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A strong Medicare Advantage (MA) Star Ratings improvement plan starts with one contract’s measure-level baseline for a specified rating year, then connects each gap to an operational cause, an accountable owner, a measurable intervention, and a review cadence. It is not a generic checklist or a CMS-mandated template. Build it from the applicable CMS technical notes, measure specifications, cut-point information, and validated contract data; then update it as CMS changes the measure set or methodology.
What the plan must control
Your plan should manage four linked problems: knowing the contract’s true performance, selecting the few opportunities that can materially improve ratings and member outcomes, changing the process that causes each gap, and detecting quickly when execution or measurement has failed. A plan that lists outreach campaigns without a validated denominator, or that chases a previous year’s star threshold, is not an improvement plan.
CMS describes quality improvement as an organizational obligation. Its Medicare Advantage Quality Strategy says, “The foundation of this strategy and the quality improvement (QI) program is improving care coordination and providing health care using evidence-based clinical protocols.” See the Medicare Advantage Quality Strategy for the policy context. Your operating plan should therefore connect rating measures to care coordination, access, service operations, and evidence-based clinical practice rather than treating stars as a reporting-only exercise.
1. Fix the scope before analyzing a score
Write a one-page scope statement and have the contract, quality, actuarial, clinical, compliance, and data teams approve it. Include every item below:
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- Rating year: name the CMS rating year you are trying to improve.
- Measurement period: record the dates that generated the performance data. Do not confuse the measurement year with the year ratings are displayed or with the year quality bonus payments are affected.
- Contract identifier and sponsor: CMS reports performance at the contract or sponsor level, so identify the exact contract rather than using an enterprise average.
- Contract type: specify MA-PD or MA-only.
- Part D scope: state whether prescription-drug measures are included.
- Population and exclusions: document enrollment, eligibility rules, attribution, denominator exclusions, and any partial-year treatment relevant to each measure.
- Decision date: set the date on which the plan will be refreshed when CMS publishes new technical notes, measure files, or data tables.
For current context, CMS published the 2027 Star Ratings on October 8, 2026. Those ratings appear in Medicare Plan Finder for 2027 open enrollment and affect 2028 MA quality bonus payments, according to the 2027 Medicare Advantage and Part D Star Ratings fact sheet. Keep those publication, display, and payment years distinct in every dashboard and executive briefing.
2. Build a defensible measure baseline
Start with the current CMS technical notes, downloadable measure files, data tables, and display-measure materials. CMS maintains these resources on its Part C and D Performance Data page, which is updated as materials change. Use the technical notes for definitions and aggregation, not a prior-year spreadsheet copied forward.
Baseline fields to capture
| Field | What to record | Why it matters |
|---|---|---|
| Measure identifier and name | CMS identifier, current label, and whether it is Part C, Part D, or a cross-cutting measure | Prevents similarly named measures from being combined or misclassified. |
| Rating-year status | Included, respecified, returned from display, moved to display, or retired | A measure that changed status may not be comparable with the prior year. |
| Score and star | Latest CMS score, assigned star, and the performance period that produced it | Separates an observed result from an internal forecast. |
| Direction | Whether a higher or lower value is better | Prevents an improvement target from pointing the wrong way. |
| Denominator and exclusions | Eligible members, attribution rules, exclusions, and sample or survey design where applicable | Shows whether a change reflects care, population mix, or denominator construction. |
| Data source and lag | Claims, encounter data, pharmacy data, clinical records, survey, vendor file, or other source; refresh date and expected lag | Lets owners distinguish a late feed from a genuine performance decline. |
| Weight and aggregation role | Current weight and the domain, summary, or overall rating to which it contributes | Allows prioritization using the correct rating architecture. |
| Trend | Comparable prior-year values, with specification changes annotated | A trend is meaningful only when the measure definition and population are comparable. |
| Data confidence | Completeness, timeliness, reconciliation status, and known integrity concerns | A low-confidence score should trigger validation before expensive intervention. |
Reconcile the contract-level result to internal records without assuming the internal extract is the CMS result. Investigate differences in membership dates, provider attribution, encounter submission, pharmacy reversals, survey response, and exclusion logic. Preserve a versioned data dictionary and a decision log showing who approved each baseline value.
