Integrated Simulation Tool to Analyze Patient Access to and Flow During Colonoscopy Appointments

Martin, J.; Singh, Pushpendra; Cohn, Amy; Kiel-Locey, Jakob; Shehadeh, Karmel S.; Saini, Sameer D.; Kurlander, Jacob E.

doi:10.1109/wsc48552.2020.9383919

Search citation statements

Order By: Relevance

Paper Sections

Select...

Previous Work1

Citation Types

Supporting

Mentioning

Contrasting

Year Published

2021

2024

Publication Types

Select...

Other2

Article1

Relationship

Self Cite0

Independent3

Authors

Journals

Cited by 3 publications

(1 citation statement)

References 15 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…There is a rich literature in adopting discrete event simulation to investigate the effectiveness of service policies in hospitals [12,3,18,21]. In these studies, researchers usually build simplified models to extract and analyze the key factors causing congestion.…”

Section: Previous Workmentioning

confidence: 99%

A High-fidelity, Machine-learning Enhanced Queueing Network Simulation Model for Hospital Ultrasound Operations

Pan¹,

Xu²,

Jin³

et al. 2021

Preprint

View full text Add to dashboard Cite

We collaborate with a large teaching hospital in Shenzhen, China and build a high-fidelity simulation model for its ultrasound center to predict key performance metrics, including the distributions of queue length, waiting time and sojourn time, with high accuracy. The key challenge to build an accurate simulation model is to understanding the complicated patient routing at the ultrasound center. To address the issue, we propose a novel two-level routing component to the queueing network model. We apply machine learning tools to calibrate the key components of the queueing model from data with enhanced accuracy.

show abstract

Section: Previous Workmentioning

confidence: 99%