PP13 Utilising in-situ simulation and failure modes and effects analysis techniques to prepare a maternity hospital and neonatal intensive care unit for preterm delivery via emergency caesarean section in a pregnant woman with suspected covid-19

• Published in: BMJ simulation & technology enhanced learning 2020-11, Vol.6 (Suppl 1), p.A20-A21
• Main Authors: Brown, Sebastian, Nash, Matthew
• Format: Article
• Language: English
• Subjects: Coronaviruses; COVID-19; Newborn babies; Pregnancy; Simulation
• ISSN: 2056-6697
• DOI: 10.1136/bmjstel-2020-aspihconf.32

IntroductionDuring the emergence of the Covid-19 pandemic, our tertiary maternity hospital was rapidly preparing strategies to manage expected dramatic changes to practice. One of the most complex medical emergencies is the ‘Category 1’ Emergency Caesarean Section, which requires a multitude of professional teams (midwives, obstetricians, anaesthetists and theatre teams, and neonatologists). A preterm delivery of a Covid-19-positive woman could increase risks to not only to mother and baby, but also staff members.We looked at using Human Factors methodology in anticipatory planning. FMEA (Failure Modes and Effects Analysis) was an attractive tool for a novel challenge, as it uses an expert team-based approach to consider a process to mitigate potential risk.1 FMEA has been used across medical specialties, with evidence supporting harm-reduction (including in NICU therapeutics2 3), as well as in identifying potential risk in obstetric emergencies, using simulated scenarios [4].MethodsWe created a standard pre-term, Category 1 Emergency Section (under General Anaesthetic) scenario. To ensure maximal learning and relevance, we engaged senior members of all key specialities, by first running a ‘walk-through’ pre-simulation brief where we followed the patient journey from hospital entrance to recovery/neonatal unit. Once we had considered tentative new-style pathways within our teams, we ran a formal high-fidelity in-situ simulation, with volunteers for all staff roles, as well as a senior representative from each speciality to observe each stage.Following on from the simulation, the volunteer actors were summarily debriefed by their individual specialty leads, who then attended a post-simulation cross-specialty meeting to discuss the simulation chronologically, where we identified potential challenges or barriers to the ideal running of a future scenario.OutcomesThis debrief formed the basis of the putative, streamlined, FMEA. Using discussion and analysis of raised issues, estimate RPNs (Risk Prioritisation Numbers) were calculated to allow a hierarchy of problems by combining risk of occurrence, likelihood of detection and severity. Expert opinions identified strategies to improve critical systems processes.Being aware of ‘Covid-19 information overload’ we carefully disseminated department-relevant key learning points, updated trust SOPs (Standard Operating Procedures), and developed Human Factors-based tools, such as pre-made equipment boxes, checklists and