Spatiotemporal characterisation of stroke care accessibility and hospital coverage in the Santiago Metropolitan Region

Abstract

Stroke is a significant cause of death in Chile, with ischemic stroke requiring urgent medical attention. A lack of detailed information on hospital coverage and service accessibility limits access to timely care. This study proposes a spatiotemporal model to characterise the distribution of stroke risk factors and access to care in the Metropolitan Region of Santiago, Chile. Using data from the 2017 Census, the 2022 CASEN survey, and hospital discharge records from the Chilean Diagnosis-Related Groups system (DRGs), we applied spatial microsimulation to estimate the geographic distribution of high-risk populations. Isochrone analysis was used to calculate travel times to hospitals treating ischemic stroke, and clustering techniques identified areas with standard profiles in terms of risk and accessibility. The results highlight significant disparities across census zones, with specific areas showing both high risk and poor access. We deployed an interactive dashboard to support decision-making and health policy planning. The study shows that combining geospatial analysis and data mining can improve the identification of critical areas and inform resource allocation.