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Record W3026566538 · doi:10.33151/ajp.17.813

Community Paramedicine in British Columbia: A Virtual Response to Covid-19

2020· article· en· W3026566538 on OpenAlexaffabout
Michelle Brittain, Christopher Michel, Leon Baranowski, Richard Armour, Amy Poll, Jennie Helmer

Bibliographic record

VenueAustralasian Journal of Paramedicine · 2020
Typearticle
Languageen
FieldMedicine
TopicCOVID-19 and healthcare impacts
Canadian institutionsUniversity of British ColumbiaIsland Health
Fundersnot available
KeywordsTelehealthPandemicCoronavirus disease 2019 (COVID-19)Personal protective equipmentTelemedicineMedicineMedical emergencyHealth careService delivery frameworkService (business)Community engagementNursingCommunity healthBusinessPublic healthPublic relationsPolitical science

Abstract

fetched live from OpenAlex

The COVID-19 pandemic has forced innovative approaches to patient care delivery. The British Columbia Emergency Health Service has worked collaboratively with health authorities throughout the province since 2015 to improve the delivery of healthcare in rural and remote communities through the community paramedicine program. In response to the COVID-19 pandemic to minimise the risk to providers and patients, as well as conserve personal protective equipment, home visits and community engagement opportunities were suspended. However, the COVID-19 pandemic saw a large increase in the number of patients referred to the service and so alternate approaches to patient care delivery were urgently required. This commentary outlines the integration of home health monitoring technology into the community paramedicine program within British Columbia as well as the integration of virtual, telehealth consultations in response to the COVID-19 pandemic.

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)0.004
metaresearch head score (Gemma)0.024
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.290
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.024
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.003
Insufficient payload (model declined to judge)0.0010.000

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 head0.093
GPT teacher head0.400
Teacher spread0.307 · 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

Citations10
Published2020
Admission routes2
Has abstractyes

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