CMS is no longer giving Medicare Advantage plans the luxury of time. With every contract now subject to annual RADV audits and extrapolation in play, audit exposure is no longer theoretical—it’s a bottom-line reality.
The clock is ticking. The first delete submission deadline is June 16, 2025. If you're feeling overwhelmed, you're not alone. But you're also not too late—there’s still time to act.
Here’s a simple, proven 3-step strategy to triage deletes, reduce audit risk, and take control before the deadlines hit.
- Build a Proactive Delete Plan
- Use the HHS-OIG Improper Payment Toolkit to Flag High-Risk Diagnoses
- Run the toolkit algorithm against active diagnosis data
- Flag high-risk codes
- Delete unsupported diagnoses proactively
- Recalculate RAF with MScore® Before You Delete
- 🧮 Instantly recalculate risk scores for individuals and populations
- 🧪 Model the impact of individual deletes
- 🎯 Calculate payment from revised RAF to quantify impact of deletes
Every plan should be actively reviewing diagnosis codes and establishing a formal delete process. Waiting for CMS to initiate review is no longer viable.
Start with the oldest payment years and work forward, setting internal milestones well before CMS’s submission cutoff.
📅 RADV Delete Submission Deadlines:
| Payment Year | Dates of Service | Submission Deadlines |
|---|---|---|
| 2020 | Jan 1 - Dec 31, 2019 | June 16, 2025 |
| 2021 | Jan 1 - Dec 31, 2020 | June 23, 2025 |
| 2022 | Jan 1 - Dec 31, 2021 | June 30, 2025 |
| 2023 | Jan 1 - Dec 31, 2022 | July 8, 2025 |
| 2024 | Jan 1 - Dec 31, 2023 | July 15, 2025 |
Assign internal reviewers, set record retrieval protocols, and establish a decision framework now.
HHS-OIG’s own audit reports show that over 90% of the diagnoses flagged by their Toolkit are ultimately found to lack documentation support.
This toolkit isn’t theoretical—it’s built from actual audit findings. In many high-risk categories, error rates exceed 95%. Here’s a snapshot of error rates from the HHS-OIG’s December 2023 toolkit:
| High-Risk Group | Total | Errors | Error % |
|---|---|---|---|
| Acute stroke | 945 | 908 | 96% |
| Acute heart attack | 791 | 751 | 95% |
| Embolism | 754 | 593 | 79% |
| Lung Cancer | 391 | 345 | 88% |
| Breast Cancer | 390 | 373 | 96% |
| Colon Cancer | 390 | 368 | 94% |
| Prostate Cancer | 360 | 322 | 89% |
| Potentially mis-keyed diagnosis codes | 522 | 421 | 81% |
| Totals | 4,543 | 4,081 | 90% |
Plans should immediately:
This alone can drastically reduce exposure to extrapolated overpayments.
⚠️ Not using this toolkit means ignoring one of the most straightforward signals the federal government has given about what leads to RADV audit errors.
Deleting a diagnosis without understanding its financial impact could backfire. That’s where MScore® comes in. Plans and consultants can:
This is more than RAF math—it’s strategic compliance planning. Use MScore® to ensure you're not flying blind when deleting diagnoses.
Bottom Line
Plans can’t control every diagnosis sent by providers—but they can control how they prepare for CMS scrutiny.
A structured, data-informed delete strategy, powered by HHS-OIG algorithms and RAF recalculation tools, is no longer a nice-to-have—it’s essential.
📌 Don’t guess—model it. Let RiskAdjustmentModel.com and MScore® help you get ahead of CMS and make every delete count.