Evidence-Based Performance Measures for Reconstruction after Skin Cancer Resection: A Multidisciplinary Performance Measure Set
Bibliographic record
Abstract
BACKGROUND: The American Society of Plastic Surgeons commissioned the multidisciplinary Performance Measure Development Work Group on Reconstruction after Skin Cancer Resection to identify and draft quality measures for the care of patients undergoing skin cancer reconstruction. Included stakeholders were the American Academy of Otolaryngology-Head and Neck Surgery, the American Academy of Facial Plastic and Reconstructive Surgery, the American Academy of Dermatology, the American Society of Dermatologic Surgery, the American College of Mohs Surgery, the American Society for Mohs Surgery, and a patient representative. METHODS: Two outcome measures and five process measures were identified. The outcome measures included the following: (1) patient satisfaction with information provided by their surgeon before their facial procedure, and (2) postprocedural urgent care or emergency room use. The process measures focus on antibiotic stewardship, anticoagulation continuation and/or coordination of care, opioid avoidance, and verification of clear margins. RESULTS: All measures in this report were approved by the American Society of Plastic Surgeons Quality and Performance Measures Work Group and Executive Committee, and the stakeholder societies. CONCLUSION: The work group recommends the use of these measures for quality initiatives, Continuing Medical Education, Continuous Certification, Qualified Clinical Data Registry reporting, and national quality reporting programs.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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".