Department of Clinical Pharmacology and Toxicology, University Hospital Zurich, Rämistrasse 100, 8091 Zurich, Switzerland.
Eur J Clin Pharmacol. 2012 Aug;68(8):1209-19. doi: 10.1007/s00228-012-1241-6. Epub 2012 Feb 29.
Clinical decision support systems (CDSS) are promoted as powerful screening tools to improve pharmacotherapy. The aim of our study was to evaluate the potential contribution of CDSS to patient management in clinical practice.
We prospectively analyzed the pharmacotherapy of 100 medical inpatients through the parallel use of three CDSS, namely, Pharmavista, DrugReax, and TheraOpt. After expert discussion that also considered all patient-specific clinical information, we selected apparently relevant alerts, issued suitable recommendations to physicians, and recorded subsequent prescription changes.
For 100 patients with a median of eight concomitant drugs, Pharmavista, DrugReax, and TheraOpt generated a total of 53, 362, and 328 interaction alerts, respectively. Among those we identified and forwarded 33 clinically relevant alerts to the attending physician, resulting in 19 prescription changes. Four adverse drug events were associated with interactions. The proportion of clinically relevant alerts among all alerts (positive predictive value) was 5.7, 8.0, and 7.6%, and the sensitivity to detect all 33 relevant alerts was 9.1, 87.9, and 75.8% for Pharmavista, DrugReax and TheraOpt, respectively. TheraOpt recommended 31 dose adjustments, of which we considered 11 to be relevant; three of these were followed by dose reductions.
CDSS are valuable screening tools for medication errors, but only a small fraction of their alerts appear relevant in individual patients. In order to avoid overalerting CDSS should use patient-specific information and management-oriented classifications. Comprehensive information should be displayed on-demand, whereas a limited number of computer-triggered alerts that have management implications in the majority of affected patients should be based on locally customized and supported algorithms.
临床决策支持系统(CDSS)被宣传为一种强大的筛选工具,可用于改善药物治疗。本研究的目的是评估 CDSS 在临床实践中对患者管理的潜在贡献。
我们通过同时使用 Pharmavista、DrugReax 和 TheraOpt 这三个 CDSS,前瞻性地分析了 100 名住院患者的药物治疗情况。在专家讨论之后,我们还考虑了所有患者的具体临床信息,选择了明显相关的警报,向医生发出了合适的建议,并记录了随后的处方更改。
对于 100 名平均同时使用 8 种药物的患者,Pharmavista、DrugReax 和 TheraOpt 分别生成了 53、362 和 328 个相互作用警报。我们确定并转发了 33 个临床相关警报给主治医生,导致 19 个处方更改。有 4 起药物不良事件与药物相互作用有关。所有警报中临床相关警报的比例(阳性预测值)分别为 5.7%、8.0%和 7.6%,而 Pharmavista、DrugReax 和 TheraOpt 检测到所有 33 个相关警报的灵敏度分别为 9.1%、87.9%和 75.8%。TheraOpt 建议进行 31 次剂量调整,我们认为其中 11 次是相关的;其中 3 次随后减少了剂量。
CDSS 是药物错误的有价值的筛选工具,但只有一小部分警报在个别患者中是相关的。为了避免过度警报,CDSS 应使用患者特定的信息和面向管理的分类。应按需显示全面的信息,而基于本地定制和支持的算法的、对大多数受影响患者具有管理意义的少数计算机触发警报则应被保留。