Citation

Olsen N, Williamson A. Appl. Ergon. 2017; 63: 31-40.

Copyright

(Copyright © 2017, Elsevier Publishing)

DOI

10.1016/j.apergo.2017.03.014

PMID

unavailable

Abstract

Accident classification systems are important tools for safety management. Unfortunately, many of the tools available have demonstrated poor reliability of coding, making their validity and usefulness questionable. This paper demonstrates the application of four strategies to improve the reliability of accident and incident classification systems. The strategies include creating a domain-specific system with limitations on system size and careful selection of codes, specifically the reduction of abstract concepts and bias-causing terminology. Using HFACS-ADF as a test case, the system was adapted using the strategies and validated using comprehension and comprehensiveness testing. The new system was then assessed for reliability. The reliability of the system increased by at least 20% at all levels of the classification system following the changes made. The results provide evidence that the application of theoretically and empirically-derived classification principles are effective for improving the reliability of accident and incident classification systems in high hazard industries.

Language: en