A review of bed utilisation in the West of Ireland
Bibliographic record
Abstract
To ensure efficient use of Irish acute hospitals, the study aimed to assess the appropriateness of admission and days of care. The Appropriateness Evaluation Protocol (AEP) was applied to a stratified random sample of 286 medical and surgical, elective and non-elective patients from four acute hospitals in the west of Ireland. A total of 23 patients (8%) were inappropriately admitted. Of these, 15 (65%) could have been avoided. Of the 34 elective/booked admissions, seven (21%) were inappropriate in terms of location of surgery criteria. Over three quarters of elective patients (77%) were admitted one or more days prior to surgery which was not justified for 13 (57%) of these patients. Over a quarter of days of care (n = 73, 26%) were inappropriate. Evidence of discharge planning was found for 48% of patients. The study provides a benchmark to monitor progress. Existing policies and programmes should be implemented and monitored.
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How this classification was reachedexpand
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 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".