Putting the Choice in Choice Tasks: Incorporating Preference Elicitation Tasks in Health Preference Research.

Choice-based preference elicitation methods such as the discrete choice experiment (DCE) present hypothetical choices to respondents, with an expectation that these hypothetical choices accurately reflect a 'real world' health-related decision context and that consequently the choice data can be held to be a true representation of the respondent's health or treatment preferences. For this to be the case, careful consideration needs to be given to the format of the choice task in a choice experiment. The overarching aim of this paper is to highlight important aspects to consider when designing and 'setting up' the choice tasks to be presented to respondents in a DCE. This includes the importance of considering the potential impact of format (e.g. choice context, choice set presentation and size) as well as choice set content (e.g. labelled and unlabelled choice sets and inclusion of reference alternatives) and choice questions (stated choice versus additional questions designed to explore complete preference orders) on the preference estimates that are elicited from studies. We endeavoure to instil a holistic approach to choice task design that considers format alongside content, experimental design and analysis.

Patient preferences for a guided self-help programme to prevent relapse in anxiety or depression: A discrete choice experiment.

BACKGROUND: Anxiety and depressive disorders are increasingly being viewed as chronic conditions with fluctuating symptom levels. Relapse prevention programmes are needed to increase self-management and prevent relapse. Fine-tuning relapse prevention programmes to the needs of patients may increase uptake and effectiveness. MATERIALS AND METHODS: A discrete choice experiment (DCE) was conducted amongst patients with a partially or fully remitted anxiety or depressive disorder. Patients were presented 20 choice tasks with two hypothetical treatment scenarios for relapse prevention, plus a "no treatment" option. Each treatment scenario was based on seven attributes of a hypothetical but realistic relapse prevention programme. Attributes considered professional contact frequency, treatment type, delivery mode, programme flexibility, a personal relapse prevention plan, time investment and effectiveness. Choice models were estimated to analyse the data. RESULTS: A total of 109 patients with a partially or fully remitted anxiety or depressive disorder completed the DCE. Attributes with the strongest impact on choice were high effectiveness, regular contact with a professional, low time investment and the inclusion of a personal prevention plan. A high heterogeneity in preferences was observed, related to both clinical and demographic characteristics: for example, a higher number of previous treatment episodes was related to a preference for a higher frequency of contact with a professional, while younger age was related to a stronger preference for high effectiveness. CONCLUSIONS: This study using a DCE provides insights into preferences for a relapse prevention programme for anxiety and depressive disorders that can be used to guide the development of such a programme.

The Fold-in, Fold-out Design for DCE Choice Tasks: Application to Burden of Disease.

Background In discrete-choice experiments (DCEs), choice alternatives are described by attributes. The importance of each attribute can be quantified by analyzing respondents' choices. Estimates are valid only if alternatives are defined comprehensively, but choice tasks can become too difficult for respondents if too many attributes are included. Several solutions for this dilemma have been proposed, but these have practical or theoretical drawbacks and cannot be applied in all settings. The objective of the current article is to demonstrate an alternative solution, the fold-in, fold-out approach (FiFo). We use a motivating example, the ABC Index for burden of disease in chronic obstructive pulmonary disease (COPD). Methods Under FiFo, all attributes are part of all choice sets, but they are grouped into domains. These are either folded in (all attributes have the same level) or folded out (levels may differ). FiFo was applied to the valuation of the ABC Index, which included 15 attributes. The data were analyzed in Bayesian mixed logit regression, with additional parameters to account for increased complexity in folded-out questionnaires and potential differences in weight due to the folding status of domains. As a comparison, a model without the additional parameters was estimated. Results Folding out domains led to increased choice complexity for respondents. It also gave domains more weight than when it was folded in. The more complex regression model had a better fit to the data than the simpler model. Not accounting for choice complexity in the models resulted in a substantially different ABC Index. Conclusion Using a combination of folded-in and folded-out attributes is a feasible approach for conducting DCEs with many attributes.

Exploring the Impact of Adding a Respiratory Dimension to the EQ-5D-5L.

