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 | 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: | https://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 |
Journal: | Frontiers in neurology | 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
Items in AHRO are protected by copyright, with all rights reserved, unless otherwise indicated.