Background: The application of artificial intelligence (AI) in the delivery of health care is a promising area, and guidelines, consensus statements, and standards on AI regarding various topics have been developed.
Objective: We performed this study to assess the quality of guidelines, consensus statements, and standards in the field of AI for medicine and to provide a foundation for recommendations about the future development of AI guidelines.
Methods: We searched 7 electronic databases from database establishment to April 6, 2022, and screened articles involving AI guidelines, consensus statements, and standards for eligibility. The AGREE II (Appraisal of Guidelines for Research & Evaluation II) and RIGHT (Reporting Items for Practice Guidelines in Healthcare) tools were used to assess the methodological and reporting quality of the included articles.
Results: This systematic review included 19 guideline articles, 14 consensus statement articles, and 3 standard articles published between 2019 and 2022. Their content involved disease screening, diagnosis, and treatment; AI intervention trial reporting; AI imaging development and collaboration; AI data application; and AI ethics governance and applications. Our quality assessment revealed that the average overall AGREE II score was 4.0 (range 2.2-5.5; 7-point Likert scale) and the mean overall reporting rate of the RIGHT tool was 49.4% (range 25.7%-77.1%).
Conclusions: The results indicated important differences in the quality of different AI guidelines, consensus statements, and standards. We made recommendations for improving their methodological and reporting quality.
Trial registration: PROSPERO International Prospective Register of Systematic Reviews (CRD42022321360); https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=321360.
Keywords: artificial intelligence; clinical practice; consensus statements; guidelines; standards; systematic review.
©Ying Wang, Nian Li, Lingmin Chen, Miaomiao Wu, Sha Meng, Zelei Dai, Yonggang Zhang, Mike Clarke. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 22.11.2023.