In this study, we propose FHIR-RAG-MEDS system that aims to integrate Health Level 7 Fast Healthcare Interoperability Resources (HL7 FHIR) with a Retrieval-Augmented Generation (RAG)-based system to improve personalized medical decision support on evidence-based clinical guidelines, emphasizing the need for research in practical applications. In the evolving landscape of medical decision support systems, integrating advanced technologies such as RAG and HL7 FHIR can significantly enhance clinical decision-making processes. Despite the potential of these technologies, there is limited research on their integration in practical applications.
@article{arxiv.2509.07706,
title = {FHIR-RAG-MEDS: Integrating HL7 FHIR with Retrieval-Augmented Large Language Models for Enhanced Medical Decision Support},
author = {Yildiray Kabak and Gokce B. Laleci Erturkmen and Mert Gencturk and Tuncay Namli and A. Anil Sinaci and Ruben Alcantud Corcoles and Cristina Gomez Ballesteros and Pedro Abizanda and Asuman Dogac},
journal= {arXiv preprint arXiv:2509.07706},
year = {2026}
}
Comments
23 pages, submitted to Journal AI specifically to the special issue "LLMs and AI Agents in Biomedical and Health Sciences", under review