Department of Clinical Pharmacology and Toxicology, University Hospital Zurich, Zurich, Switzerland.
Clin Pharmacol Ther. 2011 Oct;90(4):588-96. doi: 10.1038/clpt.2011.150. Epub 2011 Aug 24.
In order to improve medication safety, more epidemiological data on the prevalence and clinical relevance of drug interactions are required. We developed an interface for mass analysis using the Clinical Decision Support Software (CDSS) MediQ and a multidimensional classification (Zurich Interaction System (ZHIAS)) incorporating the Operational Classification of Drug Interactions (ORCA). These were applied to 359,207 cross-sectional prescriptions from 84,607 psychiatric inpatients collected through the international AMSP program. MediQ issued 2,308 "high" and 71,112 "average" danger interaction alerts. Among these, after ORCA reclassification, there were 151 contraindicated and 4,099 provisionally contraindicated prescriptions. The ZHIAS provided further detailed categorical information on recommended management and specific increased risks (QTc prolongation being the most frequent one) associated with interactions. We developed a highly efficient solution for the identification and classification of drug interactions in large prescription data sets; this solution may help to reduce the frequency of overalerting and improve acceptance of the efficacy of CDSS in reducing the occurrence of potentially harmful drug interactions.
为了提高用药安全性,需要更多关于药物相互作用的流行程度和临床相关性的流行病学数据。我们开发了一个使用临床决策支持软件(CDSS)MediQ 进行大规模分析的接口,并结合包含操作分类的多维分类(苏黎世相互作用系统(ZHIAS))药物相互作用(ORCA)。这些都应用于通过国际 AMSP 计划收集的 84607 名精神科住院患者的 359207 份横断面处方。MediQ 发出了 2308 次“高”和 71112 次“平均”危险相互作用警报。在这些警报中,经过 ORCA 重新分类后,有 151 份禁忌和 4099 份临时禁忌处方。ZHIAS 提供了关于推荐管理和与相互作用相关的特定风险增加(QTc 延长最常见)的更详细的分类信息。我们开发了一种用于识别和分类大型处方数据集药物相互作用的高效解决方案;该解决方案有助于减少过度警报的频率,并提高 CDSS 减少潜在有害药物相互作用发生的疗效的接受度。