The Operation of Canada’s Only Virtually Operated Radiation Oncology Service During the COVID-19 Pandemic
Bibliographic record
Abstract
PURPOSE: Our institution operates a remote radiation oncology service in Northern Ontario, Canada. Since the start of the coronavirus disease 2019 pandemic, this center has operated without radiation oncologists on site owing to safety precautions, and this study seeks to understand the effect of this shift. METHODS AND MATERIALS: Departmental level data reports were used to investigate differences in metrics between April to May of 2019 and April to May 2020. These metrics include the total number of referrals received, average wait time from referral to consult, the number of cases that underwent peer review before beginning treatment, the total number of fractions given over each period, patient-reported outcomes, and patient satisfaction. We also examined the importance of physical examinations and the use of SABR treatment. RESULTS: There was an observed decrease in the number of referrals received, total number of fractions administered, and number of patients providing patient-reported outcomes. We observed no change in patient wait times, cases undergoing peer review before commencing treatment, or overall patient satisfaction. Challenges were identified in the collection of patient- reported outcomes and the conduction of physical examinations. CONCLUSIONS: This paper provides proof of concept that a radiation clinic can function entirely virtually in the short term without sacrificing patient satisfaction, efficiency, or safety.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.003 |
| 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 | 0.000 |
| 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".