{"title":"人工智能在医疗保健中的应用:系统回顾其对护理实践和患者预后的影响。","authors":"Sahar A Abdelmohsen, Mohammed Musaed Al-Jabri","doi":"10.1111/jnu.70040","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>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.</p><p><strong>Aims: </strong>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.</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>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.</p><p><strong>Conclusion: </strong>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.</p><p><strong>Clinical relevance: </strong>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.</p>","PeriodicalId":51091,"journal":{"name":"Journal of Nursing Scholarship","volume":" ","pages":""},"PeriodicalIF":2.9000,"publicationDate":"2025-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Artificial Intelligence Applications in Healthcare: A Systematic Review of Their Impact on Nursing Practice and Patient Outcomes.\",\"authors\":\"Sahar A Abdelmohsen, Mohammed Musaed Al-Jabri\",\"doi\":\"10.1111/jnu.70040\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>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.</p><p><strong>Aims: </strong>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.</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>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.</p><p><strong>Conclusion: </strong>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.</p><p><strong>Clinical relevance: </strong>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.</p>\",\"PeriodicalId\":51091,\"journal\":{\"name\":\"Journal of Nursing Scholarship\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":2.9000,\"publicationDate\":\"2025-08-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Nursing Scholarship\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1111/jnu.70040\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"NURSING\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Nursing Scholarship","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1111/jnu.70040","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"NURSING","Score":null,"Total":0}
引用次数: 0
摘要
背景:人工智能正在通过解决复杂的挑战和加强患者护理来彻底改变医疗保健。人工智能技术,如机器学习、自然语言处理和预测分析,为影响护理实践和患者结果提供了巨大的潜力。目的:本系统综述旨在评估人工智能在医疗保健中的应用对护理实践和患者预后的影响。目的是评估这些技术在提高护理效率和病人护理方面的有效性,并确定需要进一步研究的领域。方法:本综述于2024年8月按照PRISMA指南进行。我们检索了PubMed、b谷歌SCHOLAR和Web of Science,查找截止到2024年8月发表的研究。入选标准为以英文发表的人工智能在护理和医疗保健实践中的原创性研究。一个两阶段的筛选过程被用来选择相关的研究,然后分析其对护理实践和患者结果的影响。结果:上述数据库共纳入5975项研究,符合纳入标准。研究结果表明,包括机器学习、机器人过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、患者管理和运营效率。机器学习增强了疾病检测,减少了护士的管理任务,NLP提高了文档的准确性,物理机器人提高了患者的安全性和舒适度。确定的挑战包括数据隐私问题、集成到现有工作流和方法可变性。结论:人工智能技术大大改善了护理实践和患者预后。解决与数据隐私和集成相关的挑战,以及标准化方法,对于优化人工智能在医疗保健领域的潜力至关重要。需要进一步的研究来探索人工智能在这一领域的长期影响、成本效益和伦理影响。临床相关性:人工智能(AI)正在通过加强护理实践和改善患者预后来彻底改变医疗保健。临床决策支持系统(CDSS)、预测分析、机器人流程自动化(RPA)和远程监控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。人工智能可以增强决策,提高效率,促进个性化护理,同时有助于早期发现和实时数据分析。它还通过最大限度地减少错误和实现远程会诊,有助于改善护士教育和患者安全。然而,要成功地将人工智能集成到医疗保健中,必须解决与培训、道德考虑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。
Artificial Intelligence Applications in Healthcare: A Systematic Review of Their Impact on Nursing Practice and Patient Outcomes.
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.
期刊介绍:
This widely read and respected journal features peer-reviewed, thought-provoking articles representing research by some of the world’s leading nurse researchers.
Reaching health professionals, faculty and students in 103 countries, the Journal of Nursing Scholarship is focused on health of people throughout the world. It is the official journal of Sigma Theta Tau International and it reflects the society’s dedication to providing the tools necessary to improve nursing care around the world.