Dashboard
AI-assisted medical coding workflow
Recent Encounters
| Encounter | Setting | AI Output | Status |
|---|
Workflow
Engine status
New Encounter
Enter documentation and let AI analyze the coding requirements.
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Review Queue
Every analyzed encounter and its coder decision.
| Encounter | Type | PDX | Services | Confidence | Status |
|---|
Encounter Review
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✓ FINAL CODING OUTPUT —
AI Coding Analysis
Billing Details
| Service | CPT/HCPCS | Revenue | Modifier | Units | Status |
|---|
Rules Engine Checks
Reports & Quality
Monitor AI coding quality and coder overrides.
Override log
Every encounter a coder corrected, with the reason. This is the error-analysis input for improving the prompt and the rules table.
| Encounter | AI output | Coder output | Reason |
|---|
Encounter types analyzed
Settings
Configure automatic detection, coding checks and human review.
Automatic Detection
New/established, billing type, care setting and specialty are detected from the note unless overridden on the New Encounter form.
Compliance Checks
Modifier 25, 59 and 26/TC applicability, medical-necessity linkage and documentation gaps run deterministically. NCCI and MUE tables are not loaded yet.
Coder-in-the-loop
The AI recommends; the coder validates, edits or flags. Every override is logged to Reports & Quality.
Architecture
The language model interprets documentation and reports facts. It never selects a code or an E/M level — a deterministic rules engine does that from the facts. This keeps the code set out of the model and makes every recommendation auditable.
Guidelines applied as rules
Datasets not loaded
Laboratory code table
| Matches | CPT / HCPCS |
|---|
A starter set covering common panels. Verify every code against the current code set before submission.
Stored data
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