Changing the perspective of system crowding evaluation using a new congestion measure: application to the Emergency Department

System crowding relates to the general congestion phenomenon of clients, products or patients waiting concurrently, and its adequate representation and measurement is a key step in the monitoring and optimization of system performances in response to an arrival demand. Traditional crowding and queui...

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Bibliographic Details
Published in:Operational research 2024-12, Vol.24 (4), p.53, Article 53
Main Authors: Wartelle, Adrien, Mourad-Chehade, Farah, Yalaoui, Farouk, Laplanche, David, Sanchez, Stéphane
Format: Article
Language:English
Subjects:
Business and Management
Computational Intelligence
Congestion
Crowding
Emergency medical care
Emergency medical services
Emergency response
Management Science
Mathematical analysis
Operations Research
Operations Research/Decision Theory
Optimization
Original Paper
Paradigms
Queuing theory
Time measurement
Windows (intervals)
Citations: Items that this one cites
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Summary:System crowding relates to the general congestion phenomenon of clients, products or patients waiting concurrently, and its adequate representation and measurement is a key step in the monitoring and optimization of system performances in response to an arrival demand. Traditional crowding and queuing measures such as occupation and waiting time are insufficiently studied in a data-driven context, especially with their transient behaviors on a short temporal scale. Furthermore, central to the study of Emergency Department systems, crowding scores suffer from a lack of interpretability, statistical relevance and extensibility to other types of systems. As such, this study introduces a new congestion measure based on the ratio of arrival and departure load given a specific time window to characterize system crowding. A mathematical framework is proposed and used to perform a 3-part evaluation and comparison on the new and traditional measures with their large temporal scale sample path properties, their short temporal scale fluid limit modelled properties and with a case study on a regional Emergency Department to illustrate and confirm the proven properties. The results, in the form of mathematical properties and correlations, show that this new measure is more pertinent to the tracking of crowding from a system perspective, notably service performances on a local scale, compared to other measures. Through this congestion measure and its characterization with a fluid limit model, this study proposes an alternative approach and takes a first step toward a new data-driven paradigm to better monitor, forecast and optimize system crowding.
ISSN:1109-2858
1866-1505
DOI:10.1007/s12351-024-00855-4