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Record W2735442467 · doi:10.1186/s12245-017-0149-4

Team communication patterns in emergency resuscitation: a mixed methods qualitative analysis

2017· article· en· W2735442467 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueInternational Journal of Emergency Medicine · 2017
Typearticle
Languageen
FieldMedicine
TopicSimulation-Based Education in Healthcare
Canadian institutionsUniversity of OttawaCarleton UniversityOttawa Hospital
Fundersnot available
KeywordsMedicineResuscitationMedical emergencyAngiologyEmergency medical servicesCardiopulmonary resuscitationQualitative analysisEmergency medicineQualitative researchInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: In order to enhance patient safety during resuscitation of critically ill patients, we need to optimize team communication and enhance team situational awareness but little is known about resuscitation team communication patterns. The objective of this study is to understand how teams communicate during resuscitation; specifically to assess for a shared mental model (organized understanding of a team's relationships) and information needs. METHODS: We triangulated 3 methods to evaluate resuscitation team communication at a tertiary care academic trauma center: (1) interviews; (2) simulated resuscitation observations; (3) live resuscitation observations. We interviewed 18 resuscitation team members about shared mental models, roles and goals of team members and procedural expectations. We observed 30 simulated resuscitation video recordings and documented the timing, source and destination of communication and the information category. We observed 12 live resuscitations in the emergency department and recorded baseline characteristics of the type of resuscitations, nature of teams present and type and content of information exchanges. The data were analyzed using a qualitative communication analysis method. RESULTS: We found that resuscitation team members described a shared mental model. Respondents understood the roles and goals of each team member in order to provide rapid, efficient and life-saving care with an overall need for situational awareness. The information flow described in the interviews was reflected during the simulated and live resuscitations with the most responsible physician and charting nurse being central to team communication. We consolidated communicated information into six categories: (1) time; (2) patient status; (3) patient history; (4) interventions; (5) assistance and consultations; 6) team members present. CONCLUSIONS: Resuscitation team members expressed a shared mental model and prioritized situational awareness. Our findings support a need for cognitive aids to enhance team communication during resuscitations.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.093
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.189
GPT teacher head0.600
Teacher spread0.411 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it