Taylor Laurel K, Tamblyn Robyn
Faculty of Management, McGill University, Montreal, Quebec, Canada.
Stud Health Technol Inform. 2004;107(Pt 2):1101-5.
Many adverse drug errors may be prevented through electronic order entry systems that provide decision support to physicians by screening prescriptions for dosing errors, drug-disease, drug-allergy and drug-drug interactions. The adherence to such decision aids is varied and the reasons for this variance not well understood.
To assess the feasibility and performance auto-mated drug alerts within an electronic decision support system for physician prescribing.
Drug alert data were collected from a pilot project with 30 participating general practitioners who were provided with interactive electronic prescription capabilities through a personal digital assistant (PDA).
66,642 electronic prescriptions resulted in a total of 1,869 drug alerts. The most common alert types were analysed, along with reasons for non-adherence to automated drug alerts.
Non-adherence to alert information appears to be associated with additional knowledge of the clinical situation, beyond that inherent in the decision support tool, for the specific patient context. Further work is required to understand how best to provide this type of support to physicians.
许多药物不良事件可以通过电子医嘱录入系统来预防,该系统通过筛查处方中的剂量错误、药物-疾病、药物-过敏及药物-药物相互作用为医生提供决策支持。对这类决策辅助工具的依从性各不相同,且造成这种差异的原因尚不清楚。
评估电子决策支持系统中自动药物警示功能在医生开处方时的可行性和性能。
从一个试点项目收集药物警示数据,该项目有30名参与的全科医生,通过个人数字助理(PDA)为他们提供交互式电子处方功能。
66642份电子处方共产生了1869次药物警示。分析了最常见的警示类型以及不遵守自动药物警示的原因。
对于特定患者情况,不遵守警示信息似乎与超出决策支持工具固有临床情况的额外知识有关。需要进一步开展工作以了解如何最好地为医生提供此类支持。