Categorization of measures of quality in radiation treatment.
Bibliographic record
Abstract
187 Background: The Canadian Partnership for Quality Radiotherapy (CPQR) has revised an outdated version of quality assurance (QA) guidelines for use in Canadian radiation treatment (RT) centres. This updated document contains concise, specific quality statements against which program structure and performance can be evaluated. Our objective was to review available international guidelines for quality in RT, categorize them according to a defined taxonomy, and inform a modified Delphi process for further evaluation of the guidelines. Methods: We identified 8 relevant standards documents issued by jurisdictions internationally. Taken together, 454 statements, or groups of statements, describing measures of quality were identified. These disparate quality statements were consolidated into a limited number of manageable groups using an appropriate classification scheme. A decision tree with two major categories was developed. Category 1 was based on the classification proposed by Donabedian as to whether the statement addressed a structure, process, outcome, or other. Category 2 addressed whether the statement referred to activities directed towards the organization, patients, staff, equipment/clinical processes, or other. Five reviewers assigned each of the 454 statements independently to one of these 20 (4 x 5) category decision tree endpoints. Results: A free marginal kappa analysis of agreement between the 5 reviewers in all 20 endpoints yielded a value of 0.38 which is fair agreement. Restricting analysis to Category 1, there is better agreement with a kappa of 0.54. Alternatively, 3 or more of the 5 reviewers agreed on their assignments 93% of the time for Category 1 and 76% for Categories 1 and 2. There were 290 statements with less than 100% agreement in Category 1 extracted for a second mapping using additional descriptive qualifiers. Subsequently, the overall free-marginal kappa increased to 0.71, considered substantial agreement. Conclusions: Kappa values varied among the 8 documents reviewed, possibly indicating differences in clarity of the descriptions. The 454 standards identified have been categorized and provide a manageable input to our ongoing effort to maintain appropriate, up-to-date Canadian quality guidelines for RT.
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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 | 0.048 | 0.106 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.020 | 0.015 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.004 |
| 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".