Urology residents on call: Investigating the workload and relevance of calls
Bibliographic record
Abstract
INTRODUCTION: On-call medical services assumed by residents represent many hours of hard work and no studies have documented what it really entails. As part of an effort to improve our on-call system, we examined phone calls received by residents on call. Our objectives were to evaluate the characteristics of phone calls received by residents on call (who, when, why, need to go to the hospital) and to determine residents' perception of these calls. We also looked into implementing strategies to reduce unnecessary calls. METHODS: We prospectively collected information about calls using a standardized reporting form with the participation of all residents (10) from a single urology program over two periods of four weeks from November 2014 to March 2015. Residents answered pre- and post-collecting period questionnaires. RESULTS: A total of 460 calls were recorded on 97 on-call days in two on-call lists. There was a mean of 3.5 (median 3, range 0-12) calls per weeknight and 7.7 (median 6, range 0-23) calls per weekend full day. Nintey-three calls (20%) led to the need for bedside evaluation and many of these were for new consultations (49%). The majority of calls originated from the clinical in-patient ward (49%) and emergency room (29%), and nurses (66%) and doctors (23%) most commonly initiated the calls. Calls between 11:00 pm and 8:00 am represented 13% of all calls. Most of the calls (77%) were perceived as relevant or very relevant. Most residents reported at least 80% of calls. CONCLUSIONS: Although likely representing an underestimate of the reality, we provide a first effort in documenting the call burden of Canadian urology residents.
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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 | 0.001 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".