CMS-HCC, RxHCC, and HHS-HCC each forecast the healthcare costs a member is likely to incur, and those forecasts flow directly into capitation payments for Medicare Advantage, Medicare Part D, and the Affordable Care Act marketplaces. CMS uses three separate frameworks, CMS-HCC for Medicare Advantage, RxHCC for Part D drug plans, and HHS-HCC for ACA marketplace plans, because a single score cannot capture the wildly different cost drivers of seniors on Medicare, pharmacy-only enrollees, and commercial marketplace members. A diagnosis that triggers a high weight under one model can drop to zero under another, so picking the right framework is where payment accuracy begins.
This breakdown unpacks the three CMS risk adjustment frameworks side by side, comparing how CMS-HCC, RxHCC, and HHS-HCC score diagnoses, calibrate spending, and shape capitation for Medicare Advantage, Part D, and ACA plans.
Why One Risk Score Is Never Enough
Risk adjustment exists to stop payers from being punished for enrolling sicker members. The Centers for Medicare and Medicaid Services pays Medicare Advantage contracts a monthly capitation rate for each enrollee, and that rate is multiplied by a risk score derived from diagnosis and demographic data. Without this adjustment, plans would compete for healthy members and avoid high-cost patients, leaving the most vulnerable people without coverage options.
Every model produces a normalized risk score, and 1.0 is the anchor. A member with a score of 1.0 represents average expected spending for the population being measured. Scores above 1.0 pull in higher capitation, scores below 1.0 pull in less, and the gap between a 0.7 and a 1.4 member can mean thousands of dollars per year in payment.
Three populations drive the need for three models. Seniors on Medicare carry chronic disease burdens and long diagnostic histories that diagnosis-based hierarchical condition categories capture well. Part D enrollees often have no reliable diagnosis data, so pharmacy claims become the proxy. ACA marketplace members span working-age adults, children, and infants, with cost patterns that don’t map cleanly onto a Medicare framework. Forcing one universal model across all three would systematically underpay or overpay for the underlying illness burden, which is exactly what the separate frameworks were built to prevent.
CMS-HCC and the Architecture of Medicare Advantage Payment
Capitation dollars for roughly 30 million Medicare Advantage members run through the CMS-HCC framework, making it the largest risk-adjustment engine by payment volume in U.S. healthcare. Every January, plans submit the prior calendar year’s diagnosis codes from inpatient, outpatient, and physician encounters, and CMS maps those ICD-10-CM codes into hierarchical condition categories. Each HCC carries a coefficient representing its relative cost contribution, and hierarchies ensure that only the highest-weighted related condition in a disease family is counted, so a member with both uncomplicated diabetes and diabetes with chronic complications pulls in only the higher weight.
How a Raw Risk Score Becomes Capitation
An enrollee’s age, sex, dual-eligible status, and whether they live in an institution are layered on top of their HCC weights to assemble the raw risk score that payers normalize each year. CMS then normalizes that score by plan and contract, which means the average enrollee in each contract lands at 1.0 after normalization. The normalized score is multiplied against the base capitation rate to produce the actual monthly payment.
Annual recalibrations shift both the coefficients and the normalization factors. The most significant recent shift is the phase-in of the v28 model, which tightened the hierarchy structure, removed several higher-weighted HCCs, and reset demographic factors. A weight that produced $1,200 in capitation under v24 may produce $900 under v28, so any plan relying on stale coefficients will misjudge revenue projections. Predictive ratio and R-squared statistics measure how well the model explains actual spending, and CMS tracks these metrics across years to justify each recalibration.
Annual CMS recalibrations are not optional adjustments. A diagnosis-to-weight map from one payment year cannot be assumed valid for the next, and revenue forecasts built on outdated coefficients are the first place audit exposure creeps in.
RxHCC and the Pharmacy-Only Lens for Part D
The RxHCC model was built specifically for Medicare Part D prescription drug plans, where diagnosis data is often missing or unreliable. Instead of ICD-10-CM codes, RxHCC pulls National Drug Codes from pharmacy claims and clusters them into clinically meaningful groups that proxy for underlying conditions. A member filling metformin and a sulfonylurea lands in the diabetes cluster, even if no diabetes diagnosis code was ever submitted.
Drug-Disease Interactions and Why They Matter
RxHCC includes interaction terms that adjust the score upward when a member takes medications suggesting multiple co-existing conditions. A patient filling both an HIV antiretroviral and a statin pulls a higher weight than the simple sum of the two clusters would suggest, because the combination signals greater clinical complexity. These interaction factors are one of the most underappreciated parts of the model and the source of meaningful payment variation between Part D plans with superficially similar populations.
