CAPTAR Project intended to increase the efficiency of how occupational accident information is used to improve safety organizational learning and prevention. The processing of information progresses up in the hierarchy through a cycle of different activities, such as: the initial gathering of accident data, its coding and interpretation (sometimes using pre-defined classification systems), the analysis of aggregated data and, finally, the way in which this information is used to learn and to develop prevention strategies. The “quality” of the resulting information, in terms of both comprehensiveness and reliability, will depend on many variables: the deepness of the investigation process, the experience of the investigator, the way questions are made, the victim’s self-interpretation of the facts, the way other people interpret and code the data, the way data is analyzed, the current practices in terms of feedback communication and the way in which accident information is used to make improvements. These factors will influence the design of prevention strategies at both public and private levels. Much of the existing research work on occupational safety assumes that the available accident raw data is accurate and reliable; therefore it can be used for deriving adequate and valid conclusions. This raises the question of knowing to what extent such assumption is valid. The current project was designed to give a contribution to answer this question and to produce guidance on good practice.
Partners: CIS-ISCTE, IST-UTL, FCT-UNL
Funding organization: Science and Technology Foundation (PT)
Project Website: http://www.mar.ist.utl.pt/captar/en/home.aspx