Department of Health Informatics, College of Health Sciences, Saudi Electronic University, Dammam, Saudi Arabia.
Department of Health Informatics, College of Health Sciences, Saudi Electronic University, 11673, Riyadh, Saudi Arabia.
J Med Syst. 2024 Aug 12;48(1):74. doi: 10.1007/s10916-024-02098-4.
This review aims to assess the effectiveness of AI-driven CDSSs on patient outcomes and clinical practices. A comprehensive search was conducted across PubMed, MEDLINE, and Scopus. Studies published from January 2018 to November 2023 were eligible for inclusion. Following title and abstract screening, full-text articles were assessed for methodological quality and adherence to inclusion criteria. Data extraction focused on study design, AI technologies employed, reported outcomes, and evidence of AI-CDSS impact on patient and clinical outcomes. Thematic analysis was conducted to synthesise findings and identify key themes regarding the effectiveness of AI-CDSS. The screening of the articles resulted in the selection of 26 articles that satisfied the inclusion criteria. The content analysis revealed four themes: early detection and disease diagnosis, enhanced decision-making, medication errors, and clinicians' perspectives. AI-based CDSSs were found to improve clinical decision-making by providing patient-specific information and evidence-based recommendations. Using AI in CDSSs can potentially improve patient outcomes by enhancing diagnostic accuracy, optimising treatment selection, and reducing medical errors.
本次综述旨在评估人工智能驱动的临床决策支持系统(CDSS)对患者结局和临床实践的影响。我们在 PubMed、MEDLINE 和 Scopus 上进行了全面检索。符合纳入标准的研究为 2018 年 1 月至 2023 年 11 月期间发表的研究。经过标题和摘要筛选后,对全文文章进行了方法学质量评估和纳入标准的评估。数据提取重点关注研究设计、所使用的人工智能技术、报告的结果,以及人工智能-CDSS 对患者和临床结局影响的证据。我们采用主题分析法来综合研究结果并确定关于人工智能-CDSS 有效性的关键主题。文章筛选后共选择了 26 篇符合纳入标准的文章。内容分析揭示了四个主题:早期检测和疾病诊断、增强决策制定、药物错误以及临床医生的观点。基于人工智能的 CDSS 可以通过提供患者特定信息和基于证据的建议来改善临床决策。在 CDSS 中使用人工智能有可能通过提高诊断准确性、优化治疗选择和减少医疗错误来改善患者结局。