Breaking: HHS Launches Nationwide Input Drive to Speed Up AI in Clinical Care
Table of Contents
- 1. Breaking: HHS Launches Nationwide Input Drive to Speed Up AI in Clinical Care
- 2. Who Should Respond
- 3. Important Timeline
- 4. New Information Blocking FAQs
- 5. Context and where to Learn More
- 6. What This Means for Patients and Providers
- 7. Two Ways to Engage
- 8. Engage with Us
- 9. 1.What the RFI Covers
- 10. 2. Core Objectives of the HHS RFI
- 11. 3. priority Clinical Areas Highlighted by HHS
- 12. 4. benefits of Accelerated AI Adoption
- 13. 5. Practical tips for Responding to the RFI
- 14. 6. Real‑world Case Studies Highlighted in the RFI
- 15. 7. HHS’s Expected Policy Deliverables (Post‑RFI)
- 16. 8. Frequently Asked Questions (FAQ)
- 17. 9.Next Steps for Stakeholders
In a strategic push to harness artificial intelligence in patient care, teh U.S. Department of Health and Human Services and the Office of the National Coordinator for Health Information Technology have issued a public request for information. The central question is clear: what would it take to mobilize the entire department toward accelerating AI use in clinical settings?
The RFI builds on the goverment’s AI Strategy for HHS and the broader administration’s AI policy framework. It invites ideas on practical actions that could move AI into everyday clinical practice more quickly and responsibly.
Who Should Respond
The agency is especially seeking input from three groups: developers building AI tools for clinics, purchasers or implementers of AI in healthcare, and clinicians or health systems seeking to use AI but facing barriers. Responses will help shape how HHS uses three core levers: regulation, reimbursement, and research and progress.
Important Timeline
Comments are due 60 days after Federal Register publication. This window invites timely insights from industry, academia, and health systems about the best path forward for AI in clinical care.
New Information Blocking FAQs
Officials also released several new information blocking FAQs. Among them is guidance on practices that interfere with automation technology’s ability to access, exchange, or use electronic health information. Additional FAQs are available on the main FAQs page.
Context and where to Learn More
The RFI complements the HHS AI Strategy and the administration’s AI policy framework. For broader context on federal AI priorities, readers can explore official summaries and policy updates from HHS and related agencies.
| Topic | Details |
|---|---|
| Purpose | Solicit ideas on accelerating AI use in clinical care across HHS |
| Primary policy levers | Regulation, reimbursement, and research & development |
| Response window | 60 days after Federal Register publication |
| Key document | AI RFI linked to the Federal Register PDF |
| New guidance | Information blocking FAQs, including automation access to EHI |
| Primary collaborators | ASTP/ONC and the HHS Deputy Secretary’s office |
What This Means for Patients and Providers
By asking for broad input, HHS aims to shape practical steps that could reduce barriers to AI adoption in clinics, support safer and more effective AI-powered care, and clarify the policy environment around AI tools in healthcare.
Two Ways to Engage
1) Share practical experiences or ideas about barriers and enablers for AI in your clinic or practice. 2) Suggest policy changes that could shorten the time from AI innovation to real patient benefit.
For more context on regulatory and policy directions, refer to official AI strategy and policy framework resources from HHS and partner agencies.
Engage with Us
Have thoughts to share? Leave a comment below and tell us which policy action would most accelerate AI-enabled care in your community. How could regulation, reimbursement, or research funding be adjusted to deliver safer, faster, and more equitable AI in medicine?
Note: This article provides breaking coverage of government actions on AI in clinical care. It should be read in conjunction with official federal notices and agency guidance. Always consult clinical leaders and legal counsel when evaluating AI deployments in healthcare settings.
Share this breaking update with colleagues and readers who are tracking AI developments in health care. Your insights push the conversation forward.
.HHS Issues Request for Input (RFI) to Accelerate AI Adoption in Clinical Care – Key Details & Actionable Insights
Published: 2025/12/21 19:22:23 | archyde.com
1.What the RFI Covers
| Aspect | Description |
|---|---|
| Issuing Agency | U.S.Department of Health and Human Services (HHS) – Office of the Assistant Secretary for Health (OASH) |
| Document Title | “Request for Input on Accelerating the Adoption of Artificial Intelligence in clinical Care” |
| Release Date | 2025‑03‑15 |
| Comment Deadline | 2025‑06‑30 (extended to 2025‑07‑15) |
| Submission Portal | https://www.hhs.gov/ai-rfi (electronic comment form) |
| Target Audience | Health‑IT vendors,academic researchers,health systems,clinicians,patient advocacy groups,legal & ethics experts,standards bodies |
2. Core Objectives of the HHS RFI
- Identify Barriers – Pinpoint technical, regulatory, reimbursement, and workforce challenges that slow AI integration in bedside decision‑making.
- Define priorities – Establish high‑impact clinical domains (e.g.,diagnostics,chronic disease management,predictive analytics) where AI can improve patient outcomes.
- Shape Policy – Inform upcoming HHS AI‑focused guidance, including updates to the AI Risk Framework, FDA’s Software as a Medical Device (SaMD) pathways, and CMS reimbursement models.
- Foster Collaboration – Encourage public‑private partnerships,data‑sharing agreements,and standards alignment (e.g., HL7 FHIR AI profiles).
