Data-driven queueing modelling: a simulation case study of emergency department crowding
This study shows an alternative approach successfully bridging the modelling gap by establishing a model that can effectively predict system crowding dynamics under the influence of multiple key variables.
Authors
- Adrien Wartelle (ORCID: https://orcid.org/0000-0003-1471-0866)
- S. Sanchez
- David Laplanche (ORCID: https://orcid.org/0000-0002-0399-5985)
- Farah Mourad-Chehade (ORCID: https://orcid.org/0000-0002-5048-9372)
- Farouk Yalaoui
Institutions
- Centre National de la Recherche Scientifique (FR)
- Université Toulouse III - Paul Sabatier (FR)
- Université de Technologie de Troyes (FR)
- Université Fédérale de Toulouse Midi-Pyrénées (FR)
- Université Toulouse-I-Capitole (FR)
- Institut de Recherche en Informatique de Toulouse (FR)
- Centre Hospitalier de Troyes (FR)
- Université Toulouse - Jean Jaurès (FR)
- Institut Polytechnique de Bordeaux (FR)
- Université de Reims Champagne-Ardenne (FR)
Publication Details
- Journal
- BMJ Health & Care Informatics
- Published
- 2026-01-01
- DOI
- https://doi.org/10.1136/bmjhci-2025-101462
- Primary Topic
- Healthcare Operations and Scheduling Optimization
- Type
- article
- Field-Weighted Citation Impact
- 0.00