Coding / CDS

Code the encounter while you document it. The Coding & Clinical Decision Support module sits between Clinical Documentation and RCM, listening to the encounter as it is built and returning coded suggestions, E/M level proposals, HCC capture hints, and CDS Hooks 2.0 alerts — all clinician-in-the-loop, all evidence-linked, all auditable.

What Makes This Different

We are not another AI scribe.
Every EHR vendor ships an ambient scribe that listens and types. That is table stakes. REV.health's differentiator is the Question Learning Loop: every encounter produces a set of clinical questions that become clickable, reusable prompts for the next encounter of the same type. The system gets smarter with every visit — not because an LLM was retrained, but because real clinicians accepted, edited, or rejected real questions during real encounters, and those signals feed back into the encounter-type template.

How the Loop Works

  1. Encounter runs. During an acute visit, follow-up, AWV, or any encounter type, the clinician asks questions, orders labs, adjusts meds, and signs the note. The ambient scribe captures what was discussed; the coding module captures what was coded.
  2. Questions are extracted. After sign-off, the system extracts the clinical questions that drove the encounter — "Are you still taking lisinopril?", "Any chest pain on exertion?", "Has the cough resolved since the Z-pack?" — and tags each with the encounter type, the ICD-10/CPT codes involved, and the accept/edit/reject signal from the clinician.
  3. Questions surface as clickable prompts. The next time a clinician opens an encounter of the same type (e.g., "HTN follow-up"), the template presents the highest-signal questions as one-tap prompts. The clinician clicks a question to ask it; the answer flows into the SOAP note automatically. No typing, no dictation, no free-text guesswork.
  4. A task is created to update the encounter type. When the system detects new questions that were asked but are not yet in the encounter-type template, it automatically creates a review task assigned to the practice manager or lead clinician. The task title is explicit: "Review 3 new questions from acute-visit encounters this week". The task links to the questions, their source encounters, and the accept/reject stats. No question enters the template without human review.

Where This Is Already Demoed

Why Competitors Cannot Copy This

The loop requires three things competitors lack: (1) encounter-type templates that are versioned and practice-configurable, not static forms; (2) a global patient record so questions can reference cross-org clinical facts (medications from pharmacy A, labs from lab B); and (3) a task-management system that enforces human review before any question enters the template. Scribes transcribe. REV.health learns.

Key Capabilities

Real-Time CPT / ICD-10-CM Suggestions with Evidence

As the ambient scribe writes the SOAP note, the coding service emits a ranked list of ICD-10-CM problems and CPT procedure candidates. Each suggestion is pinned to the moment-in-transcript that triggered it — "Code suggested because: 'patient reports chest pain on exertion radiating to the left arm' in HPI." The clinician accepts, edits, or rejects each suggestion. Every suggestion carries an EvidenceUriString pointing at the supporting transcript fragment or document.

E/M Level Rationale

When the note reaches signing, the service proposes an E/M level (e.g., 99214) with an MDM-based justification: number and complexity of problems, amount of data reviewed, risk of complications. The clinician sees the proposed level and a downcode option (e.g., 99213) with rationale for each — defensible E/M levels, not upcoded ones. The E/M downcode rate target is ≤ 5% audit-traceable.

Code Optimizer

The code optimizer surface surfaces Dx/Proc pairings, payer-specific coding rules, and combo history to maximize legitimate reimbursement without upcoding. NCCI edit checking runs at code-acceptance time, flagging mutually exclusive or column-one/column-two code pairs. Modifier suggestions (-25, -59, -95, etc.) are offered with clinical context so the clinician understands why a modifier is needed before accepting it. Up to four modifiers per procedure are supported.

Clinical Decision Support Alerts

The CDS Hooks 2.0 service evaluates rules at chart-open, problem-add, and order-sign trigger points. Four HTI-1 §170.315(b)(11) DSI baseline checks fire on order-sign and medication-prescribe:

Because clinical facts are global in REV.health, the CDS engine sees the union of every contributing org's medications, allergies, and conditions — not a single-org silhouette of the patient. Rule precision goes up; alert fatigue comes down. Override rate target: ≤ 60% per rule. Sustained overrides above threshold auto-enter the rule into managed review.

Audit-Ready Coding Documentation

Every coding suggestion, every override, and every accepted code carries full provenance. CdsHookEvent rows capture the trigger, context, rule version, suggestion cards returned, clinician action (accepted / overridden / dismissed), structured override reason, and end-to-end evaluation latency. Overrides are captured with structured reason codes (e.g., "patient already taking, well-tolerated"), not free text. The audit trail traces every code back to the clinical evidence that supports it.

Persona Connections

Technical Highlights

Domain Entities at a Glance

2026–2027 Regulatory Window

Delivery Phases

Phase 1 — Coding Foundations + Core CDS
Real-time ICD-10-CM and CPT suggestions emitted as the encounter is built, with evidence links. E/M level prediction with MDM rationale at note signing. CdsRule versioning and the four DSI baseline checks (drug-drug, drug-allergy, drug-disease, dose-range) are live on order-sign. NCCI edit checking and modifier suggestions fire at code-acceptance. Every fired hook produces a CdsHookEvent audit row within 5 seconds. CDS evaluation latency target: p95 ≤ 400 ms.
Phase 2 — HCC Capture + Order Sets + AI-CPT
HCC capture hints surface at chart-open when a chronic condition documented in a prior year is missing from the active problem list. Order-set application lets the clinician apply a condition-tied bundle of orders in one action, with each order linked to the source OrderSetID and version. CY2026 AI-augmented CPT support detects when an AI scribe or AI image-analysis result was the basis for a billable element and proposes the AI-augmented CPT variant. Override-rate alarm triggers managed review when per-rule override exceeds OverrideThresholdDecimal over a rolling 30-day window.
Phase 3 — Specialty CDS + Advanced Analytics
Specialty-specific CDS rule packs beyond primary care (pediatric immunization schedules, women's health screening, geriatric polypharmacy). Code-set versioning at write time — every Diagnosis and Procedure stores the CodeSetVersionID in force at coding time, with automatic deprecated→current mapping on read. Retrospective coding-compliance analytics and clinician coding-accuracy dashboards (tied to Payer Optimization). DSI transparency surface expanded with model-card drill-down and performance-metric visualizations.

Success Metrics

Module Dependencies

Try This in the Demo

Developer Reference — Entity schemas (Diagnosis, Procedure, CdsRule, CdsHookEvent & more), CDS Hooks flow, RBAC, and functional/non-functional requirements: Coding & CDS Dev Spec →