An unprecedented, coordinated healthcare fraud takedown highlights the power of collaboration and data sharing among government agencies and private insurers to combat increasingly sophisticated fraud schemes
Key insights:
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Coordinated investigations boost detection — The recent operation formed a fusion center in which data was shared and compared, enabling earlier and more effective identification of fraudulent patterns.
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Advanced analytics uncover complex schemes — Fraudsters allegedly used hundreds of shell companies to mask illicit activities, complicating detection, but analytics platforms leveraging third-party data help identify anomalies.
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Multi-entity collaboration is essential — Broader cooperation and data sharing across entities increase the likelihood of timely detection and enforcement actions.
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State and federal prosecutors recently charged more than 320 people for $14.6 billion in false claims in what is described as the largest coordinated takedown of healthcare fraud schemes in the history of the U.S. Department of Justice.
The key word here is coordinated. Traditionally, Medicare, Medicaid, private insurers, and other organizations have tended to investigate fraud in isolation. Each agency or carrier worked its own pipeline — reviewing claims, generating leads, and pursuing cases on its own.
Fraudsters, meanwhile, are more equal opportunity exploiters, often spreading their tentacles across numerous targets. This not only increases their total potential illicit gains, but it also reduces their detectable footprint within any single target. In schemes that sprawl across multiple targeted entities, even if the fraudulent activity is discovered, each target only sees a slice of the total picture.
This recent operation completely flipped that script. The organizations that were targeted for fraud formed a fusion center that shared and compared data. While each individual organization carries its own unique vulnerabilities, the more data that’s shared between more parties, the more likely that patterns can be identified or that perpetrators will hit a trip wire somewhere along the way in one of the targeted organizations and be detected.
The goal of such coordination is to spot fraud as early as possible, before it has a chance to permeate more deeply into each affected organization. Even with coordination, the challenge remains to detect sophisticated fraud before it balloons into multi-billion-dollar losses. The $14.6 billion figure likely reflects activity that went undiscovered for years.
Early detection is key
In many of these types of fraud schemes, there are massive numbers of dots to connect and threads to follow. In this recent takedown, fraudsters had allegedly set up hundreds of shell companies to mask their illicit transactions, which intentionally made it difficult to trace the fraud back through the shadow businesses to the individual perpetrators.
Advanced analytics platforms that leverage third-party data can help spot these suspicious patterns. And the more entities and more data that these platforms have to work with, the greater their ability to spot anomalies through analysis, such as:
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- Risk scoring — Assigning fraud-specific risk ratings based on abnormal billing patterns, outlier service volumes and geographic spikes
- Entity resolution — Linking providers, clinicians, and business owners to spot potential shell companies
- Ownership mapping — Uncovering hidden relationships among entities registered in different states or countries
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Yet, even with advanced analytics and other data sources, detecting fraud and piecing together the multitude of disparate leads that could potentially point back to the perpetrators is a daunting task. Further, the government agencies and private insurers involved both make extensive use of contractors, which, on the one hand, can add another layer of complexity, but at the same time, these contractor networks can also provide additional resources and data for spotting fraudulent patterns.
As the recent takedown demonstrates, it’s difficult for any single entity to handle this by themselves. For example, the alleged fraudsters in the recent takedown reportedly used entities spread across multiple countries. So, the wider the net is cast, the more likely it is to get better, faster results that can lead to enforcement actions.
Coordinating learnings to assist prevention
While it’s vital to analyze cases after they’re successfully concluded to better identify and correct weaknesses and vulnerabilities and to prevent fraud from recurring, it’s equally important for agencies and organizations to find out what went right and share best practices.
While one organization may fall victim to a fraud scheme, another organization may find that they managed to partially or completely deter the same scheme. By comparing notes along with data, organizations can see which policies, procedures, or technology solutions specifically either enabled or deterred the fraud.
Then, policies and procedures can be reshaped based on what other agencies or carriers are learning in real time as they deal with fraudsters. When organizations share datasets, a suspicious provider or transaction that is flagged by one organization can immediately trigger alerts across the coordinated agencies and carriers. Even if organizations have dissimilar systems or datasets, they can share best practices and adopt similar data taxonomies to make sharing of data easier.
Even if an organization isn’t part of a multi-agency task force, the principle holds: The more you break down silos — between departments, between payers, and between public and private sectors — the faster organizations will be able to spot patterns that might otherwise get missed, enabling earlier detection and faster action.
The extent and breadth of the recent takedown — from bogus wound-care supplies to illegal pill mills, fraudulent catheter claims, and more totaling billions of dollars — underscores how fraudsters will seek to exploit every vulnerability and loophole they can find. At the same time, the successfully coordinated crackdown demonstrates how collaboration, data sharing, and the right technologies can help organizations and agencies turn the tide.
You can find out more about the ongoing fight against medical fraud here
