Decision Support System to Prioritize Ventilators for COVID-19 Patients using AHP, Interpolation, and SAW

Nikolas Adhi Prasetyo, Retantyo Wardoyo
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引用次数: 1

Abstract

Ventilator shortages is a common problem faced by hospitals during the COVID-19 pandemic era. Healthcare workers are forced to make choices because of how big the difference between resources and lives needing it. This issue rarely comes, because normally every patient has the same rights to receive treatment and resources, but it becomes a clear problem when there are barely enough resources. Therefore, a prioritization mechanism that can objectively decide the allocation must be made to achieve the best outcome.A decision support system is a system that can support humans using data as decision makers to help them decide semi-structured/unstructured problems. The goal of this research is to create a DSS to prioritize patients who need a ventilator by incorporating two different methods, which are AHP, Interpolation, and SAW. It is hoped that the result of the research can be used to rank patients based on predetermined criterias and policy.
基于AHP、插值和SAW的COVID-19患者呼吸机优先排序决策支持系统
呼吸机短缺是新冠肺炎大流行时期医院面临的普遍问题。卫生保健工作者被迫做出选择,因为资源和需要资源的生命之间存在巨大差异。这个问题很少出现,因为通常每个病人都有同样的接受治疗和资源的权利,但当资源几乎不足时,这就成为一个明显的问题。因此,必须制定一个能够客观决定分配的优先级机制,以达到最佳结果。决策支持系统是一个能够支持人类使用数据作为决策者来帮助他们决定半结构化/非结构化问题的系统。本研究的目的是通过结合AHP、插值和SAW两种不同的方法,创建一个DSS来优先考虑需要呼吸机的患者。希望研究结果可以用于根据预先确定的标准和政策对患者进行排名。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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