Mapping the Health of Nation Outcomes Scale (HoNOS) onto the Recovering Quality of Life Utility Index (ReQoL-UI)

Aim: The aim of this project is to develop and assess a mapping function to predict ReQoL-UI (a patient-reported mental health-specific preference-based measure) scores from HoNOS scores (clinician-reported measure, Health of Nation Outcomes Score). Methods: Participants were recruited from 14 secondary mental health services in England, UK, and their clinician completed HoNoS. Mapping models were estimated using Ordinary Least Squares (OLS) on individual level and mean level data and different model specifications were explored. Model performance was assessed using mean absolute error (MAE), root mean square error (RMSE), percentage of observations with absolute errors greater than 0.1, and plots of the observed and predicted ReQoL-UI utilities and errors. Results: Matched ReQoL-UI and HoNOS scores were collected for 649 participants. The sample comprised 56% inpatients, with overall mean ReQoL-UI utility of 0.683 and range from 1 to -0.195. Correlations between ReQoL-UI (items and utility) and HoNOS scores were moderate (0.2<r<0.4) or small (<0.2). The best model was OLS estimated using mean level data, with lowest MAE (0.046) and RMSE (0.056). Discussion: There is little conceptual overlap between ReQoL-UI and HoNOS. They measure different concepts and, arguably, service users and clinicians, who complete the measures respectively, have different perspectives. Under these circumstances, caution is recommended when applying these estimates

Estimating a preference-based index for mental health from the Recovering Quality of Life (ReQoL) measure : valuation of ReQoL-UI

Objectives There are increasing concerns about the appropriateness of generic preference-based measures to capture health benefits in the area of mental health. This study estimates preference weights for a new measure, Recovering Quality of Life (ReQoL-10), to better capture the benefits of mental health care. Methods Psychometric analyses of a larger sample of mental health service users (n = 4266) using confirmatory factor analyses and item response theory (IRT) 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, gender and region was conducted using face-to-face interviewer administered time-trade-off (TTO) 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-UI classification system comprises six mental health items and one physical health (PH) 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 modelled 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 IRT methods for generating the classification system and selecting health states for valuation. Conventional TTO was used to elicit utility values that are modelled to enable the generation of QALYs for use in cost-utility analysis of mental health interventions

Use of generic and condition-specific measures of health-related quality of life in NICE decision-making: systematic review, statistical modelling and survey.

© Queen’s Printer and Controller of HMSO 2014Background: The National Institute for Health and Care Excellence recommends the use of generic preference-based measures (GPBMs) of health for its Health Technology Assessments (HTAs). However, these data may not be available or appropriate for all health conditions. Objectives: To determine whether GPBMs are appropriate for some key conditions and to explore alternative methods of utility estimation when data from GPBMs are unavailable or inappropriate. Design: The project was conducted in three stages: (1) A systematic review of the psychometric properties of three commonly used GPBMs [EQ-5D, SF-6D and Health Utilities Index Mark 3 (HUI3)] in four broadly defined conditions: visual impairment, hearing impairment, cancer and skin conditions. (2) Potential modelling approaches to ‘map’ EQ-5D values from condition-specific and clinical measures of health [European Organisation for Research and Treatment of Cancer Quality-of-life Questionnaire Core 30 (EORTC QLQ-C30) and Functional Assessment of Cancer Therapy – General Scale (FACT-G)] are compared for predictive ability and goodness of fit using two separate data sets. (3) Three potential extensions to the EQ-5D are developed as ‘bolt-on’ items relating to hearing, tiredness and vision. They are valued using the time trade-off method. A second valuation study is conducted to fully value the EQ-5D with and without the vision bolt-on item in an additional sample of 300 people. Main outcome measures: Comparisons of EQ-5D, SF-6D and HUI3 in four conditions with various generic and condition-specific measures. Mapping functions were estimated between EORTC QLQ-C30 and FACT-G with EQ-5D. Three bolt-ons to the EQ-5D were developed: EQ + hearing/vision/tiredness. A full valuation study was conducted for the EQ + vision. Results: (1) EQ-5D was valid and responsive for skin conditions and most cancers; in vision, its performance varied according to aetiology; and performance was poor for hearing impairments. The HUI3 performed well for hearing and vision disorders. It also performed well in cancers although evidence was limited and there was no evidence in skin conditions. There were limited data for SF-6D in all four conditions and limited evidence on reliability of all instruments. (2) Mapping algorithms were estimated to predict EQ-5D values from alternative cancer-specific measures of health. Response mapping using all the domain scores was the best performing model for the EORTC QLQ-C30. In an exploratory analysis, a limited dependent variable mixture model performed better than an equivalent linear model. In the full analysis for the FACT-G, linear regression using ordinary least squares gave the best predictions followed by the tobit model. (3) The exploratory valuation study found that bolt-on items for vision, hearing and tiredness had a significant impact on values of the health states, but the direction and magnitude of differences depended on the severity of the health state. The vision bolt-on item had a statistically significant impact on EQ-5D health state values and a full valuation model was estimated. Conclusions: EQ-5D performs well in studies of cancer and skin conditions. Mapping techniques provide a solution to predict EQ-5D values where EQ-5D has not been administered. For conditions where EQ-5D was found to be inappropriate, including some vision disorders and for hearing, bolt-ons provide a promising solution. More primary research into the psychometric properties of the generic preference-based measures is required, particularly in cancer and for the assessment of reliability. Further research is needed for the development and valuation of bolt-ons to EQ-5D.UK Medical Research Council (MRC) as part of the MRC-NIHR methodology research programme (reference G0901486

