Literature DB >> 31437920

Transforming Two Decades of ePR Data to OMOP CDM for Clinical Research.

Daniel M Lima1, Jose F Rodrigues-Jr1, Agma J M Traina1, Fabio A Pires1, Marco A Gutierrez2.   

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' 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.

Entities:  

Keywords:  Data Curation; Health Information Exchange; Medical Informatics

Mesh:

Year:  2019        PMID: 31437920     DOI: 10.3233/SHTI190218

Source DB:  PubMed          Journal:  Stud Health Technol Inform        ISSN: 0926-9630


  2 in total

1.  Common Problems, Common Data Model Solutions: Evidence Generation for Health Technology Assessment.

Authors:  Seamus Kent; Edward Burn; Dalia Dawoud; Pall Jonsson; Jens Torup Østby; Nigel Hughes; Peter Rijnbeek; Jacoline C Bouvy
Journal:  Pharmacoeconomics       Date:  2020-12-18       Impact factor: 4.981

2.  Development and Validation of the Radiology Common Data Model (R-CDM) for the International Standardization of Medical Imaging Data.

Authors:  ChulHyoung Park; Seng Chan You; Hokyun Jeon; Chang Won Jeong; Jin Wook Choi; Rae Woong Park
Journal:  Yonsei Med J       Date:  2022-01       Impact factor: 2.759

  2 in total

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