Capsa Coding
Capsa Charge Capture · the product that's live today

Coding built on your data — proven against your claims.

Capsa encodes your guidelines, reads the signed note, and recommends every CPT/HCPCS code the chart supports with a plain-English reason — verifying each quote is verbatim in the chart before a coder sees it, then scoring itself against what your coders actually billed. 93–96% accuracy.

96.9% precision · 95.5% recall (vaccines) 100% of codes cited to the chart
Visit · well-child, 4 mo acct 5000004
Capsa recommends · evidence attached
90460
VAC-ADM-001
“…admin with counseling by physician; first component…”
billed
90686
VAC-PROD-014
“…Influenza, quadrivalent, 0.5 mL IM administered today…”
billed
96110
HS-DEV-001
“…ASQ-3 developmental screen completed, score recorded…”
caught
precision 96.9%recall 95.5% +1 missed charge recovered
Why it matters

Both ways coding goes wrong are expensive.

After a provider signs a note, a coder reads it and bills every service performed. Billable work is easy to miss, inconsistent between coders, and hard to audit after the fact.

Missed codes

Lost, compliant revenue — gone for good

Billable work the coder didn't capture is money you earned and won't see. At scale, a few missed codes per visit is a seven-figure annual leak.

Over-coded claims

Audit risk and clawback exposure

Codes billed without support in the chart invite denials and recoupment. The goal isn't “more billing” — it's the right amount, provably.

How it works

Read the note. Prove the code. Measure against what was billed.

01

Ingest

The signed note comes in from the EHR; augmenters fill known gaps like structured vaccine records.

02

Triage

A fast model decides which coding categories even apply, so effort goes only where it's needed.

03

Analyze

Each category runs an explicit, human-readable rule set and proposes codes with a plain-English reason.

04

Cite-check

Every quote is verified verbatim in the chart. Unsupported recommendations are dropped before a coder sees them.

05

Validate

Predictions are scored against what the coder actually billed — scope-aware precision and recall.

A guided tour

Real screens from the product.

Screenshots are from the live application. Patient identifiers and clinical text are scrubbed; codes, rules, versions, and metrics are real.

capsa · visit traceability (the money-shot)
Visit traceability: AI-recommended vs coder-billed codes with match pills and the why-the-AI-recommended-these-codes evidence cards
Visit traceability. AI-recommended vs. coder-billed codes with match pills, and a card for every recommendation showing the rule and the verbatim chart text behind it.
capsa · overview
Improvement-cycle dashboard with a five-stage flow and per-stage KPIs
Overview. The improvement cycle — pipeline, validation, iterate, apply — with per-stage KPIs.
capsa · guideline detail
Guideline detail: rules, codes and modifiers, evidence patterns, examples, source materials, and version history
Guideline detail. Rules, codes, evidence patterns, worked examples, and full version history — all in one place.
capsa · validation
Validation dashboard with two-axis scorecard, overall metrics, and per-CPT, per-template and per-rule breakdowns
Validation. Scope-aware precision, recall and F1 with per-CPT, per-template, and per-rule breakdowns.
capsa · iterate
Iterate two-way worklist with run-vs-baseline KPI deltas and a per-visit AI-vs-billed grid
Iterate. A two-way worklist — where AI and the coder agree, where AI over-fired, and where the coder caught something AI missed.
capsa · coder review
Coder review ticket: a clarifying question, an answer form, and a metadata sidebar
Clinician-governed loop. CDI nurses answer clarifying questions and approve rule updates — no engineering required.
Proof, measured

Measured on cases your team already coded.

Precision = of the codes Capsa recommends, the share coders agree with. Recall = of the in-scope codes coders billed, the share Capsa caught.

Two categories measured to date

Vaccines and health screening are measured and proven; five more categories are built on the same framework with measurement in progress.

Coding categoryPrecisionRecallNote
Vaccines96.9%95.5%Recall SLA (≥95%) met; precision at target.
Health screening · A93.7%95.7%Recall SLA met.
Health screening · B93.9%93.4%Both metrics near target.
Portability proof: the health-screening category went from a 53.7% / 34.8% cold start to roughly 94% / 94% using the exact same framework that matured vaccines. New categories inherit the machinery instead of starting over.
Why Capsa

Built to be defended in an audit — not just to find more codes.

Audit-defensible by design

Every code links to the rule that produced it, and every rule to the verbatim chart text that triggered it — at the exact version that ran. Answer “why this code?” in one click.

Versioned guidelines

Rules, codes, evidence, and worked examples are versioned together with full history and side-by-side diffs. When a payer changes a rule, the change is on the record.

Scope-aware measurement

Precision and recall are measured against the codes each skill actually owns — so the numbers mean what they say instead of being diluted by out-of-scope codes.

Clinician-governed loop

CDI nurses — not engineers — answer clarifying questions and approve rule updates through a guided workflow, with a complete audit trail.

No black box, no fine-tuning

All clinical logic lives in explicit, human-readable rule sets. Nothing is hidden inside a model nobody can inspect or explain.

One framework, every category

The same engine runs every coding skill. Adding a new category is reuse, not a rebuild.

In two minutes

See the whole loop, end to end.

The Capsa Charge Capture overview

A short walkthrough of ingest → triage → analyze → cite-check → validate, on real screens.

Video coming soon — book a pilot to see it live on your data Book a pilot
FAQ

Questions coders, CDI, and compliance ask.

How is this different from a black-box coding model?+
All clinical logic lives in explicit, human-readable rule sets. Every recommended code links to the rule that produced it and the verbatim chart text that triggered it — at the exact rule version that ran. There's no fine-tuning and nothing hidden inside a model nobody can inspect.
Will Capsa replace our coders?+
No. Capsa is decision support. Coders review AI-recommended codes with the supporting chart evidence attached, and CDI nurses own the rules. Capsa partners with coders; it doesn't replace them.
How do you measure accuracy?+
Predicted codes are compared against what the coder actually billed, on a scope-aware basis that measures only the codes a given skill is responsible for. We report precision and recall with per-CPT, per-template, and per-rule breakdowns.
Is it audit-defensible?+
Yes. Every code links to its rule and the verbatim chart text, at the exact version that ran. Rules, codes, evidence, and worked examples are versioned together with full history and side-by-side diffs.
What does a pilot involve?+
We run Capsa against a sample of visits your team already coded and report scope-aware precision and recall against what was billed — no EHR rip-and-replace.
How do you handle PHI and data security?+
Pilots run under appropriate data agreements on limited or de-identified data. We do not train models on your data; all logic is in inspectable rule sets.
Book a pilot on your data

See Capsa on cases your team already coded.

We'll run Capsa Charge Capture against your guidelines, your cohorts, and your paid claims — and show you scope-aware precision and recall on visits you've already billed.

  • Pilot on a sample of your own visits
  • Precision & recall vs. what your coders billed
  • Every recommendation cited to the chart
  • No EHR rip-and-replace
[email protected] · capsacoding.com

Request a demo / pilot

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