The Stochastic Healthcare-Facility Configuration Problem

Texas A&M Engineering Experiment Station, College Station TX

Investigators

Abstract

The research objectives of this award include a model of the stochastic healthcare facility configuration problem (SHFCP); new knowledge bases to optimize SHFCP and to model workload, capacity, and recourse; and computational tests to evaluate methodology and gain insights from focused case study. SHFCP is to prescribe facility configuration, including the location and size (allowing openings, expansions, contractions, and closures) of each facility along with the services it offers - given uncertain patient needs. The goal is a scalable methodology to plan healthcare facility configuration, for example, adjusting to demand and demographic changes. This work is timely as the U.S. seeks to expand access to healthcare services. Rural healthcare is especially problematic due to the number, demographics, and health of residents; shortage of family doctors; and travel distances. The methodology can be used by healthcare administrators to plan levels of service and by government officials to evaluate policies. The method of approach entails evolving a prototype model along with solution methodology and deriving models of workload, capacity, and expected recourse. Computational tests will evaluate efficacy and undertake case study, based on information provided by healthcare collaborators and focused on rural healthcare as a testbed. The research will have five significant broad impacts. The first two comprise benefits to society at large, which accrue from the capability to solve actual SHFCPs and the generality of results in configuring other systems and solving stochastic problems in other areas important to society. The third will result from dissemination, providing public access to data according to the Data Management Plan; making research results widely available through publication, presentations, and teaching in universities; and placing students. The fourth is that research assistants will be actively recruited from under-represented groups. The fifth impact deals with education: supplementary grants will engage undergraduate students and high school teachers