Case for Programwide Statistical Reviews of Fraud and Abuse

• NCJ Number: 83316
• Journal: GAO Review Dated: (Spring 1982) Pages: 33-36
• Author(s): B H Klein
• Date Published: 1982
• Length: 4 pages
• Publication Format: Article
• Language: English
• Country: United States of America

Annotation

This article discusses a Migrant Education Program evaluation sponsored by the Department of Education as an example of the effectiveness of large-scale statistical reviews to detect fraud and abuse.

Abstract

Because of cost and staff constraints, reviews often focus on specific incidents of fraud and abuse at a small number of sites and then apply the findings to an entire program. However, large-scale statistical reviews eliminate the temptation to speculate about the magnitude of fraud and abuse based on limited data and compensate for the inability of most small-scale reviews to differentiate among programs with relatively high and low levels of abuse. The problem in the Migrant Education Program concerned the counting of ineligible students which thereby fraudulently increased the level of program funding based on these counts. While officials were aware of the potential for fraud, they also contended that many eligible students were excluded from counts because States gave low priority to identifying and enrolling these children. The program enrolls eligible children on a centralized computer system called the Migrant Student Record Transfer System (MSRTS). To validate the accuracy of data in the MSRTS, the review selected a sample of some 9,000 children whose enrollments contributed to the 1977 count and collected information on their age and eligibility. To estimate the number of eligible children not included in the program, the review screened a probability sample of children in some 2,500 classrooms to determine if eligible ones were enrolled in the MSRTS. Data analysis indicated that fraud and abuse were relatively low and that the overcount of ineligibles was offset by an undercount of eligible children. The major reason for the undercount appeared to be incompleteness of enrollment data for the overlap period between the calendar year and the school year. The article contains four references.