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.

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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
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article

Development and Evaluation of a Retrieval-Augmented Generation Chatbot for Orthopedic and Trauma Surgery Patient Education: Mixed-Methods Study

Christoph‐Eckhard Heyde, Jörg Ansorg, Anna Voelker, David Baur
4 citations
JMIR AI
AI in Service Interactions
9.92
article

Development and Evaluation of a Retrieval-Augmented Generation Chatbot for Orthopedic and Trauma Surgery Patient Education: Mixed-Methods Study

Christoph‐Eckhard Heyde, Jörg Ansorg, Anna Voelker, David Baur
article en
4 citations

Abstract

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.

JMIR AIVol. 4
Orthopaedic Trauma Association (US), University Hospital Leipzig (DE)
Openalex Percentile: Top 2%
AI in Service Interactions
9.92
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