Katebi Maryam, Bahreini Masoud, Bagherzadeh Razieh, Pouladi Shahnaz
Department of Nursing, School of Nursing and Midwifery, Bushehr University of Medical Sciences, Bushehr, Bushehr Province, Iran.
Department of Midwifery, School of Nursing and Midwifery, Bushehr University of Medical Sciences, Bushehr, Bushehr Province, Iran.
J Nurs Manag. 2025 Jul 30;2025:2797535. doi: 10.1155/jonm/2797535. eCollection 2025.
The increasing complexity of healthcare necessitates exploring emerging technologies to enhance nursing management. Artificial Intelligence (AI) has shown significant potential in optimizing decision making, improving workflow efficiency, and enhancing resource allocation within nursing leadership. However, its implementation presents both opportunities and challenges, requiring a thorough understanding of its impact on managerial processes. This scoping review aims to map the existing literature on AI applications in nursing management, identifying key benefits, limitations, ethical considerations, and future directions for AI integration in nursing management. A scoping review methodology was employed, following the framework of Arksey and O'Malley (2005), refined by Levac et al. (2010), and adhering to the PRISMA-ScR guidelines. A systematic search of English and Persian databases, including PubMed, Web of Science, ProQuest, ScienceDirect, SID, and IranDoc, was conducted for studies published between 2013 and 2024. Thematic analysis was used to categorize findings across major domains of AI in nursing management. Twelve studies were included, featuring diverse methodologies and geographic locations. The key themes identified encompass the applications of AI in nursing management, where AI is utilized for data-driven decision making, workflow automation, staffing optimization, and patient monitoring. Challenges in AI implementation-Key concerns include data privacy, algorithmic bias, staff resistance, and limitations in interoperability. Potential benefits-AI contributes to greater efficiency, alleviates workload, and enhances predictive analytics for patient care. Ethical and practical considerations-There is a necessity for strong regulatory frameworks, training programs, and strategies to ensure the responsible integration of AI. AI presents promising opportunities for nursing management, but its implementation requires careful consideration, including comprehensive training, ethical oversight, and organizational adaptation. Future research should investigate long-term implications, managerial intelligence, and workforce dynamics to enhance AI integration in nursing leadership.
医疗保健的日益复杂性使得探索新兴技术以加强护理管理成为必要。人工智能（AI）在优化决策、提高工作流程效率以及改善护理领导中的资源分配方面已显示出巨大潜力。然而，其实施既带来了机遇也带来了挑战，需要全面了解其对管理流程的影响。本范围综述旨在梳理有关人工智能在护理管理中应用的现有文献，确定人工智能集成在护理管理中的关键益处、局限性、伦理考量及未来方向。采用了范围综述方法，遵循Arksey和O'Malley（2005年）的框架，并经Levac等人（2010年）完善，同时遵循PRISMA - ScR指南。对2013年至2024年期间发表的研究进行了系统检索，检索了包括PubMed、科学网、ProQuest、ScienceDirect、SID和IranDoc在内的英文和波斯文数据库。采用主题分析法对护理管理中人工智能主要领域的研究结果进行分类。纳入了12项研究，这些研究具有不同的方法和地理位置。确定的关键主题包括人工智能在护理管理中的应用，其中人工智能用于数据驱动的决策、工作流程自动化、人员配置优化和患者监测。人工智能实施中的挑战——主要关注点包括数据隐私、算法偏差、员工抵触以及互操作性限制。潜在益处——人工智能有助于提高效率、减轻工作量并增强对患者护理的预测分析。伦理和实际考量——需要强大的监管框架、培训计划和策略，以确保人工智能的负责任集成。人工智能为护理管理带来了有前景的机遇，但其实施需要仔细考虑，包括全面培训、伦理监督和组织适应。未来研究应调查长期影响、管理智能和劳动力动态，以加强人工智能在护理领导中的集成。
