Minimize disruptions from decommissioning

Why does this matter?

AI products may fail or need to be stopped abruptly. This can cause disruptions in clinical workflow and healthcare operations. If the AI product is used in a critical task, sudden changes to the product could lead to patient harm.

How to do this?

Step 1: Assess preparedness 

Step 2: Keep stable components of the solution running

  • Work with the AI product developer to understand which components of the solution are unstable and need to be decommissioned.
  • Maintain stable components of the solution, which may continue to be helpful, even if an AI model is no longer meeting performance expectations. 
  • Consider turning off  isolated, unstable components of the solution, while continuing to run more stable components of the solution. Work with the AI product developer to uncouple unstable components from stable components. 

Step 3: Empower the clinical lead to transition to a new workflow

“Obviously, you know, the stakeholders… especially for clinical solutions, who are dependent on those solutions have to be given an alternative that they see as more beneficial than what you’re decommissioning.”

Technical Leader

Step 4: Generate and dissemination information about decommissioning

Step 5: Closely monitor the care delivery setting and work environment 

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