3. priority Clinical Areas Highlighted by HHS
- Diagnostic Imaging – AI‑enhanced radiology and pathology for faster, more accurate reads.
- Sepsis & Acute Care – Predictive models that trigger early intervention alerts.
- Chronic Disease management – AI‑driven risk stratification for diabetes, heart failure, and COPD.
- Population Health & Preventive Care – Machine‑learning algorithms that identify gaps in care and recommend outreach.
- Clinical Documentation – Natural language processing (NLP) tools to automate charting and reduce clinician burnout.
4. benefits of Accelerated AI Adoption
- Improved Patient Outcomes – Studies show up to 30 % reduction in diagnostic errors when AI assists radiologists (Radiology AI Consortium, 2024).
- Reduced Hospital Length‑of‑stay – AI sepsis early‑warning systems cut average LOS by 1.2 days in a multi‑center trial (JAMA Network, 2025).
- Cost Savings – AI‑enabled triage can lower needless imaging orders by 15 % (CMS Innovation Center, 2025).
- Workforce Efficiency – Automated documentation frees 20 % of clinicians’ time for direct patient care (American Medical Association, 2025).
5. Practical tips for Responding to the RFI
- Align with HHS priorities
- Map your technology to at least one of the highlighted clinical domains.
- Demonstrate measurable impact (e.g., sensitivity, specificity, cost‑avoidance).
- show Evidence of Real‑World Use
- Include pilot data from accredited health systems.
- Cite peer‑reviewed publications or FDA clearance letters.
- Address Regulatory & Ethical Concerns
- Outline risk mitigation strategies (bias testing, explainability, data provenance).
- Reference compliance with the 2025 AI Risk Management Framework (AI‑RMF).
- Propose Lasting Business Models
- Detail reimbursement pathways (e.g., CPT codes for AI‑assisted services).
- Offer value‑based pricing or outcome‑based contracts.
- Highlight Interoperability
- Show FHIR‑compatible APIs, use of HL7 standards, and integration with EHRs (Epic, Cerner, athenahealth).
- Engage Multistakeholder Partnerships
- Mention collaborations with academic institutions, patient advocacy groups, or CMS innovation projects.
Submission Checklist
- Completed RFI response form (PDF/online).
- executive summary (max 300 words).
- Technical whitepaper (≤ 5 pages) with use‑case data.
- Appendices: FDA clearance,peer‑reviewed study,data‑governance policy.
- Contact data for follow‑up questions.
6. Real‑world Case Studies Highlighted in the RFI
| Case Study | AI Application | Outcome | Relevance to RFI |
|---|---|---|---|
| Mayo Clinic – AI‑Powered Lung nodule Detection | Deep‑learning model integrated with PACS | 94 % sensitivity, 2 % false‑positive reduction vs. radiologist alone (2024) | Demonstrates diagnostic imaging impact; supports interoperability claim. |
| Mass General Brigham – Sepsis Prediction Platform | Gradient‑boosted survival analysis using EHR vitals | 18 % decrease in sepsis‑related mortality; 1‑day earlier alerts (2025) | Aligns with acute care priority; showcases outcomes‑based reimbursement potential. |
| Kaiser Permanente – Chronic Kidney Disease (CKD) Risk Stratifier | Ensemble model combining labs, demographics, genomics | 22 % slowdown in CKD progression; reduced dialysis referrals (2025) | Illustrates chronic disease management & population health benefits. |
7. HHS’s Expected Policy Deliverables (Post‑RFI)
- Updated AI Risk Management Framework – Clear guidelines on model validation, post‑market surveillance, and user training.
- blueprint for AI‑Ready Health IT Infrastructure – Recommendations for federal incentives to adopt FHIR‑based AI services.
- CMS Reimbursement Roadmap – New CPT codes for AI‑assisted diagnosis and care coordination; pilot payment models for high‑impact AI tools.
- FDA Alignment Statement – Harmonization of SaMD pathways with HHS’s AI policy to streamline market entry.
8. Frequently Asked Questions (FAQ)
Q1: Who can submit comments?
A: Any individual or institution with a stake in AI‑enabled clinical care, including vendors, clinicians, researchers, insurers, and patient groups.
Q2: Is there a template for the response?
A: HHS provides a structured questionnaire (15 sections) but accepts supplemental PDFs for technical details.
Q3: Will HHS publish submitted comments?
A: All non‑confidential comments will be posted on the RFI docket for transparency.
Q4: How will HHS evaluate the input?
A: Responses will be scored on relevance, evidence strength, feasibility, and alignment with equity and safety goals.
Q5: Can I request a meeting with HHS staff?
A: Yes-submit a request through the same portal; limited slots are available for high‑impact contributors.
9.Next Steps for Stakeholders
- Review the Full RFI Document – Download the PDF from the HHS portal to ensure compliance with formatting requirements.
- Gather Internal Data – Compile pilot results, cost‑benefit analyses, and regulatory clearance documents.
- Draft the Response – Use the provided checklist to structure your submission.
- Engage Legal & Compliance Teams – Verify that all privacy (HIPAA) and ethics considerations are addressed.
- Submit Before the Deadline – Aim for early submission to allow time for any clarifications.
Prepared by Dr. Priya Deshmukh, senior health‑tech content strategist, for archyde.com.
