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Record W2379408854 · doi:10.18192/uojm.v6i1.1282

Physician Assistants as Chronic Care Coordinators - An Interdisciplinary Patient Centered Approach to Managing Diabetes

2016· article· fr· W2379408854 on OpenAlexaffvenueabout
Nicolas Santi

Bibliographic record

VenueUniversity of Ottawa Journal of Medicine · 2016
Typearticle
Languagefr
FieldHealth Professions
TopicPrimary Care and Health Outcomes
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsChronic diseaseMedicineBattlePrimary careHealth careGerontologyFamily medicinePolitical scienceGeography

Abstract

fetched live from OpenAlex

With an aging population and an increasing number of people living with chronic disease, Canada’s primary care system is in need of change. Healthcare must better incorporate prevention and patient education in the battle against chronic disease. This article exploresthe growing role of Physician Assistants (PAs) in enhancing access to appropriate care for the chronically ill, using an example of a PA working as part of a family physician practice in Northern Ontario to improve the care of its diabetic patients. Avec une population vieillissante et un nombre croissant de personnes vivant avec une maladie chronique, le système de soins primaires canadien est en besoin de changement. Les soins de santé doivent mieux intégrer la prévention et l’éducation des patients dans la lutte contre les maladies chroniques. Cet article explore le rôle croissant des adjoints au médecin (AM) dans l’amélioration de l’accès aux soins appropriés pour les patients vivants avec des malades chroniques. Ceci sera illustré par le biais d’un exemple d’un AM travaillant dans une pratique de médecine familiale au Nord de l’Ontario pour améliorer les soins de ses patients diabétiques.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.568
Threshold uncertainty score0.873

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.022
GPT teacher head0.332
Teacher spread0.311 · 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 designNot applicable
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

Citations1
Published2016
Admission routes3
Has abstractyes

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