Measuring electronic communication networks in virtual care teams using electronic health records access-log data

Xi Zhu; Shin-Ping Tu; Daniel Sewell; Nengliang Aaron Yao; Vimal Mishra; Alan Dow; Colin Banas

doi:10.1016/j.ijmedinf.2019.05.012

Measuring electronic communication networks in virtual care teams using electronic health records access-log data

Int J Med Inform. 2019 Aug:128:46-52. doi: 10.1016/j.ijmedinf.2019.05.012. Epub 2019 May 13.

Authors

Xi Zhu¹, Shin-Ping Tu², Daniel Sewell³, Nengliang Aaron Yao⁴, Vimal Mishra⁵, Alan Dow⁵, Colin Banas⁵

Affiliations

¹ University of Iowa, Department of Health Management and Policy, 145 N Riverside Dr, N222, Iowa City, IA 52242, United States. Electronic address: xi-zhu@uiowa.edu.
² University of California Davis, Department of Internal Medicine, Davis, CA, United States.
³ University of Iowa, Department of Biostatistics, Iowa City, IA, United States.
⁴ University of Virginia, Department of Public Health Sciences, Charlottesville, VA, United States.
⁵ Virginia Commonwealth University, Department of Internal Medicine, Richmond, VA, United States.

PMID: 31160011
DOI: 10.1016/j.ijmedinf.2019.05.012

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.

Keywords: Communication networks; Electronic health records; Methods; Virtual care teams.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Communication*
Computer Communication Networks / organization & administration*
Electronic Health Records / statistics & numerical data*
Health Personnel / standards*
Humans
Patient Care Team / organization & administration*
Primary Health Care / organization & administration*
Telemedicine / organization & administration*