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

Bram RoudijkA Rogier T DondersPeep F M Stalmeiernull null
Published in: Medical decision making : an international journal of the Society for Medical Decision Making (2019)
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.
Keyphrases
  • healthcare
  • public health
  • mental health
  • health information
  • health promotion
  • risk assessment
  • artificial intelligence
  • climate change
  • health insurance
  • case control
  • data analysis