How Network Adequacy Decisions Drive Star Ratings: The Hidden Quality Connection

Which Star Rating Domains Are Affected by Network Adequacy

CMS evaluates Medicare Advantage plan quality across five domains, with the Part C Summary Star Rating weighting those domains differently based on the evidence base for their impact on member health outcomes. Of the five domains, three are directly and materially affected by network adequacy decisions: Member Experience (which draws heavily from CAHPS survey data), Access and Availability, and Care Coordination. Together, these domains account for roughly one-third of the Part C Summary Star Rating.

The connection between network adequacy and Star Ratings is not theoretical — it runs through documented causal pathways. When members cannot access a needed specialist in a reasonable timeframe, they report worse experiences on CAHPS. When care coordination fails because a member's primary care physician cannot get timely specialist referrals filled, care gaps accumulate and HEDIS clinical measure rates decline. When members experience difficulty getting appointments, they submit complaints that feed into the Appeals, Grievances, and Access domain. Every adequacy failure leaves a measurable signature in the Star Rating data.

Plans that manage adequacy and Stars as separate workstreams — with different teams, different reporting cycles, and different strategic frameworks — are structurally prevented from seeing this connection. The network operations team is focused on county-specialty thresholds; the quality team is focused on CAHPS scores and HEDIS rates. Neither team has visibility into how the other's decisions and outcomes affect their own metrics. The result is a compounding performance problem that manifests in below-average Star Ratings for plans that would otherwise have the clinical and operational capabilities to perform at four or five stars.

The Member Complaint Pathway from Access Barriers to CAHPS Scores

The CAHPS Health Plan Survey asks Medicare Advantage members about their ability to get appointments with their providers — both primary care and specialists — within a reasonable timeframe. The specific CAHPS items most affected by network adequacy include: "How often was it easy to get the care, tests, or treatment you needed?" and "How often did you get an appointment for a check-up or routine care at a doctor's office or clinic as soon as you thought you needed?" These items feed directly into the Getting Needed Care composite measure, which is one of the highest-weighted items in the Part C Star Rating calculation.

The pathway from adequacy failure to CAHPS score decline is direct. A member who needs a cardiologist referral and is told by their primary care physician that the plan's contracted cardiologists have six-week new patient wait times will, if surveyed, report that it was not easy to get the care they needed. If that member then encounters difficulty obtaining a specialist appointment across multiple attempts, they may also submit a formal complaint or grievance, which counts separately in the Appeals, Grievances, and Access domain.

Plans often react to poor CAHPS scores by investing in member experience programs — care coordinator outreach, call center improvements, member advisory panels. These investments are valuable, but they cannot overcome a network composition problem. A member who genuinely cannot see a cardiologist within a reasonable timeframe will not report a better experience because they received a friendly call from a care coordinator. The underlying access barrier must be resolved through network contracting before member experience initiatives will have their full impact on CAHPS scores.

The timing dynamics of CAHPS also demand attention. CAHPS surveys are administered to a sample of members based on their experience over the prior benefit year. Adequacy improvements made in the current year affect CAHPS scores — and therefore Star Ratings — with a significant lag. Plans that make major network improvements in 2025 are improving their 2026 CAHPS scores, which affect their 2027 Star Ratings. This multi-year lag means that investments in network adequacy quality must be made early and consistently to produce the Star Rating returns that justify them.

How Provider Quality in the Network Affects Clinical Measure Stars

HEDIS clinical measure performance — the basis for the majority of Part C clinical domain Stars — is heavily determined by which providers are in network and how actively those providers pursue preventive care and chronic disease management. Plans do not control clinical practice; they control which practitioners their members can see. The quality of those practitioners directly determines whether HEDIS measures are being actively managed for plan members.

High-performing HEDIS measures require providers who order preventive screenings, close care gaps proactively, document diagnoses accurately (which also affects risk adjustment), and refer patients appropriately for follow-up services. Providers who are reactive rather than proactive in their clinical approach — who only address issues when a patient presents with a complaint, rather than proactively pursuing annual wellness visits, cancer screenings, and chronic disease monitoring — contribute to HEDIS gaps that accumulate into lower Star Ratings.

Plans that contract primarily on adequacy criteria — geographic coverage and specialty mix — without integrating provider quality data into the contracting process are building networks that may pass CMS thresholds but fail to support the clinical measure performance needed for high Stars. The network composition decisions made during the contracting phase effectively lock in a quality trajectory for the benefit year, because it is extremely difficult to substantially improve HEDIS performance through care management programs if the underlying provider network is not clinically oriented toward preventive care and gap closure.

The Relationship Between Network Adequacy and Care Gap Closure Rates

Care gap closure — the process of identifying members who have missed preventive services, overdue screenings, or lapsed chronic disease monitoring, and ensuring those gaps are addressed — is the operational mechanism through which HEDIS clinical measures improve. Care gap closure depends on provider cooperation: the member's primary care physician must be willing to act on care gap alerts, schedule the relevant service, and document the encounter in a way that creates a claimable event for HEDIS measurement.

