United States Valuation of EQ-5D-5L Health States Using an International Protocol

Pickard, A. Simon; Law, Ernest H.; Jiang, Ruixuan; Pullenayegum, Eleanor; Shaw, James W.; Xie, Feng; Oppe, Mark; Boye, Kristina S.; Chapman, Richard H.; Gong, Chen; Balch, Alan; Busschbach, Jan

doi:10.1016/j.jval.2019.02.009

Cited by 260 publications

(199 citation statements)

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“…Utility values were calculated from EQ-5D-5L responses using US-derived value weights. 16 We compared EQ-5D-5L results with pre-pandemic results we collected prior to COVID-19 (n=40) and with US population norms from previously derived online (n=2,018) as well as face-to-face (n=1,134) interviews. 15 We used ttests and chi-squared tests for numeric and categorical variables respectively to identify statistically signi cant differences.…”

Section: Methodsmentioning

confidence: 99%

“…13 It is short, simple, and validated in both online and face-to-face panels in the United States. [14][15][16] Respondents rate mobility, self-care, usual activities, pain/discomfort, and anxiety/depression on a category of 1-5 indicating no to extreme problems. The responses can be converted into health utility scores by applying a societal preference function which generates scores anchored at 0 for dead, and 1 perfect health, with negative values for states considered worse than dead.…”

Section: Introductionmentioning

confidence: 99%

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A US population health survey on the impact of COVID-19 using the EQ-5D-5L

Hay

Gong

Jiao

et al. 2020

Preprint

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Background: In addition to health and economic consequences, the COVID-19 pandemic has likely affected population health-related quality of life (HRQoL).Objective: To assess the impact of COVID-19 on US population health using the EQ-5D-5L.Design: We surveyed respondents on health status, employment, and anxiety/depression. We collected information on demographics, brief medical history, socioeconomic status, current COVID-19 status, sleep, dietary, and financial spending changes. Results were compared to US population norms. Predictors of EQ-5D-5L utility were analyzed using post-Lasso OLS regression, a machine learning algorithm designed to enhance prediction accuracy by avoiding overfitting. Robustness of regression coefficients were analyzed with E-Values to quantify unmeasured confounding.Participants: Amazon MTurk users.Main Measures: EQ-5D-5L utility score by age group.Key Results: Survey respondents (n=2776) reported significantly worse mean (SD) HRQoL utility as captured by the EQ-5D-5L among 18-24 year olds, 0.752 (0.281) vs. online, 0.844 (0.184) (p=0.001) and face-to-face norms, 0.919 (0.127) (p<0.001). Among ages 25-34, utility was worse compared to face-to-face norms only (0.825 (0.235) vs. 0.911 (0.111), p<0.001). Among ages 35-64, utility values were higher during-pandemic but only vs. online norms (0.845 (0.195) vs. 0.794 (0.247), p<0.001). At age 65+, utility values (0.827 (0.213)) were similar across all samples. Increasing age and income were correlated with increased utility, while Hawaiian/Pacific islander race, Hispanic ethnicity, married, living alone, history of chronic illness, fear of COVID-19’s impact on health, and having a family member diagnosed with COVID-19 were associated with worse utility scores. Results were relatively robust to unmeasured confounding.Conclusions: HRQoL has decreased during the pandemic compared to US population norms, especially for ages 18-24. The mental

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A US population health survey on the impact of COVID-19 using the EQ-5D-5L

Hay

Gong

Jiao

et al. 2020

Preprint

Self Cite

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“…Additionally, we did not include disease status as there is no clear evidence showing that the disease status could affect respondents' understanding of the EQ-5D-5L and chronic disease is usually under-diagnosed among rural Chinese, so respondents may not be able to report accurate information. Disease status was not considered in quota sampling in the previous EQ-5D-5L valuation studies such as in the US [24] and in China [25].…”

Section: Study Participantsmentioning

confidence: 99%

Do Rural Residents in China Understand EQ-5D-5L as Intended? Evidence From a Qualitative Study

