The utilisation of routine clinical data is increasingly vital for analysing care quality and supporting clinical decisions. This study within the POLAR_MI consortium developed a FHIR-based distributed validation method to quantify amitriptyline prescriptions in patients aged ≥65 years. Data from 10 German university hospitals were aggregated and validated through bidirectional checks, achieving 100% accuracy for inpatient and 82.7% for outpatient amitriptyline identification. High inter-rater reliability (Krippendorff's Alpha = 0.9814) confirmed data validity. Our approach demonstrated the feasibility of using standardised FHIR specifications for robust, privacy-compliant evidence generation in large-scale pharmacovigilance studies.
Keywords: Clinical Routine Data; Data Quality; Data Validation; Distributed Computing; Health Data Research; Medical Informatics Initiative; Plausibility Checks.