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Identifying Relevant FHIR Elements for Data Quality Assessment in the German Core Data Set Passed

Thursday May 25, 2023 08:30 - 08:45 G3

Lecturer: Christian Draeger

Track: MIE: Health information systems

The German Medical Informatics Initiative makes clinical routine data available for biomedical research. In total, 37 university hospitals have set up so-called data integration centers to facilitate this data reuse. A standardized set of HL7 FHIR profiles (“MII Core Data Set”) defines the common data model across all centers. Regular Projectathons ensure continuous evaluation of the implemented data sharing processes on artificial and real-world clinical use cases. In this context, FHIR continues to rise in popularity for exchanging patient care data. As reusing data from patient care in clinical research requires high trust in the data, data quality assessments are a key point of concern in the data sharing process. To support the setup of data quality assessments within data integration centers, we suggest a process for finding elements of interest from FHIR profiles. We focus on the specific data quality measures defined by Kahn et al.

Language

English

Seminar type

On site only

Level of knowledge

Advanced

Conference

MIE

Authors

Christian Draeger, Erik Tute, Carsten Oliver Schmidt, Dagmar Waltemath, Martin Boeker, Alfred Winter, Matthias Löbe

Lecturers

Profile image for Christian Draeger

Christian Draeger Lecturer

Researcher
IMISE, Leipzig University

While working at the Institute for Medical Informatics, Statistics and Epidemiology (IMISE) at the University of Leipzig I focus my research on data quality assessments of health care data. I am specifically interested in the challenges that arise from reusing such data in clinical research. Making health care data available to researchers is the goal of the Germana Medical Informatics Initiative (MII). As a member of the MII working group for Metadata I work on implementing my theoretical research in the distributed context of the MII, a context in which FAIR Metadata is increasingly important.