Viz.ai Announces CMS Reimbursement Pathway for Hypertrophic Cardiomyopathy via AI-Enhanced Electrocardiogram

Business Wire

29-07-2025

SAN FRANCISCO--(BUSINESS WIRE)--Viz.ai, the leader in AI-powered disease detection and intelligent care coordination, today announced that the Category III CPT codes for AI-enabled electrocardiogram (ECG) analysis accepted and established by the American Medical Association (AMA) CPT Editorial Panel establish a national reimbursement framework for AI algorithms that perform ECG analysis for cardiac pathology, including conditions like hypertrophic cardiomyopathy (HCM), for which Viz HCM was designed.
The Centers for Medicare & Medicaid Services established a Medicare rate of $128.90, effective January 1, 2025, for CPT codes 0764T and 0765T which apply to 'electrocardiograph, computerized analysis with artificial intelligence, for detection of cardiac pathology, with physician or other qualified health care professional interpretation and report' related to concurrently performed ECG or previously performed ECG respectively. These codes facilitate national reimbursement for AI algorithms like Viz HCM, which analyzes 12-lead ECGs to identify patterns consistent with HCM, a condition that often goes undiagnosed until serious complications arise.
'This is a major milestone for AI in cardiovascular care,' said Jamie Stern, senior director of Care Pathways at Viz.ai. 'Reimbursement for AI-powered ECG interpretation empowers clinicians to identify high-risk patients earlier, before symptoms progress or serious events occur—supporting more timely diagnosis, specialist referral, and treatment.'
Hypertrophic cardiomyopathy is one of the most common inherited heart conditions and a leading cause of sudden cardiac death, particularly in younger adults. Yet the majority of individuals living with HCM are undiagnosed. Viz HCM uses deep learning to flag patients at risk based on ECG data captured across a healthcare system in routine clinical workflows, advancing early detection and closing critical gaps in care. A recent study, published in JACC: Clinical Electrophysiology, demonstrated that Viz HCM achieved a high degree of accuracy in detecting HCM 1. The AI-ECG successfully identified 574 HCM patients, and in 691 cases where HCM was not identified the AI-ECG assisted in identifying alternate clinically relevant diagnosis, highlighting Viz HCM's value for more effective disease detection.
"Reimbursement is a meaningful step forward for the uptake of novel technologies,' said Joshua M. Lampert, MD, FACC, cardiac electrophysiologist and medical director of Machine Learning at Mount Sinai Fuster Heart Hospital. 'This development can provide institutions with a sustainable means to build and maintain the necessary infrastructure to provide safe and effective care for patients during an actively evolving healthcare modernization process."
The CPT codes 0764T and 0765T were first published in the CPT 2023 code set, effective for use on or after January 1, 2023. However, CMS had not established a national payment for these codes until January 1, 2025. This development enables physicians and health systems to integrate reimbursable AI-based ECG interpretation into routine care delivery.
Viz HCM is part of the Viz.ai One Platform, which connects disparate data and care teams in real time to accelerate diagnosis, streamline care coordination, and improve outcomes across a range of cardiovascular and neurological conditions.
1 Desai, M. Y., Rutkowski, K., Ospina, S., et al. (2025). Real‑world artificial intelligence–based electrocardiographic analysis to diagnose hypertrophic cardiomyopathy. JACC: Clinical Electrophysiology, 11(6). https://doi.org/10.1016/j.jacep.2025.02.024
About Viz.ai
Viz.ai is the pioneer in the use of AI algorithms and machine learning to increase the speed of diagnosis and care across 1,800 hospitals and health systems in the U.S. and Europe. The AI-powered Viz.ai One® is an intelligent care coordination solution that identifies more patients with a suspected disease, informs critical decisions at the point of care, and optimizes care pathways and helps improve outcomes. Backed by real-world clinical evidence, Viz.ai One delivers significant value to patients, providers, and pharmaceutical and medical device companies. For more information visit Viz.ai.