Selective centralized booking as a low-cost alternative to centralized referral
Bibliographic record
Abstract
SummaryCentralized referral systems have been successfully implemented to shorten and equalize surgical wait times; however, ongoing expenses make sustaining these projects challenging. We trialed a low-cost centralized booking project for hernia surgery in a community hospital from July to November 2019. Eligible patients (i.e., those with visible or palpable inguinal or umbilical hernias who were agreeable to an open mesh repair) were booked with the first available surgeon after initial consultation. Centrally booked patients with either inguinal or umbilical hernias waited a mean of 82 (standard deviation [SD] 32) and 80 (SD 66) days, respectively, while those who did not use the centralized system waited 137 (SD 89) and 181 (SD 92) days, respectively. Centralized booking increased operating room utilization as a larger pool of patients was available to call when last-minute cancellation occurred; centralized booking also effectively equalized wait-lists among 6 surgeons. Selective centralized booking is a promising concept that led to more efficient utilization of available operating room time with a significant decrease in wait times; this system could potentially improve access for all patients awaiting general surgery without requiring additional funding.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".