OPTIMIZATION MODEL FOR THE INSTALLATION OF SAMU BASES: APPLICATION IN NATAL-RN

• Autor(a) principal: Cabral, Eric Lucas dos Santos
• Data de Publicação: 2020
• Outros Autores: Castro, Wilkson Ricardo Silva, Francisco, Claudia Aparecida Cavalheiro, Souza, Ricardo Pires de
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: GEPROS. Gestão da Produção. Operações e Sistemas
• Texto Completo: https://revista.feb.unesp.br/gepros/article/view/2668
• topic: Emergency medical service; health care; model simulation

Purpose – The objective of this study was the application of a mathematical model aiming to designate neighborhoods to install new Mobile Emergency Care Service (SAMU) bases to minimize the distance traveled by ambulances in the city of Natal / RN.Design/methodology/approach –The data were grouped in order to obtain parameters, such as: call district, time, day of the week, number of accidents. After data collection and processing, a matrix of neighborhood-to-neighborhood distances in the city of Natal based on Google Maps was created. A model was created to minimize the distance traveled by ambulances with the aid of the AIMMS program.Findings – The application of the model allowed for the simulation of scenarios with the installation of 3 to 8 fixed bases. There was a significant reduction in the distance traveled by the ambulances, which reached 48%, after the installation of eight bases. In other words, there was a reduction of 6,560 kilometers traveled per month by ambulances.  Research, Practical & Social implications – The reduction in the total distance covered by the ambulances has practical and social implications, since it provides an increase in the number of ambulances available to serve the population and directly reflects in the reduction in the average response time of the service. Originality/value – The article contributes to the debate on efficiency in Brazilian medical emergency services by proposing engineering and management solutions for monitoring critical indicators such as response time.Keywords - Emergency medical service. Health care. Model simulation