Newborn resuscitation simulation training and changes in clinical performance and perinatal outcomes: a clinical observational study of 10,481 births

Increase in Newborns Ventilated Within the First Minute of Life and Reduced Mortality After Clinical Data-Guided Simulation Training

INTRODUCTION

Birth asphyxia-related deaths is a major global concern. Rapid initiation of ventilation within the "Golden Minute" is important for intact survival but reported to be challenging, especially in low-/middle-income countries. Helping Babies Breathe (HBB) is a simulation-based training program for newborn resuscitation. The aim of this HBB quality improvement (QI) intervention was to decrease time from birth to ventilation and document potential changes in perinatal outcomes.

METHOD

Prospective observational QI study in a rural Tanzanian hospital, October 1, 2017, to August 31, 2021, first-year baseline, second-year QI/simulation intervention, and 2-year postintervention. Trained research assistants observed wide-ranging information from all births (N = 12,938). The intervention included monthly targeted HBB simulation training addressing documented gaps in clinical care, clinical debriefings, and feedback meetings.

RESULTS

During the QI/simulation intervention, 68.5% nonbreathing newborns were ventilated within 60 seconds after birth compared with 15.8% during baseline and 42.2% and 28.9% during the 2 postintervention years ( P < 0.001). Time to first ventilation decreased from median 101 (quartiles 72-150) to 55 (45-67) seconds ( P < 0.001), before increasing to 67 (49-97) and 85 (57-133) seconds after intervention. More nonbreathing newborns were ventilated in the intervention period (12.9%) compared with baseline (8.5%) and the postintervention years (10.6% and 9.4%) ( P < 0.001). Assumed fresh stillborns decreased significantly from baseline to intervention (3.2%-0.7%) ( P = 0.013).

CONCLUSIONS

This QI study demonstrates an increase in nonbreathing newborns being ventilated within the Golden Minute and a significant reduction in fresh stillborns after introduction of an HBB QI/simulation intervention. Improvements are partially reversed after intervention, highlighting the need for continuous simulation-based training and research into QI efforts essential for sustainable changes.

Few-Shot Conditional Learning: Automatic and Reliable Device Classification for Medical Test Equipment

The limited availability of specialized image databases (particularly in hospitals, where tools vary between providers) makes it difficult to train deep learning models. This paper presents a few-shot learning methodology that uses a pre-trained ResNet integrated with an encoder as a backbone to encode conditional shape information for the classification of neonatal resuscitation equipment from less than 100 natural images. The model is also strengthened by incorporating a reliability score, which enriches the prediction with an estimation of classification reliability. The model, whose performance is cross-validated, reached a median accuracy performance of over 99% (and a lower limit of 73.4% for the least accurate model/fold) using only 87 meta-training images. During the test phase on complex natural images, performance was slightly degraded due to a sub-optimal segmentation strategy (FastSAM) required to maintain the real-time inference phase (median accuracy 87.25%). This methodology proves to be excellent for applying complex classification models to contexts (such as neonatal resuscitation) that are not available in public databases. Improvements to the automatic segmentation strategy prior to the extraction of conditional information will allow a natural application in simulation and hospital settings.

Use of digital technologies for staff education and training programmes on newborn resuscitation and complication management: a scoping review

BACKGROUND

Poor-quality care is linked to higher rates of neonatal mortality in low-income and middle-income countries (LMICs). Limited educational and upskilling opportunities for healthcare professionals, particularly those who work in remote areas, are key barriers to providing quality neonatal care. Novel digital technologies, including mobile applications and virtual reality, can help bridge this gap. This scoping review aims to identify, analyse and compare available digital technologies for staff education and training to improve newborn care.

METHODS

We conducted a structured search of seven databases (MEDLINE (Ovid), EMBASE (Ovid), EMCARE (Ovid), Global Health (CABI), CINAHL (EBSCO), Global Index Medicus (WHO) and Cochrane Central Register of Controlled Trials on 1 June 2023. Eligible studies were those that aimed to improve healthcare providers' competency in newborn resuscitation and management of sepsis or respiratory distress during the early postnatal period. Studies published in English from 1 January 2000 onwards were included. Data were extracted using a predefined data extraction format.

RESULTS

The review identified 93 eligible studies, of which 35 were conducted in LMICs. E-learning platforms and mobile applications were common technologies used in LMICs for neonatal resuscitation training. Digital technologies were generally well accepted by trainees. Few studies reported on the long-term effects of these tools on healthcare providers' education or on neonatal health outcomes. Limited studies reported on costs and other necessary resources to maintain the educational intervention.

CONCLUSIONS

Lower-cost digital methods such as mobile applications, simulation games and/or mobile mentoring that engage healthcare providers in continuous skills practice are feasible methods for improving neonatal resuscitation skills in LMICs. To further consider the use of these digital technologies in resource-limited settings, assessments of the resources to sustain the intervention and the effectiveness of the digital technologies on long-term health provider performance and neonatal health outcomes are required.

