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预测血液制品的需求:朝着一种易腐烂产品的库存管理

Sanjay Kumar Thakur^1,2, Anil Kumar Sinha¹, Dinesh Kumar Negi²

¹P.G. Department of Zoology, Veer Kunwar Singh University, Ara, Bihar-802301, India.

|February 14, 2024

概括

使用简单平均与平均年增量 (SAMAI) 方法预测血液产品需求,可以显著减少库存并防止短缺. 与其他预测模型相比,SAMAI表现出更高的准确性.

科学领域:

医疗保健管理的管理
运营研究运营研究
生物统计学生物统计学

背景情况:

准确预测血液产品消费量对于优化库存水平和防止短缺至关重要.
现有的预测方法可能不适合所有医疗机构,特别是那些缺乏先进的统计专业知识的医疗机构.

研究的目的:

开发和评估血液制品的"平均年增量简单平均值" (SAMAI) 时间序列预测方法.
为了比较SAMAI方法与ARIMA,比率与趋势和简单平均方法的性能.

主要方法:

2017年1月至2022年12月使用的每月血液成分需求数据 (数据集I).
2020-2021年从事从前几年的平均月度值,以减轻COVID-19大流行影响 (数据集II).
在2023年1月至7月的测试数据上使用平均绝对百分比误差 (MAPE) 评估模型准确性.

主要成果:

与简单平均值,比率与趋势和SARIMA方法相比,SAMAI方法实现了较低的整体平均绝对百分比误差 (MAPE).
对于数据集I,SAMAI显示MAPE值为18.82% (献血),13.39% (血液问题),14.52% (RDP问题) 和27.64% (FFP问题).
所有测试的方法在数据集II中显示了较低的平均MAPE,SAMAI始终优于其他方法.

结论:

SAMAI 方法是一种简单,有效,易于实施的工具,用于预测血液成分需求.
萨马伊可以改善库存管理,减少订单频率高达60%,并减少库存水平40%.
这种方法适用于医疗机构,不需要先进的统计知识.

关键词:

献血是献血,献血是献血,献血是献血,献血是献血.血液问题血液问题需求预测需要预测.库存管理库存管理

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