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Please use this identifier to cite or link to this item: http://hdl.handle.net/10525/4125

Title: Addressing Data Quality in Healthcare
Authors: Kaloyanova, Kalinka
Naydenova, Ina
Kovacheva, Zlatinka
Keywords: Data Quality
Data Quality Dimensions
Healthcare
Medical Records
Issue Date: 19-Aug-2021
Publisher: CEUR Workshop Proceedings
Citation: Kaloyanova, К., Naydenova, I., Kovacheva, Zl. Addressing Data Quality in Healthcare. Information Systems and Grid Technologies, ISGT 2021, CEUR Workshop Proceedings, 2933, 2021, 155-164
Series/Report no.: CEUR Workshop Proceedings, 2933;16
Abstract: Data quality is an important part of information processing, but its application in practice is often underestimated. The complexity of data quality management, especially in the case of big data, makes it difficult to work in different areas of application. Although medical records are a significant source of errors in most cases data quality assessment on medical data is partially performed. The presented data quality analysis and recommendations in this paper can help physicians and software developers to understand better data quality dimensions, identify gaps in quality assessment, and develop |own procedures and techniques that correspond to their specific use cases.
URI: http://hdl.handle.net/10525/4125
ISSN: 1613-0073
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