Collaborative quality improvement to promote evidence based surfactant for preterm infants: a cluster randomised trial
Bibliographic record
Abstract
OBJECTIVE: To test a multifaceted collaborative quality improvement intervention designed to promote evidence based surfactant treatment for preterm infants of 23-29 weeks' gestation. DESIGN: Cluster randomised controlled trial. SETTING AND PARTICIPANTS: 114 neonatal intensive care units (which treated 6039 infants of 23-29 weeks gestation born in 2001). MAIN OUTCOME MEASURES: Process of care measures: proportion of infants receiving first surfactant in the delivery room, proportion receiving first surfactant more than two hours after birth, and median time from birth to first dose of surfactant. Clinical outcomes: death before discharge home, and pneumothorax. INTERVENTION: Multifaceted collaborative quality improvement advice including audit and feedback, evidence reviews, an interactive training workshop, and ongoing faculty support via conference calls and email. RESULTS: Compared with those in control hospitals, infants in intervention hospitals were more likely to receive surfactant in the delivery room (adjusted odds ratio 5.38 (95% confidence interval 2.84 to 10.20)), were less likely to receive the first dose more than two hours after birth (adjusted odds ratio 0.35 (0.24 to 0.53)), and received the first dose of surfactant sooner after birth (median of 21 minutes v 78 minutes, P < 0.001). The intervention effect on timing of surfactant was larger for infants born in the participating hospitals than for infants transferred to a participating hospital after birth. There were no significant differences in mortality or pneumothorax. CONCLUSION: A multifaceted intervention including audit and feedback, evidence reviews, quality improvement training, and follow up support changed the behaviour of health professionals and promoted evidence based practice.
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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 | 0.018 | 0.035 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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".