Abstract
Objective This study attempts to characterize the inpatient communication network within a
quaternary pediatric academic medical center by applying network analysis methods
to secure text-messaging data.
Methods We used network graphing and statistical software to create network models of an
inpatient communication system with secure text-messaging data from physicians, nurses,
and other ancillary staff in an academic medical center. Descriptive statistics about
the network, users within the network, and visualizations informed the team's understanding
of the network and its components.
Results Analysis of messages exchanged over approximately 23 days revealed a large, scale-free
network with 4,442 nodes and 59,913 edges. Quantitative description of user behavior
(messages sent and received) and network metrics (i.e., importance of nodes within
a network) revealed several operational and clinical roles both sending and receiving > 1,000
messages over this time period. While some of these nodes represented expected “dispatcher”
roles in our inpatient system, others occupied important frontline clinical roles
responsible for bedside clinical care.
Conclusion Quantitative and network analysis of secure text-messaging logs revealed several
key operational and clinical roles at risk for alert fatigue and information overload.
This analysis also revealed a communication network highly reliant on these key roles,
meaning disruption to these individuals or their workflows could lead to dysfunction
of the communication network. While secure text-messaging applications play increasingly
important roles in facilitating inpatient communication, little is understood about
the impact these systems have on health care providers. Developing methods to understand
and optimize communication between inpatient providers might help operational and
clinical leaders to proactively prevent poorly understood pitfalls associated with
these systems and build resilient and effective communication structures.
Keywords
hospital communication systems - interdisciplinary communication - text messaging
- hospital information systems
