The United States Treasury Department is turning more to artificial intelligence (AI) to fight fraud, using the technology to thwart 4bn in improper payments in the last year. The agency released the estimate in a press release Thursday announcing the success of its "technology and data-driven approach". In fiscal year 2024, which ran from October 2023 to September 2024, the Treasury used machine-learning AI to halt 1bn in cheque fraud, it said. At the same time, its AI processes helped weed out 3bn in other improper payments, including by pinpointing at-risk transactions and improving screening, it added. The 4bn total annual fraud prevention was six times higher than that captured in the previous year, according to the agency.

Is CDI about to embark on a long journey to reinvent Itself? There is no arguing that artificial intelligence (AI) and natural language processing (NLP) are making inroads in the healthcare revenue cycle, creating better efficiencies with the automation of a multitude of historically manually performed tasks, thereby reducing positions that were once performed by staff. AI is clearly beginning to take hold and make significant inroads in the clinical documentation integrity (CDI) space. I have noticed serval posts on LinkedIn, as well as in Becker's Healthcare e-newsletters, discussing the role of AI in the revenue cycle. Just recently, there was a blog post published in KevinMD titled "How an AI bot transformed my EHR experience (KevinMD blog)" centering on how AI streamlined the provider's documentation and charting in the electronic health record (EHR) by scanning through the documentation as the note is being completed, providing suggested diagnoses with associated ICD-10 codes.

On October 22, 2019, the Centers for Medicare and Medicaid Services ("CMS") issued a Request for Information ("RFI") to obtain input on how CMS can utilize Artificial Intelligence ("AI") and other new technologies to improve its operations. CMS' objectives to leverage AI chiefly include identifying and preventing fraud, waste, and abuse. The RFI specifically states CMS' aim "to ensure proper claims payment, reduce provider burden, and overall, conduct program integrity activities in a more efficient manner." The RFI follows last month's White House Summit on Artificial Intelligence in Government, where over 175 government leaders and industry experts gathered to discuss how the Federal government can adopt AI "to achieve its mission and improve services to the American people." Advances in AI technologies have made the possibility of automated fraud detection at exponentially greater speed and scale a reality. A 2018 study by consulting firm McKinsey & Company estimated that machine learning could help US health insurance companies reduce fraud, waste, and abuse by $20-30 billion.