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BACKGROUND: A new preference-based measure (MacNew-7D) has recently been developed to allow condition-specific data to be used to capture the quality of life in health economic evaluations in cardiology; however, a general population value set has not yet been developed. This study developed a population utility value set for the MacNew-7D heart disease-specific instrument. METHODS: The discrete choice experiments (DCE) technique was chosen as the preference-elicitation method. The DCE asked respondents to compare two options and to state their preferences. The survey was conducted using an online panel of respondents, with quota sampling using age groups, sex and jurisdictions to achieve representativeness of the Australian population. The total design consisted of 200 choice sets, of which each respondent answered eight. Additionally, each respondent answered two quality control choice sets. The best-fitting models were selected on the basis of consistency, parsimony, and goodness of fit. RESULTS: In total, 1903 respondents were included in the analyses. The MacNew-7D utility value set ranged from -0.4456 to 1.000 for health states defined by the classification system. The best-fitting model retained all levels for five dimensions and collapsed one adjacent level for the other two dimensions. Findings were robust to sensitivity analyses related to the inclusion or exclusion of dominancy and repeat tasks. CONCLUSION: Findings indicated that the MacNew-7D utility value set is likely suitable for estimating quality-adjusted life years derived from the MacNew heart disease health-related quality-of-life questionnaire. This value set was derived from an Australian population-based sample and may not be generalisable to dissimilar populations.

Objectives Responses from hypothetical and experienced valuation tasks of health-related quality of life differ, yet there is limited understanding of why these differences exist, what members of the public think about them, and acceptable resolutions. This study explores public understanding of, opinions on, and potential solutions to differences between hypothetical versus experienced responses, in the context of allocating health resources. Methods Six focus groups with 30 members of the UK adult public were conducted, transcribed verbatim, and analysed using framework analysis. Participants self-completed the EQ-5D-5L, before reporting the expected consequences of being in two hypothetical EQ-5D-5L health states for ten years. Second, participants were presented with prior results on the same task from a public (hypothetical) and patient (experienced) sample. Third, a semi-structured discussion explored participants’: (1) understanding, (2) opinions, and (3) potential resolutions. Results Twenty themes emerged, clustered by the three discussion points. Most participants found imagining the health states difficult without experience, with those aligned to mental health harder to understand. Participants were surprised that health resource allocation was based on hypothetical responses. They viewed experienced responses as more accurate, but noted potential biases. Participants were in favour of better informing, but not influencing the public. Other solutions included incorporating other perspectives (e.g., carers) or combining/weighting responses. Conclusion Members of the UK public appear intuitively not to support using potentially uninformed public values to hypothetical health states in the context of health resource allocation. Acceptable solutions involve recruiting people with greater experience, including other/combinations of views, or better informing respondents.

The disruptions to health research during the COVID-19 pandemic are being recognized globally, and there is a growing need for understanding the pandemic’s impact on the health and health preferences of patients, caregivers, and the general public. Ongoing and planned health preference research (HPR) has been affected due to problems associated with recruitment, data collection, and data interpretation. While there are no “one size fits all” solutions, this commentary summarizes the key challenges in HPR within the context of the pandemic and offers pragmatic solutions and directions for future research. We recommend recruitment of a diverse, typically under-represented population in HPR using online, quota-based crowdsourcing platforms, and community partnerships. We foresee emerging evidence on remote, and telephone-based HPR modes of administration, with further studies on the shifts in preferences related to health and healthcare services as a result of the pandemic. We believe that the recalibration of HPR, due to what one would hope is an impermanent change, will permanently change how we conduct HPR in the future.

BackgroundQuantitative health preference research has shown that different “perspectives”, defined here as who is imagined to be experiencing particular health states, impact stated preferences. This qualitative project aimed to elucidate this phenomenon, within the context of adults’ valuation of child and adolescent health states.MethodsSix focus groups with 30 members of the UK adult public were conducted between December 2019 and February 2020 and analysed using framework analysis. Each focus group had two stages. First, participants individually completed time trade-off tasks and a pairwise task (mirroring a discrete choice experiment without duration) for two EQ-5D-Y health states, assuming a series of perspectives: (a) themselves at current age; (b) another adult; (c) 10-year old child; (d) themselves as a 10-year old child. Second, a semi-structured discussion explored their responses.ResultsParticipants’ views were often heterogeneous, with some common themes. Qualitatively, participants expressed a different willingness to trade-off life years for a 10-year old child versus themselves or another adult, and this differed by the health profile and child imagined. The same health states were often viewed as having a different impact on utility for a 10-year old child than adults. Imagining a 10-year old child is difficult and there is variation in who is imagined. Participants found answering based on their own—adult perspective most acceptable. There were no strong preferences for prioritising child health over working-age adults’ health.ConclusionsIf an adult sample is used to value child- and adolescent-specific health states it is important to consider the perspective employed. Members of the adult public provide different responses when different perspectives are used due to differences in the perceived impact of the same health states. If adults are asked to imagine a child, we recommend that sampling is representative for parental status, since this can affect preferences.

