A BI-OBJECTIVE LOCATION-\ALLOCATION MODEL AND CAPACITY PLANNING IN HEALTHCARE FACILITY NETWORK DESIGN

Healthcare constitutes one of the largest shares in economy. Ageing population, shortage of resources, and increasing costs of medical services cause many changes in healthcare systems. Healthcare facilities are one of the most important components of these systems. Due to these increasing changes, the facility network should be designed to use the resources optimally and serve the needsofpopulation. Inotherwords, managerstrytodesign the network in the best way in order to signicantly reduce the costs and improve the patient satisfaction. In this paper, a multi-service hospital network is presented for designing and capacity planning of healthcare facilities problem. In this model, some strategies are considered such as: 1) establishing new facilities on favorable sites, 2) opening new services in facilities, 3) determining the optimal capacity for existing and new facilities, and4)allocatingofdemandpointstofacilities. Facilities provide various services that are dierent in type, size, and quality. In some of them, it may not be allowable to open some services. In addition, it is possible to service each demand point by several hospitals and getting service from one hospital by several demand points. A bi-objective mixed integer linear mathematical programming model is presented. This bi-objective model minimizes the total network designing costs while maximizing equity throughout hospital network. Therefore, the equity is dened as the ratio of quality of providing services to distances from demand points to facilities, because the quality of services and access to care are two vital factors that directly aect the entire patient's satisfaction. We solve the model by a new version of "-constraint method (i.e., the augmented "-constraint). Also, real data from healthcare facility network in the Isfahan province of Iran is applied for validation purposes. The sensitivity analysis is done on the main parameters. Results show that the proposed model can be used to decide on designing and capacity planning of healthcare facilities.