Gagne, JoshuaGlynn, RobertRassen, JeremyWalker, AlexanderDaniel, Gregory W.Sridhar, GayathriSchneeweiss, Sebastian2014-04-112014Gagne, Joshua J., Robert J. Glynn, Jeremy A. Rassen, Alexander M. Walker, Gregory W. Daniel, Gayathri Sridhar, and Sebastian Schneeweiss. 2014. “Active safety monitoring of newly marketed medications in a distributed data network: application of a semi-automated monitoring system.” Clinical pharmacology and therapeutics 92 (1): 80-86. doi:10.1038/clpt.2011.369. http://dx.doi.org/10.1038/clpt.2011.369.0009-9236http://nrs.harvard.edu/urn-3:HUL.InstRepos:12064371We developed a semi-automated active monitoring system that uses sequential matched-cohort analyses to assess drug safety across a distributed network of longitudinal electronic healthcare data. In a retrospective analysis, we showed that the system would have identified cerivastatin-induced rhabdomyolysis. In this study, we evaluated whether the system would generate alerts for three drug-outcome pairs: rosuvastatin and rhabdomyolysis (known null association), rosuvastatin and diabetes mellitus, and telithromycin and hepatotoxicity (two examples for which alerting would be questionable). During >5 years of monitoring, rate differences (RDs) comparing rosuvastatin to atorvastatin were -0.1 cases of rhabdomyolysis per 1,000 person-years (95% CI, -0.4, 0.1) and -2.2 diabetes cases per 1,000 person-years (95% CI, -6.0, 1.6). The RD for hepatotoxicity comparing telithromycin to azithromycin was 0.3 cases per 1,000 person-years (95% CI, -0.5, 1.0). In a setting in which false positivity is a major concern, the system did not generate alerts for three drug-outcome pairs.en-USJournal Article2014-04-1110.1038/clpt.2011.369