How FWA Payor Analytics Prevented 5–10% of Improper Medicaid Claim Billings for a State Medicaid Solutions Integrator

Fraud, Waste, and Abuse Payor Analytics | Medicaid Solutions Integrator | Medicaid Program Integrity
Learn how a Medicaid program strengthened fraud, waste, and abuse oversight while reducing improper billing risks through advanced analytics.
Solutions Used
Industry
Healthcare
5–10%
improper billings prevented

Payment leakage reduction

15%
lower operating cost

Cost efficiency

New fraud patterns
identified

Program integrity intelligence

Business Challenge

State Medicaid agencies face persistent exposure to fraud, waste, and abuse across high-volume claims environments where improper billing can be hidden across providers, members, services, utilization patterns, and multi-party relationships.

The client, a leading systems integrator serving State Medicaid agencies, needed a stronger way to identify improper billing patterns that could not be detected through static rules or manual review alone.

Program integrity teams required analytics that could combine claims, provider, patient, utilization, and registry data to surface outliers and trigger cases for desktop or onsite audits.

Improper billings created payment leakage, higher administrative cost, and reduced confidence in Medicaid program integrity.

With agencies under pressure to protect public funds, improve cash flow, and act faster on emerging fraud schemes, the client needed an AI-driven FWA analytics solution that could detect known and new patterns at scale.

Solution Offered

Novacis Digital delivered Fraud, Waste, and Abuse Payor Analytics, a purpose-built Medicaid program integrity solution built on eCareVantage Payer Analytics.

The solution combined Surveillance and Utilization Review (SUR) dashboards with the Fraud and Abuse Detection System (FADS) to detect improper billing patterns across claims, providers, patients, utilization measures, and registries.

SUR used descriptive statistical techniques for outlier detection, while FADS applied AI-driven analytics and machine learning to identify complex and emerging fraud patterns.

Unlike generic claims reporting, the solution connected pre-built FWA models, measure profiles, pattern processing, registries, dashboards, and case management integration into one governed analytics layer.

User management, security controls, configurable business models, and audit-ready case outputs supported accountable program integrity workflows.

This shifted the operating model from retrospective claims review to analytics-led FWA detection and case prioritization.

Medicaid FWA Capabilities

  • Identify outlier activity
  • Discover emerging fraud patterns
  • Connect multi-party signals
  • Configure detection logic
  • Support audit workflows

Claims Integrity Features

  • Descriptive statistics across utilization measures
  • Machine learning models and FADS algorithms
  • Claims, provider, patient, and registry relationships
  • Business model creation and measure profiles
  • Case management integration and action tools

Results Delivered

Novacis Digital delivered eCareVantage Payer Analytics in record time as a secure cloud-based analytics solution for Medicaid FWA detection.

The rollout gave program integrity teams access to SUR dashboards, FADS analytics, claims and provider registries, pattern processing, measure dashboards, performance benchmarking, and case management integration.

Early adoption improved improper billing detection, reduced operating cost, strengthened cash flow, and increased visibility into program activity.

The results directly addressed the need to protect Medicaid funds, identify new fraud patterns, and help audit teams prioritize desktop or onsite investigations.

Business Outcomes:

Prevented 5–10% of improper Medicaid claim billings, protecting $10M–$20M in potential exposure across $200M of reviewed claims.

Reduced operating costs by 15%, lowering the effort required to identify outliers, review utilization, and prepare FWA cases.

Improved Medicaid payment integrity by identifying newer fraud schemes and helping agencies respond before patterns became recurring leakage.

Delivered integrated FWA coverage across claims, providers, patients, registries, measure profiles, pattern processing, dashboards, and case management tools.

Improved audit execution by routing suspicious patterns into case workflows for desktop or onsite provider and member reviews.

Additional Value:

  • Secure AWS cloud delivery supported controlled SaaS access for the client and State Medicaid agency end users.
  • User management, security controls, and configurable rules supported governed program integrity workflows.
  • SUR and FADS modules created a reusable analytics framework for additional Medicaid agency deployments.
  • Performance benchmarking and dashboards improved visibility into utilization trends and fraud indicators.
  • Machine learning methods supported continuous improvement in detection accuracy over time.

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