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PharmacoEconomics

, Volume 36, Issue 6, pp 641–643 | Cite as

Once Bitten Twice Shy: Thinking Carefully Before Adopting the EQ-5D-5L

  • Jeff RoundEmail author
Commentary

The EQ-5D-5L

The Euro-Qol group introduced the EQ-5D-5L descriptive system in 2009 [1], with the first publication describing the tool appearing in 2011 [2]. This revised version of the EQ-5D instrument introduced five response levels, alongside changes to the wording used to describe responses in the mobility domain. The five-level version of the EQ-5D descriptive system was developed in response to perceived failings of the three response-level EQ-5D-3L, notably in its sensitivity to changes in health [3], but also ceiling effects [2] and an ‘uneven’ distribution of responses as measured by the valuation tariff [4].

The first UK valuation study of the 5L descriptive system was formally available in 2017 [4]. As Brazier, Bryan and Briggs recently summarize [5], the 5L version of the instrument has been found to reduce ceiling effects and exhibits a more even distribution of responses. Hernandez et al. [6] have shown that as a consequence of the changes to the tool and the new...

Notes

Acknowledgements

The author would like to thank the Univeristy of Bristol Health Economics Journal Club for the discussion that informed this commentary. All errors or omissions are the author’s own.

Funding

No specific funding was received for the preparation of this work.

Compliance with ethical standards

Conflicts of interest

The author has no conflicts of interest to declare.

