Understanding HCC Coding and Risk Adjustment in 2026

Last Updated on September 28, 2026

Accurate Hierarchical Condition Category (HCC) coding plays an important role in Medicare Advantage and other risk-based payment arrangements. In 2026, the 2024 CMS-HCC model, commonly referred to as V28, is fully phased in for non-PACE Medicare Advantage organizations, ending the multi-year transition from the previous model.

This change affects diagnosis-to-HCC mappings, condition categories, model coefficients, and how organizations evaluate risk adjustment performance.

When clinically relevant conditions are not completely documented or accurately coded, risk scores may not appropriately reflect a patient’s documented health status. Conversely, reporting diagnoses without adequate clinical support can create compliance and audit exposure under Risk Adjustment Data Validation requirements.

For health plans, provider groups, ACOs, and organizations participating in value-based care, the priority in 2026 is therefore not simply HCC capture. It is maintaining accurate, supported, and defensible risk adjustment data as the updated model becomes the standard for payment.

What Is HCC Coding and Risk Adjustment

Hierarchical Condition Categories (HCCs) are groups of clinically related diagnosis codes used within CMS risk adjustment models to help predict expected healthcare costs.

Applicable ICD-10-CM diagnoses map to condition categories within the model. Those categories, together with demographic and other applicable model factors, contribute to an individual’s Risk Adjustment Factor score.

A higher RAF generally represents greater expected healthcare costs under the applicable model, while a lower RAF represents lower expected costs. Factors such as age, sex, disability status, Medicaid status, and institutional status may also contribute depending on the model segment.

Hierarchical logic is used within defined disease groups so related condition categories are not necessarily counted independently.

Risk adjustment coding therefore involves accurately translating clinically supported diagnoses into coded data that can be used by the applicable risk adjustment model.

The objective is not to generate as many HCCs as possible. It is to ensure that coded information accurately represents the patient’s documented health status while meeting applicable coding and risk adjustment requirements.

For additional background, see AnnexMed’s guide on what is risk adjustment coding and why it matters. It explains how diagnosis coding connects with risk-based reimbursement.

Key Changes in the CMS HCC V28 Model for 2026

CMS confirms that non-PACE organizations use 100% of the 2024 CMS-HCC model in CY 2026. 

CMS also confirms that the 2020 model had 86 payment HCCs, compared with 115 payment HCCs in the 2024 model. 

For non-PACE Medicare Advantage organizations, the previous transition blend with the 2020 CMS-HCC model has ended, with 2026 risk scores calculated entirely using the 2024 CMS-HCC model. 

Major structural changes associated with the updated model include:

• Expansion from 86 payment HCCs in the previous model to 115 payment HCCs
• Renumbering and restructuring of condition categories
• Changes to ICD-10-CM diagnosis-to-HCC mappings
• Updated model coefficients and disease interactions
• Clinical revisions across several condition categories
• Greater granularity within portions of the model

These changes mean organizations should not assume that historical HCC mappings, category numbers, or risk adjustment patterns remain applicable in 2026.

Coding systems, analytics, education materials, prospective review processes, and retrospective review logic should reflect the current model rather than relying on historical V24 assumptions.

For Medicare Advantage plans managing these changes at population scale, risk adjustment also needs to connect with broader payer operations, data quality, audit readiness, and performance reporting. These dependencies make coordination across healthcare payer operations increasingly important as organizations adapt to current model requirements.  

How RAF Scores Are Calculated

A member’s RAF score is influenced by multiple model components. At a simplified level, these include:

1. Demographic factors such as age, sex, Medicaid status, disability status, and applicable model segment.
2. Disease factors generated from eligible diagnosis information that maps to applicable HCCs.
3. Model interactions and hierarchy logic that account for certain relationships among conditions and demographic characteristics.

Within defined disease hierarchies, related HCCs are not necessarily counted independently. CMS applies model-specific hierarchical logic when calculating risk scores.

Because Medicare Advantage risk adjustment is prospective, diagnosis information from an applicable data collection period can influence future payment calculations.

This makes documentation and coding accuracy important throughout the year rather than only during retrospective review.

Persistent conditions should be appropriately documented and coded when they are assessed and remain clinically relevant to the patient’s care. Organizations should also ensure diagnosis information originates from eligible sources and encounters under applicable CMS risk adjustment requirements.

Using MEAT to Strengthen HCC Documentation

Accurate HCC coding depends on clinical documentation that supports the diagnosis being reported.

MEAT is a commonly used framework for evaluating whether documentation demonstrates clinical attention to a condition during an encounter.

MEAT stands for:

• Monitor: Tracking symptoms, laboratory findings, disease progression, or other relevant indicators
• Evaluate: Reviewing test results, medication response, clinical findings, or treatment effectiveness
• Assess or Address: Documenting clinical judgment regarding the condition, its status, or its effect on care
• Treat: Managing the condition through medications, therapies, referrals, procedures, or other interventions

MEAT can help coding, CDI, and compliance teams evaluate documentation quality, but it should not be treated as a standalone CMS coding rule. Documentation and coding decisions should remain aligned with the clinical record, official ICD-10-CM guidance, applicable CMS requirements, and organizational compliance policies.

