Optimizing Healthcare Ecosystem Performance-A Computational Study of Integrated Patient Assistance in Primary Care

Home health care professionals provide medical services to patients in their homes. With rising demand, it’s crucial to manage operational costs effectively while ensuring satisfaction for patients. This study presents a bi-objective optimization model aimed at resolving routing and scheduling challenges in home health care, with a focus on both system efficiency and patient accessibility. A Mixed-Integer Linear Programming Model (MILP) is developed. To tackle computational time challenges, we propose a Non-dominated Sorting Genetic Algorithm II to solve the multi-objective optimization problems. The evaluation of Pareto fronts demonstrates the method’s efficiency. We apply the method in a real-world case study to provide managerial implications.