LAUSR

Abstract Introduction This systematic review examines and reports on peer reviewed studies that have applied systems thinking accident analysis methods to better understand the cause of accidents in a diverse range of sociotechnical systems contexts. Methods Four databases (PubMed, ScienceDirect, Scopus, Web of Science) were searched for published articles during the dates 01 January 1990 to 31 July 2018, inclusive, for original peer reviewed journal articles. Eligible studies applied AcciMap, the Human Factors Analysis and Classification System (HFACS), the Systems Theoretic Accident Model and Processes (STAMP) method, including Causal Analysis based on STAMP (CAST), and the Functional Resonance Analysis Method (FRAM). Outcomes included accidents ranging from major events to minor incidents. Results A total of 73 articles were included. There were 20, 43, six, and four studies in the AcciMap, HFACS, STAMP-CAST, and FRAM methods categories, respectively. The most common accident contexts were aviation, maritime, rail, public health, and mining. A greater number of contributory factors were found at the lower end of the sociotechnical systems analysed, including the equipment/technology, human/staff, and operating processes levels. A majority of studies used supplementary approaches to enhance the analytical capacity of base applications. Conclusions Systems thinking accident analysis methods have been popular for close to two decades and have been applied in a diverse range of sociotechnical systems contexts. A number of research-based recommendations are proposed, including the need to upgrade incident reporting systems and further explore opportunities around the development of novel accident analysis approaches.