Decision support system for social occupational injury insurance institutions: cost analysis and targeted resource allocation

Abstract

Occupational injuries are a great burden on health care costs worldwide as they do not only cause costs directly related to the accident but also enormous long-term follow-up costs for individuals, insurance companies, employers, and the economy. We develop a detailed decision support system called “Cost Calculation Tool” for the main Austrian social occupational insurance institution (AUVA) that investigates total direct and main indirect costs of individual injury claims from the time of the incident for all injured individuals up to their death. We discuss policy implications for the occupational injury data of the year 2010. In the first two years after the accident registration, treatment costs account for about 66 %, pension costs for about 12 %, and co-payments for sick leave for about 10 % of the total AUVA costs (117.85 million Euro). An example of an underlying costly case is a middle-aged male who had a traffic-related accident at work and injured his back with lifelong costs of about 4.8 million Euro (pensions, treatment, rehabilitation, prostheses, transportation). However, pension costs are the main cost driver with nearly 50 % of total AUVA costs under a lifelong cost-perspective, while treatment costs only account for less than 15 %. In addition to these total AUVA costs, we also approximate main costs for the employers and the economy. All present and future costs predicted by the “Cost Calculation Tool” are included in the data warehouse of the AUVA and help clustering patients into risk groups according to criteria that most influence related total costs. AUVA decision makers can now optimally target prevention strategies and better plan for prevention budgets. Based on these insights and earlier research projects, the AUVA highly focuses its prevention strategies on injuries on the road to/from/at workplace, accidents at construction sites, as well as accidents in forestry and agriculture.