Editor’s Note: In a recent webinar for Bloomberg BNA, Manatt examined game-changing fraud and abuse trends and cases and revealed strategies for avoiding False Claims Act (FCA) actions. In November, we kicked off our three-part series summarizing key insights from the program with an article exploring the current state of play—and the definition of what a false claim looks like in 2017. This month, we reveal the innovative and aggressive enforcement techniques making the healthcare landscape more perilous than ever before in history. Watch for the conclusion of our series in January, explaining how to build an effective compliance program, as well as providing practical recommendations for preparing for and responding to government inquiries.

To view the full webinar free on demand, click here. To download a free copy of the presentation, click here.

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The Brave New World of Data Analytics

In the context of enforcement, data analytics means using data collected by the Centers for Medicare & Medicaid Services (CMS) to evaluate trends and discover suspected fraudulent patterns. The use of data analytics was authorized in 2010, when Congress mandated that the Department of Health and Human Services (HHS) identify fraud using predictive modeling (Section 4241 of the Small Business Jobs Act). Since June 2011, CMS has used the Fraud Prevention System on all Medicare fee-for-service claims on a streaming, national basis, using predictive modeling and building profiles of providers, networks, billing patterns and beneficiary utilization to create risk scores and flag potential fraudulent activity. This approach generates leads that trigger administrative actions before payments are released, enabling CMS to move away from the “pay and chase” model and take action more quickly.

Federal authorities have been highlighting the benefits of data analytics as an enforcement tool. In May of this year at the American Bar Association 27th Annual Institute on Healthcare Fraud, Acting Assistant Attorney General Ken Blanco said:

“… In addition to many traditional methods for developing information and evidence, the Strike Forces are using highly advanced data analysis to identify aberrant billing levels in order to target suspicious billing patterns and emerging schemes. More specifically, the Medicare Fraud Strike Force is obtaining billing data for CMS in real time. We now have an in-house data analytics team headed by some of our best and brightest. Analyzing billing data from CMS has become a key part of our investigations because it permits us to focus on the most aggravated cases and to identify quickly emerging schemes and new types of Medicare fraud. Access to CMS billing data in close to real time permits us to remain a step ahead. We have the opportunity to halt schemes as they develop. This cutting-edge method has truly revolutionized how we investigate and prosecute healthcare fraud.”

There are a few key takeaways from AAG Blanco’s statement. First, it highlights that the billing data from CMS is available in virtually real time. Second, it stresses that the focus is on the most aggravated cases. Third, it points out that data analytics are used in conjunction with other investigative tools, including more traditional methods.

Ken Blanco is not the only federal authority speaking about the power of data analytics. Andrew Weissman—who recently headed the Fraud Section of the Department of Justice (DOJ)—also stressed the value of data analytics at the October 2016 Healthcare Compliance Association’s Healthcare Enforcement Compliance Institute:

“Data isn’t everything but, in terms of getting leads, data is fantastic and unique … HHS and DOJ have gotten better at how we use data … [Both agencies] have Ph.D.s on staff to mine data and find links and leads. We can take data and make it incredibly granular, breaking it down by state and city.”

In addition, in his report to Congress justifying a $419 million budget for fiscal year (FY) 2017 for the HHS Office of the Inspector General (OIG), Inspector General Daniel Levinson reinforced the importance of data analytics, noting, “In FY 2017, OIG will incorporate additional data analytics to increase insights and capabilities for assessing performance outcomes. OIG will use these metrics to conduct performance reviews and data analysis around key performance indicators to increase our effectiveness in HHS program oversight and contributions to mission results.”

In his statement, Levinson pointed out that the insights data analytics yield are not just being used in “hot spot” areas with high incidences of healthcare fraud (such as Miami, Tampa, Los Angeles, Detroit, Brooklyn, south Texas, southern Louisiana, Chicago and Dallas). They also are being pushed out to U.S. Attorney’s Offices and investigative agencies in jurisdictions throughout the country.

In addition, State Medicare Fraud Control Units (MFCUs) are using data analytics to strengthen their effectiveness. On August 5, 2016, HHS-OIG approved the application of the New York attorney general’s MFCU to begin using data mining. Several other states recently obtained three-year renewals, including Michigan, Missouri, Oklahoma and California. Throughout the country, we are seeing an increase in enforcement activity based on data analytics.

How do investigators and prosecutors use the information from data analytics? Prosecutors get information about high-risk providers, identified as outliers when compared with their peers at the national and state levels. The data examined includes how much a provider is billing, to whom, and for which types of procedures and services. Based on that information, investigators dig deeper, through either covert or overt methods, to look for improper relationships, collusion or illegal activity.

Data analytics will play a key role in the DOJ’s new Opioid Fraud and Abuse Detection Unit. This pilot program, involving several districts across the country, will focus on using data analytics to combat the growing opioid crisis. The program will use data to identify individuals who are outliers in the distribution of opioids. For example, it will look at physicians who are prescribing opioids at an excessive level, the average age of the patients receiving the prescriptions, and the number of patients who died within a set period of time. The program also will use data to identify pharmacies that are dispensing disproportionately high amounts of opioids. The new opioid program demonstrates how much more effective investigators and prosecutors can be with data analytics added to their toolbox.

A classic example of how data analytics can uncover fraudulent behavior is the case of Dr. Boris Sachakov, a Brooklyn proctologist. Dr. Sachakov was performing hemorrhoidectomies at a rate that caused him to be the leading biller in the nation—a fact that caught the attention of investigators. When investigators examined the data on Dr. Sachakov’s procedures, they learned that he had billed for 85 hemorrhoidectomies within 20 months—and that he was billing, in some cases, for working more than 24 hours a day. In addition, they found that his procedures were more often examinations than surgeries. The claims in his case involved $22 million, of which he received more than $9 million. With the help of data analytics, Dr. Sachakov ended up spending 30 months in jail.

