Using the FITradeoff Decision Support System to Support a Brazilian Compliance Organization Program.

The technology can support multi-criteria decision-making processes, allowing managers to identify efficient solutions to complex problems in a structured and rational way. Specially, in time of crises, the use of Decision Support System (DSS) is useful since these situations demand greater accuracy in the decision-making process. Therefore, this study shows the usefulness of the Decision Support System constructed for the FITradeoff method in a practical context involving a decision-making in time of crisis. In special, in this study, the applicability of the FITradeoff DSS is discussed to solve an important problem involving a Brazilian Company. The FITradeoff DSS was employed for a compliance-program problem, in which a company sought to improve its performance in relation to the program. This problem is particularly significant in Brazil where the search for compliance programs has been increasing since the adoption of the anticorruption law. Thus, twenty-eight alternatives were created, and these alternatives were evaluated against five criteria. As a result, most of the alternatives in the top of the ranking are related to Internal Communication aspect. Hence, the DM considered that these alternatives are sufficient to direct the efforts to execute the Compliance Program, and in special this theme can be the focus in this company. Furthermore, in view of recurring crises around the world, companies must identify ways to ensure their internal processes support the sustainability of their business. For decision making in times of crisis, the DSS of the FITradeoff method is an effective tool allowing decision makers to handle complex decisions.

Decision Model for Allocation of Intensive Care Unit Beds for Suspected COVID-19 Patients under Scarce Resources.

This paper puts forward a decision model for allocation of intensive care unit (ICU) beds under scarce resources in healthcare systems during the COVID-19 pandemic. The model is built upon a portfolio selection approach under the concepts of the Utility Theory. A binary integer optimization model is developed in order to find the best allocation for ICU beds, considering candidate patients with suspected/confirmed COVID-19. Experts' subjective knowledge and prior probabilities are considered to estimate the input data for the proposed model, considering the particular aspects of the decision problem. Since the chances of survival of patients in several scenarios may not be precisely defined due to the inherent subjectivity of such kinds of information, the proposed model works based on imprecise information provided by users. A Monte-Carlo simulation is performed to build a recommendation, and a robustness index is computed for each alternative according to its performance as evidenced by the results of the simulation.

Utility-Based Multicriteria Model for Screening Patients under the COVID-19 Pandemic.

In this paper, a utility-based multicriteria model is proposed to support the physicians to deal with an important medical decision-the screening decision problem-given the squeeze put on resources due to the COVID-19 pandemic. Since the COVID-19 emerged, the number of patients with an acute respiratory failure has increased in the health units. This chaotic situation has led to a deficiency in health resources. Thus, this study, using the concepts of the multiattribute utility theory (MAUT), puts forward a mathematical model to aid physicians in the screening decision problem. The model is used to generate which of the three alternatives is the best one for where patients with suspected COVID-19 should be treated, namely, an intensive care unit (ICU), a hospital ward, or at home in isolation. Also, a decision information system, called SIDTriagem, is constructed and illustrated to operate the mathematical model proposed.