This project analyses the impact of digitalisation on public administration. This process had been required for some time, but with the Covid-19 pandemic, it has finally started and, today, it is accompanied by the rapid evolution of Artificial Intelligence. Both phenomena base their work and progress on data as the main source of information. The health sector is the area within which this change can be analysed and what are the major benefits of the use of Big-Data and the main critical issues both national and regional level. Finally, it will be highlighted how digitialisation and artificial intelligence tools could be considered as potential for implementing the principle of good performance and simplification of administrative activities, offering, in this way, a better health service to citizens

L'impatto della rivoluzione digitale sulla Pubblica amministrazione: potenzialità e rischi della gestione dei Big - Data nel settore sanitario

GIANNANDREA, Michela
2025

Abstract

This project analyses the impact of digitalisation on public administration. This process had been required for some time, but with the Covid-19 pandemic, it has finally started and, today, it is accompanied by the rapid evolution of Artificial Intelligence. Both phenomena base their work and progress on data as the main source of information. The health sector is the area within which this change can be analysed and what are the major benefits of the use of Big-Data and the main critical issues both national and regional level. Finally, it will be highlighted how digitialisation and artificial intelligence tools could be considered as potential for implementing the principle of good performance and simplification of administrative activities, offering, in this way, a better health service to citizens
15-apr-2025
Italiano
INTERLANDI, Margherita
TOMASSONI, Rosella
Università degli studi di Cassino
Università degli studi di Cassino e del Lazio Meridionale
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14242/218745
Il codice NBN di questa tesi è URN:NBN:IT:UNICAS-218745