Hu Mengdie, Wang Yan, Liu Yunsong, Cai Bingqing, Kong Fanjing, Zheng Qian, Zhao Dan, Gao Guanghui, Hui Zhouguang
Department of VIP Medical Services, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China.
China Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China.
Nurs Rep. 2025 Jun 3;15(6):198. doi: 10.3390/nursrep15060198.
Nursing decision-making is pivotal for patient safety and care quality. While artificial intelligence (AI) offers transformative potential in this field, a comprehensive analysis of global research trends is lacking. We conducted a bibliometric analysis of 238 publications (197 research papers, 41 reviews) from the Web of Science Core Collection (2003-2025) using CiteSpace and VOSviewer. The results reveal growing interest (7.59% annually) in the field of AI in nursing decision-making, with contributions from 54 countries/regions. The USA leads in the number of publications, followed by China and Canada, while the United Kingdom stands out in terms of citation impact. Institutions such as Columbia University and Harvard Medical School dominate in both the publication volume and citation frequency. Journal analysis shows that the top three journals in terms of publication volume in this field are , , and . Keyword analysis highlights the significant potential of natural language processing technologies, particularly those based on large language models (e.g., ChatGPT), in nursing decision-making. Furthermore, emerging trends are evident, with the sudden appearance and rapid growth of keywords such as "patient safety" and "user acceptance", indicating a shift in research focus from purely technology-driven studies to a greater emphasis on the practical impact of AI technologies on nursing systems and their clinical applications. This study delineates the current landscape and evolving trends of AI in nursing decision-making, emphasizing its progression from theoretical frameworks to clinical integration, thereby providing valuable references for future research.
护理决策对于患者安全和护理质量至关重要。虽然人工智能（AI）在该领域具有变革潜力，但缺乏对全球研究趋势的全面分析。我们使用CiteSpace和VOSviewer对来自科学网核心合集（2003 - 2025年）的238篇出版物（197篇研究论文、41篇综述）进行了文献计量分析。结果显示，护理决策中人工智能领域的关注度呈逐年增长态势（年增长率7.59%），有54个国家/地区做出了贡献。美国在出版物数量上领先，其次是中国和加拿大，而英国在引文影响力方面表现突出。哥伦比亚大学和哈佛医学院等机构在出版物数量和被引频次方面均占主导地位。期刊分析表明，该领域出版物数量排名前三的期刊分别是 、 和 。关键词分析突出了自然语言处理技术，特别是基于大语言模型（如ChatGPT）的技术在护理决策中的巨大潜力。此外，新兴趋势明显，“患者安全”和“用户接受度”等关键词突然出现并迅速增长，表明研究重点从单纯的技术驱动型研究转向更加强调人工智能技术对护理系统及其临床应用的实际影响。本研究描绘了人工智能在护理决策中的当前格局和发展趋势，强调了其从理论框架到临床整合的进展，从而为未来研究提供了有价值的参考。
