The traditional fee-for-service healthcare model reimburses providers based on the number of services they render, regardless of patient outcomes. On the other hand, in value-based healthcare, payment is determined by the complexity of the patient population that each provider serves. Risk adjustment and Hierarchical Condition Category (HCC) coding play crucial roles in value-based care by providing a clear picture of varying health status and risk levels of patient populations. However, value-based care coding comes with several complexities. Following HCC coding best practices helps organizations maintain compliance, strengthen RAF scores, and support better clinical and reimbursement.
Successful implementation of risk-adjusted models requires healthcare organizations to accurately capture patient data and minimize reliance on manual processes. HCC coding services that leverage advanced technologies—such as artificial intelligence (AI), machine learning (ML), and natural language processing (NLP)—help improve documentation accuracy, compliance, and reimbursement.
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Significance of Risk Adjustment and HCC Coding
Risk adjustment accounts for variations in disease burden, demographics, and clinical complexity, ensuring that providers who care for sicker or more complex patients receive fair and accurate compensation. HCC coding strengthens this process by capturing the true severity of chronic conditions through precise documentation and coding. Together, they help support appropriate reimbursement, better resource allocation, stronger quality reporting, and more coordinated, value-based care across healthcare organizations.
HCC coding uses ICD-10 codes to classify a patient’s health conditions and determine their risk score, with each HCC linked to a specific ICD-10 code category. The CMS-HCC model is updated annually to reflect new clinical guidelines, coding changes, and policy shifts. Staying ahead of these updates—and ensuring complete, accurate clinical documentation—is essential to optimizing reimbursement, reducing audit risk, and supporting improved patient outcomes.
Complexities of HCC Coding
HCC coding challenges range from incomplete or unclear documentation and shifting CMS requirements to limited reporting tools, diagnosis tracking gaps, and ongoing coder and clinical staff shortages.
- Coding Accuracy: Accurate coding is critical. While CPT/HCPCS procedure codes reflect what is being billing, diagnosis codes (ICD-10-CM) support medical necessity and risk adjustment. Medical codes change frequently and can complicate HCC coding. In the 2024/2025 CMS-HCC model, around 74,000 ICD-10 codes are aggregated into 266 HCC condition categories, of which 115 are payment-eligible HCCs in the current payment model. Coders must stay up to date on the mapping and understand which diagnosis codes map to payment-eligible HCCs so that providers capture the full risk profile of patients.
Hers’s an example: A patient presents with Type 2 diabetes with chronic kidney disease (CKD stage 3) at a routine visit.- The provider documents: “Type 2 diabetes mellitus with stage 3 chronic kidney disease. Patient is being monitored with quarterly labs, medications adjusted, and CKD progression evaluated.”
- The correct ICD-10-CM code is E11.22 (Type 2 diabetes with diabetic chronic kidney disease)
- An additional code is reported for CKD stage: N18.3 (CKD stage 3)
The combination of E11.22 + N18.3 maps to an HCC category (HCC 18 in CMS-HCC v28), which determines the patient’s RAF score and impacts risk-adjusted payment.
Errors, omissions, or use of non-specified/unsupported ICD-10 codes can lead to missed or inaccurate HCC assignments, incorrect Risk Adjustment Factor (RAF) calculations, and potential under-payment or overpayment.
- Coding Hierarchies: HCC coding follows a hierarchical structure in which diagnosis codes are grouped into condition categories based on clinical severity and expected healthcare costs. Medicare beneficiaries commonly present with chronic conditions such as:
- Hypertension
- Hyperlipidemia
- Diabetes
- Ischemic heart disease
- Congestive heart failure
- Chronic kidney disease (CKD)
- COPD
- Arthritis and musculoskeletal disorders
- Depression and other mental health conditions
- Alzheimer’s disease and other dementias
- Atrial fibrillation
Each HCC category is assigned a Risk Adjustment Factor (RAF) score that reflects the expected cost of caring for patients with that condition. Chronic, progressive, or resource-intensive conditions usually have higher scores.
Under the latest CMS-HCC V28 risk adjustment model, CMS reorganized and expanded the classification system into 115 payment HCCs and 266 total HCC categories, replacing the older V24 model that included only 86 categories. This updated hierarchy captures the true clinical complexity of patients more accurately.
Identifying the correct diagnosis code within the hierarchy – and ensuring strong clinical documentation—is essential. Coders must also adhere to CMS coding and billing compliance rules, as inaccuracies or unsupported diagnoses can result in improper payments, audits, or recoupments.
