ABSTRACT

Statistics and Health Care Fraud: How to Save Billions helps the public to become more informed citizens through discussions of real world health care examples and fraud assessment applications. The author presents statistical and analytical methods used in health care fraud audits without requiring any mathematical background. The public suffers from health care overpayments either directly as patients or indirectly as taxpayers, and fraud analytics provides ways to handle the large size and complexity of these claims.

The book starts with a brief overview of global healthcare systems such as U.S. Medicare. This is followed by a discussion of medical overpayments and assessment initiatives using a variety of real world examples. The book covers subjects as:

• Description and visualization of medical claims data

• Prediction of fraudulent transactions

• Detection of excessive billings

• Revealing new fraud patterns

• Challenges and opportunities with health care fraud analytics

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.

chapter Chapter 1|30 pages

Health Care Systems and Fraud

chapter Chapter 2|18 pages

Describing Health Care Claims Data

chapter Chapter 3|20 pages

Sampling and Overpayment Estimation

chapter Chapter 4|20 pages

Predicting Health Care Fraud

chapter Chapter 5|26 pages

Discovery of New Fraud Patterns

chapter Chapter 6|20 pages

Challenges, Opportunities, and Future Directions