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

Abdel-Latif, Mohamed E., Adegboye, Oyelola, Nowak, Gen, Elfaki, Faiz, Bajuk, Barbara, Glass, Kathryn, and Harley, David (2023) Variation in hospital morbidities in an Australian neonatal intensive care unit network. Archives of Disease in Childhood: fetal and neonatal. (In Press)

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Objective: There is an expectation among the public and within the profession that the performance and outcome of neonatal intensive care units (NICUs) should be comparable between centres with a similar setting. This study aims to benchmark and audit performance variation in a regional Australian network of eight NICUs.

Design: Cohort study using prospectively collected data.

SettingL All eight perinatal centres in New South Wales and the Australian Capital Territory, Australia.

Patients: All live-born infants born between 23+0 and 31+6 weeks gestation admitted to one of the tertiary perinatal centres from 2007 to 2020 (n=12 608).

Main outcome measures: Early and late confirmed sepsis, intraventricular haemorrhage, medically and surgically treated patent ductus arteriosus, chronic lung disease (CLD), postnatal steroid for CLD, necrotising enterocolitis, retinopathy of prematurity (ROP), surgery for ROP, hospital mortality and home oxygen.

Results: NICUs showed variations in maternal and neonatal characteristics and resources. The unadjusted funnel plots for neonatal outcomes showed apparent variation with multiple centres outside the 99.8% control limits of the network values. The hierarchical model-based risk-adjustment accounting for differences in patient characteristics showed that discharged home with oxygen is the only outcome above the 99.8% control limits.

Conclusions: Hierarchical model-based risk-adjusted estimates of morbidity rates plotted on funnel plots provide a robust and straightforward visual graphical tool for presenting variations in outcome performance to detect aberrations in healthcare delivery and guide timely intervention. We propose using hierarchical model-based risk adjustment and funnel plots in real or near real-time to detect aberrations and start timely intervention.

Item ID: 77186
Item Type: Article (Research - C1)
ISSN: 1468-2052
Copyright Information: © Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.
Date Deposited: 09 Feb 2023 03:57
FoR Codes: 42 HEALTH SCIENCES > 4206 Public health > 420602 Health equity @ 50%
49 MATHEMATICAL SCIENCES > 4905 Statistics > 490502 Biostatistics @ 50%
SEO Codes: 20 HEALTH > 2002 Evaluation of health and support services > 200202 Evaluation of health outcomes @ 100%
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