Theoretical support for enhancing data quality: Application in electronic medical records

Liu, C; Talaei-Khoei, A; Zowghi, D

Theoretical support for enhancing data quality: Application in electronic medical records

Liu, C

Talaei-Khoei, A Zowghi, D

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Publication Type:: Conference Proceeding
Citation:: Americas Conference on Information Systems 2018: Digital Disruption, AMCIS 2018, 2018
Issue Date:: 2018-01-01

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Field	Value	Language
dc.contributor.author	Liu, C https://orcid.org/0000-0002-9641-4712	en_US
dc.contributor.author	Talaei-Khoei, A	en_US
dc.contributor.author	Zowghi, D https://orcid.org/0000-0002-6051-0155	en_US
dc.date.issued	2018-01-01	en_US
dc.identifier.citation	Americas Conference on Information Systems 2018: Digital Disruption, AMCIS 2018, 2018	en_US
dc.identifier.isbn	9780996683166	en_US
dc.identifier.uri	http://hdl.handle.net/10453/127508
dc.description.abstract	© 2018 Association for Information Systems. All rights reserved. This paper aims at reviewing the existing theoretical support to enhance data quality and utilizing the findings of the review in the context of electronic medical records (EMRs). For this to happen, we first conducted a survey of publications that have a focus on an empirical investigation of factors influencing data quality in the conceptual models. By using a well-established taxonomy development method from the discipline of information systems, we then proposed 3 dimensions for studying factors influencing data quality and constructing the conceptual model for enhancing data quality: breadth, depth, and interaction, within 9 characteristics under different dimensions. Last, we compared related studies using the proposed dimensions and utilized the findings of the review in enhancing EMRs quality to disclose the limitations and possibilities of new areas for further study.	en_US
dc.relation.ispartof	Americas Conference on Information Systems 2018: Digital Disruption, AMCIS 2018	en_US
dc.title	Theoretical support for enhancing data quality: Application in electronic medical records	en_US
dc.type	Conference Proceeding
utslib.for	0803 Computer Software	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/DVC (Research)
pubs.organisational-group	/University of Technology Sydney/DVC (Research)/Graduate Research School
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Computer Science
pubs.organisational-group	/University of Technology Sydney/Strength - HCTD - Human Centred Technology Design
pubs.organisational-group	/University of Technology Sydney/Strength - STEM Education Futures
utslib.copyright.status	closed_access
pubs.publication-status	Published	en_US

Abstract:

© 2018 Association for Information Systems. All rights reserved. This paper aims at reviewing the existing theoretical support to enhance data quality and utilizing the findings of the review in the context of electronic medical records (EMRs). For this to happen, we first conducted a survey of publications that have a focus on an empirical investigation of factors influencing data quality in the conceptual models. By using a well-established taxonomy development method from the discipline of information systems, we then proposed 3 dimensions for studying factors influencing data quality and constructing the conceptual model for enhancing data quality: breadth, depth, and interaction, within 9 characteristics under different dimensions. Last, we compared related studies using the proposed dimensions and utilized the findings of the review in enhancing EMRs quality to disclose the limitations and possibilities of new areas for further study.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/127508