ArticleArchives of disease in childhood. Fetal and neonatal edition2018
Variation in hospital mortality in an Australian neonatal intensive care unit network.
Article in Archives of disease in childhood. Fetal and neonatal edition, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Article
- Neonatologist staffing is related to the inter-hospital variation of risk-adjusted mortality of very low birth weight infants in Korea.Scientific reports · 2024Article
- Variation in hospital morbidities in an Australian neonatal intensive care unit network.Archives of disease in childhood. Fetal and neonatal edition · 2023Article
- Exploring variation in quality of care and clinical outcomes between neonatal units: a novel use for the UK National Neonatal Audit Programme (NNAP).BMJ open quality · 2022Review
- Machine Learning Algorithms to Predict Mortality of Neonates on Mechanical Intubation for Respiratory Failure.Biomedicines · 2021Article
- Machine Learning Approaches to Predict In-Hospital Mortality among Neonates with Clinically Suspected Sepsis in the Neonatal Intensive Care Unit.Journal of personalized medicine · 2021Article
- Article
- A composite neonatal adverse outcome indicator using population-based data: an update.International journal of population data science · 2020Article
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundStudying 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.
objectiveWe 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.
methodsWe 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.
resultsA 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.
conclusionCharacteristics 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.
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