Effects of Physician-directed Pharmaceutical Promotion on Prescription Behaviors: Longitudinal Evidence

Abstract

Spending on prescription drugs (Rx) represents one of the fastest growing components of U.S. healthcare spending, and has coincided with an expansion of pharmaceutical promotional spending. Most (83%) of Rx promotion is directed at physicians in the form of visits by pharmaceutical representatives (known as detailing) and drug samples provided to physicians' offices. Such promotion has come under increased public scrutiny, with critics contending that physician-directed promotion may play a role in raising healthcare costs and may unduly affect physicians' prescribing habits towards more expensive, and possibly less cost-effective, drugs. In this study, we bring longitudinal evidence to bear upon the question of how detailing impacts physicians' prescribing behaviors. Specifically, we examine prescriptions and promotion for a particular drug class based on a nationally-representative sample of 150,000 physicians spanning 24 months. The use of longitudinal physician-level data allows us to tackle some of the empirical concerns in the extant literature, virtually all of which has relied on aggregate national data. We estimate fixed-effects specifications that bypass stable unobserved physician-specific heterogeneity and address potential targeting bias. In addition, we also assess differential effects at both the extensive and intensive margins of prescribing behaviors, and differential effects across physician-and market-level characteristics, questions which have not been explored in prior work. The estimates suggest that detailing has a significant and positive effect on the number of new scripts written for the detailed drug, with an elasticity magnitude of 0.06. This effect is substantially smaller than those in the literature based on aggregate information, suggesting that most of the observed relationship between physician-directed promotion and drug sales is driven by selection bias. Qualitatively consistent with the literature, we find that detailing impacts selective brand-specific demand but does not have any substantial effects on class-level demand. Results also indicate that most of the detailing response may operate at the extensive margin; detailing affects the probability of prescribing the drug more than it affects the number of prescriptions conditional on any prescribing. We draw some implications from these estimates with respect to effects on healthcare costs and public health.

Physician characteristics, industry transfers, and pharmaceutical prescribing: Empirical evidence from medicare and the physician payment sunshine act

“…Yeh et al used a 2011 cross section of Massachusetts physicians to examine transfers and Medicare part D statin prescriptions and found that transfers were positively associated with branded prescriptions. Datta and Dave use a longitudinal monthly dataset on 150 000 physicians spanning 1997‐1999 to examine the effects of industry detailing on prescriptions for the detailed drug and found a positive relationship. Carey et al examined the impact of pharmaceutical transfers on prescribing behavior under Medicare Part D from 2011 to 2013 and found that patients are more likely to be prescribed a drug when their prescriber received a transfer from its company; however, examining efficacy data from clinical trials, they find that those receiving transfers are more likely to prescribed higher quality drugs on average.…”

Ethical drug marketing criteria for the 21st century

“…Drug promotion reduces cost efficiency by, for example, increasing use of expensive drugs instead of cheaper, equally safe and effective alternatives (such as branded instead of generic) 23242526. This creates financial burdens for individuals and opportunity costs to society, and threatens the sustainability of the healthcare system.…”

Physician-Industry Interactions: Persuasion and Welfare

“…This places our study in contrast to Carey et al (2017), Datta and Dave (2016), Mizik and Jacobson (2004), in which the researchers include physician fixed effects to take out persistent unobserved differences across physicians. 32 The average treatment effect of a pharmaceutical firm providing one fewer meal to a physician in the context of a long physician-firm relationship, or of providing the first meal to a physician at the initiation of a physician-firm relationship, may be very different than the average treatment effect of turning an entire relationship on or off.…”

“…In order to examine the interactions between market power and payments to physicians, we estimate a nested logit model of statin choice, integrating our demand estimation with the machine learning procedures from Belloni et al (2017), similar to Gillen et al (2015). 8 At least two other published studies we are aware of incorporate physician-level fixed effects: Mizik and Jacobson (2004) and Datta and Dave (2016). In a market such as statins, where relationships likely pre-date the beginning of the payment data, a fixed effect intuitively controls for the unobserved relationship.…”