The same ICD-10 code that maps to a high-weighted HCC under CMS-HCC produces zero weight under RxHCC, because diagnoses are excluded entirely from the input set. That mismatch becomes a real liability for MA-PD contracts that span both models, because auditors increasingly test whether submitted diagnoses map to plausible pharmacy patterns. A chart full of high-weighted CMS-HCC diagnoses with no supporting pharmacy activity raises red flags, even if the diagnoses are technically accurate.
| Feature | CMS-HCC | RxHCC |
|---|---|---|
| Primary input | ICD-10-CM diagnosis codes | National Drug Code pharmacy claims |
| Population served | Medicare Advantage | Medicare Part D |
| Hierarchy rules | Disease-family hierarchies, highest weight wins | Drug-cluster interactions and complexity factors |
| Payment use | Medicare Advantage capitation | Part D direct subsidy and reinsurance |
| Recalibration cycle | Annual CMS update (v28 phase-in) | Annual CMS update alongside CMS-HCC |
HHS-HCC and How the ACA Marketplace Recalibrates the Formula
The HHS-HCC model runs the individual and small-group ACA marketplaces, where the federal risk-adjustment program transfers funds from insurers with lower-risk enrollees to those with higher-risk enrollees. The transfer formula uses risk scores built from the same kind of diagnosis-to-HCC mapping that drives Medicare Advantage, but the population, weights, and payment logic differ in ways that catch even experienced teams off guard.
Adults, Children, and Infants Use Different Logic
Adults in the ACA marketplace are scored on age, sex, and diagnosis-based HCCs drawn from the HHS-specific hierarchy. Children use a separate pediatric model that weights diagnoses differently and includes additional factors for low birth weight and chronic pediatric conditions. Infants under age one receive maternity-infant adjusters instead of diagnosis hierarchies, because diagnostic coding is sparse in the first year of life and cost variation is driven mostly by delivery and newborn care.
Metal-tier premiums and induced demand factors mean the same diagnosis carries a different effective weight under HHS-HCC than it does under CMS-HCC. Bronze, silver, gold, and platinum plans have different cost-sharing structures, and enrollees respond by using more or less care, which the model must adjust for. Partial-year and new-enrollee factors also carry more weight in payment accuracy than they do in steadier Medicare populations, because ACA enrollment churn is high and many members have only a few months of claims history.
Side-by-Side Mechanics Across the Three Models
The clearest way to keep these frameworks straight is to line them up on the dimensions that drive payment. The table below compares the three on population, inputs, hierarchy logic, and payment use, with a focus on the points where model selection errors actually distort revenue.
| Dimension | CMS-HCC | RxHCC | HHS-HCC |
|---|---|---|---|
| Population | Medicare Advantage seniors and dual-eligibles | Part D drug plan enrollees | ACA marketplace adults and children (some Medicaid expansions) |
| Input data | ICD-10-CM diagnoses from prior calendar year | NDC pharmacy claims from the payment year | ICD-10-CM diagnoses, with pediatric and infant adjusters |
| Hierarchy logic | Disease-family hierarchies; highest weight wins | Drug-cluster interactions and complexity terms | Disease-family hierarchies with metal-tier and induced-demand adjustments |
| Payment use | Medicare Advantage capitation | Part D direct subsidy and reinsurance | ACA marketplace risk transfers and (in adopted states) Medicaid managed care capitation |
| Notable phase-in | v28 model recalibration | Annual recalibration tied to CMS-HCC cycle | 2017 and 2024 recalibrations incorporating ICD-10 updates |
One detail that frequently trips up newer analysts is that the Medicare Shared Savings Program (MSSP) uses a blended CMS-HCC model that weights the current payment-year model and the prior payment-year model together during phase-ins. If your ACO participates in MSSP, the risk score feeding your benchmark is not the same number that flows to a Medicare Advantage contract, even when both populations look superficially similar.
Practical Selection, Coding Traps, and Audit Defense
Selecting the wrong model is the single fastest way to distort capitation revenue. Running CMS-HCC weights on a Part D-only population, or HHS-HCC weights on a Medicare Advantage contract, produces scores that have no relationship to the actual payment formula, and the error compounds across every member in the affected contract. For a mid-size plan with 50,000 members, a misapplied model can shift revenue projections by tens of millions of dollars per year.
