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...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2023-08-01
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| Series: | Heliyon |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2405844023059443 |
| _version_ | 1797733014930718720 |
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| author | Fereydoon Laal Saber Moradi Hanifi Rohollah Fallah Madvari Amir Hossein Khoshakhlagh Maryam Feiz Arefi |
| author_facet | Fereydoon Laal Saber Moradi Hanifi Rohollah Fallah Madvari Amir Hossein Khoshakhlagh Maryam Feiz Arefi |
| author_sort | Fereydoon Laal |
| collection | DOAJ |
| 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 (FBNPO). 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. |
| first_indexed | 2024-03-12T12:21:54Z |
| format | Article |
| id | doaj.art-b3c8ae99acaf45c9b4f2197a5c7b434a |
| institution | Directory Open Access Journal |
| issn | 2405-8440 |
| language | English |
| last_indexed | 2024-03-12T12:21:54Z |
| publishDate | 2023-08-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Heliyon |
| spelling | doaj.art-b3c8ae99acaf45c9b4f2197a5c7b434a2023-08-30T05:52:24ZengElsevierHeliyon2405-84402023-08-0198e18736Providing an approach to analyze the risk of central oxygen tanks in hospitals during the COVID-19 pandemicFereydoon Laal0Saber Moradi Hanifi1Rohollah Fallah Madvari2Amir Hossein Khoshakhlagh3Maryam Feiz Arefi4Determinants of Health Research Center, Department of Occupational Health Engineering, Birjand University of Medical Sciences, Birjand, IranDepartment of Occupational Health Engineering, School of Public Health, Iran University of Medical Sciences, Tehran, IranDepartment of Occupational Health, School of Public Health, Shahid Sadoughi University of Medical Sciences, Yazd, IranDepartment of Occupational Health Engineering, School of Health, Kashan University of Medical Sciences, Kashan, Iran; Corresponding author.Department of Occupational Health, School of Public Health, Gonabad University of Medical Sciences, Gonabad, IranThe 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 (FBNPO). 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.http://www.sciencedirect.com/science/article/pii/S2405844023059443Central oxygen tanksHospitalsCOVID-19 pandemicRisk assessment |
| spellingShingle | Fereydoon Laal Saber Moradi Hanifi Rohollah Fallah Madvari Amir Hossein Khoshakhlagh Maryam Feiz Arefi Providing an approach to analyze the risk of central oxygen tanks in hospitals during the COVID-19 pandemic Heliyon Central oxygen tanks Hospitals COVID-19 pandemic Risk assessment |
| 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 | Central oxygen tanks Hospitals COVID-19 pandemic Risk assessment |
| url | http://www.sciencedirect.com/science/article/pii/S2405844023059443 |
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