Boosting HEDIS Scores with AI: How Health Plans Use Intelligence to Improve Member Outcomes

Every major health plan in the United States faces is subject to public ratings and financial benchmarks, determined by the Healthcare Effectiveness Data and Information Set (HEDIS). These performance measures influence billions of dollars in contracts, member retention, and overall plan success each year. When audit season arrives, missing data or unresolved care gaps in reports trigger immediate pressure. The fallout lands on every department that touches quality, including care management, compliance, technology, and executive leadership.

HEDIS goes far beyond routine compliance. It defines which plans earn top ratings and which lag behind. Gaps in quality get flagged, forcing leaders to act quickly or risk losing crucial funding and damaging their reputation. Plans that rely on the same old workflows find themselves scrambling to respond.

Artificial intelligence (AI) is beginning to change how health plans approach HEDIS, closing care gaps faster, giving teams clearer visibility, and reducing last-minute chaos. This shift allows organizations to focus on what truly matters i.e. improving member care and Stars performance.

For those seeking a practical, real-world view of AI’s role in health plan operations, proven strategies lie ahead. There approaches not only drive HEDIS success but also safeguard the well-being of teams along the way.

Why HEDIS Still Matters: Aligning Metrics with Member Well-Being

The Healthcare Effectiveness Data and Information Set, known as HEDIS, is woven into daily operations for every health plan, aiming to stay competitive. HEDIS stands for more than a routine compliance requirement. These measures surface in audits, drive boardroom discussions, and take the center stage when members raise difficult questions about gaps in their care. In the United States, hundreds of millions of people are covered by plans measured by HEDIS. International health systems have also begun adopting these same benchmarks, which means HEDIS is fast becoming a shared language for quality across the industry.

Every measure, from diabetes checks, cancer screenings to immunizations, reflects how effectively a health plan manages its business and supports its members. Declining HEDIS scores often signal missed care, unaddressed patient concerns, and provider networks falling short of expectations. These shortfalls often lead to lost funding and declining rating.

High-performing plans treat HEDIS as a year-round compass, not just an audit-season checklist. They proactively track member engagement, monitor provider follow-through, and intervene at the first sign of gaps. Today, artificial intelligence is accelerating this shift, enabling teams to move away from constant crisis response and toward building a culture of sustained, measurable quality.

AI-powered Insights: 10 Proven Ways to Boost HEDIS Scores

Health plans are leveraging artificial intelligence to transform HEDIS performance, moving from reactive scrambling to proactive gap closure. Here’s how AI delivers measurable results:

1. Mapping Provider Performance Against HEDIS Measures

AI aggregates visits, claims, and care management to track provider performance across all HEDIS measures in real-time. Leadership gains early visibility into trends, allowing targeted support for struggling clinics before annual reporting deadlines.

2. Automated Credentialing Alerts

Every health plan faces the risk of missed renewals or expired certifications. Artificial intelligence monitors provider credentials in the background every day, so teams receive advance warning when something is off. This reduces the need for emergency paper chases and allows compliance teams to fix issues before they become serious problems.

3. Intelligent Task Assignment

Artificial intelligence reviews past performance on specific care gaps, matches this to provider strengths, and routes tasks accordingly. One team might excel at cancer screenings, while another is better with chronic disease follow-up. Assignments get smarter, closure rates go up, and time is spent where it delivers results.

4. Monitoring Provider Engagement Throughout the Year

Provider engagement tends to fluctuate, and it is easy for participation to drop as the year progresses. Artificial intelligence keeps track of training, documentation, and logins. When engagement starts to slide, quality leaders can step in quickly to re-engage the right people and prevent a drop in overall performance.

5. Building Deep Audit Trails Automatically

Every action (gap closures, follow ups) is logged with timestamps and provider attribution. Artificial intelligence organizes these actions into comprehensive audit trails. This cuts down on the last-minute rush to assemble records for surveys and keeps compliance strong every single day.

6. Optimizing Network Coverage and Suitability

Artificial intelligence assesses the overall provider network, looking at specialties, locations, and member demographics. It highlights areas where coverage, language skills, or clinical focus are lacking, helping plans take action early instead of explaining missed targets later.

7. Managing Reminders and Regulatory Updates

AI instantly identifies providers affected by mid-year guideline changes and pushes tailored updates, ensuring no one falls behind due to manual oversight.

8. Analyzing Root Causes for Provider-level Gaps

Artificial intelligence digs beneath the surface of performance problems. It looks at documentation patterns, EHR workflows, and onboarding timelines to show leaders exactly why some providers are underperforming. Teams get to solve real issues rather than rely on broad, untargeted outreach.

9. Enabling Peer Benchmarking and Knowledge Sharing

AI anonymizes performance data to facilitate peer learning, turning internal best practices into improvement opportunities (without public ranking pressure).

10. Tracking the Impact of Feedback and Incentives

After any intervention, artificial intelligence monitors what changes. Scores, engagement levels, and incentives are tracked in real time. Health plans see immediately if a strategy is working, which allows them to adjust before the next review cycle. Providers also know where they stand and what comes next.

Continuous Improvement Through AI-driven Healthcare Monitoring and Feedback

The reality of HEDIS and Stars is that performance can shift quickly, and static reports do little to prevent gaps from reopening or new issues from forming. Continuous improvement depends on feedback loops that surface problems early and support action before ratings drop.

