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Record W6907917013 · doi:10.25384/sage.c.4254181

The Utility and Efficiency of a Resident Hand Clinic for the Management of Acute Hand Trauma at the University of Alberta

2018· other· en· W6907917013 on OpenAlexaboutno aff

Bibliographic record

VenueSage Journals Data · 2018
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsReferralPatient satisfactionEmergency departmentHand injuryRetrospective cohort study

Abstract

fetched live from OpenAlex

Background:The University of Alberta established a resident-run hand clinic in 2005 to expeditiously manage the growing numbers of patients with traumatic hand injuries. The purpose of this study was to examine the clinical volume and types of cases assessed and treated in the clinic, as well as gauge patient satisfaction with care received.Methods:A retrospective chart review and patient satisfaction questionnaire were conducted for patients assessed in the hand clinic in 2015. Demographic data, referral data, and treatment required were recorded. Patients were asked to complete a survey on their experience at the end of their visit.Results:A total of 1022 charts were reviewed. The most common reason for referral was a fracture or dislocation (57%), followed by tendon injury (18%). The average wait time to be seen in clinic was 2.97 ± 2.13 days in the winter and 4.12 ± 2.14 days in the summer. Forty-seven percent of patients required splinting, 17% required a procedure, and 21% of patients were referred for surgery. Patient satisfaction on average was 9.29 ± 0.87 on a satisfaction scale of 10.Conclusion:In a 6-month period, residents attending hand clinic assessed and treated 1022 patients, providing timely management of acute injuries. A resident-run hand clinic is an effective model to decrease wait times for patients, to decrease time spent assessing nonemergent injuries in the emergency department, and to concentrate hand trauma in a setting conducive to resident training, while still maintaining high patient satisfaction.

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)0.005
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.554
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.003
Scholarly communication0.0000.000
Open science0.0030.002
Research integrity0.0000.000
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 head0.066
GPT teacher head0.335
Teacher spread0.269 · 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
GenreOther

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".

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Citations0
Published2018
Admission routes1
Has abstractyes

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Same venueSage Journals DataFrench-language works237,207