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Considering mean and inequality health outcomes together: the population health performance index
BACKGROUND: The purpose was to develop and test a population health measure that combines mean health outcomes and inequalities into a single GDP-like metric to help policymakers measure population health performance on both dimensions in one metric. METHODS: The Population Health Performance Index...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5816551/ https://www.ncbi.nlm.nih.gov/pubmed/29452592 http://dx.doi.org/10.1186/s12939-018-0731-2 |
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author | Kindig, David Lardinois, Nicholas Asada, Yukiko Mullahy, John |
author_facet | Kindig, David Lardinois, Nicholas Asada, Yukiko Mullahy, John |
author_sort | Kindig, David |
collection | PubMed |
description | BACKGROUND: The purpose was to develop and test a population health measure that combines mean health outcomes and inequalities into a single GDP-like metric to help policymakers measure population health performance on both dimensions in one metric. METHODS: The Population Health Performance Index is a weighted average of a mean index and an inequality index according to the user’s inequality aversion. We deploy this methodology for two combinations of health outcome and disparity domain: infant mortality by race and unhealthy days by education. RESULTS: The PHPI is bounded between 0 and 1, and is comprised of a weighted average of two separate indices: a mean index and an inequality index, with 1 representing the ideal state of no ill health and no inequality and 0 representing the worst state in the U.S. PHPI values across states (neutral 50:50 weighting) vary between 0.60 (Massachusetts) to 0.17 (Delaware) for infant mortality by race and between 0.65 (North Dakota) to 0.00 (West Virginia) for unhealthy days by education. For some states, the choice of inequality aversion significantly impacts their PHPI value and state rank. CONCLUSIONS: Mean and inequality health outcomes can be combined into a single Population Health Performance Index for use by public and private policy makers, like the GDP is used as a summary metric to measure economic output. The index can allow for varying degrees of inequality aversion, an individual’s or jurisdiction’s value choice that can substantially impact the value of this new summary population health metric. |
format | Online Article Text |
id | pubmed-5816551 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-58165512018-02-21 Considering mean and inequality health outcomes together: the population health performance index Kindig, David Lardinois, Nicholas Asada, Yukiko Mullahy, John Int J Equity Health Research BACKGROUND: The purpose was to develop and test a population health measure that combines mean health outcomes and inequalities into a single GDP-like metric to help policymakers measure population health performance on both dimensions in one metric. METHODS: The Population Health Performance Index is a weighted average of a mean index and an inequality index according to the user’s inequality aversion. We deploy this methodology for two combinations of health outcome and disparity domain: infant mortality by race and unhealthy days by education. RESULTS: The PHPI is bounded between 0 and 1, and is comprised of a weighted average of two separate indices: a mean index and an inequality index, with 1 representing the ideal state of no ill health and no inequality and 0 representing the worst state in the U.S. PHPI values across states (neutral 50:50 weighting) vary between 0.60 (Massachusetts) to 0.17 (Delaware) for infant mortality by race and between 0.65 (North Dakota) to 0.00 (West Virginia) for unhealthy days by education. For some states, the choice of inequality aversion significantly impacts their PHPI value and state rank. CONCLUSIONS: Mean and inequality health outcomes can be combined into a single Population Health Performance Index for use by public and private policy makers, like the GDP is used as a summary metric to measure economic output. The index can allow for varying degrees of inequality aversion, an individual’s or jurisdiction’s value choice that can substantially impact the value of this new summary population health metric. BioMed Central 2018-02-17 /pmc/articles/PMC5816551/ /pubmed/29452592 http://dx.doi.org/10.1186/s12939-018-0731-2 Text en © The Author(s). 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. 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 Kindig, David Lardinois, Nicholas Asada, Yukiko Mullahy, John Considering mean and inequality health outcomes together: the population health performance index |
title | Considering mean and inequality health outcomes together: the population health performance index |
title_full | Considering mean and inequality health outcomes together: the population health performance index |
title_fullStr | Considering mean and inequality health outcomes together: the population health performance index |
title_full_unstemmed | Considering mean and inequality health outcomes together: the population health performance index |
title_short | Considering mean and inequality health outcomes together: the population health performance index |
title_sort | considering mean and inequality health outcomes together: the population health performance index |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5816551/ https://www.ncbi.nlm.nih.gov/pubmed/29452592 http://dx.doi.org/10.1186/s12939-018-0731-2 |
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