P-108 Evidencing care of the dying adult in a district general hospital
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
<h3>Background</h3> Recent national documents, such as One Chance to Get it Right and Ambitions for Palliative and End of Life Care, have highlighted the importance of high quality end of life care. In particular they have promoted the use of individualised care planning for the dying adult. Ashford and St Peters NHS Trust is a busy district general hospital in Surrey and has over 1000 deaths per year. To ensure that high quality care was delivered to all by all healthcare professionals an individualised care plan was devised. A baseline audit was undertaken before this was rolled out across the trust. <h3>Methods</h3> An audit tool was created based on the 5 priorities of care and NICE guidance for care of the dying adult. This was to assess the documentation of care given to the dying adult and their family. A retrospective notes review of the first 100 deaths in quarter 1 was undertaken. <h3>Results</h3> Recognition of dying on the wards ranged from 50%–100% and was initially documented by the medical team in 60%. Most patients were recognised as dying in the last 48 hours. Almost 80% of patients were unable to participate in decision making about their care, although family was involved in over 95%. Over 55% were prescribed anticipatory medication and over 20% had evidence of a holistic assessment. Less than 5% of notes reviewed showed evidence of adequate individualised care planning in the last days of life. <h3>Conclusion</h3> This audit has highlighted that health professionals were recognising dying. Late recognition leads to patients not being involved in their care planning and achieving their ?priorities of care. Documentation and care is reliant on individual health care professionals approach rather than an informed, standardised practice. Individualised care planning can support healthcare professionals in delivering and evidencing this care.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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 it