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HCC Risk Adjustment Coding / Audit

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HCC Risk Adjustment Coding / Audit

HCC

HCC coding relies on ICD-10-CM coding to assign risk scores to patients. Each HCC is mapped to an ICD-10-CM code. Along with demographic factors such as age and gender, insurance companies use HCC coding to assign patients a risk adjustment factor (RAF) score. Using algorithms, insurance companies can use a patient’s RAF score to predict costs.
Hierarchical Condition Category Coding
Hierarchical condition category (HCC) coding is a risk-adjustment model originally designed to estimate future health care costs for patients. The Centers for Medicare & Medicaid Services (CMS) HCC model was initiated in 2004 and is becoming increasingly prevalent as the environment shifts to value-based payment models.

HCC coding important?

Hierarchical condition category coding helps communicate patient complexity and paint a picture of the whole patient. In addition to helping predict health care resource utilization, RAF scores are used to risk adjust quality and cost metrics. By accounting for differences in patient complexity, quality and cost performance can be more appropriately measured.
HCC coding relies on ICD-10-CM coding to assign risk scores to patients. Each HCC is mapped to an ICD-10-CM code. Along with demographic factors such as age and gender, insurance companies use HCC coding to assign patients a risk adjustment factor (RAF) score. Using algorithms, insurance companies can use a patient’s RAF score to predict costs. For example, a patient with few serious health conditions could be expected to have average medical costs for a given time. However, a patient with multiple chronic conditions would be expected to have higher health care utilization and costs.

Risk Adjustment and Value-Based Payment

Risk adjustment can play an important role in payment, and this is particularly true in value-based payment (VBP). VBP arrangements use a practice’s performance on cost and quality metrics to determine revenue, which means risk adjustment can have a direct impact on a practice’s revenue. When risk scores do not accurately reflect patient complexity, it may appear patients had higher costs and/or lower quality outcomes than would be expected. In certain payment models, this may cause a practice to fall below quality and cost performance targets and potentially miss out on the opportunity for shared savings.
In other models, such as capitation, a practice’s payment rate may be based on a patient or practice’s average risk score. For example, in Primary Care First, the population-based payment (PBP) is calculated using the average RAF of the practice’s attributed beneficiaries. Practices with more complex patients, based on RAF scores, receive a higher PBP as it is expected their patients will require more resources and have higher utilization.

Reminders for HCC coding

  • Risk adjustment scores reset every year. Practices need to report active diagnoses annually, even chronic conditions. The annual wellness visit is a good opportunity to capture all appropriate diagnoses. Preventive screenings, such as screening of risk factors for depression, aid in identifying additional diagnoses that contribute to a patient’s risk.
  • HCCs are additive, so it is important to code all conditions that coexist at the time of the encounter or affect patient care or treatment.
  • Conditions that were previously treated and no longer exist should not be coded. History codes may be used as secondary codes if the condition or family history impacts current care or influences treatment.
  • Documentation must support the diagnoses reported. A good rule of thumb is to document to the MEAT principles: a diagnosis should be monitored, evaluated, assessed, or treated (MEAT). Diagnoses that are not supported by documentation will not be upheld in the event of an audit. Coding should comply with the ICD-10-CM coding guidelines.
  • The medical record must contain a legible signature with credentials.

HCC

Hierarchical condition category (HCC) coding is a risk-adjustment model originally designed to estimate future health care costs for patients.