This study examines the comparative equivalence, feasibility and acceptability of video and in-person interviews in generating time trade-off (TTO) values. Sample participants in England were recruited using a blended approach of different methods and sampled based on age, gender, ethnicity, and index of multiple deprivation. Participants were randomly allocated to be interviewed either via video or in-person. Participants completed TTO tasks for the same block of 10 EQ-5D-5L health states using the EQ-VTv2 software. Feasibility, acceptability and equivalence was assessed across mode using: sample representativeness; participant understanding, engagement and feedback; participant preferred mode of interview; data quality; mean utility and distribution of values for each health state; and regression analyses assessing the impact of mode whilst controlling for participant characteristics. The video and in-person samples had statistically significant differences in ethnicity and income but were otherwise broadly similar. Video interviews generated marginally lower quality data across some criteria. Participant understanding and feedback was positive and similar across modes. TTO values were similar across modes; whilst mean in-person TTO values were lower for the more severe states, mode was insignificant in most regression analyses. There was no clear preference of mode across all participants, though the characteristics of participants preferring to be interviewed in-person or by video differs. Video and in-person TTO interviews were feasible, acceptable and generated good-quality data, though video interviews had lower quality data across some criteria. Whilst TTO values differed across modes for the more severe states, mode does not appear to be the cause. The study found that the characteristics of people preferring each mode differed, and this should be taken into account in future valuation studies since sample representativeness for some characteristics, and therefore potentially TTO values, could be affected by the choice of mode.

Health technology assessment agencies often prefer that utilities used to calculate quality-adjusted life years in cost-utility analyses (CUAs) are derived using standardized methods, such as generic preference-based measures completed by patients in clinical trials. However, there are situations when no standardized approach is feasible or appropriate for a specific medical condition or treatment that must be represented in a CUA. When this occurs, vignette-based methods are often used to estimate utilities. A vignette (sometimes called a "scenario," "health state description," "health state vignette," or "health state") is a description of a health state that is valued in a preference elicitation task to obtain a utility estimate. This method is sometimes the only feasible way to estimate utilities representing a concept that is important for a CUA. Consequently, vignette-based studies continue to be conducted and published, with the resulting utilities used in economic models to inform decision making about healthcare resource allocation. Despite the potential impact of vignette-based utilities on medical decision making, there is no published guidance or review of this methodology. This article provides recommendations for researchers, health technology assessment reviewers, and policymakers who may be deciding whether to use vignette-based methods, designing a vignette study, using vignette-based utilities in a CUA, or evaluating a CUA that includes vignette-based utilities. Recommendations are provided on: (A) when to use vignette-based utilities, (B) methods for developing vignettes, (C) valuing vignettes, (D) use of vignette-based utilities in models, and (E) limitations of vignette methods.

Objectives To develop a cancer-specific multi-attribute utility instrument derived from the Functional Assessment of Cancer Therapy - General (FACT-G) health-related quality of life (HRQL) questionnaire. Methods We derived a descriptive system based on a subset of the 27-item FACT-G. Item selection was informed by psychometric analyses of existing FACT-G data (n = 6912) and by patient input (n = 82). We then conducted an online valuation survey, with participants recruited via an Australian general population online panel. A discrete choice experiment (DCE) was used, with attributes being the HRQL dimensions of the descriptive system and survival duration, and 16 choice-pairs per participant. Utility decrements were estimated with conditional logit and mixed logit modeling. Results Eight HRQL dimensions were included in the descriptive system: pain, fatigue, nausea, sleep, work, social support, sadness, and future health worry; each with 5 levels. Of 1737 panel members who accessed the valuation survey, 1644 (95%) completed 1 or more DCE choice-pairs and were included in analyses. Utility decrements were generally monotonic; within each dimension, poorer HRQL levels generally had larger utility decrements. The largest utility decrements were for the highest levels of pain (-0.40) and nausea (-0.28). The worst health state had a utility of -0.54, considerably worse than dead. Conclusions A descriptive system and preference-based scoring approach were developed for the FACT-8D, a new cancer-specific multi-attribute utility instrument derived from the FACT-G. The Australian value set is the first of a series of country-specific value sets planned that can facilitate cost-utility analyses based on items from the FACT-G and related FACIT questionnaires containing FACT-G items.

Background: The international protocol for valuing EQ-5D-5L focuses upon prescribed preference elicitation methods and design. However, there are no recommendations around sampling, recruitment, data analysis or modelling to generate the EQ-5D-5L value set. This review examines methods used to generate international EQ-5D-5L values sets, across sampling, recruitment, data analysis, modelling, assessing model performance and selection of the recommended value set.\ud \ud Methods: All published EQ-5D-5L value sets were identified by a systematic search and confirmed by the EuroQol Group. Data were extracted to assess sampling, recruitment, preference elicitation techniques and design, data analysis, modelling, assessing model\ud performance, and vale set selection. These are summarised in tables.\ud \ud Results: The review included 29 studies with 27 value sets generated using time-trade-off (TTO) data (n=10) only or using a hybrid model that combines TTO and discrete choice experiment data (n=17). TTO data was most commonly estimated using a heteroscedastic Tobit model with censoring at -1, and the hybrid model using a specially created program. Model performance was generally assessed using goodness of fit, logical consistency and\ud significance of coefficients, suitability of the model for the data characteristics and parsimony, though not all selected models account for the specific characteristics of the data.\ud \ud Discussion: Different assessments of model performance and reasoning are provided for the selection of the recommended value set for a country. This raises the question of valid criteria for selecting a recommended value set and whether this should rely upon researchers’ recommendations when value sets are often used to inform public policy.\ud \ud Key points\ud \ud The international protocol for valuing EQ-5D-5L makes no recommendations around sampling, recruitment, data analysis or modelling to generate the EQ-5D-5L value set.\ud \ud This review paper of published EQ-5D-5L value sets demonstrates variability in the methods used to generate international EQ-5D-5L values sets, across sampling, recruitment, modelling, assessing model performance and selection of the recommended value set.\ud \ud This raises the question of valid criteria for selecting a recommended value set and whether this should rely upon the researchers’ recommendation when these value sets are often used to inform public policy.

