Factors predictive of hospital admission for children via emergency departments in Australia and Sweden: an observational cross-sectional study

Abstract

BackgroundIdentifying factors predictive of hospital admission can be useful to prospectively inform bed management and patient flow strategies and decrease emergency department (ED) crowding. It is largely unknown if admission rate or factors predictive of admission vary based on the population to which the ED served (i.e., children only, or both adults and children). This study aimed to describe the profile and identify factors predictive of hospital admission for children who presented to four EDs in Australia and one ED in Sweden.MethodsA multi-site observational cross-sectional study using routinely collected data pertaining to ED presentations made by children < 18 years of age between July 1, 2011 and October 31, 2012. Univariate and multivariate analysis were undertaken to determine factors predictive of hospital admission.ResultsOf the 151,647 ED presentations made during the study period, 22% resulted in hospital admission. Admission rate varied by site; the children’s EDs in Australia had higher admission rates (South Australia: 26%, Queensland: 23%) than the mixed (adult and children’s) EDs (South Australia: 13%, Queensland: 17%, Sweden: 18%). Factors most predictive of hospital admission for children, after controlling for triage category, included hospital type (children’s only) adjusted odds ratio (aOR):2.3 (95%CI: 2.2–2.4), arrival by ambulance aOR:2.8 (95%CI: 2.7–2.9), referral from primary health aOR:1.5 (95%CI: 1.4–1.6) and presentation with a respiratory or gastrointestinal condition (aOR:2.6, 95%CI: 2.5–2.8 and aOR:1.5, 95%CI: 1.4–1.6, respectively). Predictors were similar when each site was considered separately.ConclusionsAlthough the characteristics of children varied by site, factors predictive of hospital admission were mostly similar. The awareness of these factors predicting the need for hospital admission can support the development of clinical pathways.