6906 How big is the gap? Creating a learning health system to assess inequities in hospital outcomes for Australian children from priority populations

Objectives Child health inequity in Australia is not being systematically addressed and is limiting children from achieving optimal health and wellbeing.¹ ² Closing the inequity gap in health outcomes for children and young people (CYP) from priority populations is critical.³ ⁴ We aimed to accurately quantify inequities in health outcomes for Australian CYP. Methods Design, setting: Analysis of prospective electronic medical record data from Sydney Children's Hospitals Network from 2015–2020. Participants: CYP from priority populations (Indigenous, Culturally and Linguistically Diverse, refugee/asylum seeking, Out of Home Care backgrounds and National Disability Insurance Scheme participants) aged 0–17 years. Main outcome measures: High acuity presentations, potentially preventable hospitalisations (PPH), chronic condition hospitalisations, Discharge against medical advice (DAMA), ward and critical care admission, 28-day readmission and extended length of stay (LOS). The cost of health inequity between priority and non-priority populations was calculated using mean inpatient hospital cost. Results Amongst 253,934 inpatient admissions and 446,924 Emergency Department (ED) attendances, priority population CYP comprised one third of all encounters. Compared to non-priority populations, priority population CYP had increased risk of PPH by 25% (relative risk [RR], 1.25; 95% confidence interval [CI], 1.23–1.27), chronic conditions by 9% (RR, 1.09; 95% CI, 1.07–1.10), DAMA by 33% (RR, 1.33; 95% CI, 1.19–1.49), ward admission by 16% (RR, 1.16; 95% CI 1.15–1.18), readmission by 48% (RR, 1.48; 95% CI, 1.42–1.53), extended inpatient LOS by 21% (RR, 1.21; 95% CI, 1.18–1.24) and ED LOS by 11% (RR, 1.11; 95% CI, 1.10–1.12). As an example of cumulative risk, Indigenous CYP living with a disability had a 239-fold increased risk of readmission compared to CYP without these risk factors (RR, 3.39; 95% CI, 2.92–3.93). Our study estimated the potential cost of health inequity at SCHN over five years. The cost of health inequity between priority and non-priority populations was more than $AUD107 million. Conclusion Inequity in health outcomes in children and young people from priority populations persists and can be quantified using routine data within a learning health system that focuses on equity. Urgent interventions are required to reduce inequities in health outcomes for children from priority populations. Routinely collected data from hospital systems can form the foundation of a learning health system. This enables real-time evaluation of health system interventions driven by consumer and designed to reduce child health disparities in priority populations. References Singer R, Zwi K, Menzies R. Predictors of in-hospital mortality in aboriginal children admitted to a tertiary paediatric hospital. Int J Environ Res Public Health. 2019 May 29;16(11):1893. Joshua P, Zwi K, Moran P, White L. Prioritising vulnerable children: why should we address inequity? Child Care Health Dev. 2015 Nov;41(6):818–26. Kahn RS, Cheng TL, Mitchell MJ. A framework for pursuing child health equity in pediatric practice. Pediatr Clin North Am. 2023 Aug;70(4):629–38. Brown AF, Ma GX, Miranda J, Eng E, Castille D, Brockie T, et al. Structural interventions to reduce and eliminate health disparities. Am J Public Health. 2019 Jan;109(S1):S72–8.