Practice Patterns of Medical Oncologists: A Survey of Advance Care Planning in the Outpatient Setting
Bibliographic record
Abstract
Introduction . Advance care planning (ACP) is an important part of cancer care. We determined the ACP practice patterns of medical oncologists at our academic cancer centre in Canada. Methods . Medical oncologists were invited to participate in a questionnaire in August 2019. Questions were validated by a local survey expert. Twelve multiple‐choice questions were included. Results . Seventeen of the 23 eligible oncologists responded. 64% were male, and 76% were in practice for <16 years. Common tumour sites treated by respondents included breast (53%), lung (24%), gastrointestinal (24%), and genitourinary (24%) cancers. Oncologists responded that components of ACP included designating a substitute decision‐maker (100%), determining goals of care (100%), making decisions about cardiopulmonary resuscitation (94%), and disposition of property/finances (88%). They discuss ACP with curable vs. incurable patients 6% vs. 93% of the time. While 88% of oncologists reported it would be desirable to initiate ACP discussions in the first 3 visits, in the incurable setting, only 29% reported doing so. Patient characteristics that prompt oncologists to discuss ACP in the first 3 visits in the curative vs. incurable settings include elderly age (23% vs. 59%), poor performance status (47% vs. 88%), and short prognosis (47% vs. 88%). Oncologists thought the most appropriate time to discuss ACP in the curative setting was at the time the patient initiates it (35%), and during visits 2‐3 in the incurable setting (41%). The most common barriers to discussing ACP include insufficient time (71%) and too much information for the patient (71%). Conclusions . While medical oncologists believe that discussing ACP with cancer patients in the first few outpatient visits is important, this seldom occurs due to the presence of several barriers.
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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 | 0.002 | 0.004 |
| 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".