P-112 Palliative care in ICU: A collective endeavour
Bibliographic record
Abstract
Background Despite considerable collective improvement efforts and clinical initiatives to integrate palliative and end-of-life care the intensive care unit (ICU), few patients are currently receiving palliative care in this particular setting as promoted by the World health organisation (WHO). Aim Our first study showed that three conditions promote the integration of palliative care in the ICU: sharing a common vision, a concerted decision-making process and a proper environment. In light of these findings, we developed, implemented and evaluated an intervention integrating these previously identified conditions. The purpose of this communication is to present our research process and its main results. Method and discussion An action research design was chosen for this study because this method is highly collaborative, values consensual decision-making process and provides an organisational structure allowing success and sustainability. Results The first phase of this study led to the development of a two component communication intervention: an interactive educational workshop and an interdisciplinary component, making the entire team and the patient active participant in the decision making. This intervention was implemented in the ICU and evaluated with a constructivist approach through a pilot-case study which offered an operational illustration of palliative care in the ICU through an integrative model. Conclusions This study clearly demonstrates that changing the culture of the ICU is a collective endeavour that could be empowered by action research process. Early proactive interdisciplinary rounds and regular patient-family meeting, improves successful goal-directed care, quality end-of-life care and satisfaction.
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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 | 0.006 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.015 | 0.002 |
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".