Document Type : Article
Authors
1
Department of Industrial and Systems Engineering, Isfahan University of Technology
2
Department of Industrial and Systems Engineering, Isfahan University of Technology,
3
ِDepartment of Industrial and Systems Engineering, Isfahan University of Technology
10.24200/j65.2023.61158.2323
Abstract
The aging of the societies, social changes, medical advances, and high in-person treatment costs have increased the demand for home healthcare services. Additionally, the development of communication technology has led to the advent of the remote health systems which have benefits for caregivers and patients. In this study, we propose an integrated approach to decide on patient admission, the service types (in person or remote), patient assignment to treatment staff, and routing and scheduling of caregivers. It is assumed that, if a patient is admitted, all their requested visits must be provided. During planning horizon, patients can receive multiple visits of various types of services. However, during a single day, each patient can be visited at most once during their time window. Each treatment staff starts (ends) the routes from (to) the healthcare center, and the telehealth service is carried out from the center. Each caregiver has specific work schedules and skills. The objective is to maximize the patients' preferences and efficiency of treatment staffs as well as minimizing the patients' dissatisfaction in terms of visit day and treatment staff changes. A three-phased algorithm is developed: First, a relaxed model decides on the patient admission, the service types, and assigning patients to treatment staffs. Second, an ant colony system (ACS) determines the routing and scheduling of the staffs based on the output of the first phase. Finally, a local search is used to improve the best-known plan. To evaluate the proposed method, we use the obtained upper bound of the first phase. The computational time is considered to be at most 10 minutes. Numerical results on benchmark data show that, for all instances, the average gap between the best-found solutions and their corresponding upper bounds is less than 10%. Finally, a case study on the Maxa healthcare center is presented. According to the results, the proposed plans can improve their patient satisfaction and efficiency of treatment staffs about 31%.
Keywords
)