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Patient Intake Automation

Intake is where most healthcare data quality problems begin. A patient fills in a form, a staff member reads the handwriting, types it into the EHR, and the transcription error travels through the entire encounter and into the claim.

We rebuild intake as a data pipeline. Forms are completed digitally where possible and captured with document AI where they are not, values are validated against the chart, and only genuine conflicts reach a person.

What breaks today

Transcription is the bottleneck

Staff spend the first hour of every clinic day typing yesterday’s paperwork into the chart rather than preparing today’s patients.

Fax and PDF still exist

Outside records, referral packets, and prior imaging arrive as scanned documents that nobody has time to index properly.

Consent tracking is manual

Knowing which patient signed which consent version, and when, becomes an archaeology exercise during an audit.

Duplicate records

Intake without deterministic matching creates a second chart for the same patient, which splits their history in half.

What we build

Scoped during the assessment, then delivered in one to three week increments against your real systems.

  1. Digital forms with EHR write-back

    Patient-completed forms map field by field into discrete EHR elements. No free-text dumping into a note.

  2. Document capture and classification

    Incoming faxes and scans are classified by document type, split into individual documents, and routed to the right chart section.

  3. Insurance card capture

    Card images are read, member IDs extracted, and an eligibility check fired automatically before the value is committed.

  4. Consent versioning

    Every consent captured records the exact document version, timestamp, and capture method, which is what an OCR auditor asks for.

  5. Patient matching

    Deterministic matching rules on identity fields, with ambiguous cases routed to a human rather than merged automatically.

What changes

Ranges reflect what comparable engagements have produced. Your baseline is measured during the assessment before anyone commits to a number.

  • Registration time per new patient reduced by 8 to 15 minutes
  • Transcription errors in demographic and insurance fields materially reduced
  • Outside documents indexed on arrival instead of accumulating in a queue
  • Consent audit trail that answers an OCR request in minutes

Systems this touches

Integration channel is chosen on verified capability in your environment, not on what is easiest to document.

  • Epic
  • Oracle Health (Cerner)
  • athenahealth
  • NextGen
  • eClinicalWorks
  • Dentrix
  • HL7 v2
  • FHIR R4

Not sure this is the right workflow to start with? The $24,997 assessment exists to answer exactly that, and it frequently points somewhere other than where leadership expected.

(307) 454-0600

Common Questions

Do you replace our existing patient portal?

Usually not. Most organizations already have a portal patients know. We automate what happens to the data after it is captured, and we add capture only for the documents the portal does not handle, such as faxed outside records.

How is document AI kept safe with PHI?

Document processing runs inside your environment or through a vendor covered by a BAA that you approve during the assessment. We do not send PHI to a general-purpose model endpoint without an executed agreement and a documented data flow.

Talk it through with an engineer.

Tell us what this workflow costs you today and we will tell you honestly whether automating it is worth the engagement.

Do not include protected health information in this form. We execute a business associate agreement before any PHI or workflow detail is shared.

Start with a conversation, not a proposal.

A 45-minute call with a senior engineer. We will tell you honestly whether automation is the right answer for the workflow you have in mind.