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Record W2765394774 · doi:10.1093/fampra/cmx095

Contextual levers for team-based primary care: lessons from reform interventions in five jurisdictions in three countries

2017· article· en· W2765394774 on OpenAlexafffund
Grant Russell, William L. Miller, Jane Gunn, Jean‐Frédéric Lévesque, Mark Harris, William Hogg, Cathie Scott, Jenny Advocat, Lisa Halma, Sabrina M. Chase, Benjamin F. Crabtree

Bibliographic record

VenueFamily Practice · 2017
Typearticle
Languageen
FieldHealth Professions
TopicInterprofessional Education and Collaboration
Canadian institutionsAlberta Health ServicesPolicyWise for Children & FamiliesBruyèreUniversity of Ottawa
FundersCanadian Institutes of Health ResearchMonash UniversityUniversity of Ottawa
KeywordsMedicineTeamworkPublic relationsAccountabilityNursingHealth care reformPsychological interventionHealth policyMedical educationPublic healthPolitical science

Abstract

fetched live from OpenAlex

Background: Most Western nations have sought primary care (PC) reform due to the rising costs of health care and the need to manage long-term health conditions. A common reform-the introduction of inter-professional teams into traditional PC settings-has been difficult to implement despite financial investment and enthusiasm. Objective: To synthesize findings across five jurisdictions in three countries to identify common contextual factors influencing the successful implementation of teamwork within PC practices. Methods: An international consortium of researchers met via teleconference and regular face-to-face meetings using a Collaborative Reflexive Deliberative Approach to re-analyse and synthesize their published and unpublished data and their own work experience. Studies were evaluated through reflection and facilitated discussion to identify factors associated with successful teamwork implementation. Matrices were used to summarize interpretations from the studies. Results: Seven common levers influence a jurisdiction's ability to implement PC teams. Team-based PC was promoted when funding extended beyond fee-for-service, where care delivery did not require direct physician involvement and where governance was inclusive of non-physician disciplines. Other external drivers included: the health professional organizations' attitude towards team-oriented PC, the degree of external accountability required of practices, and the extent of their links with the community and medical neighbourhood. Programs involving outreach facilitation, leadership training and financial support for team activities had some effect. Conclusion: The combination of physician dominance and physician aligned fee-for-service payment structures provide a profound barrier to implement team-oriented PC. Policy makers should carefully consider the influence of these and our other identified drivers when implementing team-oriented PC.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.035
metaresearch head score (Gemma)0.031
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.052
Threshold uncertainty score0.183

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0350.031
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0090.008
Scholarly communication0.0050.003
Open science0.0020.011
Research integrity0.0020.002
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 head0.102
GPT teacher head0.484
Teacher spread0.382 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations40
Published2017
Admission routes2
Has abstractyes

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