Advancing Artificial Intelligence in Healthcare: Key Policy Focus Areas from the 2025 HHS Information Request
By
David C. Klonoff
Agatha F. Scheideman
Mandy M. Shao
Juan Espinoza
August 15, 2026
Clinical Scorecard: Advancing Artificial Intelligence in Healthcare: Key Policy Focus Areas from the 2025 HHS Information Request
At a Glance
Category Detail
Condition Artificial Intelligence in Healthcare Key Mechanisms Regulatory frameworks, reimbursement structures, and implementation science for AI integration. Target Population Healthcare providers and patients utilizing AI technologies. Care Setting Clinical settings integrating AI tools.
Key Highlights
HHS seeks public feedback on AI integration in healthcare. Focus on regulatory, reimbursement, and research strategies for AI. Diabetes management exemplifies AI's potential in clinical care. Emphasis on patient safety, data privacy, and public trust. Stakeholder engagement is crucial for shaping future AI policies. Guideline-Based Recommendations
Diagnosis
Management
Establish new FDA regulatory frameworks for AI in diabetes management. Develop enhanced reimbursement structures linked to clinical outcomes. Monitoring & Follow-up
Risks
Potential re-identification risks from AI analysis of CGM data. Concerns regarding privacy and civil rights due to behavioral profiling. Patient & Prescribing Data
Individuals with diabetes and other conditions benefiting from AI.
AI tools support risk prediction, clinical decision-making, and medication management.
Clinical Best Practices
Implement privacy-preserving strategies for AI applications. Utilize differential privacy and federated learning to protect patient data. Related Resources & Content
