The Effects of Detailing on Prescribing Decisions Under Quality Uncertainty

Abstract

Motivated by recent empirical findings on the relationship between new clinical evidence and the effectiveness of detailing, this paper develops a new structural model of detailing and prescribing decisions under the environment where both manufacturers and physicians are uncertain about drug qualities. Our model assumes (i) a representative opinion leader is responsible for updating the prior belief about the quality of drugs via consumption experiences and clinical trial outcomes, and (ii) manufacturers use detailing as a means to build/maintain the measure of physicians who are informed of the current information sets. Unlike previous learning models with informative detailing, our model directly links the effectiveness of detailing to the current information sets and the measures of well-informed physicians. To illustrate the empirical implications of the new model, we estimate our model using a product level panel data on sales volume, prices, detailing minutes, and clinical trial outcomes for ACE-inhibitors with diuretics in Canada. Using our estimates, we demonstrate how the effectiveness of detailing depends on the information sets and the measure of well-informed physicians. Furthermore, we conduct a policy experiment to examine how a public awareness campaign, which encourages physicians/patients to report their drug experiences, would affect managerial incentives to detail. The results demonstrate that the empirical implications of our model are very different from those of previous models. We argue that our results point out the importance of developing a structural model that captures the mechanism of how detailing/advertising conveys information in the market under study.

Keywords: Detailing, Prescription Drugs, Decisions Under Uncertainty, Bayesian Learning, Representative Opinion Leader, Diffusion

JEL Classification: D83, I11, I18, M31, M37, M38