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Key Points About Risk Adjustment of Quality and Cost Data

Key Points About Risk Adjustment of Quality and Cost Data

  • January 23, 2018

Almost every provider I’ve ever known claims that their patients are more complex and challenging to manage than others. This perspective is especially true when providers review quality or cost efficiency data that shows them performing lower than their peers.

The good news is that CMS has a system to account for clinical complexity and uses this risk adjustment methodology to ensure they are comparing apples to apples and not apples to oranges in value-based reimbursement (VBR) programs (e.g., MACRA and Medicare Advantage). The bad news is that very few providers know how Medicare’s model works and how they can take steps to make sure their data is appropriately risk-adjusted. Here are the key details to remember:

  • The Medicare risk adjustment model uses hierarchical clinical conditions (HCCs) along with demographics and socioeconomic factors to capture risk in a specific provider’s patient population.
  • Each HCC must be addressed in one of the following ways to count toward the risk adjustment factor (a provider’s score that indicates the risk of their patient population).

Monitored. For a condition like diabetes, this would include monitoring the progression of this disease over time, e.g., did the patient develop diabetic-related eye disease, kidney disease, nerve damage, or other complications of diabetes?

Evaluated. Continuing with diabetes, this might involve specific tests like hemoglobin A1C levels, urine protein/albumin levels, renal function testing, or eye exams.

Assessed. For diabetes, the provider needs to document whether the condition is stable, progressing, or regressing/resolved.

Treated. Finally, as it relates to diabetes, this might involve the prescription of oral hypoglycemic agents, insulin, or other diabetic treatment measures.

  • The individual HCCs are added up to produce the Risk Adjustment Factor (RAF) score.
  • The RAF score is used to adjust performance data. For example, two providers with identical performance measures (Quality or Cost) might not be judged as equivalent performers if one of the provider’s RAF score was higher. The provider with the higher RAF score, in essence, would receive extra credit for taking care of sicker, more complicated patients, and his or her performance metrics would be adjusted to account for this variable. Note that this might also result in the higher performer receiving more incentives under a VBR system like those in MACRA.
  • ELLIS M. KNIGHT, MD

    ELLIS M. KNIGHT, MD

    Senior Vice President/Chief Medical Officer

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