Factors influencing prioritization for carpal tunnel syndrome consultation
Bibliographic record
Abstract
BACKGROUND: In a socialized medicine model, prioritization of referrals for specialist consultation is highly important in the distribution of heath care. For high-burden diseases, such as carpal tunnel syndrome (CTS), the factors that influence prioritization are not well understood. OBJECTIVE: To determine the factors that influence the prioritization of referrals for CTS consultation by plastic surgeons in Canada. METHODS: All members of the Canadian Society of Plastic Surgery with e-mail addresses were invited to participate in an online survey regarding the method by which they prioritize referrals for CTS. RESULTS: Forty per cent of invited members completed the survey (150 surgeons). Of these, 118 (79%) stated that they performed CTS surgery. The majority of respondents who performed CTS surgery prioritized their consultation list chronologically (77%). Factors that would alter the chronological order or prioritization included subsequent contact by the referring physician (24%); personal relationship with the patient (16%); and specific information in the referral letter (15%), which usually involved symptom severity or electromyography findings. Sixty-six per cent of plastic surgeons stated that there was no conscious decision on how they came to choose the method of prioritization they used for referrals regarding CTS. DISCUSSION: The majority of plastic surgeons in Canada prioritize referrals for consultation on CTS chronologically. A minority of respondents reported reassigning priority based on clinical severity. The rationale for the methods by which Canadian Society of Plastic Surgery members prioritize these referrals is poorly understood. Further study on developing evidence-based prioritization methods may be useful in assisting surgeons and their patients in outcome-based decisions.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".