Sebastian Schneeweiss, MD, ScD; Jeremy A. Rassen, ScD; Jeffrey S. Brown, PhD; Kenneth J. Rothman, DrPH; Laura Happe, PharmD, MPH; Peter Arlett, MD; Gerald Dal Pan, MD, MHS; Wim Goettsch, PhD; William Murk, PhD; Shirley V. Wang, PhD
Disclaimer: The views expressed in this article are those of the authors and may not be understood or quoted as being made on behalf of or reflecting the position of the European Medicines Agency or the U.S. Food and Drug Administration.
Financial Support: Writing of this manuscript was supported by internal funds from the Division of Pharmacoepidemiology and Pharmacoeconomics of the Department of Medicine at Brigham and Women's Hospital and Harvard Medical School.
Disclosures: Dr. Schneeweiss reports grants from the U.S. Food and Drug Administration, the Patient-Centered Outcomes Research Institute, and the National Institutes of Health during the conduct of the study and personal fees from WHISCON, equity in Aetion, and being principal investigator of research contracts to Brigham and Women's Hospital from Bayer, Vertex, Boehringer Ingelheim, and the Arnold Foundation outside the submitted work. In addition, Dr. Schneeweiss has a patent for a database system for analysis of longitudinal data sets, with no royalties paid. Dr. Rassen reports that he is an employee of and has an ownership stake in Aetion outside the submitted work. Dr. Murk reports that he is an employee of and holds stock options in Aetion outside the submitted work. Dr. Wang reports being principal investigator on research contracts to Brigham and Women's Hospital from Boehringer Ingelheim, Novartis, and Johnson & Johnson, and the Arnold Foundation outside the submitted work. She is also a consultant to Aetion for unrelated work. Dr. Arlett is a full-time employee of the European Medicines Agency. Dr. Dal Pan is a full-time employee of the Food and Drug Administration. Authors not named here have disclosed no conflicts of interest. Disclosures can also be viewed at www.acponline.org/authors/icmje/ConflictOfInterestForms.do?msNum=M18-3079.
Corresponding Author: Shirley V. Wang, PhD, 1620 Tremont Street, Suite 303, Boston, MA 02120; e-mail, firstname.lastname@example.org.
Current Author Addresses: Drs. Schneeweiss and Wang: 1620 Tremont Street, Suite 303, Boston, MA 02120.
Drs. Rassen and Murk: 1441 Broadway 20th Floor, New York, NY 10018.
Dr. Brown: 401 Park Drive, Suite 401 East, Boston, MA 02215.
Dr. Rothman: 307 Waverley Oaks Road, Suite 101, Waltham, MA 02452-8413.
Dr. Happe: JMCP, 675 North Washington Street, Suite 220, Alexandria, VA 22314.
Dr. Arlett: Department of Pharmacovigilance and Epidemiology, European Medicines Agency, 30 Churchill Place, London E14 5EU, United Kingdom.
Dr. Dal Pan: 10903 New Hampshire Avenue, Silver Spring, MD 20993.
Dr. Goettsch: Zorginstituut Nederland, Health Care Insurance Board Health Care TA Program, Postbus 320, NL-1110 AH Diemen, the Netherlands.
Author Contributions: Conception and design: S. Schneeweiss, S.V. Wang, J.A. Rassen.
Analysis and interpretation of the data: S. Schneeweiss, S.V. Wang.
Drafting of the article: S. Schneeweiss, J.A. Rassen, J.S. Brown, K.J. Rothman, L. Happe, P. Arlett, G. Dal Pan, W. Goettsch, W. Murk, S.V. Wang.
Critical revision of the article for important intellectual content: S. Schneeweiss, J.A. Rassen, J.S. Brown, K.J. Rothman, L. Happe, P. Arlett, G. Dal Pan, W. Goettsch, W. Murk, S.V. Wang.
Final approval of the article: S. Schneeweiss, J.A. Rassen, J.S. Brown, K.J. Rothman, L. Happe, P. Arlett, G. Dal Pan, W. Goettsch, W. Murk, S.V. Wang.
Pharmacoepidemiologic and pharmacoeconomic analysis of health care databases has become a vital source of evidence to support health care decision making and efficient management of health care organizations. However, decision makers often consider studies done in nonrandomized health care databases more difficult to review than randomized trials because many design choices need to be considered. This is perceived as an important barrier to decision making about the effectiveness and safety of medical products. Design flaws in longitudinal database studies are avoidable but can be unintentionally obscured in the convoluted prose of methods sections, which often lack specificity. We propose a simple framework of graphical representation that visualizes study design implementations in a comprehensive, unambiguous, and intuitive way; contains a level of detail that enables reproduction of key study design variables; and uses standardized structure and terminology to simplify review and communication to a broad audience of decision makers. Visualization of design details will make database studies more reproducible, quicker to review, and easier to communicate to a broad audience of decision makers.
Schneeweiss S, Rassen JA, Brown JS, et al. Graphical Depiction of Longitudinal Study Designs in Health Care Databases. Ann Intern Med. 2019;170:398–406. [Epub ahead of print 12 March 2019]. doi: https://doi.org/10.7326/M18-3079
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Published: Ann Intern Med. 2019;170(6):398-406.
Published at www.annals.org on 12 March 2019
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