BACKGROUND Community hospital labor and delivery units manage approximately 40% of US births (1.5 million in 2022), yet face challenges with complex neonatal resuscitation due to infrequent exposure. Multiple high-acuity resuscitations in our community hospitals revealed a need for improvement. Simulation effectively augments Neonatal Resuscitation Program (NRP) training, but many community hospitals lack the necessary resources. Using QI principles, we aimed to create an affordable, sustainable, structured simulation project to improve neonatal resuscitation performance. METHODS Monthly in-situ simulation sessions at 4 community sites used low-technology mannequins rotating through 4 high-acuity, low-occurrence scenarios. NRP performance was tracked longitudinally. In a continuous change model of improvement, we refined our simulation, educated on performance gaps, and remediated latent safety threats (LSTs). Performance scores were analyzed by statistical process control methods. Comparative statistics analyzed change in NRP subset scores, participant self-efficacy, and simulation satisfaction. RESULTS In 65 sessions over 24 months, all clinicians and over 75% of respiratory therapists and nurses participated in at least one session. NRP mean performance scores demonstrated positive special cause variation-clinical scores: 51% to 66%; behavioral scores: 46% to 67%. Confidence increased significantly in all areas except medication and blood administration. Satisfaction with simulation was high (≥4, Likert scale 1–5). We identified 147 LSTs; most were mitigated. Monthly sessions continued after project completion. CONCLUSION This low-cost, sustainable simulation project improved NRP performance and self-efficacy. If widely implemented, this model can foster a culture of simulation-based education, support ongoing improvement, and reduce LSTs in community hospital labor and delivery units.
Stempowski et al. (2026) studied this question.