Estimation of promotional strategies for newer vs older drugs based on physician prescribing data

Purpose – The purpose of this paper is to use results from a comprehensive analysis of a physician‐prescribing model to draw guidelines on how to promote a new drug in the presence of competing older drugs, in a chronic therapeutic state. Design/methodology/approach – The authors use an extensive database from SDI Health, LLC, and a second data set from IMS Health. They calibrate their model using logarithmic regression methodology. The dependent variable in the model is number of new prescriptions and the explanatory variables are physician and patient characteristics, and marketing variables. Findings – The authors' estimates imply that heavy prescribers are likely to be specialists, be in solo practice, have more experience, receive more sales rep traffic, have more HMO affiliations, have a higher proportion of patients in HMOs, write more prescriptions across all therapeutic categories, see a higher number of patients, receive more free samples from the sales reps, have more rep intensity in their offices, and allow longer visits by sales reps. Originality/value – This model has novel implications for drug manufacturers on the effect of time‐in‐the‐market. Accordingly, new drug makers are well‐advised to wait until a drug gets established in the community for it to be prescribed more heavily by specialists and target physicians in solo practice and newer physicians to speed up the adoption process. Furthermore, for newer drugs traditional forms of detailing via a live sales rep are not as effective as for older more established drugs – the new‐drug manufacturer can try other means such as e‐detailing, social media, direct‐to‐consumer advertising, and word‐of‐mouth/mouse to initiate market share.