Bickley Steve J, Torgler Benno
School of Economics and Finance, Queensland University of Technology, 2 George St, Brisbane, QLD 4000, Australia.
Centre for Behavioural Economics, Society and Technology (BEST), 2 George St, Brisbane, QLD 4000, Australia.
Saf Sci. 2021 Aug;140:105312. doi: 10.1016/j.ssci.2021.105312. Epub 2021 Apr 18.
In this article, we argue for a novel adaptation of the Human Factors Analysis and Classification System (HFACS) to incidence prevention in the public health and in particular, during and in response to COVID-19. HFACS is a framework of causal categories of human errors typically applied for systematic retrospective incident analysis in high-risk domains. By leveraging this approach proactively, appropriate, and targeted measures can be quickly identified and established to mitigate potential errors at different levels within the public health system (from tertiary and secondary healthcare workers to primary public health officials, regulators, and policymakers).
在本文中，我们主张对人为因素分析与分类系统（HFACS）进行一种新颖的调整，以用于公共卫生领域的事件预防，特别是在新冠疫情期间以及应对新冠疫情时。HFACS是一个人为错误因果类别的框架，通常用于高风险领域的系统性回顾性事件分析。通过积极运用这种方法，可以迅速确定并制定适当且有针对性的措施，以减轻公共卫生系统内不同层面（从三级和二级医护人员到基层公共卫生官员、监管机构和政策制定者）的潜在错误。
