{"id":7715027,"date":"2026-02-19T00:58:00","date_gmt":"2026-02-19T00:58:00","guid":{"rendered":"https:\/\/orionhealth.com\/?p=7715027"},"modified":"2026-02-26T19:46:10","modified_gmt":"2026-02-26T19:46:10","slug":"himss26-ai-healthcare-data-readiness-in-the-us","status":"publish","type":"post","link":"https:\/\/orionhealth.com\/global\/blog\/himss26-ai-healthcare-data-readiness-in-the-us\/","title":{"rendered":"HIMSS26: Connecting AI Ambition to the Data Foundations That Make It Work\u00a0\u00a0\u00a0"},"content":{"rendered":"\n

HIMSS is a bellwether for where healthcare technology is headed. In 2026, one signal is unmistakable: AI has moved from possibility to expectation. Interoperability alone is no longer a strategy. The real constraint is no longer access to data or availability of technology, but whether organizations are truly ready to operate with their data at scale. <\/p>\n\n\n\n

Bold claims, rapid innovation, and competing visions of AI transformation will be prevalent. What matters most beneath the noise is a quieter, more practical question we hear leaders already asking: what does it actually take to make these technologies work reliably, responsibly, and across real healthcare environments?<\/em> <\/p>\n\n\n\n

HIMSS26<\/a> is an opportunity to connect themes that are often discussed separately but are deeply interdependent in practice. AI adoption, data quality, governance, and interoperability are not always discussed as parallel initiatives. Progress in one without the others often leads to stalled pilots and limited adoption. <\/p>\n\n\n\n

From Interoperability to Enterprise Data Readiness<\/strong> <\/h2>\n\n\n\n

We’re hearing consistently that interoperability has been treated as a milestone to achieve rather than a foundation to build on. Yet as digital transformation efforts mature, it\u2019s increasingly clear that data exchange alone does not create usable intelligence. <\/p>\n\n\n\n

To support care transformation, population health, and AI-enabled decision-making, data must be unified, governed, and operationally accessible across systems and settings. This challenge is especially visible when organizations move beyond the boundaries of a single platform and attempt to make data work across care teams, partners, and programs. <\/p>\n\n\n\n

In\u00a0discussions with health systems and organizations managing\u00a0risk\u00a0we see a\u00a0clear trend emerging: fragmented data is a major roadblock.\u00a0Fragmented data\u00a0isn\u2019t\u00a0just a technical issue. It directly limits care coordination,\u00a0complicates\u00a0patient identification, and slows action across teams responsible for managing risk and outcomes.\u00a0At Orion Health, platforms like\u00a0Amadeus AI<\/a>\u00a0are designed to unify fragmented data into governed, longitudinal foundations that support analytics and AI use without\u00a0sacrificing\u00a0trust or transparency.\u00a0Analytics and AI tools, no matter how advanced, struggle to deliver value when the underlying data lacks consistency, context, or trust.\u00a0<\/p>\n\n\n\n

AI Momentum Meets Operational Reality<\/strong> <\/h2>\n\n\n\n

AI will dominate the HIMSS26 agenda, but the most meaningful conversations will not be about models or features. We’ll be looking for more concrete conversations about data readiness for AI. <\/p>\n\n\n\n

Health care leaders are increasingly focused on practical concerns: <\/p>\n\n\n\n