Evidence map›Paper›PMID 30943873›Full record

ArticleErgonomics2019

Role network measures to assess healthcare team adaptation to complex situations: the case of venous thromboembolism prophylaxis.

Megan E Salwei, Pascale Carayon, Ann S Hundt, Peter Hoonakker, Vaibhav Agrawal, Peter Kleinschmidt, Jason Stamm, Douglas Wiegmann, Brian W Patterson

Open access · greenAbstract read
In one paragraph

Article in Ergonomics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
2.0field-weighted citation impact, top 15% of its field
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

6 citing papers in PubMed, 23 citations in OpenAlex.

  1. Article
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  6. SEIPS 101 and seven simple SEIPS tools.BMJ quality & safety · 2021
    Review
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

9 authors at 2 institutions in 1 country.

Megan E Salweia Department of Industrial and Systems Engineering , University of Wisconsin-Madison , Madison , Wisconsin , USA.
Pascale Carayona Department of Industrial and Systems Engineering , University of Wisconsin-Madison , Madison , Wisconsin , USA.
Ann S Hundtb Center for Quality and Productivity Improvement , University of Wisconsin-Madison , Madison , Wisconsin , USA.
Peter Hoonakkerb Center for Quality and Productivity Improvement , University of Wisconsin-Madison , Madison , Wisconsin , USA.
Vaibhav Agrawalc Geisinger Health System , Danville , Virginia , USA.
Peter Kleinschmidtd School of Medicine and Public Health , University of Wisconsin-Madison , Madison , Wisconsin , USA.
Jason Stammc Geisinger Health System , Danville , Virginia , USA.
Douglas Wiegmanna Department of Industrial and Systems Engineering , University of Wisconsin-Madison , Madison , Wisconsin , USA.
Brian W Pattersonb Center for Quality and Productivity Improvement , University of Wisconsin-Madison , Madison , Wisconsin , USA.
University of Wisconsin–Madison · USGeisinger Health System · US

Funding

University of Wisconsin Institute for Clinical and Translational ResearchUL1TR002373 · NCATS · UNIVERSITY OF WISCONSIN-MADISON · PI ELIZABETH S BURNSIDE, Allan R. Brasier · 2017 to 2026
$75.9M
Institutional Clinical and Translational Science AwardUL1TR000427 · NCATS · UNIVERSITY OF WISCONSIN-MADISON · PI DREZNER, MARC KENNETH · 2012 to 2016
$32.2M
AHRQ HHS K08 HS024558AHRQ HHS R01 HS022086NCATS NIH HHS UL1 TR000427NCATS NIH HHS UL1 TR002373
6 · The paper itself

Abstract

Hospitals are complex environments that rely on clinicians working together to provide appropriate care to patients. These clinical teams adapt their interactions to meet changing situational needs. Venous thromboembolism (VTE) prophylaxis is a complex process that occurs throughout a patient's hospitalisation, presenting five stages with different levels of complexity: admission, interruption, re-initiation, initiation, and transfer. The objective of our study is to understand how the VTE prophylaxis team adapts as the complexity in the process changes; we do this by using social network analysis (SNA) measures. We interviewed 45 clinicians representing 9 different cases, creating 43 role networks. The role networks were analysed using SNA measures to understand team changes between low and high complexity stages. When comparing low and high complexity stages, we found two team adaptation mechanisms: (1) relative increase in the number of people, team activities, and interactions within the team, or (2) relative increase in discussion among the team, reflected by an increase in reciprocity.

Indexed as

Adaptation, PsychologicalGroup ProcessesInterprofessional RelationsProfessional RoleHospitalsHumansInterdisciplinary CommunicationPatient Care TeamVenous Thromboembolismcomplexitypatient safetysocial network analysisTeam adaptation

Identifiers

PMID30943873
PMCPMC7243844
OpenAlexW2934010853

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

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.