Fundamentals of queueing theory (2nd ed.).
Fundamentals of queueing theory (2nd ed.).
Reducing time in an emergency room via a fast-track
WSC '95 Proceedings of the 27th conference on Winter simulation
Probability, Statistics, and Queueing Theory with Computer Science Applications
Probability, Statistics, and Queueing Theory with Computer Science Applications
Computers and Industrial Engineering
Analysis of ambulance diversion policies for a large-size hospital
Winter Simulation Conference
Centralized vs. Decentralized Ambulance Diversion: A Network Perspective
Management Science
Performance evaluation of medical imaging service
Proceedings of the 27th Annual ACM Symposium on Applied Computing
Comparison of ambulance diversion policies via simulation
Proceedings of the Winter Simulation Conference
Design of centralized ambulance diversion policies using simulation-optimization
Proceedings of the Winter Simulation Conference
Bi-criteria analysis of ambulance diversion policies
Proceedings of the Winter Simulation Conference
Load-sensitive dynamic workflow re-orchestration and optimisation for faster patient healthcare
Computer Methods and Programs in Biomedicine
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This paper derives an open queuing network model of an emergency department (ED) design intended to increase the capacity of an ED to treat patients. The methodology captures hospital-specific differences in patient acuity mix, arrival patterns and volumes, and efficiencies of processes in a single common computational model. A spreadsheet implementation of the resulting queuing equations is used by managers, in real time, to size ED areas using waiting time and overflow probability as quality of service targets. Non-homogeneous arrival patterns, non-exponential service time distributions, and multiple patient types are all incorporated. The methodology has been applied to a fleet of hospitals for validation. Results from one of them are used to demonstrate the methodology. Scope and purpose: Population growth, closure of emergency departments (EDs) nearby, or seasonal peak variation can cause ED patient wait times to increase dramatically. Prolonged waits induce patients to leave the ED before receiving treatment, creating a public health problem. The purpose of this paper is to introduce a new paradigm of ED care that reduces ''walk-aways'', and increases ED access, through an operational research method that customizes to any hospital through the use of hospital-specific data elements.