Description

Medicare and individual state Medicaid agencies routinely use small samples of claims that are audited and then the findings of the alleged overpayments are extrapolated, resulting in potentially huge demands made to the provider for repayment. Each year, the federal Centers for Medicare and Medicaid Services (CMS) informs Congress about the large dollar amounts it and its contractors anticipate will be recouped from audits of healthcare providers' alleged fraud and abuse activities. Many healthcare providers are significantly impacted by these audits and must defend their documentation and medical practices at the risk of huge repayment demands.

To successfully challenge these audit determinations, and to minimize repayment obligations, attorneys for healthcare providers need to understand proper statistical sampling and extrapolation principles to effectively challenge the methodology used in the audit.

Because federal and state auditors' statistical sampling and extrapolation practices are presumed valid by both federal and state contractors, and their respective Administrative Law Judges, it is the provider's burden to overcome that presumption of validity. Attorneys for healthcare providers must present sufficient credible evidence in order to successfully refute the sampling and the extrapolation process. The potential reward is huge: if the provider is successful in challenging the sampling and extrapolation, the extrapolated repayment amount will be removed from the audit, leaving only the sample disallowances to be repaid. The dollar amounts that remain in the audit tend to be relatively small such that it is not cost-effective to challenge them, so the audit is quickly settled.

Listen as our authoritative panel illustrates how Medicare and Medicaid programs use statistical sampling and extrapolation to attempt to recover large dollar amounts of alleged overpayments from healthcare providers. The panel will also discuss how audit defense counsel can obtain and present the information required to effectively challenge the sampling and extrapolation process.