人工智能在医疗保健领域的书写:平衡变革潜力与负责任的整合。

IF 3.8 3区 医学 Q2 MEDICAL INFORMATICS
Tiffany I Leung, Andrew J Coristine, Arriel Benis
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引用次数: 0

摘要

未标记:临床文件的行政负担有助于卫生保健从业者倦怠和转移宝贵的时间远离直接病人护理。环境人工智能(AI)抄写员——也被称为“数字抄写员”或“AI抄写员”——正在成为一种有前途的解决方案,因为它们具有自动化临床记录生成和减少临床医生工作量的潜力,而那些专门建立在大型语言模型(LLM)上的技术正在成为促进实时临床文档任务的技术。这种潜在的变革性发展基于长期存在的基于人工智能的转录软件,该软件使用自动语音识别和/或自然语言处理。最近的研究强调了环境人工智能抄写器对临床医生健康、工作流程效率、文档质量、用户体验和患者互动的潜在影响。到目前为止,有限的证据表明,环境人工智能抄写员与减少临床医生的职业倦怠、降低认知任务负荷以及节省大量记录时间有关,特别是在下班后的电子健康记录(EHR)工作中。一个持续报道的好处是医患互动的改善,因为医生在临床接触中感觉更在场。然而,这些好处被人工智能生成笔记的准确性、一致性、语言使用和风格等问题所抵消。研究注意到错误,遗漏,或幻觉提醒勤勉的临床医生的监督是必要的。用户体验也是异构的,其好处因专业和个人工作流而异。此外,人们还担心伦理和法律问题、算法偏见、过度依赖人工智能可能带来的长期“认知债务”,甚至可能丧失医生的自主权。其他的实际问题包括安全性、隐私性、集成、互操作性、用户接受度和培训,以及大规模采用的成本效益。最后,有限的研究描述了非医师临床医生和卫生专业人员对这些技术的采用或评估。尽管环境人工智能抄写器和人工智能驱动的文档技术有望成为改变实践的潜在工具,但仍存在许多问题。关键问题仍然存在,包括负责任的部署,目标是确保环境人工智能记录员生成临床文件,以支持更高效、公平和以患者为中心的护理。为了促进我们的集体理解和解决关键问题,JMIR医学信息学正在为“环境人工智能Scribes和人工智能驱动的文档技术”的新部分发起论文征集。作为编辑,我们期待有机会通过在JMIR医学信息学的这个新部分发表高质量和严谨的学术工作来推进科学和对这些领域的理解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

AI Scribes in Health Care: Balancing Transformative Potential With Responsible Integration.

AI Scribes in Health Care: Balancing Transformative Potential With Responsible Integration.

Unlabelled: The administrative burden of clinical documentation contributes to health care practitioner burnout and diverts valuable time away from direct patient care. Ambient artificial intelligence (AI) scribes-also called "digital scribes" or "AI scribes"-are emerging as a promising solution, given their potential to automate clinical note generation and reduce clinician workload, and those specifically built on a large language model (LLM) are emerging as technologies for facilitating real-time clinical documentation tasks. This potentially transformative development has a foundation on longer-standing, AI-based transcription software, which uses automated speech recognition and/or natural language processing. Recent studies have highlighted the potential impact of ambient AI scribes on clinician well-being, workflow efficiency, documentation quality, user experience, and patient interaction. So far, limited evidence indicates that ambient AI scribes are associated with reduced clinician burnout, lower cognitive task load, and significant time savings in documentation, particularly in after-hours electronic health record (EHR) work. One consistently reported benefit is the improvement in the patient-physician interaction, as physicians feel more present during a clinical encounter. However, these benefits are counterbalanced by persisting concerns regarding the accuracy, consistency, language use, and style of AI-generated notes. Studies noting errors, omissions, or hallucinations caution that diligent clinician oversight is necessary. The user experience is also heterogeneous, with benefits varying by specialty and individual workflow. Further, there are concerns about ethical and legal issues, algorithmic bias, the potential for long-term "cognitive debt" from overreliance on AI, and even the potential loss of physician autonomy. Additional pragmatic concerns include security, privacy, integration, interoperability, user acceptance and training, and the cost-effectiveness of adoption at scale. Finally, limited studies describe adoption or evaluation of these technologies by nonphysician clinicians and health professionals. Although ambient AI scribes and AI-driven documentation technologies are promising as potentially practice-changing tools, there are many questions remaining. Key issues persist, including responsible deployment with the goal of ensuring that ambient AI scribes produce clinical documentation that supports more efficient, equitable, and patient-centered care. To advance our collective understanding and address key issues, JMIR Medical Informatics is launching a call for papers for a new section on "Ambient AI Scribes and AI-Driven Documentation Technologies." As editors, we look forward to the opportunity to advance the science and understanding of these fields through publishing high-quality and rigorous scholarly work in this new section of JMIR Medical Informatics.

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来源期刊
JMIR Medical Informatics
JMIR Medical Informatics Medicine-Health Informatics
CiteScore
7.90
自引率
3.10%
发文量
173
审稿时长
12 weeks
期刊介绍: JMIR Medical Informatics (JMI, ISSN 2291-9694) is a top-rated, tier A journal which focuses on clinical informatics, big data in health and health care, decision support for health professionals, electronic health records, ehealth infrastructures and implementation. It has a focus on applied, translational research, with a broad readership including clinicians, CIOs, engineers, industry and health informatics professionals. Published by JMIR Publications, publisher of the Journal of Medical Internet Research (JMIR), the leading eHealth/mHealth journal (Impact Factor 2016: 5.175), JMIR Med Inform has a slightly different scope (emphasizing more on applications for clinicians and health professionals rather than consumers/citizens, which is the focus of JMIR), publishes even faster, and also allows papers which are more technical or more formative than what would be published in the Journal of Medical Internet Research.
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