The role of socio-economic determinants in the interregional allocation of healthcare resources: Some insights from the 2023 reform in the Italian NHS
Fantozzi R., Gabriele S., Zanardi A., 2025 – Health policy
The Italian National Health Service (NHS) introduced in 2023 a reform in its funding mechanism by incorporating socio-economic indicators into the scheme for allocating financial resources to regions. This reform aims to address regional disparities in healthcare access, drawing inspiration from international best practices.
In a recent article titled “The role of socio-economic determinants in the interregional allocation of healthcare resources: Some insights from the 2023 reform in the Italian NHS”, published in Health Policy, Roberto Fantozzi, Stefania Gabriele and Alberto Zanardi proposed a possible improvement of the reform, fully exploiting the information on the heterogeneity of health needs based on both age and socio-economic indicators.
The NHS funding system is primarily based on a top-down setup, with the central government determining the overall budget and allocating funds to regions. The previous system used population size and age composition as the sole criteria for allocating total financial resources to the regions. This mechanism led to criticism and calls for greater consideration of social and economic factors as key drivers in resource allocation to regions.
The 2023 reform has followed a very simplified scheme, by simply introducing new allocation criteria for a limited share of funding (1.5%), namely premature mortality and a composite deprivation index (including poverty, low education, and unemployment). This means that the additional indicators serve merely as a marginal adjustment to the territorial allocation based on the criteria used so far.
These socio-economic criteria have led to some redistribution from Northern to Southern Regions and signal a step forward, but their impact remains limited and lacks a robust risk-adjustment approach. Moreover, the reform’s effect is partially offset by the discretionary distribution of an “incentive component” (“quota premiale”) to regions (see Table 1).
The study explores the potential for a more comprehensive approach, which involves developing a matrix of healthcare consumption weights based on age and socio-economic status jointly considered, within a risk-adjustment framework. Using survey data (micro-data are taken from the sample an annual survey “Aspetti della vita quotidiana” (Aspects of daily life) carried out by ISTAT), we simulate the interregional allocation of financial resources resulting from an approach closely replicating the reform (Reform scenario) and then compare it with a scenario in which, in line with a risk-adjustment perspective, data on healthcare consumption according to age and socio-economic indicators are jointly considered (Full information scenario). In the latter case, a matrix of consumption weights, measured at the national level, is developed to account for the impact of the two variables on health needs (each element of the matrix measures the weight associated with an individual identified by a specific couple of values of age and socio-economic status).
Figure 2 shows how, diverging from the simplified formula adopted by the reform and adopting a more comprehensive approach, the Full information scenario redistributes significantly more funds than the Reform scenario (about 86 million euros), in particular in favor of Southern regions, with higher levels of deprivation (Campania, Apulia and Calabria), whereas all Central and Northern regions are penalized (especially Veneto, Piedmont, and Lombardy).
To make the approach suggested in the study operational would require an effort to evaluate the weighting of deprivation, as well as age, for regional populations, based on administrative data (and not on survey data used here for illustrative purposes). The databases on healthcare benefits and their costs, available to Italian government departments, could be used for this purpose. This would require, however, a number of developments and adjustments, as these databases would have to be linked to those on the economic condition of patients, such as tax data, social security data, and data on the Equivalent Economic Situation Indicator (which describes the economic condition of those applying for benefits and facilities), whilst taking care to comply with privacy regulations. This seems feasible and indeed it has been already partially carried out by the Italian tax authorities to provide taxpayers with precompiled tax returns, in which tax credits for healthcare expenses are incorporated. The obstacles to the adoption of this approach come on the one hand, from the difficulties of collecting and managing information, including privacy obligations, and on the other hand, from the consequent restrictions on the discretionary control of policymakers over resource allocation.
In any case, the debate within the Italian NHS on revising the criteria for inter-regional allocation of healthcare financial resources remains open. The 2023 reform aimed to implement Legislative Decree 68/2011, which, however, also provided that the pathway for improving quality standards and other indicators should be considered among the criteria to be adopted. These aspects were postponed pending the availability of adequate data for their application, particularly those covering the New Guarantee System (NSG) for verifying the maintenance of essential levels of healthcare (LEA).
Finally, the 2025 Budget Law introduced two additional measures. On the one hand, two significant portions of funding (20 and 100 million euros per year) have been allocated, respectively, to smaller regions and to those that comply with waiting list reduction targets. On the other hand, the law has provided for the introduction of additional indicators within the NSG, aimed at reflecting management, organizational, economic, accounting, financial and asset aspects, to strengthen the monitoring of expenditure and the evaluation of performance. In the future, these additional indicators could potentially be integrated into the mechanism for allocating healthcare financial resources across regions.