In response to the U.S. Department of Health and Human Services' request for comments on the "Request for Information: Accelerating the Adoption and Use of Artificial Intelligence as Part of Clinical Care," the Academy collaborated with the American Society for Nutrition (ASN) in submitting input for consideration.
Key takeaways from the comments include:
- Federal funding for AI adoption across regulation, reimbursement and research; without sustained investment, policy reforms alone will not achieve scalable or equitable implementation.
- Absent sustained federal investment in data infrastructure, implementation science, and workforce capacity, accelerated AI adoption risks producing fragmented, opaque, and inequitable deployment, increasing safety risks and undermining public trust rather than improving care.
- Ambiguities in HIPAA, information blocking, and clinical decision support governance disproportionately hinder the development of continuous-learning AI systems and smaller or safety-net providers.
- Current reimbursement models fail to recognize AI as an enabler of clinical infrastructure, particularly disadvantaging prevention-, nutrition-, and population health–focused AI tools.
- National data assets such as NHANES and the NIH All of Us Research Program function as essential AI infrastructure and require sustained, expanded funding to support model validity, equity and public trust.
- Federal investment in applied implementation science and workforce capacity is necessary to translate AI innovation into real-world clinical impact.
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