Fairness in Healthcare Services for Italian Older People: A Convolution-Based Evaluation to Support Policy Decision Makers

Davide Donato Russo (), Frida Milella and Giuseppe Di Felice
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Davide Donato Russo: Institute for Systems Analysis and Computer Science “Antonio Ruberti”, National Research Council, Via dei Taurini 19, 00185 Rome, Italy
Frida Milella: Department of Informatics, Systems and Communication (DISCo), University of Milano-Bicocca, Viale Sarca 336, 20126 Milan, Italy
Giuseppe Di Felice: Departiment of Bioscience and Territory (DiBT), University of Molise, C.da Fonte Lappone, 86090 Pesche, Italy

Mathematics, 2025, vol. 13, issue 9, 1-17

Abstract: In Italy, the current demographic transition makes it a strategic goal to realign the distribution of health services based on the population aged over 65. The traditional challenge of achieving a fine-grained assessment of health resource statistics and evaluating the fairness of health services across regions is a concern in current research on the fairness of health services. In this study, the authors propose a methodological approach to foster a novel analysis of fairness in the allocation of primary health care services in Italy with a specific focus on the population aged 65 or over, which facilitates the processing of extensive administrative and demographic data to ensure a clear and precise visualization for informed decision making. The proposed methodology integrates convolution matrices weighted by aged population density within a fine-grained geographic grid representation. This approach is combined with an image convolution technique for filtering, enabling an effective estimation of health resource impact and a clear visualization of their spatial distribution across geographical areas. The integration of several data sources to evaluate the equity in accessibility distribution through the Gini index is also exploited to quantify the disparity between healthcare service provision and the aged population at the regional district level. Our findings showed a substantial unfairness in service distribution, with a concentration of healthcare effect in prominent regions such as Campania, Lazio, and Lombardia, indicating that healthcare accessibility is predominantly disproportionate in Italy, particularly for the population aged over 65.

Keywords: convolution-based algorithm; fairness; aging; Gini coefficient; policymaking; Italy (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2025
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