Here’s how AI-powered systems support ongoing feedback and monitoring:

• Centralized intake of complaints, appeals, and grievances using a digital CAG platform
• Real-time tracking of resolutions, follow-ups, and recurring issues
• Automated trend analysis for quality and compliance teams to spot trouble spots fast
• Transparent audit trails that reduce the manual burden during survey preparation

When health plans combine digital CAG with predictive analytics, they create a foundation for faster course correction, better compliance, and less firefighting at the end of the year

Personalized Member Engagement with AI-driven Journeys

No two members move through the healthcare system the same way. Traditional outreach strategies that rely on generic reminders and standard scripts fall flat when members need different levels of attention, motivation, and support. Health plans that want real improvement in HEDIS and Star Ratings have turned to AI-driven personalization for member engagement.

Here’s a quick run down of how AI makes member engagement more effective:

• Segmentation of members based on risk, history, and preferred communication channels
• Dynamic creation of outreach journeys, where content and timing adjust automatically
• Escalation logic that flags high-risk or disengaged members for tailored interventions
• Integration of feedback from provider lifecycle management and complaints, appeals and grievances, so member interactions reflect recent provider and complaint history

When health plans build journeys that reflect the realities of member experience, closure rates on care gaps rise. Satisfaction scores improve, and fewer members fall through the cracks. Personalized engagement is not a side project anymore. It is a central driver for both regulatory success and real outcomes.

Turning Health Plan Data into Action: Why Integration and Transparency Matter More Than Ever

There is a point where every health plan team realizes that data on its own does not move HEDIS scores or change Stars ratings. The missing link is almost always the way information moves between teams, workflows, and systems. The biggest lifts in quality happen when claims data, provider records, and member feedback are all connected, without silos or manual clean-up marathons.

Artificial intelligence has a role to play, but the first step is making sure that everyone from the compliance analyst to the case manager works from a single, current source of truth.

Many health plans still spend too much time reconciling mismatched records, piecing together a member’s journey from half a dozen systems, or following up on incomplete provider details. It slows down care gap closure, frustrates providers, and leaves members without answers. The plans making real progress have invested in platforms that unify all data related to provider performance, member outreach, grievances, and compliance. This unified view does not just improve reporting. It makes every follow-up, intervention, or audit run smoother and faster.

Here are the ways integrated, transparent data flows can help health plans protect both quality and outcomes:

• A member’s entire interaction history, from the first screening to the last follow-up, is always visible and current
• Provider status, credentialing, and compliance data are linked in real time to quality tracking, so gaps never hide in a stack of old files
• Complaints, appeals, and grievances are tied back to both provider action and member experience, helping plans close the loop and learn from every touchpoint
• Quality teams can drill down from high-level metrics to the individual events, identifying root causes without chasing down disconnected spreadsheets
• Leaders see which interventions move the needle, so budgets and resources get pointed at what works

The real payoff shows up when surveyors or regulators come into the picture. With everything in one place, the stress of last-minute data gathering fades. Audit readiness becomes a daily habit, not an annual emergency. Health plans free up bandwidth to actually engage members and support providers instead of getting stuck in endless reporting cycles.

For organizations aiming to raise HEDIS and Stars scores, and to meet every new demand from CMS or NCQA, this level of operational integration is no longer optional. It is the foundation for real improvement. Artificial intelligence and automation work best when the underlying data is clean, current, and always ready for action. In a landscape where quality is measured at every step, health plans that build for integration and transparency set themselves up for long-term, measurable success.

Insights into Newgen’s Health Solutions

For health plans, who are looking to streamline operations, ensure compliance, and move from reactive to proactive management, a connected suite of solutions makes the difference. The right platform is one that supports every stage of quality, provider, and member management. Here are the core health solutions available:

• Provider Lifecycle Management (PLM) for automated credentialing, performance tracking, and seamless network operations
• Complaints, Appeals, and Grievances (CAG) for centralizing intake, speeding resolution, and providing audit-ready transparency
• Provider Data Management (PDM) as a single source of truth for provider records, network verification, and analytics
• Integrated member engagement tools, so outreach aligns with care gaps and compliance needs
• Workflow Automation: End-to-end workflow automation to drive efficiency, reduce manual errors, and ensure consistent reporting across teams

Each solution has been designed to work with the others. Plans see the greatest value when data, process, and decision-making flow together without silos.

The Path Forward: Smarter HEDIS and Stars, Better Health Plan Results

Performance in healthcare is measured one member, one provider, and one process at a time. Plans that want to lead the market can no longer settle for slow, manual, or fragmented quality operations. AI is already proving it can surface risks early, close gaps faster, and keep teams focused on what matters most: outcomes, experience, and compliance.

With connected systems for provider management, member engagement, and digital CAG, health plans move from reacting to problems to anticipating them. Better data, smarter analytics, and live feedback drive the results that matter, whether that is higher HEDIS scores, improved Stars, or healthier, more satisfied members.

If your organization is ready to take the next step, now is the time to invest in systems and solutions that match the realities of modern healthcare. Data-driven operations, continuous improvement, and member-focused engagement are not merely trendy words. They are the foundation of health plan leadership in the years ahead.