Modelo multicritério de apoio à decisão aplicado na priorização do acesso a leitos de unidade de terapia intensiva do estado do Rio Grande do Norte

• Ano de defesa: 2021
• Autor(a) principal: Santos, Ana Flávia Alves dos
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal do Rio Grande do Norte; Brasil; UFRN; PROGRAMA DE PÓS-GRADUAÇÃO EM ENGENHARIA DE PRODUÇÃO
• Palavras-chave em Português: UTI; Priorização de pacientes; Alocação de recursos para atenção à saúde; Tomada de decisão; MCDA
• Link de acesso: https://repositorio.ufrn.br/handle/123456789/43117

The excess demand profile in relation to the available care capacity is a reality in public health services. In the context of Intensive Care Units (ICU) in Brazil the scenario is one of inequality: out of the 45,848 ICU beds distributed among 532 of the 5,570 Brazilian cities, only 49% are available to the Unified Health System (SUS), while the amount corresponding to 51% is reserved for the benefit of only 23% of the population. Given this scenario, the multicriteria decision support analysis (MCDA) acts as a potential tool to application in the decision-making process of resource allocation due to the robustness and capacity of the multicriteria methods to consider conflicting criteria. This research aimed to develop a multi-criteria model to support the decision for allocation of Adult ICU beds in the state of Rio Grande do Norte, which are under the management of the Complexo Estadual de Regulação (CER/RN). A twelve-step framework was used to apply the PROMETHEE I and II methods. The prioritization problem was approached from the perspective of the P.γ ranking problem in which six clinical vignettes based on real patients were ranked in order of preference, defined by the observed value judgments of the decision maker. Two pre-orders were recommended: a partial one, in which four pairs of actions were incomparable to each other, and a complete one, in which relationships between each pair of alternatives were described. The sensitivity analysis performed identified considerable robustness of the model since changes in positions in the rankings could be justified by the proximities of the values of each patient's positive and negative over-ranking fluxes. Thus, the proposed model formalized the decision-making process of prioritizing access to adult ICU beds and granted it a transparent and rational character by structuring the considered elements.