Abstract
dc:description.abstract<p> Medicare and Medicaid fraud has taken center stage over the last decade due to the sheer magnitude (in expenditures and enrollment) of the programs. Even a small percentage of fraud in terms of total annual expenditures within Medicare or Medicaid can constitute billions of dollars as an expense that is passed on to the taxpayers of the United States. This paper examines methods of quantifying this fraud by using statistical techniques that are consistent with the Centers for Medicare and Medicaid Services guidelines (CMS, 2005). Our interest is in the total overpayment amount of a population of payments made to a given healthcare provider, denoted &tau<sub>Y</sub>, and specifically and in accordance with CMS guidelines, a 90% lower bound for &tau<sub>Y</sub>. The paper considers classical methods of estimation in which the Central Limit Theorem is used, and also newer methods based on the Hypergeometric distribution. It studies the efficiency of "pennysampling" (Edwards et al., submitted) wherein the sampling unit is the penny. It also extends the idea of pennysampling to dollar sampling and allows for different sampling units (beneficiary IDs, claims, and claim lines) to be considered. </p>
Degree
thesis:*- Name thesis:degree_name
- M.S.
- Level thesis:degree_level
- Campus Access Thesis
- Discipline thesis:degree_discipline
- Statistics
- Year dc:date.available
- 2011
Author and committee
dc:creator, dc:contributor.*- Author dc:creator
-
- Lawrence, Matthew
- Contributors dc:contributor
-
- Don Edwards
Subjects
dc:subject × 3Rights
dc:rights- Statement dc:rights
-
- © 2011, Matthew Lawrence
Identifiers
dc:identifier.*- Repository record dc:identifier
- https://scholarcommons.sc.edu/etd/2677
- OAI identifier oai:identifier
- oai:scholarcommons.sc.edu:etd-3671