The financial impact of risk adjustment errors

Highly accurate risk adjustment data is essential to aligning health plan reimbursement with the true cost of care. Precise measurement of the risk of your member population puts your organization in the best position to appropriately allocate resources, prioritizing closing care gaps and driving quality improvement.  

Unfortunately, too many health plans rely on incomplete documentation and manual risk adjustment processes, making their data and resulting risk adjustment factor (RAF) scores prone to errors. The result is a significant financial cost, a cost that threatens the competitiveness and performance of your health plan.  

Understanding exactly when and how risk adjustment errors occur can help plans improve the accuracy of their data and reduce financial losses, particularly when supported by artificial intelligence (AI) in healthcare.

Calculating the true cost of risk adjustment errors

Successful health plans depend on the accuracy of their risk adjustment data to pay for the services their members need. When errors occur, it jeopardizes your plan’s financial performance, relationships with providers, and, ultimately, member health outcomes. Here are some of the ways risk adjustment errors incur costs for your plan.

Your reimbursement doesn’t align with the true cost of care.

When your risk adjustment data has holes or other inaccuracies, it throws off the risk adjustment model. Health plans that miss critical diagnoses may be underreporting the severity of risk in their member population.  

The Centers for Medicare & Medicaid Services (CMS) bases Medicare Advantage plan reimbursement on annually submitted data. To make sure that data is accurate and error-free, health plans need ways of identifying and coding hierarchical condition categories (HCCs) with extreme precision and accuracy. That way, CMS produces RAF scores that reflect the true level of risk of your member population, and the resulting reimbursement reflects that risk level.

Too much staff time is spent on inefficient processes.

Far too often, valuable time and expertise are wasted handling routine, tedious, and time-consuming tasks. Risk adjustment is a complex, multi-layered process that requires the management of an extremely large volume of claims and encounter data. This includes training providers on documentation and coding accuracy to make sure all relevant diagnoses are captured. It also entails extracting critical data through the medical record retrieval process, following up with queries to providers as needed, and conducting clinical chart review.  

When errors occur, resulting audits may require even more staff time to uncover the genesis of the error, correct it, and report the new information to CMS. Without the power of advanced technology, including AI and intelligent automation, it can take hundreds to thousands of hours to complete necessary risk adjustment tasks. This time is costly, encompassing both the direct cost of staff time and the lost time that could be spent focusing on other organizational priorities.

You are subject to penalties for non-compliance.

Errors in risk adjustment, whether intentional or not, can result in overpayments. That level of non-compliance is extremely costly. First, prepared health plans pay for the legal and compliance teams they need to be a part of the submission process and respond to auditors. Still, the cost of that expertise is less than the cost of the governmental penalties that can occur.  

Health plans receiving overpayments can be subject to recoupments from Risk Adjustment Data Validation (RADV) audits, False Claims Act fines, and Department of Labor penalties. Some plans have incurred fines of over $150 million for risk adjustment violations.  

Because governmental agencies are increasingly using advanced analytics to identify errors in submissions, your health plan should consider implementing a first line of defense against errors. Using advanced analytics and AI, you can spot errors before submission deadlines and leave ample time to correct them.

Payments have to be made to the risk adjustment pool if risk scores are too low.

If your risk adjustment errors are underestimating the overall risk of your member population, not only are you subject to lower reimbursements. You could be overpaying into the risk adjustment pool.  

For plans with healthier-than-average members, this can add up to 14% of their total premiums. Accurately capturing member risk with little to no errors is essential to making sure your plan receives the necessary resources to serve your members.

Longer-term goals like quality improvement and growth suffer.

Finally, perhaps the greatest financial impact of risk adjustment errors comes with the loss of investment in long-term health plan goals. For example, to address quality of care and truly meet the goals of value-based care, many plans invest in programs for chronic disease management, wellness, transportation to appointments, community health workers, and more. These programs help to improve member outcomes and reduce disease escalation, lowering costs over time. However, when risk adjustment errors create financial losses, these programs suffer.  

Health plans may also lose the ability to invest in programs to improve member satisfaction and attract new members to their plan. These programs help plans grow and increase their market share, and yet the financial losses that can occur from risk adjustment errors threaten the viability of these strategies.

How to reduce risk adjustment errors

Even though risk adjustment is a complex process, dealing with mountains of data and tight deadlines, using advanced, AI-powered technology can drastically improve the speed and accuracy of your risk adjustment process.  

AI-powered technology transforms the medical record retrieval and clinical coding processes, working to extract, sort, and route patient records to the right member with incredible accuracy. Also, by accelerating clinical coding (in some cases tripling previous coding speeds), staff have more time to focus on inconsistencies in the data, follow up with providers to fill documentation gaps, and reduce loss-inducing errors.

Case study: How one health plan coded over a million charts in four months

One large payer looking to scale its risk adjustment processes to grow its Medicare Advantage business incorporated Reveleer's solution into its operations.  

The results were fast and transformative. In addition to increasing efficiency by 30% and coding over a million charts in just four months, incorporating Reveleer’s AI-powered Risk Adjustment Solution helped the MA plan reduce errors, fill documentation gaps, and, ultimately, achieve 40% more value per chart.

Interested in reducing risk adjustment errors and the high costs they incur? Schedule a tour of Reveleer’s Risk Adjustment Solution to build a strategy that:

• Increases the accuracy of your risk scores

• Accelerates the speed of risk adjustment and frees up staff time

• Is purpose-built for CMS compliance

• Reduces overpayments to the risk pool

• Powers your long-term goals