References

  1. 1.
    EuroQol Research Foundation. EQ-5D-5L | About. https://euroqol.org/eq-5d-instruments/eq-5d-5l-about/. Accessed 13 Feb 2018.
  2. 2.
    Herdman M, et al. Development and preliminary testing of the new five-level version of EQ-5D (EQ-5D-5L). Qual Life Res. 2011;20(10):1727–36.CrossRefPubMedPubMedCentralGoogle Scholar
  3. 3.
    Lloyd A. EQ-5D: Moving from three levels to five. Value Health. 2018;21(1):57–8.CrossRefPubMedGoogle Scholar
  4. 4.
    Devlin NJ, et al. Valuing health-related quality of life: An EQ-5D-5L value set for England. Health Econ. 2018;27(1):7–22.CrossRefPubMedGoogle Scholar
  5. 5.
    Brazier J, Briggs A, Bryan S. EQ-5D-5L: Smaller steps but a major step change? Health Econ. 2018;27(1):4–6.CrossRefPubMedGoogle Scholar
  6. 6.
    Hernandez Alava M, et al. EQ-5D-5L versus EQ-5D-3L: the impact on cost effectiveness in the United Kingdom. Value Health. 2018;21(1):49–56.CrossRefPubMedGoogle Scholar
  7. 7.
    National Institute for Health and Care Excellence. Position statement on use of the EQ-5D-5L valuation set. London: NICE; 2017.Google Scholar
  8. 8.
    National Institute for Health and Care Excellence. Guide to the methods of technology appraisal. 2013. https://www.nice.org.uk/process/pmg9/chapter/foreword. Accessed 13 Feb 2018.
  9. 9.
    Konerding U, et al. The validity of the EQ-5D-3L items: an investigation with type 2 diabetes patients from six European countries. Health Qual Life Outcomes. 2014;12:181.CrossRefPubMedPubMedCentralGoogle Scholar
  10. 10.
    Jensen-Dahm C, et al. Discrepancy between self- and proxy-rated pain in Alzheimer’s disease: results from the Danish Alzheimer Intervention Study. J Am Geriatr Soc. 2012;60(7):1274–8.CrossRefPubMedGoogle Scholar
  11. 11.
    Ramakers GG, et al. Agreement between health utility instruments in cochlear implantation. Clin Otolaryngol. 2016;41(6):737–43.CrossRefPubMedGoogle Scholar
  12. 12.
    Dickerson JF, et al. Evidence on the longitudinal construct validity of major generic and utility measures of health-related quality of life in teens with depression. Qual Life Res. 2017.Google Scholar
  13. 13.
    Janssen MF, et al. Measurement properties of the EQ-5D-5L compared to the EQ-5D-3L across eight patient groups: a multi-country study. Qual Life Res. 2013;22(7):1717–27.CrossRefPubMedGoogle Scholar
  14. 14.
    Brazier J, et al. A systematic review, psychometric analysis and qualitative assessment of generic preference-based measures of health in mental health populations and the estimation of mapping functions from widely used specific measures. Health Technol Assess. 2014;18(34):vii–viii, xiii–xxv, 1–188.CrossRefGoogle Scholar
  15. 15.
    Mulhern B, et al. Using generic preference-based measures in mental health: psychometric validity of the EQ-5D and SF-6D. Br J Psychiatry. 2014;205(3):236–43.CrossRefPubMedGoogle Scholar
  16. 16.
    Noyes J, Edwards RT. EQ-5D for the assessment of health-related quality of life and resource allocation in children: a systematic methodological review. Value Health. 2011;14(8):1117–29.CrossRefPubMedGoogle Scholar
  17. 17.
    Bailey C, et al. ‘The ICECAP-SCM tells you more about what I’m going through’: A think-aloud study measuring quality of life among patients receiving supportive and palliative care. Palliat Med. 2016;30(7):642–52.CrossRefPubMedPubMedCentralGoogle Scholar
  18. 18.
    Brazier JE, et al. First validation of the short recovering quality of life (ReQoL) measure. Qual Life Res. 2016;25:96.Google Scholar
  19. 19.
    Stevens K. Assessing the performance of a new generic measure of health-related quality of life for children and refining it for use in health state valuation. Appl Health Econ Health Policy. 2011;9(3):157–69.CrossRefPubMedGoogle Scholar
  20. 20.
    Huynh E, et al. Values for the ICECAP-Supportive Care Measure (ICECAP-SCM) for use in economic evaluation at end of life. Soc Sci Med. 2017;189:114–28.CrossRefPubMedGoogle Scholar
  21. 21.
    Jurkovic D. Organisation of Early Pregnancy Units and its effects on quality of care. 2015 13th February, 2018. https://ukctg.nihr.ac.uk/trials/trial-details/trial-details?trialNumber=ISRCTN10728897. Accessed 13 Feb 2018.
  22. 22.
    National Institute for Clinical Excellence, Guide to the Methods of Technology Appraisal. 2004. National Institute for Clinical Excellence.Google Scholar
  23. 23.
    National Institute for Health and Clinical Excellence, Guide to the methods of technology appraisal. 2008.Google Scholar
  24. 24.
    Al-Janabi H, Flynn TN, Coast J. Development of a self-report measure of capability wellbeing for adults: the ICECAP-A. Qual Life Res. 2012;21(1):167–76.CrossRefPubMedGoogle Scholar
  25. 25.
    Dolan P, Layard R, Metcalfe R. Measuring Subjective Wellbeing for Public Policy: Recommendations on Measures. 2011.Google Scholar
  26. 26.
    van Stel HF, Buskens E. Comparison of the SF-6D and the EQ-5D in patients with coronary heart disease. Health Qual Life Outcomes. 2006;4:20.CrossRefPubMedPubMedCentralGoogle Scholar
  27. 27.
    McCrone P, et al. A comparison of SF-6D and EQ-5D utility scores in a study of patients with schizophrenia. J Ment Health Policy Econ. 2009;12(1):27–31.PubMedGoogle Scholar
  28. 28.
    Sayah FA, et al. Comparative performance of the EQ-5D-5L and SF-6D index scores in adults with type 2 diabetes. Qual Life Res. 2017;26(8):2057–66.CrossRefPubMedGoogle Scholar
  29. 29.
    Patel AR, et al. The validity of the SF-12 and SF-6D instruments in people living with HIV/AIDS in Kenya. Health Qual Life Outcomes. 2017;15(1):143.CrossRefPubMedPubMedCentralGoogle Scholar
  30. 30.
    Dritsaki M, et al. An empirical evaluation of the SF-12, SF-6D, EQ-5D and Michigan Hand Outcome Questionnaire in patients with rheumatoid arthritis of the hand. Health Qual Life Outcomes. 2017;15(1):20.CrossRefPubMedPubMedCentralGoogle Scholar
  31. 31.
    Yousefi M, et al. Comparison of SF-6D and EQ-5D scores in patients with breast cancer. Iran Red Crescent Med J. 2016;18(5):e23556.CrossRefPubMedPubMedCentralGoogle Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of Population Health Sciences, Bristol Medical SchoolUniversity of BristolBristolUK

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