Whole-process Quality Improvement of Patients With Acute Ischemic Stroke Undergoing Endovascular Treatment Based on an Artificial Intelligence-aided Clinical Feedback System
Whole-process Quality Improvement of Patients With Acute Ischemic Stroke Undergoing Endovascular Treatment Based on an Artificial Intelligence-aided Clinical Feedback System
A clustered randomized control trial to evaluate whether multi-aspect intervention based on an AI-aided clinical feedback system could improve the quality of EVT and functional outcome of patients.
Endovascular treatment (EVT) is the standard treatment for acute ischemic stroke (AIS) caused by large vessel occlusion (LVO) according to current guidelines. However, while a rapidly-growing number of stroke centers become capable of performing EVT, the general quality of EVT remains unsatisfied, resulting in a considerable proportion of patients who could not reach functional independence. Our pre-established artificial intelligence (AI)-aided clinical feedback system could dynamically record and report key timepoints of EVT in-hospital process. Combined with multi-aspect intervention via remote/on-site surveillance and education, this may be a potential solution for quality improvement of EVT. Therefore, the aim of the study is to evaluate whether an AI-aided clinical feedback system coupled with multi-aspect intervention could improve the quality of EVT. Twenty hospitals with annual EVT cases > 30 will be 1:1 randomized into intervention group and control group. The intervention group will receive AI-based clinical feedback system coupled with multi-aspect intervention, including remote/on-site surveillance and education regarding in-hospital workflow and surgical procedures of EVT. The control group only deploys AI-aided clinical feedback system. The primary outcome is the ratio of good functional outcome at 3 month.
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