@article {1216, title = {Transforming Two Decades of ePR Data to OMOP CDM for Clinical Research.}, journal = {Stud Health Technol Inform}, volume = {264}, year = {2019}, month = {2019 Aug 21}, pages = {233-237}, abstract = {

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{\textquoteright} 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.

}, issn = {1879-8365}, doi = {10.3233/SHTI190218}, author = {Lima, Daniel M and Rodrigues-Jr, Jose F and Traina, Agma J M and Pires, Fabio A and Gutierrez, Marco A} }