A qualitative study of interprofessional learning related to electronic health record (EHR) medication reconciliation within a social knowledge networking (SKN) system
Received 20 December 2018
Accepted for publication 12 March 2019
Published 29 March 2019 Volume 2019:11 Pages 23—41
Checked for plagiarism Yes
Review by Single-blind
Peer reviewer comments 2
Editor who approved publication: Professor Russell Taichman
Pavani Rangachari,1 Kevin C Dellsperger,2 R Karl Rethemeyer3
1Department of Interdisciplinary Health Sciences, College of Allied Health Sciences, Augusta University, Augusta, GA 30912, USA; 2Cardiovascular Division, AU Health, Department of Medicine, Medical College of Georgia, Augusta University, Augusta, GA, 30912, USA; 3Rockefeller College of Public Affairs and Policy, University at Albany, State University of New York, Albany, NY, 12222, USA
Background: Similar to issues faced in health systems across the USA, AU Health faced a scenario of low physician engagement in and limited use of its Electronic Health Record (EHR) Medication Reconciliation (MedRec) technology, which translated to high rates of medication discrepancies and low accuracy of the patient’s active medication list, during transitions of care. In fall 2016, a 2-year research grant was secured to pilot a Social Knowledge Networking (SKN) system on “EHR MedRec” to enable AU Health to progress from “limited use” of EHR MedRec technology to “meaningful use.”
Purpose: The aims of this study were to 1) examine dynamics of interprofessional knowledge exchange and learning related to EHR MedRec on the SKN system and 2) explore associations between “SKN Use” and “Meaningful Use (MU) of EHR MedRec,” with the latter being assessed in terms of adherence to best practices in EHR MedRec.
Methods: Over a 1-year period, 50 SKN Users (practitioners from inpatient and outpatient medicine settings), participated in discussing issues related to EHR MedRec, moderated by five SKN Moderators (senior administrators). Qualitative analysis was used to understand dynamics of interprofessional knowledge exchange and descriptive analysis was used to examine trends in two measures of MU of EHR MedRec, identified for the study.
Results: Interprofessional knowledge exchanges related to EHR MedRec on the SKN system, progressed from “problem statements” to “problem-solving statements” to “IT system education” to “best-practice assertions” to “culture change assertions” to “collective learning (aha) moments” to lay a foundation for practice change. These interprofessional learning dynamics were associated with distinct improvement trends in both measures of MU of EHR MedRec technology.
Conclusion: Results suggest that an SKN system could be a valuable tool in enabling MU of EHR MedRec technology. The study helps identify strategies for the creation of “learning health systems,” to enable successful change implementation in healthcare organizations.
Keywords: interprofessional learning, qualitative analysis, electronic health records, medication reconciliation, meaningful use, change implementation
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