Purpose: The MacNew Heart Disease Health-Related Quality of Life Instrument (MacNew) is a validated, clinically sensitive, 27-item disease-specific questionnaire. This study aimed to develop a new heart disease-specific classification system for the MacNew amenable for use in health state valuation. Methods: Patients with heart disease attending outpatient clinics and inpatient wards in Brisbane, Australia, completed MacNew. The development of the new disease-specific classification system included three stages. First, a principal component analysis (PCA) established dimensionality. Second, Rasch analysis was used to select items for each dimension. Third, Rasch analysis was used to explore response-level reduction. In addition, clinician and patient judgement informed item selection. Results: Participants included 685 patients (acute coronary 6%, stable coronary 41%, chronic heart failure 20%). The PCA identified 4 dimensions (restriction, emotion, perception of others, and symptoms). The restriction dimension was divided into physical and social dimensions. One item was selected from each to be included in the classification system. Three items from the emotional dimension and two symptom items were also selected. The final classification system had seven dimensions with four severity levels in each: physical restriction; excluded from doing things with other people; worn out or low in energy; frustrated, impatient or angry; unsure and lacking in self-confidence; shortness of breath; and chest pain. Conclusion: This study generated a brief heart disease-specific classification system, consisting of seven dimensions with four severity levels in each. The classification system is amenable to valuation to enable the generation of utility value sets to be developed for use in economic evaluation.

ObjectiveBased on concerns about existing patient-reported outcome measures (PROMs) for assessing quality of life (QoL) in Duchenne muscular dystrophy (DMD), we describe the mixed methods development of a new QoL PROM for use in boys and men with DMD: the DMD-QoL.MethodsThe DMD-QoL was developed in 3 stages. First, draft items were generated from 18 semistructured qualitative interviews with boys and men with DMD, analyzed using framework analysis. Second, cognitive debriefing interviews with patients (n = 10), clinicians (n = 8), and patients' parents (n = 10) were undertaken, and a reduced item set was selected and refined. Third, psychometric data on the draft items from a cross-sectional online survey (n = 102) and stakeholder input from patients and patients' parents were used to produce the final questionnaire. Patient and public involvement and engagement was embedded throughout the process.ResultsFrom an initial draft of 47 items, a revised set of 27 items was produced at stage 2, and this set was further refined at stage 3 to generate the DMD-QoL, a 14-item QoL PROM. The DMD-QoL is designed for use from 7 years of age by proxy report and from 10 years of age by self-report or proxy report. The final measure showed good psychometric properties.ConclusionThe DMD-QoL is a new 14-item QoL PROM for boys and men with DMD, with demonstrable content and face validity.

Objective\ud This review examined the psychometric performance of 4 generic child- and adolescent-specific preference-based measures that can be used to produce utilities for child and adolescent health.\ud \ud Methods\ud A systematic search was undertaken to identify studies reporting the psychometric performance of the Child Health Utility (CHU9D), EQ-5D-Y (3L or 5L), and Health Utilities Index Mark 2 (HUI2) or Mark 3 (HUI3) in children and/or adolescents. Data were extracted to assess known-group validity, convergent validity, responsiveness, reliability, acceptability, and feasibility. Data were extracted separately for the dimensions and utility index where this was reported.\ud \ud Results\ud The review included 76 studies (CHU9D n = 12, EQ-5D-Y-3L n = 20, HUI2 n = 26,HUI3 n = 43), which varied considerably across conditions and sample size. EQ-5D-Y-3L had the largest amount of evidence of good psychometric performance in proportion to the number of studies examining performance. The majority of the evidence related to EQ-5D-Y-3L was based on dimensions. CHU9D was assessed in fewer studies, but the majority of studies found evidence of good psychometric performance. Evidence for HUI2 and HUI3 was more mixed, but the studies were more limited in sample size and statistical power, which was likely to have affected performance.\ud \ud Conclusions\ud The heterogeneity of published studies means that the evidence is based on studies across a range of countries, populations and conditions, using different study designs, different languages, different value sets and different statistical techniques. Evidence for CHU9D in particular is based on a limited number of studies. The findings raise concerns about the comparability of self-report and proxy-report responses to generate utility values for children and adolescents.

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.

