Mini-Sentinel: Signal Evaluation Methods (Automated)

Project Title Mini-Sentinel: Signal Evaluation Methods (Automated)
Date Posted
Wednesday, August 17, 2011
Status
Complete
Deliverables
Mini-Sentinel Methods: Signal Evaluation Report
Description

Project to evaluate statistical methods to improve automated confounding control in electronic healthcare databases in a range of drug safety scenarios by 1) applying high-dimensional propensity score adjustment to medical product safety surveillance systems and 2) examining the effect of Z-bias, a type of bias caused by adjusting for an instrumental variable in an analysis.
Workgroup Leader(s)

Robert Glynn PhD, ScD; Brigham and Women’s Hospital Division of Pharmacoepidemiology and Pharmacoeconomics, and Harvard Medical School, Boston, MA
Workgroup Members

Jeremy A. Rassen ScD; Jessica Myers PhD, ScD; Sebastian Schneeweiss MD, ScD; Joshua J. Gagne MS, PharmD; Krista F. Huybrechts MS, PhD; Brigham and Women’s Hospital Division of Pharmacoepidemiology and Pharmacoeconomics, and Harvard Medical School, Boston, MA

Kenneth J. Rothman MPH, DrPH; RTI International, Research Triangle Park, NC

Marshall M. Joffe MD, MPH, PhD; University of Pennsylvania School of Medicine, Philadelphia, PA
Project ID
MD00004
Related Links
Brigham and Women's Hospital Division of Pharmacoepidemiology and Pharmacoeconomics
Using High-Dimensional Propensity Scores to Automate Confounding Control in a Distributed Medical Product Safety Surveillance System
Effects of Adjusting for Instrumental Variables on Bias and Precision of Effect Estimates