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计算机化临床决策支持在潜在不适当药物中的应用。

Utilization of computerized clinical decision support for potentially inappropriate medications.

机构信息

Division of Geriatric Medicine, Department of Medicine, University of Alberta, Edmonton, Alberta, Canada.

Chief Medical Information Office, Alberta Health Services, Division of Critical Care Medicine, University of Alberta, Edmonton, Alberta, Canada.

出版信息

Clin Interv Aging. 2019 Apr 29;14:753-762. doi: 10.2147/CIA.S192927. eCollection 2019.

DOI:10.2147/CIA.S192927
PMID:31118596
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6500432/
Abstract

Electronic medical record (EMR) alerts may inform point of care decisions, including the decision to prescribe potentially inappropriate medications (PIM) identified in the Beers criteria. EMR alerts may not be considered relevant or informative in the clinician context, leading to a phenomenon colloquially known as "alert fatigue." To assess the frequency of clinical interaction with EMR alerts and associated deprescribing behaviors in ambulatory settings. This is a retrospective observational study in two ambulatory clinics (the Kaye Edmonton Clinic Senior's Clinic and the Lynnwood Family Practice Clinic) in Edmonton over an observational period of 30 months. Statistical analysis was done using descriptive statistics, chi-square and regression analysis. The reminder performance for interactions with the alert was 17.2% across the two clinics. The Number Needed to Remind (NNR) or mean number of alerts shown on clinician screens prior to a single interaction of any kind with the alert was 5.8. When actions were defined as a deprescribing (ie discontinuation) event that was related to the alert and that particular interaction in the EMR, the reminder performance was 1.2%, for an NNR of 82.8. The configuration of alerts in the EMR was not associated with a clinically detectable increase in the uptake of the Beers criteria for high hazard medications.

摘要

电子病历 (EMR) 警报可能会为即时决策提供信息,包括根据 Beers 标准开出潜在不适当药物 (PIM) 的决策。在临床医生的背景下,EMR 警报可能被认为不相关或没有信息量,从而导致一种通俗称为“警报疲劳”的现象。评估在门诊环境中与 EMR 警报进行临床互动的频率以及相关的减药行为。这是一项在埃德蒙顿的两个门诊诊所(Kaye Edmonton 诊所老年人诊所和 Lynnwood 家庭实践诊所)进行的回顾性观察研究,观察期为 30 个月。使用描述性统计、卡方检验和回归分析进行统计分析。在这两个诊所中,与警报互动的提醒性能为 17.2%。在屏幕上显示任何类型的与警报的单一交互之前,需要提醒的数量 (NNR) 或平均警报数量为 5.8。当将操作定义为与警报相关的减药(即停药)事件,并且是 EMR 中的特定交互事件时,提醒性能为 1.2%,NNR 为 82.8。EMR 中的警报配置与接受 Beers 标准中高危药物的比例的临床可检测增加无关。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e71a/6500432/9c050210796e/CIA-14-753-g0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e71a/6500432/9c050210796e/CIA-14-753-g0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e71a/6500432/9c050210796e/CIA-14-753-g0001.jpg

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