Why Excel isn’t the solution for health care fraud, waste and abuse investigations

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Regardless of how you feel about spreadsheets, you need powerful analytics to uncover health care fraud. Image: https://www.flickr.com/photos/craigmoulding/8399214678/

Regardless of how you feel about spreadsheets, you need powerful analytics to uncover health care fraud. Image: https://www.flickr.com/photos/craigmoulding/8399214678/

To prepare for the data challenges of 2015 and beyond, health care fraud, waste and abuse investigative units (government funded and commercial insurance plans, alike) need a data management infrastructure that provides access to data across programs, products and channels.

This goes well beyond sorting and filtering small sets of data, which is what Excel is designed to do. Yet many, I would say most, organizations rely on Excel as a solution for healthcare fraud, waste and abuse investigations.

Why is this true?

Many believe they cannot afford a more robust solution, typically because they have been misinformed about expensive database overhauls. Despite what many may think, moving toward a data management foundation and applying advanced data analytics on top of it, doesn’t require a database overhaul; rather, it requires a data integration layer that can source from databases around the organization, business partner organizations, social media outlets, and from external public or purchased data.

Unscrupulous providers and suppliers will sometimes intentionally provide inaccurate, incomplete or inconsistent information to prevent records matching across disparate systems. In many other cases, matching is hindered by a lack of data sharing agreements between agencies. This prevents government-funded and commercial plans from introducing data quality capabilities that support entity resolution. For example, entity resolution would reveal that William T. Jones in one system is the same person as William Taylor Jones in another.

Since the devil is in the details, the data management, integration, and quality infrastructure must be supported by a robust business analytics foundation. To make proper use of internal and external data sources, the business analytics foundation must have a variety of analytic “arrows” in its quiver. It can deploy multiple processes that identify suspicious patterns that could point to programmatic fraud, waste, or abuse.

Time is money, and in this new payment frontier, government-funded and commercial plans need an infrastructure designed to stop the improper payments, instead of chasing them down after the money is long gone.

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About Author

Ricky D. Sluder, CFE

Principal Solutions Consultant

Ricky D. Sluder, Certified Fraud Examiner, is a Principal Solution Architect in the Security Intelligence Practice at SAS. He has ~20 years of investigative experience in white collar crime, Medicare and Medicaid fraud, waste and abuse. In 2012, five major cases identified under his investigative/data analytic operational model resulted in DOJ criminal prosecutions exceeding $846 million in fraud.

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