Objectives:\ud There has been some debate about the choice of perspective and the age of the child considered when completing preference elicitation tasks in the 3-level version of EQ-5D-Y (EQ-5D-Y-3L) valuation protocol. This study aimed to clarify the impact on latent scale EQ-5D-Y-3L values of varying the age of the child experiencing the health state considered by respondents completing the discrete choice experiment (DCE) tasks of the protocol.\ud \ud Methods:\ud We conducted an online DCE with a representative sample of 1000 adults in the United Kingdom and 1000 adults in the United States. Respondents selected the health state they prefer from a series of DCE paired EQ-5D-Y-3L health state comparisons using their own perspective and that of a hypothetical child from the following age groups: “5-7 years old,” “8-10 years old,” “11-13 years old,” and “14-15 years old.” Data analysis was conducted using separate multinomial logit models for each perspective and country. We also estimated combined models including data from each possible pair of perspectives and used interactions between EQ-5D-Y-3L levels and perspective to determine whether any differences were statistically significant.\ud \ud Results:\ud No statistically significant differences in coefficients between perspectives were found in the United States. In the United Kingdom, there were differences between the own perspective and the 5 to 7 years old perspective (looking after myself level 3) and between the 5 to 7 years old perspective and the 8 to 10 years old perspective (usual activities level 3).\ud \ud Conclusions:\ud Our results suggest that there is minimal impact on latent scale values when using different ages of the hypothetical child in the current EQ-5D-Y-3L valuation protocol.

Evaluating quality in mental healthcare is essential for ensuring a high-quality experience for service users (SUs). Policy-defined quality indicators, however, risk misalignment with the perspectives of SUs and mental healthcare professionals (MHPs). There is value in exploring how SUs and frontline MHPs think quality should be measured.Our study objectives were to: (1) identify aspects that SUs and MHPs deem important for assessing quality in mental healthcare to help support attribute selection in a subsequent discrete choice experiment and (2) explore similarities and differences between SU and MHPs' views.Semi-structured qualitative focus groups (n = 6) were conducted with SUs (n = 14) and MHPs (n = 8) recruited from a UK National Health Service Trust. A topic guide was generated from a review of UK policy documents and existing data used to measure quality in mental healthcare in England. Transcripts were analysed using a framework analysis.Twenty-one subthemes were identified, grouped within six themes: accessing mental healthcare; assessing the benefits of care; co-ordinated approach; delivering mental healthcare; individualised care; and role of the person providing care. Themes such as person-centred care, capacity and resources, and receiving the right type of care received more coverage than others. Service users and MHPs displayed high concordance in their views, with minor areas of divergence.We developed a comprehensive six-theme framework for understanding quality in mental healthcare from the viewpoint of the SU and frontline MHP, which can be used to help inform the selection of a meaningful set of quality indicators in mental health for research and practice.

Objectives\ud \ud 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.\ud \ud \ud \ud Methods\ud \ud 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.\ud \ud \ud \ud Results\ud \ud 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).\ud \ud \ud \ud Conclusions\ud \ud 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.

Cystic fibrosis (CF) limits survival and negatively affects health-related quality of life (HRQOL). Cost-effectiveness analysis (CEA) may be used to make reimbursement decisions for new CF treatments; however, generic utility measures used in CEA, such as EQ-5D, are insensitive to meaningful changes in lung function and HRQOL in CF. Here we develop a new, CF disease-specific, preference-based utility measure based on the adolescent/adult version of the Cystic Fibrosis Questionnaire-Revised (CFQ-R), a widely used, CF-specific, patient-reported measure of HRQOL.Blinded CFQ-R data from 4 clinical trials (NCT02347657, NCT02392234, NCT01807923, and NCT01807949) were used to identify discriminating items for a classification system using psychometric (eg, factor and Rasch) analyses. Thirty-two health states were selected for a time-trade-off (TTO) exercise with a representative sample of the UK general population. TTO utilities were used to estimate a preference-based scoring algorithm by regression analysis (Tobit models with robust standard errors clustered on participants with censoring at -1).A classification system with 8 dimensions (CFQ-R-8D; Physical Functioning, Vitality, Emotion, Role Functioning, Breathing Difficulty, Cough, Abdominal Pain, and Body Image) was generated. TTO was completed by 400 participants (mean age, 47.3 years; 49.8% female). Among the regression models evaluated, the Tobit heteroscedastic-ordered model was preferred, with a predicted utility range from 0.236 to 1, no logical inconsistencies, and a mean absolute error of 0.032.The CFQ-R-8D is the first disease-specific, preference-based scoring algorithm for CF, enabling estimation of disease-specific utilities for CEA based on the well-validated and widely used CFQ-R.

IntroductionThe SF-6D is a preference-based measure of health, derived from the SF-36 for economic evaluation. No value set exists for the SF-6D in Lebanon and other Arabic speaking countries in the Middle East. The aim of this study was to examine the feasibility and acceptability of using the standard gamble (SG) technique to generate preference-based values for the Arabic version of SF-6D in a Lebanese population.MethodsThe SF-6D was translated into Arabic using forward and backward translations. Forty-nine states defined by the SF-6D were selected using an orthogonal design and grouped into seven sets. A gender-occupation stratified sample of 126 Lebanese adults from the American University of Beirut were recruited to value seven states and the pits (worst) SF-6D health states using SG. Mean and individual level multivariate regression models were fitted to estimate preference weights for all SF-6D states. The quality of data and the predictive power of the models were compared with results from the United Kingdom (UK).ResultsAll respondents completed the interviews with 25 percent reporting that the SG task was difficult and 21 percent felt some degree of irritation or boredom. A total of 992 (98% out of 1,008 observations) SG valuations were useable for econometric modeling. There was no significant change in the test–retest values of 21 subjects. The mean absolute errors in the mean and individual level models were 0.036 and 0.050, respectively, both of which were lower than the UK results. The random effects model adequately predicts the SG values, with the worst state having a value of 0.322 compared to 0.271 in the UK.ConclusionsThis study confirmed that it was feasible and acceptable to generate preference values with the SG method for the Arabic SF-6D in a Lebanese population. This would be the first step towards developing SF-6D value set for Lebanon to be used in economic evaluation studies and to support resources allocation decisions.

