前景理论和纠正方法:质量质量质量测量最新发展的政策含义

S. Lipman, W. Brouwer, A. Attema
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引用次数: 2

摘要

常见的健康状态评估方法,如时间权衡(TTO)和标准赌博(SG),通常在几个描述性无效的假设下应用,例如假设线性质量aly或预期效用(EU)理论。因此,健康状态评估练习可能导致有偏差的QALY权重。这种偏见可能反过来影响基于使用这些权重的经济评估的决策。已经提出了一些方法来纠正与不同健康状态评估技术相关的这些偏差。在本文中,我们概述了前景理论(PT)的相关性,它已成为欧盟的主要描述性替代方案,用于健康状态评估和经济评估。我们提供了工作的概述,建议解决QALY权重对所选方法的依赖。我们称之为矫正方法。通过量化PT参数,如损失厌恶、概率加权和非线性效用,有可能纠正TTO和SG的偏差,试图对健康状态的偏好产生更有效的估计。通过简单的实例说明了这种校正方法的效果。目前有几个尚未解决的问题限制了修正权重与政策的相关性,本文列出了这些问题,并为解决这些问题的研究提供了建议。然而,如果有效修正的权重是可用的,我们赞成审慎的方法来纠正有偏见的健康状态估值,其中政策制定者利用修正的权重。最后,我们建议,在认为相关的情况下,可以适用预防健康损失的损失规避溢价。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Prospect Theory and the Corrective Approach: Policy Implications of Recent Developments in QALY Measurement
Common health state valuation methodology, such as time trade-off (TTO) and standard gamble (SG), is typically applied under several descriptively invalid assumptions, for example assuming linear QALYs or expected utility (EU) theory. Hence, health state valuation exercises may lead to biased QALY weights. This bias may in turn affect decisions based on economic evaluations using such weights. Methods have been proposed to correct for these biases associated with different health state valuation techniques. In this paper we outline the relevance of prospect theory (PT), which has become the dominant descriptive alternative to EU, for health state valuations and economic evaluations. We provide an overview of work suggesting a solution for the dependence of QALY weights on the chosen methodology. We label this the corrective approach. By quantifying PT parameters, such as loss aversion, probability weighting and non-linear utility, it may be possible to correct TTO and SG for biases, in an attempt to produce more valid estimates of preferences for health states. Through straightforward examples this paper illustrates the effects of this corrective approach. Several unresolved issues currently limit the relevance of corrected weights for policy, these are listed and suggestions for research addressing these issues are provided. However, if validly corrected weights are available, we argue in favor of a deliberative approach to correcting biased health state valuations, in which policy makers utilize corrected weights. Finally we suggest that loss aversion premium for prevented health losses may be applied when deemed relevant.
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