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Estimating health system opportunity costs: the role of non-linearities and inefficiency
BACKGROUND: Empirical estimates of health system opportunity costs have been suggested as a basis for the cost-effectiveness threshold to use in Health Technology Assessment. Econometric methods have been used to estimate these in several countries based on data on spending and mortality. This study...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9617442/ https://www.ncbi.nlm.nih.gov/pubmed/36309687 http://dx.doi.org/10.1186/s12962-022-00391-y |
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author | Hernandez-Villafuerte, Karla Zamora, Bernarda Feng, Yan Parkin, David Devlin, Nancy Towse, Adrian |
author_facet | Hernandez-Villafuerte, Karla Zamora, Bernarda Feng, Yan Parkin, David Devlin, Nancy Towse, Adrian |
author_sort | Hernandez-Villafuerte, Karla |
collection | PubMed |
description | BACKGROUND: Empirical estimates of health system opportunity costs have been suggested as a basis for the cost-effectiveness threshold to use in Health Technology Assessment. Econometric methods have been used to estimate these in several countries based on data on spending and mortality. This study examines empirical evidence on four issues: non-linearity of the relationship between spending and mortality; the inclusion of outcomes other than mortality; variation in the efficiency with which expenditures generate health outcomes; and the relationship among efficiency, mortality rates and outcome elasticities. METHODS: Quantile Regression is used to examine non-linearities in the relationship between mortality and health expenditures along the mortality distribution. Data Envelopment Analysis extends the approach, using multiple measures of health outcomes to measure efficiency. These are applied to health expenditure data from 151 geographical units (Primary Care Trusts) of the National Health Service in England, across eight different clinical areas (Programme Budget Categories), for 3 fiscal years from 2010/11 to 2012/13. RESULTS: The results suggest differences in efficiency levels across geographical units and clinical areas as to how health resources generate outcomes, which indicates the capacity to adjust to a decrease in health expenditure without affecting health outcomes. Moreover, efficient units have lower absolute levels of mortality elasticity to health expenditure than inefficient ones. CONCLUSIONS: The policy of adopting thresholds based on estimates of a single system-wide cost-effectiveness threshold assumes a relationship between expenditure and health outcomes that generates an opportunity cost estimate which applies to the whole system. Our evidence of variations in that relationship and therefore in opportunity costs suggests that adopting a single threshold may exacerbate the efficiency and equity concerns that such thresholds are designed to counter. In most health care systems, many decisions about provision are not made centrally. Our analytical approach to understanding variability in opportunity cost can help policy makers target efficiency improvements and set realistic targets for local and clinical area health improvements from increased expenditure. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12962-022-00391-y. |
format | Online Article Text |
id | pubmed-9617442 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-96174422022-10-30 Estimating health system opportunity costs: the role of non-linearities and inefficiency Hernandez-Villafuerte, Karla Zamora, Bernarda Feng, Yan Parkin, David Devlin, Nancy Towse, Adrian Cost Eff Resour Alloc Research BACKGROUND: Empirical estimates of health system opportunity costs have been suggested as a basis for the cost-effectiveness threshold to use in Health Technology Assessment. Econometric methods have been used to estimate these in several countries based on data on spending and mortality. This study examines empirical evidence on four issues: non-linearity of the relationship between spending and mortality; the inclusion of outcomes other than mortality; variation in the efficiency with which expenditures generate health outcomes; and the relationship among efficiency, mortality rates and outcome elasticities. METHODS: Quantile Regression is used to examine non-linearities in the relationship between mortality and health expenditures along the mortality distribution. Data Envelopment Analysis extends the approach, using multiple measures of health outcomes to measure efficiency. These are applied to health expenditure data from 151 geographical units (Primary Care Trusts) of the National Health Service in England, across eight different clinical areas (Programme Budget Categories), for 3 fiscal years from 2010/11 to 2012/13. RESULTS: The results suggest differences in efficiency levels across geographical units and clinical areas as to how health resources generate outcomes, which indicates the capacity to adjust to a decrease in health expenditure without affecting health outcomes. Moreover, efficient units have lower absolute levels of mortality elasticity to health expenditure than inefficient ones. CONCLUSIONS: The policy of adopting thresholds based on estimates of a single system-wide cost-effectiveness threshold assumes a relationship between expenditure and health outcomes that generates an opportunity cost estimate which applies to the whole system. Our evidence of variations in that relationship and therefore in opportunity costs suggests that adopting a single threshold may exacerbate the efficiency and equity concerns that such thresholds are designed to counter. In most health care systems, many decisions about provision are not made centrally. Our analytical approach to understanding variability in opportunity cost can help policy makers target efficiency improvements and set realistic targets for local and clinical area health improvements from increased expenditure. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12962-022-00391-y. BioMed Central 2022-10-29 /pmc/articles/PMC9617442/ /pubmed/36309687 http://dx.doi.org/10.1186/s12962-022-00391-y Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Hernandez-Villafuerte, Karla Zamora, Bernarda Feng, Yan Parkin, David Devlin, Nancy Towse, Adrian Estimating health system opportunity costs: the role of non-linearities and inefficiency |
title | Estimating health system opportunity costs: the role of non-linearities and inefficiency |
title_full | Estimating health system opportunity costs: the role of non-linearities and inefficiency |
title_fullStr | Estimating health system opportunity costs: the role of non-linearities and inefficiency |
title_full_unstemmed | Estimating health system opportunity costs: the role of non-linearities and inefficiency |
title_short | Estimating health system opportunity costs: the role of non-linearities and inefficiency |
title_sort | estimating health system opportunity costs: the role of non-linearities and inefficiency |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9617442/ https://www.ncbi.nlm.nih.gov/pubmed/36309687 http://dx.doi.org/10.1186/s12962-022-00391-y |
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