JMIR Publications

ABSTRACT

Background:

Communication among healthcare professionals is essential for effective clinical care. Asynchronous text-based clinician communication—secure messaging— is rapidly becoming the preferred mode of communication. The use of secure messaging platforms across healthcare institutions creates large-scale communication networks that can be used to characterize how interaction structures affect the behaviors and outcomes of network members. However, the understanding of the structure and interactions within these networks is relatively limited.

Objective:

To investigate the characteristics of a large-scale secure messaging network and its association with healthcare professional messaging behaviors.

Methods:

Data on EHR-integrated secure messaging use from 14 inpatient and 282 outpatient practice locations within a large Midwestern health system over a 6-month period (June 1, 2023—November 30, 2023) were collected. Social network analysis techniques were utilized to quantify the global (network)- and node (healthcare professional)-level properties of the network. Hierarchical clustering techniques were employed to identify clusters of healthcare professionals based on network characteristics; associations between the clusters and the following messaging behaviors were assessed: message read time, message response time, total volume of messages, character length of messages sent, and character length of messages received.

Results:

The dataset included 31,800 healthcare professionals and 7,672,832 messages; the resultant messaging network consisted of 31,800 nodes and 1,228,041 edges. Network characteristics differed based on professional roles and practice location (P<.001). Four clusters were identified, representing differences in connectivity within the network. Statistically significant differences across clusters were identified between all considered secure messaging behaviors (P<.001), implying a potential link between one’s network connectivity and secure messaging behaviors.

Conclusions:

Secure messaging use within a large healthcare system manifested as an expansive communication network where connectivity varied based on healthcare professional role and practice setting. These findings provide insights into the complexities of communication and coordination structures among healthcare providers and downstream secure messaging use.