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Blog
Demetri Giannikopoulos

The Roles to Include in AI Governance Conversations

Adoption, C-Suite, Information Technology
Table of Contents

Healthcare operates on a “minimum viable access” basis to ensure sensitive information is restricted to only those who truly need it to deliver quality care. In diagnostic imaging, the guiding principle of safety is “ALARA” or “as low as reasonably achievable.” 

According to the CDC, ALARA means avoiding exposure to radiation that does not have a direct benefit to you, even if the dose is small. To do this, you need three basic protective measures: time, distance and shielding.

This principle is a great example to apply to AI governance. 

Much like imaging, multiple inputs can enhance understanding, but too much information – or excessive radiation – can overwhelm and compromise the system.

In working with more than 1,200 healthcare organizations, we’ve encountered many AI governance models, but the biggest challenge for most facilities is speed. Delays in reviews, scheduling and clarifications, often compounded by conflicting guidance, hinder progress. Agile, empowered decision-making structures are essential for efficient and effective governance.

With the rapid evolution of care our nation is experiencing, having clear lines of responsibility and fostering informed decision-making is crucial to AI’s success.  

That’s not to say diversity in opinions isn’t important, it’s simply a matter of bringing in the right voices at the right time rather than setting up a structure where decision paralysis and conflicting interests could stall momentum. 

Since enthusiasm and support are critical aspects of change management, here are tips for establishing an AI governance structure that is agile but allows for broader collaboration. 

The “Minimum Viable Stakeholders”

Consider these individuals the foundation of your governance committee and the drivers that have ultimate decision authority. 

  • Executive Champion: This individual is responsible for KPIs and ensures alignment to facility strategy. They should also hold budget responsibility.   
  • Clinical Champion: This individual identifies opportunities to support better patient care and outcomes. They should also be a key conduit between stakeholder groups. 
  • Department Chair: A key figure in successful AI adoption for end users. Their support is necessary for resource allocation and change management initiatives. 
  • IT Leader: They will ensure smooth integration with existing systems and assess the short and long-term data, security and management needs.

Essential Voices at the Right Time

With evolving regulations and patient care needs, it is important to know the internal and external experts to engage when needed.

  • Legal: Ensures compliance with state, federal and regulatory requirements and reviews business contracts for new solutions.
  • Quality: Helps develop monitoring and performance metrics to measure the impact of the solution on quality improvement initiatives.  
  • AI Partner: Your partner likely has experience working with other health systems and can share best practices for governance and regulatory compliance.

Powerful Advisors

Since ongoing governance deals with monitoring performance, ensuring compliance and assessing future needs, many voices hold value.  

  • Project Manager: In the initial vetting, an implementation project manager is a must have resource for success. With ongoing monitoring their advisor role will step back a bit but still prove important for ongoing success.
  • Patient Experience: Patient experience and outcomes is the north star by which healthcare operates. The opinion and engagement of the patient experience team will prove invaluable to the successful adoption of AI. With the Open Notes Rule included in the 21st Century Cures Act, patients have greater access to their medical journey than ever before. 
  • Finance: With the newly emerging standards of care, finance is an advisory role that should be included often and early through the governance process. 
  • Marketing: We’re all doing this together. Having the advice and support of the marketing team will set you up for ongoing success. Remember: “if a tree falls in a forest and no one is around to hear it, does it make a sound?”

Clinical AI Governance Best Practices

Successful AI governance isn’t about creating a bureaucratic nightmare, rather it should foster a collaborative environment that prioritizes responsible AI adoption for the benefit of patients and clinicians alike. By adopting a “strong core” with an extended teams of advisors approach to AI governance, you can ensure focused decision-making without stifling enthusiasm.

Before you put an AI governance infrastructure in place, read these best practices and pitfalls.

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Demetri Giannikopoulos

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