Transforming the Intensive Care Culture Using the Palliative Approach
Bibliographic record
Abstract
Introduction: Although the ultimate goal of the intensive care unit (ICU) is to save and prolong human life, the integration of palliative care approach in this fast-paced highly technologic environment is increasingly recognized as a means of restoring the global nature of care and enhances the integrity of the person. In this perspective, a recent study showed that three conditions promote the integration of palliative care in the ICU: sharing a common vision, a collaborative decision-making process and a proper environment.Objective: In light of these findings, this study proposes to develop, implement and evaluate an intervention to integrate these previously identified conditions. The purpose of this communication is to present our approach and its main results.Method: Based on the premise that research and action can coexist to improve practice, a qualitative inquiry of action research was chosen for this study. Valuing the consensual decision-making process, this research method provides an organizational structure allowing success and sustainability of this intervention.Results: The intervention aims to improve the quality of interdisciplinary communication and consisted of two main components. The first propose to enhance the skills and leadership of nurses through interactive training and the second focused on the improvement of intra and inter disciplinary intervention plan.Conclusions: The integration of the palliative care approach in the ICU is definitely an innovative strategy to transform the mission of the ICU caregivers and improve the care of the whole person.
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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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.013 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".