The American College of Surgeons Children's Surgery Verification and Quality Improvement Program
Bibliographic record
Abstract
PURPOSE OF REVIEW: The Task Force for Children's Surgical Care, an ad-hoc multidisciplinary group of invited leaders in pediatric perioperative medicine, was assembled in May 2012 to consider approaches to optimize delivery of children's surgical care in today's competitive national healthcare environment. Over the subsequent 3 years, with support from the American College of Surgeons (ACS) and Children's Hospital Association (CHA), the group established principles regarding perioperative resource standards, quality improvement and safety processes, data collection, and verification that were used to develop an ACS-sponsored Children's Surgery Verification and Quality Improvement Program (ACS CSV). RECENT FINDINGS: The voluntary ACS CSV was officially launched in January 2017 and more than 125 pediatric surgical programs have expressed interest in verification. ACS CSV-verified programs have specific requirements for pediatric anesthesia leadership, resources, and the availability of pediatric anesthesiologists or anesthesiologists with pediatric expertise to care for infants and young children. SUMMARY: The present review outlines the history of the ACS CSV, key elements of the program, and the standards specific to pediatric anesthesiology. As with the pediatric trauma programs initiated more than 40 years ago, this program has the potential to significantly improve surgical care for infants and children in the United States and Canada.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| 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".