To compare satisfaction levels of neurology residents that worked night shift prior to the implementation of a swing shift versus after the implementation of the shift.

Neurology residents often face challenges during night shifts including high workload, fatigue, and reduced support. This can adversely impact their learning environment, satisfaction, overall well-being, and patient care. Prior studies showed that interns made substantially more medical errors when working frequent 24hr shifts compared to shorter shifts. Not many studies are evaluating resident satisfaction with shorter shifts.

Current and recent neurology graduates from The University of Kansas Medical Center were asked to complete a survey one year after the implementation of a swing shift (16:30-23:00). This shift was designed to bridge the gap between day shift (07:00-16:30) and night shift (19:00-07:00). Resident satisfaction was measured using a novel survey instrument. Responses were compared between pre- and post-implementation of the swing shift. Statistical analysis was performed using paired t-tests.

A total of 26 residents and graduates participated in the study. Nine graduates and four PGY4 residents experienced night shift pre-implementation of the swing shift. Seven PGY3 residents and six PGY2 residents experienced night shift post-implementation. The swing shift was associated with a statistically significant increase in satisfaction with night shift (mean difference 1.492, p < 0.0005). Specifically, individual workload decreased (clinical duties 18 pre and 16 post), burnout decreased (69.2% pre and 38.5% post), time to respond to an emergency decreased (8.3% <5 min pre and 53.8% post) and patient safety concerns decreased (84.6% pre and 30.8% post).

The implementation of a swing shift improved neurology resident satisfaction. Taking into account recall bias, these findings suggest that changes in scheduling can impact resident well-being and patient care. Further longitudinal studies are warranted to assess the long-term benefits and potential scalability across different specialties and institutions.