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Record W1893297346 · doi:10.1097/ccm.0000000000001136

Beyond the Team

2015· article· en· W1893297346 on OpenAlexaffabout
Janet Alexanian, Simon Kitto, Kim J. Rak, Scott Reeves

Bibliographic record

VenueCritical Care Medicine · 2015
Typearticle
Languageen
FieldHealth Professions
TopicInterprofessional Education and Collaboration
Canadian institutionsUniversity of OttawaCARE CanadaUniversity of Toronto
Fundersnot available
KeywordsTeamworkContext (archaeology)Psychological interventionMedicineNursingHealth careIntensive careWork (physics)Patient safetyQuality managementIntensive care medicine

Abstract

fetched live from OpenAlex

OBJECTIVE: To examine the ways in which healthcare professionals work together in the ICU setting, through a consideration of the contextual, organizational, processual, and relational factors that impact their interprofessional collaboration. DESIGN: Data from over 350 hours of ethnographic observation and 35 semistructured interviews with clinicians in two ICUs were collected by two medical anthropologists over a period of 6 months. SETTING: Medical surgical ICUs in two urban research hospitals in Canada and the United States. MAIN RESULTS: Although the concept of teamwork is often central to interventions to improve patient safety in the ICU, our observations suggest that this concept does not fully describe how interprofessional work actually occurs in this setting. With the exception of crisis situations, most interprofessional interactions in the two ICUs we studied could be better described as forms of interprofessional work other than teamwork, which include collaboration, coordination, and networking. CONCLUSIONS: A singular notion of team is too reductive to account for the ways in which work happens in the ICU and therefore cannot be taken for granted in quality improvement initiatives or among healthcare professionals in this setting. Adapting interventions to the complex nature of interprofessional work and each ICUs unique local context is an important and necessary step to ensure the delivery of safe and effective patient care.

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)0.001
metaresearch head score (Gemma)0.004
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.930
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.070
GPT teacher head0.516
Teacher spread0.445 · 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 designNot applicable
Domainnot available
GenreEmpirical

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

Citations94
Published2015
Admission routes2
Has abstractyes

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