Providing Security to Health Care Systems based on CRISP-DM

Abstract

All the health data are considered to be the personal private data and those data should need security. Like confidentiality, integrity, authority should be preserved in the case of medical data. Nowadays, there is no framework for health supporting the data modeling design, i.e. the existing models are generic and therefore are not suitable to support personalized systems and they do not consider the quality of clinical and personal data, required in health care. Based on the CRISP-DM methodology, a framework is proposed to design a data model for personalized health systems. This framework ensures the security of personal and clinical data to relate it with health standards, particularly with the Personal Health (PHR) ISO/TR 14292 standard, which addresses the recommendations of the parameters that must be within a personalized health system. To perform accurate recommendations it is important to make a data mining process, data mining is the process of analyzing the data from different perspective and summarizing it into useful information.