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Record W2407916310

Integration of nurse practitioners into a family health network.

2007· article· en· W2407916310 on OpenAlexaff
Jennie Humbert, Frances Legault, Simone Dahrouge, Brenda Halabisky, Gail Boyce, William Hogg, Stephanie Amos

Bibliographic record

VenuePubMed · 2007
Typearticle
Languageen
FieldHealth Professions
TopicNursing Roles and Practices
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsPharmacistMultidisciplinary approachMultidisciplinary teamNursingMedicineNurse practitionersHealth careFamily medicinePharmacy
DOInot available

Abstract

fetched live from OpenAlex

A randomized controlled study called Anticipatory and Preventative Team Care (APTCare) explored a new role for nurse practitioners (NPs) within a multidisciplinary team. The aim of the study was to evaluate whether integrating NPs and a pharmacist was an effective approach for the management of patients living with multiple chronic illnesses. Over an 18-month period, three part-time NPs and a pharmacist became part of a rural Family Health Network (FHN). They established relationships with study patients and collaborated to provide optimum care. Each NP had 40 patients, all of whom received care in the home. Study results showed that an initial home visit was invaluable for establishing a care plan, developing a relationship with the patient and assessing the home environment. Ongoing monitoring at home, however, was found to be an inefficient use of the NP role. By the end of the study, all clinicians agreed that the NP role had been successfully integrated into the multidisciplinary team.

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)0.007
metaresearch head score (Gemma)0.020
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.037

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.020
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.068
GPT teacher head0.426
Teacher spread0.358 · 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 designQualitative
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

Citations21
Published2007
Admission routes1
Has abstractyes

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