Objectives. To evaluate the impact of adding a respiratory dimension (a bolt-on dimension) to the EQ-5D-5L health state valuations. Methods. Based on extensive regression and principal component analyses, 2 respiratory bolt-on candidates were formulated: R1, limitations in physical activities due to shortness of breath, and R2, breathing problems. Valuation interviews for the selected bolt-ons were performed with a representative sample from the Dutch general public using the standardized interview protocol and software of the EuroQol group. Hybrid models based on the combined time-tradeoff (TTO) and discrete choice experiment (DCE) data were estimated to assess whether the 5 levels of the respiratory bolt-on led to significant changes in utility values. Results. For each bolt-on candidate, slightly more than 200 valuation interviews were conducted. Mean TTO values and DCE choice probabilities for health states with a level 4 or 5 for the respiratory dimension were significantly lower compared with the same health states in the Dutch EQ-5D-5L valuation study without the respiratory dimension. Results of hybrid models showed that for the bolt-on "limitations in physical activities," the utility decrements were significant for level 3 (-0.055), level 4 (-0.087), and level 5 (-0.135). For "breathing problems," the utility decrements for the same levels were greater (-0.086, -0.219, and -0.327, respectively). Conclusions. The addition of each of the 2 respiratory bolt-ons to the EQ-5D-5L had a significant effect on the valuation of health states with severe levels for the bolt-on. The bolt-on dimension "breathing problems" showed the greatest utility decrements and therefore seems the most appropriate respiratory bolt-on dimension.

Attribute level overlap (and color coding) can reduce task complexity, improve choice consistency, and decrease the dropout rate in discrete choice experiments.

A randomized controlled discrete choice experiment (DCE) with 3,320 participating respondents was used to investigate the individual and combined impact of level overlap and color coding on task complexity, choice consistency, survey satisfaction scores, and dropout rates. The systematic differences between the study arms allowed for a direct comparison of dropout rates and cognitive debriefing scores and accommodated the quantitative comparison of respondents' choice consistency using a heteroskedastic mixed logit model. Our results indicate that the introduction of level overlap made it significantly easier for respondents to identify the differences and choose between the choice options. As a stand-alone design strategy, attribute level overlap reduced the dropout rate by 30%, increased the level of choice consistency by 30%, and avoided learning effects in the initial choice tasks of the DCE. The combination of level overlap and color coding was even more effective: It reduced the dropout rate by 40% to 50% and increased the level of choice consistency by more than 60%. Hence, we can recommend attribute level overlap, with color coding to amplify its impact, as a standard design strategy in DCEs.

Advocating a Paradigm Shift in Health-State Valuations: The Estimation of Time-Preference Corrected QALY Tariffs.

BACKGROUND: Despite evidence of nonproportional trade-offs in time trade-off exercises and the explicit incorporation of exponential discounting in health technology assessment calculations, quality-adjusted life-year (QALY) tariffs are currently still established under the assumption of linear time preferences. OBJECTIVES: The aim of this study was to introduce a general method of accommodating for nonlinear time preferences in discrete choice experiment (DCE) duration studies and to evaluate its impact on estimated QALY tariffs. METHODS: A parsimonious utility function is proposed that accommodates any discounting function and preserves linear time preferences as a special case. Based on an efficient DCE design and 1775 respondents from a nationally representative scientific household panel, preferences and QALY tariffs for the Dutch SF-6D were estimated while accommodating for nonlinear time preferences via exponential and hyperbolic discounting functions. RESULTS: When the discount rate was estimated directly, we found strong evidence of nonlinear time preferences (with an exponential and hyperbolic discount rate of 5.7% and 16.5%, respectively). When the discount rate was estimated as a function of health state severity, we found that years lived in better health states are discounted minus years lived in impaired health states. Finally, the best statistical fit was obtained when using a hyperbolic discount function, which resulted in smaller QALY decrements and fewer health states classified as worse than immediate death. CONCLUSIONS: Our results highlight the relevance and even necessity of a paradigm shift in health valuation studies in favor of time-preference corrected QALY tariffs, with potentially important implications for health technology assessment calculations and regulatory decisions.

Effect of Level Overlap and Color Coding on Attribute Non-Attendance in Discrete Choice Experiments.

