Measuring electronic communication networks in virtual care teams using electronic health records access-log data. (August 2019)

• Record Type: Journal Article
• Authors: Zhu, Xi; Tu, Shin-Ping; Sewell, Daniel; Yao, Nengliang (Aaron); Mishra, Vimal; Dow, Alan; Banas, Colin
• Is Part Of: International journal of medical informatics. Volume 128(2019)
• Page Start: 46
• Page End: 52
• Publication Date: 2019-08
• Subjects: Electronic health records -- Virtual care teams -- Communication networks -- Methods; Medical informatics -- Periodicals; Information science -- Periodicals; Computers -- Periodicals; Medical technology -- Periodicals; Medical Informatics -- Periodicals; Technology, Medical -- Periodicals; Computers; Information science; Medical informatics; Medical technology; Electronic journals; Periodicals; Electronic journals; 610.285
• DOI: 10.1016/j.ijmedinf.2019.05.012
• Languages: English
• ISSNs: 1386-5056

Abstract

Graphical abstract: Highlights: We developed a method for measuring electronic communication networks in virtual care teams using EHR access-log data. Electronic communication networks in the sample patient's virtual care teams showed substantial structural variations. Electronic communication networks' structures differ from those of random networks and are associated with patients' clinical differences. Core teams derived from the analysis of electronic communication networks mirror the composition of the core team defined by practice experts. Abstract: Objective: To develop methods for measuring electronic communication networks in virtual care teams using electronic health records (EHR) access-log data. Methods: For a convenient sample of 100 surgical colorectal cancer patients, we used time-stamped EHR access-log data extracted from an academic medical center's EHR system to construct communication networks among healthcare professionals (HCPs) in each patient's virtual care team. We measured communication linkages between HCPs using the inverse of the average time between access events in which the source HCPs sent information to and the destination HCPs retrieved information from the EHR system. Social network analysis was used to examine and visualize communication network structures, identify principal care teams, and detect meaningful structural differences across networks. We conducted a non-parametric multivariate analysis of variance (MANOVA) to test the association between care teams' communication network structures and patients' cancer stage and site. Results: The 100 communication networks showed substantial variations in size and structures. Principal care teams, the subset of HCPs who formed the core of the communication networks, had higher proportions of nurses, physicians, and pharmacists and a lower proportion of laboratory medical technologists than the overall networks. The distributions of conditional uniform graph quantiles suggested that our network-construction technique captured meaningful underlying structures that were different from random unstructured networks. MANOVA results found that the networks' topologies were associated with patients' cancer stage and site. Conclusions: This study demonstrates that it is feasible to use EHR access-log data to measure and examine communication networks in virtual care teams. The proposed methods captured salient communication patterns in care teams that were associated with patients' clinical differences.