RESUMO
OBJECTIVE: To apply the THOR 2 multi-criteria support system to select the Brazilian navy's most suitable hospital care vessel (NAsH) to support the fight against the covid-19 pandemic. METHODS: We used the first three stages of the Soft Systems Methodology for structuring and modeling of the problem. For the evaluation and ordering of alternatives, we used the Thor 2 multi-criteria support system, comparing four classes of NAsH in the light of their operational and hospital criteria: "Dr. Montenegro," "Soares Meirelles," "Oswaldo Cruz" and "Tenente Maximiano." The chosen ship would support the amazon hospital system, which has an increasing number of cases of covid-19. RESULTS: After the application of the methods, we analyzed three distinct scenarios of ordering the alternatives, which allowed a robust sensitivity analysis, conferring greater transparency and reliability to the decision-making process. The NAsH "Oswaldo Cruz" was selected to be used in the fight against the pandemic. CONCLUSIONS: This study brings valuable contribution to academia and society, since it represents the application of a multi-criteria decision-aid method in the state of the art to contribute to the solution of a real problem that affects millions of people in Brazil and worldwide.
Assuntos
Comportamento de Escolha , Infecções por Coronavirus/prevenção & controle , Hospitais , Pandemias/prevenção & controle , Pneumonia Viral/prevenção & controle , Navios , Brasil/epidemiologia , COVID-19 , Infecções por Coronavirus/epidemiologia , Humanos , Pneumonia Viral/epidemiologiaRESUMO
ABSTRACT OBJECTIVE: To apply the THOR 2 multi-criteria support system to select the Brazilian navy's most suitable hospital care vessel (NAsH) to support the fight against the covid-19 pandemic. METHODS: We used the first three stages of the Soft Systems Methodology for structuring and modeling of the problem. For the evaluation and ordering of alternatives, we used the Thor 2 multi-criteria support system, comparing four classes of NAsH in the light of their operational and hospital criteria: "Dr. Montenegro," "Soares Meirelles," "Oswaldo Cruz" and "Tenente Maximiano." The chosen ship would support the amazon hospital system, which has an increasing number of cases of covid-19. RESULTS: After the application of the methods, we analyzed three distinct scenarios of ordering the alternatives, which allowed a robust sensitivity analysis, conferring greater transparency and reliability to the decision-making process. The NAsH "Oswaldo Cruz" was selected to be used in the fight against the pandemic. CONCLUSIONS: This study brings valuable contribution to academia and society, since it represents the application of a multi-criteria decision-aid method in the state of the art to contribute to the solution of a real problem that affects millions of people in Brazil and worldwide.
RESUMO OBJETIVO: Aplicar o método multicritério THOR 2 para selecionar o navio de assistência hospitalar (NAsH) da Marinha do Brasil mais indicado para apoiar o combate à pandemia de covid-19. MÉTODOS: Para a estruturação e modelagem do problema, foram usados os três primeiros estágios da Soft Systems Methodology. Já para a avaliação e ordenação das alternativas, foi utilizado o método de análise multicritério Thor 2, comparando quatro classes de NAsH à luz de seus critérios operativos e hospitalares: "Dr. Montenegro", "Soares Meirelles", "Oswaldo Cruz" e "Tenente Maximiano". O navio escolhido apoiaria o sistema hospitalar do Amazonas, que apresenta número cada vez maior de casos de covid-19. RESULTADOS: Após a aplicação dos métodos, foi possível analisar três cenários distintos de ordenação das alternativas, o que permitiu uma análise de sensibilidade robusta, conferindo maior transparência e confiabilidade ao processo decisório. O NAsH "Oswaldo Cruz" foi selecionado para ser empregado no combate à pandemia. CONCLUSÕES: Este trabalho traz valiosa contribuição para academia e sociedade, uma vez que representa a aplicação de um método de auxílio à decisão multicritério no estado da arte para contribuir com a solução de um problema real que afeta milhões de pessoas no Brasil e no mundo.
