Detecting Contraindications in Routinely Collected Healthcare Data to Emulate Decision Support for Medication Reviews Within the INTERPOLAR Study
Schmidt F, Struebing A, Köster H, Beppler T, Staeubert S, Loeffler M, Neumann D (2026)
Publication Type: Journal article
Publication year: 2026
Journal
Book Volume: 336
Pages Range: 453-457
DOI: 10.3233/SHTI260196
Abstract
INTRODUCTION: Medication-related problems (MRPs), including contraindications, are a major cause of preventable harm. Despite clinical decision support systems (CDSS), relevant contraindications often remain undetected due to missing clinical context. METHODS: We developed a computable, FHIR-based approach using the CDS Toolchain to identify contraindications in routinely collected EHR data. FHIR resources (Patient, Encounter, MedicationRequest/Administration/Statement, Medication, Condition, Observation, Procedure) were harmonized under the German Medical Informatics Initiative (MII) Core Dataset. Absolute contraindications from product information were mapped to ATC, ICD-10, LOINC, and OPS and implemented as two-trigger rules. A potential MRP fired only when both triggers were active and their defined time intervals overlapped. RESULTS: The algorithm was applied to routinely collected data from 2,005 inpatient cases corresponding to 1,729 unique patients. Of these, 789 cases had a documented medication review. Among the analyzed cases, 411 (52.1%) contained at least one potential MRP. CONCLUSION: The approach demonstrates feasibility of detecting temporally defined contraindications from FHIR-based routine data, providing a reproducible foundation for pharmacist validation and multicenter studies.
Involved external institutions
Germany (DE)How to cite
APA:
Schmidt, F., Struebing, A., Köster, H., Beppler, T., Staeubert, S., Loeffler, M., & Neumann, D. (2026). Detecting Contraindications in Routinely Collected Healthcare Data to Emulate Decision Support for Medication Reviews Within the INTERPOLAR Study. Studies in Health Technology and Informatics, 336, 453-457. https://doi.org/10.3233/SHTI260196
MLA:
Schmidt, Florian, et al. "Detecting Contraindications in Routinely Collected Healthcare Data to Emulate Decision Support for Medication Reviews Within the INTERPOLAR Study." Studies in Health Technology and Informatics 336 (2026): 453-457.
BibTeX: Download