» Articles » PMID: 31242514

Inpatient Communication Networks: Leveraging Secure Text-Messaging Platforms to Gain Insight into Inpatient Communication Systems

Overview
Publisher Thieme
Date 2019 Jun 27
PMID 31242514
Citations 8
Authors
Affiliations
Soon will be listed here.
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.

Citing Articles

Characterizing the Patterns of Electronic Health Record-Integrated Secure Messaging Use: Cross-Sectional Study.

Baratta L, Harford D, Sinsky C, Kannampallil T, Lou S J Med Internet Res. 2023; 25:e48583.

PMID: 37801359 PMC: 10589827. DOI: 10.2196/48583.


Electronic Medical Record-Based Electronic Messaging Among Patients with Breast Cancer: A Systematic Review.

Conroy M, Powell M, Suelzer E, Pamulapati S, Min H, Wright T Appl Clin Inform. 2022; 14(1):134-143.

PMID: 36581054 PMC: 9931493. DOI: 10.1055/a-2004-6669.


Effectiveness, safety, and efficiency of a drive-through care model as a response to the COVID-19 testing demand in the United States.

Ravi S, Graber-Naidich A, Sebok-Syer S, Brown I, Callagy P, Stuart K J Am Coll Emerg Physicians Open. 2022; 3(6):e12867.

PMID: 36570369 PMC: 9767858. DOI: 10.1002/emp2.12867.


Voting with Their Thumbs: Assessing Communication Technology Use by Medical, Nursing, Midwifery, and Allied Health Clinicians.

Lynch D, Jedwab R, Foster J, Planche Y, Whitelaw L, Shi J Appl Clin Inform. 2022; 13(4):916-927.

PMID: 36170881 PMC: 9519269. DOI: 10.1055/s-0042-1757158.


Predicting Health Care Providers' Acceptance of a Personal Health Record Secure Messaging Feature.

Yousef C, Salgado T, Farooq A, Burnett K, McClelland L, Abu Esba L Appl Clin Inform. 2022; 13(1):148-160.

PMID: 35139562 PMC: 8828451. DOI: 10.1055/s-0041-1742217.


References
1.
van der Sijs H, van Gelder T, Vulto A, Berg M, Aarts J . Understanding handling of drug safety alerts: a simulation study. Int J Med Inform. 2010; 79(5):361-9. DOI: 10.1016/j.ijmedinf.2010.01.008. View

2.
Baseman J, Revere D, Painter I, Toyoji M, Thiede H, Duchin J . Public health communications and alert fatigue. BMC Health Serv Res. 2013; 13:295. PMC: 3751004. DOI: 10.1186/1472-6963-13-295. View

3.
Barabasi A, Oltvai Z . Network biology: understanding the cell's functional organization. Nat Rev Genet. 2004; 5(2):101-13. DOI: 10.1038/nrg1272. View

4.
Artis K, Dyer E, Mohan V, Gold J . Accuracy of Laboratory Data Communication on ICU Daily Rounds Using an Electronic Health Record. Crit Care Med. 2016; 45(2):179-186. PMC: 5228604. DOI: 10.1097/CCM.0000000000002060. View

5.
Shah N, Seger A, Seger D, Fiskio J, Kuperman G, Blumenfeld B . Improving acceptance of computerized prescribing alerts in ambulatory care. J Am Med Inform Assoc. 2005; 13(1):5-11. PMC: 1380196. DOI: 10.1197/jamia.M1868. View