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基于偏好的健康相关生命质量指标测量:何时仅反映研究人员的任意设定?

Preference-based index measurement of health-related quality of life: when does it reflect only arbitrary settings of the researcher?

机构信息

Trimberg Research Academy, University of Bamberg, Bamberg, Germany.

出版信息

Health Econ. 2011 Apr;20(4):471-83. doi: 10.1002/hec.1604.

Abstract

In health economics, health-related quality of life (HRQoL) is often assessed by means of preference-based index measurement instruments (e.g. EQ-5D, SF-6D, HUI). Each instrument of this kind consists of (1) a multi-attribute classification system for distinguishing health states and (2) a scoring function which assigns a valuation to each health state distinguished within the classification system. Scoring functions are often produced according to the so-called statistical approach which consists of two steps: (1) the valuations of some of the health states of the classification system are empirically determined and (2) the scoring function values for all health states are estimated from the empirically determined valuations using a theoretical model, i.e. an index model. This approach can run into problems because the empirically determined valuations necessarily contain arbitrary settings. This article is concerned with how these arbitrary settings together with the index model affect the final scoring function values. It is shown that for many conceivable index models the final scoring function values have no empirical meaning. Only additive models with a free additive constant are appropriate for representing the information contained in the empirically determined valuation. Only these models should be used within the statistical approach.

摘要

在健康经济学中,健康相关生活质量(HRQoL)通常通过偏好基础指数测量工具进行评估(例如 EQ-5D、SF-6D、HUI)。此类工具中的每一种都由(1)用于区分健康状况的多属性分类系统和(2)为分类系统中区分的每个健康状况赋值的评分函数组成。评分函数通常根据所谓的统计方法生成,该方法包括两个步骤:(1)经验确定分类系统中某些健康状况的估值,以及(2)使用理论模型(即指数模型)从经验确定的估值中估计所有健康状况的评分函数值。这种方法可能会遇到问题,因为经验确定的估值必然包含任意设置。本文关注这些任意设置以及指数模型如何影响最终的评分函数值。结果表明,对于许多可以想象的指数模型,最终的评分函数值没有实际意义。只有具有自由附加常数的加法模型才适合表示经验确定的估值中包含的信息。只有这些模型应在统计方法中使用。

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