Garfield’s healthcare environment can involve tight schedules, high patient turnover, and frequent urgent-care or ER visits—conditions where diagnostic errors can slip in. In these settings, a “best guess” can get locked in quickly, and follow-up may be delayed when symptoms shift or when test results aren’t escalated properly.
In AI-influenced workflows, that problem can be amplified:
- A risk score or prediction may influence triage priority.
- Imaging or lab interpretation assistance may shape what clinicians focus on.
- Documentation tools may streamline notes in ways that inadvertently omit context.
The result is often the same: the care team moves forward based on incomplete or misunderstood information, and the patient pays the price.


