Unbiased Analysis of Today's Healthcare Issues

The CMS HCC Model

Written By: Jason Shafrin - May• 17•11

The CMS-HCC risk adjustment model is used to adjust payments for Part C benefits offered by MA plans and Program of All-Inclusive Care for the Elderly (PACE) organizations to aged/disabled beneficiaries. The CMS-HCC model includes both diseases and demographic factors. There are separate sets of coefficients for beneficiaries in the community, beneficiaries in long term care institutions, beneficiaries with ESRD and new enrollees.  New enrollee risk adjustment is based solely on demographic factors.  The CMS-HCC model was first used for payment in 2004 and has been recalibrated two times since then (2007 and 2009). In 2011, CMS will implement an updated version of the CMS-HCC risk adjustment model, including the coefficients for the community, institutional, and new enrollee segments of the model.

Today, we explore the 2011 HCC model in more detail, referencing heavily from this CMS document.

[Correction: My colleague Sajid Zaidi pointed out that CMS will not implement the new CMS-HCC until 2012.  As stated here: “To reference the factors in the CMS-HCC risk adjustment model that will be used in 2011, see the 2009 Rate Announcement (published in April 2008).”]

General Methodology

The HCC model identifies individuals by their demographic, health history, enrollment status (e.g., Medicaid eligibility) and other factors.  There are also a number of interactions terms included in the model which interact diseases (e.g., COPD x CHF) and diseases with disability status (e.g., Disability x CHF). The model regresses the expected cost in the FFS setting on these variables to predict spending for comparable beneficiaries who enroll in the Medicare Advantage program.  The resulting dollar coefficients represent the marginal (additional) cost of the condition or demographic factor (e.g., age/sex group, Medicaid status, disability status).  Changes to the condition categories – additions, deletion, and revisions – are based on each category’s ability to predict costs for Medicare Parts A and B benefits. Condition categories that don’t predict costs well –because the coefficient is small, the t-value is low, the number of beneficiaries with a certain condition is small so the coefficient is unstable, or the condition doesn’t have well specified diagnostic coding – are not included in the model. HCCs in the current model are subject to revision, regrouping, or deletion.

In a final step, hierarchies were imposed on the condition categories, assuring that more advanced and costly forms of a condition are reflected in a higher coefficient.
In order to use the risk adjustment model to calculate risk scores for payment, we create relative factors for each demographic factor and HCC in the model. We do this by dividing all the dollar coefficients by the average per capita predicted expenditure for a specific year (i.e., the “denominator year”).

There are separate models for beneficiaries from the community, those who are institutionalized, and those with ESRD.

Changes to the 2011 HCCs

The 2011 model has 87 HCCs, up from 70. Examples of the new HCCs include:

  • Two levels of severity of dementia
  • Other significant endocrine and metabolic disorders
  • Morbid Obesity
  • Fibrosis of the Lung and Other Chronic Lung Disorders
  • Exudative Macular Degeneration

A number of diseases that are currently included in HCCs with other related conditions have been broken out into their own HCCs. These conditions include quadriplegia, cerebral palsy, ALS and other motor neuron disease, and athereosclerosis of the extremities with ulceration or gangrene. Additional conditions that have been broken out into separate HCCs are pressure ulcers and kidney disease.

Because average predicted expenditures increase after the model calibration year due to coding and population changes, CMS applies a normalization factor to adjust beneficiaries’ risk scores so that the average risk score is 1.0 in subsequent years. The normalization is conducted separately for the: 1) CMS-HCC model, 2) ESRD Dialysis Model, 3) Functioning Graft Enrollees model, 4) RxHCC model.
Adjustments for Medicare as the Secondary Payer (MSP)
MA capitation rates are calculated as if Medicare were always the primary payer; adjustments to the rates for situations in which Medicare is secondary are made as part of actual payment. The MSP adjustment factor is applied as a reduction to payment for working aged and working disabled beneficiaries. The MSP factor is calculated as the ratio of the actual Medicare spending for all MSP beneficiary months to the predicted amount of Medicare spending that the model predicts for these MSP beneficiary months.

Frailty Adjustment
The purpose of frailty adjustment is to predict the Medicare expenditures of community populations with functional impairments that are unexplained by the CMS-HCC risk adjustment model. Frailty adjustment will be applied to payment to PACE organizations.

Adjustment for MA Coding Pattern Differences
Because MA coding patterns differ from those in FFS, MA risk scores increase more quickly and are, therefore, higher than they would be if MA plans coded in the same manner as FFS providers. In other words, this means that the MA plans are more likely to upcode over time than doe FFS providers. Beginning in 2010, CMS instituted a separate adjustment to the Part C risk scores to account for differential coding patterns between MA and FFS. The adjustment for 2010 and 2011 was 3.41%. This figure is an estimate of how much lower plans’ 2010 risk scores would have been if the disease scores (the portion of the risk score attributable to diagnostic coding) for MA enrollees who stayed in an MA plan during the period 2007 to 2010 (“MA stayers”) had grown at the same rate as FFS beneficiaries’ risk scores during this period.

Budget Neutrality
From 2003 through 2006, CMS implemented risk adjusted payments that were budget neutral to the demographic payments made prior to, and throughout the transition to, full risk adjusted payments by applying to the risk rates 100 percent of the Budget Neutrality (BN) factor. In 2011, however, there is no budget neutrality adjustment for risk adjusted MA payments.

Other factors:

  • IME Phaseout – Section 161 of the Medicare Improvements for Patients and Providers Act of 2008 (MIPPA) requires CMS to phase out indirect medical education (IME) amounts from MA capitation rates.
  • EHR Incentives. Eligible professionals (EPs) and hospitals that are meaningful users of certified EHR technology receive incentive payments.
  • PQRI and E-prescribing. Physicians who have not contracted with an MAO, but who provide covered professional services to an enrollee of an MA plan offered by an organization are similarly required to be paid the amount they would receive for a non-MA enrollee, and thus would be eligible for both the Physician Quality Reporting Initiative (PQRI) bonus payment from the organization to the extent they are due such payments under the original Medicare program. When a physician is determined by Medicare to be a successful e-prescriber and qualifies for the 2% incentive under the 2009 E-prescribing Incentive Program, MAOs and cost-contracting HMOs are required to pay non-contracted physicians, and in the case of PFFS plans meeting access standards through payment, contracting physicians, 2% of the Medicare allowed charges for any applicable, covered professional services rendered in 2009 to a member of their plan.
  • Adjustment to FFS Per Capita Costs for VA-DOD Costs. Medicare makes an appropriate adjustment to the payment rates to reflect CMS’ estimate, on a per capita basis, of the amount of additional payments that would have been made in the area involved under this title if individuals entitled to benefits under this title had not received services from facilities of the Department of Defense (DoD) or the Department of Veterans Affairs.


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  1. Brad F says:

    Great and helpful post.

    I am assuming above will go towards reconciling below:

    Would greatly appreciate your input.


  2. Model says:

    Über Model informiere ich mich regelmäßig. Danke also für deinen Blogpost zum Thema. Vielen Dank dafür, Martina.

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