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Hierarchical Condition Category (HCC) Codes for All

Hierarchical Condition Category (HCC) Codes for All

By Michele Caravan

Patient health risk status and risk adjustment is one of many value-based care factors (including cost, utilization, and patient satisfaction) that are driving new models of physician/provider payments.  Payers are now utilizing Hierarchical Condition Category (HCC) codes to assess the severity of illness (risk) of patient panels. Selecting ICD-10 codes that align to HCCs will provide the most accurate status of patient health status and potentially have a positive impact on payment from all payers – Medicare Advantage, CMS alternative payment models, along with commercial health plans (capitation) and commercial health insurance exchanges.

CMS developed HCCs to pay Medicare Advantage organizations differentially based on disease burden and demographics.  Some commercial payers utilize proprietary risk adjustment models, but HCCs are the dominant choice.  CMS uses two models:

  • CMS-HCC is used to pay Medicare Advantage organization
  • HHS-HCC was developed after passage of the Affordable Care Act to pay health insurers in the ACA marketplace. Included categories are infants, children, and all age adults while including obstetrical diagnosis codes for high-risk OB care.  This framework provides a platform to drive physician/provider performance across all payers and all patients regardless of age.

HCC risk scoring forecasts the cost of care for patients with chronic conditions.  Risk Factor scoring is a methodology used to assess health risk/acuity using a numerical relational scale.   Risk Adjustment Factor (RAF) is the final scoring calculation assigned to a patient to assess risk, resulting in a payment calculation.  If ICD-10 codes are not coded correctly and HCCs underrepresent the patient’s actual disease burden, reimbursement will be lower and quality benchmarks will be more difficult to achieve in share savings programs.

Critical factors for success with risk-adjustment coding:

  • Real time, point of care insights: These not only identify the diagnosis codes that describe why the patient was seen, but also codes for any chronic conditions that affected treatment choices.
  • Specificity: If a patient presents with a serious chronic condition with a complication that has its own code, the provider should use the more specific code rather than an unspecified code to capture the patient’s true disease burden and impact the Risk Adjusted Factor (RAF) score.
  • Capturing and reporting chronic diagnosis codes annually: Risk scores reset each year and it is critical to report a patient’s qualifying diagnosis every year.  A real time list of unconfirmed diagnoses at the time of the patient’s appointment to empower the provide with the ability to resolve and confirm those diagnoses.  To drive performance a real time dashboard showing the providers personal confirmation rate as well as their ranking among their peers.

Real time, point of care analytics and insights provide an organization with a single source of truth for coding guidance.  In addition to a real time dashboard at the provider and patient level, a management dashboard that provides overall rate of physician/provider confirmation of chronic diagnoses, utilization of unspecified chronic diagnoses as well as an indication of high and low performers within the provider group.  This allows for recognition of best practices and enables the efficient allocation of CDI resources to address low performers.