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Objectives: This study generates VILL-UI (Vision Impairment in Low Luminance - Utility Index), a preference-weighted measure (PWM) derived from the VILL-33 measure for use in patients with age-related macular degeneration (AMD) and valued to generate United Kingdom and German preference weights., Methods: A PWM consists of a classification system to describe health and utility values for every state described by the classification. The classification was derived using existing data collected as part of the MACUSTAR study, a low-interventional study on AMD, conducted at 20 clinical sites across Europe. Items were selected using psychometric and Rasch analyses, published criteria around PWM suitability, alongside instrument developer views and concept elicitation work that informed VILL-33 development. An online discrete choice experiment (DCE) with duration of the health state was conducted with the United Kingdom and German public. Responses were modeled to generate utility values for all possible health states., Results: The classification system has 5 items across the 3 domains of VILL-33: reading and accessing information, mobility and safety, and emotional well-being. The DCE samples (United Kingdom: n = 1004, Germany: n = 1008) are broadly representative and demonstrate good understanding of the tasks. The final DCE analyses produce logically consistent and significant coefficients., Conclusions: This study enables responses to VILL-33 to be directly used to inform economic evaluation in AMD. The elicitation of preferences from both United Kingdom and Germany enables greater application of VILL-UI for economic evaluation throughout Europe. VILL-UI fills a gap in AMD in which generic preference-weighted measures typically lack sensitivity., Competing Interests: Author Disclosures Author disclosure forms can be accessed in the Supplemental Material section., (Copyright © 2024. Published by Elsevier Inc.)

Objectives: A high-quality and widely accepted UK EQ-5D-5L value set is urgently required to enable the latest version of EQ-5D scored using recent UK public preferences to inform policy including health technology assessments submitted to the National Institute for Health and Care Excellence. This article outlines the study protocol for the generation of a new EQ-5D-5L UK value set., Methods: Twelve hundred interviews will be undertaken using the composite time trade-off elicitation technique for 102 health states (86 from the international EQ-5D-5L valuation protocol, plus 16 with best predictive performance in an extended design used in the Native American EQ-5D-5L valuation). The sample will be UK adults (age ≥18 years) proportionately representative across England, Wales, Scotland, and Northern Ireland, representative for age, sex, ethnicity, and socioeconomic group, with inclusion of participants with/without health problems. Participants will choose to be interviewed via videoconference (by Zoom) or in-person in a central venue. Data quality will be rigorously assessed., Results: The value set will be generated using tobit random effects and heteroscedastic tobit models (with censoring at -1) using all data, excluding time trade-off values highlighted by participants as ones they would reconsider and data from interviewers failing protocol compliance. Quality and acceptance will be achieved by public involvement, regular Steering Group meetings, independent assessment of data quality at 4 time points, and final endorsement of data and analyses., Conclusion: This study will produce a UK value set for the EQ-5D-5L for use in prospective and retrospective data sets containing EQ-5D-5L data., (Copyright © 2023. Published by Elsevier Inc.)

Objectives: This article aims to describe the generation and selection of items (stage 2) and face validation (stage 3) of a large international (multilingual) project to develop a new generic measure, the EQ-HWB (EQ Health and Wellbeing), for use in economic evaluation across health, social care, and public health to estimate quality-adjusted life-years., Methods: Items from commonly used generic, carer, social care, and mental health quality of life measures were mapped onto domains or subdomains identified from a literature review. Potential terms and items were reviewed and refined to ensure coverage of the construct of the domains/subdomain (stage 2). Input on the potential item pool, response options, and recall period was sought from 3 key stakeholder groups. The pool of candidate items was tested in qualitative interviews with potential future users in an international face validation study (stage 3)., Results: Stage 2 resulted in the generation of 687 items. Predetermined selection criteria were applied by the research team resulting in 598 items being dropped, leaving 89 items that were reviewed by key stakeholder groups. Face validation (stage 3) tested 97 draft items and 4 response scales. A total of 47 items were retained and 14 were modified, whereas 3 were added to the candidate pool of items. This resulted in a 64-item set., Conclusions: This international multiculture, multilingual study with a common methodology identified many items that performed well across all countries. These were taken to the psychometric testing along with modified and new items for the EQ-HWB., (Copyright © 2022. Published by Elsevier Inc.)

