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

We consider a three-echelon blood sample supply chain comprising the following elements: (i) clinics, where blood samples are taken from patients, (ii) centrifugation centers, where collected blood samples are separated into their different components, and (iii) a centralized testing laboratory, where the samples are analyzed. We focus on the scheduling of vehicles that transport blood samples from clinics to centrifugation centers—a special case of the vehicle routing problem (VRP). Our study presents a novel simulation-based approach to the VRP, designed and implemented in MATLAB, and tailored to the unique constraints of the three-echelon blood sample collection chain. We apply this approach to data from a large Health Maintenance Organization to determine the optimal vehicle fleet size for blood sample transport, while ensuring that the quality of the healthcare service is not compromised. Results suggest that our simulation model can be generalized to serve as a useful and straightforward decision support tool for optimizing resource utilization and service quality in healthcare systems.