Enhancing Physician Satisfaction and Patient Safety Through an Artificial Intelligence-Driven Scheduling System in...

Area of Science:

• Healthcare Operations
• Medical Informatics
• Artificial Intelligence

Background:

• Physician burnout and patient safety are critical challenges in clinical practice.
• Effective solutions require dynamic approaches to healthcare operations.

Purpose of the Study:

• To evaluate the impact of an AI-driven scheduling system on physician burnout.
• To assess the effect of AI scheduling on patient safety metrics, specifically intraoperative transitions of care.

Main Methods:

• Implementation of an AI scheduling system (Lightning Bolt Scheduling) in an anesthesiology department.
• Development of over 400 scheduling rules based on historical data and an idealized design framework.
• Collection of pre- and post-implementation data on physician satisfaction, vacation approvals, and intraoperative handoffs.

Main Results:

• Six months post-implementation, physician satisfaction and vacation approvals increased, indicating improved work-life balance and reduced burnout.
• A significant reduction in intraoperative handoffs (1,072 fewer) was observed.
• This reduction correlated with 71.5 fewer adverse events and estimated healthcare cost savings of $335,550 over 21 months.

Conclusions:

• AI-driven scheduling systems demonstrate potential for enhancing physician well-being.
• These systems can significantly improve patient safety by optimizing care transitions.
• Data-driven scheduling promotes adaptability and continuous improvement in healthcare operations.