Transforming Two Decades of ePR Data to OMOP CDM for Clinical Research...The 17th World Congress of Medical and Health Informatics, 25-30 August 2019, Lyon, France

This paper presents the extract-transform-and-load (ETL) process from the Electronic Patient Records (ePR) at the Heart Institute (InCor) to the OMOP Common Data Model (CDM) format. We describe the initial database characterization, relational source mappings, selection filters, data transformations...

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Detalles Bibliográficos
Publicado en:Studies in Health Technology & Informatics Vol. 264; pp. 233 - 238
Autores principales: Lima, Daniel M., Rodrigues-Jr., Jose F., Traina, Agma J. M., Pires, Fabio A., Gutierrez, Marco A.
Formato: proceedings research tables/charts Journal Article
Publicado: Sage Publications Inc. 2019
Acceso en línea:Ver este registro en EBSCOhost
Descripción
Sumario:This paper presents the extract-transform-and-load (ETL) process from the Electronic Patient Records (ePR) at the Heart Institute (InCor) to the OMOP Common Data Model (CDM) format. We describe the initial database characterization, relational source mappings, selection filters, data transformations and patient de-identification using the open-source OHDSI tools and SQL scripts. We evaluate the resulting InCor-CDM database by recreating the same patient cohort from a previous reference study (over the original data source) and comparing the cohorts' descriptive statistics and inclusion reports. The results exhibit that up to 91% of the reference patients were retrieved by our method from the ePR through InCor-CDM, with AUC=0.938. The results indicate that the method that we employed was able to produce a new database that was both consistent with the original data and in accordance to the OMOP CDM standard.