Development and Evaluation of a Retrieval-Augmented Generation Chatbot for Orthopedic and Trauma Surgery Patient Education: Mixed-Methods Study
The chatbot demonstrated strong performance in delivering orthopedic patient education through an RAG framework. Its deployment on the national Orthinform platform has led to more than 9500 real-world user interactions, supporting its relevance and acceptance. Future improvements should focus on expanding domain coverage, enhancing retrieval precision, and integrating multimodal content and advanced RAG techniques to improve robustness and safety in patient-facing apps.
Authors
- Christoph‐Eckhard Heyde (ORCID: https://orcid.org/0000-0002-9083-4062)
- Jörg Ansorg (ORCID: https://orcid.org/0000-0001-8949-8420)
- Anna Voelker (ORCID: https://orcid.org/0000-0002-2715-5438)
- David Baur (ORCID: https://orcid.org/0000-0001-8602-617X)
Institutions
- Orthopaedic Trauma Association (US)
- University Hospital Leipzig (DE)
Publication Details
- Journal
- JMIR AI
- Published
- 2025-09-27
- DOI
- https://doi.org/10.2196/75262
- Citations
- 4
- Primary Topic
- AI in Service Interactions
- Type
- article
- Field-Weighted Citation Impact
- 9.92