Cooper C B, Daniels C E
Pharmacy Services, St. Francis Regional Medical Center, Shakopee, MN 55379.
Am J Hosp Pharm. 1988 Jun;45(6):1333-7.
The development and evaluation of predictive systems to determine staffing needs in a centralized unit dose cart-filling area were studied. Data concerning actual cart-filling time and the hospital's daily census, by total beds and by bed type, were collected over 55 days. Four predictive systems were then developed, as follows: simple average, range average, simple regression, and multiple regression. In addition to these mathematical systems, a pharmacist "best-guess" system was devised, whereby the pharmacist directing the cart-filling area estimated the staffing needs on a daily basis during the trial period. The five systems were then used to predict cart-filling time daily over 14 days. During this time, the actual filling time was recorded and compared with the times predicted by the five systems. The differences among the actual or predicted mean cart-filling times for the five systems were not significant. The pharmacist best-guess system was on average the most accurate in detecting different staffing needs; the advantage of this system is that the pharmacist can evaluate differences in work habits among the scheduled technicians, which the mathematical models would be unable to do. The simple average system correlated well with changes in filling time and most precisely predicted variability in census. Although none of the systems was superior in all respects, a combination of the pharmacist best-guess and simple-average systems appeared to be the best method for predicting daily technician staffing needs in the central cart-filling area.
本研究对用于确定集中式单剂量推车装填区域人员配备需求的预测系统进行了开发和评估。在55天的时间里，收集了有关实际推车装填时间以及医院按总床位数和床位类型划分的每日普查数据。随后开发了四种预测系统，具体如下：简单平均数法、范围平均数法、简单回归法和多元回归法。除了这些数学系统外，还设计了一种药剂师“最佳猜测”系统，即在试验期间，负责推车装填区域的药剂师每天估计人员配备需求。然后使用这五种系统对14天内的每日推车装填时间进行预测。在此期间，记录实际装填时间并与这五种系统预测的时间进行比较。这五种系统实际或预测的平均推车装填时间之间的差异并不显著。药剂师最佳猜测系统在检测不同人员配备需求方面平均最为准确；该系统的优势在于药剂师能够评估排班技术人员工作习惯的差异，而数学模型则无法做到这一点。简单平均数法与装填时间的变化相关性良好，并且最精确地预测了普查中的变异性。虽然没有一个系统在所有方面都表现出色，但药剂师最佳猜测系统和简单平均数法相结合似乎是预测中央推车装填区域每日技术人员配备需求的最佳方法。
