Refinement of health care requires the elimination of frauds. This book is all about how statistical and analytical methods could help to reduce health care frauds if not their total elimination. No mathematics or statistics background is necessary to read and comprehend this book. There are six chapters covering topics health care systems and fraud, describing health care claims data, worldwide health care insurance programmes, fraud assessment, data pre-processing, sampling versus overpayment estimates, predictive health care frauds, accuracy versus validation, discovery of fraud patterns, finding excessive billings, effectiveness of analytical methods, deployment via rules, shareholders, adaptive fraudsters, data as a blessing versus a curse, legal concerns, embracing uncertainty among others. The unique features of this well written book are quotes of popular writers and leaders, citation of web sources for data, identity theft versus frauds, improper coding, kickback versus referrals, providing unnecessary care versus manipulating billing rules, managed care frauds, and selective list of bibliography among others. It is interesting that no data or graphs are displayed anywhere in the book.
I enjoyed reading this book. I recommend this book to statistics and computing professionals.