Articles

Risk Adjustment: How to ensure fair compensation for payers and providers

Navina Team

March 3, 2025

Risk adjustment strategies for payers and providers

Table of contents

It is difficult to overstate the crucial role risk adjustment plays in value-based care (VBC). Some patients naturally present a greater level of financial risk than others. In order to make sure that healthcare organizations are not penalized for providing coverage and care to patients presenting higher-than-average risk, they need to be compensated for the extra expenses they are likely to incur as a result of caring for those patients.

That is exactly what risk adjustment aims to do. By maintaining complete and accurate records of patients’ health conditions and other factors likely to affect the level of risk they present, healthcare organizations (including both payers and providers) can ensure they will get appropriate compensation. Not only does this help them get the funds they’ll need to finance the care they provide–it ensures the sustainability of the entire value-based model. With that in mind, this post will provide valuable insight into what it takes to implement effective risk adjustment strategies.

What you will learn from this post:

Why does risk adjustment play a crucial role in value-based care, and how high are the stakes for both payers and providers?
What are the key risk adjustment models that can affect healthcare organizations financially?
What are some of the biggest challenges healthcare organizations face when doing risk adjustment?
How can cutting-edge technology improve risk adjustment strategies?

What are the key benefits of effective risk adjustment strategies for both payers and providers?

Risk adjustment is the process of estimating the level of financial risk that a healthcare organization takes on by agreeing to provide for a particular patient’s medical needs. It’s a key tenet of value-based healthcare because of the critical role it plays in leveling the playing field and making sure that healthcare organizations and medical professionals are adequately compensated for the care that they provide. That makes it particularly important for both payers and providers to ensure that their risk adjustment strategies are reliable and thorough.

Not only does that mean that risk adjustment is essential in order for value-based care to work, it means that incomplete risk adjustment can do serious harm to health plans, accountable care organizations (ACOs), physician practices, individual clinicians, patients, and others. When a patient’s file is missing relevant diagnoses, that can often result in an organization providing coverage and care without receiving the full compensation they are entitled to. That can put a serious dent in the organization’s revenue, making it far more difficult for them to provide care sustainably in a risk-bearing model. At the same time, healthcare organizations need to beware of the risk of overcoding, which can result in serious penalties.

Importantly, reliable and thorough risk adjustment strategies is not just a financial matter. When done right, risk adjustment should help healthcare organizations identify patients who can and should receive specific types of screenings, medical interventions to help manage chronic diseases and conditions, and preventive care. By ensuring that risk adjustment is conducted thoroughly and accurately, healthcare organizations can ensure they have the resources available to comprehensively address each patient’s medical needs.

Pro tip: Think of the development of accurate, comprehensive, and time-efficient risk adjustment strategies as an investment in your organization’s value-based future . While specific diagnosis codes change from time to time, the central role that that risk adjustment plays in VBC isn’t going away anytime soon.

What are some important risk adjustment models, and how do they affect healthcare organizations financially?

Healthcare organizations’ finances can be impacted heavily by the risk adjustment factor (RAF) scores (also called risk scores) that are assigned to patients. Because those scores are intended to estimate the level of financial risk that a healthcare organization takes on by agreeing to provide care and coverage to patients, they consider factors including patients’ healthcare conditions and demographics. Based on that information, each RAF score is calculated using a specific mathematical formula. Then, RAF scores are used to determine the payments to which a given healthcare organization is entitled.

There are several common risk adjustment models that can be used to factor medical conditions into RAF scores. They do this by allowing for a list of hierarchical condition categories (HCCs) to be created for each patient, with each HCC putting a numerical value on a given medical condition. After a given patient’s HCCs are added, their sum is entered into the formula on which RAF scores are based.

There are three main risk adjustment models that are used to calculate RAF scores in the U.S.:

CMS-HCC, which is the main model used by the Centers for Medicare & Medicaid Services (CMS).
RxHCC, which CMS uses specifically for risk adjustment relating to prescriptions.
HHS-HCC, which the U.S. Department of Health and Human Services (HHS) uses for private healthcare plans under the Affordable Care Act.

One of the biggest shifts underway in the world of value-based care is the gradual transition from V24 to V28 of CMS-HCC. V28 has significant differences from V24, with many diagnoses added, removed, or changed. Although V28 is fully in effect for care provided in 2025, V24 codes will continue to affect some value-based care payments through at least the end of the year.

Why is it so difficult to ensure complete and accurate risk adjustment?

