Health Systems Building Data Infrastructure to Enable Personalized AI Care
Health systems are investing in stronger digital infrastructure and governance frameworks to support AI for Healthcare applications, according to Alexandra Wright, director of research at HIMSS' Office of Scientific Research.
The focus centers on interoperability-the ability of different systems to exchange and use data-as a prerequisite for deploying AI effectively. Without it, health systems cannot build the unified data analysis capabilities that personalized patient experiences require.
Wright said these foundational improvements in data governance allow organizations to move beyond isolated pilot projects toward institution-wide AI deployment. Better data infrastructure reduces the fragmentation that currently limits how hospitals and health networks use patient information.
The shift reflects a practical reality: AI tools perform only as well as the data feeding them. Health systems addressing data quality and accessibility early gain faster time-to-value when they eventually implement clinical decision support, patient engagement tools, or administrative automation.
Compliance and legal considerations remain central to these infrastructure upgrades. Governance frameworks help organizations manage regulatory requirements around data privacy and security while maintaining the data access necessary for AI systems to function.
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