Hospital Care Utilization Patterns Among Migrants and Natives in a Central Italian Region between 2011 and 2023: Findings from the MIGHTY Project (P2022ASXKR): Migrants Hospitalizations in Central Italy

BackgroundMigration has reshaped the demographic profile of Italian regions, yet evidence on differences in hospital care utilisation between migrant and native populations remains limited, particularly over long periods and across full population cohorts. This study evaluates hospital admissions in the Marche Region from 2011 to 2023 according to citizenship.MethodsA population-based longitudinal study was conducted using Healthcare Utilization Databases on residents of Marche Region, comparing Italian residents with migrants from High Migratory Pressure Countries (HMPC) and Highly Developed Countries (HDC). Age-standardised all-cause, avoidable, and cause-specific hospital admission rates were estimated. Temporal trends were assessed through Poisson regression models. Hospital care utilisation was evaluated using two-step models: logistic regression for the probability of being hospitalized and Poisson regression for the frequency of admissions among hospitalised individuals.ResultsAcross 1.52 million person-years and 2.86 million admissions, HMPC and HDC residents consistently showed lower all-cause, avoidable, and cause-specific admission rates than Italians. Hospitalisations declined over time for all groups, with a marked drop in 2020. Avoidable hospitalisations decreased by 42% in the post-pandemic period. Migrants showed a dual pattern: lower probability of being hospitalised (Odds Ratio, 95% CI: HMPC 0.79, 0.75-0.76; HDC 0.53, 0.51-0.56), but higher admission frequency among those hospitalised (Rate Ratio, 95% CI: HMPC 1.10, 1.09-1.10; HDC 1.04, 1.01-1.07) than Italians.ConclusionMigrant populations in Marche show lower hospitalisation rates but higher utilisation once admitted, suggesting possible barriers to early or appropriate access. Monitoring hospital use through administrative databases is essential to identify potential inequities and guide targeted interventions.