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Record W2472680321

[Multimorbidity and primary care: Emergence of new forms of network organization].

2015· article· en· W2472680321 on OpenAlexaboutno aff
Lise Lamothe, Chantal Sylvain, Vanessa Sit

Bibliographic record

VenuePubMed · 2015
Typearticle
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsThematic analysisHealth professionalsPrimary carePhenomenonHealth careKnowledge managementProcess managementDiseaseQualitative researchAdaptive strategiesPsychologyChronic diseaseComplex adaptive systemOrganizational structureBusinessMedicineNursingComputer scienceSociologyFamily medicinePolitical sciencePathologyGeographyArtificial intelligence
DOInot available

Abstract

fetched live from OpenAlex

OBJECTIVE: This study was designed to analyse the adaptive strategies used by primary care professionals to provide more adapted and continuous services to patients with more than one chronic disease. METHODS: A qualitative case study was conducted in a primary care structure (GMF in Québec). Data were derived from two sources: semi-structured interviews and documents. Based on our thematic analysis of data, we illustrate the adaptive processes at play. RESULTS: Our analysis identified the challenges raised by the increased prevalence of patients with more than one chronic disease and how they influence adaptive strategic initiatives from professionals at the following levels: (1) the patients themselves, (2) the professional-patient relationship, (3) the relationships between professionals of the GMF (4) the relationships between the GMF and other healthcare organizations. The description of these phenomena illustrates the dynamic emergence ofa network form of organization. CONCLUSION: This phenomenon leads to transformation of the core of the healthcare production system. A deeper understanding of its emergence, impacts and management is necessary.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.242
Threshold uncertainty score0.482

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0030.004
Scholarly communication0.0030.002
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.047
GPT teacher head0.229
Teacher spread0.182 · 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 source (direct Gemma or distilled Codex), 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

Citations8
Published2015
Admission routes1
Has abstractyes

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