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

Mohamed E Abdel-Latif; Oyelola Adegboye; Gen Nowak; Faiz Elfaki; Barbara Bajuk; Kathryn Glass; David Harley

doi:10.1136/archdischild-2022-324940

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

Arch Dis Child Fetal Neonatal Ed. 2023 Jul;108(4):400-407. doi: 10.1136/archdischild-2022-324940. Epub 2023 Jan 2.

Authors

Mohamed E Abdel-Latif^{1

2

3}, Oyelola Adegboye^{4

5}, Gen Nowak⁶, Faiz Elfaki⁷, Barbara Bajuk⁸, Kathryn Glass⁹, David Harley^{9

10}

Affiliations

¹ Department of Neonatology, Centenary Hospital for Women and Children, Canberra Hospital, Garran, Canberra, ACT, Australia abdel-Latif.Mohamed@act.gov.au.
² Department of Public Health, College of Science Health and Engineering, La Trobe University, Bundoora, Melbourne, VIC, Australia.
³ Discipline of Neonatology, School of Medicine and Psychology, College of Health and Medicine, Australian National University, Acton, Canberra, ACT, Australia.
⁴ Public Health and Tropical Medicine, College of Public Health, Medical and Veterinary Sciences, James Cook University, Townsville, Queensland, Australia.
⁵ Australian Institute of Tropical Health and Medicine, James Cook University, Townsville, QLD, Australia.
⁶ Research School of Finance, Actuarial Studies, and Statistics, College of Business and Economics, Australian National University, Acton, Canberra, ACT, Australia.
⁷ Department of Mathematics, Physics, and Statistics, Qatar University, Doha, Qatar.
⁸ Critical Care Program, Sydney Children's Hospitals Network, Westmead, Sydney, NSW, Australia.
⁹ National Centre for Epidemiology and Population Health, Australian National University, Acton, Canberra, ACT, Australia.
¹⁰ University of Queensland Centre for Clinical Research (UQCCR), University of Queensland, Brisbane, QLD, Australia.

Abstract

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.

Setting: 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.

Keywords: Health services research; Intensive Care Units, Neonatal; Neonatology.

MeSH terms

Australia / epidemiology
Cohort Studies
Hospitals
Humans
Infant, Newborn
Infant, Premature
Intensive Care Units, Neonatal
Lung Diseases*
Oxygen
Retinopathy of Prematurity*

Substances

Oxygen