Towards a Secure Semantic Knowledge of Healthcare Data Through Structural Ontological Transformations

Abstract

Current devices and sensors have revolutionized our daily lives, with the healthcare domain exploring and adapting new technologies, promising high quality of care. The diversity of healthcare data is leading to the independent operation of the latter, whilst the value emerging from their exploitation is limited. Most of the data is confined in data silos, without meeting the requirements of standards, and secure data exchange. Healthcare systems need to be able to communicate and exchange data anonymously, for better understanding about the results of prevention strategies, diseases, and efficiency of patient pathway management. Since healthcare interoperability is the only sustainable way to address these constraints, several techniques have been developed but they are partially applicable, rising the needs of a generic solution. The increased use of Electronic Health Records (EHRs) requires ontologies to capture domain knowledge, providing the basis for agreement within the healthcare domain. This manuscript focuses on the semantic interoperability of multiple EHRs – and their standards, proposing a way for primarily anonymizing the personal data stored into the EHRs, and then transforming the EHR datasets into XML Syntactic Models, for getting their semantic knowledge through their ontological representation.