Using Singular Spectrum Analysis to obtain staffing level requirements in emergency units

Using Singular Spectrum Analysis to obtain staffing level requirements in emergency units
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使用奇异谱分析来获取应急部门的人员配备水平要求

DOI:
10.1057/jors.2013.41
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发表时间:
2017
影响因子:
3.6
通讯作者:
Gillard J
Gillard J
中科院分区:
管理学4区
文献类型:
--
作者:
Gillard J

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许多运筹学(OR)技术使用历史数据来填充模型输入参数。虽然这些模式中的大多数考虑了输入的随机变化,但它们不一定考虑到季节变化和其他可能出现的随机效应。手术室的主要应用之一是在医疗保健领域,医疗保健系统面临的压力越来越大,这对那些计划提供此类服务的人产生了重大影响。应对不断增长的医疗保健需求,以及医疗机构抵达人数的不稳定性,使得医疗保健提供建模成为手术室中最具挑战性的领域之一。本文建议使用一种相对现代的时间序列技术,奇异谱分析(SSA),以改进现有的算法,以提供所需的人员配备水平。该方法用一家大型教学医院急诊科的数据进行了论证。利用时间相关排队理论和SSA,得到了人员配备水平。本文采用加权均方误差测量方法分析了该技术的性能。
Many operational research (OR) techniques use historical data to populate model input parameters. Although the majority of these models take into account stochastic variation of the inputs, they do not necessarily take into account seasonal variations and other stochastic effects that might arise. One of the major applications of OR lies within healthcare, where ever increasing pressure on healthcare systems is having major implications on those who plan the provision of such services. Coping with growing demand for healthcare, as well as the volatile nature of the number of arrivals at a healthcare facility makes modelling healthcare provision one of the most challenging fields of OR. This paper proposes the use of a relatively modern time series technique, Singular Spectrum Analysis (SSA), to improve existing algorithms that give required staffing levels. The methodology is demonstrated using data from a large teaching hospital's emergency unit. Using time dependent queueing theory, as well as SSA, staffing levels are obtained. The performance of our technique is analysed using a weighted mean square error measure, introduced in this paper.
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