Semantic Integration of Patient Data for Clinical Decision Support in Breast Cancer Care

Abstract

Achieving semantic interoperability between heterogeneous healthcare systems and integrating clinical guidelines in the automatic decision support of healthcare institutions are two key priorities of current medical informatics. They can lead to a significant improvement on patient safety by reducing medical risks and delays in diagnosis, facilitating continuity of care and preventing life threatening adverse events. The present chapter describes a project that addresses those two priorities in the field of Breast Cancer for which effective clinical guidelines are available, as well as the clinical data to apply them. However, the deployment of semantic interoperability techniques based on clinical terminologies such as SNOMED-CT and EHR exchange models such as openEHR and HL7 is required to meaningfully combine the available data. Then data mining techniques are capable of automatically adapting the parameters of clinical guidelines to the particular conditions of each healthcare environment.