Discrete-Event Simulation for Hospital Resource Planning – Possibilities and Requirements

The delivery of health care services has been under pressure due to limited funding and increasing demand. This has highlighted the need to increase not only the effectiveness but also the efficiency of health care delivery. Discrete-event simulation has been suggested as an analysis tool in health care management to support the planning of health care resources. The overall purpose of this thesis is to investigate the possibilities and requirements for using discrete-event simulation in analyzing and planning the use of hospital resources. This is achieved by three case studies that focus on improvements in patient flow of emergency patients that require a radiology examination, intensive care unit capacity planning and operating room allocation strategies, respectively. The first case investigates the current stage of digitization and process orientation in hospital care as a prerequisite for efficient process simulation and analysis. The study reveals an emergency-radiology patient flow process that is not very well measured and uncovers disparate information systems storing incompatible and fragmented data. These results indicate that the current degree of process orientation and the current IT infrastructure does not enable efficient use of quantitative process analysis and management tools like simulation. In the second case the possibilities to develop generic hospital unit simulation models by building and validating a generic intensive care unit (ICU) model are explored. The results show that some of the modeling approaches described in literature cannot replicate the actual behavior observed in all studied ICUs. It is important to identify patient groups for different admission priorities, to account for over-utilizations in the model logic, and to discover and properly model dependencies in the input data. The research shows that it is possible to develop a generic ICU simulation model that could realistically describe the performance of different real ICUs in terms of occupancy, coverage and transfers. The value of simulation modeling in health care management is examined in the third case through the development and use of a simulation model for optimal resource allocation and patient flow in a hospital operating department. The goal of the simulation modeling in this case was to identify bottlenecks in the patient flow and to try different alternatives for allocation of operating room capacity in order to increase the utilization of operating room resources. The final model was used to evaluate four different proposed changes to operating room time allocation.