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A Comparison of EQ-5D Index Scores Derived from the US and UK Population-Based Scoring Functions

Author

Listed:
  • Nan Luo

    (Centre for Health Services Research, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, medln@nus.edu.sg)

  • Jeffrey A. Johnson

    (Institute of Health Economics & University of Alberta, Edmonton, Alberta, Canada)

  • James W. Shaw

    (Department of Pharmacy Administration and Center for Pharmacoeconomics, College of Pharmacy, University of Illinois at Chicago, Illinois)

  • Stephen Joel Coons

    (College of Pharmacy and College of Public Health, University of Arizona, Tucson, Arizona)

Abstract

The authors recently introduced a new preference-based scoring function for the EQ-5D (D1 model) based on time tradeoff valuations from the general adult US population. In this study, they compared the EQ-5D index scores derived from the US (D1) algorithm to the more familiar UK (N3) algorithm. They compared preference-based EQ-5D index scores for all possible EQ-5D health states and differences in EQ-5D index scores between pairs of EQ-5D health states predicted by the D1 and N3 models. The responsiveness of D1- and N3-predicted EQ-5D index scores was assessed using simulated transitions between EQ-5D health states. The mean (SD) EQ-5D index scores for all 243 health states predicted by the D1 and N3 models were 0.37 (0.23) and 0.14 (0.31), respectively. The mean (SD) absolute difference in EQ-5D index scores for all 29,403 pairs of health states was 0.25 (0.19) and 0.35 (0.27), according to the D1 and N3 models, respectively. The D1 and N3 models were consistent in predicting gains/losses for 27,592 (94%) transitions between EQ-5D health state pairs; Cohen effect size, calculated using these 27,592 consistent transitions, was 1.58 and 1.59 for the D1 and N3 models, respectively. Based on these simulation results, it appears that the D1 model would lead to smaller gains in quality-adjusted life years than the N3 model; however, their responsiveness appears to be similar. Empirical studies are needed to examine whether these 2 EQ-5D scoring functions would lead to different conclusions in cost-utility analyses.

Suggested Citation

  • Nan Luo & Jeffrey A. Johnson & James W. Shaw & Stephen Joel Coons, 2007. "A Comparison of EQ-5D Index Scores Derived from the US and UK Population-Based Scoring Functions," Medical Decision Making, , vol. 27(3), pages 321-326, May.
    • Handle: RePEc:sae:medema:v:27:y:2007:i:3:p:321-326
    DOI: 10.1177/0272989X07300603
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    Citations

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    Cited by:

    1. Ralph Crott & Andrew Briggs, 2010. "Mapping the QLQ-C30 quality of life cancer questionnaire to EQ-5D patient preferences," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 11(4), pages 427-434, August.
    2. Raymond Oppong & Billingsley Kaambwa & Jacqueline Nuttall & Kerenza Hood & Richard Smith & Joanna Coast, 2013. "The impact of using different tariffs to value EQ-5D health state descriptions: an example from a study of acute cough/lower respiratory tract infections in seven countries," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 14(2), pages 197-209, April.
    3. Munir A. Khan & Jeff Richardson, 2019. "Is the Validity of Cost Utility Analysis Improved When Utility is Measured by an Instrument with ‘Home-Country’ Weights? Evidence from Six Western Countries," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 145(1), pages 1-15, August.
    4. Franz Ombler & Michael Albert & Paul Hansen, 2017. "The true significance of ‘high’ correlations between EQ-5D value sets," Working Papers 1704, University of Otago, Department of Economics, revised Mar 2017.
    5. Franz Ombler & Michael Albert & Paul Hansen, 2018. "How Significant Are “High†Correlations Between EQ-5D Value Sets?," Medical Decision Making, , vol. 38(6), pages 635-645, August.
    6. P. Wang & M. Li & G. Liu & J. Thumboo & N. Luo, 2015. "Do Chinese have similar health-state preferences? A comparison of mainland Chinese and Singaporean Chinese," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 16(8), pages 857-863, November.
    7. Liv Ariane Augestad & Kim Rand-Hendriksen & Ivar Sønbø Kristiansen & Knut Stavem, 2012. "Impact of Transformation of Negative Values and Regression Models on Differences Between the UK and US EQ-5D Time Trade-Off Value Sets," PharmacoEconomics, Springer, vol. 30(12), pages 1203-1214, December.
    8. Liv Augestad & Kim Rand-Hendriksen & Ivar Kristiansen & Knut Stavem, 2012. "Impact of Transformation of Negative Values and Regression Models on Differences Between the UK and US EQ-5D Time Trade-Off Value Sets," PharmacoEconomics, Springer, vol. 30(12), pages 1203-1214, December.

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