People assume misdiagnosis only happens in rare, dramatic ways. Locally, many cases start more quietly—during moments when speed and throughput matter.
Common Bloomington scenarios we see include:
- Repeat visits to urgent or emergency settings after symptoms don’t improve—followed by a later “correct” diagnosis.
- Imaging and lab handoffs where results are in the system, but the clinical team’s response is delayed or incomplete.
- Triage and risk-scoring workflows that route patients or recommend next steps, then get treated as more certain than they should.
- Communication gaps between departments (or between an initial provider and a follow-up clinician), especially when a patient needs prompt escalation.
When automated tools are involved, the legal question typically becomes: Were they used appropriately, verified correctly, and escalated when the facts didn’t match the output?


