What does DME fax intake OCR do?

It converts inbound faxed referrals (typed, handwritten, stamped) into structured data — patient demographics, prescription details, payer ID, ICD-10 codes — validates against Medicare LCDs and payer rules, then posts into Brightree, WellSky, or NikoHealth with missing-element flags.

Can the OCR pipeline read handwriting?

Yes. The pipeline is layered — printed text and handwriting use separately tuned models, and stamped signatures are classified by a third detection task. Low-confidence fields surface to staff for one-click verification.

How is this different from generic OCR tools?

Generic OCR returns raw text. This pipeline is tuned for clinical documentation: it knows what an LCD requirement looks like, recognizes payer-specific document patterns, and validates output before posting downstream.

Is the OCR HIPAA-compliant?

Yes. BAA-covered, encrypted transport and storage, role-based access, full audit trails.

DME OCR · Fax-to-EHR

Stop Re-Typing Faxed Referrals. We Parse Them.

A purpose-built OCR pipeline for DME intake. Typed referrals, handwritten forms, stamped signatures, multi-page packets — extracted, validated, and posted directly into Brightree, WellSky, or NikoHealth.

Free DME leakage audit See the engagement

Your front office still types every referral by hand

Fax-to-PDF is not data — it's a picture of data. Somebody still reads it and types it into Brightree. That somebody is your intake coordinator, five hours a day.

Handwritten chicken scratch

Doctor's handwriting, nurse-jotted ICD-10, a phone number that's either a 3 or an 8. Re-typed best-guess into your platform.

15-page faxed packets

Patient demographics on page 1, sleep study on page 4, prescription on page 9, insurance card scan on page 12. Nobody is paginating fast.

Stamped physician signatures

The "signed" version looks identical to the unsigned version unless you squint. Audit-trail-breaking when missed.

Skewed, dim, double-fed scans

The fax came through at a 3-degree angle. Half the document is gray. Two pages stuck together. Every fix is manual.

See it in action

From clipboard to chart — automatically

Watch a faxed patient packet become structured chart data — the OCR workflow that hands intake teams 250+ hours a year back.

The pipeline, step by step

Not a single OCR model trying to do everything. A layered pipeline tuned to each input type.

1De-skew, de-noise, split

Multi-page faxes split per page, auto de-skewed and contrast-normalized. Stuck pages flagged for review.

2Layered OCR

Printed text, clinical handwriting, and stamped signatures each get a tuned model. Every field carries a confidence score.

3Field extraction

Demographics, RX details, payer ID, ICD-10s, physician, signature — structured fields. Low-confidence fields get one-click human verification.

4Rule validation

Medicare LCDs and payer-specific doc rules per product line. Missing-element flags raised before the referral hits your queue.

5Post into your platform

Clean fields pushed into Brightree, WellSky, or NikoHealth via API or RPA. Source PDF attached; flags become owned tasks.

Outcomes from a working pipeline

From the anonymized DME in the case study, six months in.

40–60%less time re-typing referrals

25–35%fewer documentation-driven denials

~48 hrstypical referral → setup turnaround

Zeropaper-to-keyboard re-entry on standard fields

See how much your team types every week

Free DME leakage audit. 30 minutes. We quantify the re-typing time in dollars on the call.

Book the audit Read the case study