protection. Covering costs for both first‐ and second‐line therapy and other medical costs alleviates the financial burden from epilepsy and is cost‐effective across wealth quintiles and in all Indian states. John Wiley and Sons Inc. 2016-01-14 2016-03 /pmc/articles/PMC5019268/ /pubmed/26765291 http://dx.doi.org/10.1111/epi.13294 Text en © 2016 The Authors. Epilepsia published by Wiley Periodicals, Inc. on behalf of International League Against Epilepsy. This is an open access article under the terms of the Creative Commons Attribution‐NonCommercial (http://creativecommons.org/licenses/by-nc/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes. |
spellingShingle | Full‐length Original Research Megiddo, Itamar Colson, Abigail Chisholm, Dan Dua, Tarun Nandi, Arindam Laxminarayan, Ramanan Health and economic benefits of public financing of epilepsy treatment in India: An agent‐based simulation model |
title | Health and economic benefits of public financing of epilepsy treatment in India: An agent‐based simulation model |
title_full | Health and economic benefits of public financing of epilepsy treatment in India: An agent‐based simulation model |
title_fullStr | Health and economic benefits of public financing of epilepsy treatment in India: An agent‐based simulation model |
title_full_unstemmed | Health and economic benefits of public financing of epilepsy treatment in India: An agent‐based simulation model |
title_short | Health and economic benefits of public financing of epilepsy treatment in India: An agent‐based simulation model |
title_sort | health and economic benefits of public financing of epilepsy treatment in india: an agent‐based simulation model |
topic | Full‐length Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5019268/ https://www.ncbi.nlm.nih.gov/pubmed/26765291 http://dx.doi.org/10.1111/epi.13294 |
work_keys_str_mv | AT megiddoitamar healthandeconomicbenefitsofpublicfinancingofepilepsytreatmentinindiaanagentbasedsimulationmodel AT colsonabigail healthandeconomicbenefitsofpublicfinancingofepilepsytreatmentinindiaanagentbasedsimulationmodel AT chisholmdan healthandeconomicbenefitsofpublicfinancingofepilepsytreatmentinindiaanagentbasedsimulationmodel AT duatarun healthandeconomicbenefitsofpublicfinancingofepilepsytreatmentinindiaanagentbasedsimulationmodel AT nandiarindam healthandeconomicbenefitsofpublicfinancingofepilepsytreatmentinindiaanagentbasedsimulationmodel AT laxminarayanramanan healthandeconomicbenefitsofpublicfinancingofepilepsytreatmentinindiaanagentbasedsimulationmodel |