血小板库存管理:纳入数据驱动的需求预测
Maryam Motamedi1, Jessica Dawson1, Na Li1,2,3
1Department of Computing and Software, McMaster University, Hamilton, L8S 4L8, Ontario, Canada.
Health care management science
|May 2, 2025
概括
这项研究引入了一个数据驱动的模型来管理血小板库存,旨在减少短缺和浪费. 调查结果显示,结合需求预测可以改善库存管理,即使有预测错误.
科学领域:
- 运营研究 运营研究
- 医疗保健管理的管理
- 供应链优化 供应链优化
背景情况:
- 血小板产品对于治疗癌症等严重疾病至关重要,但由于保质期短,价格昂贵.
- 管理血小板库存是具有挑战性的,因为需求不确定和高度可变.
- 目前的库存管理策略很难有效地平衡减少短缺和浪费.
研究的目的:
- 为血小板产品开发和评估数据驱动的库存管理模型.
- 将需求预测纳入库存管理,以优化订单政策.
- 为了尽量减少血小板短缺和输血系统中的浪费.
主要方法:
- 开发了一种新的库存管理模型,利用对血小板产品的需求预测.
- 员工预测依赖的目标库存水平以指导订单政策.
- 利用了2016-2018年每日血小板输血的大型临床数据集,用于为四家医院提供服务的集中血液分发中心.
主要成果:
- 拟议的数据驱动政策有效地减少了血小板产品的短缺和浪费.
- 该模型表现出弹性,随着系统规模的增加 (例如,通过需求聚合和库存聚合),可以容忍更大的预测错误.
- 灵敏度分析证实了该模型的稳定性,并表明不太频繁而不是每天订单的可行性.
结论:
- 将需求预测纳入库存管理可以显著提高血小板产品供应链效率.
- 开发的模型提供了一个切实可行的解决方案,以减少与血小板浪费和短缺相关的成本.
- 这种方法支持更可持续和可靠的输血服务.
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