Emergency Departments (EDs) play a significant role in the healthcare system across the nation. Not only do they serve the function of providing emergency service to trauma and non-trauma patients, but they also act as the entry points to the hospitals. As the multifunctional facilities designed to serve and care for patients with almost any medical condition, EDs are integrated across every aspect of the healthcare system and, hence, are critical to the overall functioning of hospitals. In such an environment, overcrowding of EDs has been a critical area under study for several years now. Additional growing market competition from retail-based healthcare providers and the increasing need to ease ED operations also resulted in an increased number of process improvement initiatives that have been undertaken by health systems across the nation.; Since EDs play an integral role in not only providing care to the emergent population, but also to a large segment of patients who can be classified as 'low acuity', it is important that this population of patients be studied and services be designed to fulfill their needs and requirements. Therefore, this research aimed to study the viability of scheduling low acuity patients in an ED while taking into account the stochastic nature of processes at such a highly dynamic environment. In particular, the research proposes various scheduling rules that could be implemented to schedule patients in real-time based on the ED's current state characteristics. Three different rule sets were tested and compared: simple rules, ranking-based rules, and rules based on the current state queuing characteristics. Additionally, the effects of variability in patient arrival and allowance before penalty for late arrivals were also studied. Discrete events simulation was used to assess the feasibility of these rules. Significant reductions of up to 65% in patient waiting time at the ED were observed and validated, thereby illustrating the operational benefits that could be realized by scheduling low acuity patients.
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