Department of Emergency Medicine, Washington University School of Medicine, St. Louis, MO.
Department of Emergency Medicine, Washington University School of Medicine, St. Louis, MO.
Ann Emerg Med. 2022 Dec;80(6):528-538. doi: 10.1016/j.annemergmed.2022.05.037. Epub 2022 Aug 1.
The Emergency Department Trigger Tool (EDTT) is a novel approach to adverse event detection in the ED. We previously described the derivation, validation, and high-level performance of this tool. Here we further detail adverse events detected to demonstrate the utility of the EDTT and how it might be used for quality improvement.
This is a secondary analysis of data from a retrospective observational study. We ran the EDTT (a computerized query for triggers) on 13 months of ED visit data, reviewing 5,582 selected records using a typical 2-tiered trigger tool approach. The adverse events detected were categorized by place of occurrence (in the ED versus present on arrival), severity, omission/commission, and type using a taxonomy with categories, subcategories, and up to 3 cross-cutting modifiers. We present adverse event data in detail, focusing in turn on each of these descriptors (severity, event types, and cross-cutting themes) and highlight opportunities identified for targeted improvement.
We identified 458 adverse events occurring in the ED for a 13-month period, 10% of which required urgent intervention. Nearly all (90%) were acts of commission. Events resulting in harm were most often related to medications administered and patient care. Common cross-cutting event types included adverse events related to bleeding, opioids, and the use of propofol. Most adverse events (80%) led to temporary harm.
The EDTT identifies a broad spectrum of adverse event types, allowing a review by severity, frequency, and type to better understand existing levels of harm in the ED and identify targets for quality improvement. A multicenter study of the EDTT is currently underway, which will contribute additional power and assess generalizability.
急诊科触发工具（EDTT）是一种新颖的急诊科不良事件检测方法。我们之前描述了该工具的推导、验证和高级性能。在这里，我们进一步详细介绍了检测到的不良事件，以展示 EDTT 的实用性以及如何将其用于质量改进。
这是一项回顾性观察研究数据的二次分析。我们在 13 个月的 ED 就诊数据上运行 EDTT（用于触发的计算机查询），使用典型的两级触发工具方法审查了 5582 份选定的记录。根据发生地点（在 ED 内或就诊时）、严重程度、遗漏/失误以及使用包含类别、子类别和最多 3 个交叉修饰符的分类法检测到的不良事件进行分类。我们详细介绍了不良事件数据，依次重点介绍了这些描述符（严重程度、事件类型和交叉主题）中的每一个，并强调了确定的有针对性改进的机会。
我们在 13 个月期间确定了 458 例发生在 ED 的不良事件，其中 10%需要紧急干预。几乎所有（90%）都是因失误导致的。导致伤害的事件最常与给予的药物和患者护理有关。常见的交叉主题事件类型包括与出血、阿片类药物和丙泊酚使用相关的不良事件。大多数不良事件（80%）导致暂时伤害。
EDTT 可识别广泛的不良事件类型，可根据严重程度、频率和类型进行审查，以更好地了解 ED 中现有的伤害水平，并确定质量改进的目标。目前正在进行 EDTT 的多中心研究，这将增加额外的动力并评估其普遍性。
