Faculty, Staff and Student Publications

Language

English

Publication Date

1-1-2025

Journal

AMIA Summits on Translational Science Proceedings

PMID

40502221

PMCID

PMC12150708

PubMedCentral® Posted Date

6-10-2025

PubMedCentral® Full Text Version

Post-print

Abstract

SNOMED CT is extensively employed to standardize data across diverse patient datasets and support cohort identification, with studies revealing its benefits and challenges. In this work, we developed a SNOMED CT-driven cohort query system over a heterogeneous Optum® de-identified COVID-19 Electronic Health Record dataset leveraging concept mappings between ICD-9-CM/ICD-10-CM and SNOMED CT. We evaluated the benefits and challenges of using SNOMED CT to perform cohort queries based on both query code sets and actual patients retrieved from the database, leveraging the original ICD-9-CM and ICD-10-CM as baselines. Manual review of 80 random cases revealed 65 cases containing 148 true positive codes and 25 cases containing 63 false positive codes. The manual evaluation also revealed issues in code naming, mappings, and hierarchical relations. Overall, our study indicates that while the SNOMED CT-driven query system holds considerable promise for comprehensive cohort queries, careful attention must be given to the challenges offalsely included codes and patients.

Published Open-Access

yes

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