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Networked Behaviors Associated With a Large-Scale Secure Messaging Network: Cross-Sectional Secondary Data Analysis
Laura Rosa Baratta1, Linlin Xia2, Daphne Lew3
1Division of Biology & Biomedical Sciences, Washington University School of Medicine in St. Louis, St. Louis, MO, United States.
JMIR Medical Informatics
|July 10, 2025
Summary
Secure messaging networks reveal communication patterns among health care professionals. Connectivity influences messaging behaviors, offering insights for improved clinical coordination and patient outcomes.
Area of Science:
- Health Informatics
- Social Network Analysis
- Healthcare Communication Systems
Background:
- Secure messaging is the preferred communication method for healthcare professionals.
- Understanding communication networks is crucial for optimizing healthcare delivery.
- Limited research exists on the structure and dynamics of these networks.
Purpose of the Study:
- To investigate the characteristics of a large-scale secure messaging network.
- To analyze the association between network structure and healthcare professional messaging behaviors.
Main Methods:
- Social network analysis of secure messaging data from a large Midwestern health system (June-November 2023).
- Quantified network properties at global and individual levels.
- Used hierarchical clustering to identify professional groups and assess messaging behaviors (read/response times, message volume, length).
Main Results:
- The network comprised 31,800 professionals and over 7.6 million messages.
- Network characteristics varied significantly by practice setting and professional role.
- Four distinct clusters emerged, showing significant differences in messaging behaviors; one cluster of inpatient physicians demonstrated highest connectivity and fastest response times.
Conclusions:
- Healthcare professional connectivity within secure messaging networks varies by role and setting.
- Network connectivity is linked to daily messaging behaviors.
- Findings offer insights for interventions to streamline communication and potentially improve clinician work and patient outcomes.
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