Transforming discrete choice experiment latent scale values for EQ-5D-3L using the visual analogue scale

Webb, Edward; O’Dwyer, John; Meads, David; Kind, Paul; Wright, Penny

doi:10.1007/s10198-020-01173-0

Cited by 14 publications

(16 citation statements)

References 45 publications

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“…Table 1 summarizes respondents' characteristics and Table 2 summarizes measures of their health. A higher proportion of respondents in 2020 gave illogical VAS responses (14.5%) than in 2018 (6.7%), and both figures are higher than a similar exercise using EQ-5D-3L in which 5.3% of respondents gave illogical responses (Webb et al, 2020). In both 2018 and 2020, the samples including and excluding illogical VAS responses were similar, although individuals in worse EQ-5D-5L states and with more long-term conditions were more likely to be excluded.…”

Section: Resultsmentioning

confidence: 78%

“…EQ-5D value sets have previously been estimated using EQ-VAS (Claes et al, 1999;Greiner et al, 2003;Gudex et al, 1996). A variation in the standard form of EQ-VAS previously proposed (Kind et al, 2004) has also been employed in a UK survey of the general population to anchor discrete choice experiment (DCE) values for EQ-5D-3L to a full health = 1, dead = 0 scale (Webb et al, 2020). The revised form of EQ-VAS provides for the capture of ratings for the logically best (11111) and worst (55555) health states.…”

Section: Methodsmentioning

confidence: 99%

“…VAS responses with 55555 and/or dead rated better than 11111 were considered illogical and not included in the main analysis of VAS responses. A scale ranging from 0 (dead) to 1 (full health) was generated by transforming VAS responses for 55555 using the formula Rescaling VAS scores in this way can result in a small number of extremely low valuations for 55555, possibly as low as −500, which can skew results (Webb et al, 2020). To avoid this, rescaled values were censored at −1.…”

Section: Data Preparationmentioning

confidence: 99%

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Does a health crisis change how we value health?

et al. 2021

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The general population is also impacted, including through increased anxiety and depression (Davillas & Jones, 2020). The economic fallout of the pandemic and its long-term health consequences, including a backlog of demand due to canceled operations, will result in continued pressure on healthcare resources in the future (Leahy et al., 2020). As a consequence, the processes for making decisions about how to allocate scarce healthcare resources will likely become more heavily scrutinized by all stakeholders, including patients and the public at large.Evidence of the cost-effectiveness of healthcare interventions generally incorporates generic measures of health-related quality of life such as EQ-5D (

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Section: Resultsmentioning

confidence: 78%

Section: Methodsmentioning

confidence: 99%

Section: Data Preparationmentioning

confidence: 99%

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Does a health crisis change how we value health?

et al. 2021

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“…It is important to note that an additional set of data would be required to “anchor” these DCE data onto the QALY scale. 33 , 34 It is not necessarily the case that the anchoring task would be feasible in a sample of adolescents, especially if an approach such as time tradeoff is used, as in the EQ-5D-Y-3L protocol. 6 If it were feasible, it would theoretically be possible to generate an EQ-5D-Y-3L value set based entirely on adolescent preferences, which could be used in evaluations of interventions aimed at younger populations.…”

Section: Discussionmentioning

confidence: 99%

Valuing EQ-5D-Y-3L Health States Using a Discrete Choice Experiment: Do Adult and Adolescent Preferences Differ?

Mott

Shah

Ramos-Goñi³

et al. 2021

Med Decis Making

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Background An important question in the valuation of children’s health is whether the preferences of younger individuals should be captured within value sets for measures that are aimed at them. This depends on whether younger individuals can complete valuation exercises and whether their preferences differ from those of adults. This study compared the preferences of adults and adolescents for EQ-5D-Y-3L health states using latent scale values elicited from a discrete choice experiment (DCE). Methods An online DCE survey, comprising 15 pairwise choices, was provided to samples of UK adults and adolescents (aged 11–17 y). Adults considered the health of a 10-year-old child, whereas adolescents considered their own health. Mixed logit models were estimated, and comparisons were made using relative attribute importance (RAI) scores and a pooled model. Results In total, 1000 adults and 1005 adolescents completed the survey. For both samples, level 3 in pain/discomfort was most important, and level 2 in self-care the least important, based on the relative magnitudes of coefficients. The RAI scores (normalized on self-care) indicated that adolescents gave less weight relative to adults to usual activities (1.18 v. 1.51; P < 0.05), pain/discomfort (1.77 v. 3.12; P < 0.01), and anxiety/depression (1.64 vs. 2.65; P < 0.01). The pooled model indicated evidence of differences between the two samples in both levels in pain/discomfort and anxiety/depression. Limitations The perspective of the DCE task differed between the 2 samples, and no data were collected to anchor the DCE data to generate value sets. Conclusions Adolescents could complete the DCE, and their preferences differed from those of adults taking a child perspective. It is important to consider whether their preferences should be incorporated into value sets.

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“…Recently, a large volume of work has been carried out with the purpose of addressing this anchoring problem. See for instance [18][19][20][21][22][23] for examples of this work. Until this anchoring problem is properly resolved, DCE cannot be an alternative to the TTO approach, but DCE data may add extra information to produce a better model for valuation data.…”

Section: Introductionmentioning

confidence: 99%

The Danish EQ-5D-5L Value Set: A Hybrid Model Using cTTO and DCE Data

Jensen

Sørensen

Gudex

et al. 2021

Appl Health Econ Health Policy

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Objectives Quality-adjusted life-years (QALYs) are expected to be used for priority setting of hospital-dispensed medicines in Denmark from 2021. The aim of this study was to develop the first Danish value set for the EQ-5D-5L based on interviews with a representative sample of the Danish adult population. Methods A nationally representative sample based on age (> 18 years), gender, education, and geographical region was recruited using data provided by Statistics Denmark. Computer-assisted personal interviews were carried out using the EQ-VT 2.1. Respondents each valued ten health states using composite time trade-off (cTTO) and seven health states using discretechoice experiment (DCE). Different predictive models were explored using cTTO and DCE data alone or in combination as hybrid models. Model performance was assessed using logical consistency. Results A total of 1014 interviews were included in the analyses. The sample was representative of the Danish adult population, though the sample contained slightly more respondents with higher education than in the general population. Only the heteroscedastic censored hybrid model combining cTTO and DCE data yielded consistent results, and hence was chosen for modelling the final Danish value set. The predicted values ranged from − 0.757 to 1, and anxiety/depression was the dimension assigned most value by respondents. Conclusions This study established the Danish EQ-5D-5L value set, which represents the preferences of the Danish general population, and is expected to provide key input for healthcare decision-making in a Danish context.

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Transforming discrete choice experiment latent scale values for EQ-5D-3L using the visual analogue scale

Cited by 14 publications

References 45 publications

Does a health crisis change how we value health?

Does a health crisis change how we value health?

Valuing EQ-5D-Y-3L Health States Using a Discrete Choice Experiment: Do Adult and Adolescent Preferences Differ?

The Danish EQ-5D-5L Value Set: A Hybrid Model Using cTTO and DCE Data

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