Metric-Based Simulation Training to Proficiency for Endovascular Thrombectomy in Ischemic Stroke

Ischemic stroke is one of the leading causes of death and long-term disability in the West. Mechanical revascularization techniques are considered the standard of care for large vessel occlusive stroke. Traditional apprenticeship models involve doctors training their skills on patients. Simulation platforms have long been recognized as an alternative to this. There has however been very little robust assessment of the training outcomes achieved on some of these platforms. At best, these simulations increase understanding of the procedural process and may help improve some technical skills; at worst they may instill bad habits and poor technique. The prerequisite of any simulation process must be to teach what to do, with which devices, in the correct sequence as well as what not to do. It should provide valid metric-based feedback to the trainee that is objective, transparent, and fair for formative and summative performance feedback. It should deliver a training program that measures the performance progress of trainees against expert benchmarks-benchmarks that represent an evidence-based peer-reviewed standard. In this paper, we present a perspective for PBP training for thrombectomy based on our experience with the process of procedure characterization, metric validation, and early experience of using this approach for proficiency training. Patient outcomes are not only determined by optimal performance in the Angio Suite but also by an efficient patient procedure pathway. There will be value in utilizing the PBP training standard not only for the procedure itself but also for the constituent elements of the stroke pathway to further improve treatment outcomes for ischemic stroke patients.

Automated summary

Ischemic stroke is a leading cause of death and disability in the Western world, and mechanical revascularization techniques are considered the standard care for this condition. Traditional apprenticeship models have been replaced by simulation platforms, but there is a lack of robust assessment of the training outcomes achieved on these platforms. The prerequisite of any simulation process should be to teach the correct sequence of actions, device usage, and what not to do. The simulation process should provide valid metric-based feedback that is objective, transparent, and fair, and deliver a training program that measures the trainees' performance progress against expert benchmarks.