Risk Adjustment Explained — A Practical Guide to HCCs, V28 & Accurate Payment

Risk Adjustment is one of the most misunderstood engines in healthcare — but it’s also one of the most important.

It keeps the system fair.
It keeps funding aligned with real medical needs.
And starting with the V28 model update — it’s smarter, cleaner, and closer to real-world medicine than ever before.

Let’s make sense of it.
Plain English. No equations. Zero headaches.

Why Risk Adjustment Exists (And Why It Will Never Go Away)

If Medicare paid every beneficiary, the same amount:

  • Healthy members would be overpaid

  • Complex members would be underfunded

  • Health plans would avoid the sickest patients

Risk Adjustment solves this problem by ensuring:

Every patient’s story is represented in the dollars used to care for them.

It protects access.
It protects fairness.
It protects populations often left behind.

That’s why CMS keeps enhancing the model — better coding shouldn’t inflate risk, and poor coding shouldn’t hide real disease burden.

What Exactly Is an HCC?

Think of ICD-10 codes as words.
They tell part of a story — but sometimes in confusing ways.

HCCs are like organized chapters:

  • They group similar diagnoses together

  • They help CMS pay based on clinical significance

  • They prevent double-paying for minor vs. major versions of a disease

Example idea (without specifics):

A diagnosis of seasonal allergies ≠ the same as chronic respiratory disease.

HCCs make sure payment reflects:

  • Severity

  • Clinical complexity

  • True resource needs

And because they’re hierarchical, the most serious active condition counts.

V28 — A Smarter Model for a Modern Era

CMS updates the model when:

  • Care patterns evolve

  • Coding changes

  • New technologies improve data integrity

  • Some conditions need more/less emphasis

V28 brings 4 important improvements:

  • More clinically accurate groupings

  • Updated mapping from ICD-10 → HCCs

  • Less “gaming” from borderline documentation

  • Better fairness across diverse populations

Bottom line:
V28 rewards quality and completeness instead of volume or loopholes.

How a RAF Is Built — The 5-Piece Puzzle

A finalized risk score is built from:

1. Demographics

  • Age, gender, Medicaid status, disability…
    → Sets a baseline of expected cost

2. Condition Categories (HCCs)

  • Documented & properly coded illnesses
    → Increase expected costs proportionally

3. Interactions

  • Certain combinations are clinically harder to manage
    → Adds nuance to reflect real-world care

4. Count + Hierarchy Logic

  • Avoids overpayment for multiple related diagnoses
    → Removes “double counting”

5. Adjustments for fairness

  • Ensures national costs remain stable
    → Keeps MA vs. FFS competitive balance intact

No one step alone is enough — accuracy depends on the entire chain.

Where Risk Adjustment Falls Apart

Even if a patient is complex and well-managed, their RAF may drop because of data issues.

Here’s where that happens most:

-> Chart → Code gap
Diagnosis documented but never coded = gone from the model

-> Code → Submission gap
Claim/encounter rejection = CMS doesn’t see it

-> Documentation → Validation gap
Code submitted but not supported by MEAT evidence = RADV risk

-> Yearly continuity gap
Chronic conditions not refreshed = wiped from current-year risk

Patients don’t suddenly get healthier…
But their data might say they do.

This creates payment leakage — and compliance exposure.

What Good Looks Like — Modern Risk Adjustment Standards

A strong program has:

  • Clear provider documentation standards

  • Automated data lineage tracking from chart → CMS

  • Internal RASS “mirroring” before CMS runs

  • Consistent refresh of chronic illness data

  • Proactive gap closure campaigns

  • Organizational visibility into RAF performance

This is where technology becomes a competitive advantage.

Enter Agentic AI — The New Teammate in Risk Adjustment

Agentic AI doesn’t replace staff — it extends them.

It can:

  • Scan millions of clinical notes for missing evidence

  • Flag documentation at risk of audit

  • Detect underreported chronic conditions

  • Compare internal risk vs. expected CMS results

  • Run year-round audit simulations

  • Provide clinical context, not just code checks

And importantly:

It doesn’t change diagnoses — it protects them.

AI keeps the data trail clean so care is accurately represented.

A Day in the Life of AI-Enhanced Risk Adjustment

Without AI:

  • Teams react to errors months later

  • Spreadsheets everywhere

  • Surprise payment variances

  • Scrambling during RADV cycles

With Agentic AI:

  • Daily documentation scoring

  • Real-time RAF visibility

  • Fewer provider touchpoints

  • No lost encounters

  • Confident compliance year-round

Plans stop playing catch-up and start shaping outcomes.

The Human Role: Still the Most Important

AI is powerful at:

  • Pattern recognition

  • Volume review

  • Rule enforcement

But humans excel at:

  • Clinical judgment

  • Final validation

  • Provider relationships

  • Complex medical nuance

The magic is in their partnership.
Think of AI as:

  • The detective

  • The human reviewer is the judge

Together → precision you can trust.

Final Takeaways (No Calculators Required)

  • Risk Adjustment ensures fairness in healthcare funding

  • V28 improves accuracy and clinical realism

  • Data continuity is what protects true patient complexity

  • AI keeps the entire chain clean, complete, and defensible

  • Humans remain the ultimate decision makers

Accurate data = accurate care = accurate payment
That’s risk adjustment done right.

Let’s turn accuracy into confidence.
And confidence into outcomes.