Effectiveness of Artificial Intelligence (AI) in Clinical Decision Support Systems and Care Delivery

• Published in: Journal of medical systems Vol. 48; no. 1; p. 74
• Main Authors: Ouanes, Khaled, Farhah, Nesren
• Format: Journal Article
• Language: English
• Published: New York Springer US 12-08-2024; Springer Nature B.V
• Subjects: Artificial Intelligence; Clinical Decision-Making - methods; Clinical outcomes; Content analysis; Criteria; Decision making; Decision support systems; Decision Support Systems, Clinical - organization & administration; Delivery of Health Care - organization & administration; Early Diagnosis; Error reduction; Health Informatics; Health Sciences; Humans; Impact analysis; Medicine; Medicine & Public Health; Patients; Review; Statistics for Life Sciences; System effectiveness; Deep learning; Clinical decision support systems; Neural networks; Artificial intelligence; Machine learning
• ISSN: 1573-689X; 0148-5598; 1573-689X
• 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.