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Record W1972905404 · doi:10.1177/2150131914542437

Implementing the Resource in Clinic Program in Primary Care Delivery

2014· article· en· W1972905404 on OpenAlexaffabout
Lindsay Wodinski, Kate Woodman, Margaret Wanke, Thanh Ngoc Nguyen, Philip Jacobs

Bibliographic record

VenueJournal of Primary Care & Community Health · 2014
Typearticle
Languageen
FieldHealth Professions
TopicPrimary Care and Health Outcomes
Canadian institutionsUniversity of AlbertaInstitute of Health Economics
Fundersnot available
KeywordsMedicinePrimary careFamily medicinePatient satisfactionChartResource useResource (disambiguation)Medical emergencyNursing

Abstract

fetched live from OpenAlex

Alberta's Primary Care Networks (PCNs) bring together family physicians and other health professionals to provide local, comprehensive, and readily accessible primary care services to patients. The Edmonton North PCN, one of the largest in the province, piloted the Resource in Clinic (RIC) Program with objectives to increase efficiencies in the use of physician time, increase physician workplace satisfaction, increase unattached/orphan patient access, and decrease patient wait times. An evaluation of the RIC Program employed surveys (completed by physicians with RICs, RIC staff, and patients), log chart recording, and physician billing data and cost analysis. The findings indicated high satisfaction with the model, increased physician visits, and improved access for patient with comorbidities. The study did not demonstrate increased number of patients or new patients, nor could conclusions be drawn related to patient wait times.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.110
Threshold uncertainty score0.218

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0020.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0100.001

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 head0.077
GPT teacher head0.446
Teacher spread0.368 · 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 source (direct Gemma or distilled Codex), 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

Citations4
Published2014
Admission routes2
Has abstractyes

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