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Record W1541940008 · doi:10.22230/jripe.2014v3n3a131

Interprofessional Collaboration in Ontario’s Family Health Teams: A Review of the Literature

2014· review· en· W1541940008 on OpenAlexaffvenueabout
Sophia Gocan, Mary LaPlante, Kirsten Woodend

Bibliographic record

VenueJournal of Research in Interprofessional Practice and Education · 2014
Typereview
Languageen
FieldHealth Professions
TopicInterprofessional Education and Collaboration
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsInterprofessional educationHealth careNarrativeNursingQuality (philosophy)Qualitative researchMedicineMedical educationQuality managementPsychologyPolitical scienceOperations managementSociologyEngineering

Abstract

fetched live from OpenAlex

Background: In Ontario, 200 interprofessional Family Health Teams (FHTs) have been established since 2005 to improve primary healthcare access, patient outcomes, and costs. High levels of interprofessional collaboration are important for team success; however, effective team functioning is difficult to achieve. FHTs are in their infancy, and little is known about the determinants that have influenced the quality of team collaboration or the outcomes that FHTs have achieved. The objective of this article is to examine current knowledge regarding FHT team functioning.Methods and Findings: A search of the literature resulted in eleven articles for final analysis, which were primarily qualitative in nature. A narrative synthesis of study findings was completed. A number of common challenges to interprofessional collaboration were identified. Nevertheless, patients and providers described improved healthcare access, greater satisfaction, and enhanced quality of healthcare using a FHT approach. Collaboration was fostered by effective leadership, communication, outcome evaluation, and training for both professionals and patients alike.Conclusions: Ontario FHTs have generated improvements in healthcare access and outcomes. Collaborative team functioning, while present, has not reached its full potential. Supportive public policy, education for patients and providers, and evaluation research is needed to advance FHT functioning.

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)0.020
metaresearch head score (Gemma)0.007
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.449
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0200.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0020.003
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.010
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 head0.101
GPT teacher head0.608
Teacher spread0.507 · 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
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

Citations84
Published2014
Admission routes3
Has abstractyes

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