New Drug Diffusion When Forward-Looking Physicians Learn from Patient Feedback and Detailing

The authors study physicians' prescription choices when uncertainty about drug efficacy is resolved through two channels: firms' marketing activities (e.g., detailing) and patients' experiences with the drugs. They first provide empirical evidence that suggests that the well-understood information incentive for physicians to experiment with new drugs is reduced when physicians anticipate future detailing. Therefore, increased detailing activity triggers opposing forces: Adoption is hastened as physicians become informed (assuming prior knowledge is initially low) and slows as they reduce experimentation and instead obtain information from detailing at no cost. The authors then estimate a dynamic Bayesian learning model that embodies these trade-offs using physician-level data on prescription choices and detailing received in the months surrounding the introduction of two erectile dysfunction drugs, Levitra and Cialis. Detailing elasticities are lower when physicians anticipate changes in detailing activity than when such changes are unexpected. Accordingly, the authors conclude that to maximize the effect of detailing, firms should avoid announcing increases in detailing activities.