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
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 availabl...
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| Formato: | Dissertação |
| Idioma: | pt_BR |
| Publicado em: |
Universidade Federal do Rio Grande do Norte
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| Endereço do item: | https://repositorio.ufrn.br/handle/123456789/43117 |
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| Resumo: | 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. |
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