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Towards ETL Processes to OMOP CDM Using Metadata and Modularization
Yuan Peng, Elisa Henke, Martin Sedlmayr, Franziska Bathelt
751 - 752
10.3233/SHTI230256
Research Article
Studies in Health Technology and Informatics
Volume 302: Caring is Sharing – Exploiting the Value in Data for Health and Innovation
Abstract

OMOP common data model (CDM) is designed for analyzing large clinical data and building cohorts for medical research, which requires Extract-Transform-Load processes (ETL) of local heterogeneous medical data. We present a concept for developing and evaluating a modularized metadata-driven ETL process, which can transform data into OMOP CDM regardless of 1) the source data format, 2) its versions and 3) context of use.

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