The impact of a well breast cancer patient transition model of care on oncologists’ practice.
Bibliographic record
Abstract
39 Background: The transitioning of well breast cancer patients, post-treatment, to family physicians is accepted as a safe and effective model of care. Numerous studies have focused on patients’ experience and health outcomes, but research has not examined the experience of oncologists who are practicing in this model of care. The purpose of this research is to explore the impact of a transition model of care on oncologists’ practice. Methods: Purposive sampling was employed to recruit and interview oncologists who have been transitioning patients to family physicians for two or more years. A total of 15 medical and radiation oncologists practicing in Ontario, Canada were interviewed. Data were analyzed using thematic analysis. Results: Most oncologists interviewed were confident that the transitioning of patients to family physicians is safe for many patients post-treatment. Despite some concerns about the feasibility of the model, namely acceptance of the model among patients and family physicians, oncologists perceived that the model enhances efficiency and sustainability of the cancer system. As the volume of patients in follow-up decreased, oncologists saw a variety of impacts including: a reduction in overbooking in their clinics; more new patients able to be seen in consultation each week; more flexibility in their schedules to accept urgent appointments; and an increased ability to spend more time with patients who are dealing with complex issues. For some oncologists, well patient appointments are a rewarding part of their work. Meanwhile, many experience challenges with increased intensity of workload. Oncologists recognize that some patients and family physicians may be reluctant but they believe that early communication with patients about eventual transition, and improved communication with family physicians can enhance the acceptability of this model of care. Conclusions: Oncologists interviewed in this study reported that the time they used to spend with well follow-up patients can now be spent on other activities that contribute to the enhancement of quality of care for cancer survivors and efficiency in the broader cancer system.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".