Data increases efficiency in the detection of fraud, waste and abuse

The OIG has focused the evolution of fraud, waste and abuse (FWA) detection on a foundation of data analytics. Capitalizing on the power of data drives the agency to more efficient and comprehensive investigations, reviews, audits and inspections. Each year, the OIG team uses emerging technology used for data analytics to assess the billing trends and patterns of providers, clients, retailers, and contractors participating in HHS programs. This information enables investigators to increase the recognition of potential risks and move quickly against possible misuse of taxpayer funds. 

Fraud Detection Operations

To support fraud detection operations (FDOs), the OIG's data team created more than 25 new algorithms throughout fiscal year 2022. OIG Investigations and Reviews use these tools to detect potential waste or wrongdoing by identifying providers with unusual billing patterns compared to their peers.

The creation of the new algorithms helped identify potential policy violations and suspicious billing behaviors for Non-Local Mental Health Authorities and durable medical equipment providers. The graphic below highlights providers billing for significantly higher amounts when seeing fewer clients than their peers. Outlier status is not an automatic indicator of wrongdoing; it only identifies providers who may warrant a closer look due to unusual billing activity. The initiatives are in various stages of review and investigation.

Non-LMHA Providers

In the span of a few years, the OIG's provider investigation inventory has evolved from approximately 95 percent traditional referral cases with a few self-initiated cases to approximately 60 percent now being based on data analytics, almost all of which are data initiatives project team cases. By harnessing the power of data analytics, the OIG can handle cases more efficiently from the moment they begin until each investigation reaches its final resolution.

Data Initiatives Project Team

Fiscal year 2022 has seen the OIG broaden the use of data analytics to uncover improper billing trends in Medicaid delivery through the OIG's Data Initiatives Project Team. This team specializes in expanding previously developed algorithms from reviewing one provider – whether it comes from data analytics or a referral from an MCO or the public – to examining statewide data to locate Medicaid providers with similar issues in need of review.

This process identified a repeated issue with emergency room injection and infusion reimbursements. The data indicated outpatient hospital facilities were billing for administering injections or infusions in the emergency department when the ER evaluation and management reimbursement already covered those services.

The team has settled 21 ER injection/infusion cases for more than $30 million in overpayments. The OIG is also working to develop education and outreach to help providers and MCOs prevent future overpayments.

DIPT Case Settlments

Advancing analysis

To further develop the OIG analytics-based review methods, the agency contracted with a vendor. The contract is assisting the OIG to create more advanced analytical tools to help identify FWA's potential indicators throughout state health and human services. The work performed over the past fiscal year with the contractor will enhance the agency's ability to perform highly complex data analysis, increase operational efficiencies, and advance its analytical capabilities.

Sharing data and information

The OIG's data team facilitates a cross-divisional data analytics information-sharing session with data analytics staff throughout HHS. The quarterly meetings include OIG and HHS Medicaid/CHIP Services representatives, Actuarial Analysis, and the Office of Data, Analytics, and Performance. 

During these meetings, staff share data anomalies, utilization trends, and program and financial updates that may impact Medicaid services. The information exchanged during these collaborative meetings is considered by the OIG when performing any data analysis on topics of interest and can lead to recommendations for reviews by OIG staff in the future. 

Going forward

The OIG has found data analytics to be the most effective use of state resources to detect fraud waste and abuse. While referrals to the OIG identify potential risks in specific circumstances with an individual provider contracting with one managed care organization, a data-driven approach can identify risks program-wide by identifying if the referred provider and other providers are behaving similarly across other MCOs. This approach helps the agency focus on areas of high risk, increases recoveries and ensures better compliance across the Texas health and human services system.