For citation:
Begicheva, S. V. (2025). Spatial Modeling of Healthcare Accessibility Using Probabilistic Methods: A Case Study of Sverdlovsk Oblast. AlterEconomics, 22(2), 340–361. https://doi.org/10.31063/AlterEconomics/2025.22-2.9
Abstract:
Assessing spatial accessibility to healthcare remains a key challenge for regional health systems, particularly in areas with pronounced territorial disparities. This study proposes a probabilistic model of healthcare provider choice that accounts for patients’ spatial behavior, limited availability of alternatives, and incomplete input data. The research focuses on outpatient care provider selection by residents of Sverdlovsk Oblast. The goal is to develop and validate a model that reproduces inter-municipal patient flows using aggregated statistics. The model is based on a gravity-based approach, where patients are more likely to seek care from nearby facilities, and the influence of more distant providers decreases as travel time increases. Unlike traditional models, it includes a mechanism to generate a limited choice set through spatial clustering and factors in patients’ loyalty to providers within their own municipality. Validation using the rank correlation coefficient between predicted and observed visit counts shows high predictive accuracy and reveals substantial spatial variation in healthcare utilization patterns.Designed to work with aggregated data, the model can be applied to other regions facing similar data constraints. It could help improve decision-making in planning routes, deploying mobile health teams, and optimizing healthcare networks. A noted limitation is its inability to capture individual-level decision-making. Future research could incorporate socio-economic factors and expand the model to other levels of the healthcare system.
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