Prospects for AI clinical summarization to reduce the burden of patient chart review

Autor: Chanseo Lee, Kimon A. Vogt, Sonu Kumar
Jazyk: angličtina
Rok vydání: 2024
Předmět:
Zdroj: Frontiers in Digital Health, Vol 6 (2024)
Druh dokumentu: article
ISSN: 2673-253X
DOI: 10.3389/fdgth.2024.1475092
Popis: Effective summarization of unstructured patient data in electronic health records (EHRs) is crucial for accurate diagnosis and efficient patient care, yet clinicians often struggle with information overload and time constraints. This review dives into recent literature and case studies on both the significant impacts and outstanding issues of patient chart review on communications, diagnostics, and management. It also discusses recent efforts to integrate artificial intelligence (AI) into clinical summarization tasks, and its transformative impact on the clinician’s potential, including but not limited to reductions of administrative burden and improved patient-centered care. Furthermore, it takes into account the numerous ethical challenges associated with integrating AI into clinical workflow, including biases, data privacy, and cybersecurity.
Databáze: Directory of Open Access Journals