The Clinical Specialist Radiation Therapist (CSRT): A case study exploring the effectiveness of a new advanced practice role in Canada
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
INTRODUCTION: The Clinical Specialist Radiation Therapist (CSRT), is a new advanced practice (AP) role for radiation therapists (RTTs). Following training, education and evaluation, the CSRT performs specific duties in autonomous ways, making advanced clinical decisions in their area of specialization. This case study examines the CSRT's impact on quantity (i.e., increasing capacity), improving quality and stimulating research and innovation. METHODS: Between 2007 and 2016, 23 CSRTs worked in 10 cancer centres in various AP position. A standardised metrics package, focusing on wait-times, patient volumes, patient throughput, time-savings, quality initiatives, satisfaction, research and innovation was developed and used to collect qualitative and quantitative data. Data were self-reported by the CSRTs but electronic databases, pre/post-studies, surveys and interviews were also used. RESULTS: Quantity projects (n = 76) related to patient volumes, wait-times, patient throughput and time-savings increased capacity and allowed more patients to enter the system. The presence of a CSRT allowed, on average, 13 additional patients (either new or re-treated) to be seen, at their respective cancer centre, per month. An average of 1.4 yearly quality improvement initiatives were led by each CSRT, which contributed to improvements in quality of care and satisfaction. CSRTs demonstrated a high level of involvement in research, innovation and knowledge translation activities, either as leaders or part of interprofessional teams. CONCLUSION: CSRTs positively impact quantity (capacity of the system), quality, research and innovation. Future efforts include permanent and sustainable team integration, practice standards, formal and comprehensive educational preparation, and approaches to consistent, valid assessment of AP in radiation therapy.
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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 | 0.022 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| 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 it