指南
检查表
德尔菲法
决策支持系统
临床决策支持系统
利益相关者
德尔菲
计算机科学
人工智能
比例(比率)
管理科学
医学
知识管理
过程管理
心理学
病理
工程类
物理
认知心理学
操作系统
量子力学
公共关系
政治学
作者
Baptiste Vasey,Myura Nagendran,Bruce Campbell,David A. Clifton,Gary S. Collins,Spiros Denaxas,Alastair K. Denniston,Livia Faes,Bart Geerts,Mudathir Ibrahim,Xiaoxuan Liu,Bilal A. Mateen,Piyush Mathur,Melissa D. McCradden,Lauren Morgan,Johan Ordish,Campbell Rogers,Suchi Saria,Daniel Shu Wei Ting,Peter Watkinson
出处
期刊:
日期:2022-05-18
卷期号:377: e070904-e070904
被引量:247
标识
DOI:10.1136/bmj-2022-070904
摘要
A growing number of artificial intelligence (AI)-based clinical decision support systems are showing promising performance in preclinical, in silico, evaluation, but few have yet demonstrated real benefit to patient care. Early stage clinical evaluation is important to assess an AI system’s actual clinical performance at small scale, ensure its safety, evaluate the human factors surrounding its use, and pave the way to further large scale trials. However, the reporting of these early studies remains inadequate. The present statement provides a multistakeholder, consensus-based reporting guideline for the Developmental and Exploratory Clinical Investigations of DEcision support systems driven by Artificial Intelligence (DECIDE-AI). We conducted a two round, modified Delphi process to collect and analyse expert opinion on the reporting of early clinical evaluation of AI systems. Experts were recruited from 20 predefined stakeholder categories. The final composition and wording of the guideline was determined at a virtual consensus meeting. The checklist and the Explanation & Elaboration (E&E) sections were refined based on feedback from a qualitative evaluation process. 123 experts participated in the first round of Delphi, 138 in the second, 16 in the consensus meeting, and 16 in the qualitative evaluation. The DECIDE-AI reporting guideline comprises 17 AI specific reporting items (made of 28 subitems) and 10 generic reporting items, with an E&E paragraph provided for each. Through consultation and consensus with a range of stakeholders, we have developed a guideline comprising key items that should be reported in early stage clinical studies of AI-based decision support systems in healthcare. By providing an actionable checklist of minimal reporting items, the DECIDE-AI guideline will facilitate the appraisal of these studies and replicability of their findings.
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