How Pharmacoepidemiology Networks Can Manage Distributed Analyses to Improve Replicability and Transparency and Minimize Bias

Project Title How Pharmacoepidemiology Networks Can Manage Distributed Analyses to Improve Replicability and Transparency and Minimize Bias
Date
Tuesday, January 15, 2019
Location
Description

Several pharmacoepidemiology networks have been developed over the past decade that use a distributed approach, implementing the same analysis at multiple data sites, to preserve privacy and minimize data sharing. Distributed networks are efficient, by interrogating data on very large populations. The structure of these networks can also be leveraged to improve replicability, increase transparency, and reduce bias. The authors describe some features of distributed networks using, as examples, the Canadian Network for Observational Drug Effect Studies, the Sentinel System in the USA, and the European Research Network of Pharmacovigilance and Pharmacoepidemiology.

Corresponding Author

Robert W. Platt, Department of Epidemiology, Biostatistics, and Occupational Health, McGill University, 1020 Pine Ave W, Montreal, Quebec H3A 1A2, Canada. Email: robert.platt@mcgill.ca

Authors

Robert W. Platt, Richard Platt, Jeffrey S. Brown, David A. Henry, Olaf H. Klungel, Samy Suissa