Application of a computational model in simulating an endovascular clot retrieval service system within regional Australia.

INTRODUCTION: The global demand for endovascular clot retrieval (ECR) has grown rapidly in recent years creating challenges to healthcare system planning and resource allocation. This study aims to apply our established computational model to predict and optimise the performance and resource allocation of ECR services within regional Australia, and applying data from the state of South Australia as a modelling exercise. METHOD: Local geographic information obtained using the Google Maps application program interface and real-world data was input into the discrete event simulation model we previously developed. The results were obtained after the simulation was run over 5 years. We modelled and compared a single-centre and two-centre ECR service delivery system. RESULTS: Based on the input data, this model was able to simulate the ECR delivery system in the state of South Australia from the moment when emergency services were notified of a potential stroke patient to potential delivery of ECR treatment. In the model, ECR delivery improved using a two-centre system compared to a one-centre system, as the percentage of stroke patients requiring ECR was increased. When 15% of patients required ECR, the proportion of 'failure to receive ECR' cases for a single-centre system was 17.35%, compared to 3.71% for a two-centre system. CONCLUSIONS: Geolocation and resource utilisation within the ECR delivery system are crucial in optimising service delivery and patient outcome. Under the model assumptions, as the number of stroke cases requiring ECR increased, a two-centre ECR system resulted in increased timely ECR delivery, compared to a single-centre system. This study demonstrated the flexibility and the potential application of our DES model in simulating the stroke service within any location worldwide.

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

BACKGROUND: Endovascular clot retrieval (ECR) is the standard of care for acute ischemic 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. Variables were customized by the user on the basis of 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 centers. 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.

CODE STROKE ALERT-Concept and Development of a Novel Open-Source Platform to Streamline Acute Stroke Management.

Introduction: Effective, time-critical intervention in acute stroke is crucial to mitigate mortality rate and morbidity, but delivery of reperfusion treatments is often hampered by pre-, in-, or inter-hospital system level delays. Disjointed, repetitive, and inefficient communication is a consistent contributor to avoidable treatment delay. In the era of rapid reperfusion therapy for ischemic stroke, there is a need for a communication system to synchronize the flow of clinical information across the entire stroke journey. Material/Methods: A multi-disciplinary development team designed an electronic communications platform, integrated between web browsers and a mobile application, to link all relevant members of the stroke treatment pathway. The platform uses tiered notifications, geotagging, incorporates multiple clinical score calculators, and is compliant with security regulations. The system safely saves relevant information for audit and research. Results: Code Stroke Alert is a platform that can be accessed by emergency medical services (EMS) and hospital staff, coordinating the flow of information during acute stroke care, reducing duplication, and error in clinical information handover. Electronic data logs provide an auditable trail of relevant quality improvement metrics, facilitating quality improvement, and research. Discussion: Code Stroke Alert will be freely available to health networks globally. The open-source nature of the software offers valuable potential for future development of plug-ins and add-ons, based on individual institutional needs. Prospective, multi-site implementation, and measurement of clinical impact are underway.