Addressing consistency and demand uncertainty in the Home Care planning problem

Area of Science:

• Operations Research
• Healthcare Management
• Applied Mathematics

Background:

• Home care services face challenges with patient-sensitive schedules and unpredictable demand.
• Ensuring consistency in caregiver assignments and visit times is crucial for patient satisfaction and service quality.
• Demand uncertainty, including changes in patient needs and treatment plans, complicates effective service provision.

Purpose of the Study:

• To develop a robust approach for optimizing home care services by jointly considering assignment, scheduling, and routing.
• To incorporate arrival time consistency, person-oriented consistency, and demand uncertainty into a unified optimization model.
• To introduce a novel pattern-based algorithmic framework for solving complex home care scheduling problems.

Main Methods:

• Development of a mathematical model to represent the home care optimization problem.
• Decomposition of the model into a pattern-based algorithmic framework.
• Proposal of alternative pattern generation policies addressing consistency and demand uncertainty.
• Extensive computational experiments to evaluate the proposed algorithms.

Main Results:

• The pattern-based framework effectively handles consistency and demand uncertainty.
• Policies incorporating consistency and demand uncertainty yield high-quality, robust solutions.
• Significant improvements in caregiver workload balancing were observed.
• The robust approach demonstrates superior performance compared to models lacking consistency considerations.

Conclusions:

• Jointly optimizing assignment, scheduling, and routing with consistency and demand uncertainty is essential for effective home care.
• The proposed pattern-based framework offers an efficient and robust solution methodology.
• Considering patient-centered consistency significantly enhances service quality and operational efficiency.