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In this paper, an approach to decision making in managing human resources that integrates multi-attribute decision making techniques with expert systems is described. The approach is based on the explicit articulation of qualitative decision knowledge which is represented by a tree of attributes and decision rules. The decision making process is supported by DEXi, a specialized expert system shell for interactive construction of the knowledge base, evaluation of options, and explanation of the results. Practical use of the shell is illustrated by an application in the field of personnel selection for a top manager position.

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Ventilator-associated pneumonia is a hospital-acquired infection of the lungs occurring in mechanically ventilated patients. An active risk management approach can prevent the occurrence of the disease and promote positive organizational changes, subsequently decreasing mortality and hospitalization costs. Using scientific and clinical practice knowledge, a risk evaluation model was developed to identify patients more at risk of developing the disease. For this purpose, a Decision Expert qualitative multi-criteria decision method was used, in which alternatives are evaluated according to predetermined hierarchically arranged criteria. Characteristics of each evaluated alternative are described by the members of an interdisciplinary expert team and are represented by the values of the basic criteria. Values of hierarchically higher aggregated criteria are computed in an upwards fashion according to utility functions, which are defined as simple logical rules. This method is integrated into a software solution, DEXi. The approach is applicable to vastly diverse decision problems and has been successfully used before for health-related decision support. The designed model was tested using actual clinical data. Evaluations of alternatives that most distinctly demonstrated the functionality of the evaluation model were selected and are presented in the results. The evaluation model is intended to assist a holistic evaluation of the risk of developing ventilator-associated pneumonia, by considering patient-related risk factors and the use of preventive measures. The model incorporates nursing-specific data that have hitherto been poorly utilized in preventing ventilator-associated pneumonia and promotes the active engagement of nurses in confronting this interdisciplinary healthcare problem, which has gained more prominence with the onset of COVID-19 disease.