SIM-PFED: A Simulation-Based Decision Making Model of Patient Flow for Improving Patient Throughput Time in Emergency Department

Abstract

Healthcare sectors face multiple threats, and the hospital emergency department (ED) is one of the most crucial hospital areas. ED plays a key role in promoting hospitals' goals of enhancing service efficiency. ED is a complex system due to the stochastic behavior of patient arrivals, the unpredictability of the care required by patients, and the department's complex nature. Simulations are effective tools for analyzing and optimizing complex ED operations. Although existing ED simulation models have substantially improved ED performance in terms of ensuring patient satisfaction and effective treatment services, many deficiencies continue to exist in addressing the key challenge in ED, namely, long patient throughput time. The patient throughput time issue is affected by causative factors, such as waiting time, length of stay, and decision-making. This research aims to develop a new simulation model of patient flow for ED (SIM-PFED) to address the reported key challenge of the patient throughput time. SIM-PFED introduces a new process for patient flow in ED on the basis of the newly proposed operational patient flow by combining discrete event simulation and agent-based simulation and applying a multi-attribute decisionmaking method, namely, the technique for order preference by similarity to the ideal solution. Experiments were performed on three actual hospital ED datasets to assess the effectiveness of SIM-PFED. Experimental results revealed the superiority of SIM-PFED over other alternative models in reducing patient throughput time in ED by consuming less patient waiting time and having a shorter length of stay. The findings also demonstrated the effectiveness of SIM-PFED in helping ED decision-makers select the best scenarios to be implemented in ED for ensuring minimal throughput time while being cost effective.

A Novel Data-Driven Adaptive Technique to Generate a Physician Visiting Schedule for Better Patient Experience

“…Hamza et al, developed a simulation-based model for patient flow (SIM-PEED) in the hospital. The techniques used to develop the system included "discrete event simulation, agentbased simulation,a multi-attribute decision-making method " [25]. The output of the system showed less waiting time and shorter patient stay in the hospital.…”

The Impact of Patient Infection Rate on Emergency Department Patient Flow: Hybrid Simulation Study in a Norwegian Case

“…Salmon et al examined the computerized simulation models applied to emergency department concerns and identified the typical patterns and evolving trends. The review determined that the discrete-event approach was most prominent when examining the performance of processes, resource capacity, and workforce planning within emergency departments [ 22 ]. In addition, this finding was corroborated by Hamza et al [ 23 ], who discovered that few simulation models have probed operational patient throughput.…”

Improving emergency departments during COVID-19 pandemic: a simulation and MCDM approach with MARCOS methodology in an uncertain environment

“…Simulation models allow us to assess various performance measured (e.g., patient waiting time, length of stay, utilization of doctors, nurses and facilities, treatment unit occupancy, etc.) for an ED (Hamza et al 2021;Oh et al 2016).…”

“…The issue of patient transfer in COVID-19 pandemic relates to lack of the resources in ED. Waiting time mentions to the entire time that a patient waited in advance being in the service of the ED (Hamza et al 2021;Yarmohammadian et al 2017;Zhao et al 2015). However, decision-making in EDs is particularly sensitive because of its effect on the quality of treat given and the count of rejected patients that leave ED without being treated (Uriarte et al 2017).…”

“…Integrated simulation and MCDM-based studies are especially utilized to assess alternatives that have been created from the performance measures of a simulation model. Hamza et al (2021) proposed a novel simulation model of the flow of patient to improve the performance of the ED. Gündogdu and Kahraman (2020) introduced the Spherical Fuzzy Set (SFS).…”