Towards an Application Helping to Minimize Medication Error Rate

Alharbi, AI; Gay, V; AlGhamdi, MJ; Alturki, R; Alyamani, HJ

Towards an Application Helping to Minimize Medication Error Rate

Alharbi, AI Gay, V

AlGhamdi, MJ Alturki, R Alyamani, HJ

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Publisher:: Hindawi
Publication Type:: Journal Article
Citation:: Mobile Information Systems, 2021, 2021, pp. 1-7
Issue Date:: 2021-06-28

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Field	Value	Language
dc.contributor.author	Alharbi, AI
dc.contributor.author	Gay, V https://orcid.org/0000-0002-4301-1995
dc.contributor.author	AlGhamdi, MJ
dc.contributor.author	Alturki, R
dc.contributor.author	Alyamani, HJ
dc.date.accessioned	2022-03-16T04:24:39Z
dc.date.available	2022-03-16T04:24:39Z
dc.date.issued	2021-06-28
dc.identifier.citation	Mobile Information Systems, 2021, 2021, pp. 1-7
dc.identifier.issn	1574-017X
dc.identifier.issn	1875-905X
dc.identifier.uri	http://hdl.handle.net/10453/155254
dc.description.abstract	Medication errors related to medication administration done by both doctors and nurses can be considered a vital issue around the world. It is believed that systematisation and the introduction of main documents are done manually, which might increase the opportunities to have inaccuracies and errors because of unexpected wrong actions done by medical practitioners. Experts stated that the lack of pharmacological knowledge is one of the key factors, which play an important role in causing such errors. Doctors and nurses may face problems when they move from one unit to another and the medication administration list has changed. However, promoting public health activities and recent AI-enabled applications can provide general information about medication that helps both doctors and nurses administer the right medication. However, such an application can require a lot of time and effort to search and then find a medication. Therefore, this article aims to investigate whether AI-enabled applications can help avoid or at least minimize medication error rates.
dc.language	English
dc.publisher	Hindawi
dc.relation.ispartof	Mobile Information Systems
dc.relation.isbasedon	10.1155/2021/9221005
dc.rights	info:eu-repo/semantics/openAccess
dc.subject	0805 Distributed Computing, 0806 Information Systems
dc.subject.classification	Information Systems
dc.title	Towards an Application Helping to Minimize Medication Error Rate
dc.type	Journal Article
utslib.citation.volume	2021
utslib.for	0805 Distributed Computing
utslib.for	0806 Information Systems
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Strength - CHT - Health Technologies
pubs.organisational-group	/University of Technology Sydney/Strength - INEXT - Innovation in IT Services and Applications
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Electrical and Data Engineering
pubs.organisational-group	/University of Technology Sydney/Centre for Health Technologies (CHT)
utslib.copyright.status	open_access	*
pubs.consider-herdc	false
dc.date.updated	2022-03-16T04:24:37Z
pubs.publication-status	Published
pubs.volume	2021

Abstract:

Medication errors related to medication administration done by both doctors and nurses can be considered a vital issue around the world. It is believed that systematisation and the introduction of main documents are done manually, which might increase the opportunities to have inaccuracies and errors because of unexpected wrong actions done by medical practitioners. Experts stated that the lack of pharmacological knowledge is one of the key factors, which play an important role in causing such errors. Doctors and nurses may face problems when they move from one unit to another and the medication administration list has changed. However, promoting public health activities and recent AI-enabled applications can provide general information about medication that helps both doctors and nurses administer the right medication. However, such an application can require a lot of time and effort to search and then find a medication. Therefore, this article aims to investigate whether AI-enabled applications can help avoid or at least minimize medication error rates.

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http://hdl.handle.net/10453/155254