Discrete-Event Based Patient Flow Simulation of an Emergency Surgery Department

Paper in proceeding, 2024

Increased demand for healthcare services is placing a significant strain on hospitals. Prolonged waiting times for patients are becoming commonplace, while healthcare staff are subjected to unsustainable workloads. Finding ways to increase patient flow through hospital departments is one crucial step toward efficient healthcare services.In this work, a modelling framework is proposed to model patient flow though a healthcare department. Patient progression and resource allocation is simulated, offering insights into expected outcomes, bottlenecks, and other inefficiencies.A discrete-event model of a hospital department is formulated and proposed to be used together with Monte Carlo simulations. Patient treatment is represented by a series of processes, each consisting of smaller tasks. Medical staff members are represented as resources with specific qualifications that decide what tasks they may execute. Resources are allocated dynamically to model department-specific procedures, therefore increasing the flexibility of the proposed framework and opening up modelling possibilities to different healthcare departments.A real-world healthcare department is modelled and simulated using historic data and expert knowledge. In this way, the modelling flexibility of the framework is shown. Comparisons between simulation results and actual outcomes highlight the importance of establishing high-quality quantitative data collection in healthcare departments at an early stage to provide a stable foundation for operational modelling research. With accurate process times and resource usage data, the proposed framework has the potential to serve as an important support function, and ultimately contribute to a more sustainable and efficient healthcare.