Centre for the Study of Choice (CenSoC), University of Technology, Sydney, Ultimo, New South Wales, Australia.
Pharmacoeconomics. 2010;28(9):711-22. doi: 10.2165/11535660-000000000-00000.
There is increasing interest in using ranking tasks, discrete choice experiments and best-worst scaling studies to estimate QALY values for use in cost-utility analysis. The research frontier in choice modelling is moving rapidly, with a number of issues being explored across several disciplines. These issues include the estimation of discount factors, proper modelling of the variance scale factor and the estimation of individual-level utility functions. Some of these issues are particularly acute when discrete choice tasks are used to facilitate extra-welfarist analyses that rely on population-based values. There are also potential problems in implementing such tasks that have received little interest in the non-health discrete choice literature because they are specific to the QALY framework. This article details these issues and offers recommendations on the conduct of 21st century QALY valuation exercises that propose to use any tasks that rely on discrete choices.
人们越来越感兴趣地使用排名任务、离散选择实验和最佳最差标度研究来估计用于成本效用分析的 QALY 值。选择建模的研究前沿正在迅速发展,许多问题正在几个学科中得到探讨。这些问题包括折扣因素的估计、方差尺度因素的适当建模以及个体效用函数的估计。当离散选择任务用于促进依赖于基于人群的价值观的额外福利分析时,其中一些问题尤其尖锐。在非健康离散选择文献中,由于这些问题特定于 QALY 框架,因此很少有人关注实施此类任务所存在的潜在问题。本文详细介绍了这些问题,并就拟议使用任何依赖离散选择的任务进行 21 世纪 QALY 估值练习提出了建议。