Kusserow on Compliance: Statistical Sampling in OIG Reviews

On January 12, 2015, the HHS Office of Inspector General (OIG) released a Podcast explaining the statistical sampling that it performs. The presentation was by Lisa Wombles, Senior OIG, and Jared Smith, OIG Audit Statistician. It was noted at the outset that the OIG frequently uses statistical sampling as it provides the ability to cover thousands or even millions of claims in a fair and objective fashion. If the OIG did not use sampling methodology, it would have to review a majority of claims and with the large number of records involved, such reviews would make it much more difficult for providers to gather the necessary supporting documentation and appeal any contested claim. This type of review would not be efficient or cost effective for either the provider or the OIG.

Statistical sampling is applied to a variety of areas including hospitals, home health, physician services, and durable medical equipment. The OIG will always consider using sampling whenever it’s not possible to review every claim. Each review is viewed as unique, so the sampling method used in each review varies based on different risk factors. This way, the OIG applies the appropriate statistical formulas to calculate any estimated overpayment. It documents and keeps all documents and data related to every sample so that the review can be reproduced.

Regardless of the sample design used by the OIG, it employs an estimation method that gives the provider the benefit of the doubt for any uncertainty in the sampling process. The OIG professes that it uses overpayment estimates that will almost always be lower than what it would obtain from reviewing every claim. The OIG notes that courts have held that the methodology need not be precise or optimal as long as it is statistically valid. The OIG ensures that its work meets this standard by evaluating each sample using the appropriate law or regulation. Whatever method it employs must meet four standards:

  1. Statistically valid
  2. Efficient
  3. Produce a sample that’s representative of the larger group
  4. Produce a valid estimate of any overpayment

When the OIG looks at a sample of claims selected from a larger group of claims, it makes an estimate, but only applies the estimate to the specific larger group of claims from which the sample was drawn. It reduces the overpayment estimate in order to properly account for claims that are canceled, refunded to the Medicare program, or otherwise not in error. The OIG made it clear that if done properly, the process it employs creates an accurate and efficient way to look at a lot of data. It was specially noted that numerous administrative appeal decisions and federal court cases have concluded that statistical sampling is an appropriate way to calculate any overpayment. Courts and administrative hearings have also upheld the right of providers to appeal when the OIG uses statistical sampling to question costs or claims, or in appealing an individual determination of an overpayment through the normal Medicare appeals process.

Richard P. Kusserow served as DHHS Inspector General for 11 years. He currently is CEO of Strategic Management Services, LLC (SM), a firm that has assisted more than 3,000 organizations and entities with compliance related matters. The SM sister company, CRC, provides a wide range of compliance tools including sanction-screening.

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Copyright © 2015 Strategic Management Services, LLC. Published with permission.