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Record W3201803161 · doi:10.31128/ajgp-09-20-5648

General practitioners’ knowledge and use of an urban Australian hospital General Practice Liaison service: A qualitative study

2021· article· en· W3201803161 on OpenAlexfundno aff
Sharon Clifford, Marina Kunin, Grant Russell

Bibliographic record

VenueAustralian Journal of General Practice · 2021
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicHealthcare Systems and Technology
Canadian institutionsnot available
FundersCanadian Institutes of Health ResearchAustralian GovernmentAustralian Primary Health Care Research Institute, Australian National UniversityPrimary Health Care Research, Evaluation and Development
KeywordsQualitative researchGeneral practiceService (business)NursingMedicineSociologyMedical educationFamily medicineBusinessSocial science

Abstract

fetched live from OpenAlex

BACKGROUND AND OBJECTIVES: Strong integration between primary and secondary healthcare is essential. Health services across Australia have developed General Practice Liaison (GPL) services to improve communication and understanding between general practitioners (GPs) and hospitals. The aim of this study was to explore GPs' experiences of and interaction with a health service's GPL service and capture perspectives concerning future service expansion. METHOD: This descriptive qualitative study used semi-structured interviews with 10 GPs in the catchment area of a large urban health service in Melbourne in 2018. Data were analysed thematically. RESULTS: While GPs accepted the value of a GPL service, few had direct experience. Acknowledging the challenge of negotiating complex healthcare systems, they saw GPL services ideally staffed by a health professional, not necessarily a GP. DISCUSSION: The results provide insight into what GPs want from a GPL service. This can inform development of the GPL role within health services.

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)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.378
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.012
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 head0.070
GPT teacher head0.385
Teacher spread0.315 · 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 designNot applicable
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

Citations8
Published2021
Admission routes1
Has abstractyes

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