Identifying High-Risk Workers’ Actions Contributing to Highway Construction Accidents

Analyzing historical construction accident narratives is widely implemented by researchers to understand critical causes of past accidents. Previous studies have identified accident causes and affected body parts to assist safety managers in making timely decisions to prevent accidents. However, the sequential relationship between workers’ actions and accidents, which can provide valuable insights, has not been investigated. This study addresses the gap by conducting a novel investigation into the most common sequential patterns between workers’ pre-accident actions and accidents. PrefixSpan sequential pattern mining algorithm was employed on large-scale sequential data extracted from Occupational Safety and Health Administration accident reports in highway construction. The results show that “operating machines or equipment” and “working at height” are the most common actions leading to severe highway construction accidents. Furthermore, the sequence pattern “operating machines or equipment → crushed by objects → fatality” ranks high among the top accident patterns, with an 80% confidence level. Organizations can use the findings to devise specific safety programs and interventions to mitigate future incidents.