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This book will educate the general public about statistical methnods to improve medical fraud assessment by more accurateoverpayment estimation, representative sampling and use of data mining methods for fraud detection. In the United States, total health care related spending reached 2.9 trillion USD and $9255 per person in 2013.
List of contents
Introduction. Regression modelling for spatially referenced data. Theory. Linear models. Generalized linear models. Geostatistical design. Preferential sampling. Zero-inflation. More complex problems. Appendix.
About the author
Dr. Tahir Ekin is the Brandon Dee Roberts Associate Professor of Quantitative Methods in McCoy College of Business, Texas State University. His previous work experience includes a working as a statistician on health care fraud detection. His scholarly work on health care fraud has been published in a variety of academic journals including
International Statistical Review,
The American Statistician, and
Applied Stochastic Models in Business and Industry. He is a recipient of the Texas State University 2018 Presidential Distinction Award in Scholar Activities and the ASA/NISS y-Bis 2016 Best Paper Awards. He has developed and taught courses in the areas of business statistics, optimization, data mining and analytics. Dr. Ekin also serves as Vice President of the International Society for Business and Industrial Statistics.
Summary
This book will educate the general public about statistical methnods to improve medical fraud assessment by more accurateoverpayment estimation, representative sampling and use of data mining methods for fraud detection. In the United States, total health care related spending reached 2.9 trillion USD and $9255 per person in 2013.
Additional text
" . . . the book is well organized and clearly written on a cutting-edge topic. This book may be helpful to the applied statisticians, health care policymakers, insurance analyst, forensic accountant as well as tax office to prevent health care fraud."
Kuldeep Kumar, Bond University, Robina, QLD, Australia
