Early Feasibility Lessons: A Pilot Randomized Trial of Amnioinfusion as a Novel Indication for Intrapartum Neuroprotection [ID: 1374128]

INTRODUCTION: Developing evidence-based management strategies to decrease maternal/neonatal morbidity in labor is essential. However, the barriers/facilitators to executing these trials are underreported. Our objective is to present early feasibility lessons learned after the rollout of a pilot randomized control trial examining amnioinfusion as a novel indication for intrapartum neuroprotection. METHODS: Our pilot randomized control trial began recruiting patients in July of 2022. In the first 3 months of our pilot, we followed the Plan, Do, Check, Act (PDCA) cycle to identify barriers and facilitators as a part of our feasibility aim. The PDCA cycle was executed by the primary research team and began with the first patient to be successfully consented and randomized. The barriers and facilitator were tracked by key study personnel and addressed at the weekly research meetings. Using this cycle, we developed the study protocol before widespread recruitment was initiated. RESULTS: We identified several barriers including 1) challenging acute and emergent clinical situations inherent to intrapartum care; 2) lack of provider/patient acceptability for novel indication of amnioinfusion; 3) monitoring for the development of intrapartum risk factors, and 4) unanticipated hospital system processes. We implemented several facilitators in direct response to these barriers for the pilot feasibility trial including 1) identification and presence of a research champion on labor and delivery to build rapport with staff and participants; 2) continuous education of the novel therapy; 3) incentivization of care team and participants; and 4) engagement of key stakeholders. CONCLUSION: Using a PDCA was invaluable. We identified several barriers and facilitators to be considered when designing/implementing future randomized trials intrapartum, particularly when studying novel indications of therapy.