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Where’s WALY? : A proof of concept study of the ‘wellbeing adjusted life year’ using secondary analysis of cross-sectional survey data

BACKGROUND: The Quality-Adjusted Life Year (QALY) is a measure that combines life extension and health improvement in a single score, reflecting preferences around different types of health gain. It can therefore be used to inform decision-making around allocation of health care resources to mutuall...

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Autores principales: Johnson, Rebecca, Jenkinson, David, Stinton, Chris, Taylor-Phillips, Sian, Madan, Jason, Stewart-Brown, Sarah, Clarke, Aileen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5016960/
https://www.ncbi.nlm.nih.gov/pubmed/27608769
http://dx.doi.org/10.1186/s12955-016-0532-5
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author Johnson, Rebecca
Jenkinson, David
Stinton, Chris
Taylor-Phillips, Sian
Madan, Jason
Stewart-Brown, Sarah
Clarke, Aileen
author_facet Johnson, Rebecca
Jenkinson, David
Stinton, Chris
Taylor-Phillips, Sian
Madan, Jason
Stewart-Brown, Sarah
Clarke, Aileen
author_sort Johnson, Rebecca
collection PubMed
description BACKGROUND: The Quality-Adjusted Life Year (QALY) is a measure that combines life extension and health improvement in a single score, reflecting preferences around different types of health gain. It can therefore be used to inform decision-making around allocation of health care resources to mutually exclusive options that would produce qualitatively different health benefits. A number of quality-of-life instruments can be used to calculate QALYs. The EQ-5D is one of the most commonly used, and is the preferred option for submissions to NICE (https://www.nice.org.uk/process/pmg9/). However, it has limitations that might make it unsuitable for use in areas such as public and mental health where interventions may aim to improve well-being. One alternative to the QALY is a Wellbeing-Adjusted Life Year. In this study we explore the need for a Wellbeing-Adjusted Life Year measure by examining the extent to which a measure of wellbeing (the Warwick-Edinburgh Mental Well-being Scale) maps onto the EQ-5D-3L. METHODS: Secondary analyses were conducted on data from the Coventry Household Survey in which 7469 participants completed the EQ-5D-3L, Warwick-Edinburgh Mental Well-being Scale, and a measure of self-rated health. Data were analysed using descriptive statistics, Pearson’s and Spearman’s correlations, linear regression, and receiver operating characteristic curves. RESULTS: Approximately 75 % of participants scored the maximum on the EQ-5D-3L. Those with maximum EQ-5D-3L scores reported a wide range of levels of mental wellbeing. Both the Warwick-Edinburgh Mental Well-being Scale and the EQ-5D-3L were able to detect differences between those with higher and lower levels of self-reported health. Linear regression indicated that scores on the Warwick-Edinburgh Mental Well-being Scale and the EQ-5D-3L were weakly, positively correlated (with R(2) being 0.104 for the index and 0.141 for the visual analogue scale). CONCLUSION: The Warwick-Edinburgh Mental Well-being Scale maps onto the EQ-5D-3L to only a limited extent. Levels of mental wellbeing varied greatly amongst participants who had the maximum score on the EQ-5D-3L. To evaluate the relative effectiveness of interventions that impact on mental wellbeing, a new measure – a Wellbeing Adjusted Life Year – is needed.
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spelling pubmed-50169602016-09-10 Where’s WALY? : A proof of concept study of the ‘wellbeing adjusted life year’ using secondary analysis of cross-sectional survey data Johnson, Rebecca Jenkinson, David Stinton, Chris Taylor-Phillips, Sian Madan, Jason Stewart-Brown, Sarah Clarke, Aileen Health Qual Life Outcomes Research BACKGROUND: The Quality-Adjusted Life Year (QALY) is a measure that combines life extension and health improvement in a single score, reflecting preferences around different types of health gain. It can therefore be used to inform decision-making around allocation of health care resources to mutually exclusive options that would produce qualitatively different health benefits. A number of quality-of-life instruments can be used to calculate QALYs. The EQ-5D is one of the most commonly used, and is the preferred option for submissions to NICE (https://www.nice.org.uk/process/pmg9/). However, it has limitations that might make it unsuitable for use in areas such as public and mental health where interventions may aim to improve well-being. One alternative to the QALY is a Wellbeing-Adjusted Life Year. In this study we explore the need for a Wellbeing-Adjusted Life Year measure by examining the extent to which a measure of wellbeing (the Warwick-Edinburgh Mental Well-being Scale) maps onto the EQ-5D-3L. METHODS: Secondary analyses were conducted on data from the Coventry Household Survey in which 7469 participants completed the EQ-5D-3L, Warwick-Edinburgh Mental Well-being Scale, and a measure of self-rated health. Data were analysed using descriptive statistics, Pearson’s and Spearman’s correlations, linear regression, and receiver operating characteristic curves. RESULTS: Approximately 75 % of participants scored the maximum on the EQ-5D-3L. Those with maximum EQ-5D-3L scores reported a wide range of levels of mental wellbeing. Both the Warwick-Edinburgh Mental Well-being Scale and the EQ-5D-3L were able to detect differences between those with higher and lower levels of self-reported health. Linear regression indicated that scores on the Warwick-Edinburgh Mental Well-being Scale and the EQ-5D-3L were weakly, positively correlated (with R(2) being 0.104 for the index and 0.141 for the visual analogue scale). CONCLUSION: The Warwick-Edinburgh Mental Well-being Scale maps onto the EQ-5D-3L to only a limited extent. Levels of mental wellbeing varied greatly amongst participants who had the maximum score on the EQ-5D-3L. To evaluate the relative effectiveness of interventions that impact on mental wellbeing, a new measure – a Wellbeing Adjusted Life Year – is needed. BioMed Central 2016-09-08 /pmc/articles/PMC5016960/ /pubmed/27608769 http://dx.doi.org/10.1186/s12955-016-0532-5 Text en © The Author(s). 2016 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
Johnson, Rebecca
Jenkinson, David
Stinton, Chris
Taylor-Phillips, Sian
Madan, Jason
Stewart-Brown, Sarah
Clarke, Aileen
Where’s WALY? : A proof of concept study of the ‘wellbeing adjusted life year’ using secondary analysis of cross-sectional survey data
title Where’s WALY? : A proof of concept study of the ‘wellbeing adjusted life year’ using secondary analysis of cross-sectional survey data
title_full Where’s WALY? : A proof of concept study of the ‘wellbeing adjusted life year’ using secondary analysis of cross-sectional survey data
title_fullStr Where’s WALY? : A proof of concept study of the ‘wellbeing adjusted life year’ using secondary analysis of cross-sectional survey data
title_full_unstemmed Where’s WALY? : A proof of concept study of the ‘wellbeing adjusted life year’ using secondary analysis of cross-sectional survey data
title_short Where’s WALY? : A proof of concept study of the ‘wellbeing adjusted life year’ using secondary analysis of cross-sectional survey data
title_sort where’s waly? : a proof of concept study of the ‘wellbeing adjusted life year’ using secondary analysis of cross-sectional survey data
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5016960/
https://www.ncbi.nlm.nih.gov/pubmed/27608769
http://dx.doi.org/10.1186/s12955-016-0532-5
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