Geoanalysis of clinical diagnosis and biological analytes

Biological laboratories hosted in health structures manage biochemical analytes (such as glycemia, bilirubin, cholesterol) as infor- mation useful for patients’ clinical treatments. Often biological analyses follow standard protocols such as repetition frequency, outcomes and are considered as input for diagnosis or medical treatment definition. Health codes are included in Electronic Medical Records (EMRs) to summarize patient health status and to support administrative information. In this paper we analyse diagnosis codes extracted from EMRs and bio- chemical analytes of a set of biological analysis on a set of hospitalized patients during one observation year. We cross reference data by using a semantic-based clustering procedure, extract information from EMRs and then cluster them looking for similar patterns of diseases. Finally, biological data are related to diagnosis codes and analyzed towards ar- eas of interest in order to map calculated outliers patients. Health codes are included in Electronic Medical Records to summarize patient health status and to support administrative information. Well defined protocols guide the bio-analytes studies on hospitalized patients, but few correla- tions with EMRs are usually known.