Industries

Health & Life Sciences

Wolters Kluwer Health says,

"We needed to break the cycle of more data, more requirements, more money and the answer was Netezza."

Payer Fraud & Abuse

To uncover fraudulent and abusive behavior, investigators must sort through millions of individual claims to find suspicious behavior, often relying on a pay-and-chase strategy—pursuing cases after claims have already been paid. With Netezza’s in-database analytic capabilities healthcare investigators can greatly improve their ability to proactively and retrospectively detect fraud:

• Abnormal and Outlier Claim Analysis – Identification of abnormal behavior typically requires investigators to undergo painstaking evaluation of comparative measures, often on small subsets of claims information. Customers using Netezza can greatly expand the scope of their analysis while at the same time expand and even automate much of the analysis required to detect outliers. These changes in speed and scope enable customers to not only identify previously undetected anomalies, but also identify “false positives” more quickly by providing a more comprehensive analysis.
• Spatial Analysis for Fraud Detection – Spatial analysis provides a new dimension for applying outlier analysis to detect fraudulent behavior. By linking member and physician demographics and claims with geographic measures and demographics, investigators can quickly identify outliers regarding patient travel, treatment clusters and abnormal treatment distributions based upon population demographics.
• Predictive Modeling for Fraud – Automating the identification of attributes and trends that signify fraud allows payers to not only find existing fraud schemes, but also provides a new tool to evaluate the likelihood that new claims are fraudulent. As opposed to business-rule type evaluations, predictive analytics can identify new trends that are characteristic of fraud. Traditionally evaluations of this type are performed after payment, if at all. With Netezza, payers can perform these same evaluations in seconds and minutes, making it feasible to identify potential fraud pre-adjudication.