人工智能在管理中心线相关血流感染(CLABSI)中对患者安全和护理质量的作用。

IF 2 4区 医学 Q2 HEALTH CARE SCIENCES & SERVICES
Risk Management and Healthcare Policy Pub Date : 2025-09-03 eCollection Date: 2025-01-01 DOI:10.2147/RMHP.S520035
Ahmed Alaaeldin Saad, Abduraouf Hassan, Ahmad Alali, Fathy Alkhatib, Mohammed F Tolba, Mecit Can Emre Simsekler
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引用次数: 0

摘要

中心线相关性血流感染(CLABSI)对全球医疗保健系统构成了重大挑战,导致发病率、死亡率和医疗费用增加。随着医疗机构努力提高患者安全和护理质量,人工智能(AI)在CLABSI的预防、检测和管理方面展现了相当大的前景。本文提出了一个概念性框架,将人工智能集成到医疗系统中,将技术创新与人类工作流程、系统设计和风险管理策略相结合。通过采用系统方法,该框架支持以与医疗保健服务的复杂性相兼容的方式实施人工智能工具。本文探讨了人工智能在通过预防、早期发现和管理患者安全问题(包括CLABSI)来加强医疗保健方面的潜力和意义。它强调了人工智能应用如何预测感染风险,支持及时干预,并与标准感染控制方案协同工作,以减少CLABSI的发生率。这种综合方法旨在促进更安全、更有效和以患者为中心的护理。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

The Role of Artificial Intelligence in Managing Central Line-Associated Bloodstream Infection (CLABSI) for Patient Safety and Quality of Care.

The Role of Artificial Intelligence in Managing Central Line-Associated Bloodstream Infection (CLABSI) for Patient Safety and Quality of Care.

The Role of Artificial Intelligence in Managing Central Line-Associated Bloodstream Infection (CLABSI) for Patient Safety and Quality of Care.

The Role of Artificial Intelligence in Managing Central Line-Associated Bloodstream Infection (CLABSI) for Patient Safety and Quality of Care.

Central Line-Associated Bloodstream Infections (CLABSI) pose significant challenges in healthcare systems globally, contributing to increased morbidity, mortality, and healthcare costs. As healthcare organizations strive to improve patient safety and quality of care, Artificial Intelligence (AI) presents considerable promise in the prevention, detection, and management of CLABSI. This paper proposes a conceptual framework that integrates AI within healthcare systems, aligning technological innovations with human workflows, system design, and risk management strategies. By taking a systems approach, the framework supports the implementation of AI tools in ways that are compatible with the complexity of healthcare delivery. The paper explores the potential and significance of AI in enhancing healthcare through the prevention, early detection, and management of patient safety concerns, including CLABSI. It highlights how AI applications can predict infection risks, support timely interventions, and operate in tandem with standard infection control protocols to reduce the incidence of CLABSI. This integrated approach aims to promote safer, more efficient, and patient-centered care.

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来源期刊
Risk Management and Healthcare Policy
Risk Management and Healthcare Policy Medicine-Public Health, Environmental and Occupational Health
CiteScore
6.20
自引率
2.90%
发文量
242
审稿时长
16 weeks
期刊介绍: Risk Management and Healthcare Policy is an international, peer-reviewed, open access journal focusing on all aspects of public health, policy and preventative measures to promote good health and improve morbidity and mortality in the population. Specific topics covered in the journal include: Public and community health Policy and law Preventative and predictive healthcare Risk and hazard management Epidemiology, detection and screening Lifestyle and diet modification Vaccination and disease transmission/modification programs Health and safety and occupational health Healthcare services provision Health literacy and education Advertising and promotion of health issues Health economic evaluations and resource management Risk Management and Healthcare Policy focuses on human interventional and observational research. The journal welcomes submitted papers covering original research, clinical and epidemiological studies, reviews and evaluations, guidelines, expert opinion and commentary, and extended reports. Case reports will only be considered if they make a valuable and original contribution to the literature. The journal does not accept study protocols, animal-based or cell line-based studies.
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