Hierarchical Condition Category (HCC) coding is essential to value-based care. It allows insurers to determine the health risks of a patient population and adjust reimbursement rates accordingly. Proper HCC coding depends on precise provider documentation and coding guidelines. Learn why investing in risk adjustment coding training is the smartest move healthcare providers can make.
Hierarchical condition category coding is central to the Centers for Medicare and Medicaid Services (CMS) risk-adjustment payment model. It determines a patient’s RAF score, which estimates future healthcare costs. The RAF score is heavily weighted on diagnosis codes, so it’s important to ensure that HCC coding is accurate.
Inaccurate HCC coding can have devastating effects on healthcare providers’ reimbursement. Depending on your program, even a missed diagnosis code could cost you millions of lost payments. Correctly coding HCCs can help your organization better predict patient costs and provide the necessary resources for high-risk individuals to receive care. It can also help physicians get the reimbursement they deserve.
Improving HCC coding accuracy is an ongoing process that requires specific knowledge and a commitment to continuing education. Creating systems for tracking and measuring coding accuracy is essential to make progress. What gets measured improves; establishing a consistent strategy is key to success.
Streamline the traditional coding and auditing process with technology that automates chart review and verification. It’s an effective way to increase HCC coding accuracy and reduce time spent reviewing patient records. Plus, it can save your team significant costs, ensuring you get the most out of your HCC coding investment.
When medical coders have a solid understanding of the principles behind HCC coding, they can quickly identify and close documentation gaps that would otherwise go unnoticed or uncorrected. And since these gaps can cost reimbursements, they must be resolved immediately.
But it takes time to gain a deeper understanding of the complexities behind the HCC model and how it affects healthcare providers’ reimbursements. This is why organizations need to invest in HCC risk adjustment coding training for their medical coders. HCC is a Medicare coding model designed to estimate future patient health costs.
The Centers for Medicare & Medicaid Services assigns each patient a risk factor score (RAF) using a combination of their current diagnosis and demographic details, including the patient’s age. This data is used to adjust the capitation payments for Medicare Advantage patients.
As the value-based healthcare model gains traction, it’s more important than ever for healthcare organizations to understand HCC’s role in a payer’s payment process. As a result, medical coders must focus on HCC coding training to avoid missing out on revenue opportunities and maintain RAF scores’ accuracy. This can help healthcare organizations keep up with new regulations and meet their performance goals year-over-year.
The HCC coding process is an integral part of the reimbursement process. It is used by healthcare payers like Medicare Advantage plans and health insurance marketplace insurers to determine a patient population’s potential future healthcare costs. This is done by assigning patients to specific risk groups based on their medical history and coding for the patient’s conditions. Inaccurate coding can negatively impact your revenue streams and, ultimately, your bottom line.
Fortunately, this can be avoided by investing in education and training. Educating your team on the value of accurate coding can help your organization reap significant benefits from an improved coding process. This is because your patients will be grouped more accurately, and you will be able to receive the appropriate reimbursements for their services.
Additionally, you can close documentation gaps and eliminate errors that could cause your HCCs to be under-reported, resulting in missed revenue opportunities. Using technology to collect, evaluate and analyze clinical data can help your organization identify missed HCCs that would have been overlooked during the review process.
This can be accomplished by leveraging natural language processing and machine learning. By leveraging these technologies, you can also reduce the time needed to review patient records and identify risk score-relevant disease documentation. This can save your organization valuable resources and allow you to get paid faster.
Using the right coding system and ensuring accurate diagnosis and documentation is essential to HCC. ICD-10 demands more precise and detailed information about a patient’s health than previous code sets, with many conditions requiring specific diagnoses and details that differentiate mild, moderate, or severe forms of the state.
For example, cytomegaloviral disease can be diagnosed as pneumonitis, hepatitis, or pancreatitis, depending on the specifics of the patient’s case. This level of detail is necessary to correctly code a patient’s healthcare history and accurately predict future medical needs, including HCC scores.
Inaccurate coding and CDI can negatively impact reimbursement, and a lack of accuracy can be costly for providers. It’s important to educate clinicians and the coding/billing team about the importance of this effort, as well as build systems that allow for consistency in the process.
One way to do this is by implementing an automated, time-saving system for HCC coding. A system that eliminates the need for manual review can significantly reduce the number of errors and increase coding accuracy. Additionally, a system that allows for real-time reporting can decrease the time required to submit claims and maximize revenue.
These systems and processes help healthcare providers stay ahead of changes to HCC coding rules. They also make it easier for providers and coding/billing teams to focus on the patient’s overall care, which can improve outcomes and increase revenue.