"Antibiotic Prescribing under Uncertainty about Resistance"

By Michael Ribers, University of Zurich

Abstract

The increasing level of antibiotic resistance constitutes a major worldwide health threat. Inefficient antibiotic prescribing is considered one of the main drivers of increasing resistance but no framework for evaluation of rational prescribing exists. We develop a dynamic structural model of antibiotic prescribing for forward-looking general practitioners (GP) in the presence of uncertainty concerning antibiotics’ effectiveness. Our model endogenizes information acquisition and features cross-patient learning from observed clinical microbiological testing. Reducing uncertainty is costly so that GPs have incentives to under-diagnose antibiotic resistance. Using patient-GP-level population data we estimate the structural parameters of our model and provide a framework for counterfactual evaluations of policy measures such as mandatory diagnostic testing, rapid resistance diagnostics, and the introduction of an antibiotic tax.

CCE organizes regular seminars, usually on Mondays from 13:00 to 14:15. These seminars are open to everyone.  

The seminar covers topics from all research fields in structural econometrics and computational economics including theoretical, empirical, methodological issues.