Big decisions demand the best tech-driven solutions. Learn More

Search
Close this search box.
Medical Record Audit Solutions

Home » Blogs 

In Pursuit Of Accuracy: Impact Of AI On MA Medical Record Audit Solutions

Retrospective Audit and its importance for MA organization

  • Ensure quality care is being provided to Medicare beneficiaries
  • Adhering to the Federal guidelines
  • Enhance revenue cycle management
  • Optimize reimbursements
  • Defend against federal and payer audits, health plan denials, and malpractice litigations.

Final submission of RAF scores to CMS facilitated by Retrospective Audit.

Retrospective review and audit protect MA organizations from CMS penalties by performing first- and second-level reviews to validate the medical coder’s findings for mapping the final HCC summary and RAF score calculation.

What are the types of Audits?

  • RADV (Risk Adjustment Data Validation) Audit
  • OIG (Office of Inspector General) Audit
  • IVA (Independent Validation Audit) Audit


RAAPID’s AI-powered solution empowers MA Health Plans to optimize past coding for maximum accuracy, uncover missed revenue opportunities, and proactively prepare for external audits like RADV and OIG. This dual approach ensures both financial integrity and long-term compliance.

Retrospective Audit – AI does it better

The remarkable efficiency of AI-based solutions lies in swiftly accessing, precisely organizing, and meticulously reviewing documentation and clinical data. This underscores AI’s pivotal role in ensuring a triumphant outcome for CMS audits.

The foundation of lasting CMS audit preparedness is not just having a compliance program but also fostering an ongoing culture of compliance to conduct medical record audits successfully.

NLP-Powered Medical Record Auditing Solutions seamlessly embed compliance to deliver optimized RAF scores, ensuring there’s never a gap in readiness for a CMS audit.

Befriend AI WITH Benefits

Below are some bespoke advantages of using AI as part of the Risk Adjustment Process 

  • Streamlined Efficiency: AI simplifies auditing, allowing focus on complex tasks needing human expertise.
  • Enhanced Precision: AI swiftly analyzes data, aiding in detecting issues effectively.
  • Cost Savings: AI targets testing areas, reducing time and resources.
  • Advanced Analytics: AI detects intricate patterns, enhancing auditors’ analytical capabilities.
  • Refined Risk Evaluation: AI pinpoints risks, aiding auditors in conducting thorough assessments.

AI Implementation: Challenges and Solutions

The Problem

AI – [Scoped to Tackle HCC coding challenges as part of the Risk Adjustment process]

Addressing Hierarchical Condition Category (HCC) diagnosis codes presents significant challenges for healthcare practices, including prevalent errors, staff scarcity, and compliance obstacles. Such difficulties during the risk adjustment process can lead to increased operational expenses, reimbursement delays, and potential financial sanctions.

Let’s closely examine the challenges:

Error Prone Processes:

Mistakes in coding can trigger claim rejections, forcing a loop of resubmissions and disputes consuming valuable time and resources.

OIG April 2021 report found while evaluating risk scores for 200 beneficiaries, only 1,322 (86.7%) HCCs were supported by documentation, while 203 did not. Additionally, 37 were misclassified or overlooked.

Ref – https://oig.hhs.gov/oas/reports/region7/71601165.pdf

Workforce Challenges:

A lack of experienced coders and the necessity for ongoing education can impede workflow and diminish efficiency.

Regulatory Hurdles:

Managing constantly evolving regulations presents difficulties, and failure to comply may lead to inspections and penalties.

The Solution – How we do it

RAAPID’S AI-driven solutions transform risk adjustment auditing by automating data analysis and pattern recognition, offering real-time feedback. This enhances efficiency and accuracy in adhering to coding standards, optimizes revenue cycles, and elevates patient care.

Also, AI systems enhance compliance and unstructured data by efficiently analyzing vast clinical data to identify billing discrepancies and missed diagnoses. They also automatically update with regulatory changes for real-time compliance.

