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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.

Purpose: The aim of this study was to assess the measurement properties of the 5-level classification system of the EQ-5D (5L), in comparison with the 3-level EQ-5D (3L)., Methods: Participants (n = 3,919) from six countries, including eight patient groups with chronic conditions (cardiovascular disease, respiratory disease, depression, diabetes, liver disease, personality disorders, arthritis, and stroke) and a student cohort, completed the 3L and 5L and, for most participants, also dimension-specific rating scales. The 3L and 5L were compared in terms of feasibility (missing values), redistribution properties, ceiling, discriminatory power, convergent validity, and known-groups validity., Results: Missing values were on average 0.8% for 5L and 1.3% for 3L. In total, 2.9% of responses were inconsistent between 5L and 3L. Redistribution from 3L to 5L using EQ dimension-specific rating scales as reference was validated for all 35 3L-5L-level combinations. For 5L, 683 unique health states were observed versus 124 for 3L. The ceiling was reduced from 20.2% (3L) to 16.0% (5L). Absolute discriminatory power (Shannon index) improved considerably with 5L (mean 1.87 for 5L versus 1.24 for 3L), and relative discriminatory power (Shannon Evenness index) improved slightly (mean 0.81 for 5L versus 0.78 for 3L). Convergent validity with WHO-5 was demonstrated and improved slightly with 5L. Known-groups validity was confirmed for both 5L and 3L., Conclusions: The EQ-5D-5L appears to be a valid extension of the 3-level system which improves upon the measurement properties, reducing the ceiling while improving discriminatory power and establishing convergent and known-groups validity.

Background: EQ-5D is a generic preference-based measure of health that can help to understand the impact of asthma and chronic obstructive pulmonary disease (COPD). The purpose of this paper was to synthesize literature on the validity and reliability of EQ-5D use in studies of asthma and COPD, and estimate EQ-5D utility scores associated with stage of disease., Methods: A structured search was conducted in EMBASE and MEDLINE (1988-2007) using keywords relevant to respiratory disease and EQ-5D. Original research studies in asthma or COPD that reported EQ-5D results and/or psychometric properties were included., Results: Studies that reported psychometric properties supported the construct validity, test-retest reliability, and responsiveness of EQ-5D in asthma (seven studies) and COPD (nine studies), although some evidence of ceiling effects were observed in asthma studies. In asthma studies that reported summary scores (n=11), EQ-5D index-based scores ranged from 0.42 (SD 0.30) to 0.93 (SD not reported). In COPD studies (n=8), scores ranged from 0.52 (SD 0.16) to 0.84 (SD 0.15). While few asthma studies reported scores by severity level, sufficient studies in COPD were available to calculate pooled mean utility scores according to GOLD stage: stage I=0.74 (0.62-0.87), stage II=0.74 (0.66-0.83), stage III=0.69 (0.60-0.78) and stage IV=0.61 (0.44-0.77) (most severe)., Conclusions: Evidence generally supported the validity and reliability of EQ-5D in asthma and COPD. Utility scores associated with COPD stage may be useful for modeling health outcomes in economic evaluations of treatments for COPD.

Purpose: To compare self-rated health among the United States general population in 2002 and 2017.Methods: Secondary data were analyzed from two EQ-5D valuation studies conducted in 2002 and 2017. Both studies included the EQ-5D-3L self-classifier and visual analog scale (VAS), where health is rated from 0 (worst imaginable health) to 100 (best imaginable health). VAS scores were compared between time points using regression models, adjusting for sociodemographic factors (Model 1), plus illness (Model 2), and health problems according to the EQ-5D classifier (Model 3).Results: Mean VAS scores in 2002 [84.4 (SD = 16.1)] were not different from 2017 [84.6 (SD = 14.5)] (p = 0.63), nor different after adjusting for demographics (Model 1) or illness (Model 2). However, 2017 VAS mean scores were significantly higher than 2002 [2.2 (95% CI 1.36-3.10)] upon adjusting for the presence of dimension-specific health problems.Conclusions: Self-rated health of the general US adult population in 2017 was similar to 2002, but after adjusting for health problems, scores were slightly higher in 2017. Sociodemographic shifts in age and education explain some of the differences in scores, and by removing health and sociodemographic factors, we found the VAS reveals self-rated health is slightly better in 2017 than 2002. [ABSTRACT FROM AUTHOR]

