Volume 20, Issue 1 (2023)
ioh 2023, 20(1): 178-193 |
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Shakiba Z, Farshad A A, Alimohamadi I, Hassanzadeh-Rangi N, Khosravi Y. CAUSATION OF FIRE ACCIDENT IN MEDICAL CENTERS: LEARNING FROM THE ACCIDENT IN SINA MEHR MEDICAL CLINIC IN TEHRAN (JUNE 30, 2020). ioh 2023; 20 (1) :178-193
URL: http://ioh.iums.ac.ir/article-1-3428-en.html
URL: http://ioh.iums.ac.ir/article-1-3428-en.html
Department of Occupational Health and Safety Engineering, School of Health, Non-communicable Diseases Research Center, Research Center for Health, Safety and Environment, Alborz University of Medical Sciences, Karaj, Iran , yakhosravi@yahoo.com
Abstract: (819 Views)
Abstract
Background and aims: Little is known about the causes and contributing factors of fire accidents in medical centers, like the fire accident in Sina Mehr medical clinic in Tehran on June 30, 2020 (19 killed and 14 injured). This study aims to analyze the causes and contributing factors of fire accidents in medical centers to prevent similar accidents.
Methods: We used literature review, official reports, regulations, and interviews with experts for data collection. Partial and holistic thematic analysis approaches were used to extract causes and causal factors. Fish Bone (FB), Bow Tie (BT), and Swiss Cheese Model (SCM) were used in open and axial coding of causes and causal factors, and extracting logical sequences of events and consequences of accidents. To confirm the findings, we used expert opinion.
Results: We identified 174 causal factors by open coding and 17 causal factor categories by axial coding. FB and SC were evaluated as efficient in the inductive classification of incident sub-systems. BT was able to help in presenting the system components and the logical relationships between them, drawing the time sequence, and providing control suggestions in an inductive and deductive approach.
Conclusion: Latent failures in management and supervision in issuing building and operation licenses and in occupational health and safety take medical centers to the edge of accidents. It leads to active failures in fire control and emergency response. Finally, it causes mishaps, like the fire accident in Sina Mehr medical clinic in Tehran. New accident models are useful for identifying factors that cause fire accidents and providing practical interventions for medical centers.
Background and aims: Little is known about the causes and contributing factors of fire accidents in medical centers, like the fire accident in Sina Mehr medical clinic in Tehran on June 30, 2020 (19 killed and 14 injured). This study aims to analyze the causes and contributing factors of fire accidents in medical centers to prevent similar accidents.
Methods: We used literature review, official reports, regulations, and interviews with experts for data collection. Partial and holistic thematic analysis approaches were used to extract causes and causal factors. Fish Bone (FB), Bow Tie (BT), and Swiss Cheese Model (SCM) were used in open and axial coding of causes and causal factors, and extracting logical sequences of events and consequences of accidents. To confirm the findings, we used expert opinion.
Results: We identified 174 causal factors by open coding and 17 causal factor categories by axial coding. FB and SC were evaluated as efficient in the inductive classification of incident sub-systems. BT was able to help in presenting the system components and the logical relationships between them, drawing the time sequence, and providing control suggestions in an inductive and deductive approach.
Conclusion: Latent failures in management and supervision in issuing building and operation licenses and in occupational health and safety take medical centers to the edge of accidents. It leads to active failures in fire control and emergency response. Finally, it causes mishaps, like the fire accident in Sina Mehr medical clinic in Tehran. New accident models are useful for identifying factors that cause fire accidents and providing practical interventions for medical centers.
Type of Study: Applicable |
Subject:
Safety
Received: 2022/07/17 | Accepted: 2023/01/30 | Published: 2023/03/30
Received: 2022/07/17 | Accepted: 2023/01/30 | Published: 2023/03/30
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