Integrating Nurse Preferences Into AI-Based Scheduling Systems: Qualitative Study.
Journal:
JMIR formative research
Published Date:
Jun 4, 2025
Abstract
BACKGROUND: Nurse scheduling is a complex challenge in health care, impacting both patient care quality and nurse well-being. Traditional scheduling methods often fail to consider individual preferences, leading to dissatisfaction, burnout, and high turnover. Inadequate scheduling practices, including restricted autonomy and lack of transparency, can further reduce nurse morale and negatively affect patient outcomes. Research suggests that participative scheduling approaches incorporating nurse preferences can improve job satisfaction. Artificial intelligence (AI) and mathematical optimization methods, such as mixed-integer programming (MIP), constraint programming (CP), genetic programming (GP), and reinforcement learning (RL), offer potential solutions to optimize scheduling and address these challenges.