At RAAPID, our AI Assistant surfaces appropriate Care Gaps and emerging Conditions by following the MEAT evidence accuracy, consistency, efficacy, and compliance to then present for review and potentially suppress inappropriate suggested conditions (HCC)

This powerful CNLP (Clinical Natural Language Processing) engine ingests, normalizes, and renders more highly accurate and complete results, converting and merging structured and unstructured data to deliver evidence-backed ‘findings’ to surface ‘in workflow’ to various stakeholders such as HCC Coders, Auditors, Care Teams and Providers- in each scenario and for each role the technology acts as a  “Trusted AI Assistant” to help deliver a complete, accurate, evidence-based CMS or local ‘policy mandated’ compliant output (for submission or audit/review) ready for submission to Payers, Health Plans and/or CMS..

Notably, getting this right, First Time Right also feeds Compliant ROI.
Estimates are greater than 75% of documents reviewed by Coders, Auditors, Care Teams, and Providers/Practitioners are unstructured and not necessarily immediately accurately ‘machine-readable’ .
So this creates an incredible data, costs and conversion burden to move from unstructured to structured data. This is precisely where AI algorithms work with 3rd party applications like Optical Character Recognition (OCR) and synch an integrated approach that converts unstructured clinical texts, often handwritten or scanned, into machine-readable formats for further processing by our AI risk adjustment solution.

Moreover, Adopting AI in medical auditing faces data privacy and security challenges, with the need for HIPAA compliance amidst AI’s fast evolution. Ensuring patient information protection and compliance requires written agreements, especially with AI handling PHI.
Current regulations inadequately address AI’s unique risks, including chat features.

Frequently Asked Questions (FAQ)

AI-enabled Medical Record Audit plays a crucial role in ensuring compliance and accuracy in RAF scores, reducing the risk of errors and potential financial penalties during CMS audits.

Fostering a culture of compliance ensures that every member of the organization is committed to adhering to regulatory standards, facilitating smoother and more effective medical record audits.

AI brings several benefits to the Risk Adjustment Process, including streamlined efficiency, enhanced precision in data analysis, cost savings, advanced analytics capabilities, and refined risk evaluation.

Healthcare practices often encounter challenges such as error-prone processes leading to claim rejections, workforce shortages of experienced coders, and navigating complex regulatory requirements.

RAAPID’s AI-driven solutions automate data analysis and pattern recognition, providing real-time feedback to enhance efficiency, accuracy, and adherence to coding standards, ultimately optimizing revenue cycles and improving patient care.

In conjunction with technologies like Optical Character Recognition (OCR), AI algorithms efficiently convert unstructured clinical data, such as handwritten or scanned documents, into machine-readable formats. This process reduces data conversion burdens and enhances the accuracy of risk adjustment auditing.

Conclusion

The era of artificial intelligence in medical auditing has dawned, reshaping healthcare with groundbreaking solutions promising heightened precision, efficiency, and financial resilience.

Analyzing billions of charts comprising hundreds of pages incurs exorbitant costs that are no longer sustainable for stakeholders. Therefore, our internally developed computer vision models excel in extracting crucial data from tables and forms via OCR, significantly reducing expenses and allowing MAOs to capitalize on economies of scale.

In today’s digital era, integrating AI into risk adjustment is imperative for achieving compliant ROI. Compliance through technology and an AI Assistant for any ‘human in the loop’ of risk-based management reduces variation costs and delivers appropriate reimbursement in a compliant way.

Thus In the complex world of Medicare Advantage, AI-powered medical record audits are no longer a luxury but instead have become a sought-after industry solution.

Share:

Lastest Posts

Subscribe To Our Newsletter

This field is for validation purposes and should be left unchanged.

Disclaimer: All the information, views, and opinions expressed in this blog are inspired by Healthcare IT industry trends, guidelines, and their respective web sources and are aligned with the technology innovation, products, and solutions that RAAPID offers to the Risk adjustment market space in the US.