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Five Lessons Learned Building AI in Digital Health

You don’t get to decide whether AI comes to healthcare. You do get to decide when and how you adopt it.

Drew Ivan, Chief Architect at Rhapsody, shared with the ViVE audience what he learned designing and deploying an AI assistant for healthcare integration workflows. He covered what worked, what didn’t, and how those lessons translate into practical value for your team.

Drew’s five lessons:

  • Culture comes first. Pitch AI as a way to work further down your project list, not to cut roles.
  • Data drives everything. Rhapsody trained Autopilot, which resolves gray-area patient identity matches, on its reviewers’ own decisions.
  • Move before you’re certain. Better a speeding ticket than a parking ticket. Rhapsody threw out its first prototype and replatformed to move faster.
  • Experts seed the team. New AI hires and longtime product experts now level each other up.
  • The time is now. AI adoption is a cultural change first, a technology change second.

Watch Drew’s full session below. Then read his take on why the health system is the hard part of AI.

Most healthcare AI projects don’t fail at the model. They fail at the data.
Rhapsody gives you the integration, identity, and terminology infrastructure to make healthcare data trustworthy enough for AI to use.

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