Development of a Visualization Dashboard for Medication Prescriptions Using Diagnostic and Prescription Data From Seoul National University Hospital

Background: Large-scale health data and the Observational Medical Outcomes Partnership (OMOP) common data model (CDM) enable standardized analyses for drug safety and precision medicine.Yet, few platforms translate CDM drug data into interactive tools directly usable for clinical or research purposes.Methods: We developed an OMOP CDM-based drug dashboard at Seoul National University Hospital (SNUH), using patient records from 2004 to 2024 within CDM v5.4.The backend was implemented with Express (Node.js),and the frontend with React.Features included ingredient-and drug-based queries, conditional searches by demographics and diagnoses, and patient-level prescription histories.Additional modules provided polypharmacy analysis, adverse drug reaction (ADR) monitoring with laboratory markers, and yearly prescription trend visualization.Results: The dashboard outputs standardized OMOP attributes while retaining institutionspecific identifiers.It allows users to explore prescription distributions, co-prescription patterns, and demographic-specific ADRs.These interactive functions support pharmacovigilance, epidemiological research, and individualized prescribing decisions by enabling both broad queries and patient-level detail. Conclusion:This represents the first dedicated attempt to operationalize OMOP CDM drug data into an interactive dashboard.Despite limitations, including static CDM updates and the absence of usability testing, the platform demonstrates value for drug safety monitoring.Future enhancements include real-time extracting, transforming, and loading pipelines, predictive polypharmacy risk models, and integration of multi-omics data, extending its potential for precision medicine.