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

IF 3.2 Q1 HEALTH CARE SCIENCES & SERVICES Frontiers in digital health Pub Date : 2024-11-07 eCollection Date: 2024-01-01 DOI:10.3389/fdgth.2024.1475092
Chanseo Lee, Kimon A Vogt, Sonu Kumar
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引用次数: 0

Abstract

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.

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人工智能临床总结减轻病历审查负担的前景。
有效总结电子健康记录(EHR)中的非结构化患者数据对于准确诊断和高效护理患者至关重要,但临床医生往往要面对信息超载和时间紧迫的问题。本综述深入探讨了病历审查对沟通、诊断和管理的重大影响和未决问题的最新文献和案例研究。它还讨论了最近将人工智能(AI)整合到临床总结任务中的努力,及其对临床医生潜力的变革性影响,包括但不限于减轻管理负担和改善以患者为中心的护理。此外,它还考虑到了与将人工智能融入临床工作流程相关的众多伦理挑战,包括偏见、数据隐私和网络安全。
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来源期刊
CiteScore
4.20
自引率
0.00%
发文量
0
审稿时长
13 weeks
期刊最新文献
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