Developing an Australian Value Set for the Recovering Quality of Life-Utility Index (ReQoL-UI) instrument using Discrete Choice Experiment with Duration.
{"title":"Developing an Australian Value Set for the Recovering Quality of Life-Utility Index (ReQoL-UI) instrument using Discrete Choice Experiment with Duration.","authors":"Thao Thai, Lidia Engel, Jemimah Ride, Brendan Mulhern, Richard Norman, Cathrine Mihalopoulos","doi":"10.1016/j.jval.2024.12.008","DOIUrl":null,"url":null,"abstract":"<p><strong>Objectives: </strong>The Recovering Quality of Life-Utility Index (ReQoL-UI) instrument was designed to measure the quality of life outcomes for people over 16 years of age with mental health problems. We aim to elicit societal preferences for the ReQoL-UI health states to facilitate better decision-making in Australia.</p><p><strong>Methods: </strong>A discrete choice experiment (DCE) with duration was embedded in a self-complete online survey and administered to a representative sample (n=1019) of the Australian adult population aged 18 years and more, stratified for age, sex and geographic location. A partial subset design DCE was used with 3 fixed attributes and 5 varying attributes containing 240 choice tasks that were blocked into 20 blocks, so that each respondent was assigned a block of 12 choice tasks. The value set was modelled using the conditional logit model with utility decrements directly anchored on the 0 to 1 dead-full health scale. Preference heterogeneity was tested using the mixed logit model.</p><p><strong>Results: </strong>The final value set reflects the monotonic nature of the ReQoL-UI descriptive systems where the best health state defined by the descriptive system has a value of 1 and the worst state has a value of -0.585. The most important dimension was physical health problems while the least important attribute was self-perception. Sensitivity analysis and analysis of preference heterogeneity show the stability of the value set.</p><p><strong>Conclusion: </strong>The value set which reflects the preferences of the Australian population facilitates the calculation of an index for quality-adjusted life years in mental health interventions cost-utility analyses.</p>","PeriodicalId":23508,"journal":{"name":"Value in Health","volume":" ","pages":""},"PeriodicalIF":4.9000,"publicationDate":"2025-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Value in Health","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1016/j.jval.2024.12.008","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ECONOMICS","Score":null,"Total":0}
引用次数: 0
Abstract
Objectives: The Recovering Quality of Life-Utility Index (ReQoL-UI) instrument was designed to measure the quality of life outcomes for people over 16 years of age with mental health problems. We aim to elicit societal preferences for the ReQoL-UI health states to facilitate better decision-making in Australia.
Methods: A discrete choice experiment (DCE) with duration was embedded in a self-complete online survey and administered to a representative sample (n=1019) of the Australian adult population aged 18 years and more, stratified for age, sex and geographic location. A partial subset design DCE was used with 3 fixed attributes and 5 varying attributes containing 240 choice tasks that were blocked into 20 blocks, so that each respondent was assigned a block of 12 choice tasks. The value set was modelled using the conditional logit model with utility decrements directly anchored on the 0 to 1 dead-full health scale. Preference heterogeneity was tested using the mixed logit model.
Results: The final value set reflects the monotonic nature of the ReQoL-UI descriptive systems where the best health state defined by the descriptive system has a value of 1 and the worst state has a value of -0.585. The most important dimension was physical health problems while the least important attribute was self-perception. Sensitivity analysis and analysis of preference heterogeneity show the stability of the value set.
Conclusion: The value set which reflects the preferences of the Australian population facilitates the calculation of an index for quality-adjusted life years in mental health interventions cost-utility analyses.
期刊介绍:
Value in Health contains original research articles for pharmacoeconomics, health economics, and outcomes research (clinical, economic, and patient-reported outcomes/preference-based research), as well as conceptual and health policy articles that provide valuable information for health care decision-makers as well as the research community. As the official journal of ISPOR, Value in Health provides a forum for researchers, as well as health care decision-makers to translate outcomes research into health care decisions.