Accommodating individual preferences in nurse scheduling via auctions and optimization.

Area of Science:

• Operations Research
• Healthcare Management
• Computer Science

Background:

• Traditional nurse scheduling often struggles to balance staff preferences with operational demands.
• Existing methods may lead to suboptimal schedules, impacting nurse morale and hospital efficiency.

Purpose of the Study:

• To develop and evaluate a two-stage nurse scheduling approach that integrates nurse preferences and hospital constraints.
• To improve the efficiency and fairness of nurse scheduling in a hospital setting.

Main Methods:

• A two-stage approach involving an "auction stage" where nurses bid for shifts using points.
• An "optimization model" awards shifts based on bids while meeting hospital requirements.
• A "schedule completion stage" uses another optimization model to fill remaining shifts.

Main Results:

• The approach successfully generated a schedule with a high percentage of awarded bids in minimal computer time.
• Demonstrated effectiveness in a case study within an emergency department.
• Further experiments indicated robust performance across various conditions.

Conclusions:

• The proposed two-stage nurse scheduling method effectively balances nurse preferences with hospital constraints.
• This approach offers a computationally efficient and adaptable solution for complex scheduling problems in healthcare.
• The findings suggest potential for widespread adoption in improving nurse scheduling practices.