Top Five Missed HCC Codes for Risk-Adjusted Coding

Shahyan Currimbhoy
July 27, 2016

As a data analytics company, Talix analyzes, well, a lot of data. So, it’s not surprising that we’re often asked what our Coding InSight application tells us are the top missed HCC (Hierarchical Condition Category) codes.

We’ve seen macro trends across our customer base, which encompasses a range of different healthcare institutions. Based on data from our Coding InSight application, here are the top five actively managed conditions and documented status codes that are most frequently either un-coded or inaccurately coded by clinicians:


These codes are missed for a variety of reasons. A huge stumbling block for risk-bearing organizations, particularly those that are new to risk adjustment, is the shift to value-based care. This shift requires clinicians and coders to switch from coding acute or chronic conditions related to the patient’s reason for the visit or what was diagnosed/treated to reviewing, documenting and coding all of a patient’s chronic conditions and statuses – regardless of whether or not they are related to the reason for the visit or chief compliant. It’s a significant departure from the current coding practices of most organizations and a primary reason why, in spite of documenting the presence of severe health status conditions, providers typically fail to code them.

Other reasons include the increased specificity of Diabetes coding and the introduction of more complex guidelines, particularly for combination codes. And, of course, clinicians are grappling with having to do more with less time. They have access to more data, such as specialist notes and claims from other institutions, but many struggle with balancing the need to analyze and apply it all while simultaneously trying to meaningfully engage with their patient during the often short appointment window.

No matter the reason, missed codes have a huge impact on both the quality of care patients are getting and on a provider’s bottom line. It’s important for organizations to implement processes and/or solutions that enable them to accurately identify, document and manage all high-risk conditions.

Here are some quick tips for improving coding accuracy and efficiency:

  1. Diagnose the problem. According to the AAFP, the average claims denial rate for the industry is five to 10 percent. Practices, however, should aim to keep the rate below five percent. If your practice is experiencing a high number of claims denials, conduct a thorough review and analysis to determine where the problem lies so you can take steps to fix it.

  2. Stay up-to-date. Medical codes are updated annually with thousands of changes and deletions. Providers and coders should invest the time and money necessary to keep abreast of what’s new.

  3. Invest in analytics. Risk adjustment processes are highly manual, requiring retrospective chart reviews that are time-consuming, error-prone, and costly. Investing in a more sophisticated analytics engine that can mine both structured and unstructured data at the point of care can greatly improve both coding efficiency and accuracy, resulting in a higher level of care and an improved bottom line.
Shahyan Currimbhoy is the SVP of Product Management & Engineering at Talix.
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