In this white paper, Tony Kollarmalil, Medical Director, explores the significance of Risk Adjustment Factor (RAF) scores in predicting healthcare costs for beneficiaries, particularly in the context of CMS transitioning from Version 24 to Version 28. The paper emphasizes the need for organizations to adapt to these changes by implementing a blended approach for data collection and ensuring accurate severity of illness capture through recapture processes, prospective reviews, and education initiatives.
Please click on the video to the right to learn more about the author, hear his insights on this white paper, and learn what motivated him to write about the new V28 model of risk adjustment.
To discuss this white paper in detail, please contact Tony using the information provided at the bottom of the page.
Risk Adjustment Factor (RAF) scores are the essential component of the model used by the Centers for Medicare & Medicaid Services (CMS) to predict costs for beneficiaries in various risk adjustment models. A higher rate is paid for sicker patients who have multiple conditions and conditions with greater severity, as the predicted cost of care will be higher. A component of the RAF score is based on the reported diagnoses from patient encounters. The diseases are mapped to Hierarchical Condition Categories (HCC) and assigned coefficient values.
The methodology predicts that a higher RAF score indicates a sicker patient, while a lower RAF score indicates a healthier patient. The other component of RAF is a demographic coefficient assigned by CMS. The coefficients have mostly remained the same for several years with adjustments to account for expenditure.
On March 31, 2023, Health and Human Services (HHS) announced the most significant changes yet to the Medicare Risk Adjustment Model named Version (V28).
These sweeping changes transitioning from version 24 (V24) to V28 include significant changes to HCC codes, disease mappings, and impacts on RAF scores. Some of these changes include an increased number of HCCs by 29 for a total of 115 HCCs, changes to HCC coefficient values, deletion of 2,294 diagnosis codes, addition of 268 diagnosis codes that did not map to HCCs in the V24 model.
Even though V28 increases HCCs by 268 new ICD-10 CM codes, 40% of the new codes are reflective of diagnoses not found in the Medicare population.
These changes included an estimated increase of 3.32% increase in payments to Medicare Advantage (MA) plans, which is approximately $13.8 billion in 2024. The US healthcare system transitioned to ICD-10 CM diagnosis code set in 2015.
CMS has mapped HCCs according to ICD-9 CM (previous diagnosis code set). To account for the new system, CMS built new HCCs by reviewing diagnoses and determining the best grouping. CMS also took into consideration more recent expenditure on beneficiaries The updates were developed to move from 2014 diagnosis data and 2015 fee-for-service expenditure data, restructuring condition categories using ICD-10 codes to align with 2018 diagnosis data and 2019 fee-for-service expenditure data.
| HCC differences between the V24 & V28 CMS HCC models | ||
|---|---|---|
| ICD codes | ICD-9 CM | ICD-10 CM |
| FFS Data | 2014-2015 | 2018-2019 |
| ICD-10 CM HCC diagnoses | 9797 | 7770 |
| HCC categories | 86 | 115 |
| ICD-10 CM HCC deletions | 2294 | |
| ICD-10 CM HCC additions | 268 | |
According to CMS, this new model will be phased in over the next three years in a blended model. For the 2023 data collection, the blend will include 33% of the V28 model and 67% from the prior V24 model. For 2024, the blend will be 67% of V28 and, finally, for the 2025 data collection year, the V28 model will be fully phased in at 100%. This blended approach means organizations are expected to start diagnosis capture using V24, as well as the V28 model starting January 1st, 2023.
CMS projects that the impact of the new model will reduce risk scores by 3.12% resulting in net savings of $11 billion to the Medicare Trust Fund in 2024. These changes will impact a large percentage of Medicare beneficiaries primarily those in Medicare Advantage (MA) plans. 48% of Medicare beneficiaries are in MA plans as of January 2023. This accounts for approximately 30.7 million people. In the new V28 model, according to CMS the elimination or constraint in the coefficients is largely due to the concern that these diagnoses have been intentionally or unintentionally the target of focused reviews by Medicare Advantage plans. CMS has stated that these changes will support the integrity of Medicare risk-based payments to MA plans which have ballooned in recent years.
