Evaluation of fast track strategies using agent-based simulation modeling to reduce waiting time in a hospital emergency department. (June 2015)

• Record Type: Journal Article
• Authors: Kaushal, Arjun; Zhao, Yuancheng; Peng, Qingjin; Strome, Trevor; Weldon, Erin; Zhang, Michael; Chochinov, Alecs
• Is Part Of: Socio-economic planning sciences. Number 50(2015)
• Page Start: 18
• Page End: 31
• Publication Date: 2015-06
• Subjects: Healthcare improvement -- Emergency department -- Fast track treatment -- Simulation modeling -- Agent-based system; Planning -- Periodicals; Economic policy -- Periodicals; Social policy -- Periodicals; Planification -- Périodiques; Politique économique -- Périodiques; Politique sociale -- Périodiques; ECONOMIC PLANNING; SOCIAL PLANNING; DECISION-MAKING; 361
• DOI: 10.1016/j.seps.2015.02.002
• Languages: English
• ISSNs: 0038-0121

Abstract

Abstract: Different strategies have been proposed to reduce patient waiting time in hospitals. Previous investigations indicate that up to 50% or more patients can be treated in a "fast track" process compared to the standard procedure in some emergency departments. However most studies on emergency department (ED) fast tracks were based on evidence without using an efficient decision tool to show applicability of the results. An agent-based simulation tool is proposed in this research to evaluate fast track treatment (FTT) in an ED. The tool can study the behavior change of entities and resources in a complex ED system. Static and dynamic FTT processes are evaluated. The static process uses a fixed duration in the daily ED operation. In the dynamic process, FTT is triggered based on the current patient waiting time and the state of ED operations. The simulation results provide details and information for the process of the FTT implementation at the ED to reduce patient waiting time. Highlights: An agent-based simulation model considers human decision-making in dynamic environments of healthcare operations. A systemic method is developed using strategy-linked performance measures with the quantitative prediction. Both static operation and dynamic process are evaluated to aid the FTT implementation for reduced waiting time. The FTT strategy can achieve a considerable reduction in waiting time without affecting the overall ED performance.