ReCAP: Improving the Quality of Radiation Treatment for Patients in Ontario: Increasing Peer Review Activities on a Jurisdictional Level Using a Change Management Approach
Bibliographic record
Abstract
QUESTION ASKED: What is the impact of the Cancer Care Ontario (CCO) strategy (designed with guidance from a change management framework) to accelerate the use of peer-review processes in radiation oncology (ie, review of a radiation oncologist’s proposed treatment plan by a second radiation oncologist with or without additional multidisciplinary input) across all of its 14 cancer treatment centers? SUMMARY ANSWER: By following a number of key change management principles for organizational transformation, the proportion of radical-intent radiation therapy courses peer reviewed province-wide increased from 43.5% (April 2013) to 68.0% (March 2015), with some centers reaching over 95%. METHODS: The initiative design was guided by the Kotter eight-step process for organizational transformation, including the creation of a multidisciplinary leadership team, site visits to individual centers, the development of education and implementation processes (done in collaboration with each center), and the creation of new performance metrics for central reporting. Monitoring of these metrics enabled the leadership team to track the percentage of radiation therapy courses peer reviewed and the timing of peer review (before 25% treatment visits complete, after 25% treatment visits complete). Performance targets for the quality measures were arrived at by consensus that included engagement of all center radiation treatment program leaders. BIAS, CONFOUNDING FACTOR(S), DRAWBACKS: Peer review has been shown to increase quality of care. However, it requires that resources be invested, including the time and effort of radiation oncologists, and the programmatic work required to organize, execute, and document peer-review activities. There is currently no way of confirming the quality of peer-review activities. REAL-LIFE IMPLICATIONS: A change management framework can be useful for planning and achieving substantial increases in peer-review activities on a jurisdictional basis. Ongoing work will capitalize on facilitators of peer review and on addressing barriers to its application that were identified as part of the initiative. Guidance for peer-review activities specific to common clinical cases is required and is under development. The principles of peer review could be extended to other oncological disciplines with the goal of improving individual patient care and overall program quality. [Figure: see text]
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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 | 0.004 | 0.002 |
| 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".