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Work / Kestrel Health

Patient intake that a compliance officer signed off on

Document extraction and structured intake across scanned referrals, built so that every automated decision has an audit trail and a human override.
Client
Kestrel Health
Sector
Healthcare
Year
2024
Services
AI Systems, Web & Product
All case studies

82%

of referrals processed without manual entry

12s

median extraction time per document

0

findings at external audit

The problem

Challenge

Referrals arrived as scanned faxes. Staff retyped them into the patient record, which was slow and produced transcription errors in exactly the fields that mattered. Any automation had to satisfy a compliance function that had rejected two previous vendors.

What we did

Approach

In order, including the steps that changed the plan.

  1. 01

    Design for the audit first

    We started with the compliance requirements rather than the model. Every extracted field stores its source region on the page, the confidence, and who confirmed it. That constraint shaped the architecture instead of arriving late to complicate it.

  2. 02

    Extract, then verify

    Fields below threshold are presented to staff with the relevant part of the scan highlighted, so confirming is faster than typing. Staff time per referral fell even on documents the system could not fully read.

  3. 03

    Keep humans in the loop by design

    Clinical fields always require confirmation regardless of confidence. Removing that check would raise the automation rate and was never on the table.

Where it landed

Outcome

Four referrals in five need no manual entry. The system passed external audit with no findings, largely because the audit trail was a design input rather than a retrofit.

Built with

  • Claude
  • Next.js
  • Postgres
  • Temporal
Two vendors before them told us the audit trail could come later. That answer is why they were previous vendors.
Alan BrechtCompliance Director, Kestrel Health
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