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.

IF 4.3 2区 医学 Q1 HEALTH CARE SCIENCES & SERVICES Journal of General Internal Medicine Pub Date : 2024-11-12 DOI:10.1007/s11606-024-09102-0
Byron Crowe, Shreya Shah, Derek Teng, Stephen P Ma, Matthew DeCamp, Eric I Rosenberg, Jorge A Rodriguez, Benjamin X Collins, Kathryn Huber, Kyle Karches, Shana Zucker, Eun Ji Kim, Lisa Rotenstein, Adam Rodman, Danielle Jones, Ilana B Richman, Tracey L Henry, Diane Somlo, Samantha I Pitts, Jonathan H Chen, Rebecca G Mishuris
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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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对临床医生、技术人员和医疗机构在医学中使用生成式人工智能的建议:普通内科学会的立场声明》。
生成式人工智能(Generative AI)是一项新技术,可能会在医疗保健的重要领域得到广泛应用,但如何平衡生成式人工智能的前景与采用这些工具所带来的意外后果之间的关系,仍然存在严重问题。在本立场声明中,我们代表全科内科学会就临床医生、技术人员和医疗机构如何使用这些工具提出了建议。我们重点关注医疗实践中的三大领域,临床医生和技术专家认为在这些领域中,生成式人工智能将产生巨大的直接和长期影响:临床决策、医疗系统优化和医患关系。此外,我们还强调了对这些利益相关者来说最重要的生成式人工智能伦理和公平考虑因素。对于临床医生,我们建议他们像对待其他重要的生物医学进步一样对待生成式人工智能,严格评估其证据和效用,并深思熟虑地将其融入实践中。对于为医疗保健应用开发创生型人工智能的技术人员,我们建议转变思维框架,不再期望临床医生 "监督 "创生型人工智能。相反,这些组织和个人应该以对临床工作者的同样高标准来要求自己和他们的技术,并努力设计出高性能、经过充分研究的工具,以改善护理和促进治疗关系,而不仅仅是那些提高效率或市场份额的工具。我们还建议与临床医生和患者建立深入、持续的合作关系,他们是这项工作中必要的合作者。对于医疗机构来说,我们建议将人工智能的渐进式变革和变革性变革结合起来,将资源用于这两方面的努力,避免急于用人工智能迅速取代人类临床劳动力。我们申明,医疗实践从根本上说仍然是人类的努力,它应该通过技术得到提升,而不是被技术所取代。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Journal of General Internal Medicine
Journal of General Internal Medicine 医学-医学:内科
CiteScore
7.70
自引率
5.30%
发文量
749
审稿时长
3-6 weeks
期刊介绍: The Journal of General Internal Medicine is the official journal of the Society of General Internal Medicine. It promotes improved patient care, research, and education in primary care, general internal medicine, and hospital medicine. Its articles focus on topics such as clinical medicine, epidemiology, prevention, health care delivery, curriculum development, and numerous other non-traditional themes, in addition to classic clinical research on problems in internal medicine.
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