Analisi di rete basata sul modello matematico dei grafi, sperimentazione nell'ambito del progetto BINET

The research activity carried out in BINET project aims at designing a Business Intelligence framework based on Social Network technology, better known as Complex Networks in the healthcare field, in order to establish a platform to analyze data through non-conventional graph methodologies and interfaces (graph data-browsing). Scientific validation of methodologies used by the framework is carried out in the healthcare field and focuses on the analysis of therapeutic, time and spatial associations among the various treatments, such as outpatient, drug prescriptions, length of hospital stays etc., received by the patients recruited for the study, to find out correlations between treatments at the individual level and enabling patient "follow-up". Another aspect of the validation concerns the analysis of papers extracted from epidemiological and clinical databases in order to identify emerging technologies, standard of care, "benchmarking" among various operational units dealing with the same pathologies, as well as population profiling to enable identification of homogeneous groups, from a socio-demographic point of view and healthcare demand, subject to tailored prevention campaigns. A more specific application deals with the analysis of drug prescriptions to find out correlations between patient pathology profiles (derived from all treatments and diagnosis received by patients) and prescriptive behaviors of their general practitioners in order to define shared "guidelines" and identify standard practices to compare with practice guidelines. The document describe some sperimentation in these area.