Hospital for Special Surgery, Quality Research Center , New York.
Appl Clin Inform. 2012 Oct 17;3(4):377-91. doi: 10.4338/ACI-2012-01-RA-0002. Print 2012.
Computerized provider/physician order entry (CPOE) with clinical decision support (CDS) is designed to improve patient safety. However, a number of unintended consequences which include duplicate ordering have been reported. The objective of this time-series study was to characterize duplicate orders and devise strategies to minimize them.
Time series design with systematic weekly sampling for 84 weeks. Each week we queried the CPOE database, downloaded all active orders onto a spreadsheet, and highlighted duplicate orders. We noted the following details for each duplicate order: time, order details (e.g. drug, dose, route and frequency), ordering prescriber, including position and role, and whether the orders originated from a single order or from an order set (and the name of the order set). This analysis led to a number of interventions, including changes in: order sets, workflow, prescriber training, pharmacy procedures, and duplicate alerts.
Duplicates were more likely to originate from different prescribers than from same prescribers; and from order sets than from single orders. After interventions, there was an 84.8% decrease in the duplication rate from weeks 1 to 84 and a 94.6% decrease from the highest (1) to the lowest week (75). Currently, we have negligible duplicate orders.
Duplicate orders can be a significant unintended consequence of CPOE. By analyzing these orders, we were able to devise and implement generalizable strategies that significantly reduced them. The incidence of duplicate orders before CPOE implementation is unknown, and our data originate from a weekly snapshot of active orders, which serves as a sample of total active orders. Thus, it should be noted that this methodology likely under-reports duplicate orders.
计算机化医嘱录入(CPOE)与临床决策支持(CDS)旨在提高患者安全。然而,已报告了一些意外后果,包括重复医嘱。本时间序列研究的目的是描述重复医嘱并制定策略来减少它们。
84 周的时间序列设计,每周进行系统抽样。每周我们查询 CPOE 数据库,将所有活动医嘱下载到电子表格中,并突出显示重复医嘱。我们记录了每个重复医嘱的以下详细信息:时间、医嘱细节(例如药物、剂量、途径和频率)、开方医生,包括职位和角色,以及医嘱是否来自单个医嘱或医嘱集(以及医嘱集的名称)。该分析导致了一系列干预措施,包括改变医嘱集、工作流程、开方医生培训、药房程序和重复医嘱警报。
重复医嘱更可能来自不同的医生,而不是同一个医生;并且更可能来自医嘱集,而不是单个医嘱。干预后,从第 1 周到第 84 周,重复率下降了 84.8%,从最高(第 1 周)到最低(第 75 周)下降了 94.6%。目前,我们的重复医嘱几乎为零。
重复医嘱可能是 CPOE 的一个重大意外后果。通过分析这些医嘱,我们能够设计并实施通用策略,显著减少了重复医嘱。CPOE 实施前的重复医嘱发生率未知,并且我们的数据来源于活动医嘱的每周快照,这只是活动医嘱的样本。因此,应注意到这种方法可能会低估重复医嘱的数量。