Casal-Guisande Manuel, Comesaña-Campos Alberto, Cerqueiro-Pequeño Jorge, Bouza-Rodríguez José-Benito
Department of Design in Engineering, University of Vigo, 36208 Vigo, Spain.
Healthcare (Basel). 2022 Mar 21;10(3):587. doi: 10.3390/healthcare10030587.
The triage processes prior to the assignation of healthcare resources in hospitals are some of the decision-making processes that more severely affect patients. This effect gets even worse in health emergency situations and intensive care units (ICUs). Aiming to facilitate the decision-making process, in this work the use of vague fuzzy numbers is proposed, aiming to define a multi-attribute patient hierarchization method to be used in emergency situations at hospital ICUs. The incorporation of fuzzy models allows for modelling the vagueness and uncertainty associated with decision criteria evaluation, with which more efficient support is provided to the decision-making process. After defining the methodology, the effectiveness of this new system for patient hierarchization is shown in a case study. As a consequence of that, it is proved that the integration of decision-support systems into healthcare environments results to be efficient and productive, suggesting that if a part of the decision process is supported by these systems, then the errors associated with wrong interpretations and/or diagnoses might be reduced.
医院在分配医疗资源之前的分诊过程是一些对患者影响更为严重的决策过程。在卫生紧急情况和重症监护病房(ICU)中,这种影响会变得更糟。为了促进决策过程,在这项工作中提出了使用模糊模糊数,旨在定义一种在医院ICU紧急情况下使用的多属性患者分层方法。模糊模型的纳入允许对与决策标准评估相关的模糊性和不确定性进行建模,从而为决策过程提供更有效的支持。在定义了方法之后,通过一个案例研究展示了这种新的患者分层系统的有效性。因此,证明了将决策支持系统集成到医疗环境中是高效且富有成效的,这表明如果决策过程的一部分由这些系统支持,那么与错误解释和/或诊断相关的错误可能会减少。