ACCESS HCM: Real World Evidence for Artificial-Intelligence-assisted Screening and Access to Care for HCM - A Multi-Site Registry
Viz.ai, Inc.
Summary
To describe the clinical, economic, and population characteristics of newly diagnosed, previously diagnosed, and suspected patients evaluated by Viz HCM. HCM is underdiagnosed in the community and AI algorithms have been developed as screening tools. However, it is not well understood how to best integrate AI screening tools and their potential impact.
Eligibility
- Age range
- 18+ years
- Sex
- All
- Healthy volunteers
- No
All Cohorts * Patients aged 18+ years at time of arrival to healthcare facility * Patients with a resting 12-lead digital electrocardiogram (ECG) that is flagged by Viz HCM for HCM suspicion Additional cohort-specific criteria: Cohort 1 - Newly Diagnosed Patients * Patients have been diagnosed with HCM after the Viz HCM implementation * Written informed consent is obtained prior to data collection Cohort 2 - Previously Diagnosed Patients ● Prior diagnosis of HCM as evidenced by clinical diagnosis documentation prior to Viz HCM implementation Cohort 3 - Suspected and Not Diagnosed Patient…
Interventions
- DeviceViz HCM
Viz HCM is a Software as a Medical Device (SaMD) intended to receive 12-lead ECG recordings collected as part of a routine clinical assessment and analyze them in parallel to the standard of care. The device uses a machine learning based algorithm to analyze 12-lead ECGs and identify ECGs with suspected HCM.
Locations (3)
- Emory UniversityAtlanta, Georgia
- North Shore University Health SystemEvanston, Illinois
- Thomas Jefferson UniversityPhiladelphia, Pennsylvania