A Predictive Model for Identifying Health Trends Among Māori and Pacific People – Analysis From Ten Years of New Zealand Public Hospital Discharges
aut.filerelease.date | 2022-05-16 | |
aut.relation.endpage | 190 | |
aut.relation.issue | 3 | en_NZ |
aut.relation.journal | International Journal of Medical Engineering and Informatics | en_NZ |
aut.relation.startpage | 190 | |
aut.relation.volume | 13 | en_NZ |
aut.researcher | Mirza, Farhaan | |
dc.contributor.author | Wang, S | en_NZ |
dc.contributor.author | Mirza, F | en_NZ |
dc.contributor.author | Baig, MM | en_NZ |
dc.date.accessioned | 2021-09-16T02:45:41Z | |
dc.date.available | 2021-09-16T02:45:41Z | |
dc.date.copyright | 2021 | en_NZ |
dc.date.issued | 2021 | en_NZ |
dc.description.abstract | Our 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.identifier.citation | International Journal of Medical Engineering and Informatics (IJMEI), Vol. 13, No. 3, 2021 | |
dc.identifier.doi | 10.1504/ijmei.2021.114886 | en_NZ |
dc.identifier.issn | 1755-0653 | en_NZ |
dc.identifier.issn | 1755-0661 | en_NZ |
dc.identifier.uri | https://hdl.handle.net/10292/14514 | |
dc.language | en | en_NZ |
dc.publisher | Inderscience Publishers | en_NZ |
dc.relation.uri | http://www.inderscience.com/offer.php?id=114886 | |
dc.rights | Copyright © 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.rights.accessrights | OpenAccess | en_NZ |
dc.subject | Predictive model; Hospital discharges; Machine learning model; Data analysis; Machine learning; Predictive analysis; Healthcare delivery; Disease prediction; Operative procedures; Māori Population and Pacific Islanders | |
dc.title | A Predictive Model for Identifying Health Trends Among Māori and Pacific People – Analysis From Ten Years of New Zealand Public Hospital Discharges | en_NZ |
dc.type | Journal Article | |
pubs.elements-id | 430509 | |
pubs.organisational-data | /AUT | |
pubs.organisational-data | /AUT/Faculty of Design & Creative Technologies | |
pubs.organisational-data | /AUT/Faculty of Design & Creative Technologies/School of Engineering, Computer & Mathematical Sciences | |
pubs.organisational-data | /AUT/PBRF | |
pubs.organisational-data | /AUT/PBRF/PBRF Design and Creative Technologies | |
pubs.organisational-data | /AUT/PBRF/PBRF Design and Creative Technologies/PBRF ECMS |
Files
License bundle
1 - 1 of 1
Loading...
- Name:
- AUT Grant of Licence for Tuwhera Aug 2018.pdf
- Size:
- 276.29 KB
- Format:
- Adobe Portable Document Format
- Description: