Quality of Life Research

, Volume 25, Issue 7, pp 1845–1852 | Cite as

The EQ-5D-5L valuation study in Korea

  • Seon-Ha Kim
  • Jeonghoon Ahn
  • Minsu Ock
  • Sangjin Shin
  • Jooyeon Park
  • Nan Luo
  • Min-Woo JoEmail author



This study aimed to estimate Korean preference weights for EQ-5D-5L based on values elicited from Korean population by applying the EuroQol Valuation Technology (EQ-VT) program and the standard protocol by the EuroQol Group.


The multistage quota sampling method was used to recruit 1085 subjects from the general population in Korea. Each respondent valuated 10 health states using the composite time trade-off (cTTO) and 7 health states using discrete choice experiment. The EQ-VT program was developed by the EuroQol Group and translated into Korean with the Korean research team. Computer-assisted, face-to-face interviews were conducted. A range of predictive models were explored using cTTO. The most appropriate model was determined after assessing goodness of fit, logical consistency, and parsimony.


Of 3206 contacted, 1085 subjects completed interviews (33.8 %) and 1080 were used for modeling. A model with dummy variables for each level of severity and dimension and a term that picked up whether any dimension in the state was at level 4 or 5 was selected as the best predictive model. All coefficients of the final model were statistically significant and logically consistent. In addition, it was parsimonious. This model had mean absolute error of 0.027, and the absolute error for all 86 health states was below 0.1.


The final model built in this study appears to predict the utilities of the states which were valuated directly. This model could be used to interpolate quality weights for all EQ-5D-5L health states.


EQ-5D-5L Quality of life Social values Composite time trade-off Discrete choice experiment Utility 



This study was cofunded by the National Evidence-Based Healthcare Collaborating Agency (NECA-A-13-002), Republic of Korea and the EuroQol Group.

Supplementary material

11136_2015_1205_MOESM1_ESM.docx (18 kb)
Supplementary material 1 (DOCX 17 kb)
11136_2015_1205_MOESM2_ESM.xlsx (66 kb)
Supplementary material 2 (XLSX 65 kb)


