Mohammed Sobhia Ahmed Abdel Qader, Osman Yasmine Mahmoud Moussa, Ibrahim Ateya Megahed, Shaban Mostafa
King Khalid University, Abha, Kingdom of Saudi Arabia.
Hiroshima University, Hiroshima, Japan.
Int Nurs Rev. 2025 Mar;72(1):e70010. doi: 10.1111/inr.70010.
This study systematically explores the ethical and regulatory considerations surrounding the integration of artificial intelligence (AI) and machine learning (ML) in nursing practice, with a focus on patient autonomy, data privacy, algorithmic bias, and accountability.
AI and ML are transforming nursing practice by enhancing clinical decision-making and operational efficiency. However, these technologies present significant ethical challenges related to ensuring patient autonomy, safeguarding data privacy, mitigating algorithmic bias, and ensuring transparency in decision-making processes. Current frameworks are not sufficiently tailored to nursing-specific contexts.
A systematic review was conducted, adhering to PRISMA guidelines. Six major databases were searched for studies published between 2000 and 2024. Seventeen studies met the inclusion criteria and were included in the final analysis.
Five key themes emerged from the review: enhancement of clinical decision-making, promotion of ethical awareness, support for routine nursing tasks, challenges in algorithmic bias, and the importance of public engagement in regulatory frameworks. The review identified critical gaps in nursing-specific ethical guidelines and regulatory oversight for AI integration in practice.
AI technologies offer substantial benefits for nursing, particularly in decision-making and task efficiency. However, these advantages must be balanced against ethical concerns, including the protection of patient rights, algorithmic transparency, and bias mitigation. Current regulatory frameworks require adaptation to meet the ethical needs of nursing.
The findings emphasize the need for the development of nursing-specific ethical guidelines and robust regulatory frameworks to ensure the responsible integration of AI technologies into nursing practice. AI integration must uphold ethical principles while enhancing the quality of care.
本研究系统地探讨了人工智能（AI）和机器学习（ML）融入护理实践所涉及的伦理和监管考量，重点关注患者自主权、数据隐私、算法偏差和问责制。
人工智能和机器学习正在通过提高临床决策能力和运营效率来改变护理实践。然而，这些技术在确保患者自主权、保护数据隐私、减轻算法偏差以及确保决策过程透明方面带来了重大的伦理挑战。当前的框架并未充分针对护理的特定背景进行调整。
遵循PRISMA指南进行了系统综述。在六个主要数据库中搜索了2000年至2024年发表的研究。十七项研究符合纳入标准并被纳入最终分析。
综述中出现了五个关键主题：临床决策的增强、伦理意识的提升、日常护理任务的支持、算法偏差方面的挑战以及公众参与监管框架的重要性。该综述确定了在护理特定伦理指南和人工智能融入实践的监管监督方面的关键差距。
人工智能技术为护理带来了巨大益处，特别是在决策和任务效率方面。然而，这些优势必须与伦理问题相平衡，包括保护患者权利、算法透明度和偏差缓解。当前的监管框架需要进行调整以满足护理的伦理需求。
研究结果强调需要制定针对护理的伦理指南和强大的监管框架，以确保人工智能技术负责任地融入护理实践。人工智能的融入必须在坚持伦理原则的同时提高护理质量。
