Cargando…
Providing an approach to analyze the risk of central oxygen tanks in hospitals during the COVID-19 pandemic
The central oxygen unit of hospitals is considered a high-risk unit, requiring high safety standards to maintain the integrity of the system during the COVID-19 pandemic. The linear reasoning assumption of conventional risk analysis methods cannot adequately describe these modern systems, which are...
Autores principales: | , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10404783/ https://www.ncbi.nlm.nih.gov/pubmed/37554837 http://dx.doi.org/10.1016/j.heliyon.2023.e18736 |
_version_ | 1785085376002523136 |
---|---|
author | Laal, Fereydoon Hanifi, Saber Moradi Madvari, Rohollah Fallah Khoshakhlagh, Amir Hossein Arefi, Maryam Feiz |
author_facet | Laal, Fereydoon Hanifi, Saber Moradi Madvari, Rohollah Fallah Khoshakhlagh, Amir Hossein Arefi, Maryam Feiz |
author_sort | Laal, Fereydoon |
collection | PubMed |
description | The central oxygen unit of hospitals is considered a high-risk unit, requiring high safety standards to maintain the integrity of the system during the COVID-19 pandemic. The linear reasoning assumption of conventional risk analysis methods cannot adequately describe these modern systems, which are characterized by tight connections and complex interactions between technical, human, and organizational aspects. Therefore, this study presents a new and comprehensive approach to oxygen tanks in hospitals during the COVID-19 pandemic. In this study, trapezoidal fuzzy numbers were used to calculate failure rates. After determining the probability of basic events (BEs), intermediate events (IE), and top event (TE) with fuzzy logic and transferring it into Bayesian Network (BN), deductive and inductive reasoning, and sensitivity analysis were performed using RoV in GeNIe software. The results of the case study showed that the IE of “Human Error” had the highest probability of fuzzy fault tree (FFT) and the probability of oxygen leakage was lower using FBN than FFT. According to the results, BE16 (failure to use standard and updated instructions) and BE12 (defects in the inspection and testing program of tank devices) had the highest posterior probability, while based on the FFT results, BE4 (defects in the external coating system of the tank) and, BE3 (Corrosive environment (acidity state)) had the least probability. According to the sensitivity analysis, basic events 10, 11, and 16 were the most important in the oxygen leakage event with a very small difference, which was almost in line with the results of posterior FBN (FBN(PO)). Updating the existing guidelines, fixing defects in the inspection of all types of tank gauges, and testing related equipment can greatly help the reliability of these tanks. Root cause analysis of these events provides opportunities for prevention and emergency response in critical situations, such as the COVID-19 pandemic. |
format | Online Article Text |
id | pubmed-10404783 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-104047832023-08-08 Providing an approach to analyze the risk of central oxygen tanks in hospitals during the COVID-19 pandemic Laal, Fereydoon Hanifi, Saber Moradi Madvari, Rohollah Fallah Khoshakhlagh, Amir Hossein Arefi, Maryam Feiz Heliyon Research Article The central oxygen unit of hospitals is considered a high-risk unit, requiring high safety standards to maintain the integrity of the system during the COVID-19 pandemic. The linear reasoning assumption of conventional risk analysis methods cannot adequately describe these modern systems, which are characterized by tight connections and complex interactions between technical, human, and organizational aspects. Therefore, this study presents a new and comprehensive approach to oxygen tanks in hospitals during the COVID-19 pandemic. In this study, trapezoidal fuzzy numbers were used to calculate failure rates. After determining the probability of basic events (BEs), intermediate events (IE), and top event (TE) with fuzzy logic and transferring it into Bayesian Network (BN), deductive and inductive reasoning, and sensitivity analysis were performed using RoV in GeNIe software. The results of the case study showed that the IE of “Human Error” had the highest probability of fuzzy fault tree (FFT) and the probability of oxygen leakage was lower using FBN than FFT. According to the results, BE16 (failure to use standard and updated instructions) and BE12 (defects in the inspection and testing program of tank devices) had the highest posterior probability, while based on the FFT results, BE4 (defects in the external coating system of the tank) and, BE3 (Corrosive environment (acidity state)) had the least probability. According to the sensitivity analysis, basic events 10, 11, and 16 were the most important in the oxygen leakage event with a very small difference, which was almost in line with the results of posterior FBN (FBN(PO)). Updating the existing guidelines, fixing defects in the inspection of all types of tank gauges, and testing related equipment can greatly help the reliability of these tanks. Root cause analysis of these events provides opportunities for prevention and emergency response in critical situations, such as the COVID-19 pandemic. Elsevier 2023-07-27 /pmc/articles/PMC10404783/ /pubmed/37554837 http://dx.doi.org/10.1016/j.heliyon.2023.e18736 Text en © 2023 The Authors. Published by Elsevier Ltd. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Research Article Laal, Fereydoon Hanifi, Saber Moradi Madvari, Rohollah Fallah Khoshakhlagh, Amir Hossein Arefi, Maryam Feiz Providing an approach to analyze the risk of central oxygen tanks in hospitals during the COVID-19 pandemic |
title | Providing an approach to analyze the risk of central oxygen tanks in hospitals during the COVID-19 pandemic |
title_full | Providing an approach to analyze the risk of central oxygen tanks in hospitals during the COVID-19 pandemic |
title_fullStr | Providing an approach to analyze the risk of central oxygen tanks in hospitals during the COVID-19 pandemic |
title_full_unstemmed | Providing an approach to analyze the risk of central oxygen tanks in hospitals during the COVID-19 pandemic |
title_short | Providing an approach to analyze the risk of central oxygen tanks in hospitals during the COVID-19 pandemic |
title_sort | providing an approach to analyze the risk of central oxygen tanks in hospitals during the covid-19 pandemic |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10404783/ https://www.ncbi.nlm.nih.gov/pubmed/37554837 http://dx.doi.org/10.1016/j.heliyon.2023.e18736 |
work_keys_str_mv | AT laalfereydoon providinganapproachtoanalyzetheriskofcentraloxygentanksinhospitalsduringthecovid19pandemic AT hanifisabermoradi providinganapproachtoanalyzetheriskofcentraloxygentanksinhospitalsduringthecovid19pandemic AT madvarirohollahfallah providinganapproachtoanalyzetheriskofcentraloxygentanksinhospitalsduringthecovid19pandemic AT khoshakhlaghamirhossein providinganapproachtoanalyzetheriskofcentraloxygentanksinhospitalsduringthecovid19pandemic AT arefimaryamfeiz providinganapproachtoanalyzetheriskofcentraloxygentanksinhospitalsduringthecovid19pandemic |