Development of a discrete locating model for the healthcare facilities considering efficiency and readiness

Abstract

The locating of facilities is one of the main issues in the field of operation research, and has always been a concern for many societies due to the very important role in controlling costs, quality and access to commodity and services. The use of modern scientific tools for locating in developed countries is very common and is considered as  a solution to avoid mistakes in the organization of services and production. In developing countries, these tools are also very effective in improving the ability of communities. The result of the application of modern science in locating, anywhere around the world, is well established in the quality of service and the satisfaction of suppliers and applicants. In the implementation of locating, the demand of individuals in the communities is considered as dynamic and static. In the static facilities area due to the high relative dimensions and, in principle, the impossibility of low cost relocation, locating decisions assign high importance and precision. Given influence of the efficiency and readiness of a healthcare center such as a hospital in choosing new services and locations for establishing or maintaining a service, can be very helpful and will prevent future mistakes and adjust previous preferences. The most important question that has been answered in this study is the impact of the effectioncy and services in locating and allocating services and re-examining hospital capacities. By measuring the efficiency and readiness indexes through data envelopment analysis models and ranking the provided services, a more precise decision can be made and a review of the applied policies can be considered. Therefore, in this paper, a model is proposed with consideration of different services for a hospital and quality for each service, in which it seeks to minimize operational and maintenance costs and, as well as, maximize the quality and efficiency. The goal of this model is to provide an approach for optimal location of the centers, which reduces investment and operational costs. The proposed model is solved by the modified Epsilon Limit Approach. The results indicate the proper functioning of the system after the implementation of the proposed model.