County‐Level Contributors to Geographic Variation in Medicare Fee‐for‐Service Stroke Hospitalization Rates: A Cross‐Sectional Study

BACKGROUND: Stroke hospitalization represents underlying stroke incidence and hospital utilization. We sought to identify factors associated with county-level hospitalization rates (HRs) and counties with HRs above or below expectation using publicly available data. METHODS: , the most impactful factors, and characterized proportional difference between crude and predicted HRs. RESULTS: =0.57). The most impactful factors associated with stroke HRs were prevalence of coronary heart disease, hypertension, smoking, nonadherence to antihypertensive medication, and elevation above sea level. Counties in the northwest United States generally had lower-than-expected HRs. CONCLUSIONS: Considerable unexplained county-level variance in stroke HRs exists after accounting for a wide variety of known and potential predictors. Future work to clarify the mechanism of known predictors and explain variance may inform interventions to improve systems of care.

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Publication Details

Journal
Journal of the American Heart Association
Published
2026-04-28
DOI
https://doi.org/10.1161/jaha.125.048231
Primary Topic
Acute Ischemic Stroke Management
Type
article
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article

County‐Level Contributors to Geographic Variation in Medicare Fee‐for‐Service Stroke Hospitalization Rates: A Cross‐Sectional Study

J. K. Wing, Mohamed Ridha, Kevin Kerber, Raed Hailat et al.
Journal of the American Heart Association
Acute Ischemic Stroke Management
article

County‐Level Contributors to Geographic Variation in Medicare Fee‐for‐Service Stroke Hospitalization Rates: A Cross‐Sectional Study

J. K. Wing, Mohamed Ridha, Kevin Kerber, Raed Hailat, James F. Burke, Matthew Gusler, Chun Chieh Lin
article en

Abstract

BACKGROUND: Stroke hospitalization represents underlying stroke incidence and hospital utilization. We sought to identify factors associated with county-level hospitalization rates (HRs) and counties with HRs above or below expectation using publicly available data. METHODS: , the most impactful factors, and characterized proportional difference between crude and predicted HRs. RESULTS: =0.57). The most impactful factors associated with stroke HRs were prevalence of coronary heart disease, hypertension, smoking, nonadherence to antihypertensive medication, and elevation above sea level. Counties in the northwest United States generally had lower-than-expected HRs. CONCLUSIONS: Considerable unexplained county-level variance in stroke HRs exists after accounting for a wide variety of known and potential predictors. Future work to clarify the mechanism of known predictors and explain variance may inform interventions to improve systems of care.

Journal of the American Heart AssociationVol. 15(9)
The Ohio State University Wexner Medical Center (US), The Ohio State University (US)
Openalex Percentile: Top 17%
Acute Ischemic Stroke Management
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