Predictors of Transition to Hospice Care Among Hospitalized Older Adults With a Diagnosis of Dementia in Texas: A Population-Based Study
Bibliographic record
Abstract
BACKGROUND: Decedent older adults with dementia are increasingly less likely to die in a hospital, though escalation of care to a hospital setting, often including critical care, remains common. Although hospice is increasingly reported as the site of death in these patients, the factors associated with transition to hospice care during end-of-life (EOL) hospitalizations of older adults with dementia and the extent of preceding escalation of care to an intensive care unit (ICU) setting among those discharged to hospice have not been examined. METHODS: We identified hospitalizations aged ≥ 65 years with a diagnosis of dementia in Texas between 2001 and 2010. Potential factors associated with discharge to hospice were evaluated using multivariate logistic regression modeling, and occurrence of hospice discharge preceded by ICU admission was examined. RESULTS: There were 889,008 elderly hospitalizations with a diagnosis of dementia during study period, with 40,669 (4.6%) discharged to hospice. Discharges to hospice increased from 908 (1.5%) to 7,398 (6.3%) between 2001 and 2010 and involved prior admission to ICU in 45.2% by 2010. Non-dementia comorbidities were generally associated with increased odds of hospice discharge, as were development of organ failure, the number of failing organs, or use of mechanical ventilation. However, discharge to hospice was less likely among non-white minorities (lowest among blacks: adjusted odds ratio (aOR): 0.67; 95% confidence interval (CI): 0.65 - 0.70) and those with non-commercial primary insurance or the uninsured (lowest among those with Medicaid: aOR (95% CI): 0.41 (0.37 - 0.46)). CONCLUSIONS: This study identified potentially modifiable factors associated with disparities in transition to hospice care during EOL hospitalizations of older adults with dementia, which persisted across comorbidity and severity of illness measures. The prevalent discharge to hospice involving prior critical care suggests that key discussions about goals-of-care likely took place following further escalation of care to ICU. Together these findings can inform system- and clinician-level interventions to facilitate timely and consistent use of hospice to meet patients' goals of care.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| 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 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".