Fraud and abuse in healthcare billing is as old as health insurance at the very least and remains a damaging drain on a system already beset with inefficiencies. However, more fraud, waste and abuse (FWA) scams can fail thanks to artificial intelligence (AI) and its ability to see red flags and stop this activity.
For example, 83 percent of surveyed firms that have or plan to invest in AI for FWA “consider reducing false positives as the most important expected benefit. That portion is 100 percent for firms that generate more than $1 billion in annual revenue. More than three-quarters of respondents in other revenue brackets cite it as the most important expected benefit.”
This from PYMNTS July 2021 study, AI In Focus: Targeting Fraud, Waste And Abuse In Healthcare, a collaboration with Brighterion, a Mastercard company, exploring how companies are combatting FWA with AI smarts. Based on a survey of 100 healthcare executives across a range of expertise in fraud detection and analysis, financial planning, claims payments or risk management, this excerpt examines the issue, and AI’s role in fighting it.
Per the latest Playbook, there’s much work to be done as fraud, waste and abuse (FWA) is “costing surveyed firms nearly 12 percent of their annual revenues. The problem is so rampant that insurers have flagged or investigated nearly 40 percent of provider post-payment claims and 25 percent of consumer post-payment claims for FWA during Q1 2021.”
Word is spreading fast, but per the Playbook, “Only 11 percent of surveyed firms are currently using AI systems for individual claim editing and waste and abuse detection, and only 1 percent to 2 percent are using them for individual claim fraud detection, despite the magnitude of the problem. Twelve percent of firms are using AI to detect and address FWA overall.”
The new AI In Focus: Targeting Fraud, Waste And Abuse In Healthcare study spotlights how use of AI needs to be more advanced than the many less effective in-house solutions out there.
“The majority (82 percent) of surveyed healthcare firms today rely on rules-based algorithms to manage FWA-related challenges,” researcher found. “Only 12 percent of respondents are currently using AI systems to detect and address FWA, despite these systems’ many benefits. That cannot be said for larger firms surveyed. Our research shows that 44 percent of respondents that generate more than $1 billion and 36 percent that generate between $500 million to $1 billion in annual revenue use AI-powered systems.”
Additionally, 86 percent of surveyed firms using AI to detect FWA relating to claim payments have developed their systems in-house. “Larger respondents are more likely to develop systems in this way, with all firms in our sample generating $500 million or more in annual revenue doing so. Smaller firms that generate less than $500 million in annual revenue, meanwhile, more commonly seek outside help for deploying AI.”