A generalized symbiotic simulation model of an emergency department for real-time operational decision-making
A generalized symbiotic simulation model of an emergency department for real-time operational decision-making
We describe the design of a generalizable simulation model of an emergency department (ED) that forms part of a symbiotic simulation tool designed to improve short-term decision-making. While the paper will give an overview of the planned symbiotic simulation tool, our focus here is on the generalizability of the simulation model. The model is coded such that the routing logic of patient pathways are not explicitly defined but are instead included as an input parameter. By structuring the model this way, the pathways can instead be discovered through process mining methods on standard healthcare transactions data. This enables the simulation model to be applied to other EDs without redesigning all of the logical flows within the model. As symbiotic simulation tools are designed for ongoing use within the system they model, utilizing process mining also allows for automating recalibration of the patient pathways if changes occur in the physical system.
simulation, emergency department, digital twin
1042-1053
Heib, Alexander R.
3b3d7f83-33d1-446e-b408-4411b6d1110d
Currie, Christine S.M.
dcfd0972-1b42-4fac-8a67-0258cfdeb55a
Onggo, Bhakti Stephan
8e9a2ea5-140a-44c0-9c17-e9cf93662f80
Smith, Honora K.
1eaef6a6-4b9c-4997-9163-137b956c06b5
Kerr, James
5b46fed2-fe15-4717-aa26-68516c376e71
10 December 2023
Heib, Alexander R.
3b3d7f83-33d1-446e-b408-4411b6d1110d
Currie, Christine S.M.
dcfd0972-1b42-4fac-8a67-0258cfdeb55a
Onggo, Bhakti Stephan
8e9a2ea5-140a-44c0-9c17-e9cf93662f80
Smith, Honora K.
1eaef6a6-4b9c-4997-9163-137b956c06b5
Kerr, James
5b46fed2-fe15-4717-aa26-68516c376e71
Heib, Alexander R., Currie, Christine S.M., Onggo, Bhakti Stephan, Smith, Honora K. and Kerr, James
(2023)
A generalized symbiotic simulation model of an emergency department for real-time operational decision-making.
Corlu, C.G., Hunter, S.R., Lam, H., Onggo, B.S., Shortle, J. and Biller, B.
(eds.)
In Proceedings of the 2023 Winter Simulation Conference.
IEEE.
.
(doi:10.1109/WSC60868.2023.10407981).
Record type:
Conference or Workshop Item
(Paper)
Abstract
We describe the design of a generalizable simulation model of an emergency department (ED) that forms part of a symbiotic simulation tool designed to improve short-term decision-making. While the paper will give an overview of the planned symbiotic simulation tool, our focus here is on the generalizability of the simulation model. The model is coded such that the routing logic of patient pathways are not explicitly defined but are instead included as an input parameter. By structuring the model this way, the pathways can instead be discovered through process mining methods on standard healthcare transactions data. This enables the simulation model to be applied to other EDs without redesigning all of the logical flows within the model. As symbiotic simulation tools are designed for ongoing use within the system they model, utilizing process mining also allows for automating recalibration of the patient pathways if changes occur in the physical system.
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Heib_WSC23
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Accepted/In Press date: 22 September 2023
Published date: 10 December 2023
Venue - Dates:
Winter Simulation Conference, San Antonio, Texas, USA, San Antonio, United States, 2023-12-10 - 2023-12-13
Keywords:
simulation, emergency department, digital twin
Identifiers
Local EPrints ID: 487620
URI: http://eprints.soton.ac.uk/id/eprint/487620
PURE UUID: 9103b748-7051-44f5-a2f5-1066d26a0fd3
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Date deposited: 29 Feb 2024 17:38
Last modified: 18 Mar 2024 03:50
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Contributors
Author:
Alexander R. Heib
Author:
James Kerr
Editor:
C.G. Corlu
Editor:
S.R. Hunter
Editor:
H. Lam
Editor:
B.S. Onggo
Editor:
J. Shortle
Editor:
B. Biller
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