The impact of a multi-component hospital avoidance programme in residential aged care homes: a stepped-wedge cluster randomised trial
Bibliographic record
Abstract
OBJECTIVES: To investigate if a multi-component hospital avoidance intervention would reduce hospital bed days in residential aged care (RAC) homes. DESIGN: Prospective stepped-wedge cluster randomised trial with usual care and intervention phases. SETTING: Eleven RAC homes in Queensland, Australia. PARTICIPANTS: The intervention targeted all nursing staff and personal care workers within the participating RAC homes. Outcome data were collected for all residents living in the participating RAC homes at any time throughout the trial period. INTERVENTION: The intervention comprised four core components: face-to-face training sessions with all nursing staff and personal care workers; provision of diagnostic medical equipment; decision support tools and embedded implementation facilitation and support. MAIN OUTCOME MEASURES: The primary outcome was the number of hospital bed days per 100 resident days in RAC homes. Secondary outcomes assessed emergency department (ED) transfers, subsequent admissions to hospital and hospital length of stay. RESULTS: No statistically significant intervention effects were observed across the reported outcomes. Exposure to the early detection of deterioration in elderly residents intervention was associated with a 27% relative increase in the primary outcome of hospital bed days (Estimate, 95% CI: 1.13, 0.93-1.74, P-value = 0.137). There was an 8% reduction in ED transfers (Estimate, 0.92: 0.74-1.14, P-value = 0.462) and a 10% increase in hospital admissions (Estimate, 1.10, 95% CI: 0.84-1.44, P-value = 0.486). For residents admitted to the hospital, the expected length of stay increased from 4.2 to 4.4 days (Estimate: 1.04; 95% CI: 1.00-1.07; P-value = 0.055). CONCLUSIONS: Whilst not statistically significant, findings indicate that the intervention was associated with fewer ED transfers, but increased hospital admissions and overall hospital bed days. Programme implementation was impacted by major contextual barriers, notably the COVID-19 pandemic, which contributed to pressures on staffing and workload. TRIAL REGISTRATION: Australia New Zealand Clinical Trial Registry, ACTRN12620000507987 (registered 23rd April 2020).
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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 | 0.000 | 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".