Tiwari Vikram, Furman William R, Sandberg Warren S
From the Department of Anesthesiology, Vanderbilt University School of Medicine, Nashville, Tennessee.
Anesthesiology. 2014 Jul;121(1):171-83. doi: 10.1097/ALN.0000000000000287.
Precise estimates of final operating room demand can only be made 1 or 2 days before the day of surgery, when it is harder to adjust staffing to match demand. The authors hypothesized that the accumulating elective schedule contains useful information for predicting final case demand sufficiently in advance to readily adjust staffing.
The accumulated number of cases booked was recorded daily, from which a usable dataset comprising 146 consecutive surgical days (October 10, 2011 to May 7, 2012, after removing weekends and holidays), and each with 30 prior calendar days of booking history, was extracted. Case volume prediction was developed by extrapolation from estimates of the fraction of total cases booked each of the 30 preceding days, and averaging these with linear regression models, one for each of the 30 preceding days. Predictions were verified by comparison with actual volume.
The elective surgery schedule accumulated approximately three cases per day, settling at a mean ± SD final daily volume of 117 ± 12 cases. The model predicted final case counts within 8.27 cases as far in advance as 14 days before the day of surgery. In the last 7 days before the day of surgery, the model predicted the case count within seven cases 80% of the time. The model was replicated at another smaller hospital, with similar results.
The developing elective schedule predicts final case volume weeks in advance. After implementation, overly high- or low-volume days are revealed in advance, allowing nursing, ancillary service, and anesthesia managers to proactively fine-tune staffing up or down to match demand.
只有在手术当天前1天或2天才能对最终手术室需求进行精确估计，而此时要调整人员配置以满足需求则更加困难。作者推测，累积的择期手术安排包含有用信息，能够提前足够长的时间预测最终病例需求，以便轻松调整人员配置。
每天记录已预约的病例累积数量，从中提取一个可用数据集，该数据集包括146个连续手术日（2011年10月10日至2012年5月7日，去除周末和节假日），每个手术日都有之前30个日历日的预约历史记录。通过对前30天每天预约的病例占总病例数的比例进行估计，并将这些估计值与线性回归模型（前30天每天一个模型）进行平均，从而得出病例数量预测值。通过与实际数量进行比较来验证预测结果。
择期手术安排每天大约累积3例病例，最终日均病例数稳定在117±12例（均值±标准差）。该模型在手术日前14天就能提前预测最终病例数，误差在8.27例以内。在手术日前最后7天，该模型80%的时间内预测病例数的误差在7例以内。该模型在另一家较小的医院进行了复制，结果相似。
不断发展的择期手术安排能提前数周预测最终病例数量。实施后，可以提前发现手术量过高或过低的日期，使护理、辅助服务和麻醉管理人员能够主动上调或下调人员配置以满足需求。
