ArticleBMC health services research2013
Network analysis of team communication in a busy emergency department.
Article in BMC health services research, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
20 citing papers in PubMed.
- Residents' perceptions of interprofessional education and collaboration in clinical settings and implications for medical education: a scoping review.Korean journal of medical education · 2026Article
- An electronic health record metadata-mining approach to identifying patient-level interprofessional clinician teams in the intensive care unit.Journal of the American Medical Informatics Association : JAMIA · 2025Article
- Article
- Patterns of interactions among ICU interprofessional teams: A prospective patient-shift-level survey approach.PloS one · 2024Article
- Review
- Network approaches and interventions in healthcare settings: A systematic scoping review.PloS one · 2023Article
- A network analysis of patient referrals in two district health systems in Tanzania.Health policy and planning · 2021Article
- Perception of Patient Safety Culture in the Framework of the Psychosocial Care Network in Western Amazon: A Cross-Sectional Study.Healthcare (Basel, Switzerland) · 2020Article
- Data-driven modeling of diabetes care teams using social network analysis.Journal of the American Medical Informatics Association : JAMIA · 2019Article
- Nursing Unit Design, Nursing Staff Communication Networks, and Patient Falls: Are They Related?HERD · 2018Article
- Putting the pieces together: EHR communication and diabetes patient outcomes.The American journal of managed care · 2018Observational
- The Importance of External Contacts in Job Performance: A Study in Healthcare Organizations Using Social Network Analysis.International journal of environmental research and public health · 2018Article
- Communication in the Electronic Age: an Analysis of Face-to-Face Physician-Nurse Communication in the Emergency Department.Journal of healthcare informatics research · 2017Article
- Social network analysis of Iranian researchers in the field of violence.Chinese journal of traumatology = Zhonghua chuang shang za zhi · 2016Article
- Implementation of a team-based physician staffing model at an academic emergency department.The western journal of emergency medicine · 2014Article
- Tumultuous atmosphere (physical, mental), the main barrier to emergency department inter-professional communication.Global journal of health science · 2014Article
- Barriers to implementation of a redesign of information transfer and feedback in acute care: results from a multiple case study.BMC health services research · 2014Article
- Social networking in health system for knowledge translation.Journal of cardiovascular and thoracic research · 2014Article
- A mixed methods study of backup behavior among interprofessional ICU teams.Heart & lung : the journal of critical careArticle
- Knowing your team in the intensive care unit: an ethnographic study on familiarity.Journal of interprofessional careArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
Abstract
backgroundThe Emergency Department (ED) is consistently described as a high-risk environment for patients and clinicians that demands colleagues quickly work together as a cohesive group. Communication between nurses, physicians, and other ED clinicians is complex and difficult to track. A clear understanding of communications in the ED is lacking, which has a potentially negative impact on the design and effectiveness of interventions to improve communications. We sought to use Social Network Analysis (SNA) to characterize communication between clinicians in the ED.
methodsOver three-months, we surveyed to solicit the communication relationships between clinicians at one urban academic ED across all shifts. We abstracted survey responses into matrices, calculated three standard SNA measures (network density, network centralization, and in-degree centrality), and presented findings stratified by night/day shift and over time.
resultsWe received surveys from 82% of eligible participants and identified wide variation in the magnitude of communication cohesion (density) and concentration of communication between clinicians (centralization) by day/night shift and over time. We also identified variation in in-degree centrality (a measure of power/influence) by day/night shift and over time.
conclusionsWe show that SNA measurement techniques provide a comprehensive view of ED communication patterns. Our use of SNA revealed that frequency of communication as a measure of interdependencies between ED clinicians varies by day/night shift and over time.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.