Abstract 34: Predictors of Readmission to Hospital Following Acute Stroke

Background: Readmission to hospital following discharge for acute stroke has been estimated in previous studies to be about 30% and recurrent stroke is known to be associated with a higher mortality and worse functional outcome than a first stroke. The aim of this study was to develop a risk-standardized model that identified potential predictors of readmission at 30 days, 1 year and 2 years following discharge for acute stroke. Methods: We analyzed data from eleven stroke centres in Ontario participating in Phase 3 of the Registry of the Canadian Stroke Network (RCSN). Consecutive patients admitted between July 1, 2003 and March 31, 2008 with ischemic stroke, TIA or intracerebral hemorrhage (ICH) who were alive at discharge were included in the analysis. Records were linked to a provincial administrative database to determine readmission within 30 days, 1 year and 2 years. Competing risks (death and readmission) time-to-event Cox modeling was used to evaluate potential predictors of readmission including age, sex, risk factors, initial stroke severity, comorbidities, type of stroke and discharge medications, for all stroke patients and those with ischemic stroke, TIA or ICH. Results: The final cohort consisted of 12,432 patients admitted with a final diagnosis of ischemic stroke, TIA or ICH. The mean patient age was 70.6 years, 46.7% were female and 19.8% had severe deficits on admission (Canadian Neurological Scale, 0 - 5.5). The readmission rate for any reason at 30 days, 1 year and 2 years was 9.6%, 31.4% and 42.3%, respectively, while the mortality rate for those same periods was 2.9%, 13.2% and 19.6%. The readmission rate for recurrent stroke at 30 days, 1 year and 2 years was 2.9%, 6.1% and 8.0%, respectively. Readmission at 30 days for all causes was highest for TIA patients (13.5%) and similar for ischemic stroke and ICH patients (9.0 and 8.5%). Factors associated with a lower rate of readmission for all causes included admission to a stroke unit, use of statins, warfarin and a lower modified Rankin Scale (mRS) at discharge (all p<0.05). Factors that increased the rate of readmission included the presence of atrial fibrillation, angina, peripheral vascular disease, diabetes, smoking, elevated creatinine and cancer (all p<0.05). Conclusions: Our data suggest that there are determinants of hospital readmission that can be used in a prediction model that serve to correct for case mix when comparing hospital-level readmission rates. Some of the predictors such as the use of stroke units, cigarette smoking, atrial fibrillation and statins at discharge provide potential opportunities to intervene and lower readmission rates.