Semantic analysis of SNOMED CT concept co-occurrences in clinical documentation using MIMIC-IV

Clinical notes contain rich but unstructured information that is challenging to analyze at scale. Standardized terminologies such as Systematized Nomenclature of Medicine-Clinical Terms (SNOMED CT) support semantic interoperability by providing consistent representations of clinical concepts; however, the relationship between empirical concept co-occurrence in clinical documentation and embedding-based semantic similarity remains poorly understood. This study examines how SNOMED CT concept co-occurrence patterns relate to semantic similarity in embedding space and explores the value of jointly analyzing these signals for semantic characterization of clinical narratives and exploratory phenotyping.

We analyzed SNOMED CT-annotated clinical notes from the MIMIC-IV database. Concept co-occurrence within notes was quantified using Normalized Pointwise Mutual Information (NPMI), while semantic similarity was computed using cosine similarity between pretrained biomedical concept embeddings. We examined relationships between co-occurrence and semantic similarity across temporal stages of hospitalization, clinical documentation types, and concept frequency strata.

Concept co-occurrence and embedding-based semantic similarity exhibited a weak but consistent positive association, indicating that frequently co-documented concepts are not always semantically proximate. Embeddings captured clinically meaningful associations that were infrequently documented together, highlighting latent relationships beyond documentation frequency. Temporal analysis showed more diffuse concept associations in early notes and stronger, more coherent relationships in later stages of care.

Co-occurrence statistics and embedding-based semantic similarity provide complementary views of clinical documentation. While co-occurrence reflects documentation practices and workflow, embeddings capture deeper conceptual relationships grounded in clinical context. Integrating these approaches enables improved understanding of clinical narratives.