Identifying Barriers and Facilitators to the use of Renal Tumor Biopsy (RTB) in the Management of Small Renal Masses (SRMs) in Ontario and Potential Implementation Strategies to Promote its Widespread Adoption
Bibliographic record
Abstract
Background: Renal tumor biopsy (RTB) has been shown to be a useful diagnostic tool, however, it remains underutilized in Canada. No previous study has explored the barriers/facilitators of RTB using interviews. Methods: Phase one comprised qualitative telephone interviews with Ontario Urologists to determine barriers/facilitators to the use of RTB in practice. Phase two entailed a modified Delphi process with a panel of experts to determine the most critical barriers/facilitators to address for ongoing work. Results: Four barriers/facilitators were determined to be the most appropriate to address for ongoing work to promote the adoption of RTB in Ontario and included: 1) need for disseminating current Canadian Urological Association guidelines; 2) need for new Canadian guidelines for RTB; 3) Radiologists’ RTB technical skill; 4) Colleagues promoting RTB. Conclusion: This study provides Ontario healthcare with a tool that identified the most appropriate barriers/facilitators, along with interventions, to promote the adoption of RTB.
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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 | 0.005 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| 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".