The Digital Transformation in Health: How AI Can Improve the Performance of Health Systems

• Main Authors: Periáñez, África, del Río, Ana Fernández, Nazarov, Ivan, Jané, Enric, Hassan, Moiz, Rastogi, Aditya, Tang, Dexian
• Format: Journal Article
• Language: English
• Published: 24-09-2024
• Subjects: Computer Science - Artificial Intelligence; Computer Science - Computers and Society; Computer Science - Human-Computer Interaction; Computer Science - Learning
• DOI: 10.48550/arxiv.2409.16098

Mobile health has the potential to revolutionize health care delivery and
patient engagement. In this work, we discuss how integrating Artificial
Intelligence into digital health applications-focused on supply chain, patient
management, and capacity building, among other use cases-can improve the health
system and public health performance. We present an Artificial Intelligence and
Reinforcement Learning platform that allows the delivery of adaptive
interventions whose impact can be optimized through experimentation and
real-time monitoring. The system can integrate multiple data sources and
digital health applications. The flexibility of this platform to connect to
various mobile health applications and digital devices and send personalized
recommendations based on past data and predictions can significantly improve
the impact of digital tools on health system outcomes. The potential for
resource-poor settings, where the impact of this approach on health outcomes
could be more decisive, is discussed specifically. This framework is, however,
similarly applicable to improving efficiency in health systems where scarcity
is not an issue.