- Navigating RADV Audits: Understanding the 2023 CMS Final Rule on Overpayments
- What Are RADV Audits & Why They Matter
- Importance of RADV
- Understanding Audit Expectations in Healthcare: Ensuring Precision and Compliance
- Key Changes in the 2023 CMS RADV Audit Final Rule
- How Healthcare Providers Can Prepare for RADV Audits
- Preparing for a RADV Audit: Best Practices
- RAAPID’s Role in Ensuring Compliance with RADV Audits
- Conclusion
- Source
The Regulatory Impact Analysis for the RADV Final Rule projects that extrapolated improper payment recoveries will reach approximately $479 million annually, starting with the 2018 payment year. This shift is driven by a growing focus on addressing overpayments within the Medicare Advantage (MA) program. Increased enforcement under the False Claims Act (FCA) is set to impact both Medicare Advantage Organizations (MAOs) and healthcare providers.
Navigating RADV Audits: Understanding the 2023 CMS Final Rule on Overpayments
Key changes in the Final Rule on Medicare Advantage RADV Audits include the extrapolation of audit findings and the elimination of the Fee-for-Service (FFS) Adjuster. The RADV program audits MA payments to identify improper risk adjustments when diagnosis codes submitted by MAOs are unsupported by medical records. CMS adjusts monthly capitation payments based on enrollee health status, acknowledging that complex patient care can be more costly.
CMS believes that improper payments are prevalent due to the lack of pre-payment review of diagnosis codes. This suggests that MAOs might have financial incentives to over-code diagnoses to increase payments. While RADV audits focus on identifying improper payments rather than detecting fraud, recent trends indicate that the Department of Justice (DOJ) is increasingly using the FCA to target potential fraud in the MA program.
As the MA program grows, the regulatory shift brought forth by the RADV Final Rule will likely have a significant impact on MAOs and providers alike.
What Are RADV Audits & Why They Matter
The Medicare Advantage (MA) program, established by Congress in 2003, allows Medicare-eligible individuals to receive benefits through private health insurance plans instead of traditional Medicare. The MA program operates on a capitated payment system based on the Hierarchical Condition Category (HCC) model, which assesses the health status of enrollees. Healthcare providers report ICD-10 codes grouped into about 90 HCC categories, representing over 10,000 diagnoses. Payments to Medicare Advantage Organizations (MAOs) are adjusted based on the risk profile of beneficiaries, resulting in higher payments for sicker patients who require more care.
Importance of RADV
- RADV curbs over-coding: CMS does not validate diagnosis codes upfront, leading to potential over-coding and overpayments but such coding discrepancies is addressed following RADV compliance parameters.
- Helps recover overpayments: CMS uses RADV audits to recover overpayments for unsupported diagnosis codes in medical records.
- RADV as a Key Tool for MA Integrity: Shaped by internal reviews, RADV ensures the accuracy of Medicare Advantage (MA) payments.
- RADV audits point to Errors calling for Improved accuracy: CMS and HHS OIG audits show errors, emphasizing the need for accurate documentation and coding.
Understanding Audit Expectations in Healthcare: Ensuring Precision and Compliance
Medicare Advantage organizations (MAOs) must prioritize accurate diagnoses and thorough documentation to meet CMS audit standards. Auditors focus on ensuring that diagnoses and management are appropriate, aligning with CMS’s compliance goals.
Experts emphasize that the central question is, “Are the diagnosis and management appropriate?” However, the specifics of what auditors penalize remain unclear. Despite available CMS audit standards, organizations often face penalties for other reasons. This ambiguity challenges MAOs to focus on accurate HCC coding, prioritize certain diagnoses, and maintain proper patient care documentation. These steps are essential to navigate audits and ensure compliance with RADV Rules while avoiding costly penalties.
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Key Changes in the 2023 CMS RADV Audit Final Rule
The final rule for the Medicare Advantage (MA) Risk Adjustment Data Validation (RADV) program, issued by the Centers for Medicare & Medicaid Services (CMS), introduces three key policies designed to enhance the program’s effectiveness. These policies address the extrapolation of RADV audit findings, the use of the Fee-For-Service (FFS) Adjuster, and the remission of improper payments identified during RADV audits.
- Extrapolation of RADV Audit Findings: CMS has confirmed its decision to extrapolate RADV audit findings to a broader universe of an MAO’s claims. This marks a shift from the previous method, where adjustments were made on an enrollee-level basis. The new approach allows CMS to adjust payments at the contract level based on the overall error rate of payments to an MAO. If an audit identifies errors in a sample of claims, CMS can apply those findings across a larger pool of claims to recover overpayments.