When a plan's network has access barriers — members assigned to primary care physicians who are not accepting new patients, or PCPs with large panel sizes that limit appointment availability — care gap outreach frequently fails at the appointment scheduling step. The care management team identifies a gap, sends an alert to the provider or the member, and the member cannot get an appointment within the measurement year's window. The gap remains open and the HEDIS measure does not improve regardless of how effectively the care management team performed its outreach function.

Adequacy improvements that increase the availability of primary care appointments — either through recruiting additional PCPs in high-gap areas or ensuring that contracted PCPs maintain open panels — directly improve care gap closure rates by removing the access barrier that prevents gap-closing appointments from occurring. Plans that measure care gap closure rates by county and overlay those rates against adequacy metrics for the same counties consistently find a strong correlation between adequacy tightness and gap closure underperformance.

Strategic Provider Selection for Quality Alignment

The evolution of Medicare Advantage network strategy has moved well beyond pure adequacy compliance toward a quality-aligned contracting model in which provider selection considers clinical performance metrics alongside geographic coverage. This approach, often described as value-based network design or quality-tiered network architecture, uses HEDIS performance data, patient experience data, and quality measure participation records to inform which providers to actively recruit and which providers to credential but not actively promote.

Quality-aligned provider selection requires data that most network operations teams do not currently have integrated into their contracting workflows. HEDIS measure performance at the individual provider level, patient experience survey results where available, preventive care ordering rates, documentation quality for risk adjustment purposes, and participation in quality improvement programs are all relevant inputs. Assembling this data requires integration between the network operations team and the quality analytics function — an integration that most plans have not yet built.

The practical starting point for most plans is to overlay publicly available quality data — CMS Physician Compare performance data, HEDIS measure performance from prior years where available at the provider level, and patient experience scores — against the provider contracting pipeline. Providers with strong quality profiles in high-priority HEDIS measure categories should be prioritized in contracting outreach. Providers with documented quality concerns should be contracted for adequacy purposes but not actively promoted through network positioning or value-based incentive programs.

How Blueprint Overlays Quality Data on the Adequacy Dashboard

Blueprint's adequacy scoring engine includes a quality overlay layer that maps provider-level quality indicators against the adequacy heat map for each service area. For each contracted or prospective provider in the pipeline, the platform displays available quality performance data alongside the adequacy contribution that provider would make if contracted — giving network operations teams a unified view of geographic coverage and clinical quality in a single interface.

The quality overlay sources data from multiple inputs: CMS Physician Compare quality metrics, plan-internal HEDIS measure performance by attributed provider where available, and NCQA quality recognition program participation (Patient-Centered Medical Home designation, diabetes recognition programs, and similar credentials that indicate a practice's orientation toward proactive preventive care). These inputs are weighted by relevance to the plan's priority HEDIS measures and displayed as a provider quality score alongside the standard adequacy metrics.

Network operations teams using Blueprint's quality overlay have reported that the integrated view changes contracting prioritization decisions. When a network team can see simultaneously that Provider A offers strong adequacy coverage in three counties and has above-average HEDIS performance on diabetes management while Provider B offers the same geographic coverage but below-average quality metrics, the contracting decision becomes qualitatively different than if those two dimensions of information are siloed. The quality overlay does not override adequacy requirements — a low-quality provider who is the only available specialist in a county will still be contracted — but it drives more strategic allocation of contracting resources in competitive markets where quality differentiation is possible.

Building a Network That Passes CMS and Delivers Stars

The highest-performing MA plans have moved beyond the binary of "does this network pass adequacy?" to a more sophisticated question: "does this network support the member outcomes and experiences that produce Stars?" These are related but distinct questions, and answering the second requires more data, more strategic intent, and more cross-functional integration than answering the first.

A network that passes CMS adequacy is the minimum bar. A network that delivers Stars requires enough provider depth that members consistently get timely appointments, a quality-aligned provider composition that drives proactive preventive care and HEDIS gap closure, sufficient behavioral health access to support MHPAEA compliance and the access-related CAHPS items, and a geographic distribution that minimizes access barriers for high-need member populations in the counties with the greatest care gap burden.

Plans that close this gap between adequacy compliance and Star performance typically do so through a sustained multi-year investment in network quality: building quality-aligned contracting criteria, integrating network and quality analytics into a shared reporting framework, using care gap data to identify where adequacy improvements will have the greatest impact on Stars, and aligning provider incentive programs with the clinical behaviors that drive HEDIS performance. Blueprint's platform is designed to support this integrated strategy, giving network operations and quality teams a shared data foundation that makes the connection between adequacy decisions and Star Rating outcomes visible, measurable, and actionable.