This edition of Qui Tam Quarterly focuses on:

- the history of big data in health care FCA investigations and litigation;

- how the government has increased its ability to gather health care claims data and use it to support FCA allegations;

- how big data will most likely be used as a primary tool for investigations to evaluate potential fraud due to regulatory changes brought on by COVID-19; and

- how providers can use big claims data to control discovery costs in investigations and to better understand the operations of their compliance programs to prevent improper claims from being filed.

This edition concludes with key strategies for defending allegations supported by extrapolated overpayments and some best practices for using claims data to proactively defend against scrutiny. Specifically, information and recommendations are provided on how to undermine the validity of findings on a sample set of claims that can be used to invalidate the extrapolated assumptions, how to effectively challenge an extrapolation based on improper sampling and auditing processes, and how to dispute the statistical extrapolation process after an extrapolated overpayment has been asserted against a provider. Finally, resources and suggestions are provided on how providers can take advantage of currently available claims data to reduce the risk of scrutiny.