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用于检测不良事件的急诊科触发工具的多中心测试

Multicenter Test of an Emergency Department Trigger Tool for Detecting Adverse Events.

作者信息

Griffey Richard T, Schneider Ryan M, Sharp Brian R, Pothof Jeff, Vrablik Marie C, Granzella Nic, Todorov Alexandre A, Adler Lee

机构信息

From the Division of Emergency Medicine, Washington University School of Medicine, St. Louis, Missouri.

Department of Emergency Medicine, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin.

出版信息

J Patient Saf. 2021 Dec 1;17(8):e843-e849. doi: 10.1097/PTS.0000000000000516.

Abstract

OBJECTIVES

Traditional approaches to safety and quality screening in the emergency department (ED) are porous and low yield for identifying adverse events (AEs). A better approach may be in the use of trigger tool methodology. We recently developed a novel ED trigger tool using a multidisciplinary, multicenter approach. We conducted a multicenter test of this tool and assess its performance.

METHODS

In design and participants, we studied the ED trigger tool for a 13-month period at four EDs. All patients 18 years and older with Emergency Severity Index acuity levels of 1 to 3 seen by a provider were eligible. Reviewers completed standardized training modules. Each site reviewed 50 randomly selected visits per month. A first-level reviewer screened for presence of predefined triggers (findings that increase the probability of an AE). If no trigger is present, the review is deemed complete. When present, a trigger prompts an in-depth review for an AE. Any event identified is assigned a level of harm using the Medication Event Reporting and Prevention (MERP) Index, ranging from a near miss (A) to patient death (I). Events are noted as present on arrival or in the ED, an act of commission or omission, and are assigned one of four event categories. A second-level physician performs a confirmatory review of all AEs and independently reviews 10% of cases to estimate the false-negative rate. All AEs or potential AEs were reviewed in monthly group calls for consensus on findings. The primary outcome is the proportion of visits in which an AE is identified, overall and by site. Secondary outcomes include categories of events, distribution of harm ratings, and association of AEs with sociodemographic and clinical factors and triggers. We present sociodemographic data and details about AEs and results of logistic regression for associations of AEs with of triggers, sociodemographics, and clinical variables.

RESULTS

We captured 2594 visits that are representative, within site, of their patient population. Overall, the sample is 64% white, 54% female, and with a mean age of 51. Variability is observed between sites for age, race, and insurance, but not sex. A total of 240 events were identified in 228 visits (8.8%) of which 53.3% were present on arrival, 19.7% were acts of omission, and 44.6% were medication-related, with some variability across sites. A MERP F score (contributing to need for admission, higher level of care, or prolonged hospitalization) was the most common severity level (35.4% of events). Overall, 185 (77.1%) of 240 events involved patient harm (MERP level ≥ E), affecting 175 visits (6.7%). Triggers were present in 951 visits (36.6%). Presence of any trigger was strongly associated with an AE (adjusted odds ratio = 4.6, 95% confidence interval = 3.2-6.6). Ten triggers were individually associated with AEs (adjusted odds ratio = 2.1-7.7). Variability was observed across sites in individual trigger associations, event rates, and categories, but not in severity ratings of events. The overall false-negative rate was 6.1%.

CONCLUSIONS

The trigger tool approach was successful in identifying meaningful events. The ED trigger tool seems to be a promising approach for identifying all-cause harm in the ED.

摘要

目的

急诊科(ED)传统的安全与质量筛查方法存在漏洞,识别不良事件(AE)的效率较低。一种更好的方法可能是使用触发工具方法。我们最近采用多学科、多中心方法开发了一种新型的急诊科触发工具。我们对该工具进行了多中心测试并评估其性能。

方法

在设计和参与者方面,我们在四个急诊科对该急诊科触发工具进行了为期13个月的研究。所有18岁及以上、由医护人员诊治且急诊严重程度指数为1至3级的患者均符合条件。评审人员完成了标准化培训模块。每个站点每月审查50次随机选择的就诊病例。一级评审人员筛查预定义触发因素(增加不良事件发生概率的发现)的存在情况。如果没有触发因素,则评审视为完成。当存在触发因素时,会促使对不良事件进行深入审查。任何识别出的事件都使用药物事件报告和预防(MERP)指数进行危害程度分级,范围从险些发生(A)到患者死亡(I)。记录事件是在到达时还是在急诊科发生,是作为作为还是不作为,并将其归入四个事件类别之一。二级医生对所有不良事件进行确认性审查,并独立审查10%的病例以估计假阴性率。所有不良事件或潜在不良事件在每月的小组会议上进行审查,以就结果达成共识。主要结果是识别出不良事件的就诊比例,包括总体比例和各站点的比例。次要结果包括事件类别、危害评级分布以及不良事件与社会人口统计学和临床因素及触发因素的关联。我们展示了社会人口统计学数据、关于不良事件的详细信息以及不良事件与触发因素、社会人口统计学和临床变量关联的逻辑回归结果。

结果

我们收集了2594次就诊病例,这些病例在各站点内代表了其患者群体。总体而言,样本中64%为白人,54%为女性,平均年龄为51岁。在年龄、种族和保险方面,各站点之间存在差异,但在性别方面没有差异。在228次就诊(8.8%)中总共识别出240起事件,其中53.3%在到达时就已存在,19.7%是不作为事件,44.6%与药物相关,各站点之间存在一定差异。MERP F级(导致需要住院、更高水平的护理或延长住院时间)是最常见的严重程度级别(占事件的35.4%)。总体而言,240起事件中有185起(77.1%)涉及患者伤害(MERP级别≥E),影响了175次就诊(占6.7%)。951次就诊(36.6%)中存在触发因素。任何触发因素的存在都与不良事件密切相关(调整后的优势比=4.6,95%置信区间=3.2 - 6.6)。有10个触发因素分别与不良事件相关(调整后的优势比=2.1 - 7.7)。在各个触发因素关联、事件发生率和类别方面,各站点之间存在差异,但在事件的严重程度评级方面没有差异。总体假阴性率为6.1%。

结论

触发工具方法成功识别了有意义的事件。急诊科触发工具似乎是一种在急诊科识别全因伤害的有前景的方法。

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