一个Excel预测模型,以帮助决策,影响医院资源/床位的利用-医院接收急诊室病人的能力

W. Stout, B. Tawney
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引用次数: 15

摘要

在复杂系统中,很难辨别各组成部分之间相互作用的影响。分析师可以使用Microsoft Excel对内部系统动态进行初步评估。通常,在医院环境中,早期数据识别显示为速率估计-每小时入院数与每小时出院数。例如,管理部门可能希望评估容纳从急诊科出院的患者随后入住内科(DOM)的能力,以及其他来源对内科床位容量的需求。本文探讨了电子表格模型的概念发展和实际应用。具体功能包括:按小时构建查找表,其中包含最小和最大速率的估计,使用randbetween函数从均匀分布中随机选择模型输入,开发频率分布以协助输出解释,说明条件格式,输出图形等。人们可以观察到基于单位开放床位和午夜普查的每小时患者波动的多个样本。等待的患者数量可以显示在不同的系统利用率水平。当利用率接近80%时,患者等待时间不成比例地增加。电子表格模型是一个动态的、可视化的说明,说明各个过程时间的变化如何影响整个过程能力。它的使用主要是作为一个教学工具,为那些新的仿真建模。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An Excel forecasting model to aid in decision making that affects hospital resource/bed utilization - hospital capability to admit emergency room patients
In complex systems it is difficult to discern the effects of interactions among component parts. Analysts can use Microsoft Excel for a preliminary assessment of internal systems dynamics. Often, in the hospital environment early data identification surfaces as rate estimates - admits per hour versus discharges per hour. For example, management may wish to assess capability to accommodate patients discharged from the emergency department for subsequent admission to the department of medicine (DOM) as well as demands on DOM bed capacity from other sources. This paper explores conceptual development and practical application of the spreadsheet model. Particular features include: constructing lookup tables by hour of day containing estimates of minimum and maximum rates, using the randbetween function to randomly select model inputs from a uniform distribution, developing frequency distributions to assist in output interpretation, illustrating conditional formatting, output graphing, etc. One can observe multiple samples of hourly patient fluctuations based on unit open beds and midnight census. Number of patients waiting can be shown at varying levels of system utilization. As utilization approaches approximately eighty percent, patient waiting time increases disproportionately. The spreadsheet model is a dynamic, visual illustration of how variation in individual process times can affect total process capability. Its use is primarily intended as a teaching tool for those new to simulation modeling.
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