A Semantic Transformation Methodology for the Secondary Use of Observational Healthcare Data in Postmarketing Safety Studies

Frontiers in Pharmacology
Anil PacaciGokce Banu Laleci Erturkmen

Abstract

Background: Utilization of the available observational healthcare datasets is key to complement and strengthen the postmarketing safety studies. Use of common data models (CDM) is the predominant approach in order to enable large scale systematic analyses on disparate data models and vocabularies. Current CDM transformation practices depend on proprietarily developed Extract-Transform-Load (ETL) procedures, which require knowledge both on the semantics and technical characteristics of the source datasets and target CDM. Purpose: In this study, our aim is to develop a modular but coordinated transformation approach in order to separate semantic and technical steps of transformation processes, which do not have a strict separation in traditional ETL approaches. Such an approach would discretize the operations to extract data from source electronic health record systems, alignment of the source, and target models on the semantic level and the operations to populate target common data repositories. Approach: In order to separate the activities that are required to transform heterogeneous data sources to a target CDM, we introduce a semantic transformation approach composed of three steps: (1) transformation of source datasets to Re...Continue Reading

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Citations

Jan 26, 2021·Journal of Healthcare Engineering·Rafat HammadBilal H Abed-Alguni

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Software Mentioned

OMOP DB
N3
SALUS
Chronograph
ShEx
Terminology
OMOP Database Adapter
OMOP
SPARQL
OMOP Method

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