Newborn resuscitation timelines: Accurately capturing treatment in the delivery room

OBJECTIVES

To evaluate the use of newborn resuscitation timelines to assess the incidence, sequence, timing, duration of and response to resuscitative interventions.

METHODS

A population-based observational study conducted June 2019-November 2021 at Stavanger University Hospital, Norway. Parents consented to participation antenatally. Newborns ≥28 weeks' gestation receiving positive pressure ventilation (PPV) at birth were enrolled. Time of birth was registered. Dry-electrode electrocardiogram was applied as soon as possible after birth and used to measure heart rate continuously during resuscitation. Newborn resuscitation timelines were generated from analysis of video recordings.

RESULTS

Of 7466 newborns ≥28 weeks' gestation, 289 (3.9%) received PPV. Of these, 182 had the resuscitation captured on video, and were included. Two-thirds were apnoeic, and one-third were breathing ineffectively at the commencement of PPV. PPV was started at median (quartiles) 72 (44, 141) seconds after birth and continued for 135 (68, 236) seconds. The ventilation fraction, defined as the proportion of time from first to last inflation during which PPV was provided, was 85%. Interruption in ventilation was most frequently caused by mask repositioning and auscultation. Suctioning was performed in 35% of newborns, in 95% of cases after the initiation of PPV. PPV was commenced within 60 s of birth in 49% of apnoeic and 12% of ineffectively breathing newborns, respectively.

CONCLUSIONS

Newborn resuscitation timelines can graphically present accurate, time-sensitive and complex data from resuscitations synchronised in time. Timelines can be used to enhance understanding of resuscitation events in data-guided quality improvement initiatives.

How Much Training Is Enough? Low-Dose, High-Frequency Simulation Training and Maintenance of Competence in Neonatal Resuscitation

INTRODUCTION

Facemask ventilation is a crucial, but challenging, element of neonatal resuscitation.In a previously reported study, instructor-led training using a novel neonatal simulator resulted in high-level ventilation competence for health care providers (HCPs) involved in newborn resuscitation. The aim of this study was to identify the optimal frequency and dose of simulation training to maintain this competence level.

METHODS

Prospective observational study of HCPs training through 9 months. All training was logged. Overall ventilation competence scores were calculated for each simulation case, incorporating 7 skill elements considered important for effective ventilation.Overall scores and skill elements were analyzed by generalized linear mixed effects models using frequency (number of months of 9 where training occurred and total number of training sessions in 9 months) and dose (total number of cases performed) as predictors. Training loads (frequency + dose) predictive of high scores were projected based on estimated marginal probabilities of successful outcomes.

RESULTS

A total of 156 HCPs performed 4348 training cases. Performing 5 or more sessions in 9 months predicted high global competence scores (>28/30). Frequency was the best predictor for 4 skill elements; success in maintaining airway patency and ventilation fraction was predicted by performing training in, respectively, 2 and 3 months of 9, whereas for avoiding dangerously high inflating pressures and providing adequate mask seal, 5 and 6 sessions, respectively, over the 9 months, predicted success. Skills reflecting global performance (successful resuscitation and valid ventilations) and ventilation rate were more dose-dependent.

CONCLUSIONS

Training frequency is important in maintaining neonatal ventilation competence. Training dose is important for some skill elements. This offers the potential for individualized training schedules.

"Safer Births Bundle of Care" Implementation and Perinatal Impact at 30 Hospitals in Tanzania-Halfway Evaluation

Safer Births Bundle of Care (SBBC) consists of innovative clinical and training tools for improved labour care and newborn resuscitation, integrated with new strategies for continuous quality improvement. After implementation, we hypothesised a reduction in 24-h newborn deaths, fresh stillbirths, and maternal deaths by 50%, 20%, and 10%, respectively. This is a 3-year stepped-wedged cluster randomised implementation study, including 30 facilities within five regions in Tanzania. Data collectors at each facility enter labour and newborn care indicators, patient characteristics and outcomes. This halfway evaluation reports data from March 2021 through July 2022. In total, 138,357 deliveries were recorded; 67,690 pre- and 70,667 post-implementations of SBBC. There were steady trends of increased 24-h newborn and maternal survival in four regions after SBBC initiation. In the first region, with 13 months of implementation (n = 15,658 deliveries), an estimated additional 100 newborns and 20 women were saved. Reported fresh stillbirths seemed to fluctuate across time, and increased in three regions after the start of SBBC. Uptake of the bundle varied between regions. This SBBC halfway evaluation indicates steady reductions in 24-h newborn and maternal mortality, in line with our hypotheses, in four of five regions. Enhanced focus on uptake of the bundle and the quality improvement component is necessary to fully reach the SBBC impact potential as we move forward.