An Inventory Model for Deteriorating Drugs with Stochastic Lead Time

Area of Science:

• Operations Research
• Healthcare Management
• Supply Chain Management

Background:

• Effective pharmaceutical inventory management is crucial for hospitals, balancing drug availability with short shelf lives.
• Perishable drug inventory presents unique challenges due to the need for high service levels versus limited shelf life.
• Uncontrollable factors introduce variability in drug lead times, complicating inventory decisions.

Purpose of the Study:

• To develop a stochastic lead time inventory model for deteriorating drugs with fixed demand.
• To address the trade-off between drug shelf life and service level in hospital inventory management.
• To incorporate constraints such as service level, stock space, and drug shelf life into the inventory model.

Main Methods:

• Established a stochastic lead time inventory model for deteriorating drugs.
• Modeled lead time using a specific distribution function, allowing for shortages.
• Integrated constraints on service level, stock space, and drug shelf life.

Main Results:

• Analyzed the model to determine the optimal weighting of drug shelf life and service level across different lead time distributions.
• Conducted empirical and sensitivity analyses to validate model findings.
• Identified key factors influencing inventory decisions for perishable pharmaceuticals.

Conclusions:

• The developed model provides a framework for optimizing inventory of deteriorating drugs under stochastic lead times.
• Balancing shelf life and service level is critical and depends on lead time variability.
• The findings offer valuable insights for improving pharmaceutical supply chain efficiency and patient care.