Author Affiliations: University of Texas Health Science Center-McWilliams School of Biomedical Informatics, Houston (Drs Ross, Zhi, Rasmy); and Microsoft, Redmond, Washington (Dr McGrow).
Comput Inform Nurs. 2024 May 1;42(5):377-387. doi: 10.1097/CIN.0000000000001149.
We are in a booming era of artificial intelligence, particularly with the increased availability of technologies that can help generate content, such as ChatGPT. Healthcare institutions are discussing or have started utilizing these innovative technologies within their workflow. Major electronic health record vendors have begun to leverage large language models to process and analyze vast amounts of clinical natural language text, performing a wide range of tasks in healthcare settings to help alleviate clinicians' burden. Although such technologies can be helpful in applications such as patient education, drafting responses to patient questions and emails, medical record summarization, and medical research facilitation, there are concerns about the tools' readiness for use within the healthcare domain and acceptance by the current workforce. The goal of this article is to provide nurses with an understanding of the currently available foundation models and artificial intelligence tools, enabling them to evaluate the need for such tools and assess how they can impact current clinical practice. This will help nurses efficiently assess, implement, and evaluate these tools to ensure these technologies are ethically and effectively integrated into healthcare systems, while also rigorously monitoring their performance and impact on patient care.
我们正处在人工智能蓬勃发展的时代,尤其是在能够帮助生成内容的技术(如 ChatGPT)日益普及的情况下。医疗机构正在讨论或已经开始在其工作流程中利用这些创新技术。主要的电子健康记录供应商已经开始利用大型语言模型来处理和分析大量的临床自然语言文本,在医疗保健环境中执行各种任务,以帮助减轻临床医生的负担。尽管这些技术在患者教育、起草对患者问题和电子邮件的回复、医疗记录摘要以及医学研究促进等应用中可能会有所帮助,但人们对这些工具在医疗领域的使用准备情况和当前劳动力的接受程度存在担忧。本文的目的是为护士提供对现有基础模型和人工智能工具的理解,使他们能够评估对这些工具的需求,并评估它们如何影响当前的临床实践。这将有助于护士高效地评估、实施和评估这些工具,以确保这些技术在医疗保健系统中得到合乎道德且有效的整合,同时严格监测它们对患者护理的性能和影响。