Oral appliance therapy billing crosses the dental-medical divide. We built a unified code engine that suggests the right CDT/CPT/ICD combination, blocks non-compliant pairings, and auto-generates claims.
Get StartedA California practice ran a 40% rejection rate and 60-day reimbursement cycles because staff were untrained in dental sleep cross-coding. The unified code engine suggests the right CDT/CPT/ICD set per visit, blocks non-compliant pairings, auto-generates claims, and OCRs EOBs to flag underpayments — cash cycle now 15 days.
Oral appliance therapy billing that crosses the dental-medical divide.
A California practice submitting 200+ claims a month with an audit-shy billing team.
Auto-generated claims from clinical visit data with compliance validation built in.
AI suggestions pick the right combination and guardrails block non-compliant pairings.
Scanned EOBs reconcile against submitted claims and flag every discrepancy.
Scope your own claims automation build with our healthcare billing team.
Cross-coding errors drove a 40% claim rejection rate.
The practice needed a billing solution that understood dental sleep medicine — not generic dental billing software that treated OAT like a filling. Our system was built from the ground up for the unique cross-coding requirements of sleep dentistry.
A curated library of CDT, CPT, and ICD-10 codes specific to dental sleep medicine — not a generic code database with thousands of irrelevant entries.
The system actively prevents non-compliant code pairings, protecting practices from audit risk and rejected claims.
OCR scanning of explanation of benefits documents with automatic reconciliation catches every underpayment that manual review would miss.
From code suggestion to claim generation to submission to reconciliation — the entire billing lifecycle is automated within a single workflow.
Every number below was measured in production after launch — not projected in a pitch deck.
Average Reimbursement Cycle — Down from 60 days
Claim Rejection Rate — Down from 40%
Coding Accuracy — Up from ~55%
Revenue Recovered from Denials — In the first year
