In many cases, the problem isn’t that “AI did something bad.” It’s that an AI-enabled step can shape what gets ordered, what gets noticed, and what gets documented—then clinicians may rely on that output without sufficient verification.
Locally, diagnostic issues can be tied to the realities of fast-paced care settings, including:
- Busy urgent care or ER visits where symptoms are assessed quickly and follow-up is critical
- Imaging and lab workflows where reports must be reviewed, acknowledged, and acted on
- Automated triage or risk scoring used to route patients or prioritize workups
- Decision support tools that influence what clinicians think is “most likely”
If the record shows that important findings were overlooked, delayed, or treated as less urgent than they should have been, that can become legally significant.


