Using mathematical modeling for analysis of the impact of client choice on preventive healthcare facility network design

Increasing people participation in preventive healthcare programs can improve the quality of their life and create a lot of saving. Governments can more effectively utilize their healthcare expenditures, as well. Usually, governments do not make it mandatory for people to participate in these programs but encourage them. It is necessary to design the network of preventive healthcare facilities optimally based on client choice and requirements for increasing the participation of people in such programs. Therefore, this research focuses on two models of probabilistic selection and optimal selection as different client choice for predicting and managing the preventive services networks. The limits of waiting time and the workload of each facility are also considered for ensuring the quality of care. The main characteristics of the network configuration in this paper are the number of facilities, their location, and capacity. Both models are formulated using mixed integer linear programming and a genetic algorithm is utilized in the high dimensions problems for solving them effectively and quickly. These models are implemented for actual data of Isfahan city and then their results are analyzed. The results demonstrate a significant impact of the client choice on network efficiency.