Yang

Jiang

et al. 2020

PharmacoEconomics Open

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Background The 5-level EQ-5D (EQ-5D-5L) has been increasingly used in China to measure the health status of the general population and patients. However, its content validity among rural residents in China has not been formally evaluated. This qualitative study aims to assess the content validity of EQ-5D-5L among rural Chinese. Methods Participants were recruited from four regions (North, South, East and West) across China. Eligible participants were those living in the rural area in last three years and making a living by agricultural operations. Semi-structured interviews were conducted. Interview transcripts were analysed to assess the comprehensibility, relevance, clarity and comprehensiveness. Results Sixty-two participants were included, comparable to the national figures regarding age, sex and education. For comprehensibility, participants could understand the 'mobility', 'self-care' and 'usual activities' domains well, but some reported confusions in 'pain/discomfort' (n = 42) and 'anxiety/depression' (n = 35). Some also reported difficulties in understanding anxiety (n = 6) and depression (n = 9), possibly due to the formal wording used. For relevance, all domains were reported as health-related and participants' responses were based on their own health. For clarity, all could distinguish the five levels, but suggestions on reducing response levels and alternative wording for 'slight' were raised. For comprehensiveness, two aspects (fatigue/energy and appetite) were raised beyond the EQ-5D-5L domains. The 'mobility' domain was selected as the most important and 'anxiety/depression' as the least important. Conclusion Rural Chinese reported problems on the content validity of Chinese EQ-5D-5L. It might be sensible to consider some revisions to make it more understandable for rural residents.

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“…The dimensions include mobility, self-care, usual activities, pain/discomfort and anxiety/depression, while the five severity levels constitute no problems, slight problems, moderate problems, severe problems and unable to/extreme problems. In this paper, the directly elicited EQ-5D-5L value sets from two countries (England, and the US) were applied [17,18]. Both the English and the US value sets were published based on the EQ-VT approach.…”

Section: Measures Of Variablesmentioning

confidence: 99%

Does linear equating improve prediction in mapping? Crosswalking MacNew onto EQ-5D-5L value sets

Lamu

2020

Eur J Health Econ

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Purpose Preference-based measures are essential for producing quality-adjusted life years (QALYs) that are widely used for economic evaluations. In the absence of such measures, mapping algorithms can be applied to estimate utilities from disease-specific measures. This paper aims to develop mapping algorithms between the MacNew Heart Disease Quality of Life Questionnaire (MacNew) instrument and the English and the US-based EQ-5D-5L value sets. Methods Individuals with heart disease were recruited from six countries: Australia, Canada, Germany, Norway, UK and the US in 2011/12. Both parametric and non-parametric statistical techniques were applied to estimate mapping algorithms that predict utilities for MacNew scores from EQ-5D-5L value sets. The optimal algorithm for each country-specific value set was primarily selected based on root mean square error (RMSE), mean absolute error (MAE), concordance correlation coefficient (CCC), and r-squared. Leave-one-out cross-validation was conducted to test the generalizability of each model. Results For both the English and the US value sets, the one-inflated beta regression model consistently performed best in terms of all criteria. Similar results were observed for the cross-validation results. The preferred model explained 59 and 60% for the English and the US value set, respectively. Linear equating provided predicted values that were equivalent to observed values. Conclusions The preferred mapping function enables to predict utilities for MacNew data from the EQ-5D-5L value sets recently developed in England and the US with better accuracy. This allows studies, which have included the MacNew to be used in cost-utility analyses and thus, the comparison of services with interventions across the health system.

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United States Valuation of EQ-5D-5L Health States Using an International Protocol

Cited by 260 publications

References 40 publications

A US population health survey on the impact of COVID-19 using the EQ-5D-5L

A US population health survey on the impact of COVID-19 using the EQ-5D-5L

Do Rural Residents in China Understand EQ-5D-5L as Intended? Evidence From a Qualitative Study

Does linear equating improve prediction in mapping? Crosswalking MacNew onto EQ-5D-5L value sets

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