Please use this identifier to cite or link to this item: https://ahro.austin.org.au/austinjspui/handle/1/21397
Title: Optimizing Resources for Endovascular Clot Retrieval for Acute Ischemic Stroke, a Discrete Event Simulation.
Austin Authors: Huang, Shiwei;Maingard, Julian;Kok, Hong Kuan;Barras, Christen D;Thijs, Vincent N ;Chandra, Ronil V;Brooks, Duncan Mark ;Asadi, Hamed 
Affiliation: The Canberra Hospital, Canberra, ACT, Australia
South Australian Health and Medical Research Institute, The University of Adelaide, Adelaide, SA, Australia
Interventional Radiology Service, Department of Radiology, Northern Health, Epping, Victoria, Australia
Stroke Division, Department of Neurology, Austin Health, Heidelberg, Victoria, Australia
Department of Surgery and Department of Medicine, Monash University, Clayton, Victoria, Australia
Interventional Neuroradiology, Monash Imaging, Monash Medical Centre, Clayton, Victoria, Australia
Department of Radiology, Royal Adelaide Hospital, Adelaide, SA, Australia
Stroke Division, The Florey Institute of Neuroscience and Mental Health, Parkville, Victoria, Australia
Faculty of Health, School of Medicine, Deakin University, Waurn Ponds, Victoria, Australia
Interventional Neuroradiology Service, Department of Radiology, Austin Health, Heidelberg, Victoria, Australia
Issue Date: 27-Jun-2019
metadata.dc.date: 2019-06-27
Publication information: Frontiers in neurology 2019; 10: 653
Abstract: 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.
URI: http://ahro.austin.org.au/austinjspui/handle/1/21397
DOI: 10.3389/fneur.2019.00653
ORCID: 0000-0003-2475-9727
0000-0001-8958-2411
0000-0002-6614-8417
PubMed URL: 31316449
ISSN: 1664-2295
Type: Journal Article
Subjects: ECR
discrete event simulation (DES)
endovascular clot retrieval
mechanical thrombectomy
resource allocation
resource optimization
workflow simulation
Appears in Collections:Journal articles

Show full item record

Google ScholarTM

Check


Items in AHRO are protected by copyright, with all rights reserved, unless otherwise indicated.