Statistical sampling and extrapolation have become accepted tools for establishing damages in health care administrative proceedings and False Claims Act (FCA) litigation over the past 30 years.

Key Takeaways

1. The government has been dramatically increasing the use of data mining to identify potential health care fraud and data analysis to support liability and damages in False Claims Act cases. 
2. One of the primary tools the government uses to assert FCA liability and damages based on claims data is the statistical sampling and extrapolation process. 
3. Understanding the legal standards and challenges to improper use of statistical sampling and extrapolation is critical to defending FCA allegations based on data analysis. 

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Qui Tam Quarterly is a publication authored by members of the health care fraud and abuse team highlighting emerging and pressing issues in health care fraud and abuse, including litigation and governmental investigations involving the False Claims Act, the Stark Law, the Anti-Kickback Statute, and other health care fraud related statutes.

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