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成本效益亚组分析中异质性的价值:概念框架与应用

The value of heterogeneity for cost-effectiveness subgroup analysis: conceptual framework and application.

作者信息

Espinoza Manuel A, Manca Andrea, Claxton Karl, Sculpher Mark J

机构信息

Department of Public Health, Pontificia Universidad Católica de Chile, Santiago, Chile (MAE)

Department of Scientific Affairs, Institute of Public Health, Santiago, Chile (MAE)

出版信息

Med Decis Making. 2014 Nov;34(8):951-64. doi: 10.1177/0272989X14538705. Epub 2014 Jun 18.

Abstract

This article develops a general framework to guide the use of subgroup cost-effectiveness analysis for decision making in a collectively funded health system. In doing so, it addresses 2 key policy questions, namely, the identification and selection of subgroups, while distinguishing 2 sources of potential value associated with heterogeneity. These are 1) the value of revealing the factors associated with heterogeneity in costs and outcomes using existing evidence (static value) and 2) the value of acquiring further subgroup-related evidence to resolve the uncertainty given the current understanding of heterogeneity (dynamic value). Consideration of these 2 sources of value can guide subgroup-specific treatment decisions and inform whether further research should be conducted to resolve uncertainty to explain variability in costs and outcomes. We apply the proposed methods to a cost-effectiveness analysis for the management of patients with acute coronary syndrome. This study presents the expected net benefits under current and perfect information when subgroups are defined based on the use and combination of 6 binary covariates. The results of the case study confirm the theoretical expectations. As more subgroups are considered, the marginal net benefit gains obtained under the current information show diminishing marginal returns, and the expected value of perfect information shows a decreasing trend. We present a suggested algorithm that synthesizes the results to guide policy.

摘要

本文建立了一个通用框架,以指导在集体筹资的卫生系统中使用亚组成本效益分析进行决策。在此过程中,它解决了两个关键政策问题,即亚组的识别和选择,同时区分了与异质性相关的两种潜在价值来源。这两种价值来源分别是:1)利用现有证据揭示成本和结果异质性相关因素的价值(静态价值);2)鉴于当前对异质性的理解,获取更多亚组相关证据以解决不确定性的价值(动态价值)。对这两种价值来源的考量可以指导亚组特异性治疗决策,并为是否应开展进一步研究以解决不确定性、解释成本和结果的变异性提供依据。我们将所提出的方法应用于急性冠脉综合征患者管理的成本效益分析。本研究展示了在基于6个二元协变量的使用和组合定义亚组时,当前信息和完美信息下的预期净效益。案例研究结果证实了理论预期。随着考虑的亚组增多,当前信息下获得的边际净效益增益呈现边际收益递减,完美信息的预期价值呈下降趋势。我们提出了一种综合结果以指导政策的建议算法。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/86c6/4232328/45ed388f3be2/10.1177_0272989X14538705-fig1.jpg

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