American Heart Association Issues New Framework for Responsible AI Implementation in Healthcare

The American Heart Association has released a new science advisory calling for health systems to implement clear and simple rules for using artificial intelligence in patient care, as hundreds of healthcare AI tools have received FDA clearance but only a fraction undergo rigorous evaluation for clinical impact, fairness, or bias. Published in the Association's flagship journal Circulation, the advisory introduces a pragmatic, risk-based framework specifically designed for evaluating and monitoring AI tools in cardiovascular and stroke care.

The guidance comes at a critical time when AI is transforming healthcare faster than traditional evaluation frameworks can keep up, according to Dr. Sneha S. Jain, volunteer vice chair for the American Heart Association AI Science Advisory writing group. The advisory builds on prior published AI frameworks to identify critical gaps in current practices and provides health systems with key principles for building effective AI governance covering selection, validation, implementation, and oversight of AI tools.

The framework proposes four guiding principles for deploying clinical AI: strategic alignment, ethical evaluation, usefulness and effectiveness, and financial performance. These principles aim to ensure AI tools deliver measurable clinical benefit while protecting individuals from known and unknown harms. The advisory highlights concerning gaps in current practices, noting that only 61% of hospitals using predictive AI tools validated them on local data prior to deployment, and fewer than half tested for bias, according to a recent survey.

This variability in AI validation is most pronounced among smaller, rural, and non-academic institutions, raising significant concerns about consistent care delivery across diverse patient populations and patient safety. The American Heart Association's extensive network of nearly 3,000 hospitals participating in the Get With The Guidelines® quality improvement programs, including more than 500 rural and critical access facilities, positions the organization as a trusted leader in advancing responsible AI governance. The Association has committed over $12 million in research funding in 2025 to test novel healthcare AI delivery strategies for safety and efficacy.

The science advisory writing group emphasizes that monitoring of AI tools cannot end after deployment, as performance may drift when clinical practice changes or patient populations differ. Health systems should integrate AI governance into existing quality assurance programs and define clear thresholds for retraining or retiring tools if performance declines. Dr. Lee H. Schwamm, volunteer member of the American Heart Association committee on AI and Technology Innovation, stated that responsible AI use is essential rather than optional, and this guidance provides practical steps for health systems to evaluate and monitor AI tools to ensure they improve patient outcomes and support equitable, high-quality care.