19 July The False Positive Problem July 19, 2016By Jon Coss - Blog Manager government fraud prevention, program integrity composite indicators, false positivies, fraud, fraud detection, improper payments, intelligent analytics 0 Last year, 60 Minutes did a segment on the impact of errors in the Social Security Administration’s Master Death File—a database that stores dates of death for Americans. The system stores 86 million records, and despite all best efforts, it still has some issues.60 Minutes pointed out that errors in the system contribute to millions of dollars in improper payments each year. After all, the system would seem to indicate over 6.5 million Americans over the age of 111 when, in fact, there are probably fewer than 100. On the other hand, false positives where people find themselves mistakenly placed on the list, lead to nightmarish scenarios for obtaining loans, opening bank accounts, and other everyday tasks.This story demonstrates one of the largest challenges for government agencies: how to use imperfect data sources to minimize fraud, waste, and abuse while also not “harassing” legitimate people and businesses. And unlike a private business that may view a false positive as an inconvenience (who hasn’t had to call their credit card company to say that “yes, that large ice cream purchase was legitimate”), government officials are severely criticized when they act on false positives. In effect, they are criticized for not acting and they are criticized for acting.Pondera suggests that governments mitigate the effects of false positives by using composite indicators that draw information from multiple sources—both simple data matches like the Master Death File and more complex behavioral sources. For example, a Medicaid investigator would feel much more confident looking into a person who not only shows up on the Master Death File, but also appears to be traveling 100 miles for 20-minute doctor appointments, receives highly unusual (and expensive) procedures for their apparent diagnosis, and often sees two doctors in distant cities on the same day.Anyone who has worked for or with government program integrity units understands the unique pressures they face. Combining available data sources with intelligent analytics can go a long way toward helping them investigate the right cases while not interfering with program delivery. Related Posts The Problem With Knowing What You Know I bet you cna’t bvleiee taht you can uesdtannrd waht you are rdnaieg. Unisg the icndeblire pweor of the hmuan mnid, aocdcrnig to rseecrah at Cmabrigde Uinervtisy, it dseno't mttaer in waht oderr the lterets in a wrod are, the olny irpoamtnt tihng is taht the frsit and lsat ltteer be in the rhgit pclae. The rset can be a taotl mses and you can sitll raed it whoutit a pboerlm. Tihs is bucseae the huamn mnid deos not raed ervey ltteer by istlef, but the wrod as a wlohe.The preceding paragraph, which has made its way around the Internet for years, can be really fun to share with friends. However, it also serves as a caution to anyone involved in fraud detection. In many ways, bad actors, knowingly or unknowingly, have depended on how the human mind works to perpetrate fraud schemes. Like the old expression goes, sometimes the best place for fraud to hide is in plain sight.This is especially true in government programs that process massive amounts of transactions and must adhere to a staggering number of program regulations. Traditional “top down” systems can analyze large data sets and find nothing wrong (after all, the first and last letters are in the right place). “Bottom Up” systems, on the other hand, will identify individual problems (the word is scrambled) but may miss the patterns in the data (this entire paragraph is scrambled). A common example of this is the medical provider that always “flies just below the radar” by maximizing claim amounts and frequencies.The best detection processes take both a “top down” and “bottom up” approach. They can identify individual transaction problems as well as identify patterns of bad behavior over time. In this way, you can make the old “80-20” rule work in your favor. 80% of improper payments are likely caused by 20% of program participants. If you only address each individual transaction, you’ll never run out of work but you also never really improve your program integrity efforts.Click here for an infographic on the "80-20 rule". New Age of Identity Theft Problems Remember back to last year when the IRS announced that cyber thieves stole personal data from 100,000 taxpayers? This sophisticated scheme accumulated personal data from other sites and used it to answer identity validation questions on the IRS web site to gain access to taxpayer accounts.The 100,000 taxpayers affected? The IRS revised that number later in the year to 334,000 Last week they raised the number again to more than 700,000! Combine this with the high-profile hacks at Sony, Target, Anthem, and other organizations and one thing becomes very clear: bad actors are rapidly improving their identity theft methods.In response, government agencies need to prepare for an onslaught of fraudulent tax returns, unemployment claims, Medicaid treatments, and other services. In 2015, the IRS paid out $5.8 billion in fraudulent returns. Several of Pondera’s clients also saw dramatic increases in “ghost” beneficiaries, often paired with fictitious businesses, set up solely to defraud government programs. 2016 promises to be even more problematic.As program integrity experts, we have to recognize that we are moving into a new age of identity theft problems. We can log on to YouTube and watch a music video about Unemployment Insurance Fraud. CNN has run stories on street gangs trading liquor store holdups for benefits fraud. The barbarians are at the gate and it’s our responsibility to strengthen the defenses. New Data on Problematic Government Programs One of my favorite websites, paymentaccuracy.gov, has received a number of updates which may provide some insight into the current administration’s priorities. If you haven’t done so already, I encourage you to visit the site as it provides improper payment information on the government’s high-priority programs: those that report over $750 million of improper payments in a year or have not established or reported on their error rates.The current version of the site includes many of the usual suspects including Medicaid ($36.3 billion in errors), Medicare fee-for-service ($41.1 billion), and the Earned Income Tax Credit ($16.8 billion with a whopping 24% error rate). SNAP continues to be listed but still does not provide relative numbers because of inaccurate state reporting—something we have discussed in previous posts.Other items of note are the inclusion of three Veterans Affairs programs for Disability Compensation, Community Care, and Purchased Long Term Services and Support. While the .59% error rate on the $64 billion Disability Compensation plan appears surprisingly