Claims Paid Right the First Time
Medical Copilot keeps documentation, diagnoses, and service codes aligned at every step, so claims go out fully supported the first time. The result is protected revenue, fewer denials, and a clear audit trail your team can stand behind.
Runs Inside Your EHR
Physicians launch Medical Copilot directly from the Progress Note. Encounter context is read automatically, and confirmed documentation, diagnoses, and codes are written back to the chart.
Read our announcement: Medical Copilot is live inside eClinicalWorks. eClinicalWorks® is a registered trademark of eClinicalWorks, LLC. athenahealth® is a registered trademark of athenahealth, Inc.
From Clinical Context to Claim-Ready Documentation
A guided CDI-to-coding workflow: Medical Copilot reviews encounter context, asks clarification queries when evidence is incomplete, writes only approved documentation, and then supports suggested ICD diagnosis, CPT/HCPCS services coding, and claim-ready review.
Start with the encounter evidence already in the EHR.
Medical Copilot reviews structured and free-text documentation before recommending any action. The workflow begins with clinical context, orders, services, and key findings.
Established patient with known heart failure returns with three days of worsening dyspnea on exertion, orthopnea, and 3 kg weight gain. Exam notes bibasilar crackles and trace pedal edema. A prior echocardiogram on file shows reduced ejection fraction (EF 30%). Assessment: CHF. Increase diuretic; repeat echocardiogram, chest X-ray, and BNP ordered.
When evidence is incomplete, ask one controlled CDI question.
The agent does not assume the answer. It identifies the missing clinical support and prepares a controlled clarification query, so the clinician, CDI reviewer, or coder confirms what is clinically supportable before any documentation or coding update is made.
Heart failure is documented as “CHF” only. The type and acuity are not stated, and the reduced ejection fraction on file is not linked to a specific diagnosis.
Based on the worsening symptoms and documented ejection fraction of 30%, how should the heart failure be specified?
Accepted CDI responses become a suggested diagnosis and approved note update.
After the reviewer agrees, Medical Copilot surfaces the documentation outcome as a suggested diagnosis, then writes only the approved clarification into the documentation workflow.
Heart failure characterized as acute on chronic systolic (HFrEF) based on worsening dyspnea, weight gain, and reduced ejection fraction (EF 30%). Confirmed by provider and added to the encounter note.
Free-text services become reviewable CPT/HCPCS suggestions.
After documentation context is confirmed, the system reads EHR narrative, orders, and service descriptions to suggest service codes with source text and review status.
Suggest a supported evaluation and management level.
The system reads the documented history, findings, and management to suggest an E/M level with the medical-decision-making drivers behind it, so the coder can confirm rather than calculate.
- Problems addressed: chronic illness with acute exacerbation.
- Data reviewed: chest X-ray, echocardiogram, and BNP.
- Risk: prescription drug management (diuretic titration).
Deliver a review package that is supportable and auditable.
The final output combines the specified documentation, CDI query trail, service-code and E/M-level suggestions, HCC capture, medical-necessity checks, and audit context for the billing, coding, CDI, or compliance team.
Four Connected Agents, One Documentation-to-Coding Workflow
Each capability preserves reviewer control while moving evidence from documentation to diagnosis, services coding, and claim-ready handoff.
Suggested Diagnosis Agent
Turns accepted CDI responses into suggested ICD diagnosis outcomes with rationale, source evidence, and reviewer status.
- ICD-10 diagnosis suggestions
- Accepted-query derivation
- Source-linked rationale
- Reviewer-ready handoff
Services Coding Agent
Reads encounter narrative, orders, and service descriptions to suggest reviewable CPT/HCPCS service codes with source support.
- CPT/HCPCS suggestions
- Service text extraction
- Diagnosis-service alignment
- Coder review status
CDI Query Agent
Detects documentation gaps and prepares controlled clarification queries before unsupported diagnoses or coding changes are made.
- CDI gap detection
- Controlled query options
- Approved note updates
- Audit trail generation
Ambient Documentation Agent
Transforms conversations and encounter context into structured clinical notes that feed CDI and coding review.
- Real-time voice capture
- SOAP context generation
- Key finding extraction
- Documentation-ready evidence
Six Steps From Clinical Note to Claim-Ready Handoff
Reviewer-controlled support from ambient encounter evidence through CDI clarification, suggested diagnosis, services coding, and final review.
Capture Context
Reads ambient notes, encounter summaries, orders, services, and clinical findings.
CDI Clarification
Detects missing support and asks one controlled query so reviewers confirm what is clinically supportable.
Suggest Diagnosis
Converts accepted CDI responses into suggested ICD diagnosis outcomes with source rationale.
Suggest Service Codes
Suggests reviewable CPT/HCPCS service codes from orders and service descriptions.
Suggest E/M Level
Suggests a supported evaluation and management level with the medical-decision-making drivers behind it.
Handoff Claim-Ready
Packages documentation, CDI query trail, coding rationale, and reviewer decisions for billing and audit review.
Built for Enterprise-Grade Healthcare Operations
The infrastructure your revenue cycle team can trust at scale.
Payer-Specific Logic
Custom rules per payer, updated continuously to match changing policies and coverage guidelines.
Real-Time & Bulk Processing
Handles single encounters instantly and massive batch claim runs efficiently — no bottlenecks.
HIS / RCM API Integration
Live inside eClinicalWorks today — eCW practices can go live in one day. Connects to other EHR and RCM systems via API, with athenahealth coming soon.
Custom Coding Guidelines
Create, edit, and publish your own payer and protocol rules so the AI always reflects your clinical context.
Common Questions
Ready to protect your income and ensure precise clinical documentation and coding?
Start with a focused Clinical Documentation & Coding Intelligence pilot using sample encounters, reviewer workflows, and claim-ready handoff outputs.
Book a Demo →