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3. Understand how measures become stars
CMS reports measures at the contract or sponsor level, then rolls them into domains and summary ratings. For MA-PD contracts, the overall rating combines unique Part C and Part D measures. Domain, summary, and overall ratings use different averaging approaches; a measure’s apparent importance cannot be inferred from its raw percentage alone. The Medicare 2026 Part C & D Star Ratings Technical Notes explain the applicable aggregation and technical definitions.
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Do not treat a prior cut point as a permanent target. CMS recalculates cut points each year from performance during the relevant measurement period, so the score needed for a given star can move even when your contract’s result does not. Set an internal operating target above the latest known threshold when feasible, label it as a planning assumption, and refresh it when CMS publishes the rating-year materials.
The 2027 set also illustrates why a copied scorecard fails. CMS describes new and respecified measures, measures returning from the display page, weight changes, and measures moved to display or retired. For 2027, contracts are rated on up to 43 unique measures for MA-PD and up to 32 for MA-only. Those figures are year-specific; confirm the status, specification, and weight of every measure before setting a target.
4. Rank opportunities with explicit criteria
Use a documented scoring rubric instead of allowing the loudest department or the most visible measure to determine priorities. Score each candidate on a consistent scale, such as 0–3, and record the evidence behind each score. The rubric should include:
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- Trend: persistent decline, flat performance, or credible improvement.
- Rating leverage: current weight and plausible effect on the relevant domain, summary, or overall rating.
- Data confidence: completeness, timeliness, reconciliation, and specification stability.
- Operational influence: how directly the organization and its contracted providers can change the process.
- Beneficiary impact: effect on access, safety, continuity, medication use, preventive care, or experience.
- Equity and access signal: a supported disparity by language, disability, geography, race or ethnicity, dual-eligibility status, or other valid stratifier.
- Time to effect: whether a reliable leading indicator can move in weeks or whether an outcome requires a longer clinical cycle.
- Feasibility and risk: staffing, provider burden, compliance review, member communication, and risk of unintended consequences.
| Priority tier | Typical profile | Management response |
|---|---|---|
| Tier 1 | Material gap, high rating leverage, reliable data, and a controllable process | Assign an executive sponsor, cross-functional team, funded intervention, and monthly steering review. |
| Tier 2 | Meaningful beneficiary or rating opportunity but longer feedback loop, moderate influence, or data work still required | Run a defined diagnostic and pilot with milestones before scaling. |
| Tier 3 | Small leverage, unstable specification, low confidence, or little operational influence | Monitor, validate data, and revisit after the next CMS file or measurement cycle. |
Compare like measures within the same rating year and correct domain. A clinical outcome with a long feedback loop should not be judged by the same short-term success test as a call-center process measure.
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5. Diagnose the operating cause before choosing an intervention
A contract average identifies where to look, not why performance is low. For every Tier 1 or Tier 2 measure, map the member journey and the internal workflow:
- Identify: find eligible members using the correct denominator and attribution logic.
- Reach: deliver culturally and linguistically appropriate outreach through the channels members can use.
- Access: secure an appointment, test, medication, service, transportation, or other required resource.
- Complete: verify that the member actually received the service within the measure’s timing window.
- Document: capture the result in the clinical or administrative record using accepted codes and fields.
- Transmit: submit complete, timely encounters, claims, pharmacy events, or survey information.
- Calculate: reproduce the denominator, numerator, exclusions, and directionality before interpreting movement.
Stratify results only when the data are valid and privacy protections are met. Look for differences by provider, geography, product, care setting, language, disability, dual status, and outreach channel where those fields are reliable. Treat a pattern as a signal for investigation, not proof of causation. Confirm whether the gap is caused by care delivery, member access, provider workflow, data capture, or measure interpretation.
Diagnostic questions
- Are eligible members being identified late or omitted because of attribution or enrollment timing?
- Are appointments unavailable, unaffordable, inaccessible, or scheduled outside the measure window?
- Did the provider deliver the service but fail to document or code it in an accepted form?
- Are encounters, pharmacy reversals, laboratory results, or supplemental files arriving after the analytic cutoff?
- Did CMS respecify the measure, change exclusions, alter weighting, or move it to display status?
- Could an apparent improvement result from denominator shrinkage, member churn, or a documentation artifact?
6. Match interventions to the diagnosed mechanism
Choose an intervention only after the cause is documented. Tie it to care coordination or an evidence-based clinical protocol when appropriate, and have clinical, compliance, privacy, and accessibility reviewers approve changes that affect care or member communications.
