DATA PRIVACY PRESERVING MODEL FOR HEALTH INFORMATION SYSTEM

ABSTRACT

Information systems are employed by organizations for the collection, filtering, processing, creation and distribution of data. In healthcare delivery, patients are required to share information with certain categories of health personnel to facilitate correct diagnosis and to determine appropriate treatment. There have been cases of unauthorized access to patient information by health personnel. Some of these personnel eventually cause great harm to the patient by divulging sensitive information. The existing Data Privacy Preservation (DPP) models are designed for Clinical Decision Support Systems with inadequate information available for DPP in Health Information Systems (HIS) in Nigeria. This research, therefore focused on the development of a model for Data Privacy Preservation (DPP) in HIS to address this inadequacy.

A model for DPP in HIS was developed using the iterative design technique. The model developed comprises a local database that contains the health information of patients, the Random Forest Decision Tree (RFDT) algorithm, an attribute blocking module that employs the RFDT algorithm, an attribute unblocking module which also uses the RFDT algorithm and a module for the computation of time elapsed in unblocking attributes. Mandatory Role-based Access Control was used to restrict the access health professionals have to patient data; each category of health worker can only view the attribute(s) needed for them to provide the service required to fulfill their role. An application based on the RFDT algorithm, was developed to instantiate the model following the Waterfall Software Development Life Cycle. Javascript and React.JS constitute the programming environment