Impact of a maternal sepsis training package on maternity staff compliance with Trust guidelines
Bibliographic record
Abstract
Background Maternal sepsis is the leading cause of direct maternal death in the UK. Cost-effective training for staff is essential in providing safe, high-quality maternity care. Aims This project aimed to examine the impact of a maternal sepsis training package, provided during the period 1 April – 30 September 2013 (quarters 2–3), on maternity staff's compliance with the Trust's maternal sepsis guideline, as documented in maternity notes. Methods An audit was undertaken of the staff compliance rates for the Trust's maternal sepsis guideline (on which the training package is based) recorded in maternal notes during the period 1 January – 31 December 2013 (quarters 1–4). Data were analysed to investigate significance. Findings There was no statistically significant increase in compliance with the guideline from quarter 1 through to quarter 4. Conclusions Despite its limitations, this audit suggests the training has not had a significant impact on practice. When an initiative starts to deliver results that are not providing value for money, reassessing services in the interest of quality care must be the priority.
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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 | 0.030 | 0.178 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".