Pre-assessment screening
Patient Screener
An AI screening tool that checks referral documents against suitability criteria before a private healthcare assessment is booked.
The problem
Every referral has to be read against a long list of suitability criteria before an assessment can be booked. The criteria run to dozens of separate risk, safeguarding, medical and access conditions, and they change. Reading each document by hand is slow, varies between staff, and a single relevant line buried in a GP letter is easy to miss.
We built the full platform. Staff upload up to three documents or paste text directly. Stage one scans the content against a versioned keyword configuration. Stage two sends only the matched passages, with identifying detail removed, to an AI model for contextual verification, separating genuine concerns from false positives. The result is a Red, Amber, Green outcome with the supporting evidence shown against every flag, exportable as a PDF. Separate criteria sets run for adult and child cohorts. Auth, audit logging, admin reporting, infrastructure and hosting are all ours.
A live screening tool that returns a rated, evidenced outcome in a fraction of the time a manual read takes, and produces a consistent record of why each decision was reached. All document processing and AI inference runs on UK infrastructure, with a completed DPIA and data processing agreement behind it.