low, the 75.86% error rate for the $4.7 billion Community Care program is likely the result of new reporting requirements… at least I genuinely hope so.Other high error-rate programs include school nutrition services (both breakfast and lunch), student loan programs, and Unemployment Insurance which ticked up to 11.65% this year.Regardless of political leanings, I think we can all agree that we want our tax dollars going to those who need them the most. And the transparency provided by paymentaccuracy.gov is a great step toward this goal. My hope is that the government will continue to provide easy access to this information. I am still disappointed each time I visit the expectmore.gov website (which reports on program performance, not just fraud, waste, and abuse) where I see the following message:“Expect More.gov was an initiative of the George W. Bush administration. This website has been archived and is posted here as an historical resource. It has not been updated since the end of 2008 and links to many external websites and some internal pages will not work.” Fraud, Waste, and Abuse Standards One of my colleagues recently returned from a conference on government program integrity with an interesting anecdote. He recounted a vendor presentation where the speaker was touting a 52% accuracy rate in their fraud lead generation system. So… nearly half of the system’s leads generated false positives. Not so sure I’d brag about that.High false positive rates lead to wasted investigative time and money and unwarranted intrusions into the lives of legitimate program beneficiaries and service providers. Ultimately, they lead to a lack of confidence in the system itself and investigators revert back to more manual detection methods. When one considers all the important services governments deliver and the immense political pressure they endure, this is obviously not acceptable.Shortly after hearing this story, we were asked to respond to a question about false positive rates and any existing industry standards or even benchmarks. While every vendor, including Pondera, makes claims about our system efficacy, very few standards actually exist. Conversely, our clients (the government program administrators) generally are subject to improper payment standards placed on them by the federal government.I think there is a great opportunity, even responsibility, for governments to create these standards. Fraud detection standards would challenge the vendor community to “put up or shut up”, leading to more innovation. They could also be adjusted as the standards are met and surpassed leading to constant improvement. And they would provide governments with a uniform method for measuring vendor performance.It is true that fraud detection systems still rely on quality program data and can suffer from the old adage "garbage in, garbage out”. So government would still share in the responsibility of meeting any new standards. But clearly, there is more we can do. And this would benefit all parties involved… except, of course, the fraudsters. Largest Health Care Fraud Bust in History Last week, the Department of Justice announced that they had made the largest “National Health Care Fraud Takedown” in history. In all, the DOJ brought charges against 412 people in 30 states responsible for $1.3 billion in false billings. Those charged included 115 doctors, nurses, and other licensed health care providers.Many of those busted included operators of clinics that were alleged to be illegally distributing prescription opioids—a subject that we address all too often in this blog. One Houston clinic simply sold the opioids to a room packed full of addicts and drug dealers. Another clinic in Palm Beach, FL recruited addicts by offering them drugs and visits to strip clubs. There were even cases of single doctors prescribing more medications than entire hospitals.In their press release, the DOJ points out that 59,000 Americans died last year from opioid related drug overdoses. Many of these were from prescription opioids. This is clearly a growing problem in our country and we applaud the DOJ, HHS, and law enforcement for their efforts in this takedown. This, and similar busts, should send a strong message to the bad actors in America’s health care system.It is important to note, however, that we still have a lot of work ahead of us. As large as these takedown numbers are, one must consider that they still represent only a small percentage of the problem. The government’s own Paymentaccuracy.gov website assigns $96 billion per year in overpayments for Medicare Fee-for-Service, Medicaid, Medicare Advantage (Part C), and the Medicare Prescription Drug Benefit (Part D). So even if all of the $1.3 billion from this bust was falsely billed in one year (which it wasn’t), it would still represent only 1.35% of the total estimated problem.I, for one, am hoping that this is simply one of many steps in the right direction. 36% of Lifeline Recipients Can’t be Validated Another federal subsidy program is garnering congressional attention for large amounts of fraud, waste, and abuse. This time it’s the Lifeline program that provides discounts to low-income households for home or wireless telephone and broadband service. This program, which many Americans have likely never heard of, distributed $1.5 billion in subsidies to 12.3 million households in 2016.The problem is that a recent study by the General Accounting Office (GAO) could not confirm the eligibility of a whopping 36% of program beneficiaries. The surprising part of this is that validating eligibility is as straightforward as checking an applicant’s enrollment form against a qualifying benefit program, such as Medicaid-- if someone has already been deemed eligible for Medicaid, then they are also eligible for Lifeline.It is also troubling to note that the 84-page GAO report comes after a 2010 study that found problems with the program and led to a number of recommended reforms in 2012. Fast forward five years to today, and the problems persist.Fraud in Lifeline stems from several factors common to most government programs: pressure to distribute timely benefits, a lack of effective data matching, and service providers (in this case telecommunications carriers) that benefit from a lack of control. The GAO actually called this last one out in their report when they explained that “companies may have financial incentives to enroll as many customers as possible” despite questionable eligibility.None of the problems outlined in the report are particularly difficult to solve from a technical standpoint. But turf battles often lead to data sharing problems that lead to eligibility validation issues. And an unwillingness to enforce fraud reforms on businesses provides them with incentives to simply “look the other way”. Multiply this problem over the 2,300 federal subsidy programs operating today, and this adds up to a lot of money, all lost due to fraudulent, wasteful behavior. Comment (0) Comments are closed.