Doctors publish case studies all the time which contain anonymized data. Presumably those go through reviews to make sure that nothing is being leaked but health data by it's nature is specific but not very personal (at least not identifiable).

Also, depending on what you're using ChatGPT for, this is no worse than Googling something which doctors do a lot as well.

This is the prompt that was listed.

“Write an appeal letter to a medical insurance company for a patient who needs a biopsy for a bone lesion given prior unclear diagnosis.”

Add an arbitrary ip address and timestamp and you are very far away from anything personally identifying. (Where does your computer suggest you are right now?)

De-anonomizing is usually done by combining datasets. That seems unlikely here.

Probably not. You fill in the PII afterwards and it’s essentially just metadata. Patient has this condition, needs this test, has had this and that happen” those things aren’t PII. Leave out names, places, ID numbers, etc and you have appropriately deidentified a document.

find replace name with ABCEDFG HIJKLMNOP

feed to ChatGPT

find replace ABCEDFG HIJKLMNOP with name?

A date of what? The request to ChatGPT to generate an imaginary appeal?

So you know the individual was rejected prior to that. Probably. Maybe.

And maybe roughly where the individual is located, because ChatGPT sees an IP off of… something.

So somewhere, someone asked ChatGPT about a rejected treatment or procedure appeal.

Now if the doctor provides a poorly written appeal and asks for it to be fixed, that is another case entirely, especially if they left in patient info. But there is a very large gap between these two situations, and the first one isn’t nearly as much as you suggest.