A composite neonatal adverse outcome indicator using population-based data: an update

Author:

Todd Stephanie,Bowen Jennifer,Ibiebele Ibinabo,Patterson Jillian,Torvaldson Siranda,Ford Jane,Nippita Tanya,Morris Jonathan,Randall Deborah

Abstract

Introduction Severe morbidity rates in neonates can be estimated using diagnosis and procedure coding in linked routinely collected 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 morbidity. Objectives To update the neonatal adverse outcome indicator for identifying neonates with severe 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 investigate the incidence of severe 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 relative risk of morbidity was greater for higher risk pregnancies and was lowest 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 neonatal morbidity was associated with double the risk of hospital readmission and ten times the risk of death within the first year of life. Conclusions 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.

Publisher

Swansea University

Subject

Information Systems and Management,Health Informatics,Information Systems,Demography

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