J Prev Med Public Health.  2007 Mar;40(2):169-176. 10.3961/jpmph.2007.40.2.169.

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

Affiliations
  • 1Department of Preventive Medicine, College of Medicine, Dongguk University, Korea.
  • 2Department of Preventive Medicine, University of Ulsan College of Medicine, Korea. sleemd@amc.seoul.kr

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.

Keyword

Quality of life; Quality adjusted life years; Health status

MeSH Terms

Time Factors
Questionnaires
*Quality-Adjusted Life Years
Population Surveillance
Middle Aged
Male
Korea
Humans
*Health Status
Female
Adult
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