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.

High and sustained healthcare quality is important worldwide, though health policy may prioritise the achievement of certain aspects of quality over others. This study determines the relative importance of different aspects of mental healthcare quality to different stakeholders by eliciting preferences in a UK sample using a discrete choice experiment (DCE). DCE attributes were generated using triangulation between policy documents and mental healthcare service user and mental healthcare professional views, whilst ensuring attributes were measurable using available data. Ten attributes were selected: waiting times; ease of access; person-centred care; co-ordinated approach; continuity; communication, capacity and resources; treated with dignity and respect; recovery focus; inappropriate discharge; quality of life (QoL). The DCE was conducted online (December 2018 to February 2019) with mental healthcare service users (n = 331), mental healthcare professionals (n = 510), and members of the general population (n = 1018). Respondents' choices were analysed using conditional logistic regression. Relative preferences for each attribute were generated using the marginal rate of substitution (MRS) with QoL as numeraire. Across all stakeholders, being treated with dignity and respect was of high importance. A coordinated approach was important across all stakeholders, whereas communication had higher relative importance for healthcare professionals and service users and ease of access had higher relative importance for the general population. This implies that policy could be affected by the choice of whose preferences (service users, healthcare professionals or general population) to use, since this impacts on the relative value and implied ranking of different aspects of mental healthcare quality.

The EORTC QLU-C10D is a new multi-attribute utility instrument derived from the widely used cancer-specific quality of life questionnaire, EORTC QLQ-C30. It contains 10 dimensions (physical functioning, role functioning, social functioning, emotional functioning, pain, fatigue, sleep, appetite, nausea, bowel problems), each with four levels. The aim of this study was to provide U.K. general population utility weights for the QLU-C10D. A U.K. online panel was quota-sampled to align the sample to the general population proportions of sex and age (≥18 years). The online valuation survey included a discrete choice experiment (DCE). Each participant was asked to complete 16 choice-pairs, each comprising two QLU-C10D health states plus duration. DCE data were analysed using conditional logistic regression to generate utility weights. Data from 2,187 respondents who completed at least one choice set were included in the DCE analysis. The final U.K. QLU-C10D utility weights comprised decrements for each level of each health dimension. For nine of the 10 dimensions (all except appetite), the expected monotonic pattern was observed across levels: Utility decreased as severity increased. For the final model, consistent monotonicity was achieved by merging inconsistent adjacent levels for appetite. The largest utility decrements were associated with physical functioning and pain. The worst possible health state (the worst level of each dimension) is -0.083, which is considered slightly worse than being dead. The U.K.-specific utility weights will enable cost-utility analysis (CUA) for the economic evaluation of new oncology therapies and technologies in the United Kingdom, where CUA is commonly used to inform resource allocation.

Objective\ud 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.\ud \ud Methods\ud 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.\ud \ud Results\ud 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).\ud \ud Conclusion\ud 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.

Mapping is an increasingly common method used to predict instrument-specific preference-based health-state utility values (HSUVs) from data obtained from another health-related quality of life (HRQoL) measure. There have been several methodological developments in this area since a previous review up to 2007. To provide an updated review of all mapping studies that map from HRQoL measures to target generic preference-based measures (EQ-5D measures, SF-6D, HUI measures, QWB, AQoL measures, 15D/16D/17D, CHU-9D) published from January 2007 to October 2018. A systematic review of English language articles using a variety of approaches: searching electronic and utilities databases, citation searching, targeted journal and website searches. Full papers of studies that mapped from one health measure to a target preference-based measure using formal statistical regression techniques. Undertaken by four authors using predefined data fields including measures, data used, econometric models and assessment of predictive ability. There were 180 papers with 233 mapping functions in total. Mapping functions were generated to obtain EQ-5D-3L/EQ-5D-5L-EQ-5D-Y (n = 147), SF-6D (n = 45), AQoL-4D/AQoL-8D (n = 12), HUI2/HUI3 (n = 13), 15D (n = 8) CHU-9D (n = 4) and QWB-SA (n = 4) HSUVs. A large number of different regression methods were used with ordinary least squares (OLS) still being the most common approach (used ≥ 75% times within each preference-based measure). The majority of studies assessed the predictive ability of the mapping functions using mean absolute or root mean squared errors (n = 192, 82%), but this was lower when considering errors across different categories of severity (n = 92, 39%) and plots of predictions (n = 120, 52%). The last 10 years has seen a substantial increase in the number of mapping studies and some evidence of advancement in methods with consideration of models beyond OLS and greater reporting of predictive ability of mapping functions.

