Busted by “Big Data”

A couple of weeks ago, The New York Times published a really terrific article about how companies like Target use “Big Data” to identify what its customers are likely to want to buy, so the company can customize its marketing efforts precisely. Target’s gotten so good at doing this that it can even gauge what trimester of her pregnancy a potential customer is in, then mail her customized coupons.

Wow, man.

Welcome to the age of Big Data-the shorthand term for new trends in technology that shine a bright light on the path to better understanding our world and making savvier decisions about it. Big Data is a new class of economic asset, like oil or gold.

As healthcare professionals and consumers, we all experience the power and promise of Big Data, whether we fully realize it or not. Consider, for example, Big Data from healthcare claims, which is used to negotiate third-party-payer contracts and to set insurance benefit levels throughout the U.S.

Or, consider the potential predictive power of Big Data in managing public health. Researchers have found, for example, a spike in search-engine requests for terms like “flu symptoms” and “flu treatments” a couple of weeks before there is an increase in flu patients coming to hospital emergency rooms in a region (and emergency department reports usually lag behind visits by two weeks or so).

On some level, we are all aware of the importance and power of Big Data in influencing a range of healthcare activities and decisions.

Well, almost all of us, that is.

Last week, six people were arrested near Dallas, Texas, on charges related to their alleged participation in a nearly $375 million Centers for Medicare and Medicaid Services (CMS) billing-fraud scheme. According to the indictment, Dr. Jacques A. Roy of the company Medistat and his co-conspirators ran a well-organized enterprise in the Dallas area, making millions by recruiting thousands of patients for unnecessary home health services, and billing CMS for those services.

Apparently, these folks were so busy bilking CMS and the American taxpayers out of millions of dollars that they were blissfully unaware of the power of Big Data to detect their crimes.

“Using sophisticated data analysis, we can now target suspicious billing spikes,” said Health and Human Services (HHS) Inspector General Daniel R. Levinson in an Associated Press report. “In this case, our analysts discovered that in 2010, while 99 percent of physicians who certified patients for home health signed off on 104 people or fewer, Dr. Roy of Medistat certified more than 5,000.”

Perhaps a visual would have helped Dr. Roy and his bandits to see the error of their ways.

suspicious billing spike

(Or maybe not…)

In June 2011, CMS suspended provider numbers for Dr. Roy and Medistat based on suspicions of fraud, thus ensuring that Roy did not receive payments from CMS. Immediately after the suspension, nearly all of Medistat’s employees started billing CMS under the provider number of a business called Medcare HouseCalls, whose certifying physician was…yup: none other than Dr. Roy.

If it were raining brains, this group wouldn’t get wet. Clearly, they didn’t use the spoils of their crime to buy a “Big Data Clue.”

It is reassuring to know that the feds are monitoring data for this type of fraud, but I am anxiously awaiting the day when these systems, having learned from the patterns in Big Data, can significantly speed up the process: this outfit had been in business since 2006.

It’s true: Big Data is a new class of economic asset, like oil or gold. It can catch thieves, predict an influx of flu patients, and-yes-identify and precisely market products to pregnant women!

Check out a few more examples on my blog: you’ll be amazed at the promise of Big Data to change the management and delivery of healthcare services…and our lives.

This Post Has One Comment

  1. Duncan Williamson

    I have just found your blog via a post on twitter and I have to say it’s a very rewarding experience.

    The bullet graph is new to me and I like the idea of the table lens. I am trying to learn more but a dodgy internet connection is slowing me down. I will return!

    However, I’d like to comment on this page Busted by “Big Data”. As a long time medical professional, you might well know this story: possibly the world’s biggest serial killer is a British Doctor, Harold Shipman, who was charged with the murder of 215 or so of his own patients. In reality the number is probably far higher but the data became murky. It is very sad that this man refused to acknolwedge his crimes even after he’d been found guilty and thrown in prison. Moreover, coward that he was, he hanged himself whilst in prison.

    The point of this story is that Shipman was not caught by big data or anything like it: in fact, he was investigated by the medical profession a few years before he was finally caught and exonerated. More people died following that big mistake.

    Because the data communication systems in British medicine were clearly not advanced enough, this man went on murdering over his entire career and he was in his late 50s when he died.

    So how was he caught? He was caught when taxi drivers in the town in which Shipman worked finally said, isn’t it time that Shipman was investigated as we really cannot go on sending more and more taxis to take people to funerals of his patients!! No other doctor has so many dead patients, they said!

    Eventually the message got through and he was found guilty and imprisoned. A tragic story.


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