Physician factors associated with discussions about end‐of‐life care
Bibliographic record
Abstract
BACKGROUND: Guidelines recommend advanced care planning for terminally ill patients with <1 year to live. Few data are available regarding when physicians and their terminally ill patients typically discuss end-of-life issues. METHODS: A national survey was conducted of physicians caring for cancer patients about timing of discussions regarding prognosis, do not resuscitate (DNR) status, hospice, and preferred site of death with their terminally ill patients. Logistic regression was used to identify physician and practice characteristics associated with earlier discussions. RESULTS: Among 4074 respondents, 65% would discuss prognosis "now" (defined as patient has 4 months to 6 months to live, asymptomatic). Fewer would discuss DNR status (44%), hospice (26%), or preferred site of death (21%) immediately, with most physicians waiting for patient symptoms or until there are no more treatments to offer. In multivariate analyses, younger physicians more often discussed prognosis, DNR status, hospice, and site of death "now" (all P < .05). Surgeons and oncologists were more likely than noncancer specialists to discuss prognosis "now" (P = .008), but noncancer specialists were more likely than cancer specialists to discuss DNR status, hospice, and preferred site of death "now" (all P < .001). CONCLUSIONS: Most physicians report they would not discuss end-of-life options with terminally ill patients who are feeling well, instead waiting for symptoms or until there are no more treatments to offer. More research is needed to understand physicians' reasons for timing of discussions and how their propensity to aggressively treat metastatic disease influences timing, as well as how the timing of discussions influences patient and family experiences at the end of life.
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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 | 0.001 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".