Treffer: Transforming Documents of the Austrian Nationwide EHR System into the OMOP CDM.

Title:
Transforming Documents of the Austrian Nationwide EHR System into the OMOP CDM.
Authors:
Korntheuer RL; Section of Medical Information Management, Center for Medical Statistics, Informatics and Intelligent Systems, Medical University of Vienna, Vienna, Austria., Katsch F; Section of Medical Information Management, Center for Medical Statistics, Informatics and Intelligent Systems, Medical University of Vienna, Vienna, Austria.; Ludwig Boltzmann Institute for Digital Health and Prevention, Salzburg, Austria., Duftschmid G; Section of Medical Information Management, Center for Medical Statistics, Informatics and Intelligent Systems, Medical University of Vienna, Vienna, Austria.
Source:
Studies in health technology and informatics [Stud Health Technol Inform] 2023 May 02; Vol. 301, pp. 54-59.
Publication Type:
Journal Article
Language:
English
Journal Info:
Publisher: IOS Press Country of Publication: Netherlands NLM ID: 9214582 Publication Model: Print Cited Medium: Internet ISSN: 1879-8365 (Electronic) Linking ISSN: 09269630 NLM ISO Abbreviation: Stud Health Technol Inform
Imprint Name(s):
Original Publication: Amsterdam ; Washington, DC : IOS Press, 1991-
MeSH Terms:
Electronic Health Records* , Records*, Austria/epidemiology ; Databases, Factual ; Models, Theoretical
Contributed Indexing:
Keywords: ELGA; ETL process; HL7 CDA; OMOP CDM; electronic health records
Entry Date(s):
Date Created: 20230512 Date Completed: 20230515 Latest Revision: 20230515
Update Code:
20250114
DOI:
10.3233/SHTI230011
PMID:
37172152
Database:
MEDLINE

Weitere Informationen

The Austrian nationwide EHR system ELGA can contribute valuable data for research due to its high volume of data and broad population coverage. In order to be applicable in international research projects, transformation to a standardized, research-oriented data model such as the OMOP common data model is essential. In this paper we describe our experience with the corresponding transformation task. Using Python scripts, we implemented a prototypical process that extracts, transforms, maps, and loads fully structured sections of ELGA documents to an OMOP database.