Using high-dimensional propensity scores to automate confounding control in a distributed medical product safety surveillance system
Version of Record online: 19 JAN 2012
Copyright © 2012 John Wiley & Sons, Ltd.
Pharmacoepidemiology and Drug Safety
Supplement: The U.S. Food and Drug Administration's Mini-Sentinel Program
Volume 21, Issue Supplement S1, pages 41–49, January 2012
How to Cite
Rassen, J. A. and Schneeweiss, S. (2012), Using high-dimensional propensity scores to automate confounding control in a distributed medical product safety surveillance system. Pharmacoepidem. Drug Safe., 21: 41–49. doi: 10.1002/pds.2328
- Issue online: 19 JAN 2012
- Version of Record online: 19 JAN 2012
- propensity scores;
- confounding factors (epidemiology);
- multicenter study (publication type);
- epidemiological methods
Distributed medical product safety monitoring systems such as the Sentinel System, to be developed as a part of Food and Drug Administration's Sentinel Initiative, will require automation of large parts of the safety evaluation process to achieve the necessary speed and scale at reasonable cost without sacrificing validity. Although certain functions will require investigator intervention, confounding control is one area that can largely be automated. The high-dimensional propensity score (hd-PS) algorithm is one option for automated confounding control in longitudinal healthcare databases. In this article, we discuss the use of hd-PS for automating confounding control in sequential database cohort studies, as applied to safety monitoring systems. In particular, we discuss the robustness of the covariate selection process, the potential for over- or under-selection of variables including the possibilities of M-bias and Z-bias, the computation requirements, the practical considerations in a federated database network, and the cases where automated confounding adjustment may not function optimally. We also outline recent improvements to the algorithm and show how the algorithm has performed in several published studies. We conclude that despite certain limitations, hd-PS offers substantial advantages over non-automated alternatives in active product safety monitoring systems. Copyright © 2012 John Wiley & Sons, Ltd.