医学
透明度(行为)
健康福利
价值(数学)
成本效益分析
精算学
决策分析
质量调整寿命年
梅德林
应用心理学
卫生经济学
管理科学
循证医学
比较有效性研究
医疗保健
风险分析(工程)
决策辅助工具
情感(语言学)
卫生政策
计量经济学
信息的价值
作者
Wojtek Wiercioch,Gian Paolo Morgano,Thomas Piggott,Robby Nieuwlaat,Ignacio Neumann,Bernardo Sousa‐Pinto,Pablo Alonso‐Coello,Elie A. Akl,Lawrence Mbuagbaw,Fuad Mirzayev,Lorenzo Moja,Reem A. Mustafa,Daniele Piovani,Elena Parmelli,Zuleika Saz‐Parkinson,Samuel G. Schumacher,Ilse M. Verstijnen,Stefanos Bonovas,Holger J. Schünemann
标识
DOI:10.7326/annals-24-02013
摘要
Users of GRADE (Grading of Recommendations Assessment, Development and Evaluation) make judgments about the size of intervention effects on desirable and undesirable people-important health outcomes or on benefits and harms. Benchmarking effect sizes by using decision thresholds (DTs) can help to facilitate these judgments and the process. This article provides GRADE guidance for use of DTs for judgments about the magnitude of desirable and undesirable health effects, such as in a health guideline or health technology assessment. Through iterative discussions and refinement in in-person and online meetings of a GRADE project group and through e-mail communication, the authors developed guidance for using DTs in Evidence-to-Decision (EtD) frameworks. The authors applied the approach and used these examples from guidelines and the results of a randomized methodological study to develop official GRADE guidance. Several alternatives for determining and using DTs are presented. In the first main approach, outcome-specific DTs for trivial, small, moderate, and large effects are determined through a calculation using empirically derived generic coefficients and the outcome's utility value and are compared with the effect estimate obtained from an evidence synthesis. In the second main approach, outcome-specific DTs are also determined, but through direct surveying of decision makers to explicitly assign thresholds for the prioritized health outcomes. The article also describes how these approaches can be combined. The suggested approaches provide transparency for judgments in EtD frameworks that are based on findings from evidence syntheses.
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