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Record W4390941534 · doi:10.5334/ijic.icic23307

Team Primary Care: Training for Transformation in Canada

2023· article· en· W4390941534 on OpenAlexaffabout
Ivy Lynn Bourgeault, Ivy Oandasan, Dale McMurchy, Jasbir Sunnar

Bibliographic record

VenueInternational Journal of Integrated Care · 2023
Typearticle
Languageen
FieldHealth Professions
TopicPrimary Care and Health Outcomes
Canadian institutionsSuncor Energy (Canada)College of Family Physicians of CanadaLakes Environmental (Canada)University of Ottawa
Fundersnot available
KeywordsWorkforceNursingScope of practiceGovernment (linguistics)Integrated careHealth careMedicineScope (computer science)Workforce developmentIndigenousSustainabilityPrimary careMedical educationPolitical scienceFamily medicine

Abstract

fetched live from OpenAlex

To address the growing crisis in primary care access and sustainability in Canada, Team Primary Care brings together 65+ health professional organizations to enhance the capacity of interprofessional, comprehensive primary care through improved training for practitioners, supports for teams and tools for planners and employers. Team Primary Care targets the primary care workforce including family physicians, primary care nurse practitioners, family practice nurses, pharmacists, physician assistants, mental health practitioners, traditional Indigenous Healers, and others. The project focuses on those involved in the training of the primary care workforce, including funders, accreditors, learning organizations, health professional associations and government. Team Primary Care endeavours to enhance interprofessional comprehensive primary care training; improve labour market integration for Indigenous and internationally educated practitioners, maximizing their utilization; create enabling environments for diverse, healthy, and resilient team members to practice at their optimal scope and capacity; and demonstrate, spread and scale leading integrated primary care workforce planning practices, tools, and resources. To date, Team Primary Care has launched eight primary care practitioner specific curricular development projects in parallel with workplace integrated learning demonstration projects, offered team-based training for primary care teams using cross cutting tools and supports to enhance interprofessional, equitable and inclusive, culturally safe care aimed at improving access to care and provider well-being. By March 2023 we anticipate an additional 12 curricular projects and 20+ demonstration projects will be ready for implementation. Unique to this project is its integrative approach and intentional change strategy that has been embedded in its design. In addition, an extensive process, outcome, and meta evaluation will have been carried out throughout the length of the project. Between now and March 2023, the aim is for the project to enhance primary care capacity enabling more Canadians to have access to an integrated primary care workforce that is inclusive of a broader range of practitioners working in teams that embed the principles of interprofessionalism, equity, diversity, inclusion, accessibility, psychological health and safety, reconciliation, and social accountability through enhanced and aligned training. The integrative and inclusive approach taken by Team Primary Care provides a unique country-wide case study of how to rapidly use education as a vehicle to quickly catalyze practice reform in primary care. Shifting the mental model towards team-based care inclusive of a broad range of primacy care practitioners committed to the delivery of comprehensive primary care was a major focus of the communication plan used. The cross-cutting tools developed are transferable to teams included but not limited to primary care and for both the Canadian context and beyond. The development of a sustainable interprofessional primary care training table is envisioned with a repository of team training tools and resources for use by a prepared primary care workforce prepared to scale and spread team-based care across the healthcare system. This case study will offer learned lessons on how education can be a critical enabler for primary care system reform.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.480
Threshold uncertainty score0.989

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0000.001
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 head0.051
GPT teacher head0.397
Teacher spread0.346 · 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.

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

Citations2
Published2023
Admission routes2
Has abstractyes

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