The CY2027 Final Rule Just Changed the Math on Quality and Risk Adjustment
Fewer Star Ratings measures. More weight on HEDIS. Tighter rules on which diagnoses count for risk adjustment. Find out exactly how the CY2027 Final Rule reaches into your Stars, HEDIS, and risk adjustment functions — and what it takes to get ahead.
The rate got the headlines. These are the changes that actually move your numbers.
CMS finalized the CY2027 Medicare Advantage and Part D rule in April 2026, alongside the CY2027 Rate Announcement. Together, they reset the ground rules for Stars, HEDIS, and risk adjustment.
A smaller, higher-stakes measure set
CMS is removing 11 measures where plans historically showed little variation. With fewer measures carrying the rating, Star performance and revenue now move together more tightly. No single team's dashboard tells the whole story anymore.
HEDIS Weighs More
As administrative and process measures fall away, HEDIS, outcomes, and member experience measures make up a larger share of the overall Star. These measures don't move on a quality team's effort alone; they move when care delivery and documentation are working in lockstep.
Fewer diagnoses count toward risk scores
CMS is tightening what counts as adequately supported risk. Diagnoses from unlinked chart review records — not tied to a documented service — are excluded from risk adjustment for the first time. And CMS is closing enforcement on a standard that's existed since 2020: audio-only encounters have never met the face-to-face requirement for risk adjustment, and diagnoses tied to them are now explicitly filtered out of both the CMS-HCC model and risk score processing.
iQRAS, Bloom Value's integrated Quality and Risk Adjustment Solution, was built for exactly this moment. It combines advanced AI with clinical and coding expertise to keep risk documentation and quality performance reading off the same clinical record — surfacing Stars and HEDIS risk early enough to act on, and coding risk adjustment that's accurate, encounter-linked, and defensible under the rules that take effect for 2027.
Proactive on quality. Defensible on revenue.
iQRAS pairs two purpose-built engines — one watching Stars and HEDIS performance, one governing risk adjustment coding — inside a single closed-loop system of augmented intelligence.
Intelligent Quality Optimization Service
Medicare Advantage quality performance is still managed reactively — by the time Stars and HEDIS results are clear, the window to intervene has narrowed. iQOS evaluates performance early in the measurement year, so there's still time to act.
- Early gap identification across Stars and HEDIS measures
- Agents investigate performance changes and surface underlying drivers
- Every action backed by rationale, defensible under CMS and internal review
Intelligent Risk Adjustment Service
Defensibility in risk adjustment is no longer a choice — it's a strategic imperative. iRAS combines advanced AI with clinical and coding expertise to deliver risk adjustment that's accurate and defensible by design.
- Human-in-the-loop validation on every coding suggestion
- Fully traceable logic, audit trails, and documentation
- Clinician-centric suggestions that cut noise and alert fatigue
Augmented intelligence, not automation for its own sake
Across both quality and coding, intelligent agents do the investigation — surfacing emerging performance risk, identifying the drivers behind it, and recommending the next best action. Every suggestion, whether it's a coding recommendation or a quality intervention, is backed by human-in-the-loop oversight. The closed-loop engine learns from real-world feedback, continuously improving accuracy, reducing errors, and raising the bar on defensibility over time.
Built to withstand review, not just perform well
Quality performance and coding accuracy don't end at improvement — they have to withstand scrutiny. Every recommendation, whether it moves a Star measure or supports a risk adjustment code, is fully traceable: clear rationale, transparent logic, and audit trails that stand up to CMS review. Because outputs are AI-generated but expert-governed, decisions stay defensible under internal review, CMS audits, or external scrutiny — whether reviews are prospective, concurrent, or retrospective.
Built for the people who use it every day
Providers only see relevant, review-ready suggestions — cutting down on noise, reducing alert fatigue, and streamlining review. Quality and coding teams get clear, prioritized insight on where intervention will make a difference, instead of spreading effort across broad, late-stage initiatives. Removing low-value flags and surfacing only clinically meaningful opportunities builds trust, boosts engagement, and supports a more collaborative ecosystem.
Integrity-driven intelligence, engineered for systemic trust
iQRAS goes beyond accuracy and compliance — it's designed to promote ethical risk adjustment and quality management at scale. By embedding clinical validation, removing unsupported suggestions, and prioritizing patient-centered outcomes, iQRAS helps ensure the technology is used responsibly. The result: performance and revenue gains that never come at the expense of patient record integrity, provider trust, or public credibility.
Why Health Plans Choose iQRAS
Boost Accuracy & Compliance
- Reduces coding errors and enhances risk score integrity.
- Maintains audit readiness with structured and transparent documentation.
Increase Efficiency & Reduce Administrative Burden
- Automates manual risk coding to improve coder productivity and accuracy.
- Real-time AI assistance to cut down on administrative burden.
Improve Care Quality & Star Ratings
- Enhances member insights to support proactive care management.
- Enables proactive interventions that contribute to higher Star Ratings and better patient outcomes.
Maximize Financial Performance
- Optimizes RAF scores to ensure fair reimbursement.
- Enhances financial sustainability by reducing revenue leakage.
Ready for CMS 2027?
See how iQRAS helps your quality and risk adjustment teams work from the same clinical intelligence.