Predictive Models from Accident Reports

There has been an enormous amount of resources spent on collecting data related to construction accidents but there are very few researches done on analyzing the collected data beyond trend analysis. This research is based on the premise that construction accident reports can be exploited much more than they currently are to obtain valuable information. Analyzing texts in accident reports in addition to coded data provides far more information than merely analyzing coded data. By analyzing and understanding what is in the accident report database yields useful knowledge. Passing this knowledge onto others can improve an understanding of what went wrong with incidents from the past thereby greatly enabling the prevention of future accidents. This accident prediction model proposed in this paper relies on the vast amount of information available in the accident report summaries kept by OSHA, and text mining of such textual summaries will unveil the variables and their relationships that may not be evident through structured data.