Using Breakthrough Series Collaborative Methodology to Improve Safe Delivery of Chemotherapy in Ontario
Bibliographic record
Abstract
PURPOSE: Chemotherapy delivery is complex, involving multiple providers across settings to deliver safe, effective care. Cancer Care Ontario initiated a provincial breakthrough series collaborative, based on methodology from the Institute for Healthcare Improvement (IHI), to improve the safe delivery of chemotherapy, from ordering through preparation and administration. METHODS: Over the 1-year period of the collaborative, three in-person sessions educated participants on improvement methodology. Twenty teams tested and implemented elements of a predefined change package in their local systems. Monthly teleconferences supplemented the education while encouraging a culture of knowledge sharing. Teams completed monthly self-assessment surveys that evaluated their progress using a 6-point scale, where 1 indicated no evidence of improvement and 5 indicated achievement of all goals and improvement objectives. RESULTS: Monthly self-assessment surveys revealed that over time, scores improved from 1 to 4, indicating significant progress. Moreover, 100% of participants reported in an exit survey that the collaborative had improved the culture of safety in their organizations. The gains of the collaborative have been sustained through development of a practice community and provision of ongoing coaching through the IHI Open School. CONCLUSION: Participation in the collaborative enabled local interdisciplinary teams to develop processes and structures to support ongoing quality improvement, including formation of a sustainable structure for knowledge translation and exchange. However, lack of a shared provincial target limited overall evaluation. Other lessons learned included providing adequate time for planning and clearly defining roles and responsibilities of involved teams and project sponsors.
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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 | 0.017 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| 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".