AI Governance Framework - Healthcare Edition

Overview

Healthcare AI governance is ultimately about patient safety. Every governance structure, every control, every review process exists to ensure AI helps—not harms—patients. This framework builds on that foundation while addressing the complex regulatory landscape and operational realities of healthcare organizations.

Deploy this framework to govern clinical decision support, diagnostic AI, administrative automation, and all AI touching patient care.

What's Inside

• Why Healthcare AI Governance Is Different: Patient safety stakes, regulatory complexity (FDA, HIPAA, state laws), clinical workflow integration, health equity imperatives, physician autonomy considerations
• Healthcare AI Regulatory Landscape: FDA medical device regulations (SaMD, CDS exemptions), HIPAA Privacy and Security Rules, state healthcare AI laws, CMS requirements, accreditation standards
• Framework Architecture: Healthcare governance structure integrating with medical staff, quality, compliance, and privacy functions
• The 5 Pillars for Healthcare AI:
  • Strategy & Leadership with clinical leadership engagement
  • Risk Management emphasizing patient safety
  • Compliance with healthcare regulatory requirements
  • Ethics grounded in medical ethics traditions
  • Operations for clinical workflow integration
• Organizational Structure: Healthcare-specific roles—CMIO involvement, clinical informaticists, patient safety integration, IRB coordination
• Implementation Roadmap: Phased approach accounting for clinical validation, FDA pathways, and EHR integration timelines
• Healthcare-Specific Policy Templates: Clinical AI use policies, HIPAA AI addendum, patient consent for AI
• Governance Maturity Model: Healthcare benchmarks with patient safety focus
• Measurement & KPIs: Healthcare-specific metrics including patient outcomes, safety events, regulatory compliance
• Case Studies: Healthcare AI governance successes and failures with lessons learned
• Appendix: Healthcare AI Tools & Resources: Templates, checklists, and reference materials

Who This Is For

• Chief Medical Information Officers responsible for clinical AI
• Chief AI Officers in healthcare organizations
• Patient Safety Officers ensuring AI doesn't harm patients
• Privacy Officers managing HIPAA AI compliance
• Healthcare CIOs deploying AI technology

Why This Resource

Healthcare governance must satisfy FDA, protect patient privacy under HIPAA, ensure health equity, and maintain physician trust—all while enabling AI's clinical benefits. This framework addresses healthcare's unique requirements, not generic governance principles applied to healthcare.

Clinical pathway integration ensures governance works within healthcare operations, not against them.

FAQ

Q: How do we govern FDA-regulated AI?

A: The regulatory landscape section covers FDA requirements—SaMD classification, approval pathways, and post-market obligations. The framework integrates FDA compliance into governance structures so regulatory requirements are met through normal governance operations.

Q: What about AI that uses PHI?

A: HIPAA compliance is woven throughout the framework—in risk management, compliance, and operations pillars. Healthcare-specific policy templates include HIPAA AI provisions.

Q: How do we ensure health equity in AI?

A: The ethics pillar addresses health equity specifically—bias testing requirements, equity monitoring, and ensuring AI serves all patient populations. This extends throughout governance as a core requirement, not an afterthought.