OBJECTIVE: The aim of this study was to test the hypothesis that level overlap and color coding can mitigate or even preclude the occurrence of attribute nonattendance in discrete choice experiments. METHODS: A randomized controlled experiment with five experimental study arms was designed to investigate the independent and combined impact of level overlap and color coding on respondents' attribute nonattendance. The systematic differences between the study arms allowed for a direct comparison of observed dropout rates and estimates of the average number of attributes attended to by respondents, which were obtained by using augmented mixed logit models that explicitly incorporated attribute non-attendance. RESULTS: In the base-case study arm without level overlap or color coding, the observed dropout rate was 14%, and respondents attended, on average, only two out of five attributes. The independent introduction of both level overlap and color coding reduced the dropout rate to 10% and increased attribute attendance to three attributes. The combination of level overlap and color coding, however, was most effective: it reduced the dropout rate to 8% and improved attribute attendance to four out of five attributes. The latter essentially removes the need to explicitly accommodate for attribute non-attendance when analyzing the choice data. CONCLUSIONS: On the basis of the presented results, the use of level overlap and color coding are recommendable strategies to reduce the dropout rate and improve attribute attendance in discrete choice experiments.

Choice Defines Value: A Predictive Modeling Competition in Health Preference Research.

OBJECTIVE: To identify which specifications and approaches to model selection better predict health preferences, the International Academy of Health Preference Research (IAHPR) hosted a predictive modeling competition including 18 teams from around the world. METHODS: In April 2016, an exploratory survey was fielded: 4074 US respondents completed 20 out of 1560 paired comparisons by choosing between two health descriptions (e.g., longer life span vs. better health). The exploratory data were distributed to all teams. By July, eight teams had submitted their predictions for 1600 additional pairs and described their analytical approach. After these predictions had been posted online, a confirmatory survey was fielded (4148 additional respondents). RESULTS: The victorious team, "Discreetly Charming Econometricians," led by Michal Jakubczyk, achieved the smallest χ2, 4391.54 (a predefined criterion). Its primary scientific findings were that different models performed better with different pairs, that the value of life span is not constant proportional, and that logit models have poor predictive validity in health valuation. CONCLUSIONS: The results demonstrated the diversity and potential of new analytical approaches in health preference research and highlighted the importance of predictive validity in health valuation.

ABC Index: quantifying experienced burden of COPD in a discrete choice experiment and predicting costs.

OBJECTIVE: The Assessment of Burden of COPD (ABC) tool supports shared decision making between patient and caregiver. It includes a coloured balloon diagram to visualise patients' scores on burden indicators. We aim to determine the importance of each indicator from a patient perspective, in order to calculate a weighted index score and investigate whether that score is predictive of costs. DESIGN: Discrete choice experiment. SETTING AND PARTICIPANTS: Primary care and secondary care in the Netherlands. 282 patients with chronic obstructive pulmonary disease (COPD) and 252 members of the general public participated. METHODS: Respondents received 14 choice questions and indicated which of two health states was more severe. Health states were described in terms of specific symptoms, limitations in physical, daily and social activities, mental problems, fatigue and exacerbations, most of which had three levels of severity. Weights for each item-level combination were derived from a Bayesian mixed logit model. Weights were rescaled to construct an index score from 0 (best) to 100 (worst). Regression models were used to find a classification of this index score in mild, moderate and severe that was discriminative in terms of healthcare costs. RESULTS: Fatigue, limitations in moderate physical activities, number of exacerbations, dyspnoea at rest and fear of breathing getting worse contributed most to the burden of disease. Patients assigned less weight to dyspnoea during exercise, listlessness and limitations with regard to strenuous activities. Respondents from the general public mostly agreed. Mild, moderate and severe burden of disease were defined as scores <20, 20-39 and ≥40. This categorisation was most predictive of healthcare utilisation and annual costs: €1368, €2510 and €9885, respectively. CONCLUSIONS: The ABC Index is a new index score for the burden of COPD, which is based on patients' preferences. The classification of the index score into mild, moderate and severe is predictive of future healthcare costs. TRIAL REGISTRATION NUMBER: NTR3788; Post-results.

Doctors' preferences in de-escalating DMARDs in rheumatoid arthritis: a discrete choice experiment.