Given the high stakes of risk adjustment, it is crucial for healthcare organizations to implement effective risk adjustment strategies. The problem is that having a complete record of HCCs for a given patient requires thorough analysis of that patient’s records. That tends to be a difficult, time-consuming, and unreliable process – especially because it is common for patient records to include vast amounts of unstructured data. Also adding to the challenge, that data is often spread across numerous information sources including paper records, electronic health records (EHRs), health information exchange (HIE) feeds, claims data, and more.

As a result, it is common for HCC coding to take up a significant amount of clinicians’ valuable time, contributing to their heavy administrative burden. That can make it more difficult for clinicians to devote their time and attention to actually caring for patients, taking a serious toll on the quality of care patients receive.

Despite all that effort, it is unrealistic to expect clinicians to capture every relevant HCC code. In part, that’s because the volume of varied patient information means that certain conditions can easily be overlooked. And in part, it’s because there is often a widespread lack of knowledge of relevant HCC codes. When it comes to CMS-HCC codes, the transition from V24 to V28 heightens that risk, as even clinicians who were familiar with V24 codes now need to adapt to a newer system.

Pro tip: Taking risk adjustment seriously doesn’t need to mean putting it all on the shoulders of your organization’s clinicians. It’s a heavy burden, and it’s often unrealistic to expect clinicians to capture all relevant diagnosis codes.

How can cutting-edge technology improve risk adjustment strategies?

Artificial intelligence (AI) can make a powerful difference in the challenging effort of ensuring complete and accurate risk adjustment. By integrating and analyzing patient data from numerous sources, AI can often pinpoint diagnoses that may have been missed.

By tapping into the power of AI, organizations can help ensure that their risk adjustment strategies allow for thorough and reliable HCC coding. At the same time, this approach allows for significant lightening of the administrative burden on clinicians, so that they can focus more on delivering the best possible care to each patient.

One of the keys to using AI effectively to bolster risk adjustment strategies is making sure that each suggested diagnosis is backed by solid evidence from the patient record. Given the dangers of overcoding, it is crucial to use AI in ways that empower clinicians to streamline and improve their HCC coding – without letting it make final determinations. This way, organizations can enjoy the increased comprehensiveness and efficiency that AI-powered HCC coding offers, while protecting from the risks that can result from overcoding.

Pro tip: AI can make a powerful difference to risk adjustment strategies, helping ensure that diagnosis codes aren’t missed while also lightening the administrative burden on clinicians and empowering them to focus on delivering the best possible care to each patient.

Key takeaways

Risk adjustment is a critically important challenge for both payers and providers that work in value-based models of healthcare. While it shows no signs of becoming any less important over time, technological developments are introducing new possibilities for healthcare organizations to adopt more effective risk adjustment strategies. Here are some of the most important points to keep in mind:

Risk adjustment is essential in value-based care, helping level the playing field to protect both patients who present above-average levels of risk and the healthcare organizations that provide coverage and care for them.
For both healthcare payers and providers, it is crucial to make sure that risk adjustment is conducted thoroughly, accurately, and efficiently – but making that happen tends to be an uphill battle, especially given how time-consuming and difficult it can be to navigate patient records.
AI changes this reality dramatically by automatically integrating and analyzing multi-source patient data, suggesting likely diagnoses, and providing actionable insights.
By using powerful, evidence-backed AI like Navina’s to streamline and improve risk adjustment strategies, organizations can help ensure that they receive the full compensation to which they are entitled, while also empowering their clinicians to focus on delivering the best possible care to each patient.
Using AI as a central part of an organization’s risk adjustment strategy can go a long way towards making value-based care feasible, profitable, and sustainable for payers and providers – while helping improve the patient experience and facilitating optimal patient outcomes.

FAQ

What is risk adjustment, and why is it important in healthcare?

Risk adjustment is the process of determining the level of risk inherent in providing care for a given patient, in order to ensure that their healthcare provider has enough funds to cover the cost of their care in a value-based healthcare model. Relying on information including the patient's demographics and health conditions, risk adjustment involves using a mathematical formula to estimate the cost of meeting the patient’s medical needs in a given year.

Risk adjustment plays a critical role in making the value-based model of healthcare work effectively. In this model, healthcare services are paid for holistically and based on patient outcomes, rather than on the quantity of healthcare services provided. By factoring the severity of a patient’s medical conditions into the amount of money to be paid to their provider, risk adjustment in healthcare helps ensure that that provider is able to provide for the patient’s care, and isn’t unfairly penalized for providing care to patients with a greater level of risk.

