Description
Electronic Health Records (EHR) are central to cohort identification, feasibility assessments and retrospective studies. Availability of multiple EHR systems and informatics tools create complexities in data loading processes leading to inconsistencies across cohort identification tools. We leveraged the Observational Medical Outcomes Partnership (OMOP) model and implemented a data pipeline that maps vendor specific EHR concepts into OMOP, de-identifies and feeds cohort identification tools, there by establishing data consistency across multiple informatics tools.
Learning Objective: A solution to standardize data and loading process across multiple EHR systems and cohort identification tools.
Authors:
Uma Vangala, University of Massachusetts Medical School
Yurima Guilarte-Walker, University of Massachusetts Medical School
Doug Buell, University of Massachusetts Medical School
Keith Pelletier, University of Massachusetts Medical School
Katherine Lazuriaga, University of Massachusetts Medical School
Jomol Mathew (Presenter)
University of Massachusetts Medical School
Presentation Materials: