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.
Highlights
Endovascular clot retrieval (ECR) is the first-line treatment for acute ischemic stroke (AIS) due to arterial large vessel occlusion (LVO) with several trials demonstrating its efficacy in reducing mortality and morbidity [1,2,3]
We simulated a model of an ECR service to identify workflow bottlenecks
Using data from a Comprehensive Stroke Service in Melbourne (Table 1), our simulation showed that the proportion of patients who waited, relative to those who did not, is substantially higher for a biplane angiographic suite compared to other resources (Figure 2A, red compared to other colors)
Summary
Endovascular clot retrieval (ECR) is the first-line treatment for acute ischemic stroke (AIS) due to arterial large vessel occlusion (LVO) with several trials demonstrating its efficacy in reducing mortality and morbidity [1,2,3]. ECR is considerably more costly than traditional care [4], with estimated procedure costs ranging between 9,000 and 14,000 US dollars per patient [4, 5]. Government funding agencies seek to optimize return on investment, such as that on resources allocated to acute stroke services. In contrast to other healthcare fields, a resource-use optimization model has not been implemented for comprehensive stroke services. Alvarado and colleagues have identified the optimal staffing capacity to match a service demand increase for an outpatient oncology clinic [6]. As healthcare is experiencing both increasing resource demands and fiscal constraints, there is a need to determine how resources may be optimally allocated to improve overall health care value, i.e., high quality and timely care at low cost
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