In a community like Corte Madera, people often discover issues through familiar, real-world touchpoints:
- Follow-up visits where symptoms don’t match what you were told to expect
- Imaging or pathology updates that raise new questions about timing and interpretation
- Discharge paperwork that references automated summaries, templates, or decision-support outputs
- Second opinions where a surgeon or specialist notices gaps in documentation or inconsistencies in the clinical narrative
When AI tools are involved, the “problem” may not be a dramatic mistake you can point to immediately. Instead, it can look like:
- documentation that reads smoothly but doesn’t align with what was actually done
- automated risk assessments that appear to have influenced decisions
- imaging or analysis outputs that weren’t confirmed before acting
That’s why we focus early on the details that matter—before memories fade and before electronic records become harder to retrieve.


