Journal Title
Title of Journal: Health Serv Outcomes Res Method
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Abbravation: Health Services and Outcomes Research Methodology
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Authors: Dennis Gilliland Wenning Feng
Publish Date: 2010/10/09
Volume: 10, Issue: 3-4, Pages: 154-164
Abstract
The National Health Care AntiFraud Association wwwnhcaaorg states that in 2007 over 4 billion health insurance claims were processed in the United States and that fraud amounted to 68 billion over 3 of the total paid 226 trillion Additional overpayments come from billings for unnecessary practice and procedures and errors in billings It is of vital importance that valid and efficient statistical methods be developed for audits of payments by insurers The Minimum Sum Method MSM is based on simple random sampling It is a valid statistical method for obtaining a 1 − α100 confidence level lower estimate bound for the total overcharge in a health care payment population whatever the sample size The MSM lower bound is efficient not too conservative when the payments in population are about the same size and each payment is either completely in error all overcharge or not in error It is the purpose of this paper to point out a simple adaptation of MSM that extends its effectiveness to populations where payments vary to demonstrate the advantage with a small simulation study and to point out how randomized lower estimates can be used to precisely apportion the risk due to sampling error
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