Prospects for AI clinical summarization to reduce the burden of patient chart review
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 s...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2024-11-01
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| Series: | Frontiers in Digital Health |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fdgth.2024.1475092/full |
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| _version_ | 1850199197060431872 |
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| author | Chanseo Lee Kimon A. Vogt Sonu Kumar |
| author_facet | Chanseo Lee Kimon A. Vogt Sonu Kumar |
| author_sort | Chanseo Lee |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-e1f12764d238423b8ba4584099f359e1 |
| institution | OA Journals |
| issn | 2673-253X |
| language | English |
| publishDate | 2024-11-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Digital Health |
| spelling | doaj-art-e1f12764d238423b8ba4584099f359e12025-08-20T02:12:41ZengFrontiers Media S.A.Frontiers in Digital Health2673-253X2024-11-01610.3389/fdgth.2024.14750921475092Prospects for AI clinical summarization to reduce the burden of patient chart reviewChanseo Lee0Kimon A. Vogt1Sonu Kumar2Department of Surgery, Yale School of Medicine, New Haven, CT, United StatesSporo Health, Boston, MA, United StatesSporo Health, Boston, MA, United StatesEffective 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.https://www.frontiersin.org/articles/10.3389/fdgth.2024.1475092/fullartificial intelligencepatient chart reviewclinical summarizationLLMelectronic health recordscybersecurity |
| spellingShingle | Chanseo Lee Kimon A. Vogt Sonu Kumar Prospects for AI clinical summarization to reduce the burden of patient chart review Frontiers in Digital Health artificial intelligence patient chart review clinical summarization LLM electronic health records cybersecurity |
| title | Prospects for AI clinical summarization to reduce the burden of patient chart review |
| title_full | Prospects for AI clinical summarization to reduce the burden of patient chart review |
| title_fullStr | Prospects for AI clinical summarization to reduce the burden of patient chart review |
| title_full_unstemmed | Prospects for AI clinical summarization to reduce the burden of patient chart review |
| title_short | Prospects for AI clinical summarization to reduce the burden of patient chart review |
| title_sort | prospects for ai clinical summarization to reduce the burden of patient chart review |
| topic | artificial intelligence patient chart review clinical summarization LLM electronic health records cybersecurity |
| url | https://www.frontiersin.org/articles/10.3389/fdgth.2024.1475092/full |
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