Capturing HCCs in a Changing World

Amy C. Pritchett, CCS, CRC, CPA-RA, CPC, CPMA, CPCO, CDEI, CDEO, CDEC, CANPC, CASCC, CMPM
Manager, HCC Coding/Audit & Education Services, Pinnacle Enterprise Risk Consulting Services
AAPC Fellow |Approved Instructor |ICD-10-CM/PCS Trainer

On March 31, 2023, the Centers for Medicare and Medicaid Services (CMS) released the CY 2024 Medicare Advantage (MA) Capitation Rates along with Part C and Part D payment policies. The largest key decision in the release was the finalized proposal to revise the Medicare Advantage Risk Adjustment model. The finalized memorandum noted that CMS would be phasing the new model (version 24 to version 28) beginning in 2024 and fully phasing at the beginning of 2026.

Unfortunately, lost in translation was the fact that the phase-in actually began with the CY 2023 release of the ICD-10-CM diagnosis code updates (October 1, 2023). There are common misconceptions from providers and organizations that they have three years to comply, and that is simply not the case. Accountable Care Organizations (ACOs) are paid retrospectively for their shared savings from the prior year. This means that the blended risk scores for CY 2023 will be paid in CY 2024. To everyone’s surprise, CMS has been utilizing the new blended model for CY 2024, which is 33% of the version 28 methodology and 67% of the version 24 methodology.

When utilizing the new calculation methods for risk adjustment scores, numerous changes were made for CY 2024. The changes included the addition of constraints and removing numerous HCCs that carried a Risk Adjustment Factor (RAF) in version 24. Since 2014, version 24 has been calculated using the ICD-9-CM coding system. One of the major changes of version 28 is that the model will now utilize data from ICD-10-CM methodology utilizing 2018-2019 data for expenditures.

You may still be asking yourself, “How does this affect me in CY 2023?” The answer is simple! Under the revised model, CMS is constraining (i.e., applying equal coefficients) within the values of all diabetes HCCs (36, 37, and 38). There were 29 new HCC categories added to the new model; however, there were 2,264 diagnosis code deletions. As discussed above, diabetes mellitus with chronic complications was one of the largest changes for CY 2023. With the deletion of 80 diagnosis codes, considering all coefficients equal regardless of complication or status, and the lowering of RAF scores, ACOs are going to see a shift in shared savings for CY 2024 retrospective payments.

Below, we will be looking at the upcoming changes for diabetes mellitus for Version 28 and how the changes will affect reimbursement under the new version 28 model.

V24 HCC Coefficients			V28 HCC Coefficients
Community Non-Dual, Aged Beneficiary	Age 70-74	RAF Score		Community Non-Dual, Aged Beneficiary	Age 70-74	RAF Score
HCC 21	PCM*	0.455		No HCC Assigned	PCM*	0.00
HCC 96	Atrial Fibrillation	0.268		HCC 238	Atrial Fibrillation	0.299
HCC 18/108	Diabetes w/ PVD	0.302 + 0.288		HCC 37	DM w/ PVD	0.166
HCC 85	Chronic Systolic CHF	0.331		HCC 226	Chronic Systolic CHF	0.360
HCC 189	Amputation of toe	0.519		No HCC Assigned	Amputation of Toe	0.00
Disease Interaction	Diabetes + CHF	0.121		Disease Interaction	Diabetes + CHF	0.112
Disease Interaction	CHF + AFib	0.085		Disease Interaction	CHF + Afib	0.077
6 HCCs	Condition Count Factor	0.077		4 HCCs (Condition Count Factor	No RAF Score	0.00
Total V24 Disease Coefficient Risk Score		2.446		Total V28 Disease Coefficient Risk Score		1.014

*Protein Calorie Malnutrition

As you can see in the example, the same diagnosis codes with complications, disease interactions, and HCC counts are significantly decreased in the V28 model.

What should you do?

Partner with your stakeholders and physicians to review changes already in effect.
Analyze benchmarks and review current population prevalence of chronic conditions.
Review provider performance of capturing HCCs and review documentation for education needs.
Capture data reporting and analyze how the change will affect your shared savings.
Get the right tools (i.e., update monthly accurate predictions, understand your population and the rates based on the track of high and low utilization across member populations).

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