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Record W2957225156 · doi:10.13162/hro-ors.v7i2.3821

Sustaining Rural Access to Emergency Care through Collaborative Emergency Centres in Nova Scotia

2019· article· en· W2957225156 on OpenAlexaffvenueabout
Alison Coates

Bibliographic record

VenueHealth Reform Observer - Observatoire des Réformes de Santé · 2019
Typearticle
Languageen
FieldHealth Professions
TopicNursing Roles and Practices
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsNova scotiaNova (rocket)Medical emergencyGeographyMedicineEngineeringAeronauticsArchaeology

Abstract

fetched live from OpenAlex

Collaborative Emergency Centres (CECs) were introduced in Nova Scotia in 2011 to address gaps in rural access to emergency care through enhanced primary care, urgent care, and interprofessional teams supported by remote physicians. In the wake of a historic election win by the New Democratic Party (NDP) in 2009, who promised to keep rural emergency departments open, a series of reports highlighted the troubles with small hospital emergency departments and suggested the development of CECs as a novel model of care. CECs aimed to improve access to emergency care in rural areas by matching the offered services to the needs of the community. The policy window for this reform was created through the convergence of a publicly recognized crisis in rural emergency department closures, a nationwide trend toward community-centred and interprofessional care models, and a historic NDP provincial government victory. Budgetary allocations and enabling legislation supported the development of the first set of four CECs for the province. Ministerial emergency department accountability reports and the Care Right Now report proclaimed the success of the CECs in reducing the number of hours of unplanned emergency department closures and in increasing rural communities' access to primary and emergency care. The CECs allowed Nova Scotia to provide access to around-the-clock emergency care at a greatly reduced cost, improved the work-life balance for rural physicians, and created a case for successful implementation of interprofessional teams in other environments.

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 categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.144
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.003
Science and technology studies0.0010.000
Scholarly communication0.0000.004
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.072
GPT teacher head0.455
Teacher spread0.383 · 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 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

Citations3
Published2019
Admission routes3
Has abstractyes

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