FEATURESChallenges Frequently Encountered in the Secondary Use of Electronic Medical Record Data for ResearchEdmondson, Meghan E. BSN, RN; Reimer, Andrew P. PhD, RNAuthor Information Author Affiliation: Frances Payne Bolton School of Nursing, Case Western Reserve University, Cleveland, Ohio. The authors have disclosed that they have no significant relationships with, or financial interest in, any commercial companies pertaining to this article. Corresponding author: Meghan E. Edmondson, BSN, RN, Frances Payne Bolton School of Nursing, Case Western Reserve University, 10900 Euclid Ave, Cleveland, OH 44106 (firstname.lastname@example.org). CIN: Computers, Informatics, Nursing: July 2020 - Volume 38 - Issue 7 - p 338-348 doi: 10.1097/CIN.0000000000000609 Buy Take the CE Test Metrics Abstract The wide adoption of electronic medical records and subsequent availability of large amounts of clinical data provide a rich resource for researchers. However, the secondary use of clinical data for research purposes is not without limitations. In accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, we conducted a systematic review to identify current issues related to secondary use of electronic medical record data via MEDLINE and CINAHL databases. All articles published until June 2018 were included. Sixty articles remained after title and abstract review, and four domains of potential limitations were identified: (1) data quality issues, present in 91.7% of the articles reviewed; (2) data preprocessing challenges (53.3%); (3) privacy concerns (18.3%); and (4) potential for limited generalizability (21.7%). Researchers must be aware of the limitations inherent to the use of electronic medical record data for research and consider the potential effects of these limitations throughout the entire study process, from initial conceptualization to the identification of adequate sources that can provide data appropriate for answering the research questions, analysis, and reporting study results. Consideration should also be given to using existing data quality assessment frameworks to facilitate use of standardized data quality definitions and further efforts of standard data quality reporting in publications. Copyright © 2020 Wolters Kluwer Health, Inc. All rights reserved.