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Background & Problem Summary

The Hierarchical Condition Category (HCC) risk adjustment model, which assigns eligible beneficiaries a Risk Adjustment Factor (RAF) score based on their health and other life conditions, is used by CMS to estimate predicted costs for Medicare beneficiaries. As organizations increasingly participate in risk-adjusted payment models, they choose to focus on HCC coding for several reasons:

  • Issues with HCC coding are common. Most organizations struggle to provide correct coding and specific diagnoses. The challenge is compounded by the fact that HCC/RAF scores are reset every year, so they need ongoing attention to ensure they’re in sync with patients’ current realities.
  • HCC coding strongly influences the rate that CMS pays providers in many risk-adjusted payment models. Medicare Advantage and NextGen ACOs are two prominent examples of these arrangements.
  • The impact of not monitoring HCC/RAF scores can be significant. Because HCC/RAF scores are a major driver in provider reimbursements for population risk, even small changes in average score can result in millions of dollars of annual payments for a health system.

Accelerator Overview

Insight for success in value-based contracts—helping organizations ensure appropriate care and payment

The HCC Insights Analytic Accelerator enables healthcare provider groups to prioritize strategic initiatives to improve coding and better manage chronic diseases for Medicare patients. The application surfaces potential opportunities on an individual patient and provider/practice level and helps identify appropriate interventions. The tool supports organizations’ efforts to see and meet the true health needs of their patient populations—and to ensure the organization is getting reimbursed for the value it provides.

Benefits and Features

Identify opportunities to close gaps in patient care.

The application shows—at the system, practice, PCP, and individual level—potential care gaps by identifying patients who had high risk scores last year but currently do This allows you to identify patients who have not yet been in for appointments in the calendar year, provide necessary preventive or chronic condition care, and review and document ongoing risks.

Track coding trends to support improved precision, consistency, and completeness.

The application identifies providers who use a generic code for a condition where precise codes may be more accurate. It allows you to compare providers to others in the system, and to system average, to identify providers who are overusing a generic code and may need education. The application helps identify missed documentation as well. For example, because chronic conditions are sometimes not the primary reason for a visit, they may not show up on a patient’s billing history; to address this, the application lets you pick up on persistent conditions (such as amputations) that impact a patient and their needed level of care every year—and thus identify when these codes may be necessary to improve coding accuracy.

Use Cases

  • The Director of Care Management weaves use of the application into standard workflows to ensure that high-risk patients are contacted for preventive care, receiving appropriate level of care for the severity of their condition, and enrolled in the program as needed.
  • Assigned to monitor HCC codes, the population health data analyst identifies high variation in physician coding. She then works with the ACO leadership to prioritize the highest opportunities for improvement and direct the team to appropriate interventions.
  • The Director of Primary Care services uses the Accelerator to find providers who, compared to others in the system, are overusing generic diagnosis codes. He uses the data to support his conversations with select providers and to guide an internal education offering to improve diagnostic accuracy and specificity.
Key Measures

Gaps in care
Variation in coding practices