3 challenges MA plans face under CMS's 2027 Star Ratings changes

I recently attended the 15th Medicare Stars, HEDIS®, Quality & Risk Summit and joined as a panelist on the session, What Should Plans Focus on Based on the CY2027 Final Rule?​, with health plan leaders from Johns Hopkins, Highmark, and Devoted Health. The session and overall event conversations kept coming back to the pressure health plans face on their quality goals while the tools and workflows they rely on lag behind.

Three challenges came up across nearly every session I attended.

1. CMS's 2027 methodology increases the weight on clinical outcomes, making quality improvement the sharpest differentiator.
2. Data infrastructure gaps are creating friction across risk and quality teams.
3. Digital quality measurement is arriving quickly, and many plans are still preparing.

Each challenge traces to the same root. Siloed functions, fragmented data, and legacy reporting infrastructure fall behind current CMS requirements.

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Challenge 1: Star Ratings methodology is changing

The CY2027 Final Rule session centered on aligning quality performance with the outcomes that matter to CMS and members. The removal of 11 administrative measures eliminates a buffer that many health plans relied on for strong operational consistency. CMS finalized these changes in April 2026, and the measure removals phase in across the 2028 and 2029 Star Ratings. Now, clinical outcomes are weighted more heavily, and though plans should continue the administrative and operational work that previously drove high scores, the difference will show in how well operations translate into member health. Brendan Generelli of Johns Hopkins Health Plans put it like this: "What CMS is really measuring is, are you doing the right thing for these Medicare Advantage beneficiaries?"

We also discussed the recent news of the Clover Health ruling, and the consensus was that the operating picture for all plans continues to be the same with quality programs moving forward as planned. The message for leadership teams held steady. While the details of regulatory changes and litigation shift, programs must continue to improve on member outcomes.

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Challenge 2: Data infrastructure gaps create friction between risk and quality teams

Provider abrasion is a direct consequence of fragmented retrieval. Getting the right medical records in, knowing where they are, and combining efforts for risk and quality retrieval continue to be challenges for the health plans at the Summit.

Plans running separate risk and quality teams each own different data, different workflows, and different vendor relationships. Reconciling those systems manually absorbs FTE hours that should go toward clinical work. For Summit participants, that cost is unsustainable.

The operational fix to risk and quality silos is a shared data foundation. When chart retrieval, diagnosis capture, and HEDIS measure performance all draw from the same clinical record, plans close gaps once and maintain one audit trail that satisfies both RAF submission requirements and NCQA review.

Artificial intelligence (AI) and automation can address part of this problem directly. AI can handle chart retrieval, flag diagnosis gaps, and surface evidence, while clinical staff focus on the clinical judgment those records require. Plans that have built that model report higher coder throughput and lower provider abrasion. As HEDIS measures become more outcomes-focused and RADV audits expand, health plans are prioritizing a shared clinical data layer that removes the friction between risk and quality. As my fellow panelist Mike Nieper of Highmark Health stated, "What we've always done is not going to work moving forward."

Challenge 3: Digital quality measurement is arriving faster than most plans expect

Digital Quality Measures (DQM) and the ECDS transition drew sustained attention at the Summit. The plans in the room discussed the need for organizational transformation including a multi-year roadmap for FHIR-based reporting.

FHIR-based clinical data exchange changes the retrieval model, the validation model, and the abstraction model simultaneously. Plans built around retrospective chart pull cycles will need to shift to continuous clinical data ingestion and real-time performance monitoring, but the administrative and clinical workflows that support those functions remain undeveloped in most plans today. Building them requires decisions about data architecture, vendor relationships, and staff capabilities that plans need to address before reporting requirements change.

Plans making the most progress on DQM have treated the transition as an enterprise initiative with cross-functional governance. Clinical, operational, and financial leadership are aligned from the beginning. Plans that have framed DQM as a reporting change find that it requires more coordination than anticipated.

Quality as a cross-functional capability

Plans handling all three challenges most effectively share one structural trait. Risk adjustment and quality draw on a common data layer.

Plans that have consolidated risk adjustment and quality improvement into a shared data layer report less reconciliation overhead, clearer audit defensibility, and better alignment between quality measurement and RAF submissions.

The operating environment for quality improvement continues to evolve. CMS audit expansion, Stars recalibration, and the DQM transition are converging on a two-year window that leaves limited time for program improvement. Plans structured to absorb those pressures via a unified operating model are better positioned than plans still managing each pressure through a separate program.

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Takeaways for quality and risk adjustment leaders

The Medicare Stars, HEDIS, Quality & Risk Summit confirmed a pattern the performance data already shows. Plans succeeding under the current CMS framework integrated their operating model before the regulatory environment required it. Plans struggling are still running risk and quality as parallel workstreams and treating DQM as a future-state problem.

Reveleer connects risk adjustment, HEDIS abstraction, and member management under one data layer, giving quality and risk teams a shared clinical foundation, one audit trail, and one gap closure workflow. Learn how health plans are using Reveleer to integrate risk and quality operations.

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