Clustering Provincial Health System Performance in Türkiye: A Dual-Method Analysis

Purpose: Türkiye, despite extensive health reforms, continues to exhibit substantial variation in health system performance across its 81 provinces. This study aimed to classify provincial health system performance in Türkiye by integrating key indicators of infrastructure and service utilization using complementary clustering methods.Methods: This cross-sectional study used publicly available province-level data from the Türkiye Health Statistics Yearbook 2023. Six standardized indicators were analyzed for all 81 provinces. Ward’s hierarchical clustering and K-means clustering were applied to identify homogeneous groups. Additional ANOVA analyses were performed to evaluate differences between clusters. Cluster patterns were further visualized using geographic maps, principal component analysis, and radar charts.Results: Both clustering methods identified three distinct typologies of provincial health systems. Significant between cluster differences were observed for several indicators, particularly workforce density and bed occupancy rates. One cluster demonstrated high workforce density, bed availability and service utilization, a second exhibited consistently low value across all indicators and a third represented intermediate profiles. Agreement between the two clustering methods was substantial, supporting the robustness of the classification. Geographical visualization revealed that higher performing clusters were predominantly concentrated in western and metropolitan regions, whereas lower-capacity clusters appeared more frequently in eastern and southeastern provinces.Conclusions: Integrating structural and utilization indicators through dual-method clustering provides a comprehensive framework for classifying provincial health system performance in Türkiye. These typologies highlight marked intranational disparities and can inform regionally sensitive health planning within Türkiye.