Journal article
Reporting guideline for the early stage clinical evaluation of decision support systems driven by artificial intelligence: DECIDE-AI
BMJ (Online), Vol.377, pp.e070904-e070904
05/18/2022
DOI: 10.1136/bmj-2022-070904
PMCID: PMC9116198
PMID: 35584845
Abstract
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.
Details
- Title: Subtitle
- Reporting guideline for the early stage clinical evaluation of decision support systems driven by artificial intelligence: DECIDE-AI
- Creators
- Baptiste Vasey - University of OxfordMyura Nagendran - Imperial College LondonBruce Campbell - Royal Devon and Exeter HospitalDavid A Clifton - University of OxfordGary S Collins - University of OxfordSpiros Denaxas - UCL Hospitals Biomedical Research Centre, London, UKAlastair K Denniston - Moorfields Eye Hospital NHS Foundation TrustLivia Faes - Moorfields Eye Hospital NHS Foundation TrustBart Geerts - Healthplus.ai-R&D, Amsterdam, NetherlandsMudathir Ibrahim - Maimonides Medical CenterXiaoxuan Liu - University of BirminghamBilal A Mateen - Turing InstitutePiyush Mathur - Cleveland ClinicMelissa D McCradden - University of TorontoLauren Morgan - Morgan Human Systems, Shrewsbury, UKJohan Ordish - The Medicines and Healthcare products Regulatory Agency, London, UKCampbell Rogers - HeartFlow (United States)Suchi Saria - Bayesian Health, New York, NY, USADaniel S W Ting - National University of SingaporePeter Watkinson - Oxford University Hospitals NHS TrustWim Weber - The BMJ, London, UKPeter Wheatstone - University of LeedsPeter McCulloch - University of OxfordAaron Y LeeAlan G FraserAli ConnellAlykhan ViraAndre EstevaAndrew D AlthouseAndrew L BeamAnne de HondAnne-Laure BoulesteixAnthony BradlowAri ErcoleArsenio PaezAthanasios TsanasBarry KirbyBen GlockerCarmelo VelardoChang Min ParkCharisma HehakayaChris BaberChris PatonChristian JohnerChristopher J KellyChristopher J VincentChristopher YauClare McGenityConstantine GatsonisCorinne Faivre-FinnCrispin SimonDanielle SentDanilo BzdokDarren TreanorDavid C WongDavid F SteinerDavid HigginsDawn BensonDeclan P O’ReganDinesh V GunasekaranDominic DanksEmanuele NeriEvangelia KyrimiFalk SchwendickeFarah MagrabiFrances IvesFrank E RademakersGeorge E FowlerGiuseppe FrauH D Jeffry HoggHani J MarcusHeang-Ping ChanHenry XiangHugh F McIntyreHugh HarveyHyungjin KimIbrahim HabliJames C FacklerJames ShawJanet HighamJared M WohlgemutJaron ChongJean-Emmanuel BibaultJérémie F CohenJesper KersJessica MorleyJoachim KroisJoao MonteiroJoel HorovitzJohn FletcherJonathan TaylorJung Hyun YoonKarandeep SinghKarel G M MoonsKassandra KarpathakisKen CatchpoleKerenza HoodKonstantinos BalaskasKonstantinos KamnitsasLaura MilitelloLaure WynantsLauren Oakden-RaynerLaurence B LovatLuc J M SmitsLudwig C HinskeM Khair ElZarradMaarten van SmedenMara Giavina-BianchiMark DaleyMark P SendakMark SujanMaroeska RoversMatthew DeCampMatthew WoodwardMatthieu KomorowskiMax MarsdenMaxine MackintoshMichael D AbramoffMiguel Ángel Armengol de la HozNeale HambidgeNeil DalyNiels PeekOliver RedfernOmer F AhmadPatrick M BossuytPearse A KeanePedro N P FerreiraPetra Schnell-InderstPietro MascagniProkar DasguptaPujun GuanRachel BarnettRawen KaderReena ChopraRitse M MannRupa SarkarSaana M MäenpääSamuel G FinlaysonSarah VollamSebastian J VollmerSeong Ho ParkShakir LaherShalmali JoshiSiri L van der MeijdenSusan C ShelmerdineTien-En TanTom JW StockerValentina GianniniVince I MadaiVirginia NewcombeWei Yan NgWendy A RogersWilliam OgalloYoonyoung ParkZane B PerkinsDECIDE-AI expert group
- Resource Type
- Journal article
- Publication Details
- BMJ (Online), Vol.377, pp.e070904-e070904
- DOI
- 10.1136/bmj-2022-070904
- PMID
- 35584845
- PMCID
- PMC9116198
- NLM abbreviation
- BMJ
- eISSN
- 1756-1833
- Publisher
- British Medical Journal Publishing Group
- Language
- English
- Date published
- 05/18/2022
- Academic Unit
- Roy J. Carver Department of Biomedical Engineering; Electrical and Computer Engineering; Fraternal Order of Eagles Diabetes Research Center; Ophthalmology and Visual Sciences
- Record Identifier
- 9984258752602771
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