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Pharmaceutical Economics and Policy

Paper Session

Saturday, Jan. 6, 2018 12:30 PM - 2:15 PM

Marriott Philadelphia Downtown, Grand Ballroom Salon J
Hosted By: Health Economics Research Organization
  • Chair: Sean Nicholson, Cornell University

Regulatory Incentives for Pharmaceutical Innovation: The FDA's Breakthrough Therapy Designation

Ariel Dora Stern
,
Harvard University
Jennifer Kao
,
Harvard University
Amitabh Chandra
,
Harvard University

Abstract

Incentives for biopharmaceutical firms to innovate are reduced by longer approval periods and other forms of regulatory and market uncertainty. The nature of the drug approval process therefore profoundly shapes private innovation and commercialization incentives. This paper considers a recent policy change to incentives for new drug development in the United States, the introduction of the FDA’s Breakthrough Therapy Designation (BTD). The BTD creates a pathway to new drug commercialization that is intended to make the process faster and more transparent for innovator firms. Using a synthetic control group, we consider the benefits (faster time-to-market) and cost (safety risks to patients) of the BTD program. We quantify the impact of BTD on time-to-market for new drugs and find that time spent in regulatory approval decreased by nearly four months on average. A back-of-the-envelope calculation suggests that this is likely to be valuable for pharmaceutical firms, which face large opportunity costs of capital on investment projects, and patients, who can access these therapies sooner. We then consider the implications for patient safety by considering adverse events and black-box warnings reported by the FDA. We observe a slightly higher rate of adverse events among BTD drugs and calculate the trade-offs between time-to-market and patient safety in this context

The Welfare Effects of Physician-industry Interactions: Evidence From Patent Expiration

Matthew Grennan
,
University of Pennsylvania
Ronnie Chatterji
,
Duke University
Kyle Myers
,
University of Pennsylvania
Ashley Swanson
,
University of Pennsylvania

Abstract

Many transactions occur via expert advisors, especially in the healthcare sector, and as such, firms frequently implement strategies to influence these advisors. The efficiency of these interactions is an empirical question. Using data on physician-industry interactions and prescribing behavior during the entry of a major generic statin drug, we examine the causal effect and welfare implications of the most common type of interaction: meals. Guided by a theoretical model of endogenous meals, we develop an instrumental variables identification strategy and document reduced form evidence that these meals directly influence prescribing decisions. We find a significant degree of negative selection and primarily extensive margin effects, whereby firms target small meals to prescribers with an otherwise low propensity to use the target drug. Given this evidence, we estimate a structural model of drug choice that allows us to predict counterfactual outcomes in a world where these meals are banned. Results from these counterfactuals are in line with theoretical predictions that these interactions can offset efficiency losses due to pricing with market power. However, this offset does not appear large enough to justify their existence in this particular market.

The Impact of Prescription Drug Monitoring Programs on Teen Use of ADHD Medication

Anna Chorniy
,
Princeton University
Janet Currie
,
Princeton University
Anca Cotet-Grecu
,
Seton Hall University

Abstract

Stimulants are commonly prescribed to treat individuals diagnosed with ADHD. These medications are designated as Schedule II Controlled Substances by the DEA, the same classification as opioids (“drugs with a high potential for abuse”). There is a widespread concern, reflected in the media, that ADHD is over diagnosed and that ADHD drugs are overprescribed. Data support the allegation that ADHD medication misuse and diversion is common among youths. We use 2000-2013 all-state Medicaid claims data to investigate the impact of prescription drug monitoring programs that were created in response to the abuse concerns. We use difference-in-difference design to estimate the impact of a PDMP becoming operational on the number of prescriptions for ADHD written for patients covered by Medicaid. Our primary empirical strategy identifies the sum of the two potential effects stemming from the PDMPs: informational and deterrent effects. We next, employ two empirical tests to disentangle them.
Discussant(s)
Darius Lakdawalla
,
University of Southern California
Colleen Carey
,
Cornell University
David Chan
,
Stanford University
JEL Classifications
  • I1 - Health