Details
The purpose of this project is to develop an approach to using quantitative bias analysis methods to adaptively determine whether and when medical chart validation can be stopped early within the context of Sentinel assessments.
The newly developed approach will be applied to one or more completed Sentinel assessments in which medical record review for outcome validation was performed to test the empirical and practical performance of the method.
Contributors
Joshua J. Gagne, PharmD, ScD; Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA
Noelle Cocoros, DSc, MPH; Department of Population Medicine, Harvard Pilgrim Health Care Institute and Harvard Medical School, Boston, MA
Yun Lu, PhD, MS; Center for Biologics Evaluation and Research, FDA, Silver Spring, MD
Sandra Feibelmann, MPH; Department of Population Medicine, Harvard Pilgrim Health Care Institute and Harvard Medical School, Boston, MA
Richard Forshee, PhD; Office of Biostatistics and Epidemiology, Center for Biologics Evaluation and Research, FDA, Silver Spring, MD
Matt Fox, DSc, MPH; Department of Epidemiology, Boston University School of Public Health, Boston University, Boston, MA
Chandrasekar Gopalakrishnan, MD, MPH, CPH; Martin Kulldorff, PhD; Sebastian Schneeweiss, MD, ScD; Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA
Christopher Jankosky, MD; Yun Lu, PhD, MS; Azadeh Shoaibi, PhD, MS, MHS; Center for Biologics Evaluation and Research, FDA, Silver Spring, MD
Timothy Lash, DSc, MPH; Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA