Patient flow model using hybrid discrete event and agent-based simulation in emergency department

• Main Author: Nidal Abdelgadir, Ahmed Hamza
• Format: Thesis
• Language: English
• Published: 2022
• Subjects: Q Science (General); QA75 Electronic computers. Computer science
• Online Access: http://umpir.ump.edu.my/id/eprint/38454/1/Patient%20flow%20model%20using%20hybrid%20discrete%20event%20and%20agent-based%20simulation%20in%20emergency%20department.ir.pdf; http://umpir.ump.edu.my/id/eprint/38454/

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 behaviour including the operational patient flow, the unpredictability of the care required by patients, and the department’s complex nature. ED operational patient flow refers to the transferring of patients throughout various locations in specific relation to a healthcare facility. Simulations are effective tools for analysing and optimizing complex ED operational patient flow. Although existing ED operational patient flow simulation models have substantially improved ED operational patient performance in terms of ensuring patient satisfaction and effective treatment, many deficiencies continue to exist in addressing the key challenge in ED, namely, patient throughput issue which is indicated to the long patient throughput time in ED. The patient throughput time issue is affected by causative factors, such as waiting time, length of stay (LoS), and decision-making. This research aims to improve ED operational patient flow by proposing a new ED Operational Patient Flow Simulation Model (SIM-PFED) in order 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 decision making method, namely, the technique for order preference by similarity to the ideal solution (TOPSIS). Experiments were performed on four 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 results of the experiments showed the improvement `of percentage in terms of patient throughput time (waiting time and LoS). SIM-PFED's waiting time proficiency is 35.45%, 89.21%, 87.64% and 86.00% advanced than Safety Simulation Model, ABS Model, IS-BDSF and SEDO-UCC correspondingly. In addition, the general average waiting time performance of SIM-PFED against the four models ascertains that the performance of SIM-PFED's is largely improved than that of the Safety Simulation Model, ABS Model, IS-BDSF and SEDO-UCC in regard to the waiting time at a percentage of 74.58%. SIM-PFED's LoS effectiveness is 74.4%, 85%, 91.6% and 87.4% higher than Safety Simulation Model, ABS Model, IS-BDSF and SEDO-UCC correspondingly. The general average LoS performance of SIM-PFED against the four models illustrated that the performance of SIM-PFED's is largely improved than that of the Safety Simulation Model, ABS Model, IS-BDSF and SEDO-UCC in regard to the LoS at a percentage of 85.6%.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 patient throughput time while being cost-effective.