Objectives: To identify the themes to inform the content of a new generic measure, the EQ-HWB (EQ Health and Wellbeing), that can be used in economic evaluation across health, social care, and public health, based on the views of users and beneficiaries of these services including informal carers., Methods: A qualitative review was undertaken. Systematic and citation searches were undertaken focusing on qualitative evidence of the impact on quality of life from reviews for selected health conditions, informal carers, social care users, and primary qualitative work used in the development of selected measures. A subset of studies was included in the review. Framework analysis and synthesis were undertaken based on a conceptual model., Results: A total of 42 reviews and 24 primary studies were selected for inclusion in the review. Extraction and synthesis resulted in 7 high-level themes (with subthemes): (1) feelings and emotions (sadness, anxiety, hope, frustration, safety, guilt/shame); (2) cognition (concentration, memory, confusion, thinking clearly); (3) self-identity (dignity/respect, self-esteem); (4) "coping, autonomy, and control" relationships; (5) social connections (loneliness, social engagement, stigma, support, friendship, belonging, burden); (6) physical sensations (pain, discomfort, sleep, fatigue); and (7) activity (self-care, meaningful activities, mobility, communication, hearing, vision). Apart from physical sensations, most of the other themes and subthemes were relevant across both health and social care, including for informal carers., Conclusions: The findings from this broad review identified themes that go beyond health and that are relevant to patients, informal carers, and social care users. The themes and subthemes informed the domains for the EQ-HWB., (Copyright © 2021 International Society for Pharmacoeconomics and Outcomes Research, Inc. Published by Elsevier Inc. All rights reserved.)

Objectives: Existing measures for estimating quality-adjusted life-years are mostly limited to health-related quality of life. This article presents an overview of the development the EQ-HWB (EQ Health and Wellbeing), which is a measure that encompasses health and wellbeing., Methods: Stages: (1) Establishing domains through reviews of the qualitative literature informed by a conceptual framework. (2) Generation and selection of items to cover the domains. (3) Face validation of these items through qualitative interviews with 168 patients, social care users, general population, and carers across 6 countries (Argentina, Australia, China, Germany, United Kingdom, United States). (4) Extensive psychometric testing of candidate items (using classical, factor analysis, and item response theory methods) on > 4000 respondents in the 6 countries. Stakeholders were consulted throughout., Results: A total of 32 subdomains grouped into 7 high-level domains were identified from the qualitative literature and 97 items generated to cover them. Face validation eliminated 36 items, modified 14, and added 3. Psychometric testing of 64 items found little difference in missing data or problems with response distribution, the conceptual model was confirmed except in China, and most items performed well in the item response theory in all countries. Evidence was presented to stakeholders in 2 rounds of consultation to inform the final selection of items for the EQ-HWB (25-item) and the short version of EQ-HWB (9-items)., Conclusions: EQ-HWB measures have been developed internationally for evaluating interventions in health, public health, and social care including the impact on patients, social care users, and carers., (Copyright © 2022. Published by Elsevier Inc.)

Objectives: This study generates a preference-based measure for capturing the quality of life of people with Duchenne muscular dystrophy (DMD) from a new measure of quality of life, DMD-QoL., Methods: A health state classification system was derived from the DMD-QoL based on psychometric performance of items, factor analysis, and item response theory analysis. Preferences for health states described by the classification system were elicited using an online discrete choice experiment survey with life years as an additional attribute, from members of the UK general population (n = 1043). Discrete choice experiment data was modeled using a conditional fixed-effects logit model and utility estimates were directly anchored on the 1 to 0 full health-dead scale., Results: The health state classification system has 8 dimensions: mobility, difficulty using hands, difficulty breathing, pain, tiredness, worry, participation, and feeling good about yourself. The standard model had mostly statistically significant coefficients and reflected the instrument's monotonic structure. However, 2 dimensions had inconsistent coefficients (where utility increased as health worsened) and a consistent model was estimated that merged adjacent inconsistent severity levels. The best state defined by the classification system has a value of 1 and the worst state has a value of -0.559., Conclusion: The modeled results enable DMD-QoL-8D utility values to be generated using DMD-QoL or DMD-QoL-8D data to generate QALYs for people with DMD. QALYs can then be used to inform economic models of the cost-effectiveness of interventions in DMD. Future research comparing the psychometric performance of DMD-QoL-8D to existing generic preference-based measures, including EQ-5D-5L, is recommended., (Copyright © 2021 ISPOR–The Professional Society for Health Economics and Outcomes Research. Published by Elsevier Inc. All rights reserved.)

