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How to Navigate the Complexities of Risk Adjustment and HCC Coding – An outlook on different Payment models!

How to Navigate the Complexities of Risk Adjustment and HCC Coding – An outlook on different Payment models!

As current managed healthcare industry keeps evolving vastly with time, we are also coming more face to face with newer, fresh payment model and methods. Risk Adjustment and HCCs, or Hierarchical Condition Categories although not new but relatively is a less talked about concept. Even more so for Pro-fee medical coders who are actively engaged in following fee-for-service vs value-for-service payment models. In this article, we’ll just scratch the surface and briefly go through the intricate concepts of HCC and Risk Adjustment (scoring and sharing) methodology and how it fairs against existing payment models.

Introduction to payment models:

To understand Hierarchical Condition Categories, we need to understand how these various payment system works. For that, three names come to mind:

1) Fee-for-service Model

2) Bundled or episodic care

3) Capitation Arrangement

For those who don’t know; Fee for service (FFS) is the most core traditional pricing model of our healthcare industry. In this model, the healthcare providers and physicians are reimbursed based on the number of services they provide or their procedures. Payments in an FFS model are not bundled, unlike episode-based care, instead it is for each unit in-short. Finally, then there is Capitation; where the provider has to be meet targets by attending certain number of patients in a certain duration of time (per member, per month/PMPM).

Volume vs Value?

These three are a part of ‘Volume’ based models. In past few years, Providers and healthcare organizations have started warming up to ‘Value’ based models as well. Programs APMs and MIPS, HEDIS are well-utilized. As opposed to FFS or other volume-based models which prefers quantity over quality, interestingly Value-based care is steadily getting more traction. Value based care prioritizes patient health benefits and outcomes and they only get services they need to improve those outcomes. Now, Risk adjustment is a central feature of this value-based care system and with Risk Adjustment comes HCC coding.

How does HCC coding works?

Hierarchical condition category (HCC) coding is key to risk-adjustment model originally designed in 2004 to predict future health care costs for Medicare Advantage patients. Patient risk adjustment uses a statistical process to calculate the health status of a patient into a number, called a risk score or more appropriately a ‘Risk Adjustment Factor (RAF)’, to assist in the prediction of health care costs.

CMS assigns a score or a value against each diagnosis, with Categories representing Pharmacy and ESRD as well:

A chart showing the relationship between payment models.

Click to open the image

As you might have noticed, unspecified diagnosis cannot be used to calculate risk score. It is also important that in-course of treatment the diagnosis code also progress. Which was once unspecified, can be develop into something with higher risk score later. There is variability within an individual from one year to the next in their need for medical care.

Tell us more about Risk Scoring?

Each HCC diagnosis group comes with its own score. Usually, severe chronic illness with complications and co-morbidities will make the patient ‘high-risk’ who require intensive care with ultimately higher HCCs which inadvertently will give a higher cost estimation for the treatment.

A flowchart explaining the HCC coding process.

The CMS-HCC risk score for a beneficiary is the sum of the score or weight attributed to each of the demographic factors and HCCs within the model. The CMS-HCC model is normalized to 1.0. Beneficiaries would be considered relatively healthy, and therefore less costly, with a risk score less than 1.0. Risk scores with this design are easy to interpret, as a score of 1.0 is equivalent to a person whose health care costs are exactly equal to the population mean, while a risk score of 0.1 would indicate that an individual has expected expenditures equal to 10% of the average.

What other Factors determine Risk Score?

In a risk adjustment model, risk score is also influenced on the basis on demographics, such as age and gender, as well as health status. Other factors may also include eligibility for Medicaid; initial reason for Medicare qualification; residence in an institution such as a long-term care facility. At the end of the contract year, the average risk scores of the members served by each provider group can be calculated.

How payment works with HCC or Risk Adjustment Models:

The idea of healthcare organization getting paid through HCC is quite simple. Overall cost can be estimated concurrently (current contracted period) or is set prospectively (past contracted period). Most organization might use any Risk Adjustment or value-based care software that might help them calculate.

Here for instance, three providers (A, B and C) are handling a patient, the payment would be shared as such:

A comparison table of payment distribution among providers.

This is interesting because each provider will now be compensated (almost) purely on the basis of the patient’s health outcomes!

