Application of AI in the creation of discharge summaries in psychiatric clinics
Background - The integration of artificial intelligence (AI; ChatGPT 4.0) into medical workflows presents a great potential to enhance efficiency and quality. The use of artificial intelligence in the creation of discharge summaries seems particularly interesting and valid. The course of each hospit...
Gespeichert in:
| Hauptverfasser: | , |
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| Dokumenttyp: | Article (Journal) |
| Sprache: | Englisch |
| Veröffentlicht: |
September 17, 2024
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| In: |
The international journal of psychiatry in medicine
Year: 2024, Pages: 1-8 |
| ISSN: | 1541-3527 |
| DOI: | 10.1177/00912174241284730 |
| Online-Zugang: | Verlag, kostenfrei, Volltext: https://doi.org/10.1177/00912174241284730 Verlag, kostenfrei, Volltext: https://journals.sagepub.com/doi/10.1177/00912174241284730 
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| Verfasserangaben: | Bertrand Janota, PhD and Krzysztof Janota |
MARC
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| 520 | |a Background - The integration of artificial intelligence (AI; ChatGPT 4.0) into medical workflows presents a great potential to enhance efficiency and quality. The use of artificial intelligence in the creation of discharge summaries seems particularly interesting and valid. The course of each hospitalization is described in the discharge summary, which is given to each patient and then to his general practitioner at the end of hospital treatment. An exploratory analysis of discharge summaries in psychiatric clinics underscores that these documents must fulfill diverse and specific requirements. Nevertheless, AI-generated discharge summaries offer the opportunity to optimize information transfer and alleviate the workload on physicians. - Method - The study evaluates the quality of discharge summaries produced by clinical staff and by an AI model (ChatGPT 4.0). The clinicians involved in writing of the discharge summaries were not informed about the study’s purpose or methodology. The completed summaries were subsequently assessed by four attending physicians using predefined criteria. These physicians were also blinded to the study’s objectives and were unaware of the individual authors of the summaries. The evaluation criteria included consistency, completeness, and comprehensibility. Additionally, the time required to prepare these summaries and its impact on overall quality were analyzed. - Results - The results of the study indicate that discharge summaries generated by AI are more efficient than discharge summaries prepared by clinic staff. The AI was particularly effective in terms of coherence and information structure. - Conclusion - Further research, training and development is needed to improve the accuracy and reliability of AI-generated discharge summaries. | ||
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