This article examines the reliability of the Human Factors Analysis and Classification System (HFACS) for classifying observational human factors data collected prospectively in a trauma resuscitation center.
Three trained human factors analysts individually categorized 1,137 workflow disruptions identified in a previously collected data set involving 65 observed trauma care cases using the HFACS framework.
Results revealed that the framework was substantially reliable overall (κ = 0.680); agreement increased when only the preconditions for unsafe acts were investigated (κ = 0.757). Findings of the analysis also revealed that the preconditions for unsafe acts category was most highly populated (91.95%), consisting mainly of failures involving communication, coordination, and planning.
This study helps validate the use of HFACS as a tool for classifying observational data in a variety of medical domains. By identifying preconditions for unsafe acts, health care professionals may be able to construct a more robust safety management system that may provide a better understanding of the types of threats that can impact patient safety.
For more information on this article, contact Tara N. Cohen at email@example.com.
The authors declare no conflicts of interest.