S Todd1,2,3, J Bowen1,2,4, I Ibiebele1,2, J Patterson1,2, S Torvaldsen1,2,5, F Ford1,2, M Nippita1,2,6, J Morris1,2,6, D Randall1,2. 1. The University of Sydney Northern Clinical School, Women and Babies Research, St Leonards, NSW 2065, Australia. 2. Northern Sydney Local Health District, Kolling Institute, St Leonards, NSW 2065, Australia. 3. NSW Biostatistics Training Program, NSW Ministry of Health, St Leonards, NSW 2065, Australia. 4. Department of Neonatology, Royal North Shore Hospital, St Leonards, NSW 2065, Australia. 5. School of Public Health and Community Medicine, University of New South Wales, NSW 2033, Australia. 6. Department of Obstetrics and Gynaecology, Royal North Shore Hospital, St Leonards, NSW 2065, Australia.
Abstract
INTRODUCTION: Severe morbidity rates in neonates can be estimated using diagnosis and procedure coding in linked routinely collected retrospective data as a cost-effective way to monitor quality and safety of perinatal services. Coding changes necessitate an update to the previously published composite neonatal adverse outcome indicator for identifying infants with severe or medically significant morbidity. OBJECTIVES: To update the neonatal adverse outcome indicator for identifying neonates with severe or medically significant morbidity, and to investigate the validity of the updated indicator. METHODS: We audited diagnosis and procedure codes and used expert clinician input to update the components of the indicator. We used linked birth, hospital and death data for neonates born alive at 24 weeks or more in New South Wales, Australia (2002-2014) to describe the incidence of neonatal morbidity and assess the validity of the updated indicator. RESULTS: The updated indicator included 28 diagnostic and procedure components. In our population of 1,194,681 live births, 5.44% neonates had some form of morbidity. The rate of morbidity was greater for higher-risk pregnancies and was lowest for those born at 39-40 weeks' gestation. Incidence increased over the study period for overall neonatal morbidity, and for individual components: intravenous infusion, respiratory diagnoses, and non-invasive ventilation. Severe or medically significant neonatal morbidity was associated with double the risk of hospital readmission and 10 times the risk of death within the first year of life. CONCLUSION: The updated composite indicator has maintained concurrent and predictive validity and is a standardised, economic way to measure neonatal morbidity when using population-based data. Changes within individual components should be considered when examining longitudinal data.
INTRODUCTION: Severe morbidity rates in neonates can be estimated using diagnosis and procedure coding in linked routinely collected retrospective data as a cost-effective way to monitor quality and safety of perinatal services. Coding changes necessitate an update to the previously published composite neonatal adverse outcome indicator for identifying infants with severe or medically significant morbidity. OBJECTIVES: To update the neonatal adverse outcome indicator for identifying neonates with severe or medically significant morbidity, and to investigate the validity of the updated indicator. METHODS: We audited diagnosis and procedure codes and used expert clinician input to update the components of the indicator. We used linked birth, hospital and death data for neonates born alive at 24 weeks or more in New South Wales, Australia (2002-2014) to describe the incidence of neonatal morbidity and assess the validity of the updated indicator. RESULTS: The updated indicator included 28 diagnostic and procedure components. In our population of 1,194,681 live births, 5.44% neonates had some form of morbidity. The rate of morbidity was greater for higher-risk pregnancies and was lowest for those born at 39-40 weeks' gestation. Incidence increased over the study period for overall neonatal morbidity, and for individual components: intravenous infusion, respiratory diagnoses, and non-invasive ventilation. Severe or medically significant neonatal morbidity was associated with double the risk of hospital readmission and 10 times the risk of death within the first year of life. CONCLUSION: The updated composite indicator has maintained concurrent and predictive validity and is a standardised, economic way to measure neonatal morbidity when using population-based data. Changes within individual components should be considered when examining longitudinal data.
Authors: Margaret E Harpham; Charles S Algert; Christine L Roberts; Jane B Ford; Antonia W Shand Journal: Aust N Z J Obstet Gynaecol Date: 2017-05-16 Impact factor: 2.100
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Authors: Fiona Cheong-See; Ewoud Schuit; David Arroyo-Manzano; Asma Khalil; Jon Barrett; K S Joseph; Elizabeth Asztalos; Karien Hack; Liesbeth Lewi; Arianne Lim; Sophie Liem; Jane E Norman; John Morrison; C Andrew Combs; Thomas J Garite; Kimberly Maurel; Vicente Serra; Alfredo Perales; Line Rode; Katharina Worda; Anwar Nassar; Mona Aboulghar; Dwight Rouse; Elizabeth Thom; Fionnuala Breathnach; Soichiro Nakayama; Francesca Maria Russo; Julian N Robinson; Jodie M Dodd; Roger B Newman; Sohinee Bhattacharya; Selphee Tang; Ben Willem J Mol; Javier Zamora; Basky Thilaganathan; Shakila Thangaratinam Journal: BMJ Date: 2016-09-06
Authors: Hannah Ellin Knight; Sam J Oddie; Katie L Harron; Harriet K Aughey; Jan H van der Meulen; Ipek Gurol-Urganci; David A Cromwell Journal: Arch Dis Child Fetal Neonatal Ed Date: 2018-11-28 Impact factor: 5.747