PHSSR Policy Roadmaps for Acting Early on NCDs Synthesis Report 2025

46 Acting early on NCDs The Partnership for Health System Sustainability and Resiliencepositives. They must be feasible to implement at scale, acceptable to diverse populations, and regularly updated as evidence evolves. Most critically, they must address rather than exacerbate existing health inequities by ensuring that risk assessment captures social and environmental factors. Current approaches Several countries have integrated validated risk assessment tools into their screening programmes, though implementation depth and breadth vary considerably. Poland implements SCORE2 and SCORE2-OP for cardiovascular risk stratification within its prevention programmes, using these tools to determine screening intensity and follow-up schedules (Rzepka-Cholasińska et al., 2022). Patients identified as high-risk receive more frequent monitoring and aggressive risk factor modification, whilst those at lower risk avoid unnecessary medicalisation. Early evidence suggests this targeted approach improves efficiency without compromising outcomes. Spain uses Adjusted Morbidity Groups to classify patients based on health status and risk level through electronic health records, enabling targeted preventive actions in primary care (Orueta et al., 2013). This system goes beyond simple risk scoring to create comprehensive patient profiles that account for multiple conditions, medications, and social factors. Primary care teams receive automated alerts for patients requiring screening or preventive interventions, though alert fatigue and time constraints limit response rates. Italy’s Emilia-Romagna region has developed a comprehensive risk stratification system that categorises individuals based on predicted hospitalisation or death risks using administrative data. The model divides the population aged 14 and above into four risk levels: Low, Moderate, High, and Very High, using statistical methods that integrate age, gender, and health history. High-risk groups, typically older adults with multiple health conditions on complex medication regimens, receive intensified monitoring and proactive care management. This approach has demonstrated strong predictive accuracy and represents a practical application of population health management principles, though like other regional initiatives in Italy, its implementation remains geographically limited rather than nationwide. Japan’s Specific health checkups programme incorporates metabolic syndrome criteria for risk assessment, identifying individuals requiring intensive lifestyle intervention versus routine monitoring (MHLW, 2024d). The programme’s strength lies in its systematic data collection across the entire eligible population, creating a rich database for refining risk prediction. However, the focus on metabolic parameters may miss other important risk factors, particularly psychosocial determinants that profoundly influence disease development. Greece utilises risk models in cardiovascular care through its PROLAMVANO programme but has not extended systematic risk assessment to other conditions. This disease-specific approach reflects common implementation patterns, cardiovascular risk assessment is most advanced given decades of research and validated tools, whilst risk stratification for other NCDs remains underdeveloped. Despite these initiatives, limitations constrain risk-based screening effectiveness. Development of advanced risk prediction methods remains limited, and most countries continue relying on traditional clinical risk factors – age, sex, blood pressure, cholesterol – that explain only a portion of disease risk. For example, no country in our sample reported systematic incorporation of income, education, housing quality, or environmental exposures into risk stratification. This may be driven by inconsistently recording of socioeconomic factors within electronic healthcare records. Notably, one Japanese survey found that only 12.8% of prefectures were even aware of socioeconomic disparities in their populations (MHLW, 2022b).This omission means that risk assessment may systematically underestimate disease probability in disadvantaged populations, paradoxically directing resources away from those most in need.