Risk Adjustment Coding – What You Need to Know

Risk Adjustment Coding is an essential tool for healthcare providers to use to ensure they are getting paid for their services. However, many people need to realize how complicated this process can be and know what to do to ensure they are coding correctly. The following article will help you understand what you need to know and help you prepare for this vital task.

CMS/HCC risk adjustment model

The Centers for Medicare & Medicaid Services (CMS) uses a Hierarchical Condition Category (HCC) risk adjustment coding to predict the cost of care for Medicare Advantage plan enrollees. An HCC is a medical condition with a high probability of being diagnosed and treated. Its predictive power is enhanced by incorporating information about the diagnoses.

To identify the most critical metrics in a risk adjustment model, actuaries analyze data sets of more than 1 million Medicare beneficiaries. Their results show that the CMS/HCC risk adjustment model does not account for the most important predictors. Adding more information about the diagnoses, such as how long they’ve been present, increases the model’s predictive power.

There is also a need for more information about HCCs that aren’t considered for payment. These include non-payment HCCs, such as HIV/AIDS, and clinically significant HCCs, such as cancer.

To estimate future medical costs, the CMS/HCC risk adjustment model uses an algorithm to categorize 79 HCC conditions. Each condition is assigned a unique coefficient that is then used to calculate a risk score for each patient. This calculation is different for each segment of the population.

Using this method, the average HCC risk score was higher for members with many HCCs. However, the difference in risk scores was negligible for members with a single HCC.

An additional component of the model is the Payment Condition Count model. This model uses the number of medical conditions patients have to calculate their monthly expenses the following year. During this process, Medicare pays M.A. plans a monthly sum.

While the HCC-HCC risk adjustment model is helpful, it could be better. There are still a few factors that could improve its performance.

Commercial risk payment model

Organizations that serve individuals or small groups can use a commercial risk payment model. These models distribute funds between enrollees with low and high-risk scores. The risk score is calculated based on data from medical records submitted for reimbursement in the year it occurred. It is typically assessed within six months after the end of the previous year.

In a fee-for-service (FFS) arrangement, providers receive a fee for every procedure or test. In contrast, the provider assumes the financial risk for the specific services provided under a risk-based payment scenario.

Many payers have introduced dozens of payment models in the last decade. Each one is designed to reduce costs and improve care. But these models also place more responsibility on providers for the quality of care.

Healthcare organizations and private payers are moving to more risk-sharing arrangements across the care continuum. Payors and providers work together to determine the best risk-sharing blend for each plan.

Commercial risk payment models can be effective if they are open to all participants. They also help providers share the cost savings achieved through improved care delivery. However, they are less prevalent than upside risk-only models.

A common theme among all payment models is to shift the focus from volume to value. For example, bundled payments and pay-for-performance care delivery models are designed to lower the costs of orthopedic and cardiac care. It is a crucial component of the 2022 Health Care Learning and Action Network (HLN), launched by the U.S. Department of Health and Human Services.

A payer-provider partnership is a great way to manage patients. Providers and payers can work together to build the infrastructure to support a wide range of patient care. Some associations focus on improving care coordination and data challenges, while others focus on a particular health population or area of healthcare.

Medicare risk payment model

The Medicare risk payment model, also known as RAF, is a system that determines a plan’s payments. It relies on medical record data submitted for reimbursement in a given year.

This data is then used to calculate the risk score for each plan member. The higher the patient’s risk score, the more likely the insurance company will pay. Generally, each diagnosis will not affect the score. However, specific disease interaction algorithms may increase the score.

Although this model does not account for the severity of an enrollee’s medical conditions, it does account for factors such as age, gender, deductibles, and co-payments. Using this data, the plan can calculate the cost of the healthcare a patient will require in a given year.

The current system can encourage plans to enroll sicker patients. Patients with high-risk conditions are more likely to have costly treatment. As a result, they may also earn profit. But the model does not factor in the social supports that an ailing population may need. Moreover, the model may unintentionally exaggerate the disparities between healthy and sick people.

Many experts believe that payers will continue implementing the patient risk scoring model. For example, an early adopter state found that spending in its ACOs decreased significantly.

Other models include bundled payments, savings/shared risk, and population-based payments. Each model requires a different level of risk. Nevertheless, providers must understand the other options available and their advantages and disadvantages. Keeping costs low can benefit the provider and increase profit margins.

Some physicians are worried that the financial risk involved with the various models could lead to poor quality care. That is why the Centers for Medicaid and Medicare Services encourage plans to participate in downside risk-inclusive contracts.


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