A decision support system for prevention and costing of occupational injuries

Abstract

Accident insurance institutions such as the Austrian one (Allgemeine Unfallversicherungsanstalt, AUVA) have been forced to introduce cost reduction programmes and prevention measures. For this reason, we developed sophisticated decision support systems (DSSs) from 2001 to 2012 during three projects for the AUVA. 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 using micro-simulation. A further analysis of these costs help define risk groups which is essential to derive prevention programmes and their corresponding budgets. The AUVA s data warehouse is improved by better collecting and structuring data. We also integrate main cost components for companies where casualties are working and for the economy. For example, protection clothes or specific timing of working breaks decrease costly accidents. In the future, AUVA should focus on prevention strategies for traffic injuries, preparatory site operations, building installation, and other finishing trades.