Kharroubi Samer A
Department of Mathematics, University of York, York, UK,
Appl Health Econ Health Policy. 2015 Aug;13(4):409-20. doi: 10.1007/s40258-015-0171-8.
There is interest in the extent to which valuations of health may differ between different countries and cultures, but few studies have compared preference values of health states obtained in different countries.
We sought to estimate and compare two directly elicited valuations for SF-6D health states between the Japan and U.K. general adult populations using Bayesian methods.
We analysed data from two SF-6D valuation studies where, using similar standard gamble protocols, values for 241 and 249 states were elicited from representative samples of the Japan and U.K. general adult populations, respectively. We estimate a function applicable across both countries that explicitly accounts for the differences between them, and is estimated using data from both countries.
The results suggest that differences in SF-6D health-state valuations between the Japan and U.K. general populations are potentially important. The magnitude of these country-specific differences in health-state valuation depended, however, in a complex way on the levels of individual dimensions.
The new Bayesian non-parametric method is a powerful approach for analysing data from multiple nationalities or ethnic groups, to understand the differences between them and potentially to estimate the underlying utility functions more efficiently.
人们关注不同国家和文化之间健康估值的差异程度，但很少有研究比较不同国家获得的健康状态偏好值。
我们试图使用贝叶斯方法估计并比较日本和英国普通成年人群对SF-6D健康状态的两种直接得出的估值。
我们分析了两项SF-6D估值研究的数据，在这两项研究中，分别使用类似的标准博弈方案，从日本和英国普通成年人群的代表性样本中得出了241种和249种状态的值。我们估计了一个适用于两国的函数，该函数明确考虑了两国之间的差异，并使用两国的数据进行估计。
结果表明，日本和英国普通人群之间SF-6D健康状态估值的差异可能很重要。然而，这些特定国家在健康状态估值上的差异程度以一种复杂的方式取决于各个维度的水平。
新的贝叶斯非参数方法是一种强大的方法，可用于分析来自多个民族或种族群体的数据，以了解他们之间的差异，并有可能更有效地估计潜在的效用函数。