The Use of Wires

As mentioned above, investigations can sometimes involve covert methods, including electronic surveillance. Just this year, electronic surveillance was used in the “Operation Avalanche” case against three New York City medical clinics and 13 individuals, including physicians, for defrauding Medicare and Medicaid by billing for medically unnecessary tests. In this case, patients were induced to submit to unneeded medical tests in exchange for oxycodone prescriptions.

“Operation Avalanche” involved long-term wiretaps. Shorter-term, simpler techniques—such as sending in informants who are wired to confront an employer—are also permissible in healthcare cases.

The Debate Around Statistical Sampling

Statistical sampling has become a hotly debated issue. Statistical sampling comes into play when the government or relator attempts to prove liability or damages only for claims within a statistical sample in order to avoid a more time-intensive claim-by-claim analysis. Unsurprisingly, defendants in cases supported by statistical sampling often object vehemently. Decisions have gone both ways—and the law on this issue is in flux.

In U.S. ex rel. Martin v. Life Care Centers of America, Inc. (E.D. Tenn 2014), statistical sampling was used to establish liability for lack of medical necessity claims that, in the past, would have needed to be established by proof for each individual patient. The court allowed expert testimony to establish liability for all 154,000 claims based on 400 random samples, acknowledging that a claim-by-claim review is often impractical, and that exclusion of statistical sampling would open the door to more fraudulent activity. Since Life Care, other courts have followed suit in allowing statistical sampling to establish liability.

There are cases, however, that go the other way, with courts rejecting statistical sampling. For example, in the U.S. ex rel. Wall v. Vista Hospice Care, Inc. (N.D. Tex. 2016), the court held that individual proof per patient is required to establish liability.

Clearly, the courts are going back and forth on the statistical sampling issue. The AseraCare Hospice case in Alabama illustrates the complexity of the statistical sampling challenge. In U.S. v. AseraCare Inc., 176 F. Supp. 3d 1282 (N.D. Ala. 2016), the court had originally permitted the use of statistical sampling based on more than 200 claims. It later reversed itself, however, and dismissed the case, holding that when two or more medical experts look at the same records and reach different conclusions about whether they support a certified physician’s medical opinion on hospice admissibility, all that exists is a difference of opinion and not sufficient evidence to demonstrate falsity under the False Claims Act.

The Responsible Corporate Officer Doctrine

The Responsible Corporate Officer Doctrine states:

“[A] corporate agent, through whose act, default or omission the corporation committed a crime in violation of the [Federal Food, Drug and Cosmetic Act (FDCA)] may be held criminally liable for the wrongdoing of the corporation whether or not the crime required consciousness of wrongdoing by the agent. U.S. v. Park, 421 U.S. 658, 670 (2975)”

The Responsible Corporate Officer Doctrine should concern corporate executives—and lead them to ensure that strong compliance programs are in place in their organizations. It allows responsible corporate executives to face criminal liability for failing to prevent, or even for not promptly correcting, violations that impact the health and well-being of the public.

The Responsible Corporate Officer Doctrine has been around for quite some time, but there has not been a lot of jurisprudence around it recently. In fact, the Supreme Court recently passed on an opportunity to revisit the issue in a case out of the Eighth Circuit, U.S. v. Decoster, 828 F.3d 626 (8th Cir. 2016). In that case, the Eighth Circuit upheld a three-month prison sentence for two commercial farm executives who had pled guilty to FDCA violations, leading to the introduction of salmonella-tainted eggs into interstate commerce.

The Eighth Circuit upheld the Responsible Corporate Officer Doctrine, saying that, under the Doctrine, a corporate officer is held accountable not for the acts or omissions of others but for his or her failure to remedy or prevent the conditions that caused the problem. In other words, executives in positions of responsibility don’t have to know that their companies violated the FDCA but are required to exercise sufficient care to prevent the introduction of tainted food into the stream of commerce.

The DOJ uses the Responsible Corporate Officer Doctrine sparingly. U.S. Attorneys are required to consult with the DOJ’s Consumer Protection Branch before they bring cases based on the Responsible Corporate Officer Doctrine, and are mindful of the fact that overuse could lead Congress to examine whether changes to the doctrine are warranted.

Going After Individual Executives

Related to the issues surrounding the Responsible Corporate Officer Doctrine is the Sally Yates memo from September 2015. The memo focuses on individual accountability for criminal conduct in a corporate setting and arose out of criticisms for what some perceive to be the failure to hold those involved in the 2008 financial crisis responsible.

The Yates memo focuses on “accountability from the individuals who perpetrated the wrongdoing.” Key points include:

  • To qualify for cooperation credit, companies must provide the DOJ with relevant facts pertaining to individual culpability.
  • Criminal and civil investigations should focus on individuals from inception.
  • Criminal and civil government attorneys should be in routine contact with each other during investigations.
  • Absent “extraordinary circumstances,” DOJ will not release individuals as part of settlements with companies.
  • Corporate cases should not be resolved without a clear plan to resolve related individual cases.
  • Civil attorneys should evaluate whether to bring suit against an individual based on considerations beyond that individual’s ability to pay.

Although Ms. Yates was dismissed by the current administration, her memo and its principles are still being followed. Attorney General Sessions confirmed in an April 2017 interview that “the department will look toward charging individuals responsible for corporate misbehavior or mismanagement—and less about prosecuting the corporations, which could affect the stock price. I have always felt that having stockholders paying the price for corporate mismanagement isn’t always the best solution.”