TY - JOUR
T1 - Inpatient Communication Networks
T2 - Leveraging Secure Text-Messaging Platforms to Gain Insight into Inpatient Communication Systems
AU - Hagedorn, Philip A.
AU - Kirkendall, Eric S.
AU - Spooner, S. Andrew
AU - Mohan, Vishnu
N1 - Publisher Copyright:
© 2019 Georg Thieme Verlag KG Stuttgart. New York.
PY - 2019
Y1 - 2019
N2 - 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.
AB - 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.
KW - hospital communication systems
KW - hospital information systems
KW - interdisciplinary communication
KW - text messaging
UR - http://www.scopus.com/inward/record.url?scp=85068187628&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85068187628&partnerID=8YFLogxK
U2 - 10.1055/s-0039-1692401
DO - 10.1055/s-0039-1692401
M3 - Article
C2 - 31242514
AN - SCOPUS:85068187628
SN - 1869-0327
VL - 10
SP - 471
EP - 478
JO - Applied Clinical Informatics
JF - Applied Clinical Informatics
IS - 3
ER -