Knowledge Discovery from Healthcare Electronic Records for Sustainable Environment

The medical history of a patient is an essential piece information in healthcare agencies, which keep records patients. Due to the fact that each person may have different complications, data remain sparse, high-dimensional and possibly inconsistent. knowledge discovery from such not easily manageable for behaviors. It becomes challenge both physicians agencies discover many electronic records. Data mining, as evidenced existing published literature, has proven its effectiveness transforming large collections into meaningful knowledge. This paper proposes overview mining techniques used Furthermore, based on real data, this also demonstrates case study discovering with help three techniques: (1) association analysis; (2) sequential pattern mining; (3) clustering. Particularly, analysis extract frequent correlations among examinations done by patients specific disease, allows extracting patterns events clustering find groups similar discovered enrich guidelines, improve their processes detect anomalous patients’ behavior respect guidelines.