AIM To determine whether regional variation in stroke incidence exists among individuals with AF. METHODS Using healthcare utilization claims from 2 large US databases, MarketScan (2007-2014) and Optum Clinformatics (2009-2015), and the 2010 US population as the standard, we estimated age-, sex-, race- (only in Optum) standardized stroke incidence rates by the 9 US census divisions. We also used Poisson regression to examine incidence rate ratios (IRR) of stroke and the probability of anticoagulation prescription fills across divisions. RESULTS Both databases combined included 970,683 patients with AF who experienced 15,543 strokes, with a mean follow-up of 23 months. In MarketScan, the age- and sex-standardized stroke incidence rate was highest in the Middle Atlantic and East South Central divisions at 3.8/1000 person-years (PY) and lowest in the West North Central at 3.2/1000 PY. The IRR of stroke and the probability of anticoagulation fills were similar across divisions. In Optum Clinformatics, the age-, sex-, and race-standardized stroke incidence rate was highest in the East North Central division at 5.0/1000 PY and lowest in the New England division at 3.3/1000 PY. IRR of stroke and the probability of anticoagulation fills differed across divisions when compared to New England. CONCLUSIONS These findings suggest regional differences in stroke incidence among AF patients follow a pattern that differs from the hypothesized trend found in the general population and that other factors may be responsible for this new pattern. Cross-database differences provide a cautionary tale for the identification of regional variation using health claims data.
Geographic Disparities in the Incidence of Stroke among Patients with Atrial Fibrillation in the United States.
J. Claxton,P. Lutsey,R. Maclehose,L. Chen,T. Lewis,Á. Alonso
Published 2019 in Journal of Stroke & Cerebrovascular Diseases
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- Publication year
2019
- Venue
Journal of Stroke & Cerebrovascular Diseases
- Publication date
2019-04-01
- Fields of study
Geography, Medicine
- Identifiers
- External record
- Source metadata
Semantic Scholar, PubMed
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