Risk Adjustment for Medicare/Medicaid/Commercial

Risk Adjustment models - How important is it for you to know the inner workings of Risk Adjustment models and how much you utilize your data asset to improve the quality of care? To what extent do you identify incomplete and missing chronic conditions/HCCs to effectively manage retrospective reimbursements?

The paradigm of payments for health care services will be impacted in many ways due to the Affordable Care Act. Risk Adjusted and pay-for-performance payments will play bigger roles in the service reimbursements areas. The lack of accurate Risk Score reporting and awareness can negatively affect the quality of care for patients and, consequently, the insurers' financials. For these reasons, it is important for clinicians and other decision makers to understand the fundamentals of risk adjustment and how it can provide better and more cost-effective care. By acknowledging that there are differences in patient cases, risk adjustment helps assure that clinical treatment and management decisions are based on well-grounded information.

An understanding of Risk Adjustment methodology and revenue cycle management is truly the key to succeed during emerging payment changes. Basically, there are two types of risk adjustment models: the prospective and the concurrent. The prospective model uses data from previous years or periods to estimate expenses for the following year/period. The concurrent model uses data from the current year/period to calculate expenses for the same year/period. For instance, the Health Care Financing Administration considers demographic and geographic variables when defining payment rates for Medicare risk plans. At a very high level, computer programs are used to calculate members' risk scores from medical encounters. For example, in the CMS-HCC Risk Adjustment model, health condition categories are derived using ICD/HCC mappings (Some models also use other medical codes in addition to diagnosis codes). Disease interactions are then identified using the HCCs. To avoid double counting, HCCs with low factors in the same disease group are excluded using the hierarchical elimination rules. Afterwards, HCC, Demographic, and other factors are added together to compute members' total scores. Finally, the normalization factors are applied to the total score to calculate the final score. Per member per month (PMPM) premium is the product of members' final score and bid rate.

Keeping up with evolving changes in Risk Adjustment and adhering with regulations are critical for Healthcare organizations to stay abreast in their domain. We, as a company, have the capability to integrate, analyze, and perform Risk Score and payment calculations using the medical encounters. Contact us at riskadjustment@aileronconsulting.com if we could be of assistance. Visit us at www.aileronconsulting.com