ArticlePediatric research2026
Using quality improvement to optimize neonatal transport team process metrics for critical transfers.
Article in Pediatric research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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6 authors.
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Abstract
BACKGROUND AND
objectivesTimely neonatal transport is essential for the care of critically ill infants. Identifying modifiable factors influencing transport mobilization time (MT) may improve efficiency and patient safety. This quality improvement (QI) initiative aimed to achieve ≥75% compliance with MT < 30 minutes, ambulance departure time (ADT) < 10 minutes, and complete vital sign documentation during transport.
methodsWe conducted a QI project in a Level III neonatal intensive care unit from January 2018 to August 2024 using iterative Plan-Do-Study-Act cycles guided by the Systems Engineering Initiative for Patient Safety framework. Multiple interventions were implemented.
resultsA total of 470 neonatal transports were analyzed. Statistical process control demonstrated common cause variation in MT and ADT, with no sustained improvement over time; performance was influenced by external system stressors. In contrast, complete vital sign documentation showed special cause variation with sustained improvement beginning in March-April 2020. Although documentation declined later, overall compliance improved across the project period.
conclusionQI interventions improved documentation reliability but did not consistently reduce MT or ADT. Sustained improvement in neonatal transport performance requires ongoing education, iterative refinement, and adaptability to external system pressures. IMPACT: A structured quality improvement initiative improved neonatal transport vital sign documentation but did not produce sustained reductions in mobilization or ambulance departure times Transport timing metrics were strongly influenced by external system stressors as well as internal process changes This study adds long term real world data from a Level III NICU evaluating neonatal transport performance over six years Use of the SEIPS framework and longitudinal SPC analysis differentiates internal process reliability from external system constraints The findings highlight the need for adaptable, resilient neonatal transport systems.
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