The widespread adoption of the EuroQol 5-dimensional questionnaire (EQ-5D) has been important for the comparability, transparency, and consistency of economic evaluations for informing resource allocation in healthcare. The objectives of this article were to (1) critically assess whether the widespread adoption of the EQ-5D and its time trade-off–based value sets to inform economic evaluation is likely to continue and (2) speculate about how benefits may be measured and valued to inform economic evaluation in the future. Evidence supports the use of the EQ-5D in many areas of health, but there are notable gaps. Furthermore, there has been interest among some policy makers in measuring changes in well-being, and in using common outcomes across sectors. Possibilities for measuring well-being alongside health can be achieved through bolt-on dimensions or an entirely new measure capturing both health and well-being. Nevertheless, there are significant concerns about the logic of estimating a common utility function. The development of online valuation methods has had a major impact on the field, which is likely to continue. We, however, recommend more allowance for respondents to consider their answers. There is an ongoing debate on the role of patient values or experience-based values. To date, this has seen limited take-up by decision makers and there are significant technical problems to obtaining representative and meaningful values. Policy makers and the general population must decide on the focus and scope of benefits that are incorporated into economic evaluation, and current evidence on this is mixed. In part, this will determine whether the widespread adoption will continue.

Objectives:\ud This article determines public stated preferences around different factors that influence the choice to make clinical negligence claims against a national healthcare system.\ud \ud Methods:\ud A large online survey was conducted using a discrete choice experiment (DCE) with the UK general population (N = 1013). DCE tasks involved a single profile and participants chose whether to make a claim for compensation (yes/no) after one of 3 randomly allocated patient safety incident (PSI) “scenarios” of different severities (mild, moderate, severe). DCE attributes described the actions of the healthcare system after a PSI and characteristics of the clinical negligence claims process. The data were modeled separately for each scenario (mild, moderate, severe) using logistic regression. Marginal effects and the probability of making a claim in a baseline case were estimated.\ud \ud Results:\ud Probability of choosing to claim was reduced by receipt of an apology, investigation and prevention of recurrence of the PSI, and longer time until claim decision and increased by an easy and straightforward claims process and high chance of compensation and for the mild scenario higher compensation amounts. Marginal effects and baseline case probabilities differed by scenario severity.\ud \ud Conclusions:\ud The results suggest the actions of the healthcare system after a PSI and characteristics of the claims process have a larger impact on the probability of making a claim for milder PSIs. For more severe PSIs, a larger probability of making a claim was observed, and the choice was less influenced by the actions of the healthcare system after the PSI and characteristics of the claims process.

Economic evaluation combines costs and benefits to support decision-making when assessing new interventions using preference-based measures to measure and value benefits in health or health-related quality of life. These health-focused instruments have limited ability to capture wider impacts on informal carers or outcomes in other sectors such as social care. Sector-specific instruments can be used but this is problematic when the impact of an intervention straddles different sectors.An alternative approach is to develop a generic preference-based measure that is sufficiently broad to capture important cross-sector outcomes. We consider the options for the selection of domains for a cross-sector generic measure including how to identify domains, who should provide information on the domains and how this should be framed. Beyond domain identification, considerations of criteria and stakeholder needs are also identified.This paper sets out the case for an approach that relies on the voice of patients, social care users and informal carers as the main source of domains and describes how the approach was operationalised in the ‘Extending the QALY’ project which developed the new measure, the EQ-HWB (EQ health and wellbeing instrument). We conclude by discussing the strengths and limitations of this approach. The new measure should be sufficiently generic to be used to consistently evaluate health and social care interventions, yet also sensitive enough to pick up important changes in quality of life in patients, social care users and carers.

The authors have requested that this preprint be removed from Research Square.

Duchenne muscular dystrophy is a rare degenerative neuromuscular disorder with pediatric onset. Recent approvals in Duchenne have placed attention on the economic evaluation in pricing and reimbursement decisions across a range of rare conditions. We sought to assess the appropriateness of the EQ-5D, a common measure of generic health state utility, for use among patients and caregivers affected by Duchenne.An international, cross-sectional sample of adults with Duchenne and caregivers reported patient health status using self- or proxy-reported EQ-5D-3L. Appropriateness was assessed across 6 domains of concern raised by stakeholders in Duchenne. These concerns were that the EQ-5D/EQ-VAS would not capture meaningful differences in health status, correlate with disease-specific measures, reflect real health status, exhibit face validity, be accurately interpreted, and be low burden. We evaluated these concerns by comparing EQ-5D index score and EQ-VAS scores to other condition-specific functional measures and open- and closed-ended questions.In total, 263 participants (74% response) completed the survey, 24% of whom were adult patients. Most participants lived in the United States or United Kingdom (58%). Patient age ranged from 1 to 48 y. EQ-5D index was higher in ambulatory than nonambulatory patients (0.60 v. 0.30,Contrary to anecdotal concerns, we found support for the appropriateness of EQ-5D to assess health status in Duchenne. While other measures may be more sensitive to specific outcomes in Duchenne, there may be some value in results using the EQ-5D measure.

