Brenn B Randall, Kim Margaret A, Hilmas Elora
B. Randall Brenn, M.D., is Pediatric Anesthesiologist, Department of Anesthesiology, Nemours/Alfred I. duPont Hospital for Children, Wilmington, DE. Margaret A. Kim, D.P.M., is Senior Data Research Report Analyst, Nemours Enterprise Intelligence, Jacksonville, FL. Elora Hilmas, Pharm.D., BCPS, is Pharmacy Residency Coordinator, Department of Pharmacy, Nemours/Alfred I. duPont Hospital for Children.
Am J Health Syst Pharm. 2015 Aug 15;72(16):1365-72. doi: 10.2146/ajhp140691.
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.
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.
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.
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.
描述了一种操作报告仪表板的开发，该仪表板旨在关联来自多个来源的数据，以帮助检测自动配药柜（ADC）用户的潜在药物转移情况。
使用一个商业商业智能平台创建一个仪表板工具，用于快速检测一家大型儿科医院麻醉服务提供商的ADC交易异常模式。通过在关联数据模型中链接医院药房信息管理系统（PIMS）和麻醉信息管理系统（AIMS）的信息，“麻醉药品核对仪表板”可以生成各种报告，以帮助发现与ADC发放管制物质及药物废物处理记录相关的异常活动。
通过使用麻醉服务提供商一次实际转移事件的历史数据对该程序进行“回测”，评估了仪表板的效用，该转移事件通过传统的PIMS和AIMS数据监测方法未被发现。在已知转移期间的不同时间范围内，仪表板生成的关于关键指标（如ADC交易计数、发放与核对的麻醉药品数量差异、PIMS - AIMS记录不匹配）的报告清楚地表明了转移者相对于其他授权ADC用户的异常状态。
一个将ADC交易数据与药房和患者护理数据相关联的仪表板程序可能是检测表明药物转移的ADC使用模式的有效工具。
