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Keywords: Brand loyalty, Learning, Pharmaceuticals
JEL classification: D12, I12
ABSTRACT
Medicines for chronic conditions like high cholesterol, heart disease, and diabetes are repeatedly used for a long period of time. Consumer dynamics thus plays an important role in the demand for those drugs. The paper estimates a demand model with brand loyalty and learning, using data from cholesterol-lowering drug markets in the United States. The estimates suggest high switching costs and strong learning effects at the molecule level in the markets. Switching costs raise the predicted probability of choosing the same drugs successively, and learning greatly increases patient stickiness to a molecule in the long run. I discuss implications of the estimated state-dependent effects for drug manufacturers, insurance companies, and healthcare policy makers.
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1. INTRODUCTION
In recent years, branded drug manufacturers have been facing generic competition against many of their blockbuster drugs. According to IMS Health, the patents of six of the ten best-selling prescription drugs in the US expired in 2011 and 2012. To retain revenue after patent expiration, branded drug manufacturers have employed several strategies, including pay-for-delay agreements (paying generic companies not to bring lower-cost alternatives to market), presentation proliferation (selling a drug in new forms or dosages) and copay coupons (distributing a card directly to patients to lower their out-of-pocket costs). The success of these strategies depends not only on how many patients drug manufacturers can attract today, but also on how many of the patients will stick to the brands tomorrow. Thus, patient stickiness plays an important role in these marketing strategies. Understanding the sources of patient stickiness in pharmaceuticals can help manage the programs.
To study patient stickiness, this paper estimates the demand for pharmaceuticals by incorporating brand loyalty and learning. Using micro-level databases for cholesterol-lowering drugs, I look at the switching patterns of patients with different lengths of treatment. The data show that inter-molecule switching probabilities are higher in early prescriptions and quickly decrease in a treatment, suggesting the existence of switching costs and learning about molecules. Switching costs make a patient loyal to a drug and lower the probability of choosing a different drug next time.1 On the other hand, patients learn the effects...