Abstract
BACKGROUND: Population-based Health Risk Assessment (HRA) tools are strategic for the implementation of integrated care. Various HRA algorithms have been developed in the last decades worldwide. Their full adoption being limited by technical, functional, and economical factors. This study aims to apply the Adjusted Morbidity Groups (AMG) algorithm in the context of an Italian Region, and evaluate its performance to support decision-making processes in healthcare programming. METHODS: The pilot study used five Healthcare Administrative Databases (HADs) covering the period 2015-2021. An iterative semi-automated procedure was developed to extract, filter, check and merge the data. A technical manual was developed to describe the process, designed to be standardized, reproducible and transferable. AMG algorithm was applied and descriptive analysis performed. A dashboard structure was developed to exploit the results of the tool. RESULTS: AMG produced information on the health status of Marche citizens, highlighting the presence of chronic conditions from age 45 years. Persons with high and very high level of complexity showed elevated mortality rates and an increased use of healthcare resources. A visualization dashboard was intended to provide to relevant stakeholders accessible, updated and ready-to-use aggregated information on the health status of citizens and additional insight on the use of the healthcare services and resources by specific groups of citizens. CONCLUSION: The flexibility of the AMG, together with its ability to support policymakers and clinical sector, could favour its implementation in different scenarios across Europe. A clear strategy for the adoption of HRA tools and related key elements and lessons learnt for a successful transferability at the EU level were defined. HRA strategies should be considered a pillar of healthcare policies and programming to achieve person-centred care and promote the sustainability of the EU healthcare systems.