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
White paper
Incomplete, backward-looking information during care transitions drives avoidable utilization. Learn why MA plans must focus on the handoff, not just readmissions.
Article
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.
White paper
New Optum survey of more than 450 employers signals a reset: Wellbeing strategies must close gaps in mental health, engagement and accessibility to drive impact.