Skip to main content

Article

Visualizing fraud, waste and abuse

Graph analytics and machine learning drive the future of program integrity.

Interpret data naturally with two key tools

Digging through data to identify fraud, waste and abuse (FWA) can be a huge challenge. Fortunately, graphic analytics and machine learning can help.

With graph analytics, information is displayed in graph form so viewers can see the visual relationships and interactions between data points.

A machine learning system makes predictions based on past behavior or data and compares them against new data.

Combined, agencies can identify shifting relationships and patterns that can help steer the machine learning system in the right direction.

Read the article to learn how graph analytics and machine learning can help support your agency’s program integrity initiatives.

Related healthcare insights

View all

Article

Whole-person cancer care: 4 strategies for employers and payers

Life after cancer is complex, and survivorship — living with and beyond diagnosis — demands long-term support for mental, physical and financial health.

Article

How transplant care can guide cell and gene therapy management

Payers facing rising CGT costs and complexity can draw on decades of transplant care experience to improve systems for coordination, risk management and patient support.

Article

Fecal transplant to treat recurrent urinary tract infection

Learn how leveraging a microbiome approach helped one patient with von Willebrand disease and multiple antibiotic allergies.