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Record W2123619022

Adoption of open-access scheduling in an academic family practice.

2010· article· en· W2123619022 on OpenAlexaffabout
Stewart Cameron, Laura Sadler, Beverley Lawson

Bibliographic record

VenuePubMed · 2010
Typearticle
Languageen
FieldHealth Professions
TopicHealthcare Operations and Scheduling Optimization
Canadian institutionsDalhousie University
Fundersnot available
KeywordsPrimary careScheduling (production processes)General practiceMedicineComputer sciencePatient careMedical emergencyFamily medicineNursingOperations management
DOInot available

Abstract

fetched live from OpenAlex

PROBLEM ADDRESSED: Patients have to wait too long to see their family physicians. Open access, a new approach to office scheduling, has shown promise in reducing patient wait times to see primary care physicians. OBJECTIVE OF PROGRAM: To offer same-day appointments to most patients who call the office, thus reducing wait times as measured by the third available appointment. Reductions in no-show rates have also been reported by those who have adopted the open-access system. PROGRAM DESCRIPTION: Following extensive preparation, a 2-site academic practice in Halifax, NS, adopted open-access booking in October 2008. Data on third available appointment times, no-show appointments, and patient volumes were tracked before and during the yearlong implementation. CONCLUSION: The clinics recorded a substantial, sustained reduction in third available appointment time, indicating improved patient access. There was also a decline in no-show appointments. Patient volumes were unaffected.

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)0.002
metaresearch head score (Gemma)0.006
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 score0.027
Threshold uncertainty score0.053

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0070.000

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 head0.251
GPT teacher head0.527
Teacher spread0.276 · 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

Citations42
Published2010
Admission routes2
Has abstractyes

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