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Record W4409289110 · doi:10.1186/s12875-025-02808-y

Primary care physician engagement in health systems transformation

2025· article· en· W4409289110 on OpenAlexaffabout
Atharv Joshi, Judith Belle Brown, Marie Y. Savundranayagam, Shannon L. Sibbald

Bibliographic record

VenueBMC Primary Care · 2025
Typearticle
Languageen
FieldHealth Professions
TopicPrimary Care and Health Outcomes
Canadian institutionsLondon Health Sciences CentreWestern University
Fundersnot available
KeywordsPrimary carePrimary health careTransformation (genetics)Primary (astronomy)Health careNursingMedicineFamily medicinePolitical science

Abstract

fetched live from OpenAlex

Physician engagement is critical to the success of primary care transformation, yet strategies to support meaningful engagement remain understudied. Despite existing research, gaps persist in understanding how physician engagement unfolds within system-level initiatives in primary care. This paper examines physician engagement through the development of the London Middlesex Primary Care Alliance (LMPCA), a regional initiative uniting primary care providers in Southwestern Ontario to advocate for system improvements and support health system transformation, including the Middlesex-London Ontario Health Team (ML-OHT). Rather than centering solely on physician perspectives, our study explores physician engagement as part of a broader collaborative effort involving healthcare administrators and support personnel. Data were collected through interviews (n = 13; including primary care physicians, healthcare administrators, and administrative support personnel), document analysis, and an environmental scan. Findings highlight the importance of grassroots leadership, governance structures, and system-level supports in driving physician engagement. The role of a primary care transformation lead emerged as a key facilitator, while lack of compensation for system-level work remained a barrier. This study provides insights into the formation of a sustainable, self-governing primary care organization and offers considerations for scaling engagement strategies while mitigating burnout and ensuring long-term participation.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.870
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
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 head0.044
GPT teacher head0.390
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.

Study designNot applicable
Domainnot available
GenreOther

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

Citations3
Published2025
Admission routes2
Has abstractyes

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