Survey on Barriers to Critical Care and Palliative Care Integration
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Purpose:It has been shown that integrating palliative care (PC) in intensive care unit (ICU) improves end-of-life care (EOLC), but very few Canadian hospitals have adopted this practice. Our study aims to evaluate the perceived quality of EOLC at participating institutions and explore barriers toward ICU-PC integration.Materials and Methods:A self-administered questionnaire was developed by a multidisciplinary team. Survey items were extracted from published quality indicators in EOLC and barriers to ICU-PC integration. The study took place at 2 academic institutions. Participants consisted of physicians and nurses, ICU administrators, and allied health workers.Results:An overall response of 45% was achieved. Of total, 85% of the respondents were ICU nurses. The following main themes were identified: (1) There is a poor presence of PC in the ICU and 78% of respondents felt that increasing ICU-PC integration will improve quality of EOLC; (2) the main barrier to integration was unrealistic patient and/or family expectations; and (3) criteria-triggered consultation to PC was the most feasible way to achieve integration.Conclusion:Our findings indicate that the majority of respondents perceive that the presence of PC in ICU will improve EOLC. Future quality improvement initiatives can focus on developing a set of criteria for triggering PC consults.
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.
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 | 0.001 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.004 |
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 it