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人工智能在医疗保健中的应用:对护理实践和患者结局影响的系统评价

Artificial Intelligence Applications in Healthcare: A Systematic Review of Their Impact on Nursing Practice and Patient Outcomes.

作者信息

Abdelmohsen Sahar A, Al-Jabri Mohammed Musaed

机构信息

Department of Nursing Sciences, College of Applied Medical Sciences in Wadi Aldawaser, Prince Sattam bin Abdul-Aziz University, Wadi Aldawaser, Saudi Arabia.

Adult Nursing Department, Faculty of Nursing, Professor of Medical Surgical Nursing- Adult Nursing Department, Faculty of Nursing, Assiut University, Asyut, Egypt.

出版信息

J Nurs Scholarsh. 2025 Aug 20. doi: 10.1111/jnu.70040.

Abstract

BACKGROUND

Artificial Intelligence is revolutionizing healthcare by addressing complex challenges and enhancing patient care. AI technologies, such as machine learning, natural language processing, and predictive analytics, offer significant potential to impact nursing practice and patient outcomes.

AIMS

This systematic review aims to assess the impact of Artificial Intelligence applications in healthcare on nursing practice and patient outcomes. The goal is to evaluate the effectiveness of these technologies in improving nursing efficiency and patient care and to identify areas requiring further research.

METHODS

This review, conducted in August 2024, followed PRISMA guidelines. We searched PubMed, GOOGLE SCHOLAR, and Web of Science for studies published up to August 2024. The inclusion criteria were original research on AI in nursing and healthcare practice published in English. A two-stage screening process was used to select relevant studies, which were then analyzed for their impact on nursing practice and patient outcomes.

RESULTS

A total of 5975 studies were surveyed from the previously mentioned databases, which met the inclusion criteria. Findings show that AI applications, including machine learning, robotic process automation, and natural language processing, have improved diagnostic accuracy, patient management, and operational efficiency. Machine learning enhanced disease detection, reduced administrative tasks for nurses, NLP improved documentation accuracy, and physical robots increased patient safety and comfort. Challenges identified include data privacy concerns, integration into existing workflows, and methodological variability.

CONCLUSION

AI technologies have substantially improved nursing practice and patient outcomes. Addressing challenges related to data privacy and integration, as well as standardizing methodologies, is essential for optimizing AI's potential in healthcare. Further research is needed to explore the long-term impacts, cost-effectiveness, and ethical implications of Artificial Intelligence in this field.

CLINICAL RELEVANCE

Artificial Intelligence (AI) is revolutionizing healthcare by enhancing nursing practices and improving patient outcomes. Tools such as Clinical Decision Support Systems (CDSS), predictive analytics, robotic process automation (RPA), and remote monitoring empower nurses to make informed decisions, optimize workflows, and monitor patients more effectively. AI enhances decision-making, boosts efficiency, and facilitates personalized care, while aiding in early detection and real-time data analysis. It also contributes to better nurse education and patient safety by minimizing errors and enabling remote consultations. However, for AI to be successfully integrated into healthcare, it is essential to tackle challenges related to training, ethical considerations, and data privacy to guarantee its effective implementation and positive impact on the quality and safety of healthcare.

摘要

背景

人工智能正在通过应对复杂挑战和改善患者护理来彻底改变医疗保健行业。机器学习、自然语言处理和预测分析等人工智能技术在影响护理实践和患者结局方面具有巨大潜力。

目的

本系统评价旨在评估医疗保健领域中人工智能应用对护理实践和患者结局的影响。目标是评估这些技术在提高护理效率和患者护理方面的有效性,并确定需要进一步研究的领域。

方法

本评价于2024年8月进行,遵循PRISMA指南。我们在PubMed、谷歌学术和科学网中搜索截至2024年8月发表的研究。纳入标准是用英文发表的关于人工智能在护理和医疗保健实践中的原始研究。采用两阶段筛选过程来选择相关研究,然后分析这些研究对护理实践和患者结局的影响。

结果

从上述数据库中总共检索到5975项符合纳入标准的研究。研究结果表明,包括机器学习、机器人流程自动化和自然语言处理在内的人工智能应用提高了诊断准确性、患者管理水平和运营效率。机器学习增强了疾病检测能力,减少了护士的行政任务,自然语言处理提高了文档记录的准确性,物理机器人提高了患者的安全性和舒适度。发现的挑战包括数据隐私问题、融入现有工作流程以及方法的变异性。

结论

人工智能技术极大地改善了护理实践和患者结局。解决与数据隐私和整合相关的挑战,以及规范方法,对于优化人工智能在医疗保健领域的潜力至关重要。需要进一步研究来探索人工智能在该领域的长期影响、成本效益和伦理意义。

临床意义

人工智能正在通过改善护理实践和提高患者结局来彻底改变医疗保健行业。临床决策支持系统(CDSS)、预测分析、机器人流程自动化(RPA)和远程监测等工具使护士能够做出明智的决策、优化工作流程并更有效地监测患者。人工智能增强了决策能力,提高了效率,促进了个性化护理,同时有助于早期检测和实时数据分析。它还通过最大限度地减少错误并实现远程咨询,有助于更好的护士教育和患者安全。然而,为了使人工智能成功融入医疗保健领域,必须应对与培训、伦理考量和数据隐私相关的挑战,以确保其有效实施并对医疗保健的质量和安全产生积极影响。

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