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A Framework for Criteria-Based Selection and Processing of Fast Healthcare Interoperability Resources (FHIR) Data for
Julian Gruendner1, Christian Gulden1, Marvin Kampf2
1Chair of Medical Informatics, Department of Medical Informatics, Biometrics and Epidemiology, Friedrich-Alexander University Erlangen-Nürnberg, Erlangen-Tennenlohe, Germany.
JMIR Medical Informatics
|April 1, 2021
Summary
This study demonstrates how PostgreSQL can store Fast Healthcare Interoperability Resources (FHIR) data, enabling direct statistical analysis through a preprocessing service. This approach streamlines medical data utilization for research while maintaining patient privacy.
Area of Science:
- Health Informatics
- Database Management
- Statistical Analysis
Background:
- Standardizing digital medical data for research is complex.
- Existing repositories require significant data harmonization.
- Fast Healthcare Interoperability Resources (FHIR) format is common in EHRs but not analysis-ready.
Purpose of the Study:
- To demonstrate direct querying of FHIR data using a preprocessing service for statistical analysis.
- To evaluate the suitability of PostgreSQL for storing and processing FHIR data.
Main Methods:
- Proposed using PostgreSQL's binary JSON format to store and extend FHIR data.
- Developed and deployed a preprocessing and filtering service.
- Integrated the service with the KETOS analysis platform at University Hospital Erlangen-Nürnberg.
Main Results:
- Imported ~35.5 million FHIR resources (Patient, Encounter, Condition, Procedure, Observation) into PostgreSQL.
- Successfully performed advanced statistical analyses in three clinical scenarios.
- Demonstrated feasibility of data-driven reference intervals, anemia prevalence, and drug adverse effects studies.
Conclusions:
- PostgreSQL can effectively store FHIR data for integrated statistical analysis.
- A custom preprocessing service enables advanced medical data subset generation.
- The local deployment protects patient privacy and integrates with open-source analysis tools.
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