Ng Zi Qi Pamela, Ling Li Ying Janice, Chew Han Shi Jocelyn, Lau Ying
Alice Lee Centre for Nursing Studies, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore.
J Nurs Manag. 2022 Nov;30(8):3654-3674. doi: 10.1111/jonm.13425. Epub 2021 Aug 13.
To present an overview of how artificial intelligence has been used to improve clinical nursing care.
Artificial intelligence has been reshaping the healthcare industry but little is known about its applicability in enhancing nursing care.
A scoping review was conducted. Seven electronic databases (CINAHL, Cochrane Library, EMBASE, IEEE Xplore, PubMed, Scopus, and Web of Science) were searched from 1 January 2010 till 20 December 2020. Grey literature and reference lists of included articles were also searched.
Thirty-seven studies encapsulating the use of artificial intelligence in improving clinical nursing care were included in this review. Six use cases were identified - documentation, formulating nursing diagnoses, formulating nursing care plans, patient monitoring, patient care prediction such as falls prediction (most common) and wound management. Various techniques of machine learning and classification were used for predictive analyses and to improve nurses' preparedness and management of patients' conditions CONCLUSION: This review highlighted the potential of artificial intelligence in improving the quality of nursing care. However, more randomized controlled trials in real-life healthcare settings should be conducted to enhance the rigor of evidence.
Education in the application of artificial intelligence should be promoted to empower nurses to lead technological transformations and not passively trail behind others.
概述人工智能如何被用于改善临床护理。
人工智能一直在重塑医疗行业,但对于其在加强护理方面的适用性却知之甚少。
进行了一项范围综述。检索了7个电子数据库(CINAHL、Cochrane图书馆、EMBASE、IEEE Xplore、PubMed、Scopus和科学网),检索时间为2010年1月1日至2020年12月20日。还检索了灰色文献和纳入文章的参考文献列表。
本综述纳入了37项关于人工智能在改善临床护理方面应用的研究。确定了6个用例——记录、制定护理诊断、制定护理计划、患者监测、患者护理预测(如跌倒预测(最常见))和伤口管理。使用了各种机器学习和分类技术进行预测分析,并改善护士对患者病情的准备和管理。
本综述强调了人工智能在提高护理质量方面的潜力。然而,应该在现实医疗环境中进行更多随机对照试验,以提高证据的严谨性。
应推广人工智能应用方面的教育,使护士有能力引领技术变革,而不是被动地追随他人。