Contents lists available at ScienceDirect International Journal of Medical Informatics journal homepage: www.elsevier.com/locate/ijmedinf Education and Training on Electronic Medical Records (EMRs) for health care professionals and students: A Scoping Review Mahnaz Samadbeik a,b, *, Farhad Fatehi a,c , Mark Braunstein d,e , Ben Barry f , Marzieh Saremian g , Fatemeh Kalhor g , Sisira Edirippulige a a Centre for Online Health, The University of Queensland, Brisbane, Australia b Social Determinants of Health Research Center, Lorestan University of Medical Sciences, Khorramabad, Iran c School of Advanced Technologies in Medicine, Tehran University of Medical Sciences, Tehran, Iran d School of Interactive Computing, Georgia Tech, Atlanta, United States of America e The Australian e-Health Research Centre, Commonwealth Scientific and Industrial Research, Australia f Faculty of Medicine, The University of Queensland, Australia g Student Research Committee, Lorestan University of Medical Sciences, Khorramabad, Iran ARTICLE INFO Keywords: Education Training Electronic Medical Records (EMRs) Health care professionals Students ABSTRACT Background and objectives: The ability of health care providers and students to use EMRs efciently can lead to achieving improved clinical outcomes. Training policies and strategies play a major role in successful technology implementation and ongoing use of the EMR systems. To provide evidence-based guidance for developing and implementing educational interventions and training, we reviewed and summarized the current literature on EMR training targeting both healthcare professionals (HCP) and students. Methods: We used the Joanna Briggs Institute (JBI) approach for scoping reviews and the PRISMA extension of scoping reviews (PRISMA-ScR) checklist for reporting our review. 46 full-text articles that met the eligibility criteria were selected for the review. Narrative synthesis was performed to summarize the evidence using nu- merical and descriptive analysis. We used inductive content analysis for categorizing the training methods. Also, the modifed version of the Kirkpatrick's levels model was used for abstracting the training outcome. Results: Five types of training methods were identifed: one-on-one training, peer-coach training, classroom training (CRT), computer-based training (CBT), and blended training. A variety of CBT platforms were used, including a prototype academic electronic medical record system (AEMR), AEMR/simulated EMR (Sim-EMR), mobile based AEMR, eLearning, and electronic educational materials. Each training intervention could have resulted in several outcomes. Most outcomes were related to levels 1–3 of the Kirkpatrick model that involves learners (n = 108), followed by level 4a that involves organizations (n = 7), and lastly level 4b that involves patients (n = 1). The outcomes related to participants' knowledge (level 2b) was the most often measured training outcome (n = 44). Conclusions: This review presents a comprehensive synthesis of the evidence on EMR training. A variety of training methods, participants, locations, strategies, and outcomes were described in the studies. Training should be aligned with the particular training needs, training objectives, EMR system utilized, and organizational en- vironment. A training plan should include an overall goal and SMART (Specifc, Measurable, Achievable, Realistic, Tangible) training objectives, that would allow a more rigorous evaluation of the training outcomes. 1. Introduction The importance of the availability of timely medical information for health care professionals to optimize diagnosis and the clinical decision process to determine treatment has been well-documented [1–4]. With the advancement of digital technologies, electronic medical records (EMRs) have emerged as the preferred method for recording, storing, retrieving and collating health and medical information. The potential advantages of EMR have been widely recognized [5–7]. EMRs are the electronic format of medical records that replace traditional paper- https://doi.org/10.1016/j.ijmedinf.2020.104238 Received 24 May 2020; Received in revised form 1 July 2020; Accepted 23 July 2020 ⁎ Corresponding author at: Centre for Online Health, Building 33, Princess Alexandra Hospital, Queensland 4102, Australia. E-mail addresses: Samadbeik.m@lums.ac.ir (M. Samadbeik), fatehi@gmail.com (F. Fatehi), mark.braunstein@csiro.au, mark.braunstein@cc.gatech.edu (M. Braunstein), b.barry@uq.edu.au (B. Barry), marziehsaremian@yahoo.com (M. Saremian), kalhorfatemeh1373@gmail.com (F. Kalhor), s.edirippulige@uq.edu.au (S. Edirippulige). International Journal of Medical Informatics 142 (2020) 104238 Available online 14 August 2020 1386-5056/ © 2020 Elsevier B.V. All rights reserved. T