In our experience, potential AI involvement often comes to light in ways that feel unsettling—particularly when the medical story doesn’t line up with what you were told or what your body experienced.
Common Palatka scenarios we see include:
- Discharge paperwork or follow-up summaries that reference automated outputs you weren’t informed about.
- Imaging or report language that appears to come from automated interpretation, but the clinical team didn’t respond appropriately to what it indicated.
- Inconsistent charting—for example, dates, timings, or descriptions that don’t match the operative timeline.
- Care decisions that seem influenced by computer-generated risk scores or documentation templates rather than the patient’s actual condition.
- Delay in escalation—when symptoms worsened after surgery, but the team’s response didn’t reflect the seriousness suggested by the clinical picture.
These aren’t “proof” by themselves. But they are clues that an investigation should look closely at how the tool was used, what information it relied on, and whether clinicians verified and acted responsibly.


