Rotstein Z, Wilf-Miron R, Lavi B, Shahar A, Gabbay U, Noy S
The Department of Medical Management, The Chaim Sheba Medical Center, Tel Hashomer, Israel.
Am J Emerg Med. 1997 Oct;15(6):596-9. doi: 10.1016/s0735-6757(97)90166-2.
Using a public hospital's computerized database, we formulated a statistical model to explain emergency department (ED) patient volume for better staffing and resource allocation. All patients visiting the ED over a 3-year period were included in this retrospective study. Each observation described the total daily number of referrals and was defined by the following variables: day of the week, month of the year, holiday/ weekday, relative order in a 3-year sequence, and number of visits to the ED on that day. The statistical method used to build the model was analysis of covariance. Periodicity in average number of daily visits existed for each of the seasonal factors that were examined, repeating every year during the study period. Based on a graphic analysis, the model was defined and explained 65% of the variance during the 3-year study, with a relatively low standard deviation of error. A statistically significant correlation existed between time-related factors and the number of visits to the ED. This statistical model may prove to be of value for planning emergency services, which operate under stressful, unpredictable situations.
利用一家公立医院的计算机数据库，我们构建了一个统计模型来解释急诊科患者数量，以便更好地进行人员配备和资源分配。本回顾性研究纳入了在3年期间前往急诊科就诊的所有患者。每个观测值描述了每日转诊总数，并由以下变量定义：星期几、一年中的月份、节假日/工作日、3年序列中的相对顺序以及当日急诊科就诊次数。用于构建模型的统计方法是协方差分析。在所研究的每个季节性因素中，每日就诊平均数量都存在周期性，在研究期间每年重复出现。基于图形分析，该模型在3年研究期间定义并解释了65%的方差，误差标准差相对较低。时间相关因素与急诊科就诊次数之间存在统计学上的显著相关性。这个统计模型可能被证明对规划在压力大、不可预测的情况下运作的急诊服务有价值。
