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Missouri Medicaid Audit & Compliance Transforms FWA Detection Strategy & Results

AI-Powered Analytics Yields $50 Return for Every $1 Spent


Challenge: Tackling Rising Costs and Fraud in Medicaid

The Missouri Medicaid system, serving 1.3 million residents and processing over 100 million claims annually, faced mounting pressure to control costs and improve the detection of fraud, waste, and abuse (FWA). Medicaid spending in Missouri exceeded $13 billion in medical benefits and $2 billion in pharmacy benefits in 2022. Given the significant financial outlay, reducing improper payments became a top priority for state administrators.

Traditional FWA detection methods had proven inefficient, with existing tools and processes unable to keep pace with the scale and complexity of fraudulent activities. The multi-layered Medicaid system, involving numerous providers, facilities, and claims types, required a more advanced solution to proactively prevent overpayments and recover funds lost to improper billing.

Missouri’s Medicaid Audit and Compliance (MMAC) team needed a comprehensive tool to efficiently identify and address improper claims, reduce the administrative burden, and maximize financial recoveries. The search for a solution led them to Alivia Analytics’ FWA Finder™, a powerful AI-driven platform capable of revolutionizing FWA detection.


Results Summary

Missouri MMAC

23,327 Leads identified

15,480 Retrospective leads

7,847 New leads

$50:$1 Extrapolated ROI


Solution: Implementing Alivia Analytics’ FWA Finder™

In 2021, Missouri’s MMAC team implemented Alivia Analytics’ FWA Finder™ tool to tackle FWA challenges head-on. The tool is designed to enhance fraud detection, reduce improper payments, and ensure compliance with Medicaid regulations. By leveraging advanced AI algorithms and real-time data analysis, FWA Finder™ offers a tech-enabled service that integrates seamlessly into Medicaid operations.

Over the course of three years, MMAC applied FWA Finder™ to analyze retrospective Medicaid claims data. The tool quickly identified areas of significant variance in spending, helping the MMAC team pinpoint potential FWA cases. The analysis focused on:

  • Providers (counselors, physicians, nurses)
  • Facilities (outpatient clinics, hospitals)
  • Service types (medical, pharmacy, behavioral health)

The platform’s algorithms highlighted irregularities such as:

  • Billing for more hours than possible in a day
  • Services provided to multiple family members simultaneously
  • Outpatient services billed while patients were recorded as hospitalized

By applying these insights, MMAC auditors were able to identify improper billing patterns, recover improperly spent Medicaid dollars, and reduce the risk of future fraud.

By providing real-time insights, FWA Finder™ enabled MMAC to take swift corrective actions, including suspending improper payments, recovering funds, and terminating relationships with non-compliant providers. The tool also supported long-term efforts to improve compliance and reduce improper payments in both pre-payment and post-payment phases.

Key Results: Measurable Impact and Financial Recovery


A Tech-Enabled Solution for Long-Term Success

FWA Finder offered more than just immediate recoveries. Its capabilities extended to long-term operational improvements by equipping the MMAC team with:

  • Comprehensive data integration: The tool utilizes external data sources such as provider exclusion lists, professional licensing boards, and Electronic Visit Verification (EVV) data to validate claims and provider eligibility.
  • Advanced AI and machine learning: Algorithms continuously learn and adapt to emerging fraud schemes, providing the MMAC team with insights that improve over time.
  • Customizable queries and reports: The MMAC team could generate specific queries based on provider type, service type, or location, allowing for deep dives into identified FWA patterns.
  • Collaborative auditing: Findings could be easily shared across the team, enabling faster audits, investigations, and recoupments.

The proactive approach empowered Missouri Medicaid to move beyond traditional reactive FWA detection. The tech-enabled solution prevented future fraud while optimizing workflows and minimizing administrative burdens.


Why Choose Alivia?

Alivia Analytics stands out as a leader in providing tech-driven solutions that enhance fraud detection and operational efficiency for Medicaid programs. The FWA Finder™ platform offers unmatched capabilities to detect fraud, waste, and abuse, providing:

  • Advanced Data Analytics: Leveraging AI and machine learning to uncover complex fraud patterns that traditional systems often miss.
  • Real-Time Insights: Empowering teams to act swiftly on fraud detection with automated analysis and actionable data.
  • Scalable Solutions: Customizable to meet the needs of state Medicaid programs, including data integration and reporting tailored to client specifications.
  • Proven ROI: As demonstrated in Missouri, Alivia’s FWA Finder™ can yield significant financial recoveries, far exceeding program costs.

Conclusion: Missouri’s Path to Medicaid Payment Integrity

The partnership between Missouri Medicaid and Alivia Analytics demonstrates the power of AI-driven fraud detection in preserving Medicaid resources. The FWA Finder™ tool has transformed how MMAC identifies and addresses improper claims, delivering substantial financial recoveries while streamlining processes.

With an ROI of $50:$1, Missouri’s investment in Alivia’s platform has proven to be both cost-effective and impactful, setting a new standard for Medicaid fraud detection. As Missouri continues to navigate rising healthcare costs, FWA Finder™ will remain a key tool in ensuring financial integrity and compliance across the Medicaid program.