Whole-process Quality Improvement of Endovascular Treatment Basd on an AI-aided Clinical Feedback System

Zhejiang University

Status: Completed

Conditions: Stroke, Acute

Treatments: Behavioral: AI-aided clinical feedback system coupled with multi-aspect intervention basd on Behaviour Change Wheel model

Study type: Interventional

Funder types: Other

Identifiers

NCT05874596

OPTIMAL

Details and patient eligibility

About

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.

Full description

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.

Enrollment: 1,289 patients

Sex: All

Ages: 18+ years old

Volunteers: No Healthy Volunteers

Inclusion criteria

• Age > 18
• AIS patients receiving EVT within 24 hours of stroke onset
• Written informed consent is obtained

Exclusion criteria

• Patients refuse to participate in this study

Trial design

Primary purpose: Treatment

Allocation: Randomized

Interventional model: Parallel Assignment

Masking: Double Blind

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1,289 participants in 2 patient groups

Intervention

Experimental group

Description:

AI-aided clinical feedback system coupled with multi-aspect intervention based on the Behaviour Change Wheel model

Treatment:

Behavioral: AI-aided clinical feedback system coupled with multi-aspect intervention basd on Behaviour Change Wheel model

Control

No Intervention group

Description:

AI-aided clinical feedback system only