The EchoGo Heart Failure platform is reportedly the only AI-powered technology to receive a CPT reimbursement code for echocardiography detection of heart failure with preserved ejection fraction.
For clinicians utilizing the artificial intelligence (AI)-enabled EchoGo Heart Failure technology to assess patients for heart failure with preserved ejection fraction (HFpEF), the American Medical Association (AMA) has issued a new Category III CPT reimbursement code (0923T), which will go into effect on January 1, 2025.1
Recently published research revealed a sensitivity rate of 87.8 percent and a specificity rate of 81.9 percent for EchoGo Heart Failure, which can detect HFpEF based off assessment of one echocardiographic video, according to Ultromics, the developer of the technology.2
Ultromics said the new CPT code, which will replace the current HCPCS outpatient code C9786, supports the growing role of EchoGo Heart Failure in facilitating improved accuracy in detecting the frequently undiagnosed HFpEF.
“This recognition by the AMA underscores the significant impact our technology is having in the field of heart failure care. HFpEF represents a significant and growing patient population, accounting for 50% of heart failure cases worldwide, and may go undiagnosed in up to 64% of cases. We believe that EchoGoHeart Failure will transform diagnostic pathways for these patients, enable earlier intervention, improve quality of life, and deliver benefits to payors and healthcare systems,” noted Ross Upton, Ph.D., the chief executive officer and founder of Ultromics.
References
1. Ultromics. Ultromics granted Category III CPT reimbursement code for EchoGo Heart Failure. PR Newswire. Available at: https://www.prnewswire.com/news-releases/ultromics-granted-category-iii-cpt-reimbursement-code-for-echogo-heart-failure-302187915.html . Published July 2, 2024. Accessed July 2, 2024.
2. Akerman AP, Porumb M, Scott CG, et al. Automated echocardiographic detection of heart failure with preserved ejection fraction using artificial intelligence. JACC Adv. 2023;2(6):100452. Doi: 10.1016/j.jacadv.2023.100452.
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