NLP and HCC Coding are Essential For Today’s Risk Adjustment Solution

Medicare Advantage (MA) has proven to be successful in giving Medicare beneficiaries the healthcare alternatives that are tailored to their specific requirements. The MA system offers the advantages for private healthcare sector innovation and growth to a government plan, and Centers for Medicare & Medicaid Services’ (CMS) is dedicated to bolstering MA by supporting increased innovation, accountability, adaptability, and application clarity.

Risk Adjustment Solution helps in the statistical technique for forecasting a person's likelihood of using and paying for healthcare services. It's utilized in Medicare Advantage to modify the government's fee for service reimbursement to cover participants' predicted healthcare spending.

As we have approached 2022, various studies and data analysis will be able to adequately facilitate healthcare professionals to know the open care gaps for preemptive closing, and even provide insurer agnostic data to assist diagnostic, performance, and Risk Adjustment (RA) plans for improved efficiency, risk adjustment scores, and patient outcomes.

The Importance of Risk Adjustment Solution 

The efficient and reliable Risk Adjustment Solution for Healthcare Plans employs the most up-to-date technologies to enhance predictive analytics, gather specified but unaccounted for chronic conditions, find patient records with the best possible chance of producing additional coverage, and depict the true cost of the participant group.

Model of CMS-HCC Coding

CMS uses Hierarchical Condition Category (HCC Coding) to pay Medicare Advantage plans based on the health of its subscribers. It compensates for patients' anticipated cost expenditure by altering payments associated with socioeconomic indicators and individual health history.

By using HCC Coding, the risk adjustment discovers patients who require therapeutic intervention and determines the monetary care offered by CMS for each individual's annual care. The Risk Adjustment Factor (RAF) is calculated using each unique diagnosis, and the ranking is used to assess not just insurer reimbursement but also prospective future expenses associated with every patient. All diagnoses that impact the patient's evaluation, treatment, and remedial actions, such as co-existing chronic diseases and comorbidities, must be submitted for HCC Coding to be successful.

Natural Language Processing (NLP) is Needed for Risk Adjustment  

Health insurance providers can use an NLP-assisted coding system to effectively and quickly risk classify its subscribers, focusing those with the most misdiagnosed conditions and the highest proportion of claimed codebase without references. The NLP-assisted risk categorization provides a lot of value since it allows practitioners to start with the important individuals and work their way down the priority list.

By improving scanning, compiling, and intelligent data retrieval, NLP software can help accelerate the database recovery. It aids in the elimination or reduction of chart searching issues, as well as improve productivity, expense, and frustration on both sides.