Healthcare Fraud: Auditing and Detection Guide, 2nd Edition

Chapter 14

Data Management

In the fields of observation, chance favors only the prepared mind.

–Louis Pasteur (1822–1895)

With the prevalence of healthcare fraud and economical structural fraud, being anything other than thoroughly prepared leaves a gaping gateway of ongoing and new vulnerabilities. According to the Association of Certified Fraud Examiners, the tip is still the number-one source of identification of one-time or ongoing frauds (www.acfe.com). Without the development of sophisticated data management (DM) models, an effective audit or investigation will never reach the analytics of prevention or detection. The next several chapters are dedicated to the fundamental understanding of data; they serve as building blocks toward effective audits and investigations.

The number of store-shelf computer data mining software products is increasing at an accelerated rate, as is the number of software engineers who custom-program business solutions for data analytics. In addition, various professional organizations are dedicated to the subject. A group established in 1839 and known as the American Statistical Association (ASA) (www.amstat.org) is one resource for statistical science in applying analytics to healthcare fraud investigations. Another professional association, founded in the late 1970s, is the Data Management Association (DAMA) (www.dama.org). It is focused on the development and practice of managing data, information, and knowledge.