Objective: This study examines the impact of data collection method on the sociodemographic and health profile of samples of people with diabetes who complete either an online or postal patient-reported outcome measure (PROM) validation survey., Methods: A longitudinal survey of people with diabetes was conducted using online and postal survey versions. The survey consisted of sociodemographic and health questions, a health and self-management PROM (Health and Self-Management in Diabetes [HASMID]), and 5-level version of EQ-5D. Dose adjustment for normal eating Online, Diabetes UK, and social media were used to recruit online survey participants. A panel of patients at a local National Health Service Trust was randomly allocated to participate in either survey version (two-thirds to postal version). Participants were asked to complete the survey again approximately 3 months later., Results: A total of 2784 participants completed the survey (1908 online, 876 postal). The samples (online versus postal) differed; the online sample was younger, with a larger proportion of women and respondents with type 1 diabetes. There were significant differences in sociodemographic characteristics by type of diabetes across data collection mode. The proportion of respondents who responded again at point 2 was higher in the postal sample (525 postal, 698 online)., Conclusion: The sociodemographic and health profile of samples of people with diabetes differed depending on whether they completed the online or postal survey. Differences are likely due to different recruitment methods and differences in those choosing to respond to different survey versions. Future PROM validation surveys should select data collection methods carefully because these can affect sample characteristics and results., (Copyright © 2019 ISPOR–The Professional Society for Health Economics and Outcomes Research. Published by Elsevier Inc. All rights reserved.)

Objectives: To describe the use of a novel approach in health valuation of a discrete-choice experiment (DCE) including a cost attribute to value a recently developed classification system for measuring the quality-of-life impact (both health and treatment experience) of self-management for diabetes., Methods: A large online survey was conducted using DCE with cost on UK respondents from the general population (n = 1497) and individuals with diabetes (n = 405). The data were modeled using a conditional logit model with robust standard errors. The marginal rate of substitution was used to generate willingness-to-pay (WTP) estimates for every state defined by the classification system. Robustness of results was assessed by including interaction effects for household income., Results: There were some logical inconsistencies and insignificant coefficients for the milder levels of some attributes. There were some differences in the rank ordering of different attributes for the general population and diabetic patients. The WTP to avoid the most severe state was £1118.53 per month for the general population and £2356.02 per month for the diabetic patient population. The results were largely robust., Conclusions: Health and self-management can be valued in a single classification system using DCE with cost. The marginal rate of substitution for key attributes can be used to inform cost-benefit analysis of self-management interventions in diabetes using results from clinical studies in which this new classification system has been applied. The method shows promise, but found large WTP estimates exceeding the cost levels used in the survey., (Copyright © 2018 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.)

Objective: This article reports on a study that used contact lenses to simulate the effects of a visual impairment caused by age-related macular degeneration (ARMD). The primary objective was to examine the feasibility of using this method of simulation. A secondary objective was to compare the results from this experiment with those obtained from ARMD patients (n = 209) using generic preference-based measures (Health Utilities Index 3 (HUI3) and EUROQOL 5 Dimensions (EQ-5D) and patient time trade-off (TTO)., Methods: Utility values were elicited from healthy participants (n = 108) for three ARMD states simulated using contact lenses., Results: A significant relationship was found between visual acuity and TTO values elicited from our sample population (n = 108). It was stronger than that found for HUI3, EQ-5D, and own TTO values from patients (n = 209). Our sample values informed by the experience of simulation were found to be significantly different from values from patient TTO and generic preference-based measures obtained from patients for the same level of visual impairment. Sociodemographic characteristics did not significantly affect results, although baseline TTO utility values were positively associated with TTO values for simulated states. Nevertheless, the patient population was significantly older than the sample population., Conclusions: ARMD has a major impact on our sample values TTO health state values. Differences across four visual health severity groups appear larger than those found for a generic preference-based measure and patient TTO values. For conditions that are difficult to describe and imagine, simulation methods may offer an additional tool when combined with usual methods of description for obtaining better informed general population preferences.