Department of Pharmacy Practice and Science, The University of Arizona College of Pharmacy, Tucson, Arizona 85721-0202, USA.
J Am Med Inform Assoc. 2011 Jan-Feb;18(1):32-7. doi: 10.1136/jamia.2010.007609. Epub 2010 Dec 3.
Pharmacy clinical decision-support (CDS) software that contains drug-drug interaction (DDI) information may augment pharmacists' ability to detect clinically significant interactions. However, studies indicate these systems may miss some important interactions. The purpose of this study was to assess the performance of pharmacy CDS programs to detect clinically important DDIs.
Researchers made on-site visits to 64 participating Arizona pharmacies between December 2008 and November 2009 to analyze the ability of pharmacy information systems and associated CDS to detect DDIs. Software evaluation was conducted to determine whether DDI alerts arose from prescription orders entered into the pharmacy computer systems for a standardized fictitious patient. The fictitious patient's orders consisted of 18 different medications including 19 drug pairs-13 of which were clinically significant DDIs, and six were non-interacting drug pairs.
The sensitivity, specificity, positive predictive value, negative predictive value, and percentage of correct responses were measured for each of the pharmacy CDS systems.
Only 18 (28%) of the 64 pharmacies correctly identified eligible interactions and non-interactions. The median percentage of correct DDI responses was 89% (range 47-100%) for participating pharmacies. The median sensitivity to detect well-established interactions was 0.85 (range 0.23-1.0); median specificity was 1.0 (range 0.83-1.0); median positive predictive value was 1.0 (range 0.88-1.0); and median negative predictive value was 0.75 (range 0.38-1.0).
These study results indicate that many pharmacy clinical decision-support systems perform less than optimally with respect to identifying well-known, clinically relevant interactions. Comprehensive system improvements regarding the manner in which pharmacy information systems identify potential DDIs are warranted.
含有药物相互作用(DDI)信息的药学临床决策支持(CDS)软件可以增强药师检测具有临床意义的相互作用的能力。然而,研究表明这些系统可能会错过一些重要的相互作用。本研究旨在评估药学 CDS 程序检测具有临床意义的 DDI 的性能。
研究人员于 2008 年 12 月至 2009 年 11 月期间对 64 家参与亚利桑那州的药店进行了现场访问,以分析药学信息系统和相关 CDS 检测药物相互作用的能力。软件评估是为了确定是否从输入到药店计算机系统的标准化虚构患者的处方订单中产生了药物相互作用警报。虚构患者的订单包括 18 种不同的药物,其中包括 19 对药物,其中 13 对是具有临床意义的药物相互作用,6 对是非相互作用的药物对。
为每个药学 CDS 系统测量了灵敏度、特异性、阳性预测值、阴性预测值和正确响应的百分比。
只有 18 家(28%)的 64 家药店正确识别了合格的相互作用和非相互作用。参与药店的平均正确 DDI 反应百分比为 89%(范围 47-100%)。检测已建立的相互作用的中位灵敏度为 0.85(范围 0.23-1.0);中位特异性为 1.0(范围 0.83-1.0);中位阳性预测值为 1.0(范围 0.88-1.0);中位阴性预测值为 0.75(范围 0.38-1.0)。
这些研究结果表明,许多药学临床决策支持系统在识别已知的、具有临床相关性的相互作用方面表现不佳。需要全面改进药学信息系统识别潜在药物相互作用的方式。