IQ healthcare, 's-Hertogenbosch, The Netherlands.
J Am Med Inform Assoc. 2012 Jan-Feb;19(1):66-71. doi: 10.1136/amiajnl-2011-000360. Epub 2011 Sep 2.
OBJECTIVE To compare the clinical relevance of medication alerts in a basic and in an advanced clinical decision support system (CDSS).
A prospective observational study.
We collected 4023 medication orders in a hospital for independent evaluation in two pharmacotherapy-related decision support systems. Only the more advanced system considered patient characteristics and laboratory test results in its algorithms. Two pharmacists assessed the clinical relevance of the medication alerts produced. The alert was considered relevant if the pharmacist would undertake action (eg, contact the physician or the nurse). The primary analysis concerned the positive predictive value (PPV) for clinically relevant medication alerts in both systems.
The PPV was significantly higher in the advanced system (5.8% vs 17.0%; p<0.05). Significant differences were found in the alert categories: drug-(drug) interaction (9.9% vs 14.8%; p<0.05), drug-age interaction (2.9% vs 73.3%; p<0.05), and dosing guidance (5.6% vs 16.9%; p<0.05). Including laboratory values and other patient characteristics resulted in a significantly higher PPV for the advanced CDSS compared to the basic medication alerts (12.2% vs 23.3%; p<0.05).
The advanced CDSS produced a higher proportion of clinically relevant medication alerts, but the number of irrelevant alerts remained high. To improve the PPV of the advanced CDSS, the algorithms should be optimized by identifying additional risk modifiers and more data should be made electronically available to improve the performance of the algorithms. Our study illustrates and corroborates the need for cyclic testing of technical improvements in information technology in circumstances representative of daily clinical practice.
比较基本和高级临床决策支持系统(CDSS)中药物警报的临床相关性。
前瞻性观察研究。
我们在一家医院收集了 4023 份药物医嘱,由两名药师在两个与药物治疗相关的决策支持系统中进行独立评估。只有更高级的系统在其算法中考虑了患者特征和实验室检查结果。两名药师评估了产生的药物警报的临床相关性。如果药师采取行动(例如联系医生或护士),则认为警报相关。主要分析涉及两个系统中临床相关药物警报的阳性预测值(PPV)。
高级系统的 PPV 明显更高(5.8%比 17.0%;p<0.05)。在警报类别中发现了显著差异:药物-(药物)相互作用(9.9%比 14.8%;p<0.05)、药物-年龄相互作用(2.9%比 73.3%;p<0.05)和剂量指导(5.6%比 16.9%;p<0.05)。与基本药物警报相比,包括实验室值和其他患者特征在内,高级 CDSS 的 PPV 显著更高(12.2%比 23.3%;p<0.05)。
高级 CDSS 产生了更高比例的临床相关药物警报,但无关警报的数量仍然很高。为了提高高级 CDSS 的 PPV,应通过识别其他风险修饰符来优化算法,并应提供更多的电子数据以改善算法的性能。我们的研究说明了并证实了在具有代表性的日常临床实践环境中,需要周期性地测试信息技术的技术改进。