Keeping Artificial Intelligence at the Fore to Prevent Healthcare Payment Fraud
Published on : Friday 10-04-2020
In the healthcare sector, payment fraud is one of the leading challenges for medical systems. According to the National Health Care Anti-Fraud Association (NHCAA), the financial losses due to health care fraud are in the tens of billions of dollars each year. Most health care fraud is perpetrated by a small number of deceitful healthcare providers, while in some cases, it is performed by individuals.
A 2018 AFP Survey revealed that in 2017 a record 78 percent of U.S. organizations were the target of payment fraud. The survey further found that check fraud ranked highest, as 74 percent of U.S. organizations experienced check fraud during the same period. On the other hand, 28 percent were the target of automated clearinghouse (ACH) debit fraud. Now in the current scenario, where the entire world is fighting against the pandemic of Covid-19, healthcare systems are facing an unprecedented challenge of deception.
In this way, Artificial Intelligence technology has proved to be effective. Many companies are already experiencing productive gains by using AI and machine learning techniques that are able to spot and prevent fraud in real-time. For instance, Teradata, an AI firm specialized in selling fraud detection solutions to banks, claims that it helped Danske Bank in reducing its false positives by 60% and increased real fraud detection by 50%.
Moreover, Highmark Inc.’s Financial Investigations and Provider Review (FIPR) department has said it generated $260 million in savings that would have otherwise been lost to fraud, waste, and abuse last year, according to a recent report. Additionally, the department has saved $850 million in the last five years. With the help of an internal team made up of investigators, accountants, and programmers, as well as seasoned professionals, FIPR detects fraud across its clients’ services. The team generally focused on identifying unusual activities, such as registered nurses and former law enforcement agents.
Human audits, performed to detect unusual claims and analyze the aptness of provider payments, are used as training data for AI systems that can adapt and react more rapidly to distrustful changing consumer behavior. Many other service operators are also in hunt of AI fraud detection systems, especially in healthcare space. A survey from Optum uncovered that 43% of health industry leaders reported they strongly believe AI will become an integral part of detecting telehealth fraud, waste, or abuse in reimbursement.
In fact, in many business scenarios, the use of artificial intelligence and machine learning has already recognized as powerful tools to manage such complex matters. Integrating these technologies for a payment integrity strategy into healthcare systems requires an innovative approach, which exhibits the explicit needs of an organization, and appropriate industry best practices. There is also a need for support from organizations' stakeholders while adopting AI for payment integrity initiatives successfully.
Furthermore, spending on AI technology is growing tremendously with total spending set to value $15 billion by 2024, the most sought-after solutions being network optimization and fraud mitigation.
So, artificial intelligence is very effective technology in fraud detection and mitigating risks of payment fraud within the healthcare sector, and in our perspective, the technology will increasingly be used across the sector, with many healthcare providers looking to leverage this tech.