Patient safety and artificial intelligence in clinical care
Open accessAbstract
This Viewpoint offers 3 recommendations for health care organizations and other stakeholders to consider as part of the Health and Human Services’ artificial intelligence safety program.
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Clinicians may ignore alerts, over-trust outputs, misunderstand scores, or use the tool outside its intended scope.
“Clinicians may ignore alerts, over-trust outputs, misunderstand scores, or use the tool outside its intended scope.”
From The AI Hospital Formulary: A Practical Governance Framework for Prescribing, Monitoring, and Deprescribing Artificial Intelligence in Hospitals (2026) · cites this paper as [24]
The safe-implementation discussion (page not available in our copy) identifies a tendency to overly trust AI and health care professional complacency. It does not specifically describe clinicians ignoring alerts, misunderstanding scores, or using tools outside their intended scope. (LLM, conf=0.87)
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Cites
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Research works printed but not linked: 7
- Bates DW, Levine D, Syrowatka A, et al. The potential of artificial intelligence to improve patient safety: a scoping review. NPJ Digit Med. 2021;4(1):54. doi:10.1038/s41746-021-00423-6 · DOI
- Alsentzer E, Rasmussen MJ, Fontoura R, et al. Zero-shot interpretable phenotyping of postpartum hemorrhage using large language models. NPJ Digit Med. 2023;6(1):212. doi:10.1038/s41746-023-00957-x · DOI · Paper page
- Classen DC, Longhurst C, Thomas EJ. Bending the patient safety curve: how much can AI help? NPJ Digit Med. 2023;6(1):2. doi:10.1038/s41746-022-00731-5 · DOI
- Gottlieb S, Silvis L. Regulators face novel challenges as artificial intelligence tools enter medical practice. JAMA Health Forum. 2023;4(6):e232300. doi:10.1001/jamahealthforum.2023.2300 · DOI · Paper page
- Ratwani RM, Reider J, Singh H. A decade of health information technology usability challenges and the path forward. JAMA. 2019;321(8):743-744. doi:10.1001/jama.2019.0161 · DOI
- Classen DC, Holmgren AJ, Co Z, et al. National trends in the safety performance of electronic health record systems from 2009 to 2018. JAMA Netw Open. 2020;3(5):e205547. doi:10.1001/jamanetworkopen.2020.5547 · DOI
- Gottlieb S, Silvis L. How to safely integrate large language models into health care. JAMA Health Forum. 2023; 4(9):e233909. doi:10.1001/jamahealthforum.2023.3909 · DOI · Paper page
Cited by
Sorted by citations
Artificial Intelligence in Clinical Oncology: From Productivity Enhancement to Creative Discovery
Kuno, M., Osumi, H., Udagawa, S., Yoshikawa, K., Ooki, A., Shinozaki, E., Ishikawa, T., Oba, J., Yamaguchi, K., & Sakurada, K. (2025) · Current Oncology · doi:10.3390/curroncol32110588 · Cited by 7 · see citing works
Epelde, F. (2026) · Hospitals · doi:10.3390/hospitals3030015
“Other proposals show how current patient-safety infrastructure can be extended to AI and how clinical organizations can monitor AI-related hazards [23,24].”
- Authors
- Ratwani, R. M., Bates, D. W., & Classen, D. C.
- Affiliations
- Georgetown University (US)
- Brigham and Women's Hospital (US)
- University of Utah (US)
- Corresponding author
- Ratwani, Raj M.
- Venue
- JAMA Health Forum
- Publisher
- American Medical Association (AMA)
- Published
- 2024-02-23
- Volume
- 5
- Issue
- 2
- Pages
- e235514
- ISSN
- 2689-0186 (ISSN-L)
- OpenAlex
- W4392111187
- Cited by
- 63
- References
- 0
- Citations by year
- 2026: 23 · 2025: 26 · 2024: 13
- FWCI
- 5.80
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by
- Locations
- JAMA Health Forum (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Funders
- MedStar Health Research Institute
- Agency for Healthcare Research and Quality (R01 HS026481, R18 HS029345)
- Topics
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Social Sciences › Safety Research › Ethics and Social Impacts of AI
- Physical Sciences › Engineering › Safety, Risk, Reliability and Quality › Safety Systems Engineering in Autonomy
- Keywords
- artificial intelligence, patient safety, clinical care, health care organization, AI regulation
- MeSH terms
- Artificial Intelligence, Delivery of Health Care, Humans, Patient Safety
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