Cargando…

Valuation of preference-based measures: can existing preference data be used to generate better estimates?

BACKGROUND: Experimental studies to develop valuations of health state descriptive systems like EQ-5D or SF-6D need to be conducted in different countries, because social and cultural differences are likely to lead to systematically different valuations. There is a scope utilize the evidence in one...

Descripción completa

Detalles Bibliográficos
Autor principal: Kharroubi, Samer A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5987483/
https://www.ncbi.nlm.nih.gov/pubmed/29866108
http://dx.doi.org/10.1186/s12955-018-0945-4
_version_ 1783329126100238336
author Kharroubi, Samer A.
author_facet Kharroubi, Samer A.
author_sort Kharroubi, Samer A.
collection PubMed
description BACKGROUND: Experimental studies to develop valuations of health state descriptive systems like EQ-5D or SF-6D need to be conducted in different countries, because social and cultural differences are likely to lead to systematically different valuations. There is a scope utilize the evidence in one country to help with the design and the analysis of a study in another, for this to enable the generation of utility estimates of the second country much more precisely than would have been possible when collecting and analyzing the country’s data alone. METHODS: We analyze SF-6D valuation data elicited from representative samples corresponding to the Hong Kong (HK) and United Kingdom (UK) general adult populations through the use of the standard gamble technique to value 197 and 249 health states respectively. We apply a nonparametric Bayesian model to estimate a HK value set using the UK dataset as informative prior to improve its estimation. Estimates are compared to a HK value set estimated using HK values alone using mean predictions and root mean square error. RESULTS: The novel method of modelling utility functions permitted the UK valuations to contribute significant prior information to the Hong Kong analysis. The results suggest that using HK data alongside the existing UK data produces HK utility estimates better than using the HK study data by itself. CONCLUSION: The promising results suggest that existing preference data could be combined with valuation study in a new country to generate preference weights, making own country value sets more achievable for low and middle income countries. Further research is encouraged.
format Online
Article
Text
id pubmed-5987483
institution National Center for Biotechnology Information
language English
publishDate 2018
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-59874832018-07-10 Valuation of preference-based measures: can existing preference data be used to generate better estimates? Kharroubi, Samer A. Health Qual Life Outcomes Research BACKGROUND: Experimental studies to develop valuations of health state descriptive systems like EQ-5D or SF-6D need to be conducted in different countries, because social and cultural differences are likely to lead to systematically different valuations. There is a scope utilize the evidence in one country to help with the design and the analysis of a study in another, for this to enable the generation of utility estimates of the second country much more precisely than would have been possible when collecting and analyzing the country’s data alone. METHODS: We analyze SF-6D valuation data elicited from representative samples corresponding to the Hong Kong (HK) and United Kingdom (UK) general adult populations through the use of the standard gamble technique to value 197 and 249 health states respectively. We apply a nonparametric Bayesian model to estimate a HK value set using the UK dataset as informative prior to improve its estimation. Estimates are compared to a HK value set estimated using HK values alone using mean predictions and root mean square error. RESULTS: The novel method of modelling utility functions permitted the UK valuations to contribute significant prior information to the Hong Kong analysis. The results suggest that using HK data alongside the existing UK data produces HK utility estimates better than using the HK study data by itself. CONCLUSION: The promising results suggest that existing preference data could be combined with valuation study in a new country to generate preference weights, making own country value sets more achievable for low and middle income countries. Further research is encouraged. BioMed Central 2018-06-05 /pmc/articles/PMC5987483/ /pubmed/29866108 http://dx.doi.org/10.1186/s12955-018-0945-4 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
Kharroubi, Samer A.
Valuation of preference-based measures: can existing preference data be used to generate better estimates?
title Valuation of preference-based measures: can existing preference data be used to generate better estimates?
title_full Valuation of preference-based measures: can existing preference data be used to generate better estimates?
title_fullStr Valuation of preference-based measures: can existing preference data be used to generate better estimates?
title_full_unstemmed Valuation of preference-based measures: can existing preference data be used to generate better estimates?
title_short Valuation of preference-based measures: can existing preference data be used to generate better estimates?
title_sort valuation of preference-based measures: can existing preference data be used to generate better estimates?
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5987483/
https://www.ncbi.nlm.nih.gov/pubmed/29866108
http://dx.doi.org/10.1186/s12955-018-0945-4
work_keys_str_mv AT kharroubisamera valuationofpreferencebasedmeasurescanexistingpreferencedatabeusedtogeneratebetterestimates