As value-based care providers and organizations aim to ensure accurate risk adjustment for Medicare reimbursement, understanding strategies to mitigate audit risks and optimize revenue is crucial.
In this blog post, we’ll explore the Centers for Medicare & Medicaid Services (CMS) perspective on retrospective risk adjustment. We’ll emphasize the importance of data accuracy and documentation integrity, highlight key compliance protocols for audit preparedness, and demonstrate the synergy between AI and regulatory compliance for strategically maximizing revenue.
Join us as we navigate the intricate world of Compliance and accuracy in the context of retrospective audit benefits and healthcare payment integrity.
Rationale Behind Risk Adjustment Audits
In recent times, the Office of Inspector General (OIG) has observed an increase in avoidable coding errors during audits. The OIG’s primary focus is providing financial oversight for Medicare Advantage Organizations (MAOs).
In 2022, the federal government spent over $403 billion on managed care programs, with 50% of Medicare enrollees receiving care through MAOs.
To combat fraud, waste, and abuse and to protect taxpayer dollars, the OIG conducts health plan audits to validate risk-adjusted payments made by CMS.
As of August 2023, these audits have identified approximately $377 million in risk adjustment overpayments due to inaccurate coding.
In a June 2024 report, the OIG revealed that despite CMS implementing the two-midnight rule starting in FY 2014, hospitals continued to bill Medicare for numerous potentially inappropriate short inpatient stays, leading to nearly $2.9 billion in costs.
The audit assessed measures taken to address these stays from 2016 to 2020.
Additionally, recent news about nationwide audits of Medicare Part C high-risk diagnosis codes by the OIG indicates that these audits will target diagnosis codes considered at high risk for miscoding.
OIG: The Custodian of Compliance
The Office of Inspector General (OIG) rigorously audits to ensure compliance with federal requirements. Discrepancies often arise when individuals transition from traditional Medicare to Medicare Advantage (MA). High-risk diagnosis codes, identified through data mining and expert consultations, can lead to overpayments. A key focus was on acute stroke diagnosis codes, aiming to maintain financial and operational integrity in the program.
CMS Perspective -Compliance Pivots on Retrospective Coding Accuracy
Why does CMS expect coding accuracy to be between 95-98 percent in retrospective auditing?
CMS payment models require high accuracy during retrospective audits to manage Value-Based Care programs effectively, protect beneficiaries, maintain financial integrity, comply with laws and regulations, and ensure trust in the Value-Based Care system. This commitment to accuracy is vital for the responsible administration of government-funded healthcare programs.
Retrospective risk adjustment, according to CMS, plays an important role as retrospective chart review happens after the patient’s encounter or discharge, involving a thorough examination of coded data against supporting documentation to ensure accuracy and completeness.
This process is crucial for identifying errors or inconsistencies that may have occurred earlier. It also provides valuable insights into coder performance trends over time, offering opportunities for education and improvement based on identified patterns or discrepancies.
A drawback of retrospective validation is its dependence on data analysis rather than real-time intervention. Consequently, any errors identified retrospectively have already impacted reimbursement rates or led to penalties.
We shall soon see how a risk mitigation approach based on advanced AI-powered risk adjustment solutions can address such gaps in retrospective risk adjustment.
The Pursuit of Accuracy + Fulfillment of Compliance = Equitable Quality healthcare
Accuracy in healthcare is more than just trust; it’s about compliance!
Indeed, achieving accuracy in Health risk assessment demands meticulous attention to data collection and documentation integrity. This entails capturing comprehensive, & precise details on each patient’s medical conditions, treatments, and outcomes. Correct coding is essential for accurate risk scoring and subsequent reimbursement calculations.
Retrospective validation not only identifies coding inaccuracies post hoc but also fosters continuous improvement within healthcare organizations.
Furthermore, establishing compliance protocols to adhere to CMS coding guidelines is crucial for conducting regular internal audits. Organizations can improve accuracy by identifying past errors or missed opportunities to assign accurate codes, enabling them to implement corrective actions in the future.
Nevertheless, retrospective validation is crucial in medical coding, underscoring its significance. The knowledge gained from this process guarantees precise reimbursement and enhances the overall data quality.
Best Practices for Audit Compliance & Accuracy
Healthcare organizations can successfully navigate the nuances of audits and optimize revenue streams by prioritizing proactive measures. These include risk mitigation measures such as continuous education, regular internal audits, and strict protocol compliance, which are all part of precise retrospective risk management practices.
Risk Mitigation Measures To Boost Audit Confidence.
- Audit Preparation: Prepare your organization for RADV audits through ongoing reviews, policy discussions, and specialized outsourcing. Ensure accurate documentation and retrospective coding practices to mitigate non-compliance risks.
- Modernization of Systems and Practices: Utilize advanced technologies and outsourcing services to streamline audits, enhance HCC coding accuracy in risk adjustment, and improve compliance, thereby boosting performance and providing educational initiatives.
- Enhanced Coding Accuracy: Conduct continuous assessments through Retrospective HCC reviews in order to prevent errors and penalties, ensuring precise RAF scores and appropriate health plan reimbursements.
- Improved Clinical Documentation: Ensure compliance and accurate reporting by performing comprehensive patient data analysis and addressing discrepancies between physicians and MAOs to enhance coding accuracy and adherence to CMS guidelines.
- Alignment with Regulatory Policies: Audit claim data accuracy must comply with HCC coding regulations. Timelines for RADV audit submissions must be effectively managed to avoid penalties for non-compliance.
