Anatomy of the Pain Centre waiting list at the Centre hospitalier de l'Université de Montréal (CHUM)
Bibliographic record
Abstract
BACKGROUND: Waiting list management at chronic pain clinics has become a serious problem throughout Canada. We analyzed the waiting list at the Centre hospitalier de l'Université de Montréal (CHUM) Pain Centre. METHODS: The present study is an observational, prospective study. We used a specifically designed survey questionnaire. Survey findings were analyzed with descriptive statistical methods. RESULTS: A total of 270 patients were contacted; only 146 were included. Of these, 93 were women and 53 men. The average age was 55.9 years. Fifty-two percent of the patients were referred by a medical specialist; 34% by family physicians; 3% for emergency; and 11% unknown. The mean for pain score was 6.7/10. Seventy-three percent were taking pain killers with an average improvement on their pain score of 52%. Ten percent of respondents were not taking any type of analgesic medication, while 17% were taking over-the-counter drugs. Fifty-three percent of the patients had been suffering from chronic pain for 5 years or less, while 10% had been suffering and awaiting specialized pain treatment for more than 20 years. CONCLUSION: Our data suggests that accessibility to specialized health care is not the sole obstacle to the timely and effective management of chronic pain. Seventy-three percent of the patients were taking some form of pharmaceutical treatment for pain and reported an average improvement rate of 52% on their pain score under medication. Such inconsistency may be attributable to patients' lack of compliance with their treatment. The World Health Organization Working Group recommended in chronic patients a novel approach to health care, based on patient therapeutic education. Our results show that patients need to acquire self-management skills regarding their chronic conditions.
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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 | 0.017 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".