Kognitos + Reveal HealthTech: Automating Medical Document Processing
Watch Kognitos automate medical intake for Reveal HealthTech — extracting patient data, validating identifiers across documents, and handling a date-of-birth discrepancy with a human in the loop.
What's in this video
A joint demo with Reveal HealthTech showing how Kognitos automates the front end of medical intake: extracting patient data from varied forms, validating it across documents, resolving exceptions with a clinician in the loop, and writing the records to a structured destination (SharePoint and an Excel report).
The intake pipeline
- Email trigger: new patient and records-request documents arrive by email; Kognitos can also pull from other sources.
- Extraction: for each document, Kognitos extracts the patient identifiers — name, MRN, date of birth — plus age, related doctors, and any relevant notes.
- Cross-document validation: the same patient identifiers are checked across the document set to catch inconsistencies. In the demo, patient Charles's date of birth is inconsistent across forms.
- Consolidation: validated data is rolled up into an Excel new patient intake report attached to a notification email.
- SharePoint filing: each patient's documents are placed into a unique SharePoint folder. (Other file-storage systems work too.)
Human-in-the-loop exception handling
When the date-of-birth mismatch is detected, the automation pauses and emails a designated team. The email links to an interface where a clinician can review the documents, type the correct DOB into a dialog, and — importantly — teach Kognitos how to handle similar mismatches in the future. Once the DOB is supplied, the automation resumes from where it paused.
Why this approach fits healthcare ops
Hospital intake teams deal with handwritten forms, faxed referrals, and mixed PDF layouts that break template-based IDP. Kognitos extracts from those varied formats and — crucially — keeps a clinician in the loop on identity discrepancies, which keeps the automation safe in a clinical context.