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Variation in hospital mortality in an Australian neonatal intensive care unit network

Mohamed, Abdel-Latif; Nowak, Gen; Bajuk, Barbara; Glass, Kathryn; Harley, David

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Background: Studying centre-to-centre (CTC) variation in mortality rates is important because inferences about quality of care can be made permitting changes in practice to improve outcomes. However, comparisons between hospitals can be misleading unless there is adjustment for population characteristics and severity of illness. Objective: We sought to report the risk-adjusted CTC variation in mortality among preterm infants born <32 weeks and admitted to all eight tertiary neonatal intensive...[Show more]

dc.contributor.authorMohamed, Abdel-Latif
dc.contributor.authorNowak, Gen
dc.contributor.authorBajuk, Barbara
dc.contributor.authorGlass, Kathryn
dc.contributor.authorHarley, David
dc.date.accessioned2019-11-26T00:45:07Z
dc.date.available2019-11-26T00:45:07Z
dc.identifier.issn1359-2998
dc.identifier.urihttp://hdl.handle.net/1885/186644
dc.description.abstractBackground: Studying centre-to-centre (CTC) variation in mortality rates is important because inferences about quality of care can be made permitting changes in practice to improve outcomes. However, comparisons between hospitals can be misleading unless there is adjustment for population characteristics and severity of illness. Objective: We sought to report the risk-adjusted CTC variation in mortality among preterm infants born <32 weeks and admitted to all eight tertiary neonatal intensive care units (NICUs) in the New South Wales and the Australian Capital Territory Neonatal Network (NICUS), Australia. Methods: We analysed routinely collected prospective data for births between 2007 and 2014. Adjusted mortality rates for each NICU were produced using a multiple logistic regression model. Output from this model was used to construct funnel plots. Results: A total of 7212 live born infants <32 weeks gestation were admitted consecutively to network NICUs during the study period. NICUs differed in their patient populations and severity of illness. The overall unadjusted hospital mortality rate for the network was 7.9% (n=572 deaths). This varied from 5.3% in hospital E to 10.4% in hospital C. Adjusted mortality rates showed little CTC variation. No hospital reached the +99.8% control limit level on adjusted funnel plots. Conclusion: Characteristics of infants admitted to NICUs differ, and comparing unadjusted mortality rates should be avoided. Logistic regression-derived risk-adjusted mortality rates plotted on funnel plots provide a powerful visual graphical tool for presenting quality performance data. CTC variation is readily identified, permitting hospitals to appraise their practices and start timely intervention.
dc.format.mimetypeapplication/pdf
dc.language.isoen_AU
dc.publisherBMJ Publishing Group
dc.rights© Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018.
dc.rights.urihttp://creativecommons.org/ licenses/by-nc/4.0/
dc.sourceArchives of Disease in Childhood Fetal and Neonatal Edition
dc.titleVariation in hospital mortality in an Australian neonatal intensive care unit network
dc.typeJournal article
local.description.notesImported from ARIES
local.identifier.citationvolume103
dc.date.issued2017
local.identifier.absfor111403 - Paediatrics
local.identifier.ariespublicationu5369653xPUB183
local.publisher.urlhttps://www.biomedcentral.com/
local.type.statusPublished Version
local.contributor.affiliationMohamed, Abdel-Latif, College of Health and Medicine, ANU
local.contributor.affiliationNowak, Gen, College of Business and Economics, ANU
local.contributor.affiliationBajuk, Barbara, NSW Pregnancy and Newborn Services Network
local.contributor.affiliationGlass, Kathryn, College of Health and Medicine, ANU
local.contributor.affiliationHarley, David, College of Health and Medicine, ANU
local.bibliographicCitation.issue4
local.bibliographicCitation.startpageF331
local.bibliographicCitation.lastpageF336
local.identifier.doi10.1136/archdischild-2017-313222
local.identifier.absseo920501 - Child Health
dc.date.updated2019-05-19T08:23:42Z
local.identifier.scopusID2-s2.0-85049028283
dcterms.accessRightsOpen Access
dc.provenanceThis is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/ licenses/by-nc/4.0/ © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.
dc.rights.licenseCreative Commons Attribution Non Commercial (CC BY-NC 4.0) license
CollectionsANU Research Publications

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