A webinar moderated by MedCity News Editor-in-Chief Arundhati Parmar delved into findings of the recently published Healthcare AI Readiness Index. Panelists discussed how best to balance AI adoption, governance, how to scale AI at healthcare institutions and best practices for doing so. Sponsored by Cotiviti, the webinar included perspectives from Cotiviti CIO Sean Warren and Thomasina Anane, Associate Vice President, Enterprise Analytics, with the Alliance of Community Health Plans.
Cotiviti turns fragmented data into actionable insights. It helps healthcare organizations reduce waste, fraud, and abuse, and works with them to simplify their operations.
“In many ways, what we’ve become is the connective tissue that helps healthcare work more efficiently across all of the payers, providers, and other stakeholders,“ Warren said.
Anane referenced a recent annual meeting of ACHP, which included a candid discussion on AI governance.
“One theme that really came through clearly is that AI governance has to start well before deployment and evolve along the use case. Many of our health plans are grappling with issues like: What is my state saying about AI use? What does that look like federally and what does that look like as a health plan?….What data are actually involved? What decision is being influenced? What happens when the output is wrong?”
The biggest challenge with AI governance in a clinical and payer setting is the need for constant vigilance, a point made by both Anane and Warren.
“Deployment is really not the finish line,” Warren said. “It’s constant follow-up, constant security checks, and we have a lot of human-in-the-loop and human oversight with observability. It’s ten times more important when we add AI to the mix to be able to know what that AI is doing. Do you have the guardrails around what the AI is doing in your environment? Do you have the ability to undo it? Do you have the ability to follow and trace every transaction?”
Additionally, the webinar discussion also touched on other issues such as:
- What should leaders assess before moving an AI use case from pilot to enterprise deployment?
- Are traditional vendor questionnaires and point-in-time assessments still sufficient?
- What is driving shadow AI use?
- Important considerations for Chinese AI models and frontier AI models.
- Why might traditional cybersecurity controls be necessary, but insufficient in the new threat environment healthcare organizations face?
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Photo: Sandwish, Getty Images
