Optimization of the Healthcare Infrastructure Planning in Guanajuato: A Comprehensive Primary Healthcare Units Planning Model

Abstract: The planning of primary healthcare infrastructure is essential for improving population access to healthcare services, especially in developing countries where access to healthcare is limited. In this work, we propose the use of a bi-objective optimization model to support the decision-making process related to the strategic decisions of locating new Primary Healthcare Units (PHUs), upgrading the installed capacity in the PHUs network, and allocating demand points to PHUs. We present a case study based on the State of Guanajuato, Mexico; a federal entity with more than 6 million inhabitants in 2020, where more than 21% of the population lacks formal healthcare insurance and the other 35% is affiliated to a public healthcare institution. The problem addressed was solved for each of the state's eight regions, with instances between 650 and 1398 demand points, generating the Pareto set for five different budget scenarios. The problem minimizes the weighted total travel distance from demand points to PHUs for general medical consultation while maximizing the demand coverage for complementary services such as nutrition counseling, dental care, mental health, clinical analysis, and imaging. An augmented version of the ε-constraint method is used to find the Pareto sets, and the Cplex solver is employed to solve all the generated instances. The model's usefulness is shown through its application in the case study.