Development of a Methodological Approach for Data Quality Ontology in Diabetes Management

The role of ontologies in chronic disease management and associated challenges such as defining data quality (DQ) and its specification is a current topic of interest. In domains such as Diabetes Management, a robust Data Quality Ontology (DQO) is required to support the automation of data extraction semantically from Electronic Health Record (EHR) and access and manage DQ, so that the data set is fit for purpose. A five steps strategy is proposed in this paper to create the DQO which captures the semantics of clinical data. It consists of: (1) Knowledge acquisition; (2) Conceptualization; (3) Semantic modeling; (4) Knowledge representation; and (5) Validation. The DQO was applied to the identification of patients with Type 2 Diabetes Mellitus (T2DM) in EHRs, which included an assessment of the DQ of the EHR. The five steps methodology is generalizable and reusable in other domains. Alireza Rahimi University of New South Wales, Australia & Isfahan University of Medical Sciences, Iran & SWSLHD General Practice Unit, Australia Nandan Parameswaran University of New South Wales, Australia Pradeep Kumar Ray University of New South Wales, Australia Jane Taggart University of New South Wales Australia, & SWSLHD General Practice Unit, Australia Hairong Yu University of New South Wales, Australia Siaw-Teng Liaw University of New South Wales, Australia & SWSLHD General Practice Unit, Australia