03-001 – Analysis and optimization of installed capacity in medical services through discrete event simulation and continuous improvement

Healthcare services face critical challenges due to the sustained growth in demand and the increasing complexity of diagnostic processes. This study explores how Discrete Event Simulation (DES) models can analyze, model, and optimize the installed capacity in diagnostic processes at the tertiary healthcare level, including angiographies, biopsies, and cytologies. Using the DMAIC structure from Six Sigma and Lean Manufacturing tools, key bottlenecks were identified, and validated simulations were employed to evaluate operational and logistical solutions. The results showed significant reductions in waiting times and improvements in the utilization of human and technical resources, underscoring the flexibility and precision of DES models in integrating multiple variables and scenarios. Additionally, the economic and operational implications of the proposed strategies were assessed, demonstrating their feasibility in enhancing service quality and ensuring financial sustainability. This methodological approach provides a robust and replicable tool to address current challenges in healthcare resource management, fostering data-driven decision-making and a continuous improvement model centered on patient care.