The Ohio State University Wexner Medical Center (OSUWMC) manages thousands of referrals and payor communications via fax, a highly manual process that delays patient care coordination and increases administrative workload for clinicians.
Cuvris piloted an AI-driven document triage solution to automate fax intake, classification, and integration into hospital systems, reducing manual effort and improving speed and accuracy.
My role
I led the end-to-end design of the referral and payor fax workflows within our post-acute care coordination platform. The system leverages intelligent agents that listen, speak, extract, and represent data from unstructured documents. Helping reduce manual fax handling time by up to 70-80% through AI automation, enabling clinicians to dedicate more time to patient care.
Deliverables:
AI DOCUMENT TRIAGE
One of the earliest design challenges was figuring out how to present dozens of incoming documents without overwhelming users. I worked with our ML team to surface classification results directly into the inbox so instead of just filenames, users see each document pre-labeled by the agent: Referral, Payor Doc, or Needs Review.
