AI, Health, and Health Care Today and Tomorrow: The JAMA Summit Report on Artificial Intelligence
Abstract
Importance Artificial intelligence (AI) is changing health and health care on an unprecedented scale. Though the potential benefits are massive, so are the risks. The JAMA Summit on AI discussed how health and health care AI should be developed, evaluated, regulated, disseminated, and monitored. Observations Health and health care AI is wide-ranging, including clinical tools (eg, sepsis alerts or diabetic retinopathy screening software), technologies used by individuals with health concerns (eg, mobile health apps), tools used by health care systems to improve business operations (eg, revenue cycle management or scheduling), and hybrid tools supporting both business operations (eg, documentation and billing) and clinical activities (eg, suggesting diagnoses or treatment plans). Many AI tools are already widely adopted, especially for medical imaging, mobile health, health care business operations, and hybrid functions like scribing outpatient visits. All these tools can have important health effects (good or bad), but these effects are often not quantified because evaluations are extremely challenging or not required, in part because many are outside the US Food and Drug Administration's regulatory oversight. A major challenge in evaluation is that a tool's effects are highly dependent on the human-computer interface, user training, and setting in which the tool is used. Numerous efforts lay out standards for the responsible use of AI, but most focus on monitoring for safety…
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In the United States, nearly half of hospitals and up to two-thirds of physicians report using some form of AI in their practice.
“in the United States nearly half of hospitals12 and up to two-thirds of physicians report using some form of AI in their practice13.”
From What the AI era doctor should know: a scoping review of proposed artificial intelligence competencies for medical education (2026) · cites this paper as [13]
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- Authors
- Angus, D. C., Khera, R., Lieu, T., Liu, V., Ahmad, F. S., Anderson, B., Bhavani, S. V., Bindman, A., Brennan, T., Celi, L. A., Chen, F., Cohen, I. G., Denniston, A., Desai, S., Embí, P., Faisal, A., Ferryman, K., Gerhart, J., Gross, M., Hernandez-Boussard, T., Howell, M., Johnson, K., Lee, K., Liu, X., Lomis, K., London, A. J., Longhurst, C. A., Mandl, K. D., McGlynn, E., Mello, M. M., Munoz, F., Ohno-Machado, L., Ouyang, D., Perlis, R., Phillips, A., Rhew, D., Ross, J. S., Saria, S., Schwamm, L., Seymour, C. W., Shah, N. H., Shah, R., Singh, K., Solomon, M., Spates, K., Spector-Bagdady, K., Wang, T., Gichoya, J. W., Weinstein, J., Wiens, J., Bibbins-Domingo, K., AI, J. S. O., Alterovitz, G., Clancy, H. A., Dawson, L., Diamond, M., Holve, E. C., Kahn, J., Pengetnze, Y. M., Rao, S., Shrank, W. H., & Termulo, C.
- Affiliations
- Yale University (US)
- Kaiser Permanente (US)
- Northwestern University (US)
- Clinton Health Access Initiative (US)
- Emory University (US)
- Harvard University (US)
- Massachusetts Institute of Technology (US)
- American Medical Association (US)
- University of Birmingham (GB)
- Vanderbilt University Medical Center (US)
- Imperial College London (GB)
- Johns Hopkins University (US)
- Epic Systems (United States) (US)
- Stanford University, Stanford, California
- Google (United States) (US)
- University of Pennsylvania (US)
- Microsoft (United Kingdom) (GB)
- Carnegie Mellon University (US)
- University of California, San Diego Health
- Boston Children's Hospital (US)
- Kaiser Permanente Bernard J. Tyson School of Medicine (US)
- Stanford University (US)
- San Ysidro Health (US)
- Yale School of Medicine, New Haven, Connecticut
- Apple (United States) (US)
- Microsoft (United States) (US)
- University of Pittsburgh (US)
- University of Utah (US)
- University of California San Diego (US)
- Sutter Health (US)
- Joint Commission (US)
- University of Michigan Medical School, Ann Arbor
- Health Care and Organizational Economist, Palo Alto, California
- University of Michigan (US)
- Editor in Chief, JAMA and the JAMA Network, Chicago, Illinois
- for the JAMA Summit on AI
- Corresponding author
- Angus, Derek C.
- ORCID
- Angus, Derek C.
- Khera, Rohan
- Lieu, Tracy
- Liu, Vincent
- Ahmad, Faraz S.
- Bhavani, Sivasubramanium V.
- Bindman, Andrew
- Celi, Leo Anthony
- Cohen, I. Glenn
- Denniston, Alastair
- Desai, Sanjay
- Embí, Peter
- Faisal, Aldo
- Ferryman, Kadija
- Gross, Marielle
- Johnson, Kevin
- Lee, Kristine
- Liu, Xiaoxuan
- Lomis, Kimberly
- London, Alex John
- Mandl, Kenneth D.
- McGlynn, Elizabeth
- Mello, Michelle M.
- Ouyang, David
- Perlis, Roy
- Rhew, David
- Ross, Joseph S.
- Saria, Suchi
- Schwamm, Lee
- Seymour, Christopher W.
- Shah, Nigam H.
- Shah, Rashmee
- Singh, Karandeep
- Solomon, Matthew
- Gichoya, Judy Wawira
- Weinstein, James
- Wiens, Jenna
- Bibbins-Domingo, Kirsten
- Alterovitz, Gil
- Holve, Erin C
- Kahn, Jeremy
- Pengetnze, Yolande M
- Termulo, Cesar
- Venue
- JAMA
- Publisher
- American Medical Association (AMA)
- Published
- 2025-11-11
- Volume
- 334
- Issue
- 18
- Pages
- 1650
- ISSN
- 0002-9955 (ISSN-L)
- 0098-7484
- OpenAlex
- W4415107779
- Cited by
- 195
- References
- 34
- Citations by year
- 2026: 181 · 2025: 14
- FWCI
- 46.94
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- JAMA (publishedVersion)
- PubMed (publishedVersion)
- University of Birmingham Research Portal (University of Birmingham) (submittedVersion)
- Funders
- National Heart, Lung, and Blood Institute (R01HL175626)
- Topics
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Social Sciences › Safety Research › Ethics and Social Impacts of AI
- Physical Sciences › Computer Science › Artificial Intelligence › Artificial Intelligence Applications
- Keywords
- artificial intelligence in healthcare, AI evaluation, AI regulation, multi-stakeholder engagement, AI equity, mobile health apps, diagnostic imaging, clinical decision support, AI certification, health data infrastructure, health policy incentives, FDA regulation, healthcare delivery efficiency, user training
- MeSH terms
- Artificial Intelligence, Congresses as Topic, Delivery of Health Care, Health Policy, Humans, United States, United States Food and Drug Administration, User-Computer Interface, Telemedicine, Mobile Applications
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