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Designing highly reliable adverse-event detection systems to predict subsequent claims.
May 6, 2015
Helmchen LA, Burke ME, Wojtusiak J. J Healthc Risk Manag. 2015;34(4):7-17.
Efforts to increase incident reporting may lead to reporting of events that do not have risk for subsequent litigation. This study demonstrated that modeling based on automated data mining of event reports could identify reports that were most likely to be associated with subsequent malpractice claims. This suggests that actions to address adverse events, such as disclosure programs, could be deployed more efficiently using an automated algorithm to detect high-risk event reports in real time.
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