  1. 1.
    Dolan, P., Gudex, C., Kind, P., & Williams, A. (1996). Valuing health states: A comparison of methods. Journal of Health Economics, 15(2), 209–231.CrossRefPubMedGoogle Scholar
  2. 2.
    Torrance, G. W. (1986). Measurement of health state utilities for economic appraisal. Journal of Health Economics, 5(1), 1–30.CrossRefPubMedGoogle Scholar
  3. 3.
    Torrance, G. W., Feeny, D. H., Furlong, W. J., Barr, R. D., Zhang, Y., & Wang, Q. (1996). Multiattribute utility function for a comprehensive health status classification system. Health Utilities Index Mark 2. Medical Care, 34(7), 702–722.CrossRefPubMedGoogle Scholar
  4. 4.
    Feeny, D., Furlong, W., Torrance, G. W., Goldsmith, C. H., Zhu, Z., DePauw, S., et al. (2002). Multiattribute and single-attribute utility functions for the health utilities index mark 3 system. Medical Care, 40(2), 113–128.CrossRefPubMedGoogle Scholar
  5. 5.
    Brazier, J., Roberts, J., & Deverill, M. (2002). The estimation of a preference-based measure of health from the SF-36. Journal of Health Economics, 21(2), 271–292.CrossRefPubMedGoogle Scholar
  6. 6.
    Norman, R., Cronin, P., Viney, R., King, M., Street, D., & Ratcliffe, J. (2009). International comparisons in valuing EQ-5D health states: A review and analysis. Value in Health, 12(8), 1194–1200.CrossRefPubMedGoogle Scholar
  7. 7.
    Jo, M. W., Yun, S. C., & Lee, S. I. (2008). Estimating quality weights for EQ-5D health states with the time trade-off method in South Korea. Value in Health, 11(7), 1186–1189.CrossRefPubMedGoogle Scholar
  8. 8.
    Lee, Y. K., Nam, H. S., Chuang, L. H., Kim, K. Y., Yang, H. K., Kwon, I. S., et al. (2009). South Korean time trade-off values for EQ-5D health states: Modeling with observed values for 101 health states. Value in Health, 12(8), 1187–1193.CrossRefPubMedGoogle Scholar
  9. 9.
    Herdman, M., Gudex, C., Lloyd, A., Janssen, M., Kind, P., Parkin, D., et al. (2011). Development and preliminary testing of the new five-level version of EQ-5D (EQ-5D-5L). Quality of Life Research, 20(10), 1727–1736.CrossRefPubMedPubMedCentralGoogle Scholar
  10. 10.
    Kim, S. H., Kim, H. J., Lee, S. I., & Jo, M. W. (2012). Comparing the psychometric properties of the EQ-5D-3L and EQ-5D-5L in cancer patients in Korea. Quality of Life Research, 21(6), 1065–1073.CrossRefPubMedGoogle Scholar
  11. 11.
    Pickard, A. S., DeLeon, M. C., Kohlmann, T., Cella, D., & Rosenbloom, S. (2007). Psychometric comparison of the standard EQ-5D to a 5 level version in cancer patients. Medical Care, 45(3), 259–263.CrossRefPubMedGoogle Scholar
  12. 12.
    Janssen, M. F., Birnie, E., Haagsma, J. A., & Bonsel, G. J. (2008). Comparing the standard EQ-5D three-level system with a five-level version. Value in Health, 11(2), 275–284.CrossRefPubMedGoogle Scholar
  13. 13.
    van Reenen, M., & Janssen, B. (2015). EQ-5D-5L user guide basic information on how to use the EQ-5D-5L instrument version 2.1.
  14. 14.
    Oppe, M., Devlin, N. J., van Hout, B., Krabbe, P. F., & de Charro, F. (2014). A programme of methodological research to arrive at the new international EQ-5D-5L valuation protocol. Value in Health, 17(4), 445–453.CrossRefPubMedGoogle Scholar
  15. 15.
    Devlin, N. J., Tsuchiya, A., Buckingham, K., & Tilling, C. (2011). A uniform Time Trade Off method for states better and worse than dead: Feasibility study of the ‘lead time’ approach. Health Economics, 20(3), 348–361.CrossRefPubMedGoogle Scholar
  16. 16.
    Ramos-Goni, J. M., Pinto-Prades, J. L., Oppe, M., Cabases, J. M., Serrano-Aguilar, P., & Rivero-Arias, O. (2014). Valuation and modeling of EQ-5D-5L health states using a hybrid approach. Medical Care. doi: 10.1097/MLR.0000000000000283.
  17. 17.
    Badia, X., Roset, M., & Herdman, M. (1999). Inconsistent responses in three preference-elicitation methods for health states. Social Science and Medicine, 49(7), 943–950.CrossRefPubMedGoogle Scholar
  18. 18.
    Tsuchiya, A., Ikeda, S., Ikegami, N., Nishimura, S., Sakai, I., Fukuda, T., et al. (2002). Estimating an EQ-5D population value set: The case of Japan. Health Economics, 11(4), 341–353.CrossRefPubMedGoogle Scholar
  19. 19.
    Dolan, P. (1997). Modeling valuations for EuroQol health states. Medical Care, 35(11), 1095–1108.CrossRefPubMedGoogle Scholar
  20. 20.
    Wittrup-Jensen, K. U., Lauridsen, J., & Pedersen, K. M. (2008). An assessment of inconsistencies in the valuation of hypothetical EuroQol (EQ-5D) health states. Health Economics Papers, 5, 1–24. Accessed March 25, 2015.
  21. 21.
    Dolan, P., Gudex, C., Kind, P., & Williams, A. (1996). The time trade-off method: Results from a general population study. Health Economics, 5(2), 141–154.CrossRefPubMedGoogle Scholar
  22. 22.
    Kind, P., Brooks, R., & Rabin, R. (Eds.). (2005). EQ-5D concepts and method. Dordrecht: Springer.Google Scholar
  23. 23.
    Norman, R., Cronin, P., & Viney, R. (2013). A pilot discrete choice experiment to explore preferences for EQ-5D-5L health states. Applied Health Economics and Health Policy, 11(3), 287–298.CrossRefPubMedGoogle Scholar
  24. 24.
    Walters, S. J., & Brazier, J. E. (2005). Comparison of the minimally important difference for two health state utility measures: EQ-5D and SF-6D. Quality of Life Research, 14(6), 1523–1532.CrossRefPubMedGoogle Scholar
  25. 25.
    Shaw, J. W., Johnson, J. A., & Coons, S. J. (2005). US valuation of the EQ-5D health states: Development and testing of the D1 valuation model. Medical Care, 43(3), 203–220.CrossRefPubMedGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Seon-Ha Kim
    • 1
  • Jeonghoon Ahn
    • 2
  • Minsu Ock
    • 3
  • Sangjin Shin
    • 2
  • Jooyeon Park
    • 2
  • Nan Luo
    • 4
  • Min-Woo Jo
    • 1
    • 3
    Email author
  1. 1.Department of Nursing, College of Health ScienceDankook UniversityCheonanSouth Korea
  2. 2.Division for Healthcare Technology Assessment ResearchNational Evidence-Based Healthcare Collaborating AgencySeoulSouth Korea
  3. 3.Department of Preventive MedicineUniversity of Ulsan College of MedicineSeoulSouth Korea
  4. 4.Saw Swee Hock School of Public HealthNational University of SingaporeSingaporeSingapore

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