Improving Patient Flow and Operational Efficiency in Emergency Rooms using a Discrete Event Simulation Approach

Abstract

Emergency rooms (ERs) are essential components of the healthcare system, but in recent times, ERs across Canada have been experiencing extended emergency room length of stay (ERLOS), patients leaving without being seen, and overcrowding. The purpose of this research is to address these issues by utilizing a discrete event simulation approach to improve patient flow and operational efficiency. We propose two policies and interventions that can help alleviate the pressure on ERs, improve operational efficiency, and reduce complications associated with delayed treatment. The first policy is an Acute Medical Unit which is hospital unit that is staffed and equipped to receive patients with acute medical illness and provide rapid assessment and treatment to emergency patients. The second policy is an On-Call Physician, a physician who is called when the number of active patients in ER exceeds twice the ER capacity and helps with the increased workload. To develop the simulation model and test the impact of proposed strategies, we use Rockwell Arena 16 and factor in real-life factors associated with ERs such as arrival rates, service times, and patient acuity levels. In addition, the impact of entry and access blocks to and from the ER is examined. An Entry Block prevents patients from accessing treatment in the ER as a result of a lack of capacity. An Access Block prevents patients from accessing a bed in the hospital itself. Both factors have a significant impact on ER operations and efficiency. Our findings indicate that the proposed intervention strategies can reduce the time patients spend waiting for treatment and the number of patients leaving without being seen. This reduces the complications associated with delayed treatment and addresses overcrowding in emergency rooms. Therefore, the proposed policies have the potential to improve patient flow and operational efficiency in ERs. These findings have significant implications for healthcare facilities as they can utilize this simulation model to test various resource planning strategies and make informed decisions to improve patient healthcare experiences.