The scariest part is that these numbers—11 nurses and 5 physicians—came from an extremely small dataset, and we have now confirmed our conclusions were correct.
Now we’re sorting through a massive amount of data.
Medical Board of California (MDs): 155,303 current Physician and Surgeon licenses in effect.
Osteopathic Medical Board of California (DOs): 17,164 licensed osteopathic physicians and surgeons in effect.
California Board of Registered Nursing (BRN) 579,169 licensed Registered Nurses.
Even with advanced custom-written AI to sort credentials and conduct deep dives into records, an enormous amount of human capital must still be expended during the verification phase to confirm physician and nurse licensing and verify that they indeed hold a valid degree.
The issues with credentialing platforms like Medallion, Modio Health, Assured, Verifiable, symplr Provider, Credentially, FileFlo, MedTrainer, and ProviderPassport seem to be intentional.
Even the strongest tools leave a confirmation phase requiring human capital because:
- Not every board or school exposes a reliable API.
- Identity collisions (common names, hyphenation, former names) need review.
- Foreign medical/nursing schools and older records are uneven.
- Accreditation rules still expect primary-source evidence and documented exception handling.
- Privileging, competency, and “is this person actually who they claim” questions sit above a green license status.
So my original point still holds: AI can sort and deep-dive at scale, but confirming that a physician or nurse holds a valid license and degree still requires human review for exceptions, mismatches, and audit sign-off.
We have identified 11 nurses and 5 physicians in five Southern California hospitals who may have counterfeit degrees from India, including a current emergency medicine trauma surgeon.