BACKGROUND: Current guidelines suggest reduction of DMARDs can be considered in RA patients in remission. Objectives were (1) to estimate the relative importance of patient characteristics rheumatologists consider in their decision to de-escalate (2) to assess whether heterogeneity exists among rheumatologists with respect to de-escalation and (3) to identify the preferred de-escalation strategy. METHODS: A discrete choice experiment (DCE) was conducted. All rheumatologists and trainees in The Netherlands were invited to participate. A conditional logit model was estimated to assess overall preference for de-escalation and its determinants. Heterogeneity was estimated by latent class analysis. RESULTS: The DCE questionnaire was completed by 156 doctors. This questionnaire was constructed using the results of semi-structured interviews with 12 rheumatologists that identified five patient characteristics relevant for de-escalation: number of swollen joints (SJC), presence of DAS remission/low disease activity (LDA), patient history, duration of remission/LDA and patient willingness to de-escalate DMARDs. Overall SJC and patient history were most important. Latent class analysis revealed five subgroups of doctors, showing differences regarding willingness to de-escalate and relative importance of patient characteristics. De-escalation of the TNF inhibitor rather than methotrexate first was the most preferred strategy. CONCLUSIONS: Rheumatologists are not uniform in their decision on whom to de-escalate. Differences emerged in which characteristics they traded off resulting in five subgroups: those that taper (1) always, (2) in absence of swollen joints, (3) in absence of swollen joints and presence of favorable patient history, (4) in DAS remission and favorable patient history, and (5) taking into account all factors.

Are Health State Valuations from the General Public Biased? A Test of Health State Reference Dependency Using Self-assessed Health and an Efficient Discrete Choice Experiment.

Health state valuations of patients and non-patients are not the same, whereas health state values obtained from general population samples are a weighted average of both. The latter constitutes an often-overlooked source of bias. This study investigates the resulting bias and tests for the impact of reference dependency on health state valuations using an efficient discrete choice experiment administered to a Dutch nationally representative sample of 788 respondents. A Bayesian discrete choice experiment design consisting of eight sets of 24 (matched pairwise) choice tasks was developed, with each set providing full identification of the included parameters. Mixed logit models were used to estimate health state preferences with respondents' own health included as an additional predictor. Our results indicate that respondents with impaired health worse than or equal to the health state levels under evaluation have approximately 30% smaller health state decrements. This confirms that reference dependency can be observed in general population samples and affirms the relevance of prospect theory in health state valuations. At the same time, the limited number of respondents with severe health impairments does not appear to bias social tariffs as obtained from general population samples. Copyright © 2016 John Wiley & Sons, Ltd.

Head-to-head comparison of health-state values derived by a probabilistic choice model and scores on a visual analogue scale.

BACKGROUND: Health states were quantified based on discrete choice (DC) modeling and visual analogue scale (VAS) values using the five-level version of the EQ-5D (EQ-5D-5L). The aim of this study was to determine the extent of the relationship between DC derived values (indirect method) and VAS values (direct method). METHODS: Data were collected in Canada, the United Kingdom, the Netherlands, and the United States. Respondents were asked to perform paired comparisons between two EQ-5D-5L health states for DC. In total, 400 different EQ-5D-5L states were included. After each DC task, respondents were prompted to score the two states one after another on a VAS. Intraclass correlation coefficients were calculated between DC and VAS values and illuminating graphs were designed. RESULTS: Approximately 400 respondents participated from each country. High similarity [individual intraclass correlation coefficients (ICC) >0.85] of DC and moderate correspondence of VAS values were observed for the four countries. Cross-country comparison of DC values shows a nonlinear relationship to the VAS values. CONCLUSION: EQ-5D-5L derived DC and VAS values show a close but nonlinear relationship. Given the obvious biases associated with the VAS, DC methods based on ordinal responses may be a better alternative.

EQ-5D in Central and Eastern Europe: 2000-2015.

OBJECTIVE: Cost per quality-adjusted life year data are required for reimbursement decisions in many Central and Eastern European (CEE) countries. EQ-5D is by far the most commonly used instrument to generate utility values in CEE. This study aims to systematically review the literature on EQ-5D from eight CEE countries. METHODS: An electronic database search was performed up to 1 July 2015 to identify original EQ-5D studies from the countries of interest. We analysed the use of EQ-5D with respect to clinical areas, methodological rigor, population norms and value sets. RESULTS: We identified 143 studies providing 152 country-specific results with a total sample size of 81,619: Austria (n = 11), Bulgaria (n = 6), Czech Republic (n = 18), Hungary (n = 47), Poland (n = 51), Romania (n = 2), Slovakia (n = 3) and Slovenia (n = 14). Cardiovascular (21 %), neurologic (17 %), musculoskeletal (15 %) and endocrine, nutritional and metabolic diseases (13 %) were the most frequently studied clinical areas. Overall, 112 (78 %) of the studies reported EQ VAS results and 86 (60 %) EQ-5D index scores, of which 27 (31 %) did not specify the applied tariff. Hungary, Poland and Slovenia have population norms. Poland and Slovenia also have a national value set. CONCLUSIONS: Increasing use of EQ-5D is observed throughout CEE. The spread of health technology assessment activities in countries seems to be reflected in the number of EQ-5D studies. However, improvement in informed use and methodological quality of reporting is needed. In jurisdictions where no national value set is available, in order to ensure comparability we recommend to apply the most frequently used UK tariff. Regional collaboration between CEE countries should be strengthened.

