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Record W2982463728 · doi:10.22605/rrh4066

Community health nurses: the mainstay of remote primary care in the Canadian North

2016· article· en· W2982463728 on OpenAlexaboutno aff
W A Macdonald

Bibliographic record

VenueRural and Remote Health · 2016
Typearticle
Languageen
FieldHealth Professions
TopicGlobal Health Workforce Issues
Canadian institutionsnot available
Fundersnot available
KeywordsStaffingNursingHealth careCommunity healthMedicineWorkforceWork (physics)Family medicinePublic healthPolitical science

Abstract

fetched live from OpenAlex

Since the 1950s when aboriginal people in the Canadian North began to be settled in communities health care has been provided by a variety of agents including missionaries, RCMP, trading post staff among others. This evolved finally into a system of 'Nursing Stations' staffed by 'Community Health Nurses' in small, remote communities across the Canadian Arctic and sub-Arctic. These nurses worked independently as advanced practice nurses with varying degrees of support from general practitioner/family physicians. They are often the only care provider in the community, and over a thousand kilometers away from a tertiary centre, they are obliged to deal with whatever medical problems present to them. Community Health Nurses work in large numbers in Nunavut and the other Northern Regions of Canada. These nurses work with family practitioners in a more collaborative relationship as opposed to the more traditional consultative physician - nurse model that is seen in other health care settings. This presentation will review the close working relationship between Community Health Nurses and family physicians in the Canadian North; will reference the potential for new classes of providers including Nurse Practitioners and Physician Assistants; and will identify some organizational and technological innovations that may enhance the working relationship between the advanced practice nurses and family physicians; and identify some challenges facing this critical group of health care providers: lack of appropriate training, outdated staffing models, high rates of staff turnover.This abstract was presented at the Innovative Solutions in Remote Healthcare - 'Rethinking Remote' conference, 23-24 May 2016, Inverness, Scotland.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.870
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0040.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.034
GPT teacher head0.382
Teacher spread0.349 · 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.

Study designOther design
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

Citations0
Published2016
Admission routes1
Has abstractyes

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