In our experience, disputes often start after a second look—sometimes at a follow-up appointment, sometimes when a patient requests records for a new specialist, and sometimes after a complication that “doesn’t fit” the explanation given at discharge.
Common ways AI-related issues surface include:
- Imaging or report inconsistencies: findings that appear in an automated or system-generated summary but don’t align with later reads or your symptoms.
- Generated or auto-populated documentation: notes that reference “decision support,” templated assessments, or imported data you never saw verified.
- Care coordination gaps across facilities: when results are transmitted between providers, automated summaries may be incomplete, late, or misunderstood.
- Timeline confusion: when the sequence of events in the record (pre-op, intra-op, post-op) conflicts with what you were told.
Surgery is already high-stakes. When additional technology steps are involved, the question becomes whether the clinical team verified what the system produced and responded appropriately to the patient in front of them.


