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How much might a society spend on life-saving interventions at different ages while remaining cost-effective? A case study in a country with detailed data
OBJECTIVE: We aimed to estimate the maximum intervention cost (EMIC) a society could invest in a life-saving intervention at different ages while remaining cost-effective according to a user-specified cost-effectiveness threshold. METHODS: New Zealand (NZ) was used as a case study, and a health syst...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4493819/ https://www.ncbi.nlm.nih.gov/pubmed/26155199 http://dx.doi.org/10.1186/s12963-015-0052-2 |
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author | Kvizhinadze, Giorgi Wilson, Nick Nair, Nisha McLeod, Melissa Blakely, Tony |
author_facet | Kvizhinadze, Giorgi Wilson, Nick Nair, Nisha McLeod, Melissa Blakely, Tony |
author_sort | Kvizhinadze, Giorgi |
collection | PubMed |
description | OBJECTIVE: We aimed to estimate the maximum intervention cost (EMIC) a society could invest in a life-saving intervention at different ages while remaining cost-effective according to a user-specified cost-effectiveness threshold. METHODS: New Zealand (NZ) was used as a case study, and a health system perspective was taken. Data from NZ life tables and morbidity data from a burden of disease study were used to estimate health-adjusted life-years (HALYs) gained by a life-saving intervention. Health system costs were estimated from a national database of all publicly funded health events (hospitalizations, outpatient events, pharmaceuticals, etc.). For illustrative purposes we followed the WHO-CHOICE approach and used a cost-effectiveness threshold of the gross domestic product (GDP) per capita (NZ$45,000 or US$30,000 per HALY). We then calculated EMICs for an “ideal” life-saving intervention that fully returned survivors to the same average morbidity, mortality, and cost trajectories as the rest of their cohort. FINDINGS: The EMIC of the “ideal” life-saving intervention varied markedly by age: NZ$1.3 million (US$880,000) for an intervention to save the life of a child, NZ$0.8 million (US$540,000) for a 50-year-old, and NZ$0.235 million (US$158,000) for an 80-year-old. These results were predictably very sensitive to the choice of discount rate and to the selected cost-effectiveness threshold. Using WHO data, we produced an online calculator to allow the performance of similar calculations for all other countries. CONCLUSIONS: We present an approach to estimating maximal cost-effective investment in life-saving health interventions, under various assumptions. Our online calculator allows this approach to be applied in other countries. Policymakers could use these estimates as a rapid screening tool to determine if more detailed cost-effectiveness analyses of potential life-saving interventions might be worthwhile or which proposed life-saving interventions are very unlikely to benefit from such additional research. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12963-015-0052-2) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-4493819 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-44938192015-07-08 How much might a society spend on life-saving interventions at different ages while remaining cost-effective? A case study in a country with detailed data Kvizhinadze, Giorgi Wilson, Nick Nair, Nisha McLeod, Melissa Blakely, Tony Popul Health Metr Research OBJECTIVE: We aimed to estimate the maximum intervention cost (EMIC) a society could invest in a life-saving intervention at different ages while remaining cost-effective according to a user-specified cost-effectiveness threshold. METHODS: New Zealand (NZ) was used as a case study, and a health system perspective was taken. Data from NZ life tables and morbidity data from a burden of disease study were used to estimate health-adjusted life-years (HALYs) gained by a life-saving intervention. Health system costs were estimated from a national database of all publicly funded health events (hospitalizations, outpatient events, pharmaceuticals, etc.). For illustrative purposes we followed the WHO-CHOICE approach and used a cost-effectiveness threshold of the gross domestic product (GDP) per capita (NZ$45,000 or US$30,000 per HALY). We then calculated EMICs for an “ideal” life-saving intervention that fully returned survivors to the same average morbidity, mortality, and cost trajectories as the rest of their cohort. FINDINGS: The EMIC of the “ideal” life-saving intervention varied markedly by age: NZ$1.3 million (US$880,000) for an intervention to save the life of a child, NZ$0.8 million (US$540,000) for a 50-year-old, and NZ$0.235 million (US$158,000) for an 80-year-old. These results were predictably very sensitive to the choice of discount rate and to the selected cost-effectiveness threshold. Using WHO data, we produced an online calculator to allow the performance of similar calculations for all other countries. CONCLUSIONS: We present an approach to estimating maximal cost-effective investment in life-saving health interventions, under various assumptions. Our online calculator allows this approach to be applied in other countries. Policymakers could use these estimates as a rapid screening tool to determine if more detailed cost-effectiveness analyses of potential life-saving interventions might be worthwhile or which proposed life-saving interventions are very unlikely to benefit from such additional research. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12963-015-0052-2) contains supplementary material, which is available to authorized users. BioMed Central 2015-07-08 /pmc/articles/PMC4493819/ /pubmed/26155199 http://dx.doi.org/10.1186/s12963-015-0052-2 Text en © Kvizhinadze et al. 2015 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Kvizhinadze, Giorgi Wilson, Nick Nair, Nisha McLeod, Melissa Blakely, Tony How much might a society spend on life-saving interventions at different ages while remaining cost-effective? A case study in a country with detailed data |
title | How much might a society spend on life-saving interventions at different ages while remaining cost-effective? A case study in a country with detailed data |
title_full | How much might a society spend on life-saving interventions at different ages while remaining cost-effective? A case study in a country with detailed data |
title_fullStr | How much might a society spend on life-saving interventions at different ages while remaining cost-effective? A case study in a country with detailed data |
title_full_unstemmed | How much might a society spend on life-saving interventions at different ages while remaining cost-effective? A case study in a country with detailed data |
title_short | How much might a society spend on life-saving interventions at different ages while remaining cost-effective? A case study in a country with detailed data |
title_sort | how much might a society spend on life-saving interventions at different ages while remaining cost-effective? a case study in a country with detailed data |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4493819/ https://www.ncbi.nlm.nih.gov/pubmed/26155199 http://dx.doi.org/10.1186/s12963-015-0052-2 |
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