Pediatric Critical Care Medicine Fellow UCLA Mattel Childrens Hospital Tarzana, California, United States
Background: Burnout is a well-known, extensively studied phenomenon in the medical workplace. Given the demands of clinical training, and the degree of complex decision-making, trainees are especially at risk. Many residents endorse burnout during their pediatric intensive care unit (PICU) rotations where they experience critical illness, chronically ill children, and death and dying. Time management may also be a challenge, leading to workdays becoming “task-oriented” and detracting residents from the bedside. Currently, many interventions focus on global changes such as schedules, wellness sessions, and establishment of support-based professionals. Objective: We aimed to engage residents within pediatric critical care, empower them with caring for complex children, and reduce burnout associated with the rotation by providing protected time to enhance the humanistic connection and teaching coping strategies to be used within the workplace. Design/Methods: This was a cohort study of pediatric residents rotating through a quaternary-level PICU during the 2022-2023 academic year. Measures of burnout, mood, and resiliency were evaluated. Residents completed the Mini Z Burnout Scale, Brief Resilience Scale, and Subjective Happiness Scale pre- and post-intervention. Nurses and fellows were surveyed regarding perceptions of resident engagement at similar timeframes. The intervention saw the implementation of “social rounds,” where after formal family-centered rounds the teams rounded on a different patient and their family, learning about them from a non-medical perspective; and the establishment of a resiliency curriculum, which expanded upon an existing, structured, physiology-based PICU resident curriculum. These skills-building sessions included guides on Grief, Communication, Emotions, Active Listening, and Medical Ethics. This project has received “Certified – Exempt” status from the institutional review board. Data analysis is currently underway and will be completed in the next month.
