Few studies explore emergency medicine (EM) residency shift scheduling software as a mechanism to reduce administrative demands and broader resident burnout. A local needs assessment demonstrated a learning curve for chief resident schedulers and several areas for improvement. In an institutional quality improvement project, we utilized an external online cross-sectional convenience sampling pilot survey of United States EM residency programs to collect information on manual versus software-based resident shift scheduling practices and associated scheduler and scheduler-perceived resident satisfaction. Our external survey response rate was 19/253 (8%), with all United States regions (i.e., northeast, southeast, midwest, west, and southwest) represented. Two programs (11%) reported manual scheduling without any software. ShiftAdmin was the most popularly reported scheduling software (53%). Although not statistically significant, manual scheduling had the lowest satisfaction score and programs with ≤30 residents reported the highest levels of satisfaction. Our data suggest that improvements in existing software-based technologies are needed. Artificial intelligence technologies may prove useful for reducing administrative scheduling demands and optimizing resident scheduling satisfaction.
Keywords: ACGME; AI; MedEd; burnout; medical education; wellness.