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Assessing the impact of inaccurate decision support systems on experts' behavior and decisions

Decision support systems increasingly support experts' work, but errors caused by them may have severe consequences, especially in the medical domain. To better understand how these inaccuracies affect experts' behavior and decisions, a quality of context model was constructed. Based on the model a controlled online experiment was conducted in which physicians had to treat hypothetical cases while seeing inaccurate medication suggestions. Initial results indicate that raw information quality and cover rate significantly improve patient outcomes and reduce required time, whereas high misleadingness leads to poorer patient outcomes and more time being required.