Background: Lombardy Region (RL) is organized into 8 Health Protection Agencies (ATS) and 86 Districts, which are responsible for organizing and coordinating territorial health care for reference population ranging between 80,000 and 120,000 inhabitants. RL has implemented the Health Profiles Portal, an advanced system that integrates health care, socio-health, and social data to provide a clear and comparable view of the population's needs at different territorial levels. To develop the portal, it was necessary to construct denominators that would ensure the accuracy and comparability of the healthcare indicators.
Objectives: to compare three different methods for constructing population denominators: two based on Regional Registries (NAR) and one on the Italian National Institute of Statistics (Istat) data.
Methods: the first denominator (NAR_portale) used for the portal was constructed from all monthly extractions of NAR in 2023 collected by the ATSs; the second denominator (NAR_202401) was based on the assisted population as of January 2024, including those who died in 2023; the third denominator (ISTAT_202401) was based on Istat population data as of 01.01.2024. Comparisons, expressed as percentage variations (VP) relative to NAR_portale, were carried out at both the ATS and District levels, with separate analyses by gender, age, nationality, and residence in nursing homes (RSA). Results: overall, NAR_portale identified a population of 10,111,769 residents, NAR_202401 recorded 10,106,191 subjects (VP 0.05%), and ISTAT_202401 recoded 10,012,054 (VP 0.99%). Greater variability was observed at the ATS level, whereas districts within the same ATS exhibited more homogeneous trends. The largest VPs were observed in the extreme age groups (0-1 and 85+ years), among foreign citizens, and among RSA residents.
Conclusions: the differences between denominators highlight the complexity of constructing reference populations for health monitoring. NAR_portale provides greater dynamism and completeness, but efforts are needed to standardise and ensure comparability with other sources. In the future, the integration of different data sources and the use of advanced methodologies could improve monitoring quality and support more effective healthcare planning.
Keywords: administrative healthcare data; health profile; public heal.