1. Estimating a Preference-Based Index for Mental Health From the Recovering Quality of Life Measure: Valuation of Recovering Quality of Life Utility Index
- Author
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Anju Devianee Keetharuth, Jakob B. Bjorner, Donna Rowen, and John Brazier
- Subjects
Adult ,Male ,Quality of Life/psychology ,Adolescent ,Psychometrics ,Interview ,ReQoL-10 ,Cost-Benefit Analysis ,Health Status ,Psychological intervention ,QALYs ,Hope ,Young Adult ,03 medical and health sciences ,Leisure Activities ,0302 clinical medicine ,Preference-Based Assessment ,Surveys and Questionnaires ,Scoring algorithm ,Cost-Benefit Analysis/methods ,Item response theory ,Mental Health/economics ,Humans ,Interpersonal Relations ,030212 general & internal medicine ,Aged ,Valuation (finance) ,Aged, 80 and over ,Surveys and Questionnaires/standards ,Actuarial science ,030503 health policy & services ,Health Policy ,ReQoL-20 ,Public Health, Environmental and Occupational Health ,Regression analysis ,Middle Aged ,Random effects model ,Mental health ,Mental Health ,Socioeconomic Factors ,Personal Autonomy ,Quality of Life ,Female ,preference-based measure ,0305 other medical science ,Psychology - Abstract
Background There are increasing concerns about the appropriateness of generic preference-based measures to capture health benefits in the area of mental health. Objectives The aim of this study is to estimate preference weights for a new measure, Recovering Quality of Life (ReQoL-10), to better capture the benefits of mental healthcare. Methods Psychometric analyses of a larger sample of mental health service users (n = 4266) using confirmatory factor analyses and item response theory were used to derive a health state classification system and inform the selection of health states for utility assessment. A valuation survey with members of the UK public representative in terms of age, sex, and region was conducted using face-to-face interviewer administered time-trade-off with props. A series of regression models were fitted to the data and the best performing model selected for the scoring algorithm. Results The ReQoL-Utility Index (UI) classification system comprises 6 mental health items and 1 physical health item. Sixty-four health states were valued by 305 participants. The preferred model was a random effects model, with significant and consistent coefficients and best model fit. Estimated utilities modeled for all health states ranged from −0.195 (state worse than dead) to 1 (best possible state). Conclusions The development of the ReQoL-UI is based on a novel application of item response theory methods for generating the classification system and selecting health states for valuation. Conventional time-trade-off was used to elicit utility values that are modeled to enable the generation of QALYs for use in cost-utility analysis of mental health interventions., Highlights • In light of concerns around the use of EQ-5D to assess mental health outcomes, there is a need for a new generic preference-based measure with focus on mental health for use in the economic evaluation of interventions aimed at improving outcomes in this area. • This paper uses item response theory (IRT) to construct a health classification system for the ReQoL-10 and the ReQoL-20. IRT was also used in a novel way to select health states amenable for valuation, ensuring the plausibility of these states. Preference weights were generated to enable utilities to be calculated from ReQoL-10 and ReQoL-20. • The paper highlights a novel method of selecting health states for valuation purposes. An algorithm is presented to generate quality adjusted life years from the ReQoL measures for use in the economic evaluation of health and care interventions in the area of mental health. Future research comparing ReQoL-UI and EQ-5D will determine whether the former presents an improvement in capturing benefits in the area of mental health.
- Published
- 2021
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