General Population Time Trade-off Values for 42 EQ-5D Health States in South Korea

시간교환법을 이용한 일부 EQ-5D 건강상태의 질 가중치 측정

  • Jo, Min-Woo (Department of Preventive Medicine, College of Medicine, Dongguk University) ;
  • Lee, Sang-Il (Department of Preventive Medicine, University of Ulsan College of Medicine)
  • 조민우 (동국대학교 의과대학 예방의학교실) ;
  • 이상일 (울산대학교 의과대학 예방의학교실)
  • Published : 2007.03.31

Abstract

Objectives : This study was conducted to elicit quality weights for 42 EQ-5D health states with the time trade-off (TTO) method from the general population of South Korea. Methods : We selected the same EQ-5D health states as those in the UK MVH study. The Korean version of EQ-5D questionnaire and TTO method were used for the valuation process. We interviewed 500 people as a representative sample of the general population in Seoul and Gyeonggido. The result was compared with those from UK, Japan, and USA by Spearman's rank correlation and t-test. Results : TTO values for 42 EQ-5D health states and 'unconscious' state were obtained from the general South Korean population. The best one was '11112' state and the worst one was 'unconscious' state. The states worse than death were '33323', '33333', and 'unconscious' states, which had negative TTO values. There was a strong correlation between TTO values of the EQ-5D health states and those of their corresponding states from UK, Japan, and USA (Spearman's correlation coefficient: 0.885, 0.882, and 0.944, respectively, p <0.001). However, absolute TTO values of most EQ-5D health states were significantly different from those of their corresponding states in other foreign studies (UK : 41/42, USA : 32/42, Japan : 15/17). Conclusions : We found that the Korean general population TTO values for EQ-5D health states were different from those of other foreign studies, suggesting that a specific Korean valuation set should be developed and used for economic evaluation studies in South Korea.

