Development of a Theoretical Framework to Investigate Alignment of Big Data in Healthcare through a Social Representation Lens

The aim of this paper is to develop a theoretical framework grounded in the literature, which can be used to explore the influence of big data on business-IT alignment in the healthcare context. Increasingly the availability of information systems in healthcare delivery and service management result...

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Main Authors: Kasuni Weerasinghe, David Pauleen, Shane Scahill, Nazim Taskin
Format: Article
Language:English
Published: Australasian Association for Information Systems 2018-01-01
Series:Australasian Journal of Information Systems
Subjects:
Online Access:http://journal.acs.org.au/index.php/ajis/article/view/1617
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spelling doaj-fc021deb8b8843d583a52e49f8493ed82021-08-02T05:45:51ZengAustralasian Association for Information SystemsAustralasian Journal of Information Systems1449-86181449-86182018-01-0122010.3127/ajis.v22i0.1617661Development of a Theoretical Framework to Investigate Alignment of Big Data in Healthcare through a Social Representation LensKasuni Weerasinghe0David Pauleen1Shane Scahill2Nazim Taskin3Massey UniversityMassey UniversityMassey UniversityMassey UniversityThe aim of this paper is to develop a theoretical framework grounded in the literature, which can be used to explore the influence of big data on business-IT alignment in the healthcare context. Increasingly the availability of information systems in healthcare delivery and service management results in massive amounts of complex data that have the 3V characteristics of big data (i.e. volume, variety, velocity). Use of big-healthcare-data has been identified as bringing significant benefits to the healthcare sector from improved decision making through to population health analysis. Although the technical dynamics around big data such as analytics and infrastructure requirements are extensively researched, less attention has been given to social dynamics such as peoples’ experience, understanding and perceived usefulness of this data. To address this gap, the paper uses social representation theory as a methodological lens to develop a theoretical framework to study the social dynamics around big data and its use in the healthcare context. The selected case for this development is the New Zealand healthcare sector and an approach using multi-level macro, meso, and micro analysis is taken. Use of social representation theory as a methodological lens to develop a theoretical framework is a novel approach. Such a theoretical framework will be useful as a foundation for carrying out on-going empirical research on big data to understand its influence on business-IT alignment in the healthcare context.http://journal.acs.org.au/index.php/ajis/article/view/1617big datahealthcarebusiness-IT alignmentsocial representation theoryNew Zealand healthcarehealthcare information systems
collection DOAJ
language English
format Article
sources DOAJ
author Kasuni Weerasinghe
David Pauleen
Shane Scahill
Nazim Taskin
spellingShingle Kasuni Weerasinghe
David Pauleen
Shane Scahill
Nazim Taskin
Development of a Theoretical Framework to Investigate Alignment of Big Data in Healthcare through a Social Representation Lens
Australasian Journal of Information Systems
big data
healthcare
business-IT alignment
social representation theory
New Zealand healthcare
healthcare information systems
author_facet Kasuni Weerasinghe
David Pauleen
Shane Scahill
Nazim Taskin
author_sort Kasuni Weerasinghe
title Development of a Theoretical Framework to Investigate Alignment of Big Data in Healthcare through a Social Representation Lens
title_short Development of a Theoretical Framework to Investigate Alignment of Big Data in Healthcare through a Social Representation Lens
title_full Development of a Theoretical Framework to Investigate Alignment of Big Data in Healthcare through a Social Representation Lens
title_fullStr Development of a Theoretical Framework to Investigate Alignment of Big Data in Healthcare through a Social Representation Lens
title_full_unstemmed Development of a Theoretical Framework to Investigate Alignment of Big Data in Healthcare through a Social Representation Lens
title_sort development of a theoretical framework to investigate alignment of big data in healthcare through a social representation lens
publisher Australasian Association for Information Systems
series Australasian Journal of Information Systems
issn 1449-8618
1449-8618
publishDate 2018-01-01
description The aim of this paper is to develop a theoretical framework grounded in the literature, which can be used to explore the influence of big data on business-IT alignment in the healthcare context. Increasingly the availability of information systems in healthcare delivery and service management results in massive amounts of complex data that have the 3V characteristics of big data (i.e. volume, variety, velocity). Use of big-healthcare-data has been identified as bringing significant benefits to the healthcare sector from improved decision making through to population health analysis. Although the technical dynamics around big data such as analytics and infrastructure requirements are extensively researched, less attention has been given to social dynamics such as peoples’ experience, understanding and perceived usefulness of this data. To address this gap, the paper uses social representation theory as a methodological lens to develop a theoretical framework to study the social dynamics around big data and its use in the healthcare context. The selected case for this development is the New Zealand healthcare sector and an approach using multi-level macro, meso, and micro analysis is taken. Use of social representation theory as a methodological lens to develop a theoretical framework is a novel approach. Such a theoretical framework will be useful as a foundation for carrying out on-going empirical research on big data to understand its influence on business-IT alignment in the healthcare context.
topic big data
healthcare
business-IT alignment
social representation theory
New Zealand healthcare
healthcare information systems
url http://journal.acs.org.au/index.php/ajis/article/view/1617
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AT davidpauleen developmentofatheoreticalframeworktoinvestigatealignmentofbigdatainhealthcarethroughasocialrepresentationlens
AT shanescahill developmentofatheoreticalframeworktoinvestigatealignmentofbigdatainhealthcarethroughasocialrepresentationlens
AT nazimtaskin developmentofatheoreticalframeworktoinvestigatealignmentofbigdatainhealthcarethroughasocialrepresentationlens
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