Taming the Data Quality Dragon--A Theory and Method for Data Quality by Design.
A lack of data quality (DQ) is often a significant inhibitor impeding the realization of cost and quality benefits expected from Clinical Information Systems (CIS). Attaining and sustaining DQ in CIS has been a multi-faceted and elusive goal. The current literature on DQ in health informatics mainly consists of empirical studies and practitioners' reports, but often lack a holistic approach to addressing DQ 'by design'. This paper seeks to present a general framework for clinical DQ, which blends foundational engineering theories with concepts and methods from health informatics. We define an architectural viewpoint for designing and reasoning about DQ. We introduce the notion of DQ Probes for monitoring and assuring DQ during system operation. The concepts presented have been validated in a real-world case study.
Department of Computer Science, University of Victoria, Victoria, BC, Canada.
Jens H
JH
Weber
Department of Computer Science, University of Victoria, Victoria, BC, Canada.
Morgan
M
Price
Department of Family Practice, University of British Columbia, Vancouver, BC, Canada.
Iryna
I
Davies
D000068598:Data Accuracy; D063005:Health Information Systems / Q000458:organization & administration / Q000592:standards*; D006801:Humans; D008962:Models, Theoretical; D012985:Software Design