Clouston Robin, Atkinson Paul, Canales Donaldo D, Fraser Jacqueline, Sohi Dylan, Lee Scott, Howlett Michael
Department of Emergency Medicine, Dalhousie University, Saint John Regional Hospital, 400 University Avenue, Saint John, NB, E2L 4L2, Canada.
Research Services, Horizon Health Network, Saint John, NB, Canada.
CJEM. 2022 Jan;24(1):23-26. doi: 10.1007/s43678-021-00098-8. Epub 2021 Mar 21.
Emergency department (ED) crowding compromises patient outcomes. Existing crowding measures are complex and difficult to use in real-time. This study evaluated readily available single flow variables as crowding measures.
Over 2 weeks in a tertiary Canadian ED, we recorded the following potential crowding measures during 168 consecutive two-hour study intervals: total ED patients (census), patients in beds, patients in waiting rooms, patients in treatment areas awaiting MD assessment; number of inpatients boarding, and ED occupancy. We also calculated four complex crowding scores-NEDOCS, EDWIN, ICMED, and a local modification of NEDOCS. We performed ROC analyses to assess the predictive validity of these measures against a reference standard of physician perception of crowding.
We gathered data for 144 (63.9%) of 168 study intervals. ED census correlated strongly with crowding (AUC = 0.82, 95% CI 0.76-0.89), as did ED occupancy (AUC = 0.75, 95% CI 0.66-0.83). Their performance was similar to NEDOCS (AUC = 0.80) and to the local modification of NEDOCS (AUC = 0.83).
ED occupancy as a single measure has similar predictive accuracy to complex crowding scores and is easily generalizable to diverse emergency departments. Real-time tracking of this simple indicator could be used to prompt investigation and implementation of crowding interventions.
急诊科拥挤会影响患者治疗结果。现有的拥挤程度衡量方法复杂,难以实时应用。本研究评估了易于获取的单一流量变量作为拥挤程度衡量指标。
在加拿大一家三级急诊科进行了为期2周的研究,我们在连续168个两小时的研究时段内记录了以下潜在的拥挤程度衡量指标:急诊科患者总数(普查)、住院患者数、候诊室患者数、治疗区域等待医生评估的患者数、住院患者滞留人数以及急诊科占用率。我们还计算了四个复杂的拥挤程度评分——NEDOCS、EDWIN、ICMED以及NEDOCS的局部修正版。我们进行了ROC分析,以评估这些指标相对于医生对拥挤程度感知的参考标准的预测效度。
我们收集了168个研究时段中144个时段(63.9%)的数据。急诊科普查人数与拥挤程度密切相关(AUC = 0.82,95% CI 0.76 - 0.89),急诊科占用率也是如此(AUC = 0.75,95% CI 0.66 - 0.83)。它们的表现与NEDOCS(AUC = 0.80)以及NEDOCS的局部修正版(AUC = 0.83)相似。
急诊科占用率作为单一指标,其预测准确性与复杂的拥挤程度评分相似,并且易于推广到不同的急诊科。对这一简单指标进行实时跟踪可用于促使对拥挤干预措施进行调查和实施。