TY  -  JOUR
AU  -  Baglivo, Francesco
AU  -  Diedenhofen, Giacomo
AU  -  De Angelis, Luigi
AU  -  Pivetta, Alessio
AU  -  Causio, Francesco Andrea
AU  -  D’Ambrosio, Angelo
AU  -  Sacchi, Francesca Aurora
AU  -  Di Pumpo, Marcello
AU  -  Belpiede, Alessandro
AU  -  Ghisalberti, Gianpaolo
AU  -  Ferro, Diana
AU  -  Rizzo, Caterina
T1  -  Why tomorrow’s public health needs to be digital: 
artificial intelligence and automation for a sustainable Italian National Health Service
PY  -  2025
Y1  -  2025-10-01
DO  -  10.1701/4573.45775
JO  -  Recenti Progressi in Medicina
JA  -  Recenti Prog Med
VL  -  116
IS  -  10
SP  -  551
EP  -  555
PB  -  Il Pensiero Scientifico Editore
SN  -  2038-1840
Y2  -  2026/03/15
UR  -  http://dx.doi.org/10.1701/4573.45775
N2  -  Summary. Italy’s National Health Service (SSN) serves one of Europe’s oldest populations under fiscal constraint and a fragmented data infrastructure. Rather than a standalone fix, artificial intelligence should be treated as a catalyst for a human-centred digital transformation that improves access, quality, and sustainability. Building on the Italian Society for Artificial Intelligence in Medicine (SIIAM) vision, we outline a pragmatic agenda. First, reduce elective-care backlogs by automating confirmations, reminders, cancellations, and rescheduling; deploy multilingual conversational agents to collect structured pre-visit histories and deliver summaries, while natural-language processing flags overdue follow-ups. Second, advance equity by offering inclusive digital front doors and tele-triage that prioritise patients facing language, literacy, socioeconomic, or geographic barriers. Third, curb waste through clinical-decision support and workflow automation that standardise evidence-based practice and relieve documentation burden. Fourth, modernise surveillance by pairing large language model powered voice agents for behaviour and symptom monitoring with participatory systems and AI epidemic intelligence. Fifth, link data and people through multidisciplinary teams and a human-in-the-loop approach that embeds transparency, bias mitigation, privacy, and safety. Implementation should start where impact is fastest: risk-stratified booking, proactive reminders, and shared dashboards with comparable indicators. To sustain gains, ring-fence resources for regional multidisciplinary units, enforce interoperability and reference datasets, and align procurement with European requirements for auditability and post-deployment monitoring. AI can help reshape Italian healthcare, but success ultimately depends on integrated data, trained teams, and robust governance.
ER  -