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Record W2767303138 · doi:10.1111/ajr.12385

The challenge of generalist care in remote Australia: Beyond aeromedical retrieval

2017· article· en· W2767303138 on OpenAlexaff
Zachary Pancer, Malcolm A Moore, John Wenham, Maelynn Burridge

Bibliographic record

VenueAustralian Journal of Rural Health · 2017
Typearticle
Languageen
FieldMedicine
TopicTelemedicine and Telehealth Implementation
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMedicineAuditService (business)Chronic diseasePrimary careMedical emergencyFamily medicineDisease

Abstract

fetched live from OpenAlex

OBJECTIVE: To examine clinical service activity amongst patients of the Royal Flying Doctor Service South Eastern Section in Far West New South Wales and to evaluate the management of chronic disease among frequent users of evacuation services. DESIGN: A retrospective audit of the Royal Flying Doctor Service South Eastern Section patient database inclusive of patients within the geographical study area who accessed a clinical or remote consultation, or evacuation service at least once between 1 July 2008 and 30 June 2013. Frequent users of evacuation services (≥3 evacuations per year) were investigated through RFDS patient files for determinants of chronic disease management. MAIN OUTCOME MEASURES: Category of service accessed, clinical consultation amongst frequent evacuees, determinants of chronic disease management. RESULTS: Total number of evacuees increased by 5.4%; number of remote and clinical consultation patients increased by 5.4%. Of the 47 frequent users of evacuation services, 19 (40%) were infrequent or non-users of clinics (≤3 attendances per year) and 32 (70%) did not have a general practice management plan. Frequent evacuees averaged 2.7 chronic conditions per patient and had seen an average of 16.8 primary care physicians over the 5-year evaluation. CONCLUSION: Most frequent evacuees had several chronic conditions, multiple primary care providers, did not have a general practice management plan and had infrequent clinic reviews. This evidence highlights the challenge of remote primary care and the need to improve systems of chronic disease management. It underlines the importance of current local efforts to improve electronic records, follow-up and team care and to explore further telehealth implementation.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.745
Threshold uncertainty score0.442

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.076
GPT teacher head0.425
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.

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

Citations5
Published2017
Admission routes1
Has abstractyes

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