An Agentic Model Context Protocol Framework for Medical Concept Standardization
Abstract
The Observational Medical Outcomes Partnership (OMOP) common data model (CDM) provides a standardized representation of heterogeneous health data to support large-scale, multi-institutional research. One critical step in data standardization using OMOP CDM is the mapping of source medical terms to OMOP standard concepts, a procedure that is resource-intensive and error-prone. While large language models (LLMs) have the potential to facilitate this process, their tendency toward hallucination makes them unsuitable for clinical deployment without training and expert validation. Here, we developed a zero-training, hallucination-preventive mapping system based on the Model Context Protocol (MCP), a standardized and secure framework allowing LLMs to interact with external resources and tools. The system enables explainable mapping and significantly improves efficiency and accuracy with minimal effort. It provides real-time vocabulary lookups and structured reasoning outputs suitable for immediate use in both exploratory and production environments.
Cite
@article{arxiv.2509.03828,
title = {An Agentic Model Context Protocol Framework for Medical Concept Standardization},
author = {Jaerong Ahn and Andrew Wen and Nan Wang and Heling Jia and Zhiyi Yue and Sunyang Fu and Hongfang Liu},
journal= {arXiv preprint arXiv:2509.03828},
year = {2025}
}