Problem-list entries or copied-forward diagnoses should not automatically be treated as evidence that a condition was clinically addressed during a particular encounter.

Similarly, documentation should reflect the level of specificity supported by the patient’s clinical information rather than selecting a diagnosis solely because it maps to an HCC.

For a deeper look at these documentation considerations, practices can review AnnexMed’s guidance on HCC coding and documentation.

Common HCC Coding and Documentation Gaps

Risk adjustment inaccuracies can occur when clinically supported conditions are missed, when documentation lacks sufficient specificity, or when unsupported diagnoses are reported.

Common gaps include:

• Clinically relevant conditions that are not completely documented or coded
• Diagnosis reporting that lacks adequate clinical support
• Use of unspecified codes when the record supports greater specificity
• Inconsistent documentation of persistent chronic conditions
• Gaps between specialist, hospital, and primary care documentation
• Overreliance on problem lists without adequate encounter-level context
• Coding or analytics logic based on outdated HCC mappings
• Limited feedback between providers, coders, CDI teams, and compliance teams

Missing supported diagnoses can affect the accuracy of risk adjustment data, while unsupported diagnoses can create compliance and audit exposure.

The appropriate response is not simply to search for more HCCs. Organizations need processes capable of identifying both sides of the problem.

Prospective review can identify potential documentation opportunities before or around an encounter. Retrospective review can evaluate completed records for supported diagnoses, coding accuracy, and documentation gaps. Quality assurance processes and periodic medical coding audits can then identify recurring trends across providers and patient populations.

Best Practices for Accurate HCC Coding in 2026

1. Align Coding and Documentation With the Current Model

Encoder tools, mapping logic, analytics, educational materials, and review workflows should reflect the 2024 CMS-HCC model being used in 2026.

Historical V24 category numbers and mappings should not drive current coding or risk adjustment decisions.

2. Prioritize Documentation Specificity

Code to the level of detail supported by the clinical record.

Providers should document the patient’s current clinical status clearly enough for coding professionals to select the appropriate ICD-10-CM code without inferring unsupported information.

3. Strengthen Current Year Documentation

Persistent chronic conditions should not be carried forward automatically because they appeared in a previous record.

When a condition remains clinically relevant, the current encounter documentation should accurately reflect its status, assessment, and management as appropriate.

4. Connect Providers and Coding Teams

Provider education should focus on clinical documentation quality rather than RAF optimization.

Coding teams can use recurring documentation patterns to provide targeted feedback on areas such as specificity, condition status, conflicting documentation, and missing clinical context.

5. Combine Prospective and Retrospective Review

Prospective programs can surface potential documentation gaps before or around the patient encounter.

Retrospective chart review can evaluate completed documentation for coding accuracy, supported condition capture, and potential compliance concerns.

Together, these approaches provide broader visibility than relying on year-end review alone.

6. Monitor Risk Adjustment Patterns

Organizations can evaluate trends by provider, condition category, patient population, encounter type, documentation pattern, and audit finding.

The purpose of analytics should be to identify recurring accuracy and documentation issues rather than simply tracking RAF movement.

7. Build Audit Readiness Into Routine Operations

Documentation retrieval, coding validation, quality assurance, and corrective action should be routine risk adjustment functions rather than processes introduced only when an audit occurs.

Periodic medical coding audits can help organizations identify recurring coding and documentation issues and strengthen internal controls.

Building a Sustainable Risk Adjustment Program

Accurate risk adjustment is not a one-time coding project. It requires coordination among providers, coding teams, clinical documentation specialists, compliance teams, and analytics functions. A sustainable program should include:

• Current CMS-HCC model logic
• Clear documentation and coding policies
• Provider education focused on clinical specificity
• Prospective and retrospective review where appropriate
• Coding quality assurance
• Documentation-to-code validation
• Provider and coder feedback loops
• Analytics that identify recurring patterns
• Processes for identifying unsupported diagnoses
• Audit and RADV readiness

Organizations should also consider how risk adjustment connects with broader value-based care operations. Risk adjustment, quality performance, care management, and population health may use different measures and methodologies, but each depends on reliable clinical and administrative information. AnnexMed’s resources on population health and value-based care billing provide additional context for organizations operating under risk-based reimbursement arrangements.

HCC Accuracy in 2026 Requires More Than Code Capture

The full transition to the 2024 CMS-HCC model makes accurate documentation, coding, and current model alignment increasingly important for non-PACE Medicare Advantage organizations in 2026.

But accurate risk adjustment depends on more than understanding model changes. It requires consistency across the clinical encounter, documentation, ICD-10-CM coding, HCC mapping, data validation, and audit preparation. Organizations need processes that identify both missed supported diagnoses and diagnoses that lack sufficient clinical support, while using recurring findings to improve provider documentation and coding workflows.

AnnexMed supports health plans, provider organizations, ACOs, and value-based care programs with prospective and retrospective HCC coding, documentation review, quality assurance, analytics, and audit readiness. Through Risk Adjustment and HEDIS Programs, organizations can strengthen the connection between documentation quality, coding accuracy, data integrity, and compliance.

The goal is not simply to capture more HCCs. It is to build a defensible risk adjustment process that accurately represents documented patient complexity and stands up to validation.

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