Stroke and myocardial infarction (MI) are serious conditions whose burdens vary by socio-demographic and geographic factors. Although several studies have investigated and identified disparities in burdens of these conditions at the county and state levels, little is known regarding their geographic epidemiology at the neighborhood level. Both conditions require emergency treatments and therefore timely geographic accessibility to appropriate care is critical. Investigation of disparities in geographic accessibility to stroke and MI care and the role of Emergency Medical Services (EMS) in reducing treatment delays are vital in improving health outcomes. Therefore, the objectives of this work were to: (i) classify neighborhoods based on socio-demographic and geographic characteristics; (ii) investigate spatial patterns of neighborhood level mortality; (iii) identify disparities in geographic accessibility to stroke and MI care; and (iv) identify disparities in EMS transport times for stroke and MI patients in East Tennessee. Fuzzy cluster analysis was used to classify neighborhoods into peer neighborhoods (PNs) based on their socio-demographic and geographic factors. Neighborhood level spatial patterns of stroke and MI mortality risks were investigated using Spatial Empirical Bayesian smoothing techniques and neighborhoods with high mortality risks identified using spatial scan statistics. Travel times to stroke and cardiac care facilities were computed using network analysis to investigate geographic accessibility. Records of over 3,900 suspected stroke and MI patients, from two EMS providers, were used to investigate disparities in EMS transport delays. Four distinct PNs were identified. The highest stroke/MI mortality risks were observed in less affluent, urban PNs, and lowest risks in more affluent, suburban PNs. Several significant (p<0.0001) stroke and MI high mortality risk spatial clusters were identified. Approximately 8% and 15% of the population did not have timely accessibility to appropriate stroke and MI care, respectively. The disparity was greatest for populations in rural areas. Important disparities in EMS transport delays were identified, with the travel time to a hospital contributing the longest delay. The identified disparities in neighborhood characteristics, mortality risks, geographic accessibility, and EMS transport delays are invaluable in guiding resource allocation, service provision, and policy decisions to support evidence-based population health planning and policy.