Cargando…

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...

Descripción completa

Detalles Bibliográficos
Autores principales: Kvizhinadze, Giorgi, Wilson, Nick, Nair, Nisha, McLeod, Melissa, Blakely, Tony
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2015
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
_version_ 1782379988046053376
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
work_keys_str_mv AT kvizhinadzegiorgi howmuchmightasocietyspendonlifesavinginterventionsatdifferentageswhileremainingcosteffectiveacasestudyinacountrywithdetaileddata
AT wilsonnick howmuchmightasocietyspendonlifesavinginterventionsatdifferentageswhileremainingcosteffectiveacasestudyinacountrywithdetaileddata
AT nairnisha howmuchmightasocietyspendonlifesavinginterventionsatdifferentageswhileremainingcosteffectiveacasestudyinacountrywithdetaileddata
AT mcleodmelissa howmuchmightasocietyspendonlifesavinginterventionsatdifferentageswhileremainingcosteffectiveacasestudyinacountrywithdetaileddata
AT blakelytony howmuchmightasocietyspendonlifesavinginterventionsatdifferentageswhileremainingcosteffectiveacasestudyinacountrywithdetaileddata