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| Diagnosed mechanism | Potential intervention design | Leading indicator | Guardrail |
|---|---|---|---|
| Eligible members are not identified reliably | Reconcile enrollment and attribution feeds; create a daily or weekly eligibility work queue with exception handling. | Percentage of eligible members loaded within the defined time. | Reconciliation error rate and duplicate-member rate. |
| Members cannot obtain the service in time | Reserve appointment capacity, coordinate transportation or interpreter access, and escalate unresolved barriers. | Time from referral to completed appointment. | Cancellation, no-show, access, and complaint rates. |
| Outreach is not reaching members | Use a tested sequence of channels, language preferences, accessible formats, and care-manager follow-up. | Successful contact and scheduled-service rates. | Opt-out, complaint, and inequitable reach by valid stratifier. |
| Care occurs but is not documented | Provide provider-specific documentation guidance, pre-visit prompts, and post-visit record reconciliation. | Complete, accepted documentation within the submission window. | Audit accuracy; avoid coding services that were not delivered. |
| Data arrive late or fail validation | Set feed-level completeness thresholds, rejection queues, ownership, and recovery procedures. | On-time file rate and accepted-record rate. | Change-control approval and traceable corrections. |
| Clinical outcome is genuinely poor | Deploy an evidence-based protocol, risk-appropriate care management, medication support, or provider improvement cycle. | Protocol adoption and intermediate clinical markers. | Safety events, contraindications, access, and unintended treatment burden. |
Do not label generic reminders, software, or a vendor service as proven. State the mechanism, the evidence your organization has for the use case, the population covered, and the test you will use to decide whether to scale.
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7. Put accountability and controls in writing
Every priority should have one accountable executive and one operational owner. A committee may approve a plan, but it cannot replace a named person responsible for delivery. Add the following fields to an intervention charter:
- Measure, contract, rating year, and target population.
- Problem statement and evidence for the diagnosed cause.
- Intervention description, start date, dependencies, and required budget or staffing.
- Executive sponsor, operational owner, clinical lead, data owner, provider liaison, compliance reviewer, and member-experience contact.
- Process milestones, leading indicators, outcome measure, data source, refresh date, and review cadence.
- Escalation rule, stop rule, and decision date for adapting or ending the intervention.
- Privacy, accessibility, health-equity, utilization-management, and clinical-safety checks where applicable.
Use a simple RACI matrix for handoffs. For example, the quality leader can be accountable for the measure, the care-management director responsible for outreach execution, the data team responsible for the feed, the provider organization consulted on workflow, and compliance informed or approving where required. Keep the matrix measure-specific; a single enterprise RACI often hides the real owner.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.8. Set milestones that reveal execution failure early
Separate leading indicators from the CMS outcome. Leading indicators show whether the intervention is being delivered; the outcome shows whether the measure is moving. Review them at different frequencies.
| Cadence | Review | Decision |
|---|---|---|
| Weekly or biweekly | Eligible-member volume, contact attempts, appointment capacity, completion, rejected records, and unresolved exceptions | Fix staffing, workflow, access, or data defects before the measurement window closes. |
| Monthly | Provider and segment performance, equity and access stratification, cost, complaints, safety signals, and milestone status | Continue, adapt, expand, or pause the intervention. |
| Quarterly | Validated numerator and denominator trend, specification changes, forecast, and rating leverage | Re-rank the portfolio and reallocate resources. |
| When CMS publishes updates | Technical notes, measure files, cut points, weights, display status, and rule changes | Run impact analysis, update targets, and document assumptions. |
Maintain a decision log for every material change in data, specification, intervention, or target. Short-term movement is not causal proof by itself. Where feasible, use a comparison group, phased rollout, or another evaluation design that can distinguish intervention effects from seasonality, member mix, provider changes, and ordinary variation.
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9. Build data-quality and equity checks into the plan
Data quality is part of quality improvement, not an analytics afterthought. Establish thresholds and owners for file timeliness, completeness, duplicate records, invalid codes, missing provider identifiers, encounter acceptance, pharmacy reversals, survey response, and reconciliation to source systems. Freeze and version the extract used for each executive decision so later corrections are traceable.
Use contract-level results to select investigations, then examine provider- and member-level pathways only in approved, privacy-protected environments. Suppress or combine small cells where required. If a disparity appears, test whether it persists after considering access, language, geography, disability accommodation, provider mix, and data completeness. Do not claim an intervention closes an equity gap until the relevant stratified data show a sustained change.
