A Risk Adjustment Factor (RAF) score is a number that represents a patient’s overall health status and predicted cost of care. The Centers for Medicare and Medicaid Services (CMS) uses it to adjust payments to Medicare Advantage (MA) plans. A score of 1.0 is average. A higher score means higher expected costs and higher reimbursement.
Even a small change in a RAF score can mean thousands of dollars more or less in funding per patient. That is why insurers and providers in value-based arrangements need to understand exactly how RAF scores are built, and how to keep them accurate.
A RAF score translates a patient’s health status into a single number that predicts their cost of care. CMS uses it to pay MA plans fairly. Plans that enroll sicker, higher-cost members receive more, and plans with healthier members receive less. This lets health plans balance costs across their whole membership and keep coverage accessible for everyone, regardless of health status.
The score combines two things: who the patient is (demographics) and how sick they are (documented conditions). The sicker and more complex the patient, and the more completely those conditions are documented, the higher the RAF.
A patient’s RAF score is the sum of two components:
Added together, those components produce the patient’s RAF score.
An illustrative example (CMS-HCC V28):
| Component | Risk value |
|---|---|
| Female, 76, community (demographic base) | ~0.40 |
| HCC: Diabetes with chronic complications | ~0.30 |
| HCC: Congestive heart failure | ~0.40 |
| Total RAF | ~1.10 |
At a RAF of about 1.10, this patient is roughly 10% above the average expected cost, and the plan is reimbursed accordingly. (Values are illustrative; confirm exact V28 coefficients for your population.)
The takeaway: every supportable HCC that makes it into the documentation raises the RAF, and every one that is missed quietly lowers it. Accurate RAF scoring depends on capturing the full clinical picture, which is why many organizations use automated data extraction and real-time coding support rather than relying on manual chart review alone.
According to the American Academy of Family Physicians (AAFP), a score of 1.0 is average. Decimal places represent the percentage above or below average. A plan with an average patient RAF of 1.25 receives roughly 25% more from Medicare than a plan at 1.0.
But “good” is less about a high number than an accurate one. The goal is a RAF that truly reflects your patients’ acuity, no more and no less. Overstated scores create audit exposure. Understated scores leave funding, and often unmanaged conditions, on the table. Accurate scores can also trigger appropriate case management or chronic care management, improving quality of care for the sickest patients.
Your practice’s RAF scores can affect your compensation now and in the future. Health plans typically pass gains or losses to providers in one of three ways:
In every case, the through-line is the same. Incomplete documentation means a lower RAF than your patients’ health actually warrants, and lost funding you cannot recover after the fact.
Most RAF shortfalls trace back to the same root cause: supportable diagnoses that never made it into the documentation. Capturing them during the visit, while the chart is open and the evidence is fresh, is the most reliable way to keep RAF scores accurate. That is what HCC Assistant does. It surfaces missed and suspected HCCs in real time, inside your EHR.
CMS phased in the V28 risk adjustment model over three years, reaching 100% implementation for payment year 2026. V28 renumbered and re-weighted HCCs, expanding the model to 115 categories, and it tightened documentation requirements. The practical effect: some diagnoses that raised RAF under the old V24 model no longer do, and the bar for supporting evidence is higher. Coding and documentation workflows maintained against V28 are now essential to an accurate RAF.
Calculating and protecting RAF scores across a full patient panel is difficult to manage by hand. Inferscience’s HCC Assistant surfaces missed and suspected HCCs at the point of care with 98% coding accuracy, so your RAF scores reflect the full clinical picture. Its HCC Validator confirms every diagnosis meets MEAT criteria before submission, for RADV-ready documentation. HCC Assistant runs natively inside athenaOne, Epic, and eClinicalWorks, and a 700-provider clinically integrated network has used it inside athenaOne since 2020.
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What is a good RAF score? A score of 1.0 is average (per AAFP). A RAF of 1.25 means about 25% above average expected cost, and roughly 25% more Medicare Advantage funding. What matters most is an accurate score that reflects your patients’ true acuity.
How is a RAF score calculated? CMS adds a demographic base score (age, sex, eligibility) to the sum of the risk coefficients for each documented HCC. The total is the patient’s RAF score.
What’s the difference between RAF and HCC? HCCs are the diagnosis groupings; RAF is the resulting score. HCCs are the inputs CMS uses to calculate the RAF, and RAF is the output that determines payment.
Do RAF scores reset each year? Yes. RAF is recalculated annually, so a patient’s conditions must be documented every calendar year to count toward the score.
What changed under CMS-HCC V28? V28 reached 100% implementation for payment year 2026. It renumbered and re-weighted HCCs, expanded the model to 115 categories, and tightened documentation requirements, so some diagnoses that raised RAF under V24 no longer do.
