3 Steps to Closing HCC & HEDIS Gaps Faster with Data

Use integrated analytics, precise documentation, and automated workflows to accelerate quality performance and risk capture.

Value-based payment models and quality programs make closing HCC (Hierarchical Condition Category) and HEDIS (Healthcare Effectiveness Data and Information Set) gaps essential for both patient outcomes and organizational revenue. Yet many providers struggle with fragmented data, delayed reporting, and manual workflows that slow progress and create compliance risk.

In this guide you’ll learn three practical, data-driven steps, backed by U.S. health quality guidance, to accelerate gap closure while reducing staff burden and improving year-round quality management.

Step 1: Integrate and Consolidate Data for Real-Time Visibility

Why fragmentation slows progress

Data needed to identify and close gaps typically lives in multiple systems: EHRs, claims, lab portals, and care management platforms. When these systems don’t talk to each other, care gaps remain hidden until retrospective chart review or claims adjudication — delaying interventions.

What to do: create a unified data layer

Ingest multiple sources (EHR encounters, claims, labs, pharmacy, care management logs) into a single analytics layer or data warehouse.
Enable near-real-time alerts and dashboards that flag open HEDIS measures (e.g., overdue screenings) and undocumented HCC conditions as soon as data arrives.
Provide role-based views for care managers, coders, clinicians, and revenue teams to act on items relevant to them.

Why this works: The Office of the National Coordinator for Health IT (ONC) and other authorities emphasize interoperability and data exchange as foundational for coordinated care and quality improvement. Real-time visibility moves teams from reacting at year-end to managing gaps continuously.

Action step: Prioritize a phased data integration plan — start with claims + EHR + labs for the highest-value HEDIS/HCC measures and expand from there.

Step 2: Improve Documentation and Coding Precision

The documentation bottleneck

Analytics identify opportunities, but codes and clinical notes must support them. Many HCC and HEDIS misses occur because clinical documentation lacks the specificity or clinical linkages needed for accurate coding and measure capture.

Key tactics for precise capture

Clinical specificity training: Educate clinicians on wording that supports HCC codes and specific HEDIS criteria (for example, linking comorbid conditions explicitly and documenting ongoing treatment). The Agency for Healthcare Research and Quality (AHRQ) and coding authorities recommend routine clinician education to improve documentation quality.
Prospective risk adjustment and coding workflows: Use analytics to flag likely diagnoses before claims submission so providers or coding teams can confirm and document appropriately (rather than correcting after claims are denied).
Use NLP and chart-scan tools: Natural language processing (NLP) and automated note-scanning can surface undocumented conditions or missed keywords in notes, helping coders catch gaps earlier.
Routine focused audits: Regular, targeted chart reviews ensure documentation meets HEDIS definitions and supports HCC capture.

Why this works: Accurate, specific documentation is the bridge between clinical care and measure capture. When documentation is clear, coders and claims teams can reliably represent clinical complexity to payers and quality programs.

Action step: Implement monthly or quarterly clinical documentation improvement (CDI) checks focusing on the top 10 HEDIS/HCC drivers for your population.

Step 3: Automate Gap-Closure Workflows & Prioritize Outreach

Manual outreach is slow and costly

Relying on manual inboxes, phone calls, and ad-hoc lists for outreach doesn’t scale. Practices must prioritize who to contact, what outreach to run, and how to close documentation loops quickly.

Automation tactics that scale

Prioritization with predictive logic: Use predictive scoring and rule-based prioritization to rank patients most likely to close a gap (e.g., those due for a screening who previously attended similar appointments). This ensures limited outreach resources are used where they’ll have the most impact.
Multi-channel patient outreach: Automate appointment reminders, pre-visit questionnaires, and education via SMS, email, and patient portals to increase screening and immunization adherence. Studies and digital-engagement providers show multi-channel workflows improve compliance rates.
Automated tasks for staff: When outreach results in patient action (e.g., a completed lab or screening), automatically generate tasks for coders or clinicians to verify documentation, preventing closed-loop failures.
In-year tracking dashboards: Monitor gap closure progress continuously rather than waiting for year-end reporting. Continuous tracking helps teams adjust tactics during the measurement year.

Why this works: Automation reduces manual labor, improves timeliness, and increases the throughput of gap closure activities without proportional increases in staff time.

Action step: Pilot a prioritized outreach program for one high-impact HEDIS measure (e.g., mammography or diabetes Hba1c monitoring) and measure the month-over-month closure rate.

Recap: The Three Steps at a Glance

Integrate data: Build a unified, near-real-time data layer so gaps appear immediately.
Fix documentation: Train clinicians, use NLP, and audit charts to ensure every qualified condition or service is recorded precisely.
Automate outreach: Prioritize patients with predictive logic, use multi-channel outreach, and automate staff workflows to scale closure.

Key takeaway: Combining integrated data, documentation precision, and automation changes gap closure from a seasonal scramble into a continuous, manageable process.

Measuring Success and Next Steps

Closing HCC and HEDIS gaps faster is not only possible; it’s measurable. Organizations that unify data sources, strengthen documentation, and automate workflows can expect better year-over-year quality scores, fewer missed revenue opportunities from under-captured risk, and improved population health outcomes.

The Centers for Medicare & Medicaid Services (CMS) and national quality groups emphasize continuous monitoring, documentation integrity, and interoperability as best practices for quality improvement in value-based programs.

Next step: Select one measure to pilot these three steps this quarter—measure baseline gap rates, implement the three tactics, and compare in-year closure rates after 90 days.

Data as Your Strategic Advantage

Learn how our platform, with over 30 years of healthcare experience, can unify your data, power your analytics, and guarantee improvements in your HCC and HEDIS gap closure rates. Let’s make data work for you!