Department of Surgery, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA.
Division of Traumatology, Emergency Surgery, and Surgical Critical Care, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA.
Am J Surg. 2021 Sep;222(3):625-630. doi: 10.1016/j.amjsurg.2021.01.025. Epub 2021 Jan 23.
Emergency general surgery (EGS) lacks mechanisms to compare performance between institutions. Focusing on higher-risk procedures may efficiently identify outliers.
EGS patients were identified from the 2016 State Inpatient Databases of Florida, New York, and Kentucky. Risk-adjusted mortality was calculated as an O:E ratio, generating expected mortality from a model including demographic and procedural factors. Outliers were centers whose 90% confidence intervals excluded 1. This was repeated in several subsets, to determine if these yielded outliers similar to the overall dataset.
We identified 45,430 EGS patients. Overall, 3 high performing centers and 5 low performing centers were identified. Exclusion of appendectomies and cholecystectomies resulted in a remaining data set of 13,569 patients (29.9% of the overall data set), with 2 high performers and 5 low performers. One low performer in the limited data set was not identified in the overall set.
Evaluation of 5 procedures, making up less than a third of EGS, identifies most outliers. A streamlined monitoring procedure may facilitate maintenance of an EGS registry.
急诊普通外科（EGS）缺乏机构间绩效比较的机制。关注高风险手术可能会有效地识别异常值。
从佛罗里达州、纽约州和肯塔基州的 2016 年州住院患者数据库中确定 EGS 患者。风险调整死亡率计算为 O:E 比值，通过包括人口统计学和手术因素的模型计算预期死亡率。异常值是指其 90%置信区间排除 1 的中心。在几个子集中重复此操作，以确定这些子集是否产生与整个数据集相似的异常值。
我们确定了 45430 名 EGS 患者。总体而言，确定了 3 个表现良好的中心和 5 个表现不佳的中心。排除阑尾切除术和胆囊切除术，得到了剩余的 13569 名患者数据集（占整个数据集的 29.9%），其中有 2 个表现良好的中心和 5 个表现不佳的中心。在整个数据集没有发现有限数据集的一个表现不佳的中心。
评估 5 种占 EGS 不到三分之一的手术可以识别大多数异常值。简化监测程序可能有助于维持 EGS 登记处。
