RADV success starts with provider documentation. In episode seven of Care Decoded, Mark McKeown and Colleen Gianatasio explain why the medical record—not retrospective cleanup—is what determines audit defensibility. Their conversation shows how point-of-care workflows, clearer provider guidance, and better technology can improve documentation accuracy before audit risk ever reaches CMS.
If documentation isn’t accurate at the point of care, nothing downstream—coding, validation, or audit defense—can fix it.
Providers are the source of truth for RADV.
The medical record is designed to tell the patient’s story and ensure continuity of care. But it also serves another critical function: it is the only evidence CMS uses to validate risk adjustment submissions.
That means:
As Colleen puts it, documentation isn’t just important—it’s everything.
Without it, even the most accurate coding strategy falls apart.
The challenge isn’t awareness—it’s execution.
Providers are navigating three major barriers:
1. Lack of time
Most clinicians still see patients every 15–25 minutes. That leaves little room for detailed documentation alongside clinical care.
2. Constantly changing rules
Coding requirements evolve continuously:
Staying current is effectively a full-time job.
3. Clinical vs coding misalignment
What makes sense clinically doesn’t always align with coding rules.
Examples:
This disconnect creates friction—and inconsistency.
The biggest shift isn’t technical—it’s linguistic.
Organizations that succeed with RADV change how they talk about it.
Instead of:
They use:
This reframing matters.
It moves the conversation from:
“Improve your coding performance”
To:
“Help us better understand and care for your patients”
That alignment is what drives real provider engagement.
AI works best when it disappears into the workflow.
The goal isn’t to add another tool—it’s to make documentation easier, faster, and more accurate without disrupting care.
Effective implementations include:
The key principle: treat AI like a clinical support system—not a shortcut.
Most EMRs weren’t built for value-based care.
They were designed for fee-for-service billing, which means:
Layering risk adjustment requirements onto those systems often creates more noise, not less.
High-quality solutions do the opposite:
The goal isn’t more alerts.
It’s better ones.
The biggest improvement comes from shifting left—from retrospective review to real-time support.
Instead of:
reviewing charts months later and identifying errors
Leading organizations:
fix documentation in the moment it happens
Real-world examples:
Chronic kidney disease specificity
Providers default to unspecified codes when the right option is hard to find. Modern tools surface the correct level instantly.
Lab data visibility
Providers don’t always have time to dig through historical labs. Real-time surfacing ensures important conditions are documented accurately.
This shift:
Feedback drives behavior—but only if it’s done right.
Best practices include:
This isn’t just about compliance.
It’s about building trust and consistency across the organization.
When plans and providers align on documentation, the impact extends far beyond RADV.
It leads to:
At its core, documentation isn’t about audits.
It’s about delivering the right care—and proving it.
Why is provider documentation critical for RADV audits?
Provider documentation is the foundation of RADV compliance because it is the medical record that validates the diagnoses submitted for risk adjustment. If documentation is incomplete, vague, or unsupported, the diagnosis can fail validation during a RADV audit.
What are the biggest challenges clinicians face with RADV documentation?
The biggest challenges are lack of time, constantly changing coding and compliance rules, and misalignment between clinical thinking and coding requirements. These pressures make it harder for clinicians to document with the specificity needed for RADV defensibility.
How can AI improve RADV documentation accuracy?
AI can improve RADV documentation accuracy by surfacing clinically relevant insights at the point of care, reducing noise, improving specificity, and helping providers document conditions in real time instead of relying on retrospective chart review.
What is the best way to improve provider adoption of risk adjustment practices?
The best way to improve provider adoption is to reduce workflow friction, use patient-centered language instead of technical jargon, provide small and actionable feedback, and embed support directly into the clinical workflow.
