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SAS® Fraud Framework for Health Care

SAS® Fraud Framework for Health Care

Prevent, detect and manage payment integrity issues from every angle.

Detect improper payments before they're made to save hundreds of millions of dollars that can go to improving quality of care. Improve accuracy while decreasing model-creation time from weeks to a few hours.


Detect more improper payments.

By making analytical models and rules engines part of the process, you can spot more payment integrity breaches than ever before. Process all data (not just a sample) through rules and analytical models. Use customized models to detect previously unknown schemes. And spot linked entities and crime rings, which can help stem larger losses.

Reduce false positives. Boost efficiency.

Gain real-time access to information by including analytical models in your process workflow. Apply risk-based scoring to model output before it goes to analysts, clinicians, or investigators, so you can ensure that valuable personnel are working on the highest profile cases. And by improving the efficiency of reviews, you’ll free clinicians and investigators to work on more cases than ever before.

Reduce losses while increasing recoveries.

Near-real-time daily batch scoring catches fraud quickly. Find loss padding in similar claims. Identify repeat offenders and uncover insider or collusive fraud by integrating staff data and audit records, and applying risk- and value-based scoring models to prioritize output for investigators.

Gain a consolidated view of payment integrity risk.

Continually improve models and adapt the system to address changes in payment and cost containment trends. Get a better understanding of new threats and prevent big losses early using social network diagrams and sophisticated data mining capabilities.


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SAS® Fraud Framework for Health Care
  • Data management. Consolidate historical data from internal and external sources – claims systems, watch lists, third parties, unstructured text, etc.
  • Rule and analytic model management. Create and logically manage business rules, analytic models, alerts and known bad lists.
  • Detection and alert generation. Calculate the propensity for aberrant billing at first submission, then rescore claims at each processing stage as new claims data is captured.
  • Social network analysis. Go beyond transaction and account views to analyze related activities and relationships at a network dimension.
  • Optional integrated case management solution. Systematically pave the way for operational, clinical, or investigative reviews using a configurable workflow.
  • Hosting and analytical services. Install and administer your solution at the SAS hosting site for faster implementation (and faster ROI) – while eliminating the need for payer staff to oversee the system.

With this modeling approach, our accuracy is much, much higher ... We've also decreased the time to create a model from weeks to just a few hours.
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