Member Input on Artificial Intelligence in Clinical Care

The U.S. Department of Health and Human Services (HHS) Office of the Deputy Secretary has issued a Request for Information (RFI) seeking input on what HHS can do to accelerate the responsible adoption and use of artificial intelligence (AI) in clinical care.

As the nation’s principal health regulator and a major payer, HHS plays a significant role in shaping how AI technologies are developed, evaluated, reimbursed, and deployed across the health care system. Through this survey, the American Academy of Orthotists and Prosthetists is gathering input from its members to inform a consolidated response on behalf of the profession.

Regulatory Considerations
HHS seeks to establish a regulatory approach to AI that is clear, predictable, and proportionate to risk—one that supports innovation while protecting patient safety, data privacy, and public trust.

Reimbursement and Payment Policy Considerations
Payment policies strongly influence whether and how innovations are adopted in clinical care. Legacy fee-for-service systems may create challenges for integrating new technologies, including AI-enabled tools. HHS is seeking feedback on how reimbursement models might be modernized to better align with value, innovation, and patient outcomes.

The following questions are intended to capture your experiences, observations, and perspectives related to AI in clinical care, including its opportunities, limitations, and implications for clinicians, patients, and caregivers.
1.How do current HHS regulations influence the development, adoption, and use of AI in clinical care?
Please describe any observed impacts—positive or negative—on innovation, patient safety, data privacy, or clinical workflow. Where applicable, include specific examples.
(Required.)
2.How do existing reimbursement and payment policies affect the adoption and sustainability of AI-enabled tools in clinical care?
What changes, if any, could better align payment models with value, patient outcomes, and responsible innovation?
3.What are the primary barriers to private-sector innovation in AI for health care, and to the adoption and use of these tools in clinical care settings?
Consider regulatory, financial, technical, operational, or workforce-related factors.
4.In your experience, where have AI tools used in clinical care met or exceeded expectations related to performance, cost, or outcomes, and where have they fallen short?
What types of AI applications show the greatest potential to improve care quality, generate meaningful insights, or reduce costs?
5.What challenges within health care do patients and caregivers most want addressed through the adoption of AI in clinical care?
What concerns—such as trust, transparency, access, or equity—should HHS consider when evaluating the use of AI in clinical settings?
6.Is there anything else HHS should consider when developing policies related to AI in clinical care that was not addressed above?