Many diagnostic failures aren’t obvious at first. They show up in patterns tied to how patients move through the system:
- Repeat visits after symptoms persist (a patient returns to urgent care/ER because the problem isn’t improving).
- Imaging and lab delays—results come back after the visit, but follow-up doesn’t happen quickly enough.
- “Watch and wait” that turns into a lost opportunity—a diagnosis is deferred while symptoms worsen.
- Communication gaps between providers (primary care, specialists, imaging centers, and hospital systems).
Where AI may enter the picture, it’s often through workflows such as triage support, documentation assistance, risk scoring, or imaging/lab interpretation tools. Even when a tool is intended to help, legal responsibility still turns on whether clinicians and the facility appropriately reviewed, verified, and acted on the information available at the time.


