A multi-objective model for a nurse scheduling problem by emphasizing human factors

Area of Science:

• Healthcare Management
• Operations Research
• Human Factors Engineering

Background:

• Effective nurse scheduling is crucial for healthcare system efficiency and teamwork.
• Human factors like skill, preference, and compatibility significantly impact nurse performance and satisfaction.
• Existing scheduling models often overlook the nuances of individual decision-making styles.

Purpose of the Study:

• To propose a unique multi-objective mathematical model for nurse scheduling that incorporates human factors, including decision-making styles.
• To optimize nurse assignments by minimizing staffing costs and incompatibility, while maximizing nurse satisfaction.
• To evaluate the model's effectiveness using meta-heuristics and a real-life hospital case study.

Main Methods:

• Development of a multi-objective mathematical model considering nurse skill, preference, compatibility, and decision-making styles.
• Implementation of three meta-heuristics: multi-objective Keshtel algorithm, NSGA-II, and multi-objective tabu search.
• Application of data envelopment analysis (DEA) for ranking Pareto solutions and a case study in a Tehran hospital.

Main Results:

• The proposed model successfully integrated multiple objectives: cost reduction, minimized decision-making incompatibility, and maximized nurse satisfaction.
• Meta-heuristic algorithms provided effective solutions for the complex nurse scheduling problem.
• The case study demonstrated the practical applicability and effectiveness of the developed model in a real-world healthcare setting.

Conclusions:

• The novel mathematical model offers a robust approach to nurse scheduling by incorporating human factors and decision-making styles.
• Optimized nurse scheduling leads to enhanced teamwork, increased efficiency, and improved nurse morale.
• This research provides a valuable tool for healthcare administrators seeking to improve hospital operations and staff well-being.