Simulation application in the emergency department with the theory of constraints approach

With the increasing population and globalization worldwide, continuous improvement and performance optimization in healthcare services have become inevitable. Especially in emergency services, which have a critical importance in the healthcare system, performance management due to patient density and resource constraints emerges as an important issue. The increase in the number of applications to emergency services worldwide and in our country has caused performance studies in emergency services to become increasingly important. The fact that emergency services provide uninterrupted service 24 hours a day, provide free access, easy access to doctors and also that patients with non-urgent conditions apply to these units constitute the main reasons for the high preference of emergency services. However, emergency service workflow optimization has become quite complicated due to uncertain patient arrivals, irregular workload and limited resources. This situation causes crowding in emergency services, long-term patient stays and burnout among employees. The intense and stressful environment in emergency services is directly related to providing quality service to patients and therefore patient (customer) satisfaction. In this study, it was aimed to improve performance by effectively optimizing resources in an emergency service with limited resources. The current emergency department system flow was modeled using the Arena Simulation program. In order to reflect the patient flow in a healthy way, it was important to collect the data meticulously and accurately. Patient arrival data from previous years were analyzed with the help of the Easy Fit program and statistical distributions were determined for the incoming patients. After the other processes in the system were completely defined, the real system was compared with the system established in the Arena program. Statistica statistical program was used to test the reliability of the established model. After the model validity was ensured, the results were evaluated and resource bottlenecks were determined. Different scenarios were designed within the scope of the Theory of Constraints approach to eliminate bottlenecks. Optimization was performed with the mathematical model developed on the Arena/Optquest platform within the determined constraints. As a result, patient waiting times were reduced, service delivery was improved and performance was increased.