A simulation-based approach for improving the clinical blood sample supply chain

Area of Science:

• Operations Research
• Healthcare Logistics
• Supply Chain Management

Background:

• Blood sample logistics involve multiple stages: collection at clinics, processing at centrifugation centers, and analysis at a central laboratory.
• Efficient transportation is crucial for maintaining sample integrity and timely healthcare delivery.
• The vehicle routing problem (VRP) is a key challenge in optimizing these transport networks.

Purpose of the Study:

• To develop and apply a simulation-based approach for optimizing vehicle routing in a three-echelon blood sample supply chain.
• To determine the optimal fleet size for blood sample transportation from clinics to centrifugation centers.
• To ensure that logistical optimizations do not compromise healthcare service quality.

Main Methods:

• A novel simulation-based approach to the vehicle routing problem (VRP) was developed and implemented in MATLAB.
• The model was tailored to the specific constraints of a three-echelon blood sample collection system.
• The approach was validated using data from a large Health Maintenance Organization.

Main Results:

• The simulation model successfully determined an optimal vehicle fleet size for blood sample transport.
• The findings indicate that resource utilization and service quality in healthcare logistics can be effectively optimized.
• The model provides a practical decision support tool for healthcare systems.

Conclusions:

• The developed simulation model offers a generalized and straightforward method for optimizing healthcare logistics.
• Efficient vehicle fleet management is essential for balancing operational costs and service quality in blood sample supply chains.
• This approach can be adapted for similar logistical challenges within healthcare systems.