Multicentre evaluation of the impact of the introduction of outreach services in the United Kingdom
Bibliographic record
Abstract
Critical care outreach services (CCOS) have been introduced in the United Kingdom with aims to: avert or ensure timely admission to critical care; enable discharge from critical care; and share skills with ward staff. We aimed to assess the impact of the introduction of CCOS at the critical care unit level, as characterised by the case mix, outcome and activity of critical care unit admissions. An interrupted time-series analysis was carried out using data from 108 units participating in the Case Mix Programme that had completed a survey on CCOS provision. Individual patient-level data were collapsed into monthly time series for each unit (panel data). Population-averaged panel-data models were fitted using a generalised estimating equation approach. Various outcomes reflecting the stated aims of CCOS were considered for three groups of admissions: all admissions to the unit; admissions from the ward; and unit survivors discharged to the ward. The primary exposure variable was the presence of a formal CCOS with secondary exposures of CCOS activities, coverage and staffing, identified from the survey data. Of 108 units in the analysis, 79 (73%) had a formal CCOS introduced between 1996 and 2004. For admissions from the ward, the presence of a CCOS was associated with significant reductions in: the proportion of admissions receiving cardiopulmonary resuscitation during the 24 hours prior to admission (odds ratio 0.84, 95% confidence interval 0.73–0.96); the proportion of admissions between 22:00 and 06:59 (0.91, 0.84–0.97); and the mean ICNARC physiology score (absolute reduction 1.2, 0.3–2.1). No significant effects of CCOS on outcomes including hospital mortality and readmission to critical care were identified for patients discharged to the ward.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".