HCC Coding Compliance Best Practices

HCC Coding Compliance

Coding and auditing errors can greatly impact your organization’s revenue cycle. This is especially the case with Hierarchical Condition Category (HCC) risk adjusted payers under Medicare Advantage and the Affordable Care Act.

Hospital and clinical coding staff, including managers, directors, auditors, CDI staff, clinicians and coding compliance and privacy staff: You need to be able to identify key components in the auditing of HCCs. Being alert to ways to improve your clinical documentation should include:

  • Performing an accurate, comprehensive, annual assessment for each beneficiary
  • Reporting chronic conditions, like diabetes, annually
  • Documenting co-existing acute conditions, active status conditions, pertinent past conditions, and current medications
  • Providing specific, rather than general information, and documenting the highest level of specificity


A Brief Background of HCC

HCC is a risk adjustment model set by the Centers for Medicare & Medicaid Service (CMS). In short, it’s a method used to calculate risk scores based on members’ chronic and cumulative conditions and prior health status. Diagnosis data pulled from medical records and demographics helps formulate the risk scores, which then determine payments for members enrolled in Medicare Advantage (MA) plans.

The complexity with HCC compliance is that the number of HCCs and corresponding ICD-10 codes change frequently, greatly impacting coding and auditing. On top of that, there are approximately 87 risk score categories that map to over 3000 ICD-10 codes. These ICD codes both determine medical necessity and validate CMS payments, so complete and accurate coding is critical. As a medical biller or coder, it’s crucial that you understand and keep up with coding updates and regulatory directives that impact HCCs coding and auditing.


Avoid These Risk Adjustment Pitfalls

Not only must you know how to accurately identify HCCs in coding and auditing, but you also need to analyze quality documentation and improve your query process with HCCs. As you strive to maintain HCC coding and auditing best practices, it helps to start with a benchmark. The AAPC’s “Top 10 Medicare Risk Adjustment Coding Errors” include:

  1. Health record does not have a legible signature with credentials
  2. Electronic health record was not authenticated and electronically signed
  3. Highest degree of specificity was not assigned to diagnosis
  4. A discrepancy exists between billed diagnosis and actual description of the condition noted in documentation
  5. Documentation does not indicate a condition as being monitored, evaluated, assessed, or treated
  6. Cancer status is unclear and treatment is not documented
  7. Chronic conditions such as hepatitis are not documented as chronic
  8. Lack of specificity is an issue, such as unspecified arrhythmia versus a specific type of arrhythmia
  9. Chronic conditions and status codes are not documented on an annual basis
  10. Required linking language, causal relationship, or manifestation codes are missing


Learn from others’ mistakes—make sure you’re not making these same blunders, and secure accurate reimbursements for your practice!


Brush Up Your HCC Compliance Know-How

Expert coding specialist Victoria M. Hernandez reviews HCC coding and auditing best practices in an audio conference for ProfEdOnDemand, “HCC Coding: Compliance, Audits and Documentation.” In this session, Hernandez covers coding guidelines and references that impact HCCs. Promoting compliance and quality clinical documentation, she reviews cases and identifies key areas where coding and auditing errors may be prevented.

To join the conference or see a replay, order a DVD or transcript, or read more

One Comment

  1. Thanks for sharing the great knowledge of hcc coding. Risk Adjustment and HCC coding is a payment model mandated by the
    Centers for Medicare and Medicaid Services(CMS) in 1997. It is integrated with multiple EHRs and through the integration it can receive the patient data in real time , analyze it against intelligent rules and suggest HCC codes, within seconds.

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