Abstract TP301: Outlier Analysis of NIHSS Change in a Regional Database of Acute Ischemic Stroke

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Introduction: Change in NIH Stroke Scale from admission to discharge has been proposed as an outcome-based method of assessing quality of care in the inpatient setting. Using the Kentucky Appalachian Stroke Registry database, statistical outliers were identified as potential targets for investigation. We aimed to use the analysis of this subset of patients to identify characteristics favoring exceptionally good or poor outcome.Methods: De-identified patient data was obtained from the Kentucky Appalachian Stroke Registry for all acute ischemic stroke patients from January 1, 2013 to December 31, 2014 using discharge diagnoses. Statistical process control methodology was used to identify hospitalizations with positive or negative NIHSS change more than three standard deviations from the mean. The statistical outliers underwent manual chart review to validate the data obtained from the registry and supplement it qualitatively to identify common characteristics. Chi-square tests were conducted to assess the association between patient characteristics and being a positive or negative outlier.Results: Positive outliers were less likely to have hypertension and more likely to have received intravenous thrombolysis. Negative outliers were more likely to have carotid stenosis. Both groups were more likely to have a diagnosis of cardiac arrhythmia and to have received mechanical thrombectomy.Conclusions: Gathering registry data regarding NIHSS outliers is a feasible and potentially useful tool in understanding and improving care. The absence of hypertension may represent positive predictive recovery potential in severe stroke. Patients with significant carotid disease on presentation may be at risk of neurological decline. Furthermore, patients with large vessel occlusions undergoing thrombectomy represent a high-variance population with the greatest improvements and greatest deteriorations during inpatient hospitalization.

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