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一种用于评估 COVID-19 疫情期间急诊科绩效的模糊混合多准则决策方法。

A Fuzzy Hybrid MCDM Approach for Assessing the Emergency Department Performance during the COVID-19 Outbreak.

机构信息

Department of Productivity and Innovation, Universidad de la Costa CUC, Barranquilla 081001, Colombia.

School of Transportation and Logistics, Istanbul University, Istanbul 34320, Turkey.

出版信息

Int J Environ Res Public Health. 2023 Mar 5;20(5):4591. doi: 10.3390/ijerph20054591.

Abstract

The use of emergency departments (EDs) has increased during the COVID-19 outbreak, thereby evidencing the key role of these units in the overall response of healthcare systems to the current pandemic scenario. Nevertheless, several disruptions have emerged in the practical scenario including low throughput, overcrowding, and extended waiting times. Therefore, there is a need to develop strategies for upgrading the response of these units against the current pandemic. Given the above, this paper presents a hybrid fuzzy multicriteria decision-making model (MCDM) to evaluate the performance of EDs and create focused improvement interventions. First, the intuitionistic fuzzy analytic hierarchy process (IF-AHP) technique is used to estimate the relative priorities of criteria and sub-criteria considering uncertainty. Then, the intuitionistic fuzzy decision making trial and evaluation laboratory (IF-DEMATEL) is employed to calculate the interdependence and feedback between criteria and sub-criteria under uncertainty, Finally, the combined compromise solution (CoCoSo) is implemented to rank the EDs and detect their weaknesses to device suitable improvement plans. The aforementioned methodology was validated in three emergency centers in Turkey. The results revealed that the most important criterion in ED performance was (14.4%), while evidenced the highest positive D + R value (18.239) among the dispatchers and is therefore deemed as the main generator within the performance network.

摘要

在 COVID-19 疫情期间,急诊科(EDs)的使用量增加了,这证明了这些单位在医疗系统应对当前大流行情况的整体反应中的关键作用。然而,在实际情况中出现了一些中断,包括低吞吐量、过度拥挤和延长的等待时间。因此,需要制定策略来提高这些单位对当前大流行的应对能力。鉴于上述情况,本文提出了一种混合模糊多准则决策模型(MCDM),以评估急诊科的绩效并创建有针对性的改进干预措施。首先,直觉模糊层次分析法(IF-AHP)技术用于在考虑不确定性的情况下估计准则和子准则的相对优先级。然后,直觉模糊决策试验和评估实验室(IF-DEMATEL)用于在不确定性下计算准则和子准则之间的相互依存关系和反馈。最后,实施组合妥协解(CoCoSo)来对急诊科进行排名,并发现其弱点,以制定合适的改进计划。上述方法在土耳其的三个急救中心进行了验证。结果表明,急诊科绩效的最重要准则是(14.4%),而调度员的最高正 D + R 值(18.239)表明调度员是绩效网络中的主要生成器。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5b07/10001734/ad679812482a/ijerph-20-04591-g001.jpg

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