Queueing models minimize patient wait times and optimize service delivery by analyzing peak hours and patient flow patterns. These models enable healthcare facilities to adjust staffing levels dynamically, ensuring efficient management of resources during high-demand periods.

Optimization algorithms allocate medical staff efficiently based on predicted patient demand, balancing workloads to prevent burnout while ensuring sufficient coverage. This approach maximizes resource utilization without overburdening personnel.

Inventory management models use real-time data analysis and predictive modeling to maintain optimal pharmaceutical stock levels. By anticipating demand surges and expiration dates, these models prevent shortages and reduce waste, ensuring a steady supply of critical medications.

Simulation models evaluate emergency response scenarios and predict demand surges, such as during flu seasons or public health crises. By testing contingency plans virtually, healthcare facilities can allocate resources effectively and minimize disruptions during critical times.