Ghamrawi Riane J, Kantorovich Alexander, Bauer Seth R, Pallotta Andrea M, Sekeres Jennifer K, Gordon Steven M, Neuner Elizabeth A
University of Cincinnati- West Chester Hospital, OH, USA.
University of Cincinnati- Daniel Drake Center for Post-Acute Care, OH, USA.
Hosp Pharm. 2017 Nov;52(10):679-684. doi: 10.1177/0018578717726869. Epub 2017 Aug 29.
Information technology, including clinical decision support systems (CDSS), have an increasingly important and growing role in identifying opportunities for antimicrobial stewardship-related interventions. The aim of this study was to describe and compare types and outcomes of CDSS-built antimicrobial stewardship alerts. Fifteen alerts were evaluated in the initial antimicrobial stewardship program (ASP) review. Preimplementation, alerts were reviewed retrospectively. Postimplementation, alerts were reviewed in real-time. Data collection included total number of actionable alerts, recommendation acceptance rates, and time spent on each alert. Time to de-escalation to narrower spectrum agents was collected. In total, 749 alerts were evaluated. Overall, 306 (41%) alerts were actionable (173 preimplementation, 133 postimplementation). Rates of actionable alerts were similar for custom-built and prebuilt alert types (39% [53 of 135] vs 41% [253 of 614], = .68]. In the postimplementation group, an intervention was attempted in 97% of actionable alerts and 70% of interventions were accepted. The median time spent per alert was 7 minutes (interquartile range [IQR], 5-13 minutes; 15 [12-17] minutes for actionable alerts vs 6 [5-7] minutes for nonactionable alerts, < .001). In cases where the antimicrobial was eventually de-escalated, the median time to de-escalation was 28.8 hours (95% confidence interval [CI], 10.0-69.1 hours) preimplementation vs 4.7 hours (95% CI, 2.4-22.1 hours) postimplementation, < .001. CDSS have played an important role in ASPs to help identify opportunities to optimize antimicrobial use through prebuilt and custom-built alerts. As ASP roles continue to expand, focusing time on customizing institution specific alerts will be of vital importance to help redistribute time needed to manage other ASP tasks and opportunities.
包括临床决策支持系统（CDSS）在内的信息技术，在识别抗菌药物管理相关干预机会方面发挥着越来越重要且不断增长的作用。本研究的目的是描述和比较基于CDSS生成的抗菌药物管理警报的类型及结果。在初始抗菌药物管理计划（ASP）审查中评估了15条警报。在实施前，对警报进行回顾性审查。实施后，对警报进行实时审查。数据收集包括可操作警报的总数、建议接受率以及处理每条警报所花费的时间。收集了降阶梯使用窄谱抗菌药物的时间。总共评估了749条警报。总体而言，306条（41%）警报是可操作的（实施前173条，实施后133条）。定制警报类型和预建警报类型的可操作警报率相似（39%[135条中的53条]对41%[614条中的253条]，P = 0.68）。在实施后组中，97%的可操作警报尝试了干预措施，70%的干预措施被接受。每条警报的中位处理时间为7分钟（四分位间距[IQR]，5 - 13分钟；可操作警报为15[12 - 17]分钟，不可操作警报为6[5 - 7]分钟，P < 0.001）。在抗菌药物最终降阶梯的病例中，实施前降阶梯的中位时间为28.8小时（95%置信区间[CI]，10.0 - 69.1小时），实施后为4.7小时（95%CI，2.4 - 22.1小时），P < 0.001。CDSS在抗菌药物管理计划中发挥了重要作用，通过预建和定制警报帮助识别优化抗菌药物使用的机会。随着抗菌药物管理计划的作用不断扩大，将时间集中于定制机构特定警报对于帮助重新分配管理其他抗菌药物管理任务和机会所需的时间至关重要。
