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The authors quantify the impact of social interactions and peer effects in the context of physicians’ prescription choices. Using detailed individual-level prescription data, along with self-reported social network information, the authors document that physician prescription behavior is significantly influenced by the behavior of research-active specialists, or “opinion leaders,” in the physician's reference group. The authors leverage a natural experiment in the category: New guidelines released about the therapeutic nature of the focal drug generated conditions in which physicians were more likely to be influenced by the behavior of specialist physicians in their network. The authors (1) find important, statistically significant peer effects that are robust across model specifications; (2) document asymmetries in response to marketing activity across nominators and opinion leaders; (3) measure the incremental value to firms of directing targeted sales force activity to these opinion leaders; and (4) present estimates of the social multiplier of detailing in this category.

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This chapter focuses on the identification of opinion leaders in physician networks as a substantial opportunity for pharmaceutical firms rethinking their business model, and looking for improving resource allocation in order to increase their return on investment. It points out the various challenges and the advantages of identifying regional opinion leaders, especially when it comes to sustained use of branded drugs marketed by pharmaceutical firms. It includes a basic overview of network structure and the formation of physician social networks. This is a growing area of importance for various disciplines such as epidemiology, sociology, economics, and marketing. In this chapter, the reader will get introduced to several models of physician social networks which help isolate and measure the effect of opinion leaders, both self-stated and those identified by patient referral data. The author points out the managerial implications of this stream of research and promising areas of opportunity for deeper analysis for this promising nascent research stream.