Predicting clinicians’ intentions towards the electronic health record (EHR) : an extended UTAUT model

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dc.contributor.advisor Marks, Jonathan
dc.contributor.postgraduate Johnson, Robyn
dc.date.accessioned 2020-07-15T13:09:11Z
dc.date.available 2020-07-15T13:09:11Z
dc.date.created 2020/09/30
dc.date.issued 2020
dc.description Mini Dissertation (MBA)--University of Pretoria, 2020.
dc.description.abstract The Electronic Health Record (EHR) has the potential to promote understanding or awareness of healthcare knowledge among patients and healthcare providers to facilitate collaboration between various key stakeholders to improve the quality of healthcare. The technology is also expected to provide global health communities with benefits, from improved health outcomes, reduced medical errors, and a reduction in healthcare expenditure. These benefits will not be realised unless the key stakeholders and consumers of the technology are willing to accept, adopt, and use the EHR. The purpose of this study is to identify crucial factors influencing clinicians’ adoption of the EHR in South Africa’s healthcare system by expanding the Unified Theory of Acceptance and Use of Technology (UTAUT) model to include the additional constructs Resistance to Change and Attitude Towards Organisational Change. A cross-sectional online questionnaire was used to gather data from 168 clinicians employed at various private and public healthcare facilities across South Africa. Performance expectancy and facilitating conditions were found to have a statistically significant positive impact on clinicians’ behavioural intention, whereas effort expectancy and social influence had no similar result. Resistance to change had a statistically significant negative influence on behavioural intention, and a negative attitude towards organisational change positively influenced resistance to change. The findings of this study can be used by government bodies, the private sector and technology vendors to better understand clinicians’ perceptions of the EHR in order to guide policy and effect implementation strategies accordingly.
dc.description.availability Unrestricted
dc.description.degree MBA
dc.description.department Gordon Institute of Business Science (GIBS)
dc.identifier.citation Johnson, R 2020, Predicting clinicians’ intentions towards the electronic health record (EHR) : an extended UTAUT model, MBA Mini Dissertation, University of Pretoria, Pretoria, viewed yymmdd <http://hdl.handle.net/2263/75255>
dc.identifier.uri http://hdl.handle.net/2263/75255
dc.language.iso en
dc.publisher University of Pretoria
dc.rights © 2020 University of Pretoria. All rights reserved. The copyright in this work vests in the University of Pretoria. No part of this work may be reproduced or transmitted in any form or by any means, without the prior written permission of the University of Pretoria.
dc.subject UCTD
dc.title Predicting clinicians’ intentions towards the electronic health record (EHR) : an extended UTAUT model
dc.type Mini Dissertation


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