CMS uses all the data captured and logged through HCC codes to determine the CMS-HCC risk score for a patient. This numeric indicator is based on weighted factors and data points, including medical histories, diagnoses, demographics, and other information about the patient.
This process necessitates highly accurate and precise healthcare records, along with reliable and consistent procedures to avoid gaps in HCC coding that can inadvertently lower a patient’s adjusted risk score–meaning reduced reimbursement rates and potentially impacting patient care.
A risk score of 1.0 is the baseline, where this score would be considered a healthy patient. Scores of less than 1.0 mean a reduced anticipated cost of care and a lower reimbursement rate for the healthcare provider.
How Does HCC Coding Contribute to Risk Adjustment Scoring?
HCC coding is part of a risk-adjustment model, which calculates the expected future costs of providing healthcare and treatment services. This value-based healthcare reimbursement system was introduced in 2004.
The process depends on a risk adjustment coder working on behalf of healthcare providers logging ICD-10-CM codes mapped to the corresponding HCC category. Payers, whether insurance providers or Medicare, use that data along with factors, such as the patient’s age, location, and gender, to anticipate the costs of providing ongoing care.
Risk Adjustment Factor (RAF) scores can provide a better idea of the ongoing reimbursement rates associated with a patient by recognizing the presence of multiple diseases, diagnoses, or chronic conditions that mean a patient is more likely to require a higher utilization of healthcare services–and therefore a higher cost to the provider.
The role of HCC coding is to communicate the complexities of providing patient care rather than linking individual conditions with one reimbursement rate, where the presence of multiple other diagnoses may portray a very different picture.
Risk Adjustment Calculations in Value-Based Healthcare Reimbursements
Value-based payments are made by measuring the performance of a healthcare provider against cost and quality benchmarks. Risk adjustments can directly affect reimbursement rates, where an inaccurate score may mean that a provider appears to have incurred higher costs or delivered lower outcomes than anticipated.
An RAF score used in CMS modeling dictates the amount paid to the health plan for each beneficiary within a payment year, with higher rates paid to providers managing the health of patients with multiple or more complex conditions or more serious diagnoses.
HCC Risk Score Calculations
RAF scores are calculated based on multiple data points, including:
- Disease risks: Reliant on reported diagnoses via HCC coding
- Disability status, age, and gender
- Place of residence, such as a healthcare institution, nursing center, or within the community
We’ve mentioned that a low RAF score will typically indicate a healthy patient without higher projected ongoing treatment costs, but this can be due to HCC coding gaps.
How Will CMS-HCC Version 28 Impact Risk Scoring?
The CMS is due to introduce a new HCC model, called Version 28 (v28), in 2024, which will affect RAF scoring for a significant proportion of beneficiaries enrolled in Medicare Advantage. The changes will impact risk scoring and reimbursements due to a higher number of HCC codes, differences in the numbering and names of v28 HCC codes, variations in ICD-10-CM code mapping, and adjusted coefficient values.
According to the AAPC, more than 2,200 codes will be removed, while 268 codes will be introduced that did not correspond to a CMS-HCC payment within the previous v24. There is the potential, as recognized by the CMS, that some reforms could impact RAF scoring for Medicare beneficiaries even without a corresponding change to the patient’s health status.
The CMS has stated that the newer model will deliver more appropriate weighting for HCCs as they better reflect expenditure, coding, and utilization patterns, but healthcare providers should be conscious of the changes and how this may affect their patient risk scoring and reimbursements over the transition period.