MedRep: medical concept representations for general electronic health record foundation models.

Abstract

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. 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. 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. 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. MedRep improves EHR foundation model performance, interpretability, and generalizability, serving as a standard baseline representation for EHR foundation models adopting OMOP CDM.