- Managing Increased Administrative Burden: Inaccurate patient documentation necessitates time-consuming retrospective chart reviews for MAOs, diverting resources from patient care and operational enhancements. This results in workload stress and burnout especially while meeting submission deadlines.
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Audit Preparedness and Revenue Optimization are two sides of the same coin
Preparing for audits involves meticulous documentation management, thorough staff training, robust compliance initiatives, and leveraging external expertise as needed.
By doing so, healthcare organizations can effectively minimize risks linked to audits while optimizing revenue through precise capture of risk adjustment data.
In today’s dynamic healthcare compliance environment, organizations must prioritize both regulatory adherence and revenue optimization. By integrating compliant practices with retrospective risk adjustment strategies that enhance revenue generation, healthcare providers can effectively manage risk adjustment complexities and achieve financial prosperity.
Revenue Optimization Through Effective Compliance Measures
- Accurate Documentation: Ensuring precise coding and reimbursement through recording of patient encounters and diagnoses, emphasizing specificity in diagnosis codes, supports efforts taken towards clinical documentation improvement.
- Robust adherence to Protocols: Implementing internal audits, staff training, and monitoring ongoing coding practice to address compliance issues and maintain adherence to regulatory standards proactively.
- Audit Readiness: Establishing comprehensive systems (EHR/EMR) to facilitate easy access to required documents during audits like CMS’s RADV, preventing disruptions and demonstrating compliance with regulatory requirements.
- Technology Healthcare compliance solutions: Utilizing tools for data accuracy checks, automated coding suggestions, and real-time coding pattern analysis to improve efficiency in revenue-related processes and compliance efforts.
- Revenue Optimization Strategies: Aligning compliant practices with revenue strategies to effectively navigate risk adjustment complexities, secure rightful reimbursement, and maximize financial success for healthcare organizations.
The Final Straw: Is Compliance Easily Achievable Through Accuracy?
Accuracy comes with Challenges
Complexities in risk adjustment pertaining to Medical Records & HCC Coding raise discrepancies in medical coding.
Performing retrospective reviews is operationally challenging as for Health Plans, it often involves the cost of acquiring charts from providers.
At the same time, both parties utilize internal or outsourced coding teams for review, coding, and quality assurance. This process is prone to human error, time-intensive and costly tasks, plus a lack of thorough risk assessment.
Moreover, analyzing patient conditions months after doctor visits results in outdated risk assessments. Plans often lack real-time illness data, further complicating risk management.
Additionally, retrospective risk adjustment programs can strain provider relationships & eventually cause provider abrasion. This diverts time from documenting patient encounters to coordinating with chart retrieval vendors for medical record review by multiple payers, disrupting physician CORE operations.
Retrospective Chart Review Bottlenecks
- Coding Errors: Medical coding challenges, such as failing to capture relevant conditions, result in inaccurate risk assessments and financial implications. Coders must follow updated guidelines and use coding accuracy tools.
- Detailed Documentation: Payers require comprehensive records for high-intensity E&M services, increasing the complexity of medical documentation. This is easily possible by deploying AI-based, Data-driven healthcare solutions.
- Concerns about Non-Compliance in Retrospective Risk Adjustment: A crucial focus area in retrospective risk adjustment coding is reviewing and correcting previously submitted data. Non-compliance in this area carries significant risks, potentially resulting in severe financial penalties and heightened regulatory scrutiny.
Overcoming Challenges Head-On with AI
AI-Enabled Risk Adjustment Solutions: Pathway to Accuracy and Compliant ROI
Advanced AI-driven solutions can now effectively manage risk adjustment challenges arising from manual clinical operations and outdated legacy systems.
Presenting our state-of-the-art Risk Adjustment solution, backed by cNLP (clinical natural language processing) technology and harnessing the capabilities of Artificial Intelligence.
Here’s how RAPPID’s cNLP tool achieves this
- Efficient Data Extraction: RAPPID’s cNLP tool efficiently retrieves pertinent clinical data from medical records, ensuring precise identification of medical conditions and their severity. This extraction process is tailored to meet RADV audit requirements and provides a comprehensive overview of patient health status.
- Meets MEAT Criteria: The NLP tool meets the MEAT criteria (Medical Evidence, Assessment, and Plan) by not only extracting data but also synthesizing it into a cohesive narrative. Beyond capturing medical conditions, it emphasizes assessment and planning to ensure documentation supports the accurate diagnosis, crucial for retrospective risk adjustment.
- Enhances Compliance: By automating HCC code extraction aligned with RADV and MEAT criteria, RAPPID’s NLP tool minimizes documentation errors and inconsistencies, thereby enhancing compliance. This proactive approach not only mitigates audit risks but also enhances patient care quality.
By leveraging these tools and strategies, healthcare organizations can effectively navigate RADV audits, optimize revenue, and improve patient care outcomes.
As the healthcare landscape evolves, the integration of advanced technologies like NLP becomes increasingly pivotal in achieving compliance, enhancing patient outcomes, and ensuring the financial sustainability of healthcare providers. Embracing these innovations is essential for organizations seeking to thrive in today’s dynamic healthcare environment.
Conclusion
AI advancements and regulatory changes will shape risk score optimization, and that in turn will determine care quality.. Embracing AI in risk adjustment and preparing for new regulations enhances retrospective HCC coding accuracy, reduces costs, and improves efficiency, leading to better patient outcomes and financial sustainability.
RAAPID can assist your organization with retrospective HCC chart reviews and has a proven track record of improving HCC code capture.
Source
¹OIG
²CMS
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