SIRIS is a contributory database that allows NHCAA members to submit, track, monitor and share information related to potential provider fraud and associated investigations. The new research study assessed the value of adding external provider derogatory data to SIRIS and determined the following:
- Incorporation of external derogatory provider data into SIRIS can expose providers that possess strong indicators of fraud.
- Fraud data from different industries can provide alerts of potential fraud earlier than data from within a single market.
"The key learning from the study was that incorporating public records such as bankruptcies, liens and judgements, medical license expirations and criminal records all can shine additional light on health care fraud," said
Specifically for the study, SIRIS providers were analyzed using LexisNexis Health Care data and analytics to see what derogatory data was returned and if that data applied to the SIRIS records in a meaningful way. LexisNexis Health Care applied three additional layers of data in the study:
1) Provider-centric data such as licenses, sanctions,
2) Non-health indicators such as criminal, sex offender, deceased records, bankruptcy liens and judgements; and
3) Fraud inquiries from finance, insurance and government markets from the LexisNexis® Fraud Defense Network (FDN), a cross-industry initiative offering resources and actionable intelligence to connect the dots between different industries to improve fraud mitigation and prevention efforts.
For example, in the study, the FDN detected 124 SIRIS providers at high risk for fraud from outside of health care, including one provider investigated for financial services fraud three times and insurance fraud one time the year before being added to SIRIS. The study also found several examples of bankruptcies filed the year before these providers were added to SIRIS investigations for services not provided and up-coding.
"When payers have data on licensing expirations and deceased records, they can withhold payment for further investigation of fraud," said
The ability to predict the likelihood that a provider has committed or may commit fraud in the future enables insurers to prioritize providers based on risk and optimize resource allocation for monitoring, investigating and preventing FWA.
Isbitts will discuss how data insights can help prevent fraud in his presentation, "The New Menace: FWA on the Marketplace Exchange & Organized Crime" on
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