Related Experiment Video
Updated: Mar 12, 2026

Real-Time Cardiac Mapping with a Noninvasive Imageless Electrocardiographic Imaging System
Published on: April 11, 2025
MedRep: medical concept representations for general electronic health record foundation models
Junmo Kim1, Namkyeong Lee2, Jiwon Kim3
1Interdisciplinary Program in Bioengineering, Seoul National University, Seoul 08826, Republic of Korea.
Objective:
Traditional electronic health record (EHR) foundation models fail to process unseen medical codes, limiting generalizability across institutions with different vocabularies. To address this problem, we introduce medical concept representation (MedRep), standardized medical concept representations for EHR foundation models, enabling recognition of semantically similar concepts regardless of their specific IDs.
Materials And Methods:
We utilized Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM) vocabulary covering 7.5 million concepts from 66 medical vocabularies. MedRep integrates large language model-generated concept descriptions and OMOP graph ontology using graph contrastive learning with knowledge distillation. We evaluated MedRep-based models on MIMIC-IV (internal validation) and EHRSHOT (external validation) across 9 prediction tasks including clinical outcomes, phenotypes, and in-hospital events.
Results:
MedRep consistently outperformed baseline models, particularly in external validation with average improvements of 0.088 in area under the receiver operating characteristic curve and 0.208 in area under the precision-recall curve. Qualitative analysis demonstrated that MedRep-based models identified more clinically relevant concepts when making decisions than the baseline models. Performance improvements remained stable across diverse EHR foundation model architectures, including BEHRT, Med-BERT, and CDM-BERT.
Discussion:
MedRep improves the generalizability of EHR foundation models by encouraging similar concepts to have similar representations. EHR foundation models developed at different institutions could cooperate through MedRep, merging knowledge from multiple hospital datasets. In addition, our approach could reduce healthcare disparities by enabling smaller institutions to benefit from models trained on larger datasets.
Conclusion:
MedRep improves EHR foundation model performance, interpretability, and generalizability, serving as a standard baseline representation for EHR foundation models adopting OMOP CDM.
More Related Videos
07:26Executing Complexity-Increasing Queries in Relational MySQL and NoSQL MongoDB and EXist Size-Growing ISO/EN 13606 Standardized EHR Databases
Published on: March 19, 2018
09:00TBase - an Integrated Electronic Health Record and Research Database for Kidney Transplant Recipients
Published on: April 13, 2021
Related Concept Videos
Methods of Documentation VII: EMR
Concepts of Health and Illness
Models of Health Promotion and Illness Prevention I
The health belief model (HBM) attempts to predict health-related behavior in specific belief patterns. According to the HBM, a person's...
Purpose of Health Records II
Issues And Trends In Healthcare Delivery System
Cost Containment
Payment for healthcare services has historically promoted adoption of costly and often unnecessary or inefficient...
Purpose of Health Records I
Here's a breakdown of how health records serve these purposes: