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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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
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      dt: 2019
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      place: Thousand Oaks, California
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        atl: 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
      aug:
        au:
          Lima, Daniel M.
          Rodrigues-Jr., Jose F.
          Traina, Agma J. M.
          Pires, Fabio A.
          Gutierrez, Marco A.
        affil: Institute of Mathematical and Computer Sciences (ICMC), University of São Paulo, São Carlos, São Paulo, Brazil
      sug:
        subj:
          Electronic Health Records
          Data Management
          Data Curation
          Clinical Research
          Electronic Data Interchange
          Models, Statistical
          Medical Informatics
          Resource Databases, Health
          Human
          Brazil
          Congresses and Conferences France
          France
          Funding Source
          Database Construction
          Health Information Management
          Descriptive Statistics
          Database Quality
          Database Management Software
          ROC Curve
      ab: 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.
      pubtype: Academic Journal
      doctype:
        proceedings
        research
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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