Cost Effectiveness and Impact in Quality of Care of a Pediatric Multidisciplinary Stone Clinic
Bibliographic record
Abstract
Introduction: Herein, we assess the cost-effectiveness of a multidisciplinary clinic for children with urinary stones. The clinic’s primary goals were to decrease unnecessary visits, imaging, and costs while optimizing the quality of care. Methods: Between October 2012 and January 2016, children with complex stone disease, previously treated in urology and/or nephrology clinics, were seen at a triannual pediatric combined stone clinic. We compared the number and cost of ultrasounds, emergency room (ER) visits, and stone surgeries performed before and after each patient’s initial evaluation. All patients received satisfaction surveys. Results: Among the 79 patients, 27 were seen at least twice in the combined clinic and followed multiple times in either urology or nephrology clinics. The mean number of ER visits per patient per year significantly decreased from 0.29 ± 0.36 to 0.10 ± 0.15 (P = 0.002). The mean cost of ER visits went from CAD$ 23.44 ± 28.80 to CAD$ 4.14 ± 12.18 (P = 0.002). Likewise, the mean annual number and cost of stone-related surgeries significantly decreased [(0.38 ± 0.63 versus 0.20 ± 0.32 after the MSC started (P = 0.026) and mean annual cost of surgeries went from CAD$ 182.97 ± 301.49 to CAD$ 41.59 ± 110.97 (P = 0.022)]. Among the survey responses returned, 75% of families believed the clinic was time-saving. Conclusions: Despite a small sample size, the number of ER visits and stone-related operations significantly decreased after the initial combined clinic intervention. Longer-term data will hopefully confirm if the positive findings continue.
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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 | 0.002 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".