Development of quality indicators for colorectal cancer surgery, using a 3-step modified Delphi approach.
Bibliographic record
Abstract
BACKGROUND: Little performance measurement has been undertaken in the area of oncology, particularly for surgery, which is a pivotal event in the continuum of cancer care. This work was conducted to develop indicators of quality for colorectal cancer surgery, using a 3-step modified Delphi approach. METHODS: A multidisciplinary panel, comprising surgical and methodological co-chairs, 9 surgeons, a medical oncologist, a radiation oncologist, a nurse and a pathologist, reviewed potential indicators extracted from the medical literature through 2 consecutive rounds of rating followed by consensus discussion. The panel then prioritized the indicators selected in the previous 2 rounds. RESULTS: Of 45 possible indicators that emerged from 30 selected articles, 15 were prioritized by the panel as benchmarks for assessing the quality of surgical care. The 15 indicators represent 3 levels of measurement (provincial/regional, hospital, individual provider) across several phases of care (diagnosis, surgery, adjuvant therapy, pathology and follow-up), as well as broad measures of access and outcome. The indicators selected by the panel were more often supported by evidence than those that were discarded. CONCLUSIONS: This project represents a unique initiative, and the results may be applicable to colorectal cancer surgery in any jurisdiction.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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".