Cost-effectiveness of the 'Walcheren Integrated Care Model' intervention for community-dwelling frail elderly.

BACKGROUND: An important aim of integrated care for frail elderly is to generate more cost-effective health care. However, empirical research on the cost-effectiveness of integrated care for community-dwelling frail elderly is limited. OBJECTIVE: This study reports on the cost-effectiveness of the Walcheren Integrated Care Model (WICM) after 12 months from a societal perspective. METHODS: The design of this study was quasi-experimental. In total, 184 frail elderly patients from 3 GP practices that implemented the WICM were compared with 193 frail elderly patients of 5 GP practices that provided care as usual. Effects were determined by health-related quality of life (EQ-5D questionnaire). Costs were assessed based on questionnaires, GP files, time registrations and reports from multidisciplinary meetings. Average costs and effects were compared using t-tests. The incremental cost-effectiveness ratio (ICER) was calculated, and bootstrap methods were used to determine its reliability. RESULTS: Neither the WICM nor care as usual resulted in a change in health-related quality of life. The average total costs of the WICM were higher than care as usual (17089 euros versus 15189 euros). The incremental effects were 0.00, whereas the incremental costs were 1970 euros, indicating an ICER of 412450 euros. CONCLUSIONS: The WICM is not cost-effective, and the costs per quality-adjusted life year are high. The costs of the integrated care intervention do not outweigh the limited effects on health-related quality of life after 12 months. More analyses of the cost-effectiveness of integrated care for community-dwelling frail elderly are recommended as well as consideration of the specific costs and effects.

Perspectives of Clinicians Involved in the RESTART-Study: Outcomes of a Focus Group.

PURPOSE: The purpose of this study was to explore the attitudes and beliefs of speech-language pathologists (SLPs) with regard to the Lidcombe Program and Demands and Capacities-based treatment and to examine how these attitudes and beliefs might have changed as a result of participating in the RESTART-study. METHOD: A focus group meeting with 13 SLPs was organized. The discussion was structured using questions on therapy preference, attitudes about and explicit comparison of both treatments and treatment manuals, and learnings of trial participation. RESULTS: Four main themes were identified. First, a change in attitude toward treatment choice was observed. Second, this change was related to a change in beliefs about the potential of both treatments. Third, aspects of the treatments regarded as success factors were considered. Last, learning outcomes and increased professionalism as a result of participating in the RESTART-trial were discussed. CONCLUSIONS: This study showed how attitudes and beliefs of SLPs with regard to the Lidcombe Program and Demands and Capacities-based treatment evolved during a randomized trial. This work increases our understanding of the role of attitudes and beliefs in the uptake and utilization of therapies and demonstrates the importance of collecting qualitative data. Results and recommendations should prove of value in implementing the RESTART-trial results and in training SLPs.

Sample Size Requirements for Discrete-Choice Experiments in Healthcare: a Practical Guide.

Discrete-choice experiments (DCEs) have become a commonly used instrument in health economics and patient-preference analysis, addressing a wide range of policy questions. An important question when setting up a DCE is the size of the sample needed to answer the research question of interest. Although theory exists as to the calculation of sample size requirements for stated choice data, it does not address the issue of minimum sample size requirements in terms of the statistical power of hypothesis tests on the estimated coefficients. The purpose of this paper is threefold: (1) to provide insight into whether and how researchers have dealt with sample size calculations for healthcare-related DCE studies; (2) to introduce and explain the required sample size for parameter estimates in DCEs; and (3) to provide a step-by-step guide for the calculation of the minimum sample size requirements for DCEs in health care.

