Health Services Management Department, Guizhou Medical University, Guiyang, China.
Faculty of Psychology, Universitas Padjadjaran, Jatinangor, Indonesia.
Qual Life Res. 2022 Jul;31(7):2175-2187. doi: 10.1007/s11136-021-03075-x. Epub 2022 Feb 18.
Many countries have established their own EQ-5D value sets proceeding on the basis that health preferences differ among countries/populations. So far, published studies focused on comparing value set using TTO data. This study aims to compare the health preferences among 11 Asian populations using the DCE data collected in their EQ-5D-5L valuation studies.
In the EQ-VT protocol, 196 pairs of EQ-5D-5L health states were valued by a general population sample using DCE method for all studies. DCE data were obtained from the study PI. To understand how the health preferences are different/similar with each other, the following analyses were done: (1) the statistical difference between the coefficients; (2) the relative importance of the five EQ-5D dimensions; (3) the relative importance of the response levels.
The number of statistically differed coefficients between two studies ranged from 2 to 16 (mean: 9.3), out of 20 main effects coefficients. For the relative importance, there is not a universal preference pattern that fits all studies, but with some common characteristics, e.g. mobility is considered the most important; the relative importance of levels are approximately 20% for level 2, 30% for level 3, 70% for level 4 for all studies.
Following a standardized study protocol, there are still considerable differences in the modeling and relative importance results in the EQ-5D-5L DCE data among 11 Asian studies. These findings advocate the use of local value set for calculating health state utility.
许多国家都根据各国/人群之间健康偏好的差异,建立了自己的 EQ-5D 价值体系。到目前为止,已发表的研究主要集中在使用 TTO 数据比较价值体系上。本研究旨在使用从 EQ-5D-5L 估值研究中收集的 DCE 数据比较 11 个亚洲人群的健康偏好。
在 EQ-VT 方案中,所有研究均使用 DCE 方法由一般人群样本对 196 对 EQ-5D-5L 健康状况进行了赋值。DCE 数据由研究 PI 提供。为了了解健康偏好彼此之间的差异/相似性,进行了以下分析:(1)系数之间的统计学差异;(2)五个 EQ-5D 维度的相对重要性;(3)反应水平的相对重要性。
在 20 个主要效应系数中,两项研究之间有统计学差异的系数数量从 2 到 16 不等(平均值:9.3)。对于相对重要性,没有一种普遍适用的偏好模式适用于所有研究,但具有一些共同特征,例如,移动性被认为是最重要的;对于所有研究,各水平的相对重要性约为 20%为 2 级,30%为 3 级,70%为 4 级。
在遵循标准化研究方案的情况下,在 11 项亚洲研究的 EQ-5D-5L DCE 数据中,建模和相对重要性结果仍存在相当大的差异。这些发现主张使用本地价值体系来计算健康状态效用。