Capital Health Endowed Research Chair, Faculty of Medicine and Dentistry, University of Alberta, Suite 736 University Terrace, 8303 112 Street, Edmonton, AB, T6G 2T4, Canada.
Pharmacoeconomics. 2013 Aug;31(8):635-41. doi: 10.1007/s40273-013-0071-4.
The construction of mapping models is an increasingly popular mechanism for obtaining health state utility data to inform economic evaluations in health care. There is great variation in the sophistication of the methods utilized but to date very little discussion of the appropriate theoretical framework to guide the design and evaluation of these models. In this paper, we argue that recognizing mapping models as a form of indirect health state valuation allows the use of the framework described by Dolan for the measurement of social preferences over health. Using this framework, we identify substantial concerns with the method for valuing health states that is implicit in indirect utility models (IUMs), the conflation of two sets of respondents' values in such models, and the lack of a structured and statistically reasonable approach to choosing which states to value and how many observations per state to require in the estimation dataset. We also identify additional statistical challenges associated with clustering and censoring in the datasets for IUMs, additional to those attributable to the descriptive systems, and a potentially significant problem with the systematic understatement of uncertainty in predictions from IUMs. Whilst recognizing that IUMs appear to meet the needs of reimbursement organizations that use quality-adjusted life years in their appraisal processes, we argue that current proposed quality standards are inadequate and that IUMs are neither robust nor appropriate mechanisms for estimating utilities for use in cost-effectiveness analyses.
映射模型的构建是获取健康状态效用数据以支持医疗保健经济评估的一种越来越流行的机制。所使用的方法的复杂性存在很大差异，但迄今为止，对于指导这些模型的设计和评估的适当理论框架，几乎没有讨论。在本文中，我们认为将映射模型视为间接健康状态估值的一种形式，可以使用 Dolan 描述的框架来衡量对健康的社会偏好。使用该框架，我们确定了在间接效用模型（IUM）中隐含的健康状态估值方法、在这些模型中混淆了两组受访者的价值观以及缺乏结构化和统计合理的方法来选择要估值的状态以及在估计数据集中每个状态需要多少观测值等方面存在重大问题。我们还确定了与 IUM 数据集相关的聚类和 censoring 相关的额外统计挑战，除了归因于描述性系统的那些之外，以及 IUM 预测中不确定性的系统低估可能是一个重大问题。虽然承认 IUM 似乎满足了在其评估过程中使用质量调整生命年的报销组织的需求，但我们认为当前提出的质量标准是不够的，并且 IUM 既不是用于成本效益分析的效用估计的稳健也不适当的机制。
