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Is EQ-5D-5L Better Than EQ-5D-3L? A Head-to-Head Comparison of Descriptive Systems and Value Sets from Seven Countries

Overview of attention for article published in PharmacoEconomics, February 2018
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (89th percentile)
  • High Attention Score compared to outputs of the same age and source (97th percentile)

Mentioned by

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3 policy sources
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18 X users
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2 Facebook pages

Citations

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227 Dimensions

Readers on

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176 Mendeley
Title
Is EQ-5D-5L Better Than EQ-5D-3L? A Head-to-Head Comparison of Descriptive Systems and Value Sets from Seven Countries
Published in
PharmacoEconomics, February 2018
DOI 10.1007/s40273-018-0623-8
Pubmed ID
Authors

Mathieu F. Janssen, Gouke J. Bonsel, Nan Luo

Abstract

This study describes the first empirical head-to-head comparison of EQ-5D-3L (3L) and EQ-5D-5L (5L) value sets for multiple countries. A large multinational dataset, including 3L and 5L data for eight patient groups and a student cohort, was used to compare 3L versus 5L value sets for Canada, China, England/UK (5L/3L, respectively), Japan, The Netherlands, South Korea and Spain. We used distributional analyses and two methods exploring discriminatory power: relative efficiency as assessed by the F statistic, and an area under the curve for the receiver-operating characteristics approach. Differences in outcomes were explored by separating descriptive system effects from valuation effects, and by exploring distributional location effects. In terms of distributional evenness, efficiency of scale use and the face validity of the resulting distributions, 5L was superior, leading to an increase in sensitivity and precision in health status measurement. When compared with 5L, 3L systematically overestimated health problems and consequently underestimated utilities. This led to bias, i.e. over- or underestimations of discriminatory power. We conclude that 5L provides more precise measurement at individual and group levels, both in terms of descriptive system data and utilities. The increased sensitivity and precision of 5L is likely to be generalisable to longitudinal studies, such as in intervention designs. Hence, we recommend the use of the 5L across applications, including economic evaluation, clinical and public health studies. The evaluative framework proved to be useful in assessing preference-based instruments and might be useful for future work in the development of descriptive systems or health classifications.

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X Demographics

The data shown below were collected from the profiles of 18 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 176 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 176 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 29 16%
Student > Master 24 14%
Student > Ph. D. Student 16 9%
Researcher 14 8%
Student > Doctoral Student 7 4%
Other 25 14%
Unknown 61 35%
Readers by discipline Count As %
Medicine and Dentistry 43 24%
Nursing and Health Professions 18 10%
Pharmacology, Toxicology and Pharmaceutical Science 8 5%
Social Sciences 6 3%
Psychology 5 3%
Other 20 11%
Unknown 76 43%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 23. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 25 November 2022.
All research outputs
#1,580,973
of 24,761,242 outputs
Outputs from PharmacoEconomics
#84
of 1,967 outputs
Outputs of similar age
#34,545
of 336,005 outputs
Outputs of similar age from PharmacoEconomics
#2
of 40 outputs
Altmetric has tracked 24,761,242 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 93rd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,967 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.3. This one has done particularly well, scoring higher than 95% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 336,005 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 89% of its contemporaries.
We're also able to compare this research output to 40 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 97% of its contemporaries.