Why HCC coding specificity is important:

Health status as we have discussed is determined by ICD-10 CM codes, which demand highest specificity. Typically, the predictor variables are binary condition categories.

Specificity is essential to receive full reimbursement. For example, diabetes with no complications, HCC code 19, pays a $894.40 premium bonus, while diabetes with ESRD, requires 2 HCC codes, 18 and 136, and has a bonus of $1273.60. The ability to document with greater precision can dramatically impact payment amounts.

A specialist in HCC coding is also known as risk adjustment coder establishes a risk score for each patient. The coding can be performed in Physician site of practice such as an Office or as an auditing contractor.

An HCC coder captures a complete picture of a patient’s health status. The ability to do that, heavily relies on Provider documentation. One key missing detail can tip the scale. Lack of specificity can lead to estimation of a risk score that does not reflect the actual prognosis which directly impacts on overall reimbursement. A strong Risk score stands on a strong Clinical documentation.

Where HCC Risk Adjustment Model will work in future?

CMS classified over 72,000 ICD-10-CM diagnostic codes into approximately 1,500 diagnostic groups known as DXGs. Codes were placed in DXGs if they were related in clinical and cost characteristics. Hierarchical condition codes (HCC) were then established from the DXGs creating what CMS has identified as Version 28 of the CMS-HCC risk adjustment model. Previous it was based on ICD-9, for 2024 it will be based on ICD-10 data. Insurance companies and government payers use these groupings of diagnosis coding to make comparisons of quality, cost, and estimations of resource use.

It is appropriate to report all current co-existing conditions that affect the care and management of a patient. For risk adjustment, reporting of chronic conditions is necessary at least once each calendar year for accurate risk score calculation.

Here are some Highlights from latest Version 28 for HCC risk score estimation:

CMS is moving from HCC Version 24 (V24) to Version 28 (V28).

CMS finalized a phased transition from CMS-HHC version 24 to version 28 which will be employed until 100% of payments are determined using version 28 in 2026.The renaming and renumbering of HCCs is common throughout version 28 for three primary reasons.

  • Even though the number of HCCs increased, the total number of ICD-10-CM codes designated as HCCs decreased by approximately 2,000 codes.
  • New HCCs were established increasing the total number of HCCs to 115 from 86. For example, HCC 35 Pancreas Transplant Status is a new HCC even though the ICD-10-CM code Z94.83 has been designated as an HCC in the current model, version 24.
  • Finally, the coefficient risk adjustment factors (RAF) also changed. For example, the chronic hepatitis RAF differs by .038 between the versions – .147 (V24) and .185 (V28) respectively.

This creates a challenge for the providers to follow both systems. As one risk score for the same diagnosis can variate in both systems.

  • This update aims to improve the accuracy and specificity of the HCC model based on ICD-10-CM. Transitioning to ICD-10-CM coding enhances data capture and cost prediction, aligning with industry standards and providing a robust foundation for risk adjustment. This ensures accurate payment calculations.

Is value-based care through HCC all that perfect?

Even though with its problems value-based care pricing models such as Risk Adjustment model have its intentions in the right place. In a quality-focused model, Providers incentivize patient’s need above all and they also get rewarded in the long run.

Patients get the best deal out of any value-based care pricing model. They get the services for their actual cost and value. However, it can be considered a collaborative effort. Practices might still take the situation as a hassle. The reason being that they might not feel completely in-control and the whole process can be complicated and overwhelming, taking how drastically different this system is from traditional pricing models.

Another con that is brought-up frequently is how unpredictable and subject the risk-scoring outcomes can be. Progression and outcome of a disease can be a highly uncertain thing and these are harder to measure as a metric. HCC coding strongly emphasizes on using the most suitable diagnosis for scoring. Inadvertently, improving the documentation all across the board, limits use of abused and overused diagnosis codes regardless of pricing models.

In this regard, an HCC coder should be fully capable and instinctive to capture a complete picture of a patient’s health status. The ability to do that, heavily relies on Provider documentation. One key missing detail can tip the scale. Lack of specificity can lead to estimation of a risk score that does not reflect the actual prognosis which directly impacts on overall reimbursement. A strong Risk score stands on a strong Clinical documentation.

AltuMED is a Medical Billing Services and Solutions Company. We excel at combining Revenue Cycle Management acumen with technology, enabling industry leading solutions to optimize financial health of Medical Practices and Clinical Labs. Find out more!

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