Paris Descartes University (Paris 5), Paris, France.
J Am Med Inform Assoc. 2012 Sep-Oct;19(5):782-5. doi: 10.1136/amiajnl-2012-000850. Epub 2012 Apr 20.
The objective of this case report is to evaluate the use of a clinical data warehouse coupled with a clinical information system to test and refine alerts for medication orders control before they were fully implemented. A clinical decision rule refinement process was used to assess alerts. The criteria assessed were the frequencies of alerts for initial prescriptions of 10 medications whose dosage levels depend on renal function thresholds. In the first iteration of the process, the frequency of the 'exceeds maximum daily dose' alerts was 7.10% (617/8692), while that of the 'under dose' alerts was 3.14% (273/8692). Indicators were presented to the experts. During the different iterations of the process, 45 (16.07%) decision rules were removed, 105 (37.5%) were changed and 136 new rules were introduced. Extensive retrospective analysis of physicians' medication orders stored in a clinical data warehouse facilitates alert optimization toward the goal of maximizing the safety of the patient and minimizing overridden alerts.
本病例报告的目的是评估使用临床数据仓库结合临床信息系统来测试和完善药物医嘱控制警报，然后再全面实施。使用临床决策规则完善流程来评估警报。评估的标准为 10 种药物初始处方的警报频率，这些药物的剂量水平取决于肾功能阈值。在该流程的第一迭代中，“超过最大日剂量”警报的频率为 7.10%（617/8692），而“剂量不足”警报的频率为 3.14%（273/8692）。向专家展示了指标。在该流程的不同迭代中，删除了 45 条（16.07%）决策规则，更改了 105 条（37.5%）决策规则，并引入了 136 条新规则。对存储在临床数据仓库中的医生药物医嘱进行广泛的回顾性分析有助于优化警报，以实现最大化患者安全性和最小化警报被忽略的目标。
