Development and Illustration of a Framework for Conducting Nonrandomized Studies of Medication Safety and Effectiveness Using Healthcare Databases

    Basic Details
    Date Posted
    Friday, December 10, 2021
    Status
    In progress
    Description

    This project will develop a causal inference framework for safety and effectiveness evaluations of medical products that leverage claims data alone or in combination with electronic health record data. The framework will consider the domains of study conduct including transparency, study implementation, and robustness evaluation. This framework can be used as a guide for the design and conduct of an inferential study, or to efficiently evaluate studies implemented by others. This project will demonstrate the value and utility of the proposed framework by implementing these principles in one or more case-example(s) using routinely collected healthcare data.

    Information
    Time Period
    June 1, 2021 - November 30, 2022
    Data Source(s)
    Medicare claims data linked to structured and unstructured electronic health record (EHR) fields from the Mass General Brigham (MGB) health system
    Workgroup Leader(s)

    Rishi Desai, Ph.D.; Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston MA

    Workgroup Member(s)

    Sebastian Schneeweiss, MD, ScD; Shirley Wang, PhD, ScM; Richard Wyss, PhD, MSc; Elisabetta Patorno, MD, DrPH; Sushama Sreedhara, MBBS, MSPH; Luke Zabotka, BA; Shamika More, MS; Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA

    Patrick Heagerty, PhD; Department of Biostatistics at the University of Washington, Seattle, WA

    Jennifer Clark Nelson, PhD; Biostatistics Unit, Kaiser Permanente Washington Health Research Institute, Seattle, WA

    Darren Toh, ScD; Department of Population Medicine, Harvard Pilgrim Health Care Institute and Harvard Medical School, Boston, MA

    Xu Shi, PhD; Department of Biostatistics, University of Michigan, Ann Arbor, MI

    Sarah Dutcher, PhD, MS; Jie (Jenni) Li, PhD; Dinci Pennap, PhD, MPH, MS; Christina Greene, PhD; Office of Surveillance and Epidemiology, Center for Drug Evaluation and Research, U.S. Food and Drug Administration, Silver Spring, MD