A decision support system for prevention and costing of occupational injuries

Abstract

Shrinking budgets and decreasing economic growth force accident insurance institutions to focus on cost reduction programmes as well as on prevention measures. For this reason, we developed sophisticated decision support systems (DSSs) from 2001 to 2012 during three projects for the main of the four largest Austrian accident insurance institutions (Allgemeine Unfallversicherungsanstalt, AUVA), to support their policy makers three-fold. First, we apply complex calculation schemes with an underlying population model to predict short-term and long-term occupational accident costs on an individual case basis for the AUVA using micro-simulation. Second, a further analysis of these costs allows AUVA policy makers to define risk groups which is essential to derive prevention programmes and their corresponding budgets (e.g., utilization of personal protective equipment, improvement of transportation safety, enhancement of safe driving). Third, we reveal possible improvements in collecting and structuring data for the AUVAs data warehouse for better forecasting of subsequent occupational accident costs and the underlying risk groups. Beyond the focus on AUVA interests, we integrated main cost components for companies where casualties are working (e.g., continued remuneration) and for the economy (loss in productivity for professional/non-professional work, sickness benefit). As a main result of our DSS for all three projects from 2001 to 2012, protection clothes or specific timing of working breaks decrease costly accidents. The results of the first two project periods (2001-2005) helped reduce risks of falling, while the third project (2011-2012) pointed out to focus on traffic injuries in the next years. In the future, AUVA should focus on prevention strategies in the following industries: preparatory site operations, building installation, and other finishing trades.