The benefits (or detriments) of adapting to demand disruptions in a hospital pharmacy with supply chain disruptions

被引:0
|
作者
Czerniak, Lauren L. [1 ]
Lavieri, Mariel S. [1 ]
Daskin, Mark S. [1 ]
Byon, Eunshin [1 ]
Renius, Karl [2 ]
Sweet, Burgunda, V [3 ]
Leja, Jennifer [2 ]
Tupps, Matthew A. [2 ]
机构
[1] Univ Michigan, Dept Ind & Operat Engn, 1205 Beal Ave, Ann Arbor, MI 48109 USA
[2] Univ Michigan, Michigan Med, Dept Pharm Serv, 1500 East Med Ctr Dr, Ann Arbor, MI 48109 USA
[3] Univ Michigan, Coll Pharm, 428 Church St, Ann Arbor, MI 48109 USA
基金
美国国家科学基金会;
关键词
Inventory management; Supply chain management; Simulation; Pharmaceutical drugs; Healthcare; Operations research; Operations management; DRUG SHORTAGES; INVENTORY MANAGEMENT; OPTIMIZATION; MODEL;
D O I
10.1007/s10729-024-09686-3
中图分类号
R19 [保健组织与事业(卫生事业管理)];
学科分类号
摘要
Supply chain disruptions and demand disruptions make it challenging for hospital pharmacy managers to determine how much inventory to have on-hand. Having insufficient inventory leads to drug shortages, while having excess inventory leads to drug waste. To mitigate drug shortages and waste, hospital pharmacy managers can implement inventory policies that account for supply chain disruptions and adapt these inventory policies over time to respond to demand disruptions. Demand disruptions were prevalent during the Covid-19 pandemic. However, it remains unclear how a drug's shortage-waste weighting (i.e., concern for shortages versus concern for waste) as well as the duration of and time between supply chain disruptions influence the benefits (or detriments) of adapting to demand disruptions. We develop an adaptive inventory system (i.e., inventory policies change over time) and conduct an extensive numerical analysis using real-world demand data from the University of Michigan's Central Pharmacy to address this research question. For a fixed mean duration of and mean time between supply chain disruptions, we find a drug's shortage-waste weighting dictates the magnitude of the benefits (or detriments) of adaptive inventory policies. We create a ranking procedure that provides a way of discerning which drugs are of most concern and illustrates which policies to update given that a limited number of inventory policies can be updated. When applying our framework to over 300 drugs, we find a decision-maker needs to update a very small proportion of drugs (e.g.,<5%) at any point in time to get the greatest benefits of adaptive inventory policies.
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页数:30
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