Barriers to Hospice Care Among Older Patients Dying With Lung and Colorectal Cancer
Bibliographic record
Abstract
PURPOSE: To identify factors associated with hospice enrollment and length of stay in hospice among patients dying with lung or colorectal cancer. METHODS: We used the Linked Medicare-Tumor Registry Database to conduct a retrospective analysis of the last year of life among Medicare beneficiaries diagnosed with lung or colorectal cancer at age > or = 66 years between January 1, 1973, and December 31, 1996, in the Surveillance, Epidemiology, and End Results Program who died between January 1, 1988, and December 31, 1998. Our outcomes of interest were time from cancer diagnosis to hospice enrollment and length of stay in hospice care. We used Cox proportional hazards regression to adjust for demographic and clinical information. RESULTS: We studied elderly patients dying with lung cancer (n = 62,117) or colorectal cancer (n = 57,260). Overall, 27% of patients (n = 16,750) with lung cancer and 20% of patients (n = 11,332) with colorectal cancer received hospice care before death. Median length of stay for hospice patients with lung and colorectal cancer was 25 and 28 days, respectively. Overall, 20% of patients entered hospice within 1 week of death, whereas 6% entered more than 6 months before death. Factors associated with later hospice enrollment include being male; being of nonwhite, nonblack race; having fee-for-service insurance; and residing in a rural community. Many of these factors also were associated with shorter stays in hospice. CONCLUSION: Although use of hospice care has increased dramatically over time, specific patient groups, including men, patients residing in rural communities, and patients with fee-for-service insurance continue to experience delays in hospice enrollment.
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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 | 0.007 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".