As a result, risk adjustment has a major impact on revenue for healthcare providers, while also giving them useful insights to help improve the quality and efficiency of care. By ensuring that each patient’s file includes a complete list of medical conditions, providers can help make sure they are compensated adequately for the care they deliver. On the other hand, when a list of a patient’s conditions is incomplete, the provider risks losing out on revenue to which it is entitled, making it more difficult to deliver the care the patient needs.

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What are risk adjustment factor (RAF) scores, and how do they impact revenue?

Risk adjustment factor (RAF) scores – also called risk scores – are calculated to reflect the relative risk that a healthcare provider takes on by providing care to a given patient in a value-based model of healthcare. They are determined based on various factors including the patient’s demographics and health conditions, and calculated using a mathematical formula intended to reflect differences in the cost of providing care to different patients during a particular year.

One of the key factors in determining a patient’s RAF score is a list of Hierarchical Condition Categories (HCCs) reflecting their medical conditions. In addition, the RAF score should consider other key characteristics expected to have an impact on the estimated cost of providing care to the patient.

RAF scores play a central role in determining a provider’s revenue in a value-based healthcare model. Because care is paid for holistically in this model (rather than per service provided), RAF scores help ensure that healthcare providers have enough funds to cover the cost of each patient’s healthcare needs, and aren’t penalized for covering patients presenting a greater level of risk.

To ensure that each healthcare provider receives the funds that they need, it is critical to make sure that each patient’s RAF score accurately reflects all of their medical conditions in a particular year. An incomplete list of conditions can result in a RAF score lower than it should be – needlessly reducing the provider’s revenue and making it more difficult to meet each patient’s medical needs.

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How does the shift from HCC V24 to V28 affect healthcare providers, and how can they successfully navigate this transition?

In 2023, the Centers for Medicare and Medicaid (CMS) began a transition from the HCC V24 to V28 risk adjustment model. This transition has significant implications for healthcare providers and patients. Not only does it impact the funds providers receive for patient care, but it affects the way they handle HCC coding.

Importantly, this shift is taking place gradually, with risk adjustment relying on a blend of V24 and V28 until the transition is complete. As a result, healthcare providers now need to navigate both standards for HCC coding. That complicates the process of coding in the interim, especially because there are substantive differences between V24 and V28.

Among other changes, V28 reduces the number of ICD-10 codes that map to HCC codes from roughly 10,000 to roughly 8,000, while increasing the number of HCC groups from 86 to 115. The shift also removes approximately 3,000 diagnosis codes, adds over 250 new HCC codes, and changes the weighting assigned to various codes.

Because healthcare providers now need to apply both V24 and V28 models simultaneously, they need to make sure that each patient has two complete lists of relevant HCC codes (one for V24 and one for V28). To make that happen both reliably and efficiently, they should empower their medical professionals with helpful digital solutions, including AI-powered software for capturing all relevant diagnoses. They also need to ensure that clinicians, nurses, medical assistants, and coders have access to all the information they need – and that they share information effectively, including through pre- and post-appointment workflows.

For a deeper dive into how to adapt effectively to this shift, please see our whitepaper, The Impact of HCC V28 on Medical Groups: Strategies for a Successful Transition.

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What is HCC coding, and why does it matter?

HCC coding is a way of managing risk adjustment by estimating the future costs of healthcare for a given patient. It relies on Hierarchical Condition Categories (HCCs) – medical codes representing specific groups of medical conditions, which have been used by the Centers for Medicare & Medicaid Services (CMS) since 2004. The shift toward value-based healthcare has seen HCC coding take on an increasingly central role in healthcare.

HCC coding relies on the International Classification of Diseases, Tenth Revision (ICD-10) – an updated version of which is released each year. Using this guide, a given patient’s HCCs are determined based on medical conditions the patient has in a specific year, with each condition having a weight reflecting the impact it is expected to have on a patient’s healthcare costs.

A given patient’s RAF score depends heavily on the list of the patient’s HCC diagnoses. Since the RAF score affects the amount that the healthcare provider will be paid, it is important to have a full list of relevant HCCs for any given patient. Incomplete lists of HCCs for patients can result in a needless loss of revenue for their providers, creating a financial hurdle that can prevent a value-based system of healthcare from working as it should.

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10 essential risk adjustment tips for 2025

With these actionable steps, you’ll be well-equipped to drive better outcomes, maximize revenue potential, and stay ahead in the ever-evolving landscape of value-based care.

Navina Team

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