Some examples of common diagnoses that are eliminated in the V28 model include acute kidney failure, angina pectoris, atherosclerosis of the extremities, protein-calorie malnutrition, and amputation of a toe. The recalculation of coefficients most negatively impacts patients with diabetes. In the past diabetic patients have been categorized by the absence or presence of diabetic complications or acute presentation of disease. The V28 model has constrained the hierarchical categorization of diabetes by combining the various presentation of diabetes in a singular category & reducing the coefficient by almost half from 0.302 to 0.166.
Some analyses predict these changes could negatively affect primary care physicians and those treating disadvantaged MA patients. These physicians could end up with less funds to treat these patients. For example, risk-adjusted payments will be reduced by two-thirds for patients with diabetes. This drastic change is illustrated in the table below.
|
V24 Coefficients |
|
|
V28 Coefficients |
|
|
|
|
Community, Non-Dual, Aged Beneficiary |
Age 70-74 years |
|
Community, Non-Dual, Aged Beneficiary |
Age 70-74 years |
|
|
|
HCC18/HCC108 |
Diabetes with PVD |
0.302 + 0.288 |
|
HCC37 |
Diabetes with PVD |
0.166 |
|
HCC189 |
Amputation of Toe |
0.519 |
|
No mapping |
Amputation of Toe |
N/A |
|
HCC score based on disease coefficients |
|
1.109 |
|
|
|
0.166 |
The specificity of documentation and diagnostic coding have always been essential for accurate risk adjustment. HCC model V28 will require even greater specificity in documentation and code assignment to ensure that the true level of your Medicare Advantage patients’ illness severity is captured.
As indicated earlier, a higher RAF score can indicate a sicker patient, but a lower RAF score does not necessarily indicate a healthier patient. A low score could be an indicator of a gap in care or incorrect & inaccurate coding.
Ensure that they have in place an effective recapture process. HCC codes must be addressed every 12 months. If the diagnosis is not recaptured (submitted on a claim) every 12 months, it is eliminated from the patients which results in a lower risk score that in turn leads to a lower payment. Providers must be educated on the importance of recapture. A standard goal is an 85% recapture rate. Not only is recapture important from a statistical point of view as a reconfirmation process, but it also ensures that the diagnoses are regularly addressed to identify disease progression and/or resulting comorbidities.
Prospective reviews & pre-visit planning help identify conditions that have not been addressed or net new diagnoses. This process ensures an accurate clinical picture of the patient as well as the assignment of accurate RAF scores for payment purposes. Organizations are having to adapt to these drastic changes by continuing their current HCC coding process with a bigger emphasis on provider education, prospective reviews & better point of care diagnosis code capture.
Vee Healthtek has several years of experience providing HCC coding services, having coded several million charts. Prospective clinical reviews for suspect HCC diagnoses are done by clinically trained staff. Our provider peer-to-peer education with an HCC disease-focused curriculum is conducted by expert staff. We have already implemented V28 across our existing customers and can be your valued partner to help you achieve optimal RAF accuracy and deliver extraordinary outcomes for your organization.
www.cms.gov/files/document/2024-announcement-pdf.pdf
www.medpac.gov/wp-content/uploads/2023/03/Mar2023_MA_C_AND_D_CY-2024_MedPAC_COMMENT_v2_SEC.pdf
www.apg.org/wp-content/uploads/2023/03/CY2024-HCC-Proposed-Model-Impact-Analysis-3.3.2023.pdf
https://healthpayerintelligence.com/news/how-2023-medicare-advantage-enrollment-growth-has-shifted#:~:text=Between%202019%20and%202023%2C%20Medicare,2.7%20million%20beneficiaries%20in%202023.
