开发一个优先考虑工业职业风险预防实践的模型:德尔菲研究。

Mohammad Mahdi Barati Jozan, Aynaz Lotfata, Saifuddin Khalid, Hamed Tabesh
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引用次数: 0

摘要

背景:职业事故、伤害和疾病仍然是严重的健康问题。设计和实施职业风险预防清单是减轻这些事故及其不利影响的关键策略。然而,由于职业危害的多样性,这些检查清单往往包含大量的预防措施,使其充分执行在财政和人力资源方面具有挑战性。因此,本研究旨在为这些实践提出一个优先级模型。通过识别和优先考虑最重要的预防措施,我们可以优化资源配置,提高降低职业风险的整体效果。方法:利用德尔菲法和半结构化访谈建立模型,确定职业风险预防措施优先级的影响因素。通过这个过程,我们确定了危害的类型、预防措施的性质、成本考虑和优先级排名作为重要的影响因素。随后,我们引入了一个模型,旨在根据行业需求和确定的因素优先考虑预防措施。这个建议的模型包含了已确定因素的全面整合。结果:提出的模型是基于146个预防实践设计和开发的。基于所开发模型的软件的初始版本已经由用户实现和测试。结论:所建立的模型可作为管理者的决策支持系统,根据设定的优先级提供描绘预防实践顺序的路线图。通过这种战略协调,该模型有可能对加强组织范围内的职业安全和健康产生深远影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Developing a model for prioritizing occupational risk prevention practices in industries: a Delphi study.

Background: Occupational accidents, injuries, and diseases remain critical health concerns. Designing and implementing checklists for occupational risk prevention are key strategies to mitigate these accidents and their adverse effects. However, due to the diverse nature of occupational hazards, these checklists tend to encompass a substantial number of prevention practices, making their full implementation challenging in terms of financial and human resources. Hence, this study aims to propose a prioritization model for these practices. By identifying and prioritizing the most crucial prevention practices, we can optimize resource allocation and enhance the overall effectiveness of occupational risk reduction.

Methods: To develop a model, we initiated with the utilization of the Delphi method and conducted semi-structured interviews to identify the influencing factors in prioritizing occupational risk prevention practices. Through this process, we identified the type of hazard, the nature of prevention practices, cost considerations, and priority rankings as significant influential factors. Subsequently, we introduced a model designed to prioritize prevention practices in alignment with industry needs and the identified factors. This proposed model encompasses a comprehensive integration of the identified factors.

Results: The proposed model was designed and developed based on 146 prevention practices. The initial version of the software based on the developed model has been implemented and tested by users.

Conclusions: The developed model can be used as a decision support system for managers, offering a roadmap delineating the order of prevention practices according to set priorities. Through such strategic alignment, the model holds the potential to wield a profound impact on enhancing occupational safety and health within organizational contexts.

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