Proceedings of the 3rd International Conference on Big Data Economy and Digital Management, BDEDM 2024, January 12–14, 2024, Ningbo, China

Research Article

Application of Data Analysis in Risk Management and Control of Medical Waste Treatment Workshops -Analysis and Control of the Safety Risk Data Safety Risk Data Analysis of Medical Waste Treatment Workshops

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  • @INPROCEEDINGS{10.4108/eai.12-1-2024.2347246,
        author={Huifen  Wang and Shuai  Liu and Tangxiao  Yuan and Leilei  Zhai},
        title={Application of Data Analysis in Risk Management and Control of Medical Waste Treatment Workshops -Analysis and Control of the Safety Risk Data Safety Risk Data Analysis of Medical Waste Treatment Workshops },
        proceedings={Proceedings of the 3rd International Conference on Big Data Economy and Digital Management, BDEDM 2024, January 12--14, 2024, Ningbo, China},
        publisher={EAI},
        proceedings_a={BDEDM},
        year={2024},
        month={6},
        keywords={medical waste disposal workshop (mwdw); human factors analysis and classification system (hfacs); accident causes; safety risks},
        doi={10.4108/eai.12-1-2024.2347246}
    }
    
  • Huifen Wang
    Shuai Liu
    Tangxiao Yuan
    Leilei Zhai
    Year: 2024
    Application of Data Analysis in Risk Management and Control of Medical Waste Treatment Workshops -Analysis and Control of the Safety Risk Data Safety Risk Data Analysis of Medical Waste Treatment Workshops
    BDEDM
    EAI
    DOI: 10.4108/eai.12-1-2024.2347246
Huifen Wang1,*, Shuai Liu1, Tangxiao Yuan1, Leilei Zhai1
  • 1: Nanjing University of Science and Technology
*Contact email: 188015065@qq.com

Abstract

In the post-epidemic era, the workload of medical waste disposal workshops is still huge, and it is necessary to ensure the safety of medical waste disposal personnel in various aspects. In order to explore the potential safety risks in the medical waste disposal workshop (MWDW), find out the key factors, and reveal the cause of accidents in the medical waste disposal workshop. In this paper, the HFACS-MWDW model suitable for analyzing MWDW is constructed on the basis of the Human Factors Analysis and Classification System (HFACS) method, and the causal analysis of MWDW is carried out from four levels: unsafe behavior, unsafe behavior premise, unsafe supervision, and organizational influence. The chi-square test (χ2) and odds ratio (OR) were used to analyze the causal relationship between the upper and lower levels. Based on this method, 205 accident reports of medical waste disposal workshops were analyzed as samples, and it was found that the more common causative factors in medical waste workshops were organizational process, failure to correct known problems in time, personnel factors and mistakes; the correlation strength was obtained And the largest accident-causing path is: operation management→unreasonable work arrangement→capacity limitation→decision-making error, the total OR value is 14.755. Finally, based on the analysis results, countermeasures to prevent potential security risks in MWDW are proposed.