Identifying HCC suspects to quickly and effectively identify missing HCC opportunities and protect your revenues
The risk adjustment model known as Hierarchical Condition Categories (HCCs) is used by the Centers for Medicare & Medicaid to prospectively estimate future year's predicted costs for enrollees. While this system has been in place since 2004 for Medicare Advantage plans, the model is now being applied to determine in part reimbursement for Accountable Care Organizations (ACOs) and the Hospital Value-Based Purchasing (HVBP) program. Under ACOs and the HVBP, providers assume more accountability and subsequent risk. This can translate into opportunity for providers who properly document each patient encounter; however, it can also translate into lost revenues and increased risk for those who don’t.
The challenge lies in the fact that there is no clear method that enables providers to know which HCCs they are missing before claims are sent out. In most cases, once revenue is lost, it is extremely hard for providers to get it back. And this assumes that providers can even identify where they missed HCCs.
As conventional approaches to finding HCCs are not effective, we looked to newer and smarter ways to support providers. So we applied the best and most advanced RevEgis patient phenotype platform to HCCs. This solution is able to model patients using historical data through a process that consumes thousands of characteristics at a patient level. RevEgis uses this information to identify HCC suspects so that a physician’s office or hospital can catch possible misses before they happen. The system “red flags” HCC suspects for review so that you can quickly and effectively identify missing HCC opportunities and protect your revenues.
This method is a true demonstration of patient level predictive models applied to a pure commercial condition yielding unmatched accuracy results – call it our HCC crystal ball.
While there is a clear risk when HCCs are tied to revenue, there are other important aspects of HCCs that providers need to consider. Higher HCC capture has shown a correlation to an improved case mix index because of the overlap between HCC diagnoses and CC/MCC diagnosis. Additionally, outpatient documentation improvements targeted at better HCC capture lead to optimized inpatient clinical management by providing higher quality information about a patient. And HCC capture provides hospitals with another tool to compare risk adjusted physician performance and target documentation improvement opportunities.
To find out more about HCCs, visit the Centers for Medicare & Medicaid’s website: