The increased availability of large and complex health industry data provides a basis for detailed analysis of many different types of allegedly fraudulent conduct by health care companies. Today, many pharmaceutical, biotechnology and medical device companies, as well as other health care entities, maintain rich data sets concerning the types of marketing activities and provider relationships that are often at the heart of improper promotion and kickback allegations.
For example, third-party data concerning physician prescribing data can be overlaid on call-note data, which tracks contacts between company sales representatives and physicians, and/or company records of honoraria payments to specific health care professionals. With proper attention to confounding factors that may have affected physician treatment choices, such data can be used to explore the effects on sales of company conduct at issue in a government investigation or a private litigation matter.
“The results can be used to powerfully rebut approaches that focus on only a small set of examples or even anecdotal findings.”
— Principal Richard Mortimer
In many instances, Analysis Group also turns to extensive in-house patient medical and pharmaceutical claims data covering tens of millions of patient lives. These data can shed light on patient characteristics and historical patterns of treatment and how they affect physicians’ prescribing decisions. For example, a patient with a history of drug-switching within a specific therapeutic class might suggest that unmet medical need, not marketing, underlies a later treatment choice. Such a pattern can be documented as an example of what likely would have occurred anyway even in the absence of the conduct at issue.
Principal Richard Mortimer explains, “On any given case, we rely on our extensive experience working with large and complex data sources to identify the company, third-party, and in-house data that will be most appropriate for addressing the specific issues and needs of the case. We are able to develop relevant data sets and tailor the analyses as appropriate. The results can be used to powerfully rebut approaches that focus on only a small set of examples or even anecdotal findings.” ■