Development and validation of a new index to measure emergency department crowding
Development and validation of a new index to measure emergency department crowding
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DOI：
10.1197/s1069-6563(03)00311-7
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发表时间：
2003-09-01
影响因子：
4.4
通讯作者：
Perez, I
中科院分区：
文献类型：
--
作者：
Bernstein, SL;Verghese, V;Perez, I
目的：建立急诊科（艾德）拥挤和繁忙的定量测量方法。研究方法：2002年春季，一项为期五周的研究在一个城市教学艾德比较了一个新的指数（急诊科工作指数[EDWIN]）与主治医生和护士的拥挤评级。EDWIN定义为Sigman（i）t（i）/N-a（B-T - B-A），其中n（i）=分诊类别i中艾德的患者数量，t（i）=分诊类别，N-a =值班主治医生数量，B-T =治疗间数量，B-A =急诊室收治患者数量。所用的分诊系统是急诊严重程度指数（ESI），通过颠倒分诊类别的排名进行了修改;即，ESI评分为I代表最不急性的患者，5代表病情最严重的患者。在60个8小时轮班的便利样本中，每两小时计算一次EDWIN。每次测量时，主治医师和护士使用Likert量表估计忙碌室的艾德有多繁忙/拥挤。护士和医生评估的平均值，并与EDWIN评分进行比较。用SPSS 10.0（SPSS Inc.，芝加哥，IL）。结果：共有2，647名18岁及以上的患者在连续35天的225个时间点进行了评估。护士和医生表现出良好的评价者间拥挤评估协议（加权kappa 0.61，95%置信区间= 0.53至0.69）。当艾德被评定为不忙碌、一般和非常忙碌时，中位EDWIN评分和四分位距（IQR）分别为1.07（IQR = 0.80 - 1.55）、1.55（IQR = 1.16 - 1.93）和1.83（IQR = 1.42 - 2.45）（p < 0.001）。艾德在17个时间段（占所有时间段的6.5%）进行了分流，EDWIN中位数为2.77（IQR = 1.83至3.63），而未进行分流时的EDWIN为1.45（IQR = 1.05至2.00）（p < 0.001）。EDWIN评分与选择作为次要终点的各种护理过程指标弱相关。结论：EDWIN与工作人员对艾德拥挤和分流的评估相关。该指数可以编入跟踪软件，用作“仪表板”，在艾德接近危机时提醒员工。如果在其他研究中心得到验证，EDWIN可能会提供一个工具来比较不同ED之间的拥挤程度。
Objectives: To develop a quantitative measure of emergency department (ED) crowding and busyness. Methods: A five-week study in spring 2002 in an urban teaching ED compared a new index (the Emergency Department Work Index [EDWIN]) with attending physician and nurse ratings of crowding. EDWIN is defined as Sigman(i)t(i)/N-a(B-T - B-A), where n(i) = number of patients in the ED in triage category i, t(i) = triage category, N-a = number of attending physicians on duty, B-T = number of treatment bays, and B-A = number of admitted patients in the ED. The triage system used is the Emergency Severity Index (ESI), which was modified by reversing the ranking of triage categories; that is, an ESI score of I represented the least acute patient and 5 the sickest. EDWIN was calculated every two hours in a convenience sample of 60 eight-hour shifts. With each measurement, the charge attending physician and nurse estimated how busy/crowded the ED was, using a Likert scale. Nurse and physician assessments were averaged and compared with EDWIN scores. Data were analyzed with SPSS 10.0 (SPSS Inc., Chicago, IL). Results: A total of 2,647 patients aged 18 years and older were assessed at 225 time points over 35 consecutive days. Nurses and physicians showed good interrater agreement of crowding assessment (weighted kappa 0.61, 95% confidence interval = 0.53 to 0.69). Median EDWIN scores and interquartile ranges (IQRs) when the ED was rated as not busy, average, and very busy were 1.07 (IQR = 0.80 to 1.55), 1.55 (IQR = 1.16 to 1.93), and 1.83 (IQR = 1.42 to 2.45) (p < 0.001). The ED was on diversion for 17 time blocks (6.5% of all blocks), with a median EDWIN of 2.77 (IQR = 1.83 to 3.63), compared with an EDWIN of 1.45 (IQR = 1.05 to 2.00) when not on diversion (p < 0.001). EDWIN scores correlated weakly with various process-of-care measures chosen as secondary end points. Conclusions: EDWIN correlated well with staff assessment of ED crowding and diversion. The index can be programmed into tracking software for use as a "dashboard" to alert staff when the ED is approaching crisis. If validated across other sites, EDWIN may provide a tool to compare crowding levels among different EDs.