Fraud, waste, and abuse (FWA) are a pervasive challenge in our society, across both public and private sectors. It is a complex and extensive problem in the healthcare sector that requires innovative, robust solutions that can both mitigate and stay ahead of FWA. The COVID-19 pandemic has only emboldened scammers seeking to defraud healthcare driven government agencies, organizations, programs, and consumers. Recently, the Federal Bureau of Investigation (FBI), Department of Health and Human Services Office of Inspector General (HHS-OIG), and Centers for Medicare & Medicaid Services (CMS) have engaged in efforts to make the public more aware of several types of FWA in public health programs, including Medicare, Medicaid, and the ACA (Affordable Care Act) Exchange Marketplaces. Undetected FWA needlessly inflates government healthcare program costs, which squanders hard-earned taxpayer dollars.
The sheer volume of healthcare claims, clinical records, reimbursements, and other data flowing in and out of healthcare programs makes detecting FWA extremely challenging, resource intensive, and costly. For example, Medicare now processes and pays an estimated 4 million Medicare Fee-For-Service (FFS) Claims per day and almost 1 billion claims annually. But of the claims processed and paid every year, fewer than 3 tenths of 1 percent receive any form of medical record review, making it hard to efficiently detect improper payments, provider/supplier errors, and non-compliance with rules and accepted practices on a large scale. Solving these FWA “big data” challenges requires smart solutions that combine data science expertise with accurate, relevant data, and innovative advanced analytics techniques, such as artificial intelligence and machine learning (AI/ML), and analytics process automation (APA).
How can harmful schemes be detected and stopped before they negatively impact the financial stability, service quality, and outcomes of public healthcare programs? Chief Information Officers (CIOs) and Chief Artificial Intelligence Officers (CAIOs) at U.S. federal government agencies are working with technology companies that can provide advanced analytics, and analytics process automation (APA) solutions to successfully detect FWA activities, actors, patterns, anomalies, and errors in payments, claims, and other components of government healthcare programs. The evolution of these emerging technologies, aided by high processing power, is empowering government agencies and other organizations to hone their FWA detection and improve mitigation efforts to achieve better outcomes.
The driving technical force in the quest to reduce FWA is the capability to deploy effective advanced analytics combined with a robust technology platform that can automate the process of ingesting, mapping, integrating, normalizing, and analyzing structured and unstructured “big data” from a variety of sources. Leveraging powerful analytics techniques, such as artificial intelligence, machine learning, predictive modeling, convolutional neural networks, natural language processing, and deep learning algorithms enables agencies and organizations to increase their ability and timeliness to detect FWA, including instances that had previously been undetectable.
Reveal applies sophisticated analytics expertise and techniques, combined with robust APA and other technology products, to solve complex, real world challenges while embracing open-source, technologically agnostic, agile development principles. We streamline and automate labor intensive analytics processes, eliminating thousands of hours of tedious tasks, such as conducting manual FWA audits. Our solutions can tremendously expand FWA and non-compliance audit coverage and detection, compared to limited, randomly selected reviews that leave millions of dollars subsumed by FWA.
Our clients value our expertise and advanced analytics solutions because we use quality data, innovative online analytical processing, data mining, complex event processing, business performance management, benchmarking, text mining, predictive analytics, and prescriptive analytics, among other techniques, that deliver actionable results. Our solutions utilize creative and effective techniques that agencies and organizations need to interpret and leverage large volumes of disparate data and formats to make processes more efficient, produce better, cost-effective outcomes, and improve decision-making.
Facing a tough big data problem in your agency or organization? Contact Reveal to learn how we can help.