While CMS has not adopted a specific sampling or extrapolation methodology, it will use any statistically valid method suitable for each audit. This flexibility ensures accuracy and fairness. CMS will apply extrapolation for Payment Year (PY) 2018 and beyond, while for PYs 2011 to 2017, it will collect overpayments based on enrollee-level adjustments.
- FFS Adjuster Rejection: CMS has rejected the proposal to incorporate an FFS Adjuster into the RADV program. The FFS Adjuster was suggested as a way to account for potential errors in Medicare FFS data, which some MAOs claim understate the cost of treating certain conditions. These MAOs argued that such errors could lead to lower payment rates under the MA payment model.
However, CMS concluded that there is no evidence of systematic bias in Medicare FFS data. Consequently, MAOs will be required to meet all current medical record documentation requirements, ensuring that any ICD-10 diagnosis codes reported for risk adjustment are substantiated with appropriate medical record findings.
- Remission of Improper Payments: CMS has outlined how MAOs will be required to remit improper payments identified during RADV audits. For PYs 2011 to 2017, MAOs should expect CMS to recover enrollee-level overpayments. For PY 2018 and beyond, the specific process for recovering extrapolated amounts remains unclear. The final rule reinforces the obligation of MAOs to refund any overpayments identified, extending beyond CMS audits. MAOs must take action if they discover any diagnosis code lacks support in an enrollee’s medical record, regardless of how they learn this information.
How Healthcare Providers Can Prepare for RADV Audits
As RADV audits approach, Medicare Advantage plans must take proactive measures to mitigate risk and ensure compliance. Mock RADV audits and frequent internal audits of coding vendors should be a priority. Studies highlight the importance of oversight, noting that reviewing only 8-12% of charts is insufficient, as health plans are ultimately accountable for the diagnosis codes submitted to CMS.
To further prepare, health plans should consult Office of Inspector General (OIG) reports that identify common coding errors. Investing in comprehensive compliance programs is crucial to equip teams with the right policies, procedures, and staff to handle regulatory audits effectively.
Once an audit begins, plans face strict timelines. When notified, plans have only 20 to 25 weeks to respond, stressing the urgency of acting early. The MAO Extrapolation Impact is also a key factor, as CMS expects Medicare Advantage plans to reduce improper payments. This incentivizes plans to identify and return non-validated HCCs.
Beyond RADV, health plans must also focus on OIG and improper payment measure (IPM) audits. Such steps help identify high-risk organizations for future RADV audits. Health plans performing well in these other audits may reduce their likelihood of being selected for RADV reviews, minimizing potential financial penalties.
Preparing for a RADV Audit: Best Practices
Preparing for a RADV audit requires a proactive approach, focusing on education, internal reviews, and data accuracy.
Here are key best practices to follow:
- Train and Educate Staff: Ongoing HCC education for coders, clinical staff, and scribes is vital. Ensure they understand the importance of compliance with RADV audit requirements.
- Conduct Internal Reviews: Regularly audit charts and coding practices to ensure diagnoses are properly documented. Identify and correct discrepancies early.
- Ensure Data Integrity: Confirm that ICD-10 codes are accurately assigned and that data submitted to CMS aligns with patients’ medical records.
- Develop a Response Plan: Establish a dedicated audit response team with defined roles and timelines for addressing audit requests.
- Hold Mock Audits: Conduct mock audits to spot potential issues and fine-tune processes.
Technology, like that offered by RAAPID, can streamline these preparations, helping organizations maintain compliance.
RAAPID’s Role in Ensuring Compliance with RADV Audits
Amid the rise of value-based care (VBC), achieving RADV readiness and optimizing financial outcomes is vital. Investing in comprehensive risk adjustment validation solutions with MEAT-enabled HCC coding and claims comparison capabilities enhances efficiency.
Key strategies include first and second-level chart reviews to identify and correct errors before submission.
RAAPID’s 2nd pass NLP audit leverages machine learning to analyze clinical documentation, detect risk adjustment coding gaps, and provide actionable insights. This reduces audit risks, improves coding accuracy, and ensures better compliance and financial performance for VBC organizations.
Conclusion
The final rule for the RADV program represents a significant step toward strengthening the accuracy and accountability of MA payments. By extrapolating audit findings, rejecting the FFS Adjuster, and clarifying the remission process for overpayments, CMS is ensuring that the RADV program effectively addresses coding errors and protects the integrity of the Medicare Advantage payment system.
To avoid overpayment liabilities, MAOs must adapt to these new policies and remain diligent in their documentation practices, supported by new-age AI-driven NLP technologies.
Source
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