Abstract TP144: Mapping Stroke Risk: A Community-Driven Heatmap Approach

Introduction: Heatmaps are a powerful tool for hospitals to monitor the geographic variation in stroke risk factors among their population of influence. By mapping patient-reported data at the zipcode level, hospitals can visually identify areas where certain risk factors are disproportionately high. Targeted educational interventions in these areas can address gaps in stroke risk factor awareness and symptom recognition, as recommended by the American Stroke Association and the American Heart Association1. Methods: We conducted an exploratory, cross-sectional survey as part of the BEFAST QR Code Initiative to identify the prevalence of patient-reported stroke risk factors at the zipcode level. Volunteers and clinic patients and their caregivers/families, were invited to participate during clinic visits and outreach events. Participants scanned a QR code that linked to an anonymous online questionnaire. The survey collected zipcodes and self-reported presence of stroke risk factors, including hypertension (HTN), smoking, diabetes (DM), hyperlipidemia (HLD), atrial fibrillation (AF), and other lifestyle/medical conditions. Responses were stored securely and aggregated to create geographic heatmaps for visualizing the distribution of stroke risk factors across the hospital’s catchment area. Results: A total of 227 participants completed the survey. The most reported stroke risk factor was HTN (137 respondents, 60.4%), followed by HLD (78, 34.4%), physical inactivity (74, 32.6%), unhealthy diet (67, 29.5%), and smoking (58, 25.6%). DM was reported by 42 participants (18.5%), and AF by 33 (14.5%).Other risk factors included heart disease (28, 12.3%), heart failure (6, 2.6%), and family history of stroke (4, 1.8%). Three respondents (1.3%) reported a personal history of stroke, and fewer than 1% reported alcohol use, drug misuse, high hemoglobin, cancer history, or lack of sleep as risk factors. Conclusion: Community-driven data allows us to create heatmaps that reflect our unique patient catchment area, enabling focused prevention strategies and more efficient outreach efforts. References: 1. Adeoye, O., Nyström, K. V., Yavagal, D. R., Luciano, J., Nogueira, R. G., Zorowitz, R. D., Khalessi, A. A., Bushnell, C., Barsan, W. G., Panagos, P., Alberts, M. J., Tiner, A. C., Schwamm, L. H.,&Jauch, E. C. (2019). Recommendations for the Establishment of Stroke Systems of Care: A 2019 Update. Stroke, 50(7), e187–e210. https://doi.org/10.1161/STR.0000000000000173.

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Journal
Stroke
Published
2026-01-29
DOI
https://doi.org/10.1161/str.57.suppl_1.tp144
Primary Topic
Cardiovascular Health and Risk Factors
Type
article
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article

Abstract TP144: Mapping Stroke Risk: A Community-Driven Heatmap Approach

D Pierotti, Ashleigh Mackey, rebecca sugg, Kimberlyn Bryan et al.
Stroke
Cardiovascular Health and Risk Factors
article

Abstract TP144: Mapping Stroke Risk: A Community-Driven Heatmap Approach

D Pierotti, Ashleigh Mackey, rebecca sugg, Kimberlyn Bryan, Emily Dahlmann
article en

Abstract

Introduction: Heatmaps are a powerful tool for hospitals to monitor the geographic variation in stroke risk factors among their population of influence. By mapping patient-reported data at the zipcode level, hospitals can visually identify areas where certain risk factors are disproportionately high. Targeted educational interventions in these areas can address gaps in stroke risk factor awareness and symptom recognition, as recommended by the American Stroke Association and the American Heart Association1. Methods: We conducted an exploratory, cross-sectional survey as part of the BEFAST QR Code Initiative to identify the prevalence of patient-reported stroke risk factors at the zipcode level. Volunteers and clinic patients and their caregivers/families, were invited to participate during clinic visits and outreach events. Participants scanned a QR code that linked to an anonymous online questionnaire. The survey collected zipcodes and self-reported presence of stroke risk factors, including hypertension (HTN), smoking, diabetes (DM), hyperlipidemia (HLD), atrial fibrillation (AF), and other lifestyle/medical conditions. Responses were stored securely and aggregated to create geographic heatmaps for visualizing the distribution of stroke risk factors across the hospital’s catchment area. Results: A total of 227 participants completed the survey. The most reported stroke risk factor was HTN (137 respondents, 60.4%), followed by HLD (78, 34.4%), physical inactivity (74, 32.6%), unhealthy diet (67, 29.5%), and smoking (58, 25.6%). DM was reported by 42 participants (18.5%), and AF by 33 (14.5%).Other risk factors included heart disease (28, 12.3%), heart failure (6, 2.6%), and family history of stroke (4, 1.8%). Three respondents (1.3%) reported a personal history of stroke, and fewer than 1% reported alcohol use, drug misuse, high hemoglobin, cancer history, or lack of sleep as risk factors. Conclusion: Community-driven data allows us to create heatmaps that reflect our unique patient catchment area, enabling focused prevention strategies and more efficient outreach efforts. References: 1. Adeoye, O., Nyström, K. V., Yavagal, D. R., Luciano, J., Nogueira, R. G., Zorowitz, R. D., Khalessi, A. A., Bushnell, C., Barsan, W. G., Panagos, P., Alberts, M. J., Tiner, A. C., Schwamm, L. H.,&Jauch, E. C. (2019). Recommendations for the Establishment of Stroke Systems of Care: A 2019 Update. Stroke, 50(7), e187–e210. https://doi.org/10.1161/STR.0000000000000173.

StrokeVol. 57(Suppl_1)
University of Mobile (US), University of South Alabama (US)
Good health and well-being
Openalex Percentile: Top 75%
Cardiovascular Health and Risk Factors
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