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Medicare and Medicaid Audit Overpayments: Challenging Statistical Sampling and Extrapolation

Recording of a 90-minute CLE video webinar with Q&A

This program is included with the Strafford CLE Pass. Click for more information.
This program is included with the Strafford All-Access Pass. Click for more information.

Conducted on Wednesday, November 2, 2022

Recorded event now available

or call 1-800-926-7926

This CLE course will provide insight to counsel for Medicare and Medicaid providers on how to effectively evaluate and challenge overpayment determinations in provider audits using statistical sampling and extrapolation.

Description

Medicare and individual state Medicaid agencies routinely use samples of providers’ claims universes to extrapolate overpayment determinations. Each year, CMS informs Congress about the large dollar amounts it anticipates it will recoup from healthcare provider’s fraud and abuse activities. Many healthcare providers are impacted by these audits and must defend their documentation and other practices. To successfully challenge these audit determinations of overpayments that need to be repaid to federal health care programs, counsel for providers need to understand proper statistical sampling and extrapolation methods. They need to know how to identify and attack questionable methods and processes to minimize potential repayment obligations.

Government auditors’ statistical practices are presumed valid. it is the provider's burden to overcome that presumption and present sufficient credible evidence to refute the sampling and the extrapolation process. If the provider is successful, the extrapolated repayment amount will be removed from the case, leaving only the sample disallowances, which typically are relatively small and not worth challenging separately, to be repaid.

Listen as our authoritative panel illustrates how Medicare and Medicaid programs use statistical sampling and extrapolation to seek to recover very large dollar amounts of alleged Medicare and Medicaid overpayments. The panel will discuss how counsel for healthcare providers can obtain the information required to effectively challenge the sampling process and calculated demand amounts.

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Outline

  1. Using samples to calculate overpayment dollar demands
    1. Proactive steps needed to mount the challenge: what must you do
    2. Due process
      1. Governmental experts and review processes (role and practice)
      2. Documentation necessary to replicate auditor work
      3. Cross examination
    3. Relevant cases, rulings, and regulations
      1. What is the MPIM
      2. Leveraging guidance from Medicare cases and the MPIM
    4. Impact of extrapolating from a sample – what matters to Administrative Law Judges
    5. Do you need a statistical expert
  2. Statistically valid probability sampling and extrapolation for accurate measurement of overpayments
    1. Demonstrating when the audit process is invalid
    2. Identifying fatal flaws in audit design and execution, including simple and stratified sampling
    3. The requirements of probability sampling
    4. Demonstrating when the overpayment demand is inaccurate
    5. CMS requirement of auditor reliability

Benefits

The panel will review these and other key issues:

  • Recognizing the statistical requirements auditors must meet to properly use the results of auditing a sample for extrapolation
  • Preparing your case utilizing the benefits of understanding probability statistics
  • Recognizing common mistakes auditors make that invalidate sampling methods
  • Making statistics accessible to attorneys challenging extrapolated audit findings

Faculty

Maykuth, Patricia
Dr. Patricia L. Maykuth, Ph.D

President
Research Design Associates

Dr. Maykuth is a statistical expert with particular skill in experimental design, statistical sampling and...  |  Read More

Ross, David
David R. Ross

Senior Shareholder
O’Connell and Aronowitz

Mr. Ross concentrates his practice on Medicaid, Medicare and private insurance audits & investigations, and health...  |  Read More

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