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

Lauren L Czerniak (), Mariel S Lavieri (), Mark S Daskin (), Eunshin Byon (), Karl Renius (), Burgunda V Sweet (), Jennifer Leja () and Matthew A Tupps ()
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Lauren L Czerniak: University of Michigan
Mariel S Lavieri: University of Michigan
Mark S Daskin: University of Michigan
Eunshin Byon: University of Michigan
Karl Renius: University of Michigan
Burgunda V Sweet: University of Michigan
Jennifer Leja: University of Michigan
Matthew A Tupps: University of Michigan

Health Care Management Science, 2024, vol. 27, issue 4, No 3, 525-554

Abstract: Abstract 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., $$

Keywords: Inventory management; Supply chain management; Simulation; Pharmaceutical drugs; Healthcare; Operations research; Operations management (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s10729-024-09686-3

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