PURPOSE

Confounding by disease severity has been viewed as an intractable problem in claims-based studies. A novel 7-variable stroke severity index (SSI) was designed for estimating stroke severity by using claims data. This study compared the performance of mortality models with various proxy measures of stroke severity, including the SSI, in patients hospitalized for acute ischemic stroke (AIS).

METHODS

Data from the Taiwan National Health Insurance Research Database (NHIRD) were analyzed. Three proxy measures of stroke severity were evaluated: Measure 1, the SSI; Measure 2, intensive care unit admission and length of stay; and Measure 3, surgical operation, mechanical ventilation, hemiplegia or hemiparesis, and residual neurological deficits. We performed logistic regression by including age, sex, vascular risk factors, Charlson comorbidity index, and one of the proxy measures as covariates to predict 30-day and 1-year mortality after AIS. Model discrimination was evaluated using the area under the receiver-operating characteristic curve (AUC).

RESULTS

We identified 7551 adult patients with AIS. Models using the SSI (Measure 1) outperformed models using the other proxy measures in predicting 30-day mortality (AUC 0.892 vs 0.851, p < 0.001 for Measure 2; 0.892 vs 0.853, p < 0.001 for Measure 3) and 1-year mortality (AUC 0.816 vs 0.784, p < 0.001 for Measure 2; 0.816 vs 0.782, p < 0.001 for Measure 3).

CONCLUSIONS

Using the SSI facilitated risk adjustment for stroke severity in mortality models for patients with AIS. The SSI is a viable methodological tool for stroke outcome studies using the NHIRD.