AHCA/NCAL submitted comments recently to the Assistant Secretary for Technology Policy and the Office of the National Coordinator for Health Information Technology (ASTP/ONC) within the U.S. Department of Health and Human Services (HHS) in response to a
request for information (RFI) titled
Accelerating the Adoption and Use of Artificial Intelligence and use of in Clinical Care.
The RFI outlines the HHS strategy to support the responsible adoption of artificial intelligence (AI) in clinical care, focusing on regulation, reimbursement, and research & development. There were 10 specific questions asked by ASTP/ONC for public comment response. AHCA/NCAL submitted comments reflecting perspectives on the barriers and opportunities that adopting AI technologies in nursing homes (SNF/NF), assisted living (AL) facilities, and residences for individuals with intellectual and developmental disabilities (ID/DD).
From the AHCA/NCAL comment preamble:
Before we can provide responses to the ten specific questions this RFI seeks comment on, we believe it is important to share contextual information about our AHCA/NCAL provider members, the resident populations they serve, their current fragmented baseline digital capabilities, and historical financial, legislative, and regulatory barriers to initiating or accelerating the adoption of and use of AI as part of clinical care. We believe a critical issue that ASTP/ONC needs to consider as strategies are developed in response to the comments received to this RFI, is that increased adoption of AI in clinical care will remain extremely challenging if not impossible for LTPAC providers without first providing adequate support to eliminate the digital interoperability infrastructure gaps. True functional interoperability capacity across the healthcare ecosystem would provide the comprehensive information necessary to permit a secure, safe, and effective use of AI in clinical care.
Key AHCA/NCAL recommendations included in the AHCA/NCAL response were:
- Mandate age-stratified validation and bias testing for AI tools intended for use in Medicare populations.
- Expand interoperability standards to include geriatric-specific data elements (functional status, cognitive status, social determinants)
- Align payment policies to incentivize high-value AI adoption in LTPAC settings.
- Provide infrastructure support and technical assistance to enable AI readiness in under-resourced LTPAC providers.
- Prioritize research funding for AI applications addressing multimorbidity, functional decline, and other priorities for aging populations.
- Establish clear regulatory frameworks addressing liability, privacy, and algorithmic transparency for non-medical device AI tools.
- Create validation testbeds and evaluation frameworks that include LTPAC settings and geriatric populations.