Department of Nutrition and Food Sciences, Faculty of Agricultural and Food Sciences, American University of Beirut, P.O.BOX: 11-0236, Riad El Solh, Beirut, 1107-2020, Lebanon.
Health Economics and Decision Science, School of Health and Related Research, The University of Sheffield, Regent Court, 30 Regent Street, Sheffield, S1 4DA, UK.
Eur J Health Econ. 2019 Mar;20(2):245-255. doi: 10.1007/s10198-018-0991-1. Epub 2018 Jul 6.
Different countries have different preferences regarding health, and there are different value sets for popular preference-based measures across different countries. However, the cost of collecting data to generate country-specific value sets can be prohibitive for countries with smaller population size or low- and middle-income countries (LMIC). This paper explores whether existing preference weights could be modelled alongside a small own country valuation study to generate representative estimates. This is explored using a case study modelling UK data alongside smaller US samples to generate US estimates.
We analyse EQ-5D valuation data derived from representative samples of the US and UK populations using time trade-off to value 42 health states. A nonparametric Bayesian model was applied to estimate a US value set using the full UK dataset and subsets of the US dataset for 10, 15, 20 and 25 health states. Estimates are compared to a US value set estimated using US values alone using mean predictions and root mean square error.
The results suggest that using US data elicited for 20 health states alongside the existing UK data produces similar predicted mean valuations and RMSE as the US value set, while 25 health states produce the exact features.
The promising results suggest that existing preference data could be combined with a small valuation study in a new country to generate preference weights, making own country value sets more achievable for LMIC. Further research is encouraged.
不同国家对健康有不同的偏好，不同国家的偏好指标也有不同的价值体系。然而，对于人口规模较小或中低收入国家（LMIC）来说，收集数据以生成特定国家的价值体系的成本可能过高。本文探讨了是否可以将现有的偏好权重与小规模的本国估值研究结合起来，以生成代表性的估计值。这是通过使用来自英国和美国小样本的案例研究模型来生成美国估计值来探索的。
我们使用时间权衡法分析了来自美国和英国代表性样本的 EQ-5D 估值数据，以评估 42 种健康状态的价值。应用非参数贝叶斯模型，使用完整的英国数据集和美国数据集的子集（10、15、20 和 25 个健康状态）来估计美国的价值体系。将估计值与仅使用美国价值的美国价值体系进行比较，使用均值预测和均方根误差进行比较。
结果表明，使用美国的 20 个健康状态数据和现有的英国数据相结合，可以产生与美国价值体系相似的预测均值估值和 RMSE，而 25 个健康状态则产生完全相同的特征。
有希望的结果表明，现有的偏好数据可以与新国家的小规模估值研究相结合，以生成偏好权重，使 LMIC 更有可能生成本国的价值体系。鼓励进一步研究。
