Cultural Values: Can They Explain Differences in Health Utilities between Countries?

Med Decis Making. 2019 Jul;39(5):605-616. doi: 10.1177/0272989X19841587. Epub 2019 Jul 1.

Abstract

Introduction. Health utilities are widely used in health care. The distributions of utilities differ between countries; some countries more often report worse than dead health states, while mild states are valued more or less the same. We hypothesize that cultural values explain these country-related utility differences. Research Question. What is the effect of sociodemographic background, methodological factors, and cultural values on differences in health utilities? Methods and Analyses. Time tradeoff data from 28 EQ-5D valuation studies were analyzed, together with their sociodemographic variables. The dependent variable was Δu, the utility difference between mild and severe states. Country-specific cultural variables were taken from the World Values Survey. Multilevel models were used to analyze the effect of sociodemographic background, methodology (3L v. 5L), and cultural values on Δu. Intraclass correlation (ICC) for country variation was used to assess the impact of the predicting variables on the variation between countries. Results. Substantial variation in Δu was found between countries. Adding cultural values did not reduce ICCs for country variation. Sociodemographic background variables were only weakly associated with Δu and did not affect the ICC. Δu was 0.118 smaller for EQ-5D-5L studies. Discussion.Δu varies between countries. These differences were not explained by national cultural values. In conclusion, despite correction for various variables, utility differences between countries remain substantial and unexplained. This justifies the use of country-specific value sets for instruments such as the EQ-5D.

Keywords: EQ-5D; cultural values; health utilities; multilevel modelling.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Cultural Characteristics*
  • Facilities and Services Utilization
  • Female
  • Health Services / statistics & numerical data*
  • Health Status
  • Health Surveys / statistics & numerical data
  • Humans
  • Male
  • Patient Acceptance of Health Care / statistics & numerical data
  • Quality of Life
  • Socioeconomic Factors