Discrete choice experiments (DCEs) are a promising alternative to more resource-intensive preference elicitation methods such as time trade-off (TTO), as pairwise comparisons are more amenable to online completion, which can save time and money. However, modeling DCE data produces latent utilities which are on an unknown scale. Therefore, latent utilities need to be transformed to a full health-dead scale before they can be used in quality-adjusted life year calculations. We aimed to explore transformation functions from DCE-derived latent utilities to TTO-derived health utilities. We used EQ-5D-5L valuation data from eight different countries that collected both DCE and TTO data by using a standardized protocol. Results found less variation in the function that transformed latent utilities to health utilities in the western countries than in the eastern countries. While a global transformation function is not recommended, results suggest that regional transformation functions could potentially be used to derive health utilities from DCE data. Copyright © 2016 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Objective: The D1 model that was developed to predict US societal preferences for EQ-5D health states addressed several important conceptual and statistical issues. However, it has been criticized for being too complex, failing to account for the nonnormal distribution of health state values, and the transformation of preferences for worse-than-death health states before estimation. This research was conducted to develop an improved model for predicting median preferences for EQ-5D health states for the US population. Methods: Probability-weighted least absolute deviations regression was used to fit models to the time trade-off data collected in the US Valuation of the EQ-5D Health States study. No transformation was applied to the values for states considered worse than death. Several model specifications that differed with respect to explanatory variables were evaluated using two-sample cross-validation. Results: The best-fitting model included only fixed effects for moderate or severe problems in each of the 5 EQ-5D dimensions and excluded a constant. This specification yielded rank correlations between observed and predicted values and median observed and predicted values of 0.635 and 0.991, respectively, as well as a median absolute error of 0.026. The predicted median preferences ranged from 1.00 for full health, to –0.81 for the worst possible health state. Conclusions: Due to its simplicity and robustness, a median model is superior to other models for predicting US population preferences for EQ-5D health states. The predictions of this model are suggested for use in applications that require US societal health state values. [ABSTRACT FROM AUTHOR]

Objectives: The wording of the Hungarian EQ-5D-3L and EQ-5D-5L descriptive systems differ a great deal. This study aimed to (1) develop EQ-5D-3L and EQ-5D-5L value sets for Hungary from a common sample, and (2) compare how level wording affected valuations.Methods: In 2018 to 2019, 1000 respondents, representative of the Hungarian general population, completed composite time trade-off tasks. Pooled heteroscedastic Tobit models were used to estimate value sets. Value set characteristics, single-level transition utilities from adjacent corner health states, and mean transition utilities for all possible health states were compared between the EQ-5D-3L and EQ-5D-5L.Results: Health utilities ranged from -0.865 to 1 for the EQ-5D-3L and -0.848 to 1 for the EQ-5D-5L. The relative importance of the 5 EQ-5D-5L dimensions was as follows: mobility, pain/discomfort, self-care, anxiety/depression, and usual activities. A similar preference ranking was observed for the EQ-5D-3L with self-care being more important than pain/discomfort. The EQ-5D-5L demonstrated lower ceiling effects (range of utilities for the mildest states: 0.900-0.958 [3L] vs 0.955-0.965 [5L]) and better consistency of mean transition utilities across the range of scale. Changing "confined to bed" (3L) to "unable to walk" (5L) had a large positive impact on utilities. Smaller changes with more negative wording in the other dimensions (eg, "very much anxious/feeling down a lot" [3L] vs "extremely anxious/depressed" [5L]) had a modest negative impact on utilities.Conclusion: This study developed value sets of the EQ-5D-3L and EQ-5D-5L for Hungary. Our findings contribute to the understanding of how the wording of descriptive systems affects the estimates of utilities. [ABSTRACT FROM AUTHOR]