Healthcare fraud is a national problem, prevalent in federal and state, as well as private insurance programs. Over the last decade, healthcare fraud has skyrocketed with billions of dollars being paid on improper claims. The National Healthcare Anti-fraud Association conservatively estimates that three percent of all healthcare spending, or $60 billion, is lost to healthcare fraud. Other estimates place this number closer to $200 billion.
The increased incidence of identity theft is another major problem – more than 1.5 million people have been victimized by medical identity theft at an average cost of $20,000 to the victim. These statistics represent avoidable healthcare costs that directly impact the cost and quality of healthcare for every American. Healthcare fraud, waste and abuse (FWA) not only contributes to higher insurance premiums; every dollar spent on fraudulent or abusive claims reduces the amount of money available to improve the quality of care for those incurring legitimate expenses.
Now more than ever, the healthcare industry must migrate to a fraud control model that integrates fraud prevention and detection at the front-end of the payer workflow, applies analytic controls throughout the workflow, and incorporates post-pay detection and recovery processes at the back-end of the work flow. Claims review processes that incorporate rules-based data analytics, predictive modeling, and linking technologies allow commercial and government payers to identify fraud before an ineligible claim is paid. Effective fraud detection is best achieved through a layered approach to claims analysis, including identity analytics, claims analytics (predictive modeling and rules-based fraud detection), and social network analytics.
As schemes and various provider technologies become more complex, healthcare organizations need to create wide-reaching FWA prevention programs that address the overall problem more holistically. By combining identity and entity resolution, rules-based claim and clinical review, complex linking analysis and predictive analytics into a seamless workflow, we will come closer to migrating an integrated pre-pay fraud solution to a real risk control environment with the potential to eliminate billions of dollars in improper payments due to FWA. This is not just a healthcare imperative, but a national economic imperative that must be addressed immediately. The analytics exist. It is time for those analytics to be implemented and the hard choices that enable that implementation to be made to insure that we remain at the forefront of quality care for all Americans.