In the last decade, the process of digital transformation has affected all economic activities and has offered new opportunities in health care requiring the adoption of new approaches and ICT tools to redesign processes and policies for the sector, allowing the diffusion of e-health, that is, health practices supported by technological tools. Digital technologies, such as electronic health records, telemedicine, and artificial intelligence, are the technological pillars on which a new health model can be structured over the next few years. The objective of this article is to analyze the impact of digital technologies in e-health through a system dynamic (SD) approach applied to intensive care units to determine how these technologies interact and which outputs they return within complex systems. The findings demonstrate how SD can be used to simulate the effects of e-health technologies' adoption as a policy-making tool, overcoming the main barriers to the development of sustainable health care. The implications and limitations of the study are also provided.
System Dynamics for E-Health: An Experimental Analysis of Digital Transformation Scenarios in Health Care
Pasquale Del Vecchio;Mele Gioconda
2022-01-01
Abstract
In the last decade, the process of digital transformation has affected all economic activities and has offered new opportunities in health care requiring the adoption of new approaches and ICT tools to redesign processes and policies for the sector, allowing the diffusion of e-health, that is, health practices supported by technological tools. Digital technologies, such as electronic health records, telemedicine, and artificial intelligence, are the technological pillars on which a new health model can be structured over the next few years. The objective of this article is to analyze the impact of digital technologies in e-health through a system dynamic (SD) approach applied to intensive care units to determine how these technologies interact and which outputs they return within complex systems. The findings demonstrate how SD can be used to simulate the effects of e-health technologies' adoption as a policy-making tool, overcoming the main barriers to the development of sustainable health care. The implications and limitations of the study are also provided.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
