Geographic Service Delivery for Endovascular Clot Retrieval: Using Discrete Event Simulation to Optimize Resources.,World Neurosurgery

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Geographic Service Delivery for Endovascular Clot Retrieval: Using Discrete Event Simulation to Optimize Resources.
World Neurosurgery ( IF 2 ) Pub Date : 2020-05-24 , DOI: 10.1016/j.wneu.2020.05.168
Yifan Ren ₁ , Michael Phan ₂ , Phillip Luong ₃ , Jamin Wu ₄ , Daniel Shell ₄ , Christen D Barras ₅ , Hong Kuan Kok ₆ , Moe Burney ₇ , Bahman Tahayori ₈ , Huey Ming Seah ₂ , Julian Maingard ₉ , Kevin Zhou ₁₀ , Anthony Lamanna ₁ , Ashu Jhamb ₁₁ , Vincent Thijs ₁₂ , Duncan Mark Brooks ₁₃ , Hamed Asadi ₁₄

Affiliation

Interventional Neuroradiology Service, Department of Radiology, Austin Hospital, Melbourne, Australia.
Monash Health, 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.
South Australian Health and Medical Research Institute, University of Adelaide, Adelaide, Australia; Department of Radiology, Royal Adelaide Hospital, Adelaide, Australia.
Interventional Radiology Service, Department of Radiology, Northern Health, Melbourne, Australia.
Deloitte, Sydney, Australia.
Department of Biomedical Engineering, The University of Melbourne, Melbourne, Australia.
Interventional Neuroradiology Service, Department of Radiology, Monash Health, Melbourne, Australia; School of Medicine, Faculty of Health, Deakin University, Waurn Ponds, Australia.
Interventional Neuroradiology Service, Department of Radiology, Monash Health, Melbourne, Australia.
Interventional Radiology Service, Department of Radiology, St. Vincent's Hospital, Melbourne, Australia.
Stroke Theme, The Florey Institute of Neuroscience and Mental Health, University of Melbourne, Melbourne, Australia; Department of Neurology, Austin Health, Melbourne, Australia.
Interventional Neuroradiology Service, Department of Radiology, Austin Hospital, Melbourne, Australia; Stroke Theme, The Florey Institute of Neuroscience and Mental Health, University of Melbourne, Melbourne, Australia.
Interventional Neuroradiology Service, Department of Radiology, Austin Hospital, Melbourne, Australia; Interventional Neuroradiology Service, Department of Radiology, Monash Health, 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; Stroke Theme, The Florey Institute of Neuroscience and Mental Health, University of Melbourne, Melbourne, Australia.

Background

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.

Methods

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.

Results

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.

Conclusions

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.

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