End-of-Life Care for Older Patients With Ovarian Cancer Is Intensive Despite High Rates of Hospice Use
Bibliographic record
Abstract
PURPOSE: To date, few studies have examined end-of-life care for patients with ovarian cancer. One study documented increased hospice use among older patients with ovarian cancer from 2000 to 2005. We sought to determine whether increased hospice use was associated with less-intensive end-of-life medical care. PATIENTS AND METHODS: We identified 6,956 individuals age ≥ 66 years living in SEER areas who were enrolled in fee-for-service Medicare, diagnosed with epithelial ovarian cancer between 1997 and 2007, and died as a result of ovarian cancer by December 2007. We examined changes in medical care during patients' last month of life over time. RESULTS: Between 1997 and 2007, hospice use increased significantly, and terminal hospitalizations decreased (both P < .001). However, during this time, we also observed statistically significant increases in intensive care unit admissions, hospitalizations, repeated emergency department visits, and health care transitions (all P ≤ .01). In addition, the proportion of patients referred to hospice from inpatient settings rose over time (P = .001). Inpatients referred to hospice were more likely to enroll in hospice within 3 days of death than outpatients (adjusted odds ratio, 1.36; 95% CI, 1.12 to 1.66). CONCLUSION: Older women with ovarian cancer were more likely to receive hospice services near death and less likely to die in a hospital in 2007 compared with earlier years. Despite this, use of hospital-based services increased over time, and patients underwent more transitions among health care settings near death, suggesting that the increasing use of hospice did not offset intensive end-of-life care.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".