Costs of Hospitalisation Due to Stroke: Linked Registry and Administrative Clinical Costing Study - Kim, Joosup (International Journal of Population Data Science, 2020)
Introduction Routine clinical costing of hospital care provided for a representative sample of patients informs a national price for hospital reimbursement according to the diagnosis related group of a patient. These clinical costing data are available for linkage as part of hospital administrative datasets. Objectives and Approach The Australian Stroke Clinical Registry (AuSCR) is a national data collection program used to monitor the quality of care provided to patients who have been hospitalised with a clinical diagnosis of stroke or transient ischaemic attack (TIA). For the Stroke123 project, registrants from the Australian Stroke Clinical Registry in 2009-2013 were linked to hospital administrative datasets in four states (Victoria, Queensland, New South Wales and Western Australia). Clinical costing data were obtained for the cohort in Queensland only. Using these clinical costing data, we aimed to determine the costs of hospitalisations according to clinical and demographic characteristics of patients. Reliability of clinical costing data were tested by assessing the association with disease burden and length of stay using multivariable linear regression analysis. Results Of the 5522 patient episodes (from 23 hospitals), clinical costing data were available for 3909 (71%, from 22 hospitals). Patients with clinical costing data were more often aged <65 years (30% vs 24%, p<0.001) and more often male (56% vs 49%, p<0.001) than those without these data. Mean cost of an episode was 12,129. Episodes of intracerebral haemorrhage had a mean cost of 18,315, which was greater than the mean costs of ischaemic stroke (13,925), TIA (5,247) and undetermined stroke (8,996). Greater costs were associated with greater disease burden according to the Charlson Comorbidity Index (p<0.001) and length of stay (p<0.001). Conclusion / Implications Integration of clinical quality data and costs will enable more holistic assessment and monitoring of the effects of quality improvement initiatives and therapeutic advances.