Please use this identifier to cite or link to this item: http://ahro.austin.org.au/austinjspui/handle/1/23326
Title: Geographic service delivery for endovascular clot retrieval: Using Discrete Event Simulation to Optimize Resources.
Authors: Ren, Yifan;Phan, Michael;Luong, Phillip;Wu, Jamin;Shell, Daniel;Barras, Christen D;Kok, Hong Kuan;Burney, Moe;Tahayori, Bahman;Seah, Huey Ming;Maingard, Julian;Zhou, Kevin;Lamanna, Anthony;Jhamb, Ashu;Thijs, Vincent N;Brooks, Duncan Mark;Asadi, Hamed
Affiliation: Interventional Neuroradiology Service, Department of Radiology, Austin Health, Heidelberg, Victoria, Australia
Department of Neurology, Austin Health, Heidelberg, Victoria, Australia
Interventional Neuroradiology Service - Department of Radiology, Monash Health, Melbourne, Australia
South Australian Health and Medical Research Institute, University of Adelaide, Adelaide, Australia
Department of Radiology, Royal Adelaide Hospital, Adelaide, Australia
Stroke Theme, The Florey Institute of Neuroscience and Mental Health, University of Melbourne, Melbourne, Australia
School of Medicine - Faculty of Health, Deakin University, Waurn Ponds, Australia
Interventional Radiology Service - Department of Radiology, St Vincent's Hospital, Melbourne, Australia
School of Medicine - Faculty of Health, Deakin University, Waurn Ponds, Australia
Interventional Neuroradiology Service - Department of Radiology, Monash Health, Melbourne, Australia
Department of Biomedical Engineering, The University of Melbourne, Australia
Deloitte, Sydney, Australia
Interventional Radiology Service - Department of Radiology, Northern Health, Melbourne, Australia
Interventional Radiology Service - Department of Radiology, St Vincent's Hospital, Melbourne, Australia
School of Science, Computer Science and Information Technology, RMIT University, Melbourne, Australia
Faculty of Medicine, Nursing and Health Sciences, Monash University, Melbourne, Australia
Monash Health, Melbourne, Australia
Issue Date: 24-May-2020
EDate: 2020-05-24
Citation: World neurosurgery 2020; online first: 24 May
Abstract: Endovascular clot retrieval (ECR) is the standard of care for acute ischaemic stroke caused by large vessel occlusion. Reducing stroke symptom onset to reperfusion time is associated with improved functional outcomes. This study aims to develop a computational model to predict and identify time-related outcomes of community stroke calls within a geographic area based on variable parameters to support planning and coordination of ECR services. A discrete event simulation (DES) model to simulate and predict ECR service was designed using SimPy, a process-based DES framework written in Python. Geolocation data defined by the user as well as that used by the model were sourced using the Google Maps application programming interface (API). Variables were customized by the user based on their local environment to provide more accurate prediction. A DES model can estimate the delay between the time that emergency services are notified of a potential stroke and potential cerebral reperfusion using ECR at a capable hospital. Variables can be adjusted to observe the effect of modifying each parameter input. By varying the percentage of stroke patients receiving ECR we were able to define the levels at which our existing service begins to fail in service delivery and assess the effect of adding additional centres. This novel computational DES model can aid the optimization of delivery of a stroke service within a city, state or country. By varying geographic, population and other user defined inputs, the model can be applied to any location worldwide.
URI: http://ahro.austin.org.au/austinjspui/handle/1/23326
DOI: 10.1016/j.wneu.2020.05.168
ORCID: 0000-0003-2475-9727
0000-0001-6518-6828
0000-0002-6614-8417
0000-0003-0705-2252
PubMed URL: 32461178
Type: Journal Article
Subjects: Acute ischaemic stroke
Discrete event simulation
Endovascular treatment
Google
Appears in Collections:Journal articles

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