Open AccessBottleneck Detection and Reduction Using Simulation Modeling to Reduce Overcrowding of Hospital Emergency Department
Author(s) -
Qingjin Peng,
Jie Yang,
Trevor Strome,
Erin Weldon,
Alecs Chochinov
Publication year - 2020
Publication title -
journal of modeling and optimization
Language(s) - English
Resource type - Journals
ISSN - 1759-7676
DOI - 10.32732/jmo.2020.12.2.100
Subject(s) - overcrowding , bottleneck , workload , emergency department , computer science , reduction (mathematics) , health care , process (computing) , medical emergency , service (business) , operations management , operations research , medicine , engineering , business , nursing , marketing , geometry , mathematics , economics , economic growth , operating system
Overcrowding is a common problem in hospital emergency departments (EDs) where the ED service cannot meet care demands within reasonable time frames. This paper introduces a quantitative approach using computer simulation modeling for hospital decision makers to explore trade-offs between efficiency, workload and capacity of EDs. A computer simulation model is built based on the ED of a local hospital to improvement efficiency of the ED patient flow. Bottlenecks of the emergency care process are detected using the built model. The ED performance is examined by applying alternative strategies to reduce patient waiting time and length of stay. The proposed method can be applied to improve the operation efficiency of healthcare systems in the current pandemic, COVID -19.