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Record W4310701478 · doi:10.1177/17504589221137978

Interventions to facilitate interprofessional collaboration in the operating theatre: A scoping review

2022· review· en· W4310701478 on OpenAlexafffund
Marie‐Julie Levesque, Cole Etherington, Michelle Lalonde, Narges Moradi, Lindsey Sikora, Dawn Stacey

Bibliographic record

VenueJournal of Perioperative Practice · 2022
Typereview
Languageen
FieldHealth Professions
TopicPatient Safety and Medication Errors
Canadian institutionsOttawa HospitalUniversity of Ottawa
FundersUniversity of Ottawa
KeywordsDebriefingPsychological interventionTeamworkPatient safetyQuality managementMedical educationNursingMedicineQuality (philosophy)Knowledge managementProcess managementPsychologyHealth careOperations managementComputer scienceEngineeringManagement system

Abstract

fetched live from OpenAlex

BACKGROUND: Ineffective collaboration can increase adverse events in the operating theatre. When professionals work collaboratively, they are more likely to improve patient safety and outcomes. AIM: To identify interprofessional collaboration interventions involving operating theatre teams and describe their effect on facilitating communication, teamwork, and safety. METHODS: A scoping review of four databases. Results were analysed by identifying interventions and mapping their related outcomes. RESULTS: Twenty studies evaluated single or multi-faceted interventions. Despite low-quality study designs (no randomised controlled trials), four interventions (eg: briefings, checklists, team training, debriefing) improved communication and teamwork, and enhanced safety outcomes. Only one study, using team training, reported that organisational level interventions (eg: Standard Operating Procedures, Lean quality improvement management system) improved teamwork and safety outcomes. CONCLUSION: Several studies reported interventions enhanced interprofessional collaboration within operating theatre teams. Although findings were in favour of improved communication and teamwork, more rigorous research is required.

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.

How this classification was reachedexpand

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)0.012
metaresearch head score (Gemma)0.017
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.578
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0120.017
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.004
Insufficient payload (model declined to judge)0.0020.000

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 head0.387
GPT teacher head0.610
Teacher spread0.223 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designSystematic review
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations6
Published2022
Admission routes2
Has abstractyes

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