Coding Traps That Quietly Deflate Risk Scores
Speculative diagnoses not yet confirmed by the treating clinician are the most common coding trap. A chart note that lists “rule out diabetes” or “possible COPD” cannot be submitted for risk adjustment, because the diagnosis was never established. Missed HCCs for secondary conditions run a close second, a patient with diabetes who also has chronic kidney disease should pull the higher-weighted complication HCC, but many submissions only capture the primary diabetes code. Failure to recapture diagnoses from acceptable encounter types during the data-collection window is a third frequent miss, especially for members who see specialists outside the primary care network.
Auditors now test whether submitted diagnoses map to plausible pharmacy patterns under RxHCC, which makes clinical-pharmacy alignment a defensibility requirement rather than an optional improvement. A chart full of high-weighted CMS-HCC diagnoses with no corresponding pharmacy activity for the implied conditions will trigger a documentation request, even when every individual code is technically accurate.
Building an Internal Model Matrix
The cleanest defense is a matrix that ties each contract type, line of business, and population segment to its correct model version and recalibration year. The matrix should specify which HCC mapping logic applies, which normalization factor to use, and which recalibration year the weights come from. When that matrix is updated within 30 days of any CMS or HHS recalibration announcement, your submissions never rely on stale weights, and your revenue projections can be defended line by line at audit.
- Confirm population fit: Verify which model applies to each contract before running any risk score.
- Lock the recalibration year: Document which model version and normalization factor each payment year uses.
- Audit diagnosis-pharmacy alignment: Cross-check submitted CMS-HCC codes against RxHCC pharmacy patterns for MA-PD contracts.
- Recapture secondary HCCs: Review charts for complications and comorbidities that should map to higher-weighted categories.
- Exclude speculative diagnoses: Submit only confirmed conditions documented by the treating clinician.
- Track partial-year factors: Apply new-enrollee and mid-year enrollee adjusters correctly in high-churn populations.
The Medicare Shared Savings Program is the edge case most teams miss. ACOs participating in MSSP use a blended risk score that combines the current and prior payment-year CMS-HCC models, and the blend ratio shifts during phase-ins. Treating an MSSP benchmark like a straight Medicare Advantage risk score is a modeling error that distorts shared-savings calculations and can quietly cost or earn your organization hundreds of dollars per attributed beneficiary per year.
Bottom Line
CMS-HCC, RxHCC, and HHS-HCC cannot be swapped for one another without reshaping the populations and dollar flows they were built to govern. CMS-HCC, RxHCC, and HHS-HCC each solve for a different population, and the diagnosis-to-weight logic that drives one model’s payment has no automatic claim on the next. Match the model to the contract, lock in the right recalibration year, and audit clinical-pharmacy alignment before submission. Do those three things and your capitation revenue reflects the actual illness burden of the members on your rolls.
FAQ
What are the main risk adjustment models used in Medicare Advantage?
Medicare Advantage uses the CMS-HCC model for medical capitation and the RxHCC model for Part D drug plan payments. Both are recalibrated annually by CMS, with the most recent significant shift being the v28 phase-in for CMS-HCC.
How do CMS-HCC, RxHCC, and HHS-HCC models differ?
ICD-10-CM diagnoses drive CMS-HCC for Medicare Advantage, NDC pharmacy claims drive RxHCC for Part D, and ICD-10-CM diagnoses also drive HHS-HCC for ACA marketplace risk transfers. Each model has its own hierarchy rules, weight sets, and normalization factors.
Which risk adjustment model applies to which population?
Medicare Advantage seniors and dual-eligibles fall under CMS-HCC. Medicare Part D enrollees fall under RxHCC. ACA marketplace adults and children, plus some state Medicaid expansions, fall under HHS-HCC. ACOs in the Medicare Shared Savings Program use a blended CMS-HCC framework.
How are risk scores calculated under each model?
Each model combines demographic factors with condition- or drug-based weights to produce a raw score, then normalizes that score against the relevant denominator population. The normalized score is multiplied against the base payment rate to set capitation or transfer amounts.
Why does CMS use different risk adjustment models for different programs?
Each program serves a population with different cost drivers and different data availability. A pharmacy-only model is the only practical option for Part D, where diagnoses are often missing, and the ACA marketplace needs pediatric and infant adjusters that CMS-HCC does not include.
What diagnoses count toward risk adjustment payments?
Only confirmed diagnoses documented by a treating clinician during an acceptable encounter type, submitted from the correct setting, and captured within the data-collection window. Speculative or rule-out codes do not count, and the highest-weighted HCC in each disease family supersedes lower-weighted related codes.
