What emotions reveal about patient safety: GPT-4-based sentiment and emotion analysis of 11056 German CIRS medical reports (2005–2024)
Emotion-based analysis of incident reports provides insight into perceived burden and care context. Sentiment profiling may improve system interpretability and support emotion-sensitive safety culture and feedback. Leveraging large language models can reduce reviewer workload and enable more targeted triage of emotionally complex reports.
Authors
- Patrick Meybohm (ORCID: https://orcid.org/0000-0002-2666-8696)
- Oliver Happel (ORCID: https://orcid.org/0000-0001-7320-8521)
- Peter Kranke (ORCID: https://orcid.org/0000-0001-5324-981X)
- Carlos Ramon Hölzing (ORCID: https://orcid.org/0000-0002-3732-6544)
- Charlotte Meynhardt
Institutions
- Universitätsklinikum Würzburg (DE)
Publication Details
- Journal
- BMJ Health & Care Informatics
- Published
- 2025-12-01
- DOI
- https://doi.org/10.1136/bmjhci-2025-101741
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 0.00