HUMAN-FACTORS ANALYSIS OF POSTACCIDENT DATA - APPLYING THEORETICAL TAXONOMIES OF HUMAN ERROR

Human error is involved in nearly all aviation accidents, yet most acc ident reporting systems are not currently designed around any theoreti cal human-error framework. As a result, subsequent postaccident databa ses generally are not conducive to traditional human factors analysis, making the identification of interventions extremely difficult. To ad dress this issue, this study utilized 3 conceptual models of informati on processing and human error to reorganize the human factors database associated with U.S. Navy and Marine Corps aviation accidents between 1977-1992. All 3 taxonomies were able to accommodate well over three quarters of the pilot-causal factors contained in the database. Examin ations of the recoded data revealed that procedural and response-execu tion errors were most common, followed by errors in judgment. However, judgment errors were more frequently associated with major than with minor accidents. Minor accidents, on the other hand, were associated m ore with procedural errors than were major accidents. This investigati on demonstrates that existing postaccident databases can be reorganize d using conceptual human-error frameworks, which may allow for previou sly unforeseen trends to be identified.