What Influences Patients' Decisions When Choosing a Health Care Provider? Measuring Preferences of Patients with Knee Arthrosis, Chronic Depression, or Alzheimer's Disease, Using Discrete Choice Experiments.

OBJECTIVE: To investigate what influences patients' health care decisions and what the implications are for the provision of information on the quality of health care providers to patients. DATA SOURCES/STUDY SETTING: Dutch patient samples between November 2006 and February 2007. STUDY DESIGN: Discrete choice experiments were conducted in three patient groups to explore what influences choice for health care providers. DATA COLLECTION: Data were obtained from 616 patients with knee arthrosis, 368 patients with chronic depression, and 421 representatives of patients with Alzheimer's disease. PRINCIPAL FINDINGS: The three patients groups chose health care providers on a different basis. The most valued attributes were effectiveness and safety (knee arthrosis); continuity of care and relationship with the therapist (chronic depression); and expertise (Alzheimer's disease). Preferences differed between subgroups, mainly in relation to patients' choice profiles, severity of disease, and some background characteristics. CONCLUSIONS: This study showed that there is substantial room for (quality) information about health care providers in patients' decision processes. This information should be tailor-made, targeting specific patient segments, because different actors and factors play a part in their search and selection process.

Health-related quality of life of preschool children who stutter.

PURPOSE: The purpose of this study is to compare the health-related quality of life (HrQoL) of preschool children who stutter (CWS) and a reference population of children who do not stutter, and to evaluate the association between stuttering severity and HrQoL. METHODS: Baseline data were used from 197 children participating in a multicenter Randomized Clinical Trial in the Netherlands. Information on stuttering severity and time since onset (TSO) of stuttering was obtained from the baseline evaluation by speech- and language therapists. Stuttering severity was measured using the SSI-3. HrQoL was assessed using proxy versions of two Child Health Questionnaires (ITQOL-97 and CHQ-PF28), the Health Utility Index 3 (HUI3) and the EuroQoL EQ-VAS (EQ-VAS). RESULTS: While the outcomes on the EQ-VAS and the HUI3 showed that the HrQoL of CWS is slightly poorer than that of the Dutch reference population, results on the different dimensions of the CHQ-instruments did not reveal any difference in scores between stuttering children and reference groups. Within the group of CWS, two ITQOL-97 and four CHQ-PF28 scales showed statistically different scores for children in different SSI stuttering severity or TSO categories. However, the effect sizes showed that these differences were so small that they could be considered negligible. CONCLUSION: The results of this study do not reveal a diminished HrQoL for preschool CWS. Future research should include a larger cohort of children with severe stuttering, study the longitudinal course of HrQoL and incorporate additional parameters such as the characteristics of the child and his environment. EDUCATIONAL OBJECTIVES: The reader will be able to: (a) summarize the current evidence base on HrQoL in people who stutter; (b) describe the HrQoL of preschool CWS on different HrQoL measures; (c) describe the relationship between stuttering severity and HrQoL in preschool CWS.

Multinational evidence of the applicability and robustness of discrete choice modeling for deriving EQ-5D-5L health-state values.

AIMS: To investigate the feasibility of discrete choice experiments for valuing EQ-5D-5L states using computer-based data collection, the consistency of the estimated regression coefficients produced after modeling the preference data, and to examine the similarity of the values derived across countries. METHODS: Data were collected in Canada, England, The Netherlands, and the United States (US). Interactive software was developed to standardize the format of the choice tasks across countries, except for face-to-face interviewing in England. The choice task required respondents to choose between 2 suboptimal health states. A Bayesian design was used to generate 200 pairs of states that were randomly grouped into 20 blocks. Each respondent completed 1 block of 10 pairs. A main-effects probit model was used to estimate regression coefficients and to derive values. RESULTS: Approximately 400 respondents participated from each country. The mean time to perform 1 choice task was between 29.2 (US) and 45.2 (England) seconds. All regression coefficients were statistically significant, except level 2 for Usual Activities in The Netherlands (P=0.51). Predictions for the complete set of 3125 EQ-5D-5L health states were similar for the 4 countries. Intraclass correlation coefficients between the countries were high: from 0.80 (England vs. US) through 0.98 (Canada vs. US) CONCLUSIONS: Derivation of value sets from the general population using computer-based choice tasks for the EQ-5D-5L is feasible. Parameter estimates were generally consistent and logical, and health-state values were similar across the 4 countries.