The increasing amount of freely available health-related web content generates, on one hand, excellent conditions for self-education of patients as well as physicians, but on the other hand entails substantial risks if such information is trusted irrespective of low competence or even bad intentions of its authors. This is why medical web resources accreditation by renowned authorities is of high importance. However, various health web content surveys show that the proportion of accredited web resources is insufficient due to the difficulty of the labeling authorities to cope with the amount and dynamics of the medical web. In this paper, we address the problem of automating the accreditation of medical web content. To this end, we present a system which provides the infrastructure and the means to organize and support various aspects of the daily work of labeling experts, exploiting web content collection and information extraction techniques.