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First published October 12, 2005 as JAMIA PrePrint; doi:10.1197/jamia.M1749
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J Am Med Inform Assoc. 2006;13:16-23. DOI 10.1197/jamia.M1749.
© 2006 American Medical Informatics Association

Position Paper

The Use and Interpretation of Quasi-Experimental Studies in Medical Informatics

Anthony D. Harris, MD, MPH, Jessina C. McGregor, PhD, Eli N. Perencevich, MD, MS, Jon P. Furuno, PhD, Jingkun Zhu, MS, Dan E. Peterson, MD, MPH and Joseph Finkelstein, MD

Affiliations of the authors: Department of Epidemiology and Preventive Medicine, University of Maryland, Baltimore, MD (ADH, JCM, ENP, JPF, JZ, JF); VA Maryland Health Care System, Baltimore, MD (ADH, ENP); Cereplex Inc., Germantown, MD (DEP).

Correspondence and reprints: Anthony D. Harris, MD, MPH, Division of Healthcare Outcomes Research, Department of Epidemiology and Preventive Medicine, University of Maryland School of Medicine, 100 N. Greene Street, Lower Level, Baltimore, MD; e-mail: <aharris{at}epi.umaryland.edu>.

Received for publication: 11/19/04; accepted for publication: 08/12/05.

Quasi-experimental study designs, often described as nonrandomized, pre-post intervention studies, are common in the medical informatics literature. Yet little has been written about the benefits and limitations of the quasi-experimental approach as applied to informatics studies. This paper outlines a relative hierarchy and nomenclature of quasi-experimental study designs that is applicable to medical informatics intervention studies. In addition, the authors performed a systematic review of two medical informatics journals, the Journal of the American Medical Informatics Association (JAMIA) and the International Journal of Medical Informatics (IJMI), to determine the number of quasi-experimental studies published and how the studies are classified on the above-mentioned relative hierarchy. They hope that future medical informatics studies will implement higher level quasi-experimental study designs that yield more convincing evidence for causal links between medical informatics interventions and outcomes.






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Copyright © 2006 by the American Medical Informatics Association.