Healthcare fraud in the post-honesty world

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What does it mean for healthcare fraud when honesty is pushing up daisies?

Healthcare fraud is alive and well. Honesty is dead and gone. There, I’ve said it.  What else are we to take from surveys that find that 27% of people would sell their work passwords...44% of them for less than $1,000?* What does it mean that 37% of survey respondents think lying on a resume is fine, and 24% of men support cheating on your taxes?**

We're in the midst of International Fraud Awareness Week, which is about finding solutions to fraud. So we don’t have time for honesty's eulogy now, but acknowledging our loss is the first step to moving on. It’s time to do something about it.

Experts look to others in their field to learn, test ideas and share methods.  That approach is a best practice, and one I strongly support.  But, in a post-honesty world, threats are everywhere.  Learning from other industries and adapting their methods to healthcare fraud risks is past due.

Government has seen attacks increase dramatically with the rise of identity theft.  Government tax and benefits programs are now the second highest use of stolen identities behind banks.

Insurance companies have learned to partner with their competitors when fighting fraud, forming consortia to share data on high risk claims and claimants.

Show me the money

Taking a page from banking, look at anti-money laundering (AML) efforts.  At a basic level, it's about ownership of accounts, connections between ownership, and  money flows.

In healthcare, experts regularly look at connections between patients and providers, referring providers and pharmacies.  But, we typically ignore where the money is deposited.  Diving into details on money flows can easily make previously unknown connections.

Ghost in the machine

Government tax agencies have learned from fighting identity theft that machine generated data is vital to analysis.  Machine generated data ranges from the IP address of tax returns filed online, to the exact time stamp that return was received.

Healthcare agencies can learn a lot from their brethren in tax agencies, which are becoming masters of fraud detection, thanks to analytics.

Healthcare organizations tend to ignore this data, or don't have access to it for fighting fraud.  Analysis of this data can make a leap forward in the post-honesty world:

These ideas are just the beginning.  Look beyond your own walls.  Think about how Visa, or Geico, or Amazon, are fighting fraud today.  Those ideas can be turned back towards healthcare.  They are the core of using analytics and machine learning to stem the tide in the post-honesty world.

*Based on a 2016 SailPoint survey
** Based on a 2018 poll by YouGov and Y2 Analytics
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About Author

Carl Hammersburg

Manager, Government and Healthcare Risk and Fraud

Carl Hammersburg manages the SAS Government and Healthcare Risk and Fraud team, and has been with SAS since 2012. Prior to that, he spent 20 years in anti-fraud activities for Washington State’s exclusive workers’ comp insurer, the Department of Labor and Industries. In 2004, Carl formed that agency’s comprehensive fraud program, covering tax and premium audit, claim investigation, provider fraud and collections. Data sharing and investigative partnerships with other State and Federal agencies, as well as driving public availability of information and awareness served as cornerstones to the anti-fraud activities of the program. During his stewardship, audit and investigative activities doubled and outcomes tripled, based on a focus on data mining and predictive analytics that improved efficiency and case selection. Program success under Carl’s leadership resulted in awards from two successive Governors of Washington State.

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