Estimating a preference-based index for mental health from the recovering quality of life measure: valuation of recovering quality of life utility index

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

Evaluating public health interventions for obesity from the perspective of local health authorities

The aim of the Policy Research Unit in Economic Evaluation in Health and Care Interventions is to assist policy makers in the Department of Health (DH) to improve the allocation of resources through high - quality research. As part of the agreed programme, the unit will be undertaking applied research on obesity with special reference to evaluating public health interventions for obesity from th e local health perspectives (Annex 1) . The focus on interventions at the local level emanates from the government’s policy of local authorities in increasing the wellbeing of their po pulation as articulated below: “Local government is best placed to influence many of the wider factors that affect health and wellbeing.”[1] This paper has been produced on request from the DH a nd is designed as a discussion document intended for dissemination to policy makers to help identify areas around which joint dis cussions would be useful in terms of identifying potential ideas, issues and questions relating to the project remit

Convergent validity of EQ-5D with core outcomes in dementia: a systematic review

Objectives To explore through a systematic review, the convergent validity of EQ-5D (EQ-5D-3L and EQ-5D-5L (total score and dimensions)) with core outcomes in dementia and investigate how this may be impacted by rater-type; with the aim of informing researchers when choosing measures to use in dementia trials. Methods To identify articles relevant to the convergent validity of EQ-5D with core dementia outcomes, three databases were electronically searched to September 2022. Studies were considered eligible for inclusion within the review if they included individual level data from people with dementia of any type, collected self and/or proxy reported EQ-5D and collected at least one core dementia outcome measure. Relevant data such as study sample size, stage of dementia and administration of EQ-5D was extracted, and a narrative synthesis was adopted. Results The search strategy retrieved 271 unique records, of which 30 met the inclusion criteria for the review. Twelve different core outcome measures were used to capture dementia outcomes: cognition, function, and behaviour/mood across the studies. Most studies used EQ-5D-3L (n = 27). Evidence related to the relationship between EQ-5D and measures of function and behaviour/mood was the most robust, with unanimous directions of associations, and more statistically significant findings. EQ-5D dimensions exhibited associations with corresponding clinical outcomes, whereby relationships were stronger with proxy-EQ-5D (than self-report). Conclusion Measuring health-rated quality of life in dementia populations is a complex issue, particularly when considering balancing the challenges associated with both self and proxy report. Published evidence indicates that EQ-5D shows evidence of convergent validity with the key dementia outcomes, therefore capturing these relevant dementia outcomes. The degree of associations with clinical measures was stronger when considering proxy-reported EQ-5D and differed by EQ-5D dimension type. This review has revealed that, despite the limited targeted psychometric evidence pool and reliance on clinical and observational studies, EQ-5D exhibits convergent validity with other dementia outcome measures

Who should value children’s health and how? An international Delphi study

Valuing child health necessitates normative methodological decisions on whose preferences should be elicited and who should be imagined as experiencing impaired health. Formal guidance is limited and expert consensus unclear. This study sought to establish the degree of consensus among expert stakeholders on normative issues of who to ask and who should be imagined when valuing child health (7–17 years) to inform UK health technology assessment. Sixty-two experts (n = 47 in Round 2) from 18 countries participated in a modified, two-round online Delphi survey (Round 1: May-June 2023; Round 2: September-October 2023). Participants were expert stakeholders in child health valuation, including academics (n = 38); industry/consultancy representatives (including the charity/not-for-profit sector; n = 13); and UK policy/government representatives (n = 11). The Delphi survey was modified between rounds and consisted of 9-point Likert, categorical, multiple-choice, and free-text questions on normative issues in valuing child health. Responses were analysed descriptively and thematically. An a priori criterion of ≥75% agreement was established for formal consensus, while areas approaching consensus (≥70% agreement) and without consensus were identified as a future research primer. Consensus was observed that older adolescents (aged 16–17 years) and adults (18+ years) should be asked to value child health states. There was consensus that the former should think about themselves when valuing the health states and the latter should imagine a child of some form (e.g., imagining themselves as a child or another hypothetical child). However, no consensus was evident on what form this should take. Several other methodological issues also reached consensus. These findings are largely consistent with recent views elicited qualitatively from members of the public and other stakeholders on normative issues in valuing child health. The results mean that, contrary to what has been done in previous child health valuation studies, efforts should be made to involve both older adolescents (16+ years) and adults in child health valuation