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Value of Information Analysis in Models to Inform Health Policy.
Annual Review of Statistics and Its Application ( IF 7.4 ) Pub Date : 2022-03-07 , DOI: 10.1146/annurev-statistics-040120-010730
Christopher H Jackson 1 , Gianluca Baio 2 , Anna Heath 3 , Mark Strong 4 , Nicky J Welton 5 , Edward C F Wilson 6
Affiliation  

Value of information (VoI) is a decision-theoretic approach to estimating the expected benefits from collecting further information of different kinds, in scientific problems based on combining one or more sources of data. VoI methods can assess the sensitivity of models to different sources of uncertainty and help to set priorities for further data collection. They have been widely applied in healthcare policy making, but the ideas are general to a range of evidence synthesis and decision problems. This article gives a broad overview of VoI methods, explaining the principles behind them, the range of problems that can be tackled with them, and how they can be implemented, and discusses the ongoing challenges in the area.

中文翻译:

模型中信息分析的价值为卫生政策提供信息。

信息价值 (VoI) 是一种决策理论方法,用于估计在基于组合一个或多个数据源的科学问题中收集不同种类的进一步信息的预期收益。VoI 方法可以评估模型对不同来源的不确定性的敏感性,并有助于为进一步的数据收集设定优先级。它们已广泛应用于医疗保健政策制定,但这些想法对一系列证据综合和决策问题具有普遍意义。本文对 VoI 方法进行了广泛的概述,解释了它们背后的原理、可以用它们解决的问题范围以及如何实施它们,并讨论了该领域持续存在的挑战。
更新日期:2021-10-14
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