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Record W4206614920 · doi:10.1177/08404704211063584

A framework for interprofessional team collaboration in a hospital setting: Advancing team competencies and behaviours

2022· article· en· W4206614920 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

VenueHealthcare Management Forum · 2022
Typearticle
Languageen
FieldHealth Professions
TopicInterprofessional Education and Collaboration
Canadian institutionsQueen's UniversityHealth Sciences CentreUniversity of TorontoSunnybrook Health Science Centre
Fundersnot available
KeywordsHealth careCore competencyKnowledge managementStakeholderTeam effectivenessProcess (computing)Set (abstract data type)PsychologyNursingMedical educationMedicineBusinessComputer sciencePublic relationsPolitical science

Abstract

fetched live from OpenAlex

Healthcare teams that practice collaboratively enhance the delivery of person-centred care and improve patient and systems outcomes. Many organizations have adopted existing interprofessional frameworks that define the competencies of individual health professionals that are required to meet practice standards and advance interprofessional goals. However, to support the collective efforts of team members to deliver optimal care within complex hospital settings, healthcare organizations may benefit from adopting team-based competencies for interprofessional collaboration. The Sunnybrook framework for interprofessional team collaboration was intentionally created as a set of collective team competencies. The framework was developed using a comprehensive literature search and consensus building by a multi-stakeholder working group and supported by a broad consultation process that included patient representation, organizational development and leadership, and human resources. The six core competencies are actionable and include associated team behaviours that can be easily referenced by teams and widely implemented across the hospital.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.710
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.015
GPT teacher head0.408
Teacher spread0.393 · 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