Optimizing resources for endovascular clot retrieval for acute ischemic stroke, a discrete event simulation

Huang, Shiwei, Maingard, Julian, Kok, Hong Kuan, Barras, Christian D, Thijs, Vincent, Chandra, Ronil V, Brooks, Duncan Mark and Asadi, Hamed 2019, Optimizing resources for endovascular clot retrieval for acute ischemic stroke, a discrete event simulation, Frontiers in neurology, vol. 10, pp. 1-7, doi: 10.3389/fneur.2019.00653.

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Title Optimizing resources for endovascular clot retrieval for acute ischemic stroke, a discrete event simulation
Author(s) Huang, Shiwei
Maingard, Julian
Kok, Hong Kuan
Barras, Christian D
Thijs, Vincent
Chandra, Ronil V
Brooks, Duncan Mark
Asadi, HamedORCID iD for Asadi, Hamed orcid.org/0000-0003-2475-9727
Journal name Frontiers in neurology
Volume number 10
Article ID 653
Start page 1
End page 7
Total pages 7
Publisher Frontiers Media
Place of publication Lausanne, Switzerland
Publication date 2019-06
ISSN 1664-2295
Keyword(s) discrete event simulation (DES)
endovascular clot retrieval
resource optimization
mechanical thrombectomy
resource allocation
workflow simulation
Science & Technology
Life Sciences & Biomedicine
Clinical Neurology
Neurosciences & Neurology
Summary Objective: Endovascular clot retrieval (ECR) is the standard of care for acute ischemic stroke due to large vessel occlusion. Performing ECR is a time critical and complex process involving many specialized care providers and resources. Maximizing patient benefit while minimizing service cost requires optimization of human and physical assets. The aim of this study is to develop a general computational model of an ECR service, which can be used to optimize resource allocation. Methods: Using a discrete event simulation approach, we examined ECR performance under a range of possible scenarios and resource use configurations. Results: The model demonstrated the impact of competing emergency interventional cases upon ECR treatment times and time impact of allocating more physical (more angiographic suites) or staff resources (extending work hours). Conclusion: Our DES model can be used to optimize resources for interventional treatment of acute ischemic stroke and large vessel occlusion. This proof-of-concept study of computational simulation of resource allocation for ECR can be easily extended. For example, center-specific cost data may be incorporated to optimize resource allocation and overall health care value.
Language eng
DOI 10.3389/fneur.2019.00653
Indigenous content off
Field of Research 1109 Neurosciences
1103 Clinical Sciences
1701 Psychology
HERDC Research category C1 Refereed article in a scholarly journal
Copyright notice ©2019, Huang, Maingard, Kok, Barras, Thijs, Chandra, Brooks and Asadi
Persistent URL http://hdl.handle.net/10536/DRO/DU:30124475

Document type: Journal Article
Collections: Faculty of Health
School of Medicine
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