Network analysis of the structure of inter-professional knowledge exchange related to electronic health record medication reconciliation within a social knowledge networking system

Background: In fall 2016, a 2-year grant was secured to pilot a Social Knowledge Networking (SKN) system pertaining to Electronic Health Record (EHR) Medication Reconciliation (MedRec), to enable Augusta University Health System to progress from “limited use” of EHR MedRec technology, to “meaningful use” (MU). A total of 50 “SKN users” (practitioners), participated in discussing practice issues related to EHR MedRec, over a 1-year period. These discussions were moderated by five “SKN moderators” (senior administrators). The pilot study, completed in fall 2018, found that inter-professional knowledge exchanges on the SKN, enabled several collective learning (“aha”) moments to emerge. These learning dynamics in turn, were associated with distinct improvement trends in two measures of MU of EHR MedRec technology, identified for the study. A key takeaway was that an SKN could be a valuable tool in enabling MU of EHR MedRec technology. Purpose: The study’s key findings related to the content and dynamics of inter-professional knowledge exchange on the SKN system, and their association with trends in measures of MU of EHR MedRec technology, have been described in a separate publication. This paper seeks to describe the structure of inter-professional knowledge exchange (or the pattern of connections) related to EHR MedRec, over the 1-year SKN period. Methods: Social network analysis (SNA) techniques were used to describe the structure of inter-professional knowledge exchange on the SKN system. Results: Results revealed that three of the five SKN moderators played a strong “collective brokerage” role in facilitating inter-professional knowledge exchange related to EHR MedRec, to enable learning and practice change. Together, they played complementary roles in reinforcing best-practice assertions, providing IT system education, and synthesizing collective learning moments, to enable “champions for change” to emerge from among SKN users. Conclusion: Results provide insight into the structure of effective knowledge-sharing networks for enabling inter-professional learning and practice change in health care organizations.