Clinical trial NCT06353373: Smart Technology Facilitated Venous Thromboembolism Prophylaxis Based on Bundled Evidence-based Prevention Strategies
Official title: Smart Technology Facilitated In-hospital Venous Thromboembolism Prophylaxis Based on Bundled Evidence-based Prevention Strategies: the SmaVTE-BEST Study
Study type: OBSERVATIONAL
Overall status: NOT_YET_RECRUITING
Conditions: Venous Thromboembolism
Clinical Decision Support Systems
Digital Health
Keywords: Venous Thromboembolism
Clinical Decision Support Systems
Prophylaxis
Lead sponsor: Navy General Hospital, Beijing
Sponsor class: OTHER
First posted: 2024-04-09
Enrollment: 15626
Sex: ALL
Minimum age (years): 18
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: no
Observational model: COHORT
Time perspective: RETROSPECTIVE
Sampling method: NON_PROBABILITY_SAMPLE
Study population: In our hospital, routine use of DeVTEcare system (a CDSS for VTE risk assessment and integrated care) for in-hospital management of VTE has been launched since 2021. By retrospectively collecting information on discharged patients, all patients discharged from our hospital between April 2023 and April 2024 will be included in the pre-modified DeVTEcare group.

The modified DeVTEcare system, which incorporates bundled guideline-based VTE prevention measures, will be utilized to assist healthcare providers in VTE prophylaxis after September 2024. By retrospectively collecting information on discharged patients, all patients discharged from our hospital between September 2024 and February 2025 will be included in the post-modified DeVTEcare group.

Brief summary: Venous thromboembolism (VTE) is the third leading cause of cardiovascular disease deaths globally, and its incidence is increasing over the years. Hospital-acquired VTE accounts for approximately 75% of all deaths attributed to VTE. However, only half of patients with indications for VTE prophylaxis take preventive measures, and high rates of inappropriate VTE prophylaxis prescribing contribute to the gap between VTE prophylaxis and guidelines. To further minimize the gap between clinical practice and guidelines, a range of strategies have been employed across various fields of VTE prophylaxis. One of the most effective measures is the utilization of a Clinical Decision Support System (CDSS). Smart technology-based CDSS facilitates automated evaluation of VTE risk and detection, addressing issues at both the beginning and end of the in-hospital VTE prevention process. but there is still a lack of research on how to effectively implement evidence-based VTE prophylaxis in the middle of the process.

In our hospital, routine use of DeVTEcare system (a CDSS for VTE risk assessment and integrated care) for in-hospital management of VTE has been launched since 2021. This study aims to investigate the effect of integrating bundled guideline-based VTE prevention strategies into the DeVTEcare system on in-hospital VTE prophylaxis.


Eligibility criteria: Inclusion Criteria:

* Discharged patients who were ≥18 years of age at admission were included in the observation cohort. If a patient had multiple hospitalizations, information on only the longest hospitalization was included in the study.

Exclusion Criteria:

* Lack of diagnostic information；
* Length of hospitalization ≤ 24 hours；
* Patients on anticoagulation therapy at the time of admission: e.g., those with established VTE, atrial fibrillation, acute myocardial infarction, ischemic stroke, those on continuous renal replacement therapy, extracorporeal membrane pulmonary oxygenation, hemodialysis, and mechanical valve implantation status.

Primary outcomes:
measure: In-hospital VTE
timeFrame: During the hospitalization (assessed up to 30 days)
Secondary outcomes:
measure: Guideline-compliant prescription of VTE prophylaxis
timeFrame: During the hospitalization (assessed up to 30 days)
measure: Preventable VTE
timeFrame: During the hospitalization (assessed up to 30 days)
measure: Hospital-related VTE death
timeFrame: During the hospitalization (assessed up to 30 days)
measure: Major bleeding
timeFrame: During the hospitalization (assessed up to 30 days)
measure: Non-major bleeding
timeFrame: During the hospitalization (assessed up to 30 days)
Other outcomes:
Locations:
Study officials:
affiliation: Sixth Medical Center of Chinese PLA General Hospital
name: ZHI-GENG JIN, Doctor
role: STUDY_CHAIR
References:
citation: Henke PK, Kahn SR, Pannucci CJ, Secemksy EA, Evans NS, Khorana AA, Creager MA, Pradhan AD; American Heart Association Advocacy Coordinating Committee. Call to Action to Prevent Venous Thromboembolism in Hospitalized Patients: A Policy Statement From the American Heart Association. Circulation. 2020 Jun 16;141(24):e914-e931. doi: 10.1161/CIR.0000000000000769. Epub 2020 May 7.
citation: Jin ZG, Zhang H, Tai MH, Yang Y, Yao Y, Guo YT. Natural Language Processing in a Clinical Decision Support System for the Identification of Venous Thromboembolism: Algorithm Development and Validation. J Med Internet Res. 2023 Apr 24;25:e43153. doi: 10.2196/43153.
citation: Durieux P, Nizard R, Ravaud P, Mounier N, Lepage E. A clinical decision support system for prevention of venous thromboembolism: effect on physician behavior. JAMA. 2000 Jun 7;283(21):2816-21. doi: 10.1001/jama.283.21.2816.