This cohort will consist of individuals who are newly diagnosed with HCM after the site began using Viz HCM. These patients will serve as a key population to assess the AI tool's impact on diagnoses, timeliness, and subsequent initiation of treatment. Data collected will include pre-diagnostic clinical indicators, diagnostic pathways, and treatment decisions following diagnosis. This cohort will begin to describe patient access to care and the clinical outcomes following a new HCM diagnosis in an AI-augmented clinical workflow.

Patients in this cohort will have an existing diagnosis of HCM prior to the start of using Viz HCM. This group will allow for the evaluation of how the AI tool may influence ongoing management strategies, such as treatment adjustments, monitoring practices, risk stratification, and clinical outcomes. The cohort will also help assess whether the AI tool facilitates optimization of care by identifying missed opportunities or previously unrecognized complications.

This cohort will include patients who were suspected by Viz HCM users of having underlying HCM, but clinical work-up sufficient to produce a diagnosis of HCM (including imaging and/or genetic testing) did not occur within the data collection period. Data collected will focus on diagnostic pathways, attempts made to coordinate care, and categorical barriers to care.

This cohort will look at a subset of randomly selected patients who are suspected by Viz HCM of having underlying HCM but are moved to the subgroup 'Unlikely HCM' within the Viz app/web by a clinician. After 1 year of study enrollment, a list will be created by Viz and shared with study teams for collection of additional minimal data including age, sex, reason for unlikely HCM (via chat), demographics (race, ethnicity) and reason for ECG.

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.

To describe the clinical characteristics of patients who were alerted for suspected HCM by an AI-based ECG tool and newly diagnosed, previously diagnosed, or suspected for HCM.

To describe the clinical characteristics of medical workup for patients who were alerted for suspected HCM by an AI-based ECG tool and newly diagnosed, previously diagnosed, or suspected for HCM.

To describe the clinical characteristics of treatment plans for patients who were alerted for suspected HCM by an AI-based ECG tool and newly diagnosed, previously diagnosed, or suspected for HCM.

To describe the clinical characteristics of closed care pathways (patients diagnosed who receive treatment) for patients who were alerted for suspected HCM by an AI-based ECG tool and newly diagnosed, previously diagnosed, or suspected for HCM.

To describe HCM access to care by socioeconomic status at the time of diagnosis.

Population evaluation for access to care by clinical stage of HCM at time of diagnosis.