What 10 OIG RADV Audits Reveal About Medicare Advantage Diagnosis Code Risk

The RADV Audit Landscape

Between 2024 and 2025, the HHS Office of Inspector General (OIG) published Risk Adjustment Data Validation (RADV) audit findings for 10 Medicare Advantage organizations. These audits examined whether MA plans submitted accurate diagnosis codes to CMS — the codes that determine how much the federal government pays each plan per enrollee.

The findings were consistent across every plan: 70–99% of sampled high-risk diagnosis codes were unsupported or miscoded, resulting in millions of dollars in estimated overpayments per organization.

With Medicare Advantage now covering approximately 45% of all Medicare payments, accurate risk adjustment is a major federal financial priority. These audits are not one-off events — they are part of a systematic OIG enforcement series targeting the same high-risk diagnosis categories across plans nationwide.

Every audited plan followed the same structure: stratified random sampling by diagnosis group, independent medical review, and findings broken down by high-risk diagnosis category. All 10 plans received the same three recommendations: refund overpayments, self-identify similar errors, and improve compliance procedures. All 10 disagreed.

Key Findings at a Glance

Across the 10 audited plans, four metrics define the scale of the problem:

All 12 Diagnosis Categories Under OIG Scrutiny

OIG targeted the same high-risk diagnosis groups across plans. The consolidated table below ranks all 12 audited categories by average overpayment per enrollee-year — the most direct measure of financial exposure per finding.

Error Rate by Diagnosis Category

Visualizing error rates highlights the distinction between near-universal miscoding (cancers and acute conditions) and selectively flagged categories (Sepsis, Pressure Ulcer):

Cancer   Non-Cancer  ·  Vascular Claudication (10%) and Major Depressive Disorder (3%) omitted

Plan-Level Audit Exposure

While error patterns are consistent across plans, the financial exposure varies significantly based on plan size and enrollee universe. Below are the 10 audited organizations and their estimated overpayments:

* Triple-S Advantage amount is not extrapolated in the published report. * EmblemHealth uses HCC-level audit methodology (differs from diagnosis-group approach used by other plans); figure not directly comparable.

Cancer vs. Non-Cancer: Where the Money Is

Cancer diagnoses dominate the financial exposure in RADV audits. Understanding this split is critical for prioritizing remediation efforts.

Cancer Category Breakdown

Non-Cancer Category Breakdown

Error Rate vs. Dollar Risk: They Don't Always Align

A high error rate does not automatically mean high financial risk — and vice versa. Understanding this distinction is essential for prioritizing remediation efforts:

The 11x Extrapolation Multiplier

The most important financial dynamic in RADV audits is not the sample error — it's the extrapolation. OIG doesn't just recover overpayments found in the sample. It extrapolates findings to the entire enrollee universe.

This means pre-submission validation doesn't just prevent the face-value error — it prevents the amplified penalty. A single Lung Cancer code corrected before submission doesn't save $5,937. With the 11x multiplier, it saves approximately $65,000 in extrapolated penalty exposure.

How RADV Scrubber Works

RADV Scrubber is a rules engine that processes member data through automated clinical, demographic, and service validation — surfacing discrepancies before CMS submission. It is part of the Precise Health Risk Compass platform.

Dual Workflow Integration

RADV Scrubber supports both workflow models — catching errors at the point of encounter submission and during retrospective review:

What RADV Scrubber Validates

Three validation dimensions — clinical accuracy, demographic consistency, and service pattern verification — across all OIG/CMS-audited HCC categories and beyond.

Audit Finding → RADV Scrubber Capability

Every OIG audit finding maps directly to a RADV Scrubber capability. The same errors flagged after the fact by OIG are caught before submission:

ICD-10 Guideline Auditor

Complementing RADV Scrubber, the ICD-10 Guideline Auditor provides automated ICD-10 coding guideline validation — embedded directly in your HCC coding workflow, surfacing errors before submission.

Automates 100% of ICD-10 coding guideline validation during HCC coding. Every code validated instantly — before claim submission.

• check Code First, Use Additional Code, Excludes1 & Specificity checks
• check Laterality, Severity, and Combination Code validation
• check Gender, End-Stage, Historical vs. Active conflict detection
• check Intelligent code suggestions — surfaces new revenue opportunities
• bolt Up to 50% improvement in auditor efficiency via REST API

What RADV Scrubber Can Save Your Plan

The only cost-free intervention is catching errors before CMS submission. Every avoided error prevents approximately 11x its value in extrapolated penalties.

Savings by Diagnosis Priority

If a plan focuses RADV Scrubber specifically on the highest-exposure categories:

Sample overpayments above are from 210–300 enrollee-year samples. Extrapolated to full plan populations, these figures scale 10–15x.

Strategic Recommendations for Payors

Based on the OIG findings across all 10 audited plans, here are prioritized actions for Medicare Advantage organizations:

Lung Cancer: Plan-by-Plan Audit Data

As the single highest-cost diagnosis category, Lung Cancer warrants a detailed plan-by-plan breakdown. The consistency of findings across 8 plans underscores the systemic nature of the problem.

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