The “Acute” Stone Clinic Effect: Improving Healthcare Delivery by Reorganizing Clinical Resources
Bibliographic record
Abstract
OBJECTIVE: To determine the time to specialist urologic consultation and definitive management after establishing a subspecialist administered acute stone clinic (ASC) for adults with symptomatic upper tract stones in a publically funded universal healthcare system. MATERIALS AND METHODS: We retrospectively reviewed 337 adult referrals for stone management. Three distinct 9-week periods were assessed. Group 1 patients were seen/treated by their individual urologist before inception of a general urology emergency clinic (pre-EC). Group 2 patients were seen in a pooled EC and Group 3 patients were seen in the ASC. RESULTS: A total of 337 patients (75, pre-EC; 91, EC; 171, ASC) were reviewed. Mean time to consultation for pre-EC, EC, and ASC cohorts was 29, 7, and 7 days, respectively (p < 0.05), whereas loss to follow-up decreased from 13% to 5% (p < 0.05). On average, the number of patients seen per week increased from 9 to 20. Mean time to stone surgery from date of referral was 75 days pre-EC, 43 days EC, and 25 days ASC (p < 0.05). The percentage of patients undergoing surgery was between 59% and 63% per cohort; however, the number of patients increased from 5 to 11 per week. CONCLUSIONS: By reorganizing clinical resources, a dedicated ASC was able to increase patient capacity, reduce time to urologist consultation and reduce surgical wait times.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".