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Wound care documentation

The evidence is scattered. The money is withheld.

Proof of medical necessity is scattered across EHR exports, wound photos, prior notes, and bedside documentation. Bineha assembles it into one structured record before missing evidence puts payment at risk.

Good care is not the same as a payable record.

Before Medicare covers a skin substitute graft, its coverage policies require the record to establish a specific chain of facts. Every one of them has to be there, written the way the policy expects.

Miss a single link and the claim is denied — not because the treatment was wrong, but because the record could not prove it was necessary.

Requirements summarised from Medicare local coverage determinations L35041 and L36377. Coverage policy varies by contractor and changes; verify against your own payer before relying on it.

  1. 01Four weeks of standard caredocumented, and documented as having failed
  2. 02Serial measurementslength, width, depth — visit after visit
  3. 03Infection and osteomyelitisassessed and recorded, not assumed
  4. 04Why this productthe rationale for the one you chose
  5. 05Clinical responsewhat changed after you applied it
  6. 06Quantity and wastagehow much was used, how much was discarded
How the platform worksFragmented sources — an EHR export, a wound photo, nurse notes, a referring physician’s notes and bedside entry — feed into one record. The record is checked against the six things a payer requires, then rendered four ways: a clinical note, a nurse care plan, a coding recommendation and an audit file. Below it, drawn dashed because it is not built, sits a learning layer that would read images for progression and return outcomes to the record, alongside two planned sources: a live EHR feed and automatic code set updates.SCATTERED TODAYEHR exportany certified systemWound phototaken on a phoneBedside entrytyped at the visitCOMING NEXTNextNurse notesthe visit before yoursReferring physicianhistory and prior careLive EHR feedan interface instead of a fileCode set updatesICD-10 · CPT · HCPCS, as they changeBinehaAssembled once, checked every timeFour weeks of standard careSerial measurementsInfection / osteomyelitisWhy this productClinical responseQuantity and wastageLearning layerImages read for progression or declineOutcomes returned to the recordNextTAILORED TO ITS AUDIENCEClinical notefor the chartNurse care planfor the bedsideCoding recommendationfor a certified coder to verifyAudit filewording that holds up
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Read it as a list instead

Scattered today

  • EHR exportany certified system
  • Wound phototaken on a phone
  • Bedside entrytyped at the visit

Bineha

Assembled once, checked every time

  • Four weeks of standard care
  • Serial measurements
  • Infection / osteomyelitis
  • Why this product
  • Clinical response
  • Quantity and wastage

Output tailored to its audience

  • Clinical notefor the chart
  • Nurse care planfor the bedside
  • Coding recommendationfor a certified coder to verify
  • Audit filewording that holds up

Coming next

  • Nurse notesthe visit before yoursNext
  • Referring physicianhistory and prior careNext
  • Live EHR feedan interface instead of a fileNext
  • Code set updatesICD-10 · CPT · HCPCS, as they changeNext
  • Learning layerImages read for progression, stagnation or deterioration · outcomes returned to the recordNext

Nothing is invented

Where a fact is missing, the note says so in brackets rather than filling the gap with something plausible. A note that reads well but cannot be substantiated is worse than an obviously incomplete one — it fails at the moment it matters.

It suggests; a coder decides

Codes come with a rationale and an explicit instruction to verify. The system never selects a final code and never submits a claim. Surgical debridement codes follow the depth of tissue actually removed, not the instrument used — the kind of distinction that decides an audit.

Deterministic first

The current build contains no AI. Notes are produced by explicit rules, so every sentence can be traced to a fact someone entered. Machine learning belongs on top of a trustworthy record, not underneath it.

Want to know more?

We will walk you through a real encounter end to end — intake, the note it produces, the codes it recommends and the checks it refuses to let you past.

Get in touch

Tell us a little about your practice and what you would want it to do. We will reply personally.