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

Alireza Rahimi, Nandan Parameswaran, Pradeep Kumar Ray, Jane Taggart, Hairong Yu and Siaw-Teng Liaw
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Alireza Rahimi: UNSW School of Public Health and Community Medicine, Sydney, Australia & Isfahan University of Medical Sciences, Health information Technology Research Centre, Iran & UNSW Asia-Pacific ubiquitous Healthcare Research Centre, Sydney, Australia & SWSLHD General Practice Unit, Sydney, Australia
Nandan Parameswaran: UNSW, School of Computer Science and Engineering, Sydney, Australia & UNSW Asia-Pacific ubiquitous Healthcare Research Centre, Sydney, Australia
Pradeep Kumar Ray: UNSW, Asia-Pacific Ubiquitous Healthcare Research Centre, Sydney, Australia & UNSW, Australian School of Business, Sydney, Australia
Jane Taggart: UNSW, Centre for Primary Health Care & Equity, Sydney, Australia & SWSLHD General Practice Unit, Fairfield, Sydney, Australia
Hairong Yu: UNSW, Centre for Primary Health Care and Equity, Sydney, Australia
Siaw-Teng Liaw: UNSW, School of Public Health and Community Medicine, Sydney & UNSW, Centre for Primary Health Care and Equity, Sydney, Australia & UNSW, Asia-Pacific Ubiquitous Healthcare Research Centre, Sydney, Australia & SWSLHD General Practice Unit, Sydney, Australia

International Journal of E-Health and Medical Communications (IJEHMC), 2014, vol. 5, issue 3, 58-77

Abstract: 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.

Date: 2014
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