Using AI Based NLP To Address HCC Coding Accuracy And Risk Adjustment

The Hierarchical Condition Category (HCC) and the optimal Risk Adjustment Solution, as well as how precise coding influences healthcare organizations' compensation, have become topics of discussion in healthcare, particularly in the medical coding world.

As registration in Medicare Advantage plans evolves, healthcare organizations are required to anticipate future healthcare economic resources and provider compensation. CMS use the Hierarchical Condition Category (HCC) risk adjustment model for forecasting Medicare Advantage (MA) beneficiaries' expenses, and the estimates have a significant influence on the payment healthcare organizations get. The Risk Adjustment Solution is becoming more common as value-based financial services reach a wider audience.

HCC Coding

The HCC model provides each Medicare patient a Risk Adjustment Factor (RAF) as a predictor of potential costs, which is subsequently utilized alter capitation payments for patient populations participating in Medicare Advantage plans. Precise and reliable HCC coding and risk adjustment can have a substantial influence on economic stability and service delivery of healthcare institutions.

Healthcare companies that significantly improve their EMR, data, informatics, and skills training can deliver better reporting and tracking of on-time therapeutic treatment for chronically ill patients, resulting in more reliable HCC Coding and more appropriate remuneration for appropriate interventions, performance, and better care services. 

CMS HCC Model's Intricacies

HCC coding is not obvious, yet it is critical for healthcare organizations to obtain appropriate remuneration for their services. The following are some key points to understand regarding the CMS HCC model's intricacies and risk adjustment usages:

•  CMS mandates a visit and diagnosis by an APRN, PA, or clinician per calendar year.
• Patient records must be complete and accurate to support the diagnosis.
• Certain codes contain an RAF value. Some others do not. In most cases, increased severity does not enhance the risk adjustment factor (RAF).
• HCC codes are not always easy to understand. Clinicians may seek assistance in making decisions.
• Some HCC codes contain multipliers, while others are additive.
•  Payment in many Medicare contracts is affected by population complexity/severity.
•  RAF allows for patient registration and categorization.

NLP is Quite Useful

According to industry estimates, healthcare companies must now use solutions that allow access, storage, and retrieval of vital patient data held in unstructured information, which accounts for up to 80% of clinical health records.

Natural language processing (NLP) progressions offer enormous potential as a solution to this problem. NLP, which is becoming more widely acknowledged as a strong tool for decoding critical clinical information, converts text information into accessible data that can be evaluated and operated as per demand.