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Abstract
Community Health Centers (CHCs) provide family-oriented healthcare services for people living in rural and urban medically underserved communities; they are an important part of the government's plan to make healthcare more affordable. An optimization model is developed to determine the best location and number of new CHCs in a geographical network, as well as what services each CHC should offer at which capacity level. The weighted demand coverage of the needy population is maximized subject to budget and capacity constraints, where costs are fixed and variable. Statistical methods are applied to national health databases to determine important predictors of healthcare need and disease weights, and these methods are applied to census data to obtain county-based estimates of demand. Using several performance metrics such as the number of encounters, service of uninsured persons, and coverage of rural counties, the results of the system approach to location are analyzed using the state of Georgia as a prototype. It is demonstrated that optimizing the overall network can result in improvements of 20% in several measures. The proposed model is used to analyze policy questions such as how to serve the uninsured.
Acknowledgements
We would like to thank Professor Joel Sokol of the Georgia Institute of Technology for his advice that improved the formulation of the optimization model. We would also like to acknowledge Sebastian Urbina for his help in the initial work on this problem. This work is supported in part by grant NSF DMI-0348532. The findings and conclusions in this manuscript are those of the authors and do not necessarily represent the views of the National Science Foundation or other sponsors.