Automation Improves Schedule Quality and Increases Scheduling Efficiency for Residents.

Area of Science:

• Medical Education
• Operations Research
• Healthcare Management

Background:

• Medical resident scheduling is complex, involving numerous rules and educational objectives.
• Manual scheduling is time-consuming, leading to variable schedule quality and negative impacts on resident morale and learning.

Purpose of the Study:

• To evaluate the effectiveness of a computerized decision support system for residency scheduling.
• To determine if automated scheduling saves time and enhances schedule quality.

Main Methods:

• The Optimized Residency Scheduling Assistant was developed and implemented in a pediatric emergency department.
• Schedule quality was assessed by comparing four metrics before and after implementation: challenging shift transitions, post-clinic shifts, total shift inequity, and night shift inequity.

Main Results:

• Automated scheduling reduced creation time from 22-28 hours to 4-6 hours per month.
• Three of four quality metrics significantly improved: challenging shift transitions decreased (83 to 14), post-clinic shifts decreased (72 to 32), and night shift inequity dropped by 55.6% (P < .01).

Conclusions:

• Computerized decision support systems effectively improve medical residency scheduling.
• Automated tools reduce scheduling time and enhance schedule quality, benefiting residency programs.