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Evaluation of criteria and COVID-19 patients for intensive care unit admission in the era of pandemic: A multi-criteria decision making approach.
- Source :
-
Computer Methods & Programs in Biomedicine . Sep2021, Vol. 209, pN.PAG-N.PAG. 1p. - Publication Year :
- 2021
-
Abstract
- • Intensive care unit admission for COVID-19 positive patients is considered. • Fuzzy AHP is used to prioritize 19 criteria. • Multi MOORA is used to rank COVID-19 positive patients. • Which patient is more urgent for ICU is found out. The COVID-19 pandemic results in an intense flow of patients to hospitals especially to the intensive care units (ICUs) to be treated. The ICUs will therefore be confronted with a massive influx of patients (e.g. Spain and Italy). However, if the number of patients is higher than the resources available in ICUs, rationing decisions such as determining and evaluating the criteria for ICU admission becomes essential. In this case, the decision of which patients will be admitted to the ICUs may put significant pressure on healthcare personnel. The goal of this paper is to determine the criteria to be used in the decision of admission of COVID-19 patients to the ICUs. A three-step methodology is applied. In the first step, the evaluation criteria are determined, and then the criteria are prioritized using a fuzzy analytical hierarchy process (AHP) in an uncertain and multiple-criteria environment choice. Finally, COVID-19 patients are ranked using the Multi-Objective Optimization Method by Ratio Analysis to find out which patient is more urgent. According to experts' evaluation of ICU admission criteria, "increment of >2 in SOFA score" seems the most dominant factor among others. The proposed methodology is tested on 10 anonymous COVID-19 positive patients being treated in a public hospital and the ICU admission results are discussed. Obtained priorities and ranking is in line with the hospitals' behavior that potentially depicts the usefulness and validity of the proposed approach. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 01692607
- Volume :
- 209
- Database :
- Academic Search Index
- Journal :
- Computer Methods & Programs in Biomedicine
- Publication Type :
- Academic Journal
- Accession number :
- 152347189
- Full Text :
- https://doi.org/10.1016/j.cmpb.2021.106348