- Clinical documentation challenges: HCC coding requires accurate and specific documentation of patients’ medical conditions and diagnoses. It relies on the collection and integration of data from various sources, including medical records, laboratory tests, imaging reports, and physician documentation. Clinicians must provide comprehensive and detailed information about patients’ conditions, comorbidities, and chronic illnesses to support proper coding. Coordinating this data and ensuring its accuracy can be challenging. Incomplete or unclear clinical documentation can hinder accurate HCC coding.
- Lack of tools and shortage of medical coding resources: HCC coding becomes difficult when practices lack the tools to track diagnoses over time or generate accurate aggregate reports, making it harder to capture chronic conditions consistently. Adding to these challenges is the ongoing shortage of qualified medical coders and clinical staff, leaving organizations without the expertise needed to manage complex risk-adjusted coding requirements.
- Changes in patient health status: Chronic condition coding is inherently complex because many long-term diseases evolve over time, require ongoing management, and often coexist with multiple comorbidities. Accurate coding depends on:
- Precise documentation that reflects the patient’s current status—whether the condition is stable, worsening, or has developed complications
- Correct interpretation of nuanced clinical notes, following detailed ICD-10-CM guidelines, and ensuring that every chronic condition is captured annually for risk adjustment models.
- Specificity to map the diagnosis to the correct HCC category.
Complexity increases when chronic conditions overlap (e.g., diabetes with CKD, COPD with asthma) and when providers fail to document MEAT (monitoring, evaluation, assessment, and treatment) elements. Errors or omissions can lead to missed HCCs, inaccurate RAF scores, compliance risks, and lost reimbursement.
Due to these complexities, proper ICD-10 HCC mapping requires training and following best practices.
HCC Coding Best Practices to Optimize Chronic Condition Capture for Risk Adjustment
Here’s a step-by-step guide to navigating HCC coding complexity in clinical settings:
- Ensure strong documentation: Accurate HCC coding begins with clear, detailed documentation. Providers need to capture the full picture—medical history, chronic conditions, complications, treatments, and the care provided at each visit. Every diagnosis you report must be supported in the note.Best practice to ensure this is by using the M.E.A.T. criteria (Monitoring, Evaluation, Assessment, and Treatment). If a condition was truly addressed during the encounter, it should show up somewhere in M.E.A.T. form.
Note: A problem list, though helpful, will not justify a diagnosis unless the note shows how the provider evaluated or treated that condition that day.
- Re-capture chronic conditions every year: Chronic conditions do not automatically roll over in the risk-adjustment scenario—they must be reported every calendar year to count. The Annual Wellness Visit is a great time to update all active diagnoses. Preventive screenings, like depression or fall-risk assessments, often uncover new risk factors that also need to be coded.
- Code every condition that matters for that visit: Because HCCs are additive, it is important to capture all conditions addressed or impacting care—not just the chief complaint. If a chronic condition affects treatment decisions, medication management, or follow-up planning, it should be coded.Do not code conditions that no longer exist unless there is a status code available. History codes can still be used if they influence current care.
- Be as specific as possible: Specificity matters a lot in HCC coding. That means choosing codes that clearly describe:
- The type and underlying cause of the condition
- Severity
- Control level
- Site, location or laterality
- Any associated complications or comorbidities
- Substance use/exposure
Combination codes should be used when documentation supports them. It also important to consider coding notes like “code also” or “use additional code.”
- Use real-time reporting tools to stay ahead: Real-time reporting features in value-based programs can make a big difference. For instance, AI-powered medical coding services leverage advanced technologies like ML and NLP and skilled human coder review to automate and streamline coding workflows and identify and fix documentation gaps in real-time. By ensuring precise code assignment, they help providers capture HCCs and Risk Adjustment Factor (RAF) scores accurately and consistently. These tools help reduce delays between visits and coding, leading to better accuracy and more actionable insights.
Documenting Value-Driven Care: The Path Ahead
The shift to value-based care depends heavily on strong risk adjustment and accurate HCC coding. As value-based models expand, the focus will increasingly move toward efficiency, cost reduction, and better patient experiences. This will also drive wider adoption of outpatient CDI programs that prioritize precise HCC capture—ensuring that providers document and reflect the true complexity of each patient’s health.
Working with a medical coding company that leverages AI can help providers implement HCC coding best practices and accurately code chronic and high-risk conditions. In addition to appropriate, compliant reimbursement, strong HCC practices set the stage for improved patient outcomes and a more sustainable, data-driven healthcare system.
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