Purpose
The risk of adverse events in a hospital evaluation is an important process in healthcare management. It involves several technical, social, and economical aspects. The purpose of this paper is to propose an integrated approach to evaluate the risk of adverse events in the hospital sector.
Design/methodology/approach
This paper aims to provide a decision-making framework to evaluate hospital service. Three well-known methods are applied. More specifically are proposed the following methods: analytic hierarchy process (AHP), a structured technique for organizing and analyzing complex decisions, based on mathematics and psychology developed by Thomas L. Saaty in the 1970s; decision-making trial and evaluation laboratory (DEMATEL) to construct interrelations between criteria/factors and VIKOR method, a commonly used multiple-criteria decision analysis technique for determining a compromise solution and improving the quality of decision making.
Findings
The example provided has demonstrated that the proposed approach is an effective and useful tool to assess the risk of adverse events in the hospital sector. The results could help the hospital identify its high performance level and take appropriate measures in advance to prevent adverse events. The authors can conclude that the promising results obtained in applying the AHP–DEMATEL–VIKOR method suggest that the hybrid method can be used to create decision aids that it simplifies the shared decision-making process.
Originality/value
This paper presents a novel approach based on the integration of AHP, DEMATEL and VIKOR methods. The final aim is to propose a robust methodology to overcome disadvantages associated with each method.
Gynecobstetrics departments (GDs) oversee diagnosing, monitoring, and treating female reproductive diseases as well as assisting women during pregnancy. Their importance motivates the creation of suitable performance evaluation approaches for identifying weaknesses and designing focused interventions. Therefore, the aim of this paper is twofold: (a) provide an approach for GD performance evaluation and (b) propose interventions tackling the GDs' weaknesses. The fuzzy analytic hierarchy process (FAHP) was first applied to calculate the initial criteria and subcriteria weights under vagueness. Then, the decision-making trial and evaluation laboratory (DEMATEL) was implemented to evaluate interrelations. FAHP and DEMATEL were later combined to estimate the final criteria and subcriteria weights under vagueness and interdependency. Finally, the technique for order of preference by similarity to ideal solution (TOPSIS) was used to rank the GDs and detect improvement opportunities. A case study of a cluster including three GDs is presented to validate the proposed approach. The results evidenced that patient safety and service quality are the most critical aspects in GD performance evaluation. The results from this application can be used by healthcare managers for designing focused interventions targeting improved performance of GDs. This paper fully exploits the advantages of FAHP, DEMATEL, and TOPSIS methods for evaluating performances of GDs. Furthermore, this study presents a novel decision-making model representing the multifactorial context of the GD performance.
Companies in general must establish processes that generate profitability at lower costs. Manufacturing of rice crop protection products requires major investments and resource planning, including infrastructure, raw materials, technology, human resources, tests and trials, among others, which represents a major challenge. This paper proposes a methodology that aims to minimize production costs taking different factors into consideration. The first section identifies and describes the variables required for modeling. In the second section a linear programming model is formulated to determine the optimal function in terms of cost reduction. Lastly, the model was applied at a real company, producing satisfactory results in terms of an improved production plan and an 11% cost reduction, while enabling viewing the variables with greatest impact, such as storage and shift programming, with cost reductions of 68% and 44%, respectively. The purpose is to assist companies in this industry in applying mathematical programming models to solve problems and enable better resource planning to improve profitability.
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