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August 19, 2019 By SmartLight News Desk

Phantom billing: Can you spot it in your claims?

Three seemingly unrelated imaging providers based in FL were identified in a self-funded employer’s medical claims for what was later verified as phantom billing.


The utilization patterns seen in paid claims history for an employee and his wife indicated a strong probability of “phantom” billing – billing for services never performed. Phantom billing typically involves setting up fake corporation(s) with the intent of billing non-rendered services. The individuals involved with the phantom corporations will then recruit patients by offering them an incentive in exchange for allowing their insurance to be billed.

Patients will also be offered incentives to recruit other members of the same insurance plan. Phantom providers start and stop billing within a short period of time in order to avoid detection.

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Filed Under: costs, healthcare Tagged With: claims, phantom billing

Eliminating Out-of-Network Benefits Saves Employers Money and Discourages Fraudulent Claims

September 1, 2021 By Franklin Baumann, MD

liminating out-of-network (OON) benefits in self-funded employee healthcare plans tackles several  problems for employers and benefits administrators: healthcare plan costs, dealing with laborious ERISA out-of-network appeals and the potential for fraud.

Telemedicine leaves space open for FWA

August 1, 2021 By Franklin Baumann, MD

The continued use of telemedicine – made dramatically more mainstream during the pandemic – may open the door for more fraud, waste, and abuse in healthcare claims.

Identifying Provider Fraud in employee healthcare claims

July 14, 2021 By SmartLight News Desk

Analysis of healthcare claims from a sampling across multiple employers with self-funded healthcare plans and a combined total of more than 100,000 members, identified over $25 million in fraud, waste, and abuse by providers.

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SmartLight Analytics combines the best inferential analytic models with a team of analytic  and clinical experts to find fraud, waste, and abuse in self-funded employer health care plan claims data.
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