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

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Autor(es):
Lima, Daniel M. ; Rodrigues-Jr, Jose F. ; Traina, Agma J. M. ; Pires, Fabio A. ; Gutierrez, Marco A. ; OhnoMachado, L ; Seroussi, B
Número total de Autores: 7
Tipo de documento: Artigo Científico
Fonte: MEDINFO 2019: HEALTH AND WELLBEING E-NETWORKS FOR ALL; v. 264, p. 5-pg., 2019-01-01.
Resumo

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. (AU)

Processo FAPESP: 18/11424-0 - Criação de uma infraestrutura de Armazém de Dados para Análise Visual voltada à saúde
Beneficiário:Daniel Mário de Lima
Modalidade de apoio: Bolsas no Brasil - Programa Capacitação - Treinamento Técnico