Artificial intelligence (AI) is transforming the way healthcare operates on a systemic level, creating revolutionary change, promise, controversy, and new challenges. This rapid evolution may leave professionals in the dark if they don’t keep up with the changes, and the field of cardiology is no exception. AI has reached into almost every component of cardiology, revolutionizing how cardiovascular diseases are not only diagnosed but also managed and treated, influencing data at every step of the process and contributing to patient outcomes. AI’s ability to analyze an unprecedented amount of data is a hallmark never before achieved in history. As part of American Heart Month, we are exploring the ways AI has impacted cardiology coding and what new changes are in store for 2026.
The power to analyze a wealth of data is having an exponential impact on cardiology, extending its capabilities into echocardiograms, electrocardiograms (ECGs), and imaging studies at a scale never seen before. Experts agree that AI algorithms have the potential to improve diagnostic accuracy, enhance patient monitoring, and predict outcomes on a scale and timeline that exceed traditional methods.
AI-driven tools are already enhancing the interpretation of ECGs and echocardiograms. A series of Category III codes detail the growth and impact of these services. First introduced in 2025, these Category III codes describe the application of AI in augmentative analysis, specifically in calculating QTc intervals and detecting heart failure noninvasively. In 2026, a brand-new code 0962T was introduced as part of this evolution, accounting for the expansion of these capabilities and advances in medicine.
| 0902T | QTc interval derived by augmentative algorithmic analysis of input from an external, patient-activated mobile ECG device |
| 0932T | Noninvasive detection of heart failure derived from augmentative analysis of an echocardiogram that demonstrated preserved ejection fraction, with interpretation and report by a physician or other qualified health care professional |
| 0962T | Assistive algorithmic analysis of acoustic and electrocardiogram recording for detection of cardiac dysfunction (eg, reduced ejection fraction, cardiac murmurs, atrial fibrillation), with review and interpretation by a physician or other qualified health care professional |
These codes highlight and showcase how AI is being integrated into routine cardiovascular care, supporting clinicians in making more informed decisions and ultimately optimizing patient outcomes. Beyond cardiovascular services, AI is making significant advances in medical imaging. The introduction of additional Category III codes in 2025 for chest imaging (0877T–0880T), as well as new codes in 2026 for noninvasive assessment of cardiac risk (0992T and 0993T), represents another leap forward in the application of AI.
The codes encompass the application of AI to improve the precision and efficiency of diagnosing conditions such as heart disease and abnormalities identified in chest X-rays and CT scans.
AI systems are expected to continue expanding their capabilities in the future, assisting radiologists in detecting early-stage diseases, reducing diagnostic errors, and even providing predictive analytics based on imaging data.
In 2023, the American Medical Association (AMA) laid out its principles on AI in healthcare. These principles were intended to build a robust framework to promote the safe, ethical, and effective use of AI. The framework also carries the responsibility of providing ethical guidelines to minimize the very real risks to patients, physicians, and other healthcare professionals that arise from technologies still being refined. There are several key areas professionals should be aware of, as outlined in our Peripheral & Cardiology Coder:
Oversight. The AMA advocates for a collaborative, cross-sector approach to AI governance, emphasizing the need for both government and non-government entities to participate in the development and regulation of AI technologies. This holistic governance approach ensures that risks associated with AI, such as data misuse or biased algorithms, are managed proactively. By fostering this collaboration, the AMA envisions a future where AI development is closely monitored but flexible enough to allow for innovation, addressing both safety concerns and opportunities for improved patient outcomes.
Disclosure and Documentation. In scenarios where AI directly affects medical decisions, clear and accurate documentation is essential. The AMA emphasizes the importance of disclosing AI’s role in patient care, decision-making, and healthcare records to maintain transparency, uphold ethical standards, and meet legal and compliance requirements. To ensure accuracy and accountability, healthcare professionals must implement checks and balances within the documentation process. This can involve routine audits, peer reviews, and verification systems that validate the data entered into patient records. Additionally, by documenting AI’s involvement appropriately, providers can ensure clarity in patient histories, establish a reliable chain of accountability, and reduce potential errors stemming from AI-assisted decision-making. This practice not only bolsters patient trust but also helps safeguard against legal liabilities by ensuring the accuracy of all AI-related interactions.
⚠️Your Cardiology Coding Remains Under Threat, Creating Significant Risk to Your Bottom Line. These Are NOT All the Tips and Tricks Necessary for Success.⚠️
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