Protect Your Organization from Costly Coding Errors
Automatically flag high-risk diagnosis codes before they trigger CMS/OIG audits and penalties
Simplify Medicare Advantage Risk Adjustment
The Problem
Medicare Advantage organizations face growing CMS and OIG audit scrutiny, with penalties reaching millions for improper coding:
- $650M+ in improper payments annually from unsupported diagnosis codes
- 12.5% average error rate in high-risk diagnostic categories
- Expanding RADV audits targeting specific high-risk conditions
- Significant resource drain on clinical and coding teams
How We Help
Our FHIR-compliant risk assessment tool delivers measurable results:
- Cut error rates by 83% with pre-submission validation
- Prevent revenue recoupment and avoid costly penalties
- Save 65% review time with automated risk flagging
- Protect reimbursement with proper documentation
- Stay compliant with continuous regulatory updates
Built for Healthcare Teams
- FHIR Standard: Seamless EHR integration
- Real-time: Millisecond response times
- Flexible: Cloud API or on-premises
- Comprehensive: Four critical high-risk categories
- HIPAA-Compliant: End-to-end encryption
- Detailed Reports: Precise documentation mapping
- Smart Rules: CMS/OIG risk filter engine
- Easy Setup: REST API with full documentation
Self-Guided Demo Instructions
Follow these steps to experience how the risk assessment tool works:
Load Sample FHIR Data
Click the "Load Sample" button in section 1 below to populate the text area with FHIR-compliant patient data including diagnosis codes and supporting evidence.
Technical Context: This loads a JSON bundle containing Condition, Encounter, MedicationRequest, and Procedure resources that follow the FHIR standard format.
Go to Section 1Submit for Risk Assessment
Click the "Assess Risk" button in section 1 to send the FHIR data to the risk assessment engine.
Technical Context: The API validates the FHIR resources, extracts diagnosis codes, and applies CMS/OIG high-risk validation rules.
Go to Section 1Review Business Overview
In section 2, examine the "Business Overview" tab to see a summary of risk levels and a visual breakdown of the assessment results.
Business Context: This view helps Medicare Advantage organizations quickly identify which diagnosis codes need additional documentation or review before submission.
Go to Section 2Examine Technical Details
Click the "Technical Output" tab in section 2 to see the detailed JSON response from the API.
Technical Context: This JSON output shows exactly why each diagnosis code was flagged, including specific missing documentation or validation failures.
Go to Section 2Explore Error Rate Data
Scroll down to the "CMS/OIG Reported Error Rates" chart in section 3 to see industry benchmarks for high-risk diagnosis categories.
Business Context: These error rates from official CMS/OIG audits demonstrate the financial risk associated with improper coding in Medicare Advantage programs.
Go to Section 31. FHIR Resource Input
2. Assessment Results
Risk Summary
0 High Risk 0 Moderate Risk 0 Low Risk
Total Diagnoses: 0
| Code | Description | Risk Level | Reason |
|---|
3. CMS/OIG Reported Error Rates
Data source: Office of Inspector General (OIG) Toolkit To Help Decrease Improper Payments in Medicare Advantage
Improve Your Medicare Advantage Coding Accuracy
High-risk diagnosis codes can lead to improper payments and audit failures. Our comprehensive solutions help Medicare Advantage plans identify and correct coding issues before claims submission.
JSON Response
Risk Assessment Rules
Rule Logic for High-Risk Categories:
API Usage
curl -X POST https://your-domain.com/api/assess \
-H "Content-Type: application/json" \
-d '{"resourceType": "Condition", "code": {"coding": [{"system": "http://hl7.org/fhir/sid/icd-10", "code": "I213"}]}, "subject": {"reference": "Patient/123"}}'