Reports show that 36 percent of all data breaches in 2015 impacted the health and medical sector. Although numerous healthcare technology advances, such as online patient portals and telemedicine visits, offer substantial benefits to consumers and providers, their virtual nature also increases opportunities for various types of fraud. Additionally, the sheer number of new entrants on health exchanges increased the potential for fraud and abuse.
When analyzing the problem of fraud, health plans should distinguish among three primary areas.
Identity fraud. The Affordable Care Act has introduced millions of new patients into the healthcare system, and more patients bring more opportunities for fraud—including additional chances for newly insured individuals’ identities to be stolen or for applicants to game the system using false identity information.
Broker fraud. The very existence of exchanges has greatly reduced the need for brokers. The shrinking demand may, in some instances, lead brokers to seek new ways to maintain income levels. As a result, there is the potential for an increase in fraudulent tactics, like enrollments of non-existent individuals using fictitious identity information; enrollments using the information of deceased individuals; and enrollments of minors without proper parental authorization.
Provider fraud. Fraudulent healthcare providers employ many dishonest tactics to create confusion around identities and the claims associated with them, including creating fake identities or using the identities of deceased individuals to submit fraudulent claims. Verifying and resolving identities can even be challenging when dealing with legitimate providers that may work in multiple locations and use multiple sets of contact information.
Healthcare organizations should consider using advanced analytics solutions to prevent and counter fraud. Here’s how.
Use technologies that help aggregate and join single patient information coming from multiple sources to prevent identity fraud.
Whether enrollments originate from an individual or a broker, the key to detecting fraudulent applications is the ability to analyze and verify the submitted enrollment data. Technology and linking analytics can compare enrollment data with vast quantities of public records data, gathered from thousands of reliable resources, to identify potential inaccuracies in the enrollment information. When suspicious enrollments are identified, they are flagged for further investigation and action.
Big data and advanced analytics can also uncover schemes and shady business relationships and help organizations better understand connections between patients, doctors, facilities and other caregivers.
Use a systematic approach to monitoring exchange broker communities for identity-based fraud.
The systematic approach includes deploying a system to automatically detect aberrations in applications, such as suspicious addresses and unknown names. The detection system can also look at brokers themselves and whether individual brokers show a spike in enrollees or a spike in commissions. These are red flags that the broker may be enrolling fictitious or potentially ineligible applicants.
After the detection stage, a systematic approach would perform checks to immediately notify other stakeholders of possible fraud and abuse. This includes alerting capability and a case tracking mechanism that can be integrated with the detection system.
The final stage would include devoting resources to analyze and investigate the output from that automated system. These resources would come in the form of data analysts, investigators and compliance auditors.
The largest benefit of a systematic approach is avoiding millions of dollars in broker commissions and federal fines while also gaining valuable insights into enrollees beyond simple verification, using data analytics to uncover other suspect activity from applicants and brokers.
Use tools that can quickly verify provider identities and recognize anomalies.
When it comes to provider fraud, health plans need to move from claim-level fraud prevention strategies to provider-level strategies using data, advanced analytics and linking tools that can verify and confirm valid provider identities and recognize anomalies that suggest errors or intentionally falsified identity data. For a complete picture, data must be gathered from multiple sources, including:
- Intra-industry contributory data—Claims data shared by many payers to compile the industry’s contributory database, such as SIRIS (Special Investigative Resource and Intelligence System), a contributory database that allows the National Health Care Anti-Fraud Association (NHCAA) members to submit, track, monitor and share information related to potential provider fraud and associated investigations.
- Shared data from other industries that may shed light on a health plan’s investigation and may enable them to address potential fraud earlier. For example, the Fraud Defense Network (FDN) is a cross-industry initiative that helps organizations from healthcare, finance, insurance and government markets with resources and actionable intelligence to connect the dots between different industries to improve fraud mitigation and prevention efforts.
- Public records data—Identification data including name, phone number, address as well as other “footprint” data, like bankruptcies, deceased files, watch lists and criminal records. In fact, a new research study2 done by the NHCAA and LexisNexis Health Care found that incorporating public records such as bankruptcies, liens and judgements, medical license expirations and criminal records can shine additional light on provider healthcare fraud. Advanced analytics and technology can transform disparate data into meaningful insights to arm healthcare organizations with insights to detect fraud earlier or perhaps, even prevent it. The ability to score and rank the likelihood and potential impact of suspected fraud is important so that health plans can prioritize providers, brokers and members based on risk and dedicate resources for monitoring, investigating and preventing fraud before the exposure to the organization expands.
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