Evidence map›Paper›PMID 32288125›Full record

ArticleSocial networks2017

Contact networks in the emergency department: Effects of time, environment, patient characteristics, and staff role.

Vicki Stover Hertzberg, Jason Baumgardner, C Christina Mehta, Lisa K Elon, George Cotsonis, Douglas W Lowery-North

Abstract read
In one paragraph

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.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed.

  1. Article
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  7. Article
  8. The Risk of Cross Infection in the Emergency Department: A Simulation Study.Infection control and hospital epidemiology · 2018
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Vicki Stover HertzbergDepartment of Biostatistics and Bioinformatics, Emory University, Atlanta, GA, United States.
Jason BaumgardnerDepartment of Biostatistics and Bioinformatics, Emory University, Atlanta, GA, United States.
C Christina MehtaDepartment of Biostatistics and Bioinformatics, Emory University, Atlanta, GA, United States.
Lisa K ElonDepartment of Biostatistics and Bioinformatics, Emory University, Atlanta, GA, United States.
George CotsonisDepartment of Biostatistics and Bioinformatics, Emory University, Atlanta, GA, United States.
Douglas W Lowery-NorthDepartment of Emergency Medicine, Emory University, Atlanta, GA, United States.

Funding

NIAID NIH HHS HHSN266200700006C
6 · The paper itself

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.

Indexed as

ED, emergency departmentEHR, electronic health recordEmergency medicineEMS, emergency medical servicesGI, gastrointestinalInfectious diseasePP, patient with patientPS, patient with staffRFID, radiofrequency identificationRTLS, real time location sensingSARS, severe acute respiratory syndromeSocial networkSP, staff with patientSS, staff with staff

Identifiers

PMID32288125
PMCPMC7126867

What OpenQuestion holds

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Registered trials

None linked

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.