A survey of radiation treatment planning peer-review activities in a provincial radiation oncology programme: current practice and future directions
Bibliographic record
Abstract
OBJECTIVES: To describe current patterns of practice of radiation oncology peer review within a provincial cancer system, identifying barriers and facilitators to its use with the ultimate aim of process improvement. DESIGN: A survey of radiation oncology programmes at provincial cancer centres. SETTING: All cancer centres within the province of Ontario, Canada (n=14). These are community-based outpatient facilities overseen by Cancer Care Ontario, the provincial cancer agency. PARTICIPANTS: A delegate from each radiation oncology programme filled out a single survey based on input from their multidisciplinary team. OUTCOME MEASURES: Rated importance of peer review; current utilisation; format of the peer-review process; organisation and timing; case attributes; outcomes of the peer-review process and perceived barriers and facilitators to expanding peer-review processes. RESULTS: 14 (100%) centres responded. All rated the importance of peer review as at least 8/10 (10=extremely important). Detection of medical error and improvement of planning processes were the highest rated perceived benefits of peer review (each median 9/10). Six centres (43%) reviewed at least 50% of curative cases; four of these centres (29%) conducted peer review in more than 80% of cases treated with curative intent. Fewer than 20% of cases treated with palliative intent were reviewed in most centres. Five centres (36%) reported usually conducting peer review prior to the initiation of treatment. Five centres (36%) recorded the outcomes of peer review on the medical record. Thirteen centres (93%) planned to expand peer-review activities; a critical mass of radiation oncologists was the most important limiting factor (median 6/10). CONCLUSIONS: Radiation oncology peer-review practices can vary even within a cancer system with provincial oversight. The application of guidelines and standards for peer-review processes, and monitoring of implementation and outcomes, will require effective knowledge translation activities.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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".