RESUMEN
PURPOSE: Development of an operational reporting dashboard designed to correlate data from multiple sources to help detect potential drug diversion by automated dispensing cabinet (ADC) users is described. METHODS: A commercial business intelligence platform was used to create a dashboard tool for rapid detection of unusual patterns of ADC transactions by anesthesia service providers at a large pediatric hospital. By linking information from the hospital's pharmacy information management system (PIMS) and anesthesia information management system (AIMS) in an associative data model, the "narcotic reconciliation dashboard" can generate various reports to help spot outlier activity associated with ADC dispensing of controlled substances and documentation of medication waste processing. RESULTS: The dashboard's utility was evaluated by "back-testing" the program with historical data on an actual episode of diversion by an anesthesia provider that had not been detected through traditional methods of PIMS and AIMS data monitoring. Dashboard-generated reports on key metrics (e.g., ADC transaction counts, discrepancies in dispensed versus reconciled amounts of narcotics, PIMS-AIMS documentation mismatches) over various time frames during the period of known diversion clearly indicated the diverter's outlier status relative to other authorized ADC users. CONCLUSION: A dashboard program for correlating ADC transaction data with pharmacy and patient care data may be an effective tool for detecting patterns of ADC use that suggest drug diversion.