Improving Quality of Care in a Multidisciplinary Emergency Department by the Use of Simulation Optimization: Preliminary Results

Emergency department (ED) crowding is a worldwide challenge. It adversely affects quality of care, patient safety, and employee satisfaction. The magnitude of ED crowding can be measured by the quality metrics length-of-stay (LOS), the patient’s door-to-doctor-time (DTD), and the 4-hourstandard. This standard states that 95% of the patients stay less than four hours within the ED. In order to improve those metrics, healthcare processes have to be welldesigned and resource capacity has to match the ever increasing demand. In Germany, the ED patient census exhibits an annual increase of 4-8% over the last ten years while the capacity of the ED system has not kept pace. This situation results in a widening gap between the quality of emergency care expected and received by patients. On the one hand, tight budgets limit the allocation of resources. But on the other hand, it has been realized that better quality of care often goes hand in hand with lower total care costs. Based on real-world data of an ED in Germany, this case study quantifies the effects of different process improvements on the previous mentioned quality metrics by using discrete-event simulation (DES). Furthermore, for each of the analyzed scenarios, we aim at finding staffing levels that minimize the avg. LOS subject to a given budget by combining the simulation model with a generic optimization software.

We implemented a validated, detailed DES model of a multidisciplinary ED in Germany to provide decision support for ED managers. Our model incorporates several patient flows considering patients and resources of two different medical specialties. The introduced simulation model was parameterized according to real-world data. Leveraging OptQuest and AnyLogic, we combined optimization and simulation to find input staffing levels that minimize the avg. LOS of patients. Simulation experiments show that certain process modifications, nurse pooling, and optimized staffing levels lead to improvements in quality of care. With respect to that, both avoiding boarding of inpatients and implementing nurse pooling result in a decrease of more than 14% in avg. LOS and are particularly promising. We also identified that reallocating capacities from internists to nurses dedicated to internal medicine patients enhances the quality of care.


ED layout for a medical facility simulation

ED layout for a medical facility simulation

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