Should We Prevent Off-Label Drug Prescriptions? Empirical Evidence from France

We investigate the impact of regulation of off-label prescriptions on physicians' behavior, patients' health, treatment costs and pharmaceutical firms' pricing with a structural model of demand and supply. Exploiting rich panel data on physicians' activities and office visits over a nine-year period, we first study the decision to prescribe approved vs. off-label drugs for the treatment of depression. Using a model of prescription choice and health outcomes with unobserved patient-level heterogeneity, we identify the demand for on-label and off-label drugs and the effect of prescription choice on health outcomes. On the supply side, we develop a Nash-in-Nash bargaining model between the government and the pharmaceutical companies that allows the identification of the marginal costs of drugs. Results show that there is selection into treatment based on patient-level unobservables. Consistent with the medical literature, we find that there is heterogeneity in treatment impact of drugs. Counterfactual simulations show that removing offlabel drugs from the choice set of physicians while keeping the prices of on-label drugs constant would lead to a substantial increase in the expenditure on prescription drugs due to a substitution effect. Allowing drug prices to be different under a ban on off-label prescriptions would further increase the treatment cost due to both the substitution and price effects without leading to an improvement in health outcomes