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Record W2520140075 · doi:10.1002/hpm.2380

Perceptions of the first family physicians to adopt advanced access in the province of Quebec, Canada

2016· article· en· W2520140075 on OpenAlexaffabout
Mylaine Breton, Lara Maillet, Isabelle Paré, Sabina Abou Malham, Nassera Touati

Bibliographic record

VenueThe International Journal of Health Planning and Management · 2016
Typearticle
Languageen
FieldHealth Professions
TopicPrimary Care and Health Outcomes
Canadian institutionsÉcole Nationale d'Administration PubliqueHôpital Charles-Le MoyneUniversité de Sherbrooke
Fundersnot available
KeywordsPerceptionFamily medicineBusinessMedicinePsychology

Abstract

fetched live from OpenAlex

In Quebec, several primary care physicians have made the transition to the advanced access model to address the crisis of limited access to primary care. The objectives are to describe the implementation of the advanced access model, as perceived by the first family physicians; to analyze the factors influencing the implementation of its principles; and to document the physicians' perceptions of its effects on their practice, colleagues and patients. Qualitative methods were used to explore, through semi-structured interviews, the experiences of 21 family physicians who had made the transition to advanced access. Of the 21 physicians, 16 succeeded in adopting all five advanced access principles to varying degrees. Core implementation issues revolved around the dynamics of collaboration between physicians, nurses and other colleagues. Secretaries' functions, in particular, had to be expanded. Facilitating factors were mainly related to the physicians' leadership and the professional resources available in the organizations. Impediments related to resource availability and team functioning were also encountered. This is the first exploratory study to examine the factors influencing the adoption of the advanced access model conducted with early-adopter family physicians. The lessons drawn will inform discussions on scaling up to other settings experiencing the same problems. Copyright © 2016 John Wiley & Sons, Ltd.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.671
Threshold uncertainty score0.912

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.036
GPT teacher head0.403
Teacher spread0.367 · 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 designObservational
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

Citations32
Published2016
Admission routes2
Has abstractyes

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