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The evolution of data and the impact on fraud investigations

Health care companies are using data for better insights and to stay ahead of fraud.

5 min read



This post is sponsored by General Dynamics Health Solutions.

As the instances of fraud increase across the health care industry, many organizations and investigators are collecting data from various sources in order to gain better insights. Being able to collect, categorize and utilize this data remains a key method of staying ahead of fraudsters.

In this post, we talk with Mark Starinsky, Program Manager, Program Integrity Solutions, for General Dynamics Health Solutions. He’s responsible for detecting and investigating fraud, waste and abuse, as well as preventing improper payments in support of clients.

What are some of the biggest challenges facing the health care anti-fraud industry right now?

Our biggest challenge is staying ahead of the fraudsters. Three emerging areas that are particular challenges to the industry right now are the growing prescription drug abuse epidemic, the effect of health care expansion to underserved groups and the transition by health payers to value-based models.

Those raised in the 1980s were taught the dangers of street drug dealers distributing cocaine. Today, opioid abuse is not only a public health epidemic, but also an anti-fraud challenge with the proliferation of fraudulent and illegal prescriptions. Last year, the Office of Inspector General (OIG) and the Centers for Medicare & Medicaid Services (CMS) testified that between 2006 and 2014, spending for commonly abused opioids grew by 156%, reaching $3.9 billion in 2014. The OIG also identified that the number of users receiving prescriptions for these drugs rose 92% over this period. Stronger payment controls are needed to ensure that individuals have valid needs for these drugs and they are obtained from a single appropriate source. The OIG found that Part D fraud, waste and abuse controls were not in place to prevent payments for physicians excluded from Medicare or Medicaid.[1]

With more than 30 states adopting exchanges in support of the Patient Protection and Affordable Care Act, Medicaid eligibility expansion increased to more than 21 million citizens. This climb in patients and services creates potential fraud, waste and abuse challenges to health plans. With significant increases in care delivery, opportunities for dishonest providers have also increased, including a greater volume of opportunities and smaller schemes that can be spread over a wider population to “fly under the radar.”

Third, as public and private health payers move to value-based payment models, the industry is challenged to discover and understand new, unrecognized fraud schemes. These could include physician record falsification to report patient medical improvement or offers of cash kickbacks to patients in exchange for their cooperation or to accept different medical treatments.

How has data – its availability and use to fraud investigators – evolved over time?

The key here is the definition of data, which we consider to be facts and statistics collected together for reference or analysis. When I began my anti-fraud career we collected facts from individuals, word of mouth and paper-based records. Anti-fraud professionals couldn’t simply access provider and professional history via a state’s physician licensing website. Investigators often had to travel to providers’ offices, only to find out the physicians were no longer at those locations or were still practicing because the paper records hadn’t been updated. The evolution of data availability from paper to electronic access has immeasurably eased investigative challenges over time.

How do the types or complexity of available data affect their ability to aid an investigation?

Personally, my feeling is “the more data, the better.” However, you must be able to understand what you’re looking at to benefit from the data; otherwise it can complicate your investigation. To do so, you may need to bring in experts who understand the nuances of the particular data you’re examining. For example, while working for the OIG, I knew little about the billing details for a diagnosis-related group and how certain packaged billing models affected or didn’t affect an investigation. Experts can help you determine whether it matters if a particular service was provided or if it didn’t affect a payment.

Can you provide an example of the role data played in supporting an investigation you were part of? 

Data plays a critical role in all of my investigations, but as data becomes more readily available (such as the CMS’s publicly-available Medicare data) it can become easier to fully quantify dollars at risk and justify increased involvement of law enforcement. For example, I investigated a Texas-based physician who was a huge outlier within our payer’s plan, with data showing that every patient was receiving the same batch of services on a monthly basis. While this was compelling and supported with solid evidence, the dollars at risk weren’t quite high enough to justify engaging the OIG or the FBI due to cost. However, by accessing publicly available CMS data, we found that fee-for-service was also paying for the same services to the same degree. This broader view showed that the physician was a significant outlier not only from the plan but from the rest of the country for services provided or billed. Once we gathered and pooled this additional data source, the OIG accepted the case.

What do you see data formats, availability and usage looking like in the future of anti-fraud investigations?

I don’t know that I see a change in the format of data per se, but I do see data’s availability increasing through pooled data initiatives. This includes the CMS Healthcare Fraud Prevention Partnership that brings together federal, state and private partners’ data to paint a complete picture and profile of providers’ billing trends. The perfect future of anti-fraud investigations would include the capture of all billing data as well as federal, state, private, Medicare, Medicaid and auto-insurance claims, all combined with textual information from medical records and contracts and data available via social media. This complete universe of data would bring us the closest to helping ensure payment integrity.


[1] HHS OIG Data Brief, OEI-02-15-00190, June 2015