When people hear “AI misdiagnosis,” they often assume it’s a single software mistake. In real life, issues tend to show up as a chain of decisions—especially when patients are seen across multiple settings.
Common patterns we investigate for Reidsville families include:
- Imaging review delays or incomplete reads (e.g., scans handled by automated workflows before a final clinical interpretation)
- Triage or risk-scoring routing problems that influence how quickly someone is escalated
- Lab result handling issues where abnormal findings weren’t flagged early enough for follow-up
- Clinical decision support outputs treated as more certain than they should be
- Documentation gaps between visits that make it harder to connect symptoms to the correct diagnosis
Whether the tool was used directly or indirectly, liability usually turns on what clinicians and the facility did with the information available at the time—and whether they met the accepted standard of care.


