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E-raamat: Statistics and Health Care Fraud: How to Save Billions

(Texas State University, San Marcos, TX, USA)
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Statistics and Health Care Fraud: How to Save BillionsSuurem pilt
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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.

Arvustused

" . . . 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

Preface xi
Acknowledgments xv
Abbreviations xvii
Chapter 1 Health Care Systems and Fraud
1(30)
Overview
1(3)
Health Care Systems
4(2)
Worldwide Health Care Insurance Programs
6(3)
Medical Overpayments
9(1)
Why Health Care Fraud? Why Now?
9(4)
Impact and Importance of Fraud Assessment
13(2)
Types and Examples of Health Care Fraud
15(8)
General Fraud Assessment Framework and Initiatives
23(4)
Key Takeaways
27(1)
Additional Resources
28(3)
Chapter 2 Describing Health Care Claims Data
31(18)
Overview
31(1)
Health Care Data
32(3)
Understanding Health Care Claims Data
35(1)
Data Pre-Processing
36(4)
Descriptive Statistical Analysis
40(6)
Discussion
46(1)
Key Takeaways
47(1)
Additional Resources
48(1)
Chapter 3 Sampling and Overpayment Estimation
49(20)
Overview
49(2)
Sampling and Overpayment Estimation
51(1)
Sampling Procedures
52(4)
A Closer Look at Stratified Sampling
56(7)
Overpayment Estimation
63(1)
Discussion
64(2)
Key Takeaways
66(1)
Additional Resources
66(3)
Chapter 4 Predicting Health Care Fraud
69(20)
Overview
69(3)
Health Care Fraud Analytics
72(3)
Predictive Methods
75(2)
Prediction of Overpayment Amount and Fraud Probability
77(3)
Classification of Health Care Claims
80(3)
Accuracy and Validation
83(1)
Discussion
84(1)
Key Takeaways
85(1)
Additional Resources
86(3)
Chapter 5 Discovery of New Fraud Patterns
89(26)
Overview
89(2)
Outlier Detection: Finding Excessive Billings
91(5)
Clustering: Grouping Health Care Claims
96(5)
Association: Finding Links Among Claims
101(3)
Effectiveness of the Analytical Methods
104(2)
Deployment Via Rules
106(2)
Current Efforts
108(3)
Key Takeaways
111(1)
Additional Resources
112(3)
Chapter 6 Challenges, Opportunities, and Future Directions
115(20)
Overview
115(3)
Shareholders: Putting a Face on Fraudsters and Victims
118(3)
Challenges with Payment and Fraud Control Systems
121(1)
Organizational Issues: "No News is Good News!"
122(2)
Evolution of Fraud and Adaptive Fraudsters
124(1)
Different Sides of the Coin: Data as a Blessing, Data as a Curse
125(2)
Legal Concerns: Embracing Uncertainty
127(2)
A Take on Future
129(4)
Key Takeaways
133(1)
Additional Resources
134(1)
Bibliography 135(2)
Index 137
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.
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