Lessons Learned from a Collaborative to Develop a Sustainable Simulation-Based Training Program in Neonatal Resuscitation: Simulating Success

• Main Authors: Nandini Arul, Irfan Ahmad, Justin Hamilton, Rachelle Sey, Patricia Tillson, Shandee Hutson, Radhika Narang, Jennifer Norgaard, Henry C. Lee, Janine Bergin, Jenny Quinn, Louis P. Halamek, Nicole K. Yamada, Janene Fuerch, Ritu Chitkara
• Format: Article
• Language: English
• Published: MDPI AG 2021-01-01
• Series: Children
• Subjects: neonatal resuscitation; simulation; debriefing; quality improvement
• Online Access: https://www.mdpi.com/2227-9067/8/1/39

Newborn resuscitation requires a multidisciplinary team effort to deliver safe, effective and efficient care. California Perinatal Quality Care Collaborative’s Simulating Success program was designed to help hospitals implement on-site simulation-based neonatal resuscitation training programs. Partnering with the Center for Advanced Pediatric and Perinatal Education at Stanford, Simulating Success engaged hospitals over a 15 month period, including three months of preparatory training and 12 months of implementation. The experience of the first cohort (Children’s Hospital of Orange County (CHOC), Sharp Mary Birch Hospital for Women and Newborns (SMB) and Valley Children’s Hospital (VCH)), with their site-specific needs and aims, showed that a multidisciplinary approach with a sound understanding of simulation methodology can lead to a dynamic simulation program. All sites increased staff participation. CHOC reduced latent safety threats measured during team exercises from 4.5 to two per simulation while improving debriefing skills. SMB achieved 100% staff participation by identifying unit-specific hurdles within in situ simulation. VCH improved staff confidence level in responding to neonatal codes and proved feasibility of expanding simulation across their hospital system. A multidisciplinary approach to quality improvement in neonatal resuscitation fosters engagement, enables focus on patient safety rather than individual performance, and leads to identification of system issues.