ArticleSocial networks2017
Contact networks in the emergency department: Effects of time, environment, patient characteristics, and staff role.
Article in Social networks, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 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
8 citing papers in PubMed.
- Investigating healthcare worker mobility and patient contacts within a UK hospital during the COVID-19 pandemic.Communications medicine · 2022Article
- Measuring close proximity interactions in summer camps during the COVID-19 pandemic.EPJ data science · 2022Article
- Reorganization of nurse scheduling reduces the risk of healthcare associated infections.Scientific reports · 2021Article
- A network analysis of patient referrals in two district health systems in Tanzania.Health policy and planning · 2021Article
- Topological dynamics of the 2015 South Korea MERS-CoV spread-on-contact networks.Scientific reports · 2020Article
- Close proximity interactions support transmission of ESBL-K. pneumoniae but not ESBL-E. coli in healthcare settings.PLoS computational biology · 2019Article
- Maximizing Patient Coverage Through Optimal Allocation of Residents and Scribes to Shifts in an Emergency Department.Journal of medical systems · 2018Article
- The Risk of Cross Infection in the Emergency Department: A Simulation Study.Infection control and hospital epidemiology · 2018Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
Emergency departments play a critical role in the public health system, particularly in times of pandemic. Infectious patients presenting to emergency departments bring a risk of cross-infection to other patients and staff through close proximity interactions or contacts. To understand factors associated with cross-infection risk, we measured close proximity interactions of emergency department staff and patients by radiofrequency identification in a working emergency department. The number of contacts (degree) is not related to patient demographic characteristics. However, the amount of time in close proximity (weighted degree) of patients with ED personnel did differ, with black patients having approximately 15 min more contact with staff than non-white patients. Patients arriving by EMS had fewer contacts with other patients than patients arriving by other means. There are differences in the number of contacts based on staff role and arrival mode. When crowding is low, providers have the most contact time with patients, while administrative staff have the least. However, when crowding is high, this differential is reversed. The effect of arrival mode is modified by the extent of crowding. When crowding is low, patients arriving by EMS had longer contact with administrative staff, compared to patients arriving by other means. However, when crowding is high, patients arriving by EMS had less contact with administrative staff compared to patients arriving by other means. Our findings should help designers of emergency care focus on higher risk situations for transmission of dangerous pathogens in an emergency department. For instance, the effects of arrival and crowding should be considered as targets for engineering or architectural interventions that could artificially increase social distances.
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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.