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Record W1439963073 · doi:10.12927/hcq.2013.23239

Facilitating Specialist to Primary Care Transfer with Tools for Transition: A Quality of Care Improvement Initiative for Patients with Type 2 Diabetes

2013· article· en· W1439963073 on OpenAlexaffabout
Julie Maranger, Janine Malcolm, Clare Liddy, Sheryl Izzi, Sharon Brez, Kerri LaBrecque, Monica Taljaard, Robert D. Reid, Teik Chye Ooi

Bibliographic record

VenueHealthcare Quarterly · 2013
Typearticle
Languageen
FieldMedicine
TopicChronic Disease Management Strategies
Canadian institutionsMontreal Heart InstituteÉlisabeth Bruyère HospitalOttawa Hospital
Fundersnot available
KeywordsMedicineDiabetes mellitusPrimary careType 2 diabetesQuality managementFamily medicineHealth careQuality (philosophy)NursingMedical emergencyOperations managementPolitical science

Abstract

fetched live from OpenAlex

The epidemic of diabetes has increased pressure on the whole spectrum of the healthcare system including specialist centres. The authors' own specialist centre at The Ottawa Hospital has 20,000 annual visits for diabetes, 80% of which are follow-up visits. Since it is a tertiary facility, managers, administrators and clinicians would like to increase their ability to see newly referred patients and decrease the number of follow-up visits. In order to discharge appropriate diabetes patients, the authors decided it was essential to strengthen the transition process to decrease both the pressure on the centre and the risk for discontinuity of diabetes care after discharge.

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)0.014
metaresearch head score (Gemma)0.023
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 score0.014
Threshold uncertainty score0.072

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.023
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0040.001
Scholarly communication0.0030.003
Open science0.0020.006
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0040.000

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 head0.040
GPT teacher head0.319
Teacher spread0.280 · 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

Citations1
Published2013
Admission routes2
Has abstractyes

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