Bibliographic record
Abstract
aiting an unnecessarily long time for surgery is obviously distressing, especially when one is suffering from a serious condition such as cancer.In this issue of CUAJ, Kawakami and colleagues 1 from Queen's University report their analysis of surgical wait times since 2003 in a group urology practice.The importance of their work lies in the real-time prospective and digitized booking system that collects various categories of information, thus making the data much more accurate and reliable as compared with several other studies in this field.The authors noticed an unfortunate steady rise in wait times over the last few years in both benign and cancer surgeries, with patients waiting a median of 56 days for cancer surgery in 2007.This, despite all the attention that wait times have received in Canada and especially in Ontario over the past several years.The authors correctly point out that government financial incentives do not always result in improved performance from a wait times perspective; other measures are often required.Furthermore, this study measures only the time between the moment that the decision was made to operate and the time of surgery.We know that before the decision to operate is made there are multiple other segments of time where patients may be waiting.We look forward to future reports from this group as their system and data set matures.In December 2005, the CUA sponsored an important consensus conference on surgical wait times in urological oncology, which resulted in a set of recommended limits on wait times for specific cancers. 2Now could be an opportune time to review the experience of Canadian urologists with respect to this indicator.Finally, just about every province now has a website listing wait times for various hospitals and surgical procedures.Health care authorities and politicians have made surgical wait times a major indicator of performance and are encouraging the public to seek services where they are faster.Although it is highly desirable to significantly reduce wait times, this approach is of concern.Wait times are but one of several indicators that patients should be aware of, the most important being quality of care.Waiting less time for surgery at another institution does not mean that the quality of the surgery will be the same.We must ensure that quality of care, albeit more difficult to measure, remains paramount.R Re ef fe er re en nc ce es s
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.038 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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 source (direct Gemma or distilled Codex), 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".