Background Caries Impacts and Experiences Questionnaire for Children (CARIES-QC) is a child-centred caries-specific quality of life measure. This study aimed to select, and validate with children, a classification system for a paediatric condition-specific preference-based measure, based on CARIES-QC. Methods First, a provisional classification system for a preference-based measure based on CARIES-QC was identified using Rasch analysis, psychometric testing, involvement of children and parents, and the developer of CARIES-QC. Second, qualitative, semi-structured ‘think aloud’ validation interviews were undertaken with a purposive sample of children with dental caries. The interviewer aimed to identify whether items were considered important and easily understood, whether any were overlapping and if any excluded items should be reintroduced. Interview recordings were transcribed verbatim and thematic analysis conducted. Results Rasch analysis identified poor item spread for the items ‘cross’ and ‘school’. Items relating to eating were correlated and the better performing items were considered for selection. Children expressed some confusion regarding the items ‘school’ and ‘food stuck’. Parent representatives thought that impacts surrounding toothbrushing (‘brushing’) were encompassed by the item ‘hurt’. Five items were selected from CARIES-QC for inclusion in the provisional classification system; ‘hurt’, ‘annoy’, ‘carefully’, ‘kept awake’ and ‘cried’. Validation interviews were conducted with 20 children aged 5–16 years old. Participants thought the questionnaire was straightforward and covered a range of impacts. Children thought an item about certain foods being ‘hard to eat’ was more relevant than one about having to eat more carefully because of their teeth and so the ‘carefully’ item was replaced with ‘hard to eat’. Conclusion Following child-centred modification, the preliminary five-item classification system is considered valid and suitable for use in a valuation survey. The innovative child-centred methods used to both identify and validate the classification system can be applied in the development of other preference-based measures.

Background/aimsTo further validate the Vision Impairment in Low Luminance (VILL) questionnaire, which captures visual functioning and vision-related quality of life (VRQoL) under low luminance, low-contrast conditions relevant to age-related macular degeneration (AMD).MethodsThe VILL was translated from German into English (UK), Danish, Dutch, French, Italian and Portuguese. Rasch analysis was used to assess psychometric characteristics of 716 participants (65% female, mean age 72±7 years, 82% intermediate AMD) from the baseline visit of the MACUSTAR study. In a subset of participants (n=301), test–retest reliability (intraclass correlation coefficient (ICC) and coefficient of repeatability (CoR)) and construct validity were assessed.ResultsFour items were removed from the VILL with 37 items due to misfit. The resulting Vision Impairment in Low Luminance with 33 items (VILL-33) has three subscales with no disordered thresholds and no misfitting items. No differential item functioning and no multidimensionality were observed. Person reliability and person separation index were 0.91 and 3.27 for the Vision Impairment in Low Luminance Reading Subscale (VILL-R), 0.87 and 2.58 for the Vision Impairment in Low Luminance Mobility Subscale (VILL-M), and 0.78 and 1.90 for the Vision Impairment in Low Luminance Emotional Subscale (VILL-E). ICC and CoR were 0.92 and 1.9 for VILL-R, 0.93 and 1.8 for VILL-M and 0.82 and 5.0 for VILL-E. Reported VRQoL decreased with advanced AMD stage (pConclusionThe VILL is a psychometrically sound patient-reported outcome instrument, and the results further support its reliability and validity across all AMD stages. We recommend the shortened version of the questionnaire with three subscales (VILL-33) for future use.Trial registration numberNCT03349801.

ObjectiveThis paper reports on the valuation of quality-of-life states in the Alzheimer's Disease Five Dimensions (AD-5D) instrument in a representative sample of the general population in Australia using the discrete-choice experiment with duration (DCETTO) elicitation technique.MethodA DCE with 200 choice sets of two quality-of-life (QoL) state-duration combinations blocked into 20 survey versions, with ten choice sets in each version, was designed and administered online to a sample representative of the Australian population. Two additional choice sets comprising internal consistency and dominance checks were included in each survey version. A range of model specifications investigating preferences with respect to duration and interactions between AD-5D dimension levels were estimated. Utility weights were developed, with estimated coefficients transformed to the 0 (being dead) to 1 (full health) scale, suitable for the calculation of quality-adjusted life-year (QALY) weights for use in economic evaluation.ResultsIn total, 1999 respondents completed the choice experiment. Overall, respondents were slightly better educated and had higher annual incomes than the Australian general population. The estimation results from different specifications and models were broadly consistent with the monotonic nature of the AD-5D: utility increased with increased life expectancy and decreased as the severity level for each dimension worsened. A utility value set was generated for the calculation of utilities for all QoL states defined by the AD-5D descriptive system.ConclusionThe DCE-based utility value set is now available to use to generate QALYs for the economic evaluation of treatments and interventions targeting people with dementia and/or their family caregivers.

Objective This review summarizes and critically examines methods used to generate utilities for child and adolescent health states in previous National Institute for Health and Care Excellence (NICE) technology assessments (TA) and highly specialized technology (HST) evaluations. Methods We identified all NICE TA and HST evaluations in which the licensed indication for the technology included people younger than 18 and included in the review all evaluations using a cost-utility analysis. Results The review includes 40 TA and HST evaluations. Most assessments generated utility values with the EQ-5D scored using the adult version of the EQ-5D either exclusively (n = 16) or alongside other utility measures and direct elicitation methods of patient own utility (n = 17), although 7 did not use the EQ-5D. Eight assessments used both the EQ-5D child- and adolescent-specific preference-based measures: Health Utilities Index Mark 2 (n = 6), child- and adolescent-specific preference-based measure for atopic dermatitis (n = 1), and youth version of the EQ-5D (EQ-5D-Y) valued using the adult EQ-5D value set (n = 1) or generated using mapping and valued using the adult EQ-5D value set (n = 2). Some cost-utility analyses used age adjustment (utility subtractions, weights, and published mapping formulae) from the adult EQ-5D UK population norms to reflect the general population or disease-free health for children and adolescents (n = 9), and 1 assessment assumed full health (utility value of 1). Conclusion The review found limited use of child and adolescent population-specific measures to generate health state utility values for children and adolescents in NICE technology assessments. Often assessments involve the use of an adult-specific measure to reflect the health of children.

