Resumen:
The increasing demand for medical services and supplies as medicine delivery has been found in applied mathematical models, such as queuing theory, a tool to analyze and improve medical processes. However, these models often assume specific arrival intervals and demands without real variability and uncertainty demand. This research proposes a methodology in real systems, considering queuing theory and discrete simulation. The goal is to provide reliable scenarios and facilitate the decision-making process in medical centers. The data were collected in drug dispensing centers in Colombia as service times, service level and users’arrival. The data were processed in a simulation model by Flexsim with multiple scenarios. The results revealed a 50% reduction in average waiting time, identified staff constraints and critical processes, and improved resource allocation. This applied case demonstrated that the queue theory and simulation integration become a valuable tool for managing variability in this medical service delivery system.
