Risk factors associated with 30-day all-cause unplanned hospital readmissions at a tertiary children's hospital in Western Australia - Zhou, Jo; Della, Phill; Porter, P.; Roberts, Pamela A. (WILEY, 2020)
Aim: To identify risk factors associated with 30-day all-cause unplanned hospital readmission at a tertiary children's hospital in Western Australia. Methods: An administrative paediatric inpatient dataset was analysed retrospectively. Patients of all ages discharged between 1 January 2010 and 31 December 2014 were included. Demographic and clinical information at the index admission was examined using multivariate logistic regression analysis. Results: A total of 3330 patients (4.55%) experienced at least one unplanned readmission after discharge. Readmission was more likely to occur in patients who were either older than 16 years (odds ratio (OR) = 1.46; 95% confidence interval (CI) 1.07–1.98), utilising private insurance as an inpatient (OR = 1.16; 95% CI 1.00–1.34), with greater socio-economic advantage (OR = 1.20; 95% CI 1.02–1.41), admitted on Friday (OR = 1.21; 95% CI 1.05–1.39), discharged on Friday/Saturday/Sunday (OR = 1.26, 95% CI 1.10–1.44; OR = 1.34, 95% CI 1.15–1.57; OR = 1.24, 95% CI 1.05–1.47, respectively), with four or more diagnoses at the index admission (OR = 2.41; 95% CI 2.08–2.80) or hospitalised for 15 days or longer (OR = 2.39; 95% CI 1.88–2.98). Area under receiver operating characteristic curve of the predictive model is 0.645. Conclusions: A moderate discriminative ability predictive model for 30-day all-cause same hospital readmission was developed. A structured discharge plan is suggested to be commenced from admission to ensure continuity of care for patients identified as being at higher risk of readmission. A recommendation is made that a designated staff member be assigned to co-ordinate the plan, including assessment of patients' and primary carers' readiness for discharge. Further research is required to establish comprehensive paediatric readmission rates by accessing linkage data to capture different hospital readmissions.