P-146 Testing a 72 hr discharge nurse model at barnsley hospice
Bibliographic record
Abstract
The aim of the project was to support patients’ transition home, enabling a safe discharge and reducing readmission rates alongside reducing length of stay. The method used was a three-day pathway, where identified patients were placed on a three-day support package, where McGill QoL Expanded and IPOS scores were measured through SystmOne care plans post discharge. Nurses would follow up these patients through daily telephone calls noting/actioning any change. The results noted were that IPOS outcomes have improved for the pathway patients, in comparison to the average discharge data for non-pathway patients, reporting less severe levels of pain and reduced shortness of breath. No change has been reflected in communication, yet anxiety is less severe alongside improvement in the feeling of peacefulness. 28% of discharged patients in 2024/25 were placed on this scheme, this resulted in 41 more bed days being available to support other patients requiring specialist palliative and end of life care. We concluded that patients placed on the pathway had a very low Karnofsky score and high length of stay, as compared to patients not on the pathway, indicating that these patients were more complex. The support this pathway gave has reduced readmission rates down by 42% in 2024/25 compared to 2023/24, with readmission rates dropping to 8.7% compared to 15% in 2023/24 and patients’ Preferred Placed of Care increasing to 94% at the end of 2024/2025. Fourteen patients consented to take part in the 72-hour discharge were placed on the pathway, 13 patients were discharged after day 3 and one patient was readmitted on day 2 due to new symptoms and deterioration, requiring hospice inpatient management. This study successfully addressed the aims and prevented unnecessary hospital admissions, supported community care teams and enabled patient choice, despite complexities, through holistic management. Funded by St. James’s Place Charitable Foundation grant, managed by Hospice UK.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.040 | 0.008 |
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".