Communication Between Primary Care Physicians and Radiation Oncologists Regarding Patients With Cancer Treated With Palliative Radiotherapy
Bibliographic record
Abstract
PURPOSE: The purpose of this study was to assess the satisfaction and information needs of primary care physicians (PCPs) regarding communication with radiation oncologists (ROs), with respect to patients who receive palliative radiotherapy (RT). A selected objective was to evaluate the agreement between PCPs' expectations and the content of the RO letter sent after completion of RT. PCPs' knowledge of the role of palliative RT and their awareness of available patient support services were also determined. METHODS: The PCPs of patients discharged from the Cross Cancer Institute after receiving palliative RT were surveyed using a mail-out questionnaire. Questions regarding communication, RT knowledge, and awareness of support services were asked. The corresponding RO letter was reviewed. RESULTS: A total of 148 PCPs were identified and were mailed questionnaires, with 114 (77%) responding. Overall, 80% (87 of 109) of PCPs found the RO letter to be useful in patient management. However, there was poor (< 53%) agreement between PCPs' expectations and the actual content of the RO letter. Knowledge of the indications and effectiveness of palliative RT was limited, with PCPs obtaining a median score of 4 of a possible 8. Only 27% (31 of 114) of PCPs were aware of all five of the patient support services listed. CONCLUSION: Results show that although the majority of PCPs found the RO letter useful, they believed that the letter lacked important information while containing unnecessary details. Communication between PCPs and ROs needs improvement, especially considering that PCPs seem to have limited knowledge of palliative RT.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.032 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 source (direct Gemma or distilled Codex), 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".