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Keywords

Health Systems Cluster Analysis Europe Public Health Healthcare Workforce Catastrophic Health Expenditure Machine Learning

Abstract

Traditional health system classifications may not accurately reflect the complex realities of modern European nations. This study takes a data-driven approach to create a new classification. We used WHO data and applied a K-Means clustering algorithm to 52 European countries, focusing on recent figures for doctor density, nurse density, and catastrophic health spending. The analysis revealed three clear clusters: "High-Resource, Low-Burden" systems (n=14), "Physician-Centric, High-Burden" systems (n=18), and "Lower-Resource" systems (n=20). This classification offers a detailed way to understand current health system structures and to inform policy decisions across Europe.

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References

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Copyright (c) 2025 Poe Hnin Phyu, Mahmood Ahmad, Laiba Khan, Maham Khan, Nijat Rizayev, Manpreet Kour, Touqeer Rana, Andrew Woo, Parichatra Homhuan