HIT Consultant August 28, 2025
Artificial intelligence (AI) continues to hold the spotlight in healthcare transformation, promising everything from predictive care to streamlined administrative processes. Visionary use cases include anticipating patient deterioration, optimizing care coordination, accelerating prior authorizations, and unlocking insights from clinical notes that would otherwise remain buried.
But despite the promise, adoption remains uneven. Many organizations have piloted AI initiatives only to struggle with unreliable outputs, limited scalability, and inconsistent results. The root cause is not the sophistication of the algorithms. It is the condition of the data feeding them.
As healthcare leaders push forward with AI-driven strategies, there is a growing consensus that success begins not with modeling, but with data infrastructure. In particular, organizations need a clean, integrated, and intelligence-ready foundation...
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