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dc.contributor.authorWang, Sen_NZ
dc.contributor.authorMirza, Fen_NZ
dc.contributor.authorBaig, MMen_NZ
dc.date.accessioned2021-09-16T02:45:41Z
dc.date.available2021-09-16T02:45:41Z
dc.date.copyright2021en_NZ
dc.identifier.citationInternational Journal of Medical Engineering and Informatics (IJMEI), Vol. 13, No. 3, 2021
dc.identifier.issn1755-0653en_NZ
dc.identifier.issn1755-0661en_NZ
dc.identifier.urihttp://hdl.handle.net/10292/14514
dc.description.abstractOur research was focused on the quality of healthcare services for Māori and Pacific Islanders. We used New Zealand (NZ) Public Hospital discharges data from 2005 to 2015 for our research. A prediction model has been developed to predict the trends for patients with a specific chronic disease, external injuries and operative procedures based on the previous/historic data. Initial exploration suggests that the service demand increased from 138,656 in 2005 to 163,386 in 2015. We successfully analysed the diseases with highest incidence rate and key characteristics of this group of patients. Our research concluded with a series of key findings on the disease types including injuries, procedures, and services.
dc.languageenen_NZ
dc.publisherInderscience Publishersen_NZ
dc.relation.urihttp://www.inderscience.com/offer.php?id=114886
dc.rightsCopyright © Inderscience Enterprises Ltd., 2021. Authors retain the right to place his/her pre-publication version of the work on a personal website or institutional repository for non commercial purposes. The definitive version was published in (see Citation). The original publication is available at (see Publisher's Version).
dc.subjectPredictive model; Hospital discharges; Machine learning model; Data analysis; Machine learning; Predictive analysis; Healthcare delivery; Disease prediction; Operative procedures; Māori Population and Pacific Islanders
dc.titleA Predictive Model for Identifying Health Trends Among Māori and Pacific People – Analysis From Ten Years of New Zealand Public Hospital Dischargesen_NZ
dc.typeJournal Article
dc.rights.accessrightsOpenAccessen_NZ
dc.identifier.doi10.1504/ijmei.2021.114886en_NZ
aut.relation.endpage190
aut.relation.issue3en_NZ
aut.relation.startpage190
aut.relation.volume13en_NZ
pubs.elements-id430509
aut.filerelease.date2022-05-16
aut.relation.journalInternational Journal of Medical Engineering and Informaticsen_NZ


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