Pragmatic Investigation of Artificial Intelligence for Symptomatic Venous Thromboembolism Prevention: PRISM-VTE Study

Venous thromboembolism (VTE), which includes deep vein thrombosis and pulmonary embolism, is a common and potentially life-threatening condition affecting 1 in 10 people during their lifetime. Many cases occur during or shortly after hospitalization. Although hospitals aim to prevent these events, accurately identifying VTE using routine hospital data remains challenging, as diagnostic codes alone are often inaccurate.

This project will develop and validate a more reliable way to identify VTE using a combination of diagnostic codes, medical imaging records, and treatment information from The Ottawa Hospital Data Warehouse. Suspected cases from 2023–2024 will be reviewed and compared with expert clinical adjudication to determine how accurately the algorithm detects true VTE events.

By improving VTE identification, this research will support better prevention strategies, enhance hospital quality monitoring, reduce unnecessary treatment, and strengthen patient safety. The project will also train undergraduate students in applied clinical research and health data analytics.

Faculty Supervisor:

Yan Xu

Student:

Partner:

Ottawa Hospital Research Institute

Discipline:

Life Sciences

Sector:

Health and Related Sciences & Technology; Professional, scientific and technical services

University:

University of Ottawa

Program:

Accelerate

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