Costs of acute hospitalisation for stroke and transient ischaemic attack in Australia

Background Stroke is a high-cost condition. Detailed patient-level assessments of the costs of care received and outcomes achieved provide useful information for organisation and optimisation of the health system. Objectives To describe the costs of hospital care for stroke and transient ischaemic attack (TIA) and investigate factors associated with costs. Methods Retrospective cohort study using data from the Australian Stroke Clinical Registry (AuSCR) collected between 2009 and 2013 linked to hospital administrative data and clinical costing data in Queensland. Clinical costing data include standardised assignment of costs from hospitals that contribute to the National Hospital Costing programme. Patient-level costs for each hospital admission were described according to the demographic, clinical and treatment characteristics of patients. Multivariable median regression with clustering by hospital was used to determine factors associated with greater costs. Results Among 22 hospitals, clinical costing data were available for 3909 of 5522 patient admissions in the AuSCR (71%). Compared to those without clinical costing data, patients with clinical costing data were more often aged <65 years (30% with cost data vs 24% without cost data, p < 0.001) and male (56% with cost data vs 49% without cost data, p < 0.001). Median cost of an acute episode was $7945 (interquartile range $4176 to $14970) and the median length of stay was 5 days (interquartile range 2 to 10 days). The most expensive cost buckets were related to medical (n = 3897, median cost $1577), nursing (n = 3908, median cost $2478) and critical care (n = 434, median cost $3064). Factors associated with greater total costs were a diagnosis of intracerebral haemorrhage, greater socioeconomic position, in-hospital stroke and prior history of stroke. Conclusion Medical and nursing costs were incurred by most patients admitted with stroke or TIA, and were relatively more expensive on average than other cost buckets such as imaging and allied health. Implications Scaling this data linkage to national data collections may provide valuable insights into activity-based funding at public hospitals. Regular report of these costs should be encouraged to optimise economic evaluations.