Impact of in situ simulation training on quality of postnatal stabilization and resuscitation—a before-and-after, non-controlled quality improvement study
Bibliographic record
Abstract
This study aimed to evaluate the impact of in situ simulation-based training on quality indicators of patient care at a level IV neonatal intensive care unit. A before-and-after, non-controlled quality improvement study was performed at the Division of Neonatology, Medical University of Graz. The educational intervention comprised a period of 4 months, with structured in situ simulation training delivered regularly for neonatal providers and nurses in interprofessional teams. The primary study outcome was the quality of non-technical skills and team interaction during actual postnatal stabilization and resuscitation. This was assessed using video recording during two 2-month observational phases before (pre-training) and after the educational intervention (post-training). Delivery room video recordings were assessed by two external, blinded neonatologists using the Anaesthetists' Non-Technical Skills (ANTS) score. Furthermore, we collected clinical patient data from video-recorded neonates during the pre- and post-training periods, and training participants' individual knowledge of neonatal resuscitation guidelines was assessed using a before- and after-questionnaire. A total of 48 healthcare professionals participated in 41 in situ simulation trainings. The level of non-technical skills and team interaction was already high in the pre-training period, and it did not further improve afterwards. Nonetheless, we observed a significant increase in the teamwork event "evaluation of plans" (0.5 [IQR 0.0-1.0] versus 1.0 [1.0-2.0], p = 0.049). Following the educational intervention, training participants' knowledge of neonatal resuscitation guidelines significantly improved, although there were no differences in secondary clinical outcome parameters. CONCLUSION: We have successfully implemented a neonatal in situ simulation training programme. The observed improvement in one teamwork event category in the post-training period demonstrates the effectiveness of the training curriculum, while also showing the potential of in situ simulation training for improving postnatal care and, ultimately, patient outcome. WHAT IS KNOWN: • In situ simulation-based training is conducted in the real healthcare environment, thus promoting experiential learning which is closely aligned with providers' actual work. • In situ simulation-based training may offer an additional benefit for patient outcomes in comparison to other instructional methodologies. WHAT IS NEW: • This observational study investigated translational patient outcomes in preterm neonates before and after delivery of high-frequency in situ simulation-based training at a level IV neonatal intensive care unit. • There was a significant increase in the frequency of one major teamwork event following the delivery of in situ simulation-based training, indicating a notable improvement in the non-technical skills domain, which is closely linked to actual team performance.
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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 | 0.005 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".