Introduction : In this chapter we reanalyze Medical Innovation by Coleman, Katz and Menzel (1966), the classic study on diffusion of Tetracycline, which at that time was a newly introduced antibiotic. Their pioneering study elaborated on how different patterns of interpersonal communications can influence the diffusion of a medical innovation in four medical communities in Illinois. The motivation for our reanalysis is to capture the complex interactions involved in the diffusion process by combining Agent-based Modeling (ABM) and network analysis. Based on the findings in Medical Innovation, we develop a diffusion model called Gammanym. The topology of networks generated in Gammanym, and its evolution, are analyzed to evaluate the network structure influencing the diffusion process. We describe the original study and the rationale for our study in the following section. Section 1.3 describes the modeling framework, modeling sequences and methods. Simulation results under different scenarios are analyzed in Section 1.4. The structure of the social networks depicted in our model, and its evolution are analyzed in Section 1.5. We explore the significance of types of network integration after normalizing adoption curves in terms of numbers for professionally integrated and isolated doctors in Section 1.6. The paper concludes with discussions and a review of the implications of the simulation results.