药品不规则需求预测研究——以ABC医疗中心医院为例

Xu Luochen, N. Hasachoo
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引用次数: 2

摘要

随着ABC大学新医疗中心医院于2018年开业,患者的快速增加导致需要改善药房运营。特别是案例研究医院,由于某些药品的需求不规律,难以预测,导致库存管理效率低下。本文的主要目的是寻找一种预测具有不规则需求模式的药物的方法。首先,利用变异系数和平均需求间隔来定义药品需求模式;其次,比较了移动平均、加权移动平均、指数平滑和Holt Winter Additive四种常用预测模型的预测误差。第三,应用更具体的不规则预测模型,包括Croston的方法、TSB方法(Teunter、Syntetos和Babai的方法)、SBA方法(Syntetos- boylan近似方法)和Kalaya等人的方法(2019)方法,看其是否优于一般模型。研究发现,当使用特定模型进行非常规需求预测时,结果会更好。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The Study of Irregular Demand Forecasting for Medicines: The Case Study of ABC Medical Center Hospital
With the new medical center hospital of ABC university opened in 2018, a rapid increase in patients leads to a need to improve in pharmacy operations. Especially the case study hospital is now affected by the irregular demand in some medicine which was difficult to forecast and lead to inefficient inventory management. The main objective of this paper is to find a method to forecast a medicine with an irregular demand pattern. Firstly, the Coefficient of variation and Average inter-demand Interval were used for defining the medicine demand pattern. Secondly, forecasting error compared from applying four general forecasting models including Moving Average, Weight Moving Average, Exponential Smoothing, and Holt Winter Additive. Thirdly, apply a more specific model for Irregular forecasting, including Croston's method, TSB method (Teunter, Syntetos, and Babai's method), SBA method (Syntetos-Boylan approximation method), and Kalaya et al’ approach (2019) approach to see if it is superior to the general models. The finding found better results when using a specific model for irregular demand forecasting.
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