Keywords

References

  1. Drummond MF, O'Brien B, Stodart G, Torrance G. Methods for the Economic Evaluation of Health Care Programes. 3rd ed. New York: Oxford University Press; 2005
  2. Gold MR, Siegal JE, Russell LB, Weinstein MC. Cost-effectiveness in Health and Medicine. New York: Oxford University Press; 1996
  3. Patrick DL, Bush JW, Chen MM. Methods for measuring levels of well-being for a health status index. Health Serv Res 1973; 8(3): 228-245
  4. Kaplan RM, Anderson JP. A general health policy model: Update and applications. Health Serv Res 1988; 23(2): 203-235
  5. Torrance GW, Boyle MH, Horwood SP. Application of multi-attribute utility theory to measure social preferences for health states. Oper Res 1982; 30(6): 1043-1069 https://doi.org/10.1287/opre.30.6.1043
  6. Torrance GW, Feeny DH, Furlong WJ, Barr RD, Zhang Y, Wang Q. Multiattribute utility function for a comprehensive health status classification system: Health Utilities Index Mark 2. Med Care 1996; 34(7): 702-722 https://doi.org/10.1097/00005650-199607000-00004
  7. EuroQol Group. EuroQol: A new facility for the measurement of health-related quality of life. The EuroQol Group. Health Policy 1990; 16(3): 199-208 https://doi.org/10.1016/0168-8510(90)90421-9
  8. Brooks R. EuroQol: The current state of play. Health Policy 1996; 37(1): 53-72 https://doi.org/10.1016/0168-8510(96)00822-6
  9. Brooks R, Rabin R, Charro F. The Measure-Ment and Valuation of Health Status Using EQ-5D: A European Perspective. Dordrecht: Kluwer Academic Publisher; 2003
  10. Dolan P, Gudex C, Kind P, Williams A. Valuing health states: A comparison of methods. J Health Econ 1996; 15(2): 209-231 https://doi.org/10.1016/0167-6296(95)00038-0
  11. Park SM, Park MH, Won JH, Lee KO, Choe WS, Heo DS, Kim SY, Lee KS, Yun YH. EuroQol and survival prediction in terminal cancer patients: A multicenter prospective study in hospice-palliative care units. Support Care Cancer 2006; 14(4): 329-333 https://doi.org/10.1007/s00520-005-0889-1
  12. Lee HY, Park EC, Kim HJ, Choi JY, Kim HN. Cost-utility analysis of cochlear implants in Korea using different measures of utility. Acta Otolaryngol 2006; 126(8): 817-823 https://doi.org/10.1080/00016480500525213
  13. Oh KT, Kwak EJ, Ju EK, Kim TH, Lee JH, Chung WT, Choe WJ, Bae SC. Health-related quality of life in Korean patients with rheumatic disease. J Korean Rheum Assoc 2002; 4 suppl: S39-S59 (Korean)
  14. Lee MK, Choi JY, Kim IK, Cho YA, Kim YS, Jung HJ, Kim LN, Lee YK, Cho Y. Does living nearby a garbage dumping site degrade the quality of life? A case study based on Shindong Myeon residents, Chun-cheon Si. J Prev Med Public Health 2006; 39(4): 302-308 (Korean)
  15. Dolan P. Modeling valuations for EuroQol health states. Med Care 1997; 35(11): 1095-1108 https://doi.org/10.1097/00005650-199711000-00002
  16. Patrick DL, Starks HE, Cain KC, Uhlmann RF, Pearlman RA. Measuring preferences for health states worse than death. Med Decis Making 1994; 14(1): 9-18 https://doi.org/10.1177/0272989X9401400102
  17. Tsuchiya A, Ikeda S, Ikegami N, Nishimura S, Sakai I, Fukuda T, Hamashima C, Hisachige A, Tamura M. Estimating an EQ-5D population value set: The case of Japan. Health Econ 2002; 11(4): 341-353 https://doi.org/10.1002/hec.673
  18. Shaw JW, Johnson JA, Coons SJ. US valuation of the EQ-5D health states: Development and testing of the D1 valuation model. Med Care 2005; 43(3): 203-220 https://doi.org/10.1097/00005650-200503000-00003
  19. Greiner W, Claes C, Busschbach JJ, Graf von der Schulenburg JM. Validating the EQ-5D with time trade off for the German population. Eur J Health Econ 2004; 6(2): 124-130 https://doi.org/10.1007/s10198-004-0264-z
  20. Badia X, Roset M, Herdman M, Kind P. A comparison United Kingdom and Spanish general population time trade-off values for EQ-5D health states. Med Decis Making 2001; 21(1): 7-16 https://doi.org/10.1177/0272989X0102100102
  21. 통계청. 한국통계연감 52호. 통계청; 2005, 157-159쪽
  22. Dolan P, Gudex C, Kind P, Williams A. The time trade-off method: results from a general population study. Health Econ 1996; 5(2): 141-154 https://doi.org/10.1002/(SICI)1099-1050(199603)5:2<141::AID-HEC189>3.0.CO;2-N
  23. Burstrom K, Johannesson M, Diderichsen F. Swedish population health-related quality of life results using the EQ-5D. Qual Life Res 2001; 10(7): 621-635 https://doi.org/10.1023/A:1013171831202
  24. Johnson JA, Pickard AS. Comparison of the EQ-5D and SF-12 health surveys in a general population survey in Alberta, Canada. Med Care 2000; 38(1): 115-121 https://doi.org/10.1097/00005650-200001000-00013
  25. Seong SS, Choi CB, Sung YK, Park YW, Lee HS, Uhm WS, Kim TW, Jun JB, Yoo DH, Lee OY, Bae SC. Health-related quality of life using EQ-5D in Koreans. J Korean Rheum Assoc 2004; 11(3): 254-262 (Korean)
  26. Chen LC, Kleinman A, Ware NC. Health and Social Change in International Perspective. Boston: Harvard University Press; 1994
  27. Sen A. Health: perception versus observation. BMJ 2002; 324(7342): 860-861 https://doi.org/10.1136/bmj.324.7342.860
  28. Jelsma J, Ferguson G. The determinants of self-reported health-related quality of life in a culturally and socially diverse South African community. Bull World Health Organ 2004; 82(3): 206-212
  29. Polsky D, Willke RJ, Scott K, Schulman KA, Glick HA. A comparison of scoring weights for the EuroQol derived from patients and the general public. Health Econ 2001; 10(1): 27-37 https://doi.org/10.1002/1099-1050(200101)10:1<27::AID-HEC561>3.0.CO;2-R
  30. Balk DE. A Review of: 'Death and Bereavement in Asia, Australia, and New Zealand (vol. 4 of the death and bereavement around the world series)'. Death Stud 2006; 30(1): 87-93 https://doi.org/10.1080/07481180500348894
  31. Keown D. End of life: The Buddhist view. Lancet 2005; 366(9489): 952-955 https://doi.org/10.1016/S0140-6736(05)67323-0
  32. Yick AG, Gupta R. Chinese cultural dimensions of death, dying, and bereavement: Focus group findings. J Cult Divers 2002; 9(2): 32-42