In bacterial infections the speed in results and accuracy of the diagnostic test is essential for the targeted treatment of the disease. Untreated time aggravates infection and inappropriate use of antibiotics can lead to the development of multidrug-resistant bacteria. An optimized microbiological analysis system can guarantee lower running costs as well as a higher service level. This work presents a mathematical model of location of facilities to create a microbiological diagnostic network formed from bacterial identification strategies and/or the presence of antimicrobial resistance in populations with suspected blood infection. The objectives of the mixed integer programming model are minimizing network logistics costs, shorten sample collection and transport times as well as maximizing the benefits from rapid and efficient diagnostics. The proposed model was applied to real demand data of microbiological procedures of the State of São Paulo. Among the eligible technologies, the optimal solution suggests the installation of 12 centralized testing laboratories. The average total time of diagnosis, excluding culture times, is 10.3 hours. The estimated annual savings on medicines represents BRL 98,498,965.70 of the budget amount dedicated to drug procurement. Compared to a decentralized diagnostic network, the results show an average reduction in microbial identification time and an economy 48 percent higher. The analyzes also highlight the impact of treatment cost on diagnostic times. The results indicate the effectiveness of the model as a tool to support decision making and aid to health care institutions and can be applied to other administrative regions and at different levels of network formation.