Queuing theory & discrete simulation as a tool to improve medicine deliver center service levels

Abstract

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.