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Regulatory & Policy

Tracks and explains regulatory developments, policy guidance, and governance standards directly relevant to AI in healthcare. Covers FDA AI/ML SaMD action plans and device authorizations, CMS coverage and reimbursement decisions, WHO ethics and guidance publications, CHAI assurance standards, EU AI Act implications for medical devices, and international regulatory frameworks. Each entry is dated, source-attributed, and contextualizes the significance of the development for clinical practice, procurement, and research. This group serves policy professionals, health system administrators, researchers, and legal/compliance teams who need accurate, current regulatory intelligence. Excludes speculative policy commentary without cited basis. Entries link to primary regulatory source documents.

Jurisdictions

  • US
  • US / EU

Regulatory & Policy Entries

  • CMS Prior Authorization and AI: How Three Federal Rules Are Reshaping Utilization Management

    Effective Date:

    A structured policy analysis of how CMS-4201-F, CMS-0057-F, and the WISeR Model together constitute a deliberate federal strategy to introduce AI and electronic automation into prior authorization — examining each instrument's regulatory theory, compliance obligations, and the unresolved tensions around AI transparency, financial incentives, and health equity that will define the debate through 2026 and beyond. Written for health policy professionals, payer compliance officers, hospital administrators, and clinicians engaged in utilization management policy.

  • ONC Information Blocking Rule: What It Means for AI Systems, Agentic Workflows, and Healthcare Data Access

    Effective Date:

    A structured policy analysis of how the ONC information blocking framework under the 21st Century Cures Act has evolved into the dominant federal mechanism governing AI data access in healthcare — covering HTI-1 algorithm transparency requirements, the HTI-5 proposed rule's deregulatory paradox, and the active enforcement shift of early 2026 that transforms information blocking from a theoretical compliance risk into an operational AI governance imperative. Written for health policy professionals, compliance officers, EHR developers, and health system AI teams.

  • AI in Medicine: How the U.S. Regulatory Framework Actually Works

    Effective Date:

    A structured overview of how the FDA, ONC, and CMS regulate AI applications in clinical medicine — what gets classified as a medical device, what doesn't, and where the policy gaps remain as of Q2 2026.

  • US / EU

    Artificial Intelligence in Health: The Regulatory Landscape in 2026

    Effective Date:

    A structured overview of the formal regulatory and policy actions shaping artificial intelligence in health as of Q2 2026 — covering FDA guidance updates, CMS reimbursement positions, ONC rulemakings, and the EU AI Act's healthcare provisions, with scope labels and primary source references for each entry.

  • US

    FDA AI/ML SaMD Action Plan (2021): Five Commitments, Key Deliverables, and Implementation Status Through Q2 2026

    Effective Date:

    A structured policy-tracker record tracing the FDA's January 2021 AI/ML Software as a Medical Device Action Plan — its five regulatory commitments, the specific guidance documents each produced from 2021 through early 2025, and what remains unfinished or unaddressed as of Q2 2026. Intended for regulatory professionals, SaMD developers, and policy researchers tracking the FDA's evolving framework for continuously learning algorithms.

  • US

    FDA PCCP Guidance for AI-Enabled Devices: Document Record, Version History, and Current Status (Q2 2026)

    Effective Date:

    A structured regulatory tracker record for FDA docket FDA-2022-D-2628 — the Predetermined Change Control Plan guidance for AI/ML-enabled device software functions — documenting its statutory origin, the material changes from the April 2023 draft to the December 2024 final and August 2025 update, adoption data, and open companion document status as of Q2 2026. Intended for regulatory professionals, policy researchers, and SaMD developers who need a primary-source-anchored reference for this specific guidance document's lifecycle.

  • US

    FDA Predetermined Change Control Plan for AI/ML Medical Devices

    Effective Date:

    A structured reference entry on the FDA's Predetermined Change Control Plan (PCCP) framework — what it permits AI/ML device manufacturers to do, how submissions are structured, what regulatory boundaries apply, and why it matters for post-market device management.