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Reporting guideline for the early-stage clinical evaluation of decision support systems driven by artificial intelligence: DECIDE-AI
Nature Medicine ( IF 58.7 ) Pub Date : 2022-05-18 , DOI: 10.1038/s41591-022-01772-9
Baptiste Vasey 1, 2, 3 , Myura Nagendran 4 , Bruce Campbell 5, 6 , David A Clifton 2 , Gary S Collins 7 , Spiros Denaxas 8, 9, 10, 11 , Alastair K Denniston 12, 13, 14 , Livia Faes 14 , Bart Geerts 15 , Mudathir Ibrahim 1, 16 , Xiaoxuan Liu 12, 13 , Bilal A Mateen 8, 17, 18 , Piyush Mathur 19 , Melissa D McCradden 20, 21 , Lauren Morgan 22 , Johan Ordish 23 , Campbell Rogers 24 , Suchi Saria 25, 26 , Daniel S W Ting 27, 28 , Peter Watkinson 3, 29 , Wim Weber 30 , Peter Wheatstone 31 , Peter McCulloch 1 ,
Affiliation  

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 multi-stakeholder, 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 analyze expert opinion on the reporting of early clinical evaluation of AI systems. Experts were recruited from 20 pre-defined 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. In total, 123 experts participated in the first round of Delphi, 138 in the second round, 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 ten generic reporting items, with an E&E paragraph provided for each. Through consultation and consensus with a range of stakeholders, we 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.



中文翻译:


人工智能驱动的决策支持系统早期临床评估报告指南:DECIDE-AI



越来越多的基于人工智能 (AI) 的临床决策支持系统在临床前、计算机评估中显示出良好的性能,但很少有系统能够证明对患者护理有真正的好处。早期临床评估对于评估人工智能系统小规模的实际临床表现、确保其安全性、评估其使用的人为因素并为进一步的大规模试验铺平道路非常重要。然而,这些早期研究的报告仍然不足。本声明为人工智能驱动的决策支持系统(DECIDE-AI)的开发和探索性临床研究提供了多方利益相关者基于共识的报告指南。我们进行了两轮改进的德尔菲流程,以收集和分析专家对人工智能系统早期临床评估报告的意见。专家是从 20 个预先定义的利益相关者类别中招募的。该指南的最终组成和措辞是在虚拟共识会议上确定的。根据定性评估过程的反馈,对清单和解释与阐述 (E&E) 部分进行了完善。共有 123 名专家参与第一轮德尔菲、138 名专家参与第二轮、16 名专家参与共识会议、16 名专家参与定性评估。 DECIDE-AI 报告指南包括 17 个 AI 特定报告项目(由 28 个子项目组成)和 10 个通用报告项目,并为每个项目提供了一个 E&E 段落。通过与一系列利益相关者的协商和共识,我们制定了一份指南,其中包括在基于人工智能的医疗保健决策支持系统的早期临床研究中应报告的关键项目。 通过提供最小报告项目的可操作清单,DECIDE-AI 指南将促进这些研究的评估及其研究结果的可复制性。

更新日期:2022-05-18
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