A proposed AI governance model for healthcare includes a cross-functional governance structure, clear policies and procedures, risk management, technical standards, stakeholder engagement, continuous monitoring, regulatory compliance, and incentive structures. The article recommends standardizing AI adoption, managing vendor risk, addressing AI in existing systems, and adopting best practices. The ultimate goal is to harness AI's transformative potential while maintaining a commitment to patient safety, ethics, trust, and transparency.
Key takeaways:
- AI in healthcare presents significant potential but also introduces unique risks that require structured governance approaches.
- Effective AI governance in healthcare necessitates a cross-functional structure, clear policies, risk management, and stakeholder engagement.
- Organizations should prioritize patient safety, ethical considerations, transparency, and regulatory compliance in AI adoption.
- Continuous monitoring, evaluation, and alignment with emerging AI guidelines are essential for successful AI governance in healthcare.