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Developing a dementia-specific health state classification system for a new preference-based instrument AD-5D

BACKGROUND: With an ageing population, the number of people with dementia is rising. The economic impact on the health care system is considerable and new treatment methods and approaches to dementia care must be cost effective. Economic evaluation requires valid patient reported outcome measures, a...

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Autores principales: Nguyen, Kim-Huong, Mulhern, Brendan, Kularatna, Sanjeewa, Byrnes, Joshua, Moyle, Wendy, Comans, Tracy
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5264482/
https://www.ncbi.nlm.nih.gov/pubmed/28122626
http://dx.doi.org/10.1186/s12955-017-0585-0
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author Nguyen, Kim-Huong
Mulhern, Brendan
Kularatna, Sanjeewa
Byrnes, Joshua
Moyle, Wendy
Comans, Tracy
author_facet Nguyen, Kim-Huong
Mulhern, Brendan
Kularatna, Sanjeewa
Byrnes, Joshua
Moyle, Wendy
Comans, Tracy
author_sort Nguyen, Kim-Huong
collection PubMed
description BACKGROUND: With an ageing population, the number of people with dementia is rising. The economic impact on the health care system is considerable and new treatment methods and approaches to dementia care must be cost effective. Economic evaluation requires valid patient reported outcome measures, and this study aims to develop a dementia-specific health state classification system based on the Quality of Life for Alzheimer’s disease (QOL-AD) instrument (nursing home version). This classification system will subsequently be valued to generate a preference-based measure for use in the economic evaluation of interventions for people with dementia. METHODS: We assessed the dimensionality of the QOL-AD to develop a new classification system. This was done using exploratory and confirmatory factor analysis and further assessment of the structure of the measure to ensure coverage of the key areas of quality of life. Secondly, we used Rasch analysis to test the psychometric performance of the items, and select item(s) to describe each dimension. This was done on 13 items of the QOL-AD (excluding two general health items) using a sample of 284 residents living in long-term care facilities in Australia who had a diagnosis of dementia. RESULTS: A five dimension classification system is proposed resulting from the three factor structure (defined as ‘interpersonal environment’, ‘physical health’ and ‘self-functioning’) derived from the factor analysis and two factors (‘memory’ and ‘mood’) from the accompanying review. For the first three dimensions, Rasch analysis selected three questions of the QOL-AD (‘living situation’, ‘physical health’, and ‘do fun things’) with memory and mood questions representing their own dimensions. The resulting classification system (AD-5D) includes many of the health-related quality of life dimensions considered important to people with dementia, including mood, global function and skill in daily living. CONCLUSIONS: The development of the AD-5D classification system is an important step in the future application of the widely used QOL-AD in economic evaluations. Future valuation studies will enable this tool to be used to calculate quality adjusted life years to evaluate treatments and interventions for people diagnosed with mild to moderate dementia.
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spelling pubmed-52644822017-01-30 Developing a dementia-specific health state classification system for a new preference-based instrument AD-5D Nguyen, Kim-Huong Mulhern, Brendan Kularatna, Sanjeewa Byrnes, Joshua Moyle, Wendy Comans, Tracy Health Qual Life Outcomes Research BACKGROUND: With an ageing population, the number of people with dementia is rising. The economic impact on the health care system is considerable and new treatment methods and approaches to dementia care must be cost effective. Economic evaluation requires valid patient reported outcome measures, and this study aims to develop a dementia-specific health state classification system based on the Quality of Life for Alzheimer’s disease (QOL-AD) instrument (nursing home version). This classification system will subsequently be valued to generate a preference-based measure for use in the economic evaluation of interventions for people with dementia. METHODS: We assessed the dimensionality of the QOL-AD to develop a new classification system. This was done using exploratory and confirmatory factor analysis and further assessment of the structure of the measure to ensure coverage of the key areas of quality of life. Secondly, we used Rasch analysis to test the psychometric performance of the items, and select item(s) to describe each dimension. This was done on 13 items of the QOL-AD (excluding two general health items) using a sample of 284 residents living in long-term care facilities in Australia who had a diagnosis of dementia. RESULTS: A five dimension classification system is proposed resulting from the three factor structure (defined as ‘interpersonal environment’, ‘physical health’ and ‘self-functioning’) derived from the factor analysis and two factors (‘memory’ and ‘mood’) from the accompanying review. For the first three dimensions, Rasch analysis selected three questions of the QOL-AD (‘living situation’, ‘physical health’, and ‘do fun things’) with memory and mood questions representing their own dimensions. The resulting classification system (AD-5D) includes many of the health-related quality of life dimensions considered important to people with dementia, including mood, global function and skill in daily living. CONCLUSIONS: The development of the AD-5D classification system is an important step in the future application of the widely used QOL-AD in economic evaluations. Future valuation studies will enable this tool to be used to calculate quality adjusted life years to evaluate treatments and interventions for people diagnosed with mild to moderate dementia. BioMed Central 2017-01-25 /pmc/articles/PMC5264482/ /pubmed/28122626 http://dx.doi.org/10.1186/s12955-017-0585-0 Text en © The Author(s). 2017 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
Nguyen, Kim-Huong
Mulhern, Brendan
Kularatna, Sanjeewa
Byrnes, Joshua
Moyle, Wendy
Comans, Tracy
Developing a dementia-specific health state classification system for a new preference-based instrument AD-5D
title Developing a dementia-specific health state classification system for a new preference-based instrument AD-5D
title_full Developing a dementia-specific health state classification system for a new preference-based instrument AD-5D
title_fullStr Developing a dementia-specific health state classification system for a new preference-based instrument AD-5D
title_full_unstemmed Developing a dementia-specific health state classification system for a new preference-based instrument AD-5D
title_short Developing a dementia-specific health state classification system for a new preference-based instrument AD-5D
title_sort developing a dementia-specific health state classification system for a new preference-based instrument ad-5d
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5264482/
https://www.ncbi.nlm.nih.gov/pubmed/28122626
http://dx.doi.org/10.1186/s12955-017-0585-0
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