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Open Access 12-11-2024 | Artificial Intelligence in Healthcare | Position Papers

Recommendations for Clinicians, Technologists, and Healthcare Organizations on the Use of Generative Artificial Intelligence in Medicine: A Position Statement from the Society of General Internal Medicine

Authors: Byron Crowe, MD, Shreya Shah, MD, Derek Teng, MD, Stephen P. Ma, MD PhD, Matthew DeCamp, MD PhD, Eric I. Rosenberg, MD, MSPH, Jorge A. Rodriguez, MD, Benjamin X. Collins, MD MS MA, Kathryn Huber, MD MS, Kyle Karches, MD PhD, Shana Zucker, MD MPH MS, Eun Ji Kim, MD MS MS, Lisa Rotenstein, MD MBA, Adam Rodman, MD MPH, Danielle Jones, MD, Ilana B. Richman, MD, MHS, Tracey L. Henry, MD, MPH, MS, Diane Somlo, MD MBA, Samantha I. Pitts, MD MPH, Jonathan H. Chen, MD PhD, Rebecca G. Mishuris, MD MS MPH

Published in: Journal of General Internal Medicine

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Abstract

Generative artificial intelligence (generative AI) is a new technology with potentially broad applications across important domains of healthcare, but serious questions remain about how to balance the promise of generative AI against unintended consequences from adoption of these tools. In this position statement, we provide recommendations on behalf of the Society of General Internal Medicine on how clinicians, technologists, and healthcare organizations can approach the use of these tools. We focus on three major domains of medical practice where clinicians and technology experts believe generative AI will have substantial immediate and long-term impacts: clinical decision-making, health systems optimization, and the patient-physician relationship. Additionally, we highlight our most important generative AI ethics and equity considerations for these stakeholders. For clinicians, we recommend approaching generative AI similarly to other important biomedical advancements, critically appraising its evidence and utility and incorporating it thoughtfully into practice. For technologists developing generative AI for healthcare applications, we recommend a major frameshift in thinking away from the expectation that clinicians will “supervise” generative AI. Rather, these organizations and individuals should hold themselves and their technologies to the same set of high standards expected of the clinical workforce and strive to design high-performing, well-studied tools that improve care and foster the therapeutic relationship, not simply those that improve efficiency or market share. We further recommend deep and ongoing partnerships with clinicians and patients as necessary collaborators in this work. And for healthcare organizations, we recommend pursuing a combination of both incremental and transformative change with generative AI, directing resources toward both endeavors, and avoiding the urge to rapidly displace the human clinical workforce with generative AI. We affirm that the practice of medicine remains a fundamentally human endeavor which should be enhanced by technology, not displaced by it.
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Metadata
Title
Recommendations for Clinicians, Technologists, and Healthcare Organizations on the Use of Generative Artificial Intelligence in Medicine: A Position Statement from the Society of General Internal Medicine
Authors
Byron Crowe, MD
Shreya Shah, MD
Derek Teng, MD
Stephen P. Ma, MD PhD
Matthew DeCamp, MD PhD
Eric I. Rosenberg, MD, MSPH
Jorge A. Rodriguez, MD
Benjamin X. Collins, MD MS MA
Kathryn Huber, MD MS
Kyle Karches, MD PhD
Shana Zucker, MD MPH MS
Eun Ji Kim, MD MS MS
Lisa Rotenstein, MD MBA
Adam Rodman, MD MPH
Danielle Jones, MD
Ilana B. Richman, MD, MHS
Tracey L. Henry, MD, MPH, MS
Diane Somlo, MD MBA
Samantha I. Pitts, MD MPH
Jonathan H. Chen, MD PhD
Rebecca G. Mishuris, MD MS MPH
Publication date
12-11-2024

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