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Distilling Influence Networks Abstract

Great physician targets are not synonymous with high-vol­ume prescribers. There are many physicians who do not write many scripts but who exert significant influence on other physicians that do. Often, they are prominent figures but they may also be low key, and there are many of them. There is another breed of physician equally worthy of sales and market­ing attention: physicians who make referral decisions for the patient. Depending on which way the referral goes, this can translate into significant additional or missed revenues.

Whereas no one would challenge the wisdom of tapping into influencers and referring/referred-to physicians, actually tapping into this group has been arduous. For starters, such physicians are difficult to pin down. To accomplish this, mar­keters have essentially resorted to two techniques: (1) inter­views, primary research, and feeds from the sales force and (2) the culling of rosters such as hospital affiliation and group­ practice affiliation. In both cases, the picture is spotty and may fail to portray the dynamics at work within physician circles.
 

This paper takes an off-the-beaten-track approach to this formidable problem by deploying patient-level data. The idea is very simple: Just like a phone call between two people may flag a relationship between the two, a patient that moves from one physician to another may be a giveaway that there is some relationship between the two. Patient level data capture exactly that. In addition, this approach identifies and profiles influencers and referral networks, the various levels of influence involved, unofficial networks at work, and insightful group dynamics.
 

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