The objective of this study was to develop the classification system for version of the SF-6D (SF-6Dv2) from the SF-36v2. SF-6Dv2 is an improved version of SF-6D, one of the most widely used generic measures of health for the calculation of quality-adjusted life years.A 3-step process was undertaken to generate a new classification system: (1) factor analysis to establish dimensionality; (2) Rasch analysis to understand item performance; and (3) tests of differential item function. To evaluate robustness, Rasch analyses were performed in multiple subsets of 2 large cross-sectional datasets from recently discharged hospital patients and online patient samples.On the basis of factor analysis, other psychometric evidence, cross-cultural considerations, and amenability to valuation, the 6-dimension classification used in SF-6D was maintained. SF-6Dv2 resulted in the following modifications to SF-6D: a simpler classification of physical function with clearer separation between levels; a more detailed 5-level description of role limitations; using negative wording to describe vitality; and using pain severity rather than pain interference.The SF-6Dv2 classification system describes more distinct levels of health than SF-6D, changes the descriptions used for a number of dimensions and provides clearer wording for health state valuation. The second stage of the study has developed a utility value set using discrete choice methods so that the measure can be used in health technology assessment. Further work should investigate the psychometric characteristics of the new instrument.

Background The Health And Self-Management In Diabetes (HASMIDv1) questionnaire consists of 8 attributes, 4 about quality of life, and 4 about self-management. The overall aim of this study was to rigorously examine the psychometric properties of the HASMIDv1 questionnaire. Methods The study comprised two phases. Phase 1 identified items of the HASMIDv1 questionnaire that potentially required rewording through consultation with a patient involvement panel and two focus groups of people with diabetes. Phase 2 involved a cross-sectional longitudinal survey where HASMID, EQ-5D-5L, health, treatment and sociodemographic questions were administered using both paper and online versions to people with diabetes. Participants were asked to complete the survey again approximately 3 months later. Psychometric analyses were undertaken to examine floor and ceiling effects, item distributions, known group differences and internal consistency. Rasch analysis was undertaken to assess differential item functioning and disordered thresholds. Results Phase 1 derived five alternative wordings to items: Irritable, Affects Mealtimes, Daily Routine, Social Activities and Problem. Phase 2 achieved 2835 responses at time point 1 (n = 1944 online, n = 891 paper version) and 1243 at time point 2 (n = 533 online, n = 710 paper version). Overall the HASMID items performed well, though two alternative worded items (Irritable and Social Activities) provided additional information not fully captured by the original HASMID items. Conclusion Psychometric evaluation and Rasch analysis were used in conjunction with expert opinion to determine the final questionnaire. The application of psychometric analyses or Rasch analysis alone to inform item selection would have resulted in different items being selected for the final instrument. The benefit of a combined approach has produced an instrument which has a broader evaluation of self-management. The final validated HASMID-10 is a short self-report PRO that can be used to evaluate the impact of self-management for people living with diabetes. HASMID-10 can be scored using total summative scores, with utility and monetary values also available for use in cost-utility and cost-benefit analyses.

Objectives: The SF-6D is a preference-based measure of health developed to generate utility values from the SF-36. The aim of this pilot study was to examine the feasibility and acceptability of using the standard gamble (SG) technique to generate preference-based values for the Arabic version of SF-6D in a Lebanese population. Methods: The SF-6D was translated into Arabic using forward and backward translations. Forty-nine states defined by the SF-6D were selected using an orthogonal design and grouped into seven sets. A gender-occupation stratified sample of 126 Lebanese adults from the American University of Beirut were recruited to value seven states and the pits using SG. The sample size is appropriate for a pilot study, but smaller than the sample required for a full valuation study. Both interviewers and interviewees reported their understanding and effort levels in the SG tasks. Mean and individual level multivariate regression models were fitted to estimate preference weights for all SF-6D states. The models were compared with those estimated in the UK. Results: Interviewers reported few problems in completing SG tasks (0.8% with a lot of problems) and good respondent understanding (5.6% with little effort and concentration), and 25% of respondents reported the SG task was difficult. A total of 992 SG valuations were useable for econometric modeling. There was no significant change in the test&ndash, retest values from 21 subjects. The mean absolute errors in the mean and individual level models were 0.036 and 0.050, respectively, both of which were lower than the UK results. The random effects model adequately predicts the SG values, with the worst state having a value of 0.322 compared to 0.271 in the UK. Conclusion: This pilot confirmed that it was feasible and acceptable to generate preference values with the SG method for the Arabic SF-6D in a Lebanese population. However, further work is needed to extend this to a more representative population, and to explore why no utility values below zero were observed.