Critical care at the end of life: a population-level cohort study of cost and outcomes
Bibliographic record
Abstract
BACKGROUND: Despite the high cost associated with ICU use at the end of life, very little is known at a population level about the characteristics of users and their end of life experience. In this study, our goal was to characterize decedents who received intensive care near the end of life and examine their overall health care use prior to death. METHODS: This was a retrospective cohort study that examined all deaths in a 3-year period from April 2010 to March 2013 in Ontario, Canada. Using population-based health administrative databases, we examined healthcare use and cost in the last year of life. RESULTS: There were 264,754 individuals included in the study, of whom 18% used the ICU in the last 90 days of life; 34.5% of these ICU users were older than 80 years of age and 53.0% had more than five chronic conditions. The average cost of stay for these decedents was CA$15,511 to CA$25,526 greater than for those who were not admitted to the ICU. These individuals also died more frequently in hospital (88.7% vs 36.2%), and spent more time in acute-care settings (18.7 days vs. 10.5 days). CONCLUSIONS: We showed at a population level that a significant proportion of those with ICU use close to death are older, multi-morbid individuals who incur significantly greater costs and die largely in hospital, with higher rates of readmission, longer lengths of stay and higher rates of aggressive 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 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 | 0.000 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".