Background and Purpose—We examined patient demographic and hospital characteristics and clinical predictors of delay time from hospital arrival until CT among 20 374 patients enrolled in the North Carolina Collaborative Stroke Registry (January 2005 to April 2008).

Methods—Delay time was log-transformed in linear regression analyses and dichotomized (25 minutes, >25 minutes) in logistic regression analyses to correspond to a 1999 National Institute of Neurological Disorders and Stroke guideline.

Results—In multiple linear regression analyses, prehospital delay time, mode of transport, race, gender, presumptive diagnosis, time of day of arrival, weekday versus weekend arrival, and hospital type (defined by Joint Commission Primary Stroke Center certification and teaching status) were significantly associated with CT delay. In analyses of 3549 patients arriving within 2 hours of symptom onset, time of day of arrival and weekday versus weekend arrival were no longer significant. Among patients arriving within 2 hours of symptom onset, the strongest independent predictors of meeting the National Institute of Neurological Disorders and Stroke (NINDS) guideline were arrival by emergency medical services versus other modes of transportation (odds ratio, 95% CI=2.3 [1.9, 2.8]) and a presumptive diagnosis of transient ischemic attack versus unspecified stroke type (odds ratio, 95% CI=0.4 [0.3, 0.5]).

Conclusions—Most patients do not arrive to the hospital in a timely manner and cannot be considered for time-dependent therapies. Among those that do, disparities exist in time to receipt of CT scan, suggesting room for improvement in hospital-level stroke systems of care.