Chronic conditions, rare diseases and vulnerability in Italy: building a national segmentation model

Abstract Introduction Population segmentation using administrative healthcare data has been attempted locally in Italy. As part of the Italian Strategic Foresight Initiative, promoted by the Ministry of Health and funded through the EU Next Generation programme, the first national segmentation model was developed to identify individuals with chronic conditions, rare diseases, and vulnerabilities included in the national health benefits package. Its results warrant comparison with existing evidence. Methods The model was applied to a representative sample of four million individuals, using 2017-2022 administrative data flows of the Italian national health information systems (hospitalizations, exemptions, drug dispensing, home and outpatient care, mental health, addiction services) to identify tracer conditions. Crude prevalence rates were calculated by sex and age group. Estimates were compared with regional, national, international sources, using relative percentage differences. Results The model includes 194 tracking algorithms structured into four hierarchical levels and 20 thematic areas. In 62 cases (31.6%), no direct external comparison was available. Among the others, 17 (8.8%) were aligned (relative difference <30%) with all sources, 37 (19.1%) showed higher prevalence, 31 (16.0%) lower prevalence, and 47 (24.2%) mixed results. Overall, 57 conditions (29.3%) were aligned with at least one source, increasing to 50% among the 30 most prevalent conditions. In the sample, 57% had at least one tracked condition (40% had more than one), 50.8% had chronic conditions, 28.6% had vulnerability, and 3.5% had a rare disease. Conclusions These preliminary results show the feasibility of segmentation using national administrative data, overcoming regional fragmentation. The model will support health planning, risk stratification, and forecasting. Future steps include the expansion to acute conditions, integration of new data sources, and consolidation through expert consensus. Key messages • A national segmentation model for chronic conditions, rare diseases and vulnerability using Italian administrative data was developed to support health planning, risk stratification and forecasting. • Comparison with existing evidence showed consistency for major conditions and confirmed the high burden of chronic diseases and vulnerability in the Italian population.