Key takeaways
- Document AI classifies each page of a referral packet and extracts the fields your team needs into structured data, validated against the schema you define.
- Missing information is flagged at intake, so coordinators can request it from the referring provider on day one.
- An optional model can predict which referrals are likely to stall, so coordinators follow up on those first.
- UCSF Health used H2O Document AI to process more than 1.4 million faxed documents a year, saving more than 25,000 hours of staff time and 5,000 hours of clinician time.
Every referral is read and keyed more than once
Referrals arrive as faxes and scans from many practices, each with its own layout. Someone in your access center has to work out what each document is, which patient it belongs to, what is missing, and where it goes, then type it into several systems.
That work delays the first appointment and keeps your coordinators on data entry instead of on patients. When volume rises, the backlog grows with it.