Race and sex disparities in prehospital recognition of acute stroke.
OBJECTIVE
The objective of this study was to examine prehospital provider recognition of stroke by race and sex.


METHODS
Diagnoses at emergency department (ED) and hospital discharge from a statewide database in California were linked to prehospital diagnoses from an electronic database from two counties in Northern California from January 2005 to December 2007 using probabilistic linkage. All patients 18 years and older, transported by ambulances (n = 309,866) within the two counties, and patients with hospital-based discharge diagnoses of stroke (n = 10,719) were included in the study. Logistic regression was used to analyze the independent association of race and sex with the correct prehospital diagnosis of stroke.


RESULTS
There were 10,719 patients discharged with primary diagnoses of stroke. Of those, 3,787 (35%) were transported by emergency medical services providers. Overall, 32% of patients ultimately diagnosed with stroke were identified in the prehospital setting. Correct prehospital recognition of stroke was lower among Hispanic patients (odds ratio [OR] = 0.77, 95% confidence interval [CI] 0.61 to 0.96), Asians (OR = 0.66, 95% CI 0.55 to 0.80), and others (OR = 0.71, 95% CI = 0.53 to 0.94), when compared with non-Hispanic whites, and in women compared with men (OR = 0.82, 95% CI = 0.71 to 0.94). Specificity for recognizing stroke was lower in females than males (OR = 0.84, 95% CI = 0.78 to 0.90).


CONCLUSIONS
Significant disparities exist in prehospital stroke recognition.
The Department of Emergency Medicine, University of California at San Francisco, San Francisco, CA.
Prasanthi
P
Govindarajan
Benjamin T
BT
Friedman
James Q
JQ
Delgadillo
David
D
Ghilarducci
Lawrence J
LJ
Cook
Barbara
B
Grimes
Charles E
CE
McCulloch
S Claiborne
SC
Johnston
D000367:Age Factors; D000368:Aged; D000369:Aged, 80 and over; D000552:Ambulances / Q000706:statistics & numerical data*; D002140:California / Q000453:epidemiology; D003430:Cross-Sectional Studies; D005260:Female; D054625:Healthcare Disparities / Q000706:statistics & numerical data*; D006630:Hispanic or Latino; D006801:Humans; D007348:Insurance, Health; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D016017:Odds Ratio; D044469:Racial Groups / Q000706:statistics & numerical data*; D012189:Retrospective Studies; D012680:Sensitivity and Specificity; D012737:Sex Factors; D020521:Stroke / Q000175:diagnosis*; D044465:White People