Few things in American healthcare are as universally disliked as prior authorization.
A doctor recommends a treatment, and before the patient can receive it, someone at the health plan has to review the request against the plan's medical policies and decide whether to approve it.
Done slowly, it delays care, sometimes dangerously. Done at scale, it consumes armies of nurses and clinicians on both sides. The work is high-volume, high-stakes, document-heavy, and deeply rules-bound, which is exactly the shape of problem AI is now good at.
A New York company called Anterior has built clinician-led AI to take it on.
Its platform reads a prior-authorization request, checks it against the plan's clinical criteria, and helps the payer approve appropriate care in seconds instead of days.
This is a deep look at what Anterior does, the results it reports, and, just as important, what it actually takes to deploy this inside a health plan so it delivers the return on investment it promises.
That last part is where healthcare AI succeeds or fails.
Read more on this on AiDOOS blog at: https://aidoos.com/blog/anterior-ai-prior-authorization/
