Statistical Sampling in Healthcare FCA Litigation

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CLE Approved in California and Illinois

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This presentation will discuss statistical sampling in False Claims Act (FCA) litigation about alleged healthcare fraud.  The presentation will focus on what litigators need to know.  It briefly discusses the legal context for admissibility and weight of evidence based on statistical sampling, and then describes the steps involved in sampling and extrapolation, potential pitfalls, and common misconceptions.  Throughout, the emphasis is on providing the audience with an understanding of such concepts as point estimates, margin of error, confidence levels, and confidence intervals.  The course is equally applicable to Medicare audits and self-disclosure of overpayments.  Topics to be covered include:

  • Admissibility and weight of statistical evidence
  • Key concepts: point estimate, bias, margin of error, confidence level, confidence interval
  • Steps involved in sampling and extrapolation
  • Determinants of minimum sample size
  • Potential pitfalls and limitations
  • Common misconceptions

About the Presenter:  Dr. Panis assists attorneys with statistical and analytical aspects of healthcare litigation, including False Claims Act (FCA) cases. Prior to joining Advanced Analytical Consulting Group (AACG), he taught statistics, economics, and econometrics at the University of Southern California and the University of California at Irvine; was a Senior Manager at Deloitte; and a Senior Economist at The RAND Corporation.

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