10. Manage annual CMS changes as a formal workstream
At least once each rating cycle, assign a technical owner to compare the new CMS materials with the prior version. The owner should produce a change register covering:
- Added, removed, retired, display-only, returned, or respecified measures.
- Changed definitions, exclusions, data sources, attribution, or submission windows.
- New or changed weights and aggregation treatment.
- Updated cut points and performance-period dates.
- Implications for MA-PD versus MA-only contracts and Part D scope.
- Required changes to data pipelines, provider guidance, dashboards, contracts, and governance.
CMS’s 2027 fact sheet documents rating-year-specific changes, including new and respecified measures, weight increases for Improving or Maintaining Physical Health and Improving or Maintaining Mental Health, and measures moved to display or retired. Do not carry those details into a later rating year without checking the then-current technical notes and measure files. The Contract Year 2026 final-rule fact sheet is useful for rulemaking context, but current rules and technical materials control implementation.
11. A practical 90-day launch sequence
Days 1–15: establish the fact base
- Approve the rating year, measurement period, contract, contract type, and Part D scope.
- Download the current CMS technical notes, measure files, data tables, and display materials.
- Assign a data owner and create the versioned measure inventory.
- Reconcile internal extracts to the CMS contract-level result and flag unresolved integrity issues.
Days 16–30: select priorities
- Calculate gap, trend, weight, aggregation role, beneficiary impact, data confidence, and operational influence.
- Apply the approved scoring rubric and hold a cross-functional challenge session.
- Choose a limited Tier 1 portfolio and document why other measures are monitored rather than funded.
Days 31–60: diagnose and design
- Map each priority’s member journey and provider workflow.
- Validate denominator, exclusions, attribution, coding, and data-feed behavior.
- Use valid stratification to locate access, provider, or documentation differences.
- Write intervention charters with owners, milestones, indicators, guardrails, and escalation rules.
Days 61–90: launch and learn
- Complete clinical, compliance, privacy, accessibility, and member-communication reviews.
- Launch a controlled pilot or phased rollout where practical.
- Start weekly or biweekly operational reviews and monthly executive reviews.
- Record early decisions, defects, adaptations, and the next CMS-update checkpoint.
12. Common failure modes and recovery actions
| Failure mode | What it looks like | Recovery action |
|---|---|---|
| Targeting an old cut point | The team celebrates a score that no longer maps to the desired star. | Replace the fixed threshold with a rating-year assumption and refresh it when CMS recalculates cut points. |
| Mixing years | A measurement-period result is compared with a rating display or payment year as if they were identical. | Label all dashboards with rating year, measurement period, display year, and payment implication. |
| Using an enterprise average | Contract, provider, and product performance are blended, hiding the accountable pathway. | Start with the CMS contract baseline, then drill down using validated, privacy-protected data. |
| Choosing a popular intervention first | Reminders or a new tool launch before anyone verifies the cause. | Require a documented mechanism and baseline diagnostic before approval. |
| Ignoring specification changes | A trend appears to collapse after a measure is respecified or its denominator changes. | Annotate comparability, re-run the baseline under the current definition, and reset the forecast. |
| Measuring activity, not effect | Call volume rises while completed care, access, or outcomes do not. | Pair every activity metric with completion, outcome, safety, and equity guardrails. |
| No recovery path for bad data | A rejected file or late encounter is discovered after the review window. | Set feed thresholds, exception queues, backup owners, and escalation dates before launch. |
What national 2027 results can—and cannot—tell you
CMS reports that 37% of MA-PD contracts, or 188 contracts, earned four or more stars for the 2027 ratings, and approximately 71% of MA-PD enrollees were in contracts rated four stars or higher. These are national, year-specific context figures from CMS; they are not a target or forecast for an individual contract. Use them to understand the competitive environment, never to substitute for your own measure-level baseline and cause analysis.
Final decision rule
Approve an improvement initiative only when the team can answer five questions in writing: Which contract and rating year are in scope? What validated measure-level gap exists under the current specification? What operational mechanism explains it? Who owns the intervention and which leading and outcome indicators will be reviewed? What CMS, data-quality, beneficiary-safety, and equity changes would cause the team to adapt or stop? Revisit those answers whenever CMS issues new technical notes, measure files, data tables, or rules.
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