Early Palliative Care and Its Role in Oncology: A Qualitative Study
Bibliographic record
Abstract
INTRODUCTION: Early integration of palliative care alongside oncology is being increasingly recommended, although the strategies and models for integration remain poorly defined. We solicited the opinions of patients and caregivers who participated in a randomized trial of early palliative care versus standard oncology care, regarding the respective roles of their oncologist (both groups) and palliative care physician (early palliative care group). MATERIALS AND METHODS: The study was performed at a comprehensive cancer center. Forty-eight patients (26 intervention, 22 control) and 23 caregivers (14 intervention, 9 control) were recruited purposefully at trial end. One-on-one, semistructured qualitative interviews were conducted and analyzed using grounded theory. RESULTS: The themes resulting from the analysis fell into three categories: the focus of care, the model of care delivery, and the complementarity between teams. The focus of care in oncology was perceived to be disease-centered, with emphasis on controlling disease, directing cancer treatment, and increasing survival; palliative care was perceived to be more holistic and person-focused, with an emphasis on symptom management. Oncology visits were seen as following a structured, physician-led, time-constrained model in contrast to the more fluid, patient-led, flexible model experienced in the palliative care clinic. No differences were found in the descriptions of oncology between participants in the intervention and control groups. Participants in the intervention group explicitly described the roles of their oncologist and their palliative care physician as distinct and complementary. CONCLUSION: Participants perceived the respective roles of their oncologist and palliative care physician as discrete, important, and complementary for the provision of excellent cancer care. IMPLICATIONS FOR PRACTICE: Patients and their caregivers who experienced early palliative care described the roles of their oncologists and palliative care physicians as being discrete and complementary, with both specialties contributing to excellent patient care. The findings of the present research support an integrated approach to care for patients with advanced cancer, which involves early collaborative care in the ambulatory setting by experts in both oncology and palliative medicine. This can be achieved by more widespread establishment of ambulatory palliative care clinics, encouragement of timely outpatient referral to palliative care, and education of oncologists in palliative care.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".