Data Mining Infrastructure to Characterize Medically Unexplained Symptoms

War-related syndromes have existed throughout modern wars; however, studies to-date have not provided evidence to point to a specific group of symptoms and their causes. Nevertheless, these studies have confirmed increased rates of reported symptoms andgeneral deterioration of perceived health by war veterans. Military health care systems today offer unique opportunities in monitoring and predicting health-related events of military personnel. A closer investigation of war-related symptoms is warrantedto evaluate the adequacy of the information collected and the analytical approaches employed.A data mining infrastructure can facilitate (i) collection of specific fields not previously gathered, and (ii) avoid forced entry of data fields from field personnel that are not relevant. Existing biosurveillance systems are well suited for counts-basedanalyses and efficient data collection. They do not offer analytical techniques to visualize dependencies between known and unexplained symptoms. New approaches in assessing information content will allow examination of syndromes and their associationswith medical and non-medical inputs. Further efforts can then refine the architecture and apply a suite of analyses to provide decision management tools. The availability of such a system can not only leverage health care data for disease modeling butalso enable timely response management.