Enhancing Healthcare System Performance through Stochastic Petri Net Modelling

Hospital Information Systems are increasingly used by hospitals to streamline operations and provide patients with efficient services. However, despite advancements in technology and financial benefits, the adoption of information systems in the healthcare industry still faces obstacles, as it requires effective information management, control, and monitoring. Hospital automation has been extensively studied due to the continuous evolution of technology. The importance of healthcare systems is growing in the era of globalization, and patient satisfaction depends on effective planning. Our study focuses on hospital automation and performance improvement. However, many healthcare procedures, both in the public and private sectors, are still executed manually. Therefore, our primary goal is to reduce patient waiting times and the resources needed in a hospital. We aim to achieve this by modeling and simulating the medical care provided to patients in the intensive care unit (ICU) using stochastic Petri Nets. Additionally, we will explore the potential applications of these nets in various automation processes. In our work, an analysis model is developed to optimize the Intensive Care Unit patient care process and to detect system deadlocks. Since the PIPE tool is ideal for automating process monitoring, it is utilized for both model creation and analysis. The principal benefits of the PIPE tool are its ease of use, its capacity for manual model operation analysis, and its quick stochastic analysis execution.