Cohort Discovery Query Optimization via Computable Controlled Vocabulary Versioning.
Self-service cohort discovery tools strive to provide intuitive interfaces to large Clinical Data Warehouses that contain extensive historic information. In those tools, controlled vocabulary (e.g., ICD-9-CM, CPT) coded clinical information is often the main search criteria used because of its ubiquity in billing processes. These tools generally require a researcher to pick specific terms from the controlled vocabulary. However, controlled vocabularies evolve over time as medical knowledge changes and can even be replaced with new versions (e.g., ICD-9 to ICD-10). These tools generally only display the current version of the controlled vocabulary. Researchers should not be expected to understand the underlying controlled vocabulary versioning issues. We propose a computable controlled vocabulary versioning system that allows cohort discovery tools to automatically expand queries to account for terminology changes.
Stanford Center for Clinical Informatics, Stanford University, Stanford, CA, US.
Todd A
TA
Ferris
Stanford Center for Clinical Informatics, Stanford University, Stanford, CA, US.
Tanya
T
Podchiyska
D000068598:Data Accuracy; D057225:Data Mining / Q000379:methods*; D003628:Database Management Systems / Q000458:organization & administration*; D057286:Electronic Health Records / Q000458:organization & administration*; D038801:International Classification of Diseases; D009323:Natural Language Processing