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Optimiser l’adhésion médicamenteuse en ambulatoire. Interconnexion entre patients, infirmiers à domicile, pharmaciens et médecins

2022· article· fr· W4308683770 on OpenAlexaff
Aurélie Bongard, Blandine Strub, Jérôme Berger, Alexandre Gouveia

Bibliographic record

VenueRevue Médicale Suisse · 2022
Typearticle
Languagefr
FieldMedicine
TopicPharmaceutical Practices and Patient Outcomes
Canadian institutionsCégep de Chicoutimi
Fundersnot available
KeywordsHumanitiesMedicinePatient EmpowermentNursingHealth carePolitical sciencePhilosophy

Abstract

fetched live from OpenAlex

The World Health Organization (WHO) considers medication safety as one of the main areas for improvement in patient safety. Treatment adherence, as a dynamic process that evolves through time or life circumstances, is of paramount importance, since it depends on a number of factors that health care professionals need to approach comprehensively during patient follow-up. In this article, we describe the tools available to general practitioners or specialist physicians, in collaboration with pharmacists and home care nurses, to optimize medication adherence in an ambulatory setting. An interprofessional approach between providers allows adequate support to patients by empowerment, treatment adjustments and optimization, based on shared common goals.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.809
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.003
Insufficient payload (model declined to judge)0.0280.001

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 head0.054
GPT teacher head0.363
Teacher spread0.309 · 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; both teacher heads agree on what is shown here.

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
Published2022
Admission routes1
Has abstractyes

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