Triage for palliative radiotherapy by clinical specialist radiation therapists: A scoping review
Bibliographic record
Abstract
Patients who could benefit from palliative radiotherapy (PRT) may be in different phases of the cancer journey: they may have minimal symptoms and preserved functional status, or could be near end of life, with multiple complex care needs. Efficient triage at PRT referral is crucial to match patients with an appropriate provider and care setting as quickly as possible. Many centres have a dedicated PRT clinic, for which triage occurs by a Palliative Clinical Specialist Radiation Therapist (PCSRT). We performed an English-language literature search of 15 databases, without date limits, based on the PICO framework. After independent screening of titles and abstracts by two authors, relevant full text papers were reviewed. Twenty studies (15 publications and five abstracts) and one government report met inclusion criteria. Studies were published over a 21-year period by investigators from four countries. By identifying bottlenecks, screening out inappropriate referrals, and assessing patients in advance of consult, PSCRT triage decreased wait times by approximately 50%, on average, compared to standard pathways (range 30-82%). Increasing efficiency by pre-booking and coordinating appointments increases patient volumes and optimizes use of resources. A triage PCSRT serving a navigator role improves continuity of care, and in decreasing the number of handoffs, safety as well. Shifting triage to a PCSRT allows multidisciplinary team members to work to their maximum scope. In one clinic, after incorporation of PCSRT triage, use of